What is Talos: a quick description of Talos
Quickstart: the fastest way to get a Talos cluster up and running
Getting Started: a long-form, guided tour of getting a full Talos cluster deployed

Open Source

Community

GitHub: repo
Slack: Join our slack channel
Support: Questions, bugs, feature requests GitHub Discussions
Forum: community
Twitter: @SideroLabs
Email: info@SideroLabs.com

If you’re interested in this project and would like to help in engineering efforts, or have general usage questions, we are happy to have you! We hold a weekly meeting that all audiences are welcome to attend.

We would appreciate your feedback so that we can make Talos even better! To do so, you can take our survey.

Office Hours

When: Second Monday of every month at 16:30 UTC.
Where: Google Meet.

You can subscribe to this meeting by joining the community forum above.

Note: You can convert the meeting hours to your local time.

Enterprise

If you are using Talos in a production setting, and need consulting services to get started or to integrate Talos into your existing environment, we can help. Sidero Labs, Inc. offers support contracts with SLA (Service Level Agreement)-bound terms for mission-critical environments.

Learn More

1 - Introduction

1.1 - What is Talos?

A quick introduction in to what Talos is and why it should be used.

Talos is a container optimized Linux distro; a reimagining of Linux for distributed systems such as Kubernetes. Designed to be as minimal as possible while still maintaining practicality. For these reasons, Talos has a number of features unique to it:

it is immutable
it is atomic
it is ephemeral
it is minimal
it is secure by default
it is managed via a single declarative configuration file and gRPC API

Talos can be deployed on container, cloud, virtualized, and bare metal platforms.

Why Talos

In having less, Talos offers more. Security. Efficiency. Resiliency. Consistency.

All of these areas are improved simply by having less.

1.2 - Quickstart

A short guide on setting up a simple Talos Linux cluster locally with Docker.

Local Docker Cluster

The easiest way to try Talos is by using the CLI (talosctl) to create a cluster on a machine with docker installed.

Prerequisites

`talosctl`

Download talosctl (macOS or Linux):

brew install siderolabs/tap/talosctl

`kubectl`

Download kubectl via one of methods outlined in the documentation.

Create the Cluster

Now run the following:

talosctl cluster create

Note

If you are using Docker Desktop on a macOS computer you will need to enable the default Docker socket in your settings.

You can explore using Talos API commands:

talosctl dashboard --nodes 10.5.0.2

Verify that you can reach Kubernetes:

kubectl get nodes -o wide
NAME                     STATUS   ROLES    AGE    VERSION   INTERNAL-IP   EXTERNAL-IP   OS-IMAGE         KERNEL-VERSION   CONTAINER-RUNTIME
talos-default-controlplane-1   Ready    master   115s   v1.27.4   10.5.0.2      <none>        Talos (v1.4.8)   <host kernel>    containerd://1.5.5
talos-default-worker-1   Ready    <none>   115s   v1.27.4   10.5.0.3      <none>        Talos (v1.4.8)   <host kernel>    containerd://1.5.5

Destroy the Cluster

When you are all done, remove the cluster:

talosctl cluster destroy

1.3 - Getting Started

A guide to setting up a Talos Linux cluster on multiple machines.

This document will walk you through installing a full Talos Cluster. If this is your first use of Talos Linux, we recommend the Quickstart first, to quickly create a local virtual cluster on your workstation.

Regardless of where you run Talos, in general you need to:

acquire the installation image
decide on the endpoint for Kubernetes
- optionally create a load balancer
configure Talos
configure talosctl
bootstrap Kubernetes

Prerequisites

`talosctl`

talosctl is a CLI tool which interfaces with the Talos API in an easy manner.

Install talosctl before continuing:

curl -sL https://talos.dev/install | sh

Acquire the installation image

The most general way to install Talos is to use the ISO image (note there are easier methods for some platforms, such as pre-built AMIs for AWS - check the specific Installation Guides.)

The latest ISO image can be found on the Github Releases page:

When booted from the ISO, Talos will run in RAM, and will not install itself until it is provided a configuration. Thus, it is safe to boot the ISO onto any machine.

Alternative Booting

For network booting and self-built media, you can use the published kernel and initramfs images:

X86: vmlinuz-amd64 initramfs-amd64.xz
ARM64: vmlinuz-arm64 initramfs-arm64.xz

Note that to use alternate booting, there are a number of required kernel parameters. Please see the kernel docs for more information.

Decide the Kubernetes Endpoint

In order to configure Kubernetes, Talos needs to know what the endpoint (DNS name or IP address) of the Kubernetes API Server will be.

The endpoint should be the fully-qualified HTTP(S) URL for the Kubernetes API Server, which (by default) runs on port 6443 using HTTPS.

Thus, the format of the endpoint may be something like:

https://192.168.0.10:6443
https://kube.mycluster.mydomain.com:6443
https://[2001:db8:1234::80]:6443

The Kubernetes API Server endpoint, in order to be highly available, should be configured in a way that functions off all available control plane nodes. There are three common ways to do this:

Dedicated Load-balancer

If you are using a cloud provider or have your own load-balancer (such as HAProxy, nginx reverse proxy, or an F5 load-balancer), using a dedicated load balancer is a natural choice. Create an appropriate frontend matching the endpoint, and point the backends at the addresses of each of the Talos control plane nodes. (Note that given we have not yet created the control plane nodes, the IP addresses of the backends may not be known yet. We can bind the backends to the frontend at a later point.)

Layer 2 Shared IP

Talos has integrated support for serving Kubernetes from a shared/virtual IP address. This method relies on Layer 2 connectivity between control plane Talos nodes.

In this case, we choose an unused IP address on the same subnet as the Talos control plane nodes. For instance, if your control plane node IPs are:

192.168.0.10
192.168.0.11
192.168.0.12

you could choose the ip 192.168.0.15 as your shared IP address. (Make sure that 192.168.0.15 is not used by any other machine and that your DHCP server will not serve it to any other machine.)

Once chosen, form the full HTTPS URL from this IP:

https://192.168.0.15:6443

If you create a DNS record for this IP, note you will need to use the IP address itself, not the DNS name, to configure the shared IP (machine.network.interfaces[].vip.ip) in the Talos configuration.

For more information about using a shared IP, see the related Guide

DNS records

You can use DNS records to provide a measure of redundancy. In this case, you would add multiple A or AAAA records (one for each control plane node) to a DNS name.

For instance, you could add:

kube.cluster1.mydomain.com  IN  A  192.168.0.10
kube.cluster1.mydomain.com  IN  A  192.168.0.11
kube.cluster1.mydomain.com  IN  A  192.168.0.12

Then, your endpoint would be:

https://kube.cluster1.mydomain.com:6443

Decide how to access the Talos API

Many administrative tasks are performed by calling the Talos API on Talos Linux control plane nodes.

We recommend directly accessing the control plane nodes from the talosctl client, if possible (i.e. set your endpoints to the IP addresses of the control plane nodes). This requires your control plane nodes to be reachable from the client IP.

If the control plane nodes are not directly reachable from the workstation where you run talosctl, then configure a load balancer for TCP port 50000 to be forwarded to the control plane nodes. Do not use Talos Linux’s built in VIP support for accessing the Talos API, as it will not function in the event of an etcd failure, and you will not be able to access the Talos API to fix things.

If you create a load balancer to forward the Talos API calls, make a note of the IP or hostname so that you can configure your talosctl tool’s endpoints below.

Configure Talos

When Talos boots without a configuration, such as when using the Talos ISO, it enters a limited maintenance mode and waits for a configuration to be provided.

In other installation methods, a configuration can be passed in on boot. For example, Talos can be booted with the talos.config kernel commandline argument set to an HTTP(s) URL from which it should receive its configuration. Where a PXE server is available, this is much more efficient than manually configuring each node. If you do use this method, note that Talos requires a number of other kernel commandline parameters. See required kernel parameters. If creating EC2 kubernetes clusters, the configuration file can be passed in as --user-data to the aws ec2 run-instances command.

In any case, we need to generate the configuration which is to be provided. We start with generating a secrets bundle which should be saved in a secure location and used to generate machine or client configuration at any time:

talosctl gen secrets -o secrets.yaml

Now, we can generate the machine configuration for each node:

talosctl gen config --with-secrets secrets.yaml <cluster-name> <cluster-endpoint>

Here, cluster-name is an arbitrary name for the cluster, used in your local client configuration as a label. It should be unique in the configuration on your local workstation.

The cluster-endpoint is the Kubernetes Endpoint you selected from above. This is the Kubernetes API URL, and it should be a complete URL, with https:// and port. (The default port is 6443, but you may have configured your load balancer to forward a different port.) For example:

$ talosctl gen config --with-secrets secrets.yaml my-cluster https://192.168.64.15:6443
generating PKI and tokens
created /Users/taloswork/controlplane.yaml
created /Users/taloswork/worker.yaml
created /Users/taloswork/talosconfig

When you run this command, a number of files are created in your current directory:

controlplane.yaml
worker.yaml
talosconfig

The .yaml files are Machine Configs. They provide Talos Linux servers their complete configuration, describing everything from what disk Talos should be installed on, to network settings. The controlplane.yaml file describes how Talos should form a Kubernetes cluster.

The talosconfig file (which is also YAML) is your local client configuration file.

Controlplane and Worker

The two types of Machine Configs correspond to the two roles of Talos nodes, control plane (which run both the Talos and Kubernetes control planes) and worker nodes (which run the workloads).

The main difference between Controlplane Machine Config files and Worker Machine Config files is that the former contains information about how to form the Kubernetes cluster.

Modifying the Machine configs

The generated Machine Configs have defaults that work for many cases. They use DHCP for interface configuration, and install to /dev/sda. If the defaults work for your installation, you may use them as is.

Sometimes, you will need to modify the generated files so they work with your systems. A common example is needing to change the default installation disk. If you try to to apply the machine config to a node, and get an error like the below, you need to specify a different installation disk:

$ talosctl apply-config --insecure -n 192.168.64.8 --file controlplane.yaml
error applying new configuration: rpc error: code = InvalidArgument desc = configuration validation failed: 1 error occurred:
    * specified install disk does not exist: "/dev/sda"

You can verify which disks your nodes have by using the talosctl disks --insecure command.

Insecure mode is needed at this point as the PKI infrastructure has not yet been set up.

For example:

$ talosctl -n 192.168.64.8 disks --insecure
DEV        MODEL   SERIAL   TYPE   UUID   WWID   MODALIAS                    NAME   SIZE    BUS_PATH
/dev/vda   -       -        HDD    -      -      virtio:d00000002v00001AF4   -      69 GB   /pci0000:00/0000:00:06.0/virtio2/

In this case, you would modiy the controlplane.yaml and worker.yaml and edit the line:

install:
  disk: /dev/sda # The disk used for installations.

to reflect vda instead of sda.

Customizing Machine Configuration

The generated machine configuration provides sane defaults for most cases, but machine configuration can be modified to fit specific needs.

Some machine configuration options are available as flags for the talosctl gen config command, for example setting a specific Kubernetes version:

talosctl gen config --with-secrets secrets.yaml --kubernetes-version 1.25.4 my-cluster https://192.168.64.15:6443

Other modifications are done with machine configuration patches. Machine configuration patches can be applied with talosctl gen config command:

talosctl gen config --with-secrets secrets.yaml --config-patch-control-plane @cni.patch my-cluster https://192.168.64.15:6443

Note: @cni.patch means that the patch is read from a file named cni.patch.

Machine Configs as Templates

Individual machines may need different settings: for instance, each may have a different static IP address.

When different files are needed for machines of the same type, there are two supported flows:

Use the talosctl gen config command to generate a template, and then patch the template for each machine with talosctl machineconfig patch.
Generate each machine configuration file separately with talosctl gen config while applying patches.

For example, given a machine configuration patch which sets the static machine hostname:

# worker1.patch
machine:
  network:
    hostname: worker1

Either of the following commands will generate a worker machine configuration file with the hostname set to worker1:

$ talosctl gen config --with-secrets secrets.yaml my-cluster https://192.168.64.15:6443
created /Users/taloswork/controlplane.yaml
created /Users/taloswork/worker.yaml
created /Users/taloswork/talosconfig
$ talosctl machineconfig patch worker.yaml --patch @worker1.patch --output worker1.yaml

talosctl gen config --with-secrets secrets.yaml --config-patch-worker @worker1.patch --output-types worker -o worker1.yaml my-cluster https://192.168.64.15:6443

Apply Configuration

To apply the Machine Configs, you need to know the machines’ IP addresses.

Talos will print out the IP addresses of the machines on the console during the boot process:

[4.605369] [talos] task loadConfig (1/1): this machine is reachable at:
[4.607358] [talos] task loadConfig (1/1):   192.168.0.2
[4.608766] [talos] task loadConfig (1/1): server certificate fingerprint:
[4.611106] [talos] task loadConfig (1/1):   xA9a1t2dMxB0NJ0qH1pDzilWbA3+DK/DjVbFaJBYheE=
[4.613822] [talos] task loadConfig (1/1):
[4.614985] [talos] task loadConfig (1/1): upload configuration using talosctl:
[4.616978] [talos] task loadConfig (1/1):   talosctl apply-config --insecure --nodes 192.168.0.2 --file <config.yaml>
[4.620168] [talos] task loadConfig (1/1): or apply configuration using talosctl interactive installer:
[4.623046] [talos] task loadConfig (1/1):   talosctl apply-config --insecure --nodes 192.168.0.2 --mode=interactive
[4.626365] [talos] task loadConfig (1/1): optionally with node fingerprint check:
[4.628692] [talos] task loadConfig (1/1):   talosctl apply-config --insecure --nodes 192.168.0.2 --cert-fingerprint 'xA9a1t2dMxB0NJ0qH1pDzilWbA3+DK/DjVbFaJBYheE=' --file <config.yaml>

If you do not have console access, the IP address may also be discoverable from your DHCP server.

Once you have the IP address, you can then apply the correct configuration.

  talosctl apply-config --insecure \
    --nodes 192.168.0.2 \
    --file controlplane.yaml

The insecure flag is necessary because the PKI infrastructure has not yet been made available to the node. Note: the connection will be encrypted, it is just unauthenticated. If you have console access you can extract the server certificate fingerprint and use it for an additional layer of validation:

  talosctl apply-config --insecure \
    --nodes 192.168.0.2 \
    --cert-fingerprint xA9a1t2dMxB0NJ0qH1pDzilWbA3+DK/DjVbFaJBYheE= \
    --file cp0.yaml

Using the fingerprint allows you to be sure you are sending the configuration to the correct machine, but it is completely optional. After the configuration is applied to a node, it will reboot. Repeat this process for each of the nodes in your cluster.

Understand talosctl, endpoints and nodes

It is important to understand the concept of endpoints and nodes. In short: endpoints are the nodes that talosctl sends commands to, but nodes are the nodes that the command operates on. The endpoint will forward the command to the nodes, if needed.

Endpoints

Endpoints are the IP addresses to which the talosctl client directly talks. These should be the set of control plane nodes, either directly or through a load balancer.

Each endpoint will automatically proxy requests destined to another node in the cluster. This means that you only need access to the control plane nodes in order to access the rest of the network.

talosctl will automatically load balance requests and fail over between all of your endpoints.

You can pass in --endpoints <IP Address1>,<IP Address2> as a comma separated list of IP/DNS addresses to the current talosctl command. You can also set the endpoints in your talosconfig, by calling talosctl config endpoint <IP Address1> <IP Address2>. Note: these are space separated, not comma separated.

As an example, if the IP addresses of our control plane nodes are:

192.168.0.2
192.168.0.3
192.168.0.4

We would set those in the talosconfig with:

  talosctl --talosconfig=./talosconfig \
    config endpoint 192.168.0.2 192.168.0.3 192.168.0.4

Nodes

The node is the target you wish to perform the API call on.

When specifying nodes, their IPs and/or hostnames are as seen by the endpoint servers, not as from the client. This is because all connections are proxied through the endpoints.

You may provide -n or --nodes to any talosctl command to supply the node or (comma-separated) nodes on which you wish to perform the operation.

For example, to see the containers running on node 192.168.0.200:

talosctl -n 192.168.0.200 containers

To see the etcd logs on both nodes 192.168.0.10 and 192.168.0.11:

talosctl -n 192.168.0.10,192.168.0.11 logs etcd

It is possible to set a default set of nodes in the talosconfig file, but our recommendation is to explicitly pass in the node or nodes to be operated on with each talosctl command. For a more in-depth discussion of Endpoints and Nodes, please see talosctl.

Default configuration file

You can reference which configuration file to use directly with the --talosconfig parameter:

  talosctl --talosconfig=./talosconfig \
    --nodes 192.168.0.2 version

However, talosctl comes with tooling to help you integrate and merge this configuration into the default talosctl configuration file. This is done with the merge option.

  talosctl config merge ./talosconfig

This will merge your new talosconfig into the default configuration file ($XDG_CONFIG_HOME/talos/config.yaml), creating it if necessary. Like Kubernetes, the talosconfig configuration files has multiple “contexts” which correspond to multiple clusters. The <cluster-name> you chose above will be used as the context name.

Kubernetes Bootstrap

Bootstrapping your Kubernetes cluster with Talos is as simple as:

  talosctl bootstrap --nodes 192.168.0.2

The bootstrap operation should only be called ONCE and only on a SINGLE control plane node!

The IP can be any of your control planes (or the loadbalancer, if used for the Talos API endpoint).

At this point, Talos will form an etcd cluster, generate all of the core Kubernetes assets, and start the Kubernetes control plane components.

After a few moments, you will be able to download your Kubernetes client configuration and get started:

  talosctl kubeconfig

Running this command will add (merge) you new cluster into your local Kubernetes configuration.

If you would prefer the configuration to not be merged into your default Kubernetes configuration file, pass in a filename:

  talosctl kubeconfig alternative-kubeconfig

You should now be able to connect to Kubernetes and see your nodes:

  kubectl get nodes

And use talosctl to explore your cluster:

  talosctl -n <NODEIP> dashboard

For a list of all the commands and operations that talosctl provides, see the CLI reference.

1.4 - System Requirements

Hardware requirements for running Talos Linux.

Minimum Requirements

Role	Memory	Cores	System Disk
Control Plane	2 GiB	2	10 GiB
Worker	1 GiB	1	10 GiB

Role	Memory	Cores	System Disk
Control Plane	4 GiB	4	100 GiB
Worker	2 GiB	2	100 GiB

Storage

Talos Linux itself only requires less than 100 MB of disk space, but the EPHEMERAL partition is used to store pulled images, container work directories, and so on. Thus a minimum is 10 GiB of disk space is required. 100 GiB is desired. Note, however, that because Talos Linux assumes complete control of the disk it is installed on, so that it can control the partition table for image based upgrades, you cannot partition the rest of the disk for use by workloads.

Thus it is recommended to install Talos Linux on a small, dedicated disk - using a Terabyte sized SSD for the Talos install disk would be wasteful. Sidero Labs recommends having separate disks (apart from the Talos install disk) to be used for storage.

1.5 - What's New in Talos 1.4

List of new and shiny features in Talos Linux.

See also upgrade notes for important changes.

Interactive Dashboard

Talos now starts a text-based UI dashboard on virtual console /dev/tty2 and switches to it by default upon boot. Kernel logs remain available on /dev/tty1.

To switch between virtual TTYs, use the Alt+F1 and Alt+F2 keys.

You can disable this new feature by setting the kernel parameter talos.dashboard.disabled=1. The dashboard is disabled by default on SBCs to limit resource usage.

The output to the serial console is not affected by this change.

Interactive Dashboard on QEMU VM

Boot Process

Talos now ships with the latest Linux LTS kernel 6.1.x.

Talos ISO GRUB menu now an includes an option to wipe completely a Talos installed on a system disk.

Talos GRUB menu for a system disk boot now includes an option to wipe STATE and EPHEMERAL partition returning the machine to the maintenance mode.

Kernel Modules

Talos now automatically loads kernel drivers built as modules. If any system extensions or the Talos base kernel build provides kernel modules and if they matches the system hardware (via PCI IDs), they will be loaded automatically. Modules can still be loaded explicitly by defining it in machine configuration.

At the moment only a small subset of device drivers is built as modules, but we plan to expand this list in the future.

Kernel Modules Tree

Talos now supports re-building the kernel modules dependency tree information on upgrades. This allows modules of same name to co-exist as in-tree and external modules. System Extensions can provide modules installed into extras directory and when loading it’ll take precedence over the in-tree module.

Kernel Argument `talos.environment`

Talos now supports passing environment variables via talos.environment kernel argument.

Example:

talos.environment=http_proxy=http://proxy.example.com:8080 talos.environment=https_proxy=http://proxy.example.com:8080

Kernel Argument `talos.experimental.wipe`

Talos now supports specifying a list of system partitions to be wiped in the talos.experimental.wipe kernel argument.

`talos.experimental.wipe=system:EPHEMERAL,STATE`

Networking

Bond Device Selectors

Bond links can now be described using device selectors instead of explicit device names:

machine:
  network:
    interfaces:
      - interface: bond0
        bond:
          deviceSelectors:
            - hardwareAddr: '00:50:56:*'
            - hardwareAddr: '00:50:57:9c:2c:2d'

VLAN Machine Configuration

Strategic merge config patches now correctly support merging .vlans sections of the network interface.

`talosctl` CLI

`talosctl etcd`

Talos adds new APIs to make it easier to perform etcd maintenance operations.

These APIs are available via new talosctl etcd sub-commands:

talosctl etcd alarm list|disarm
talosctl etcd defrag
talosctl etcd status

`talosctl containers`

talosctl logs -k and talosctl containers -k now support and output container display names with their ids. This allows to distinguish between containers with the same name.

`talosctl dashboard`

A dashboard now shows same information as interactive console (see above), but in a remote way over the Talos API:

talosctl dashboard CLI

Previous monitoring screen can be accessed by using <F2> key.

`talosctl logs`

An issue was fixed which might lead to the log output corruption in the CLI under certain conditions.

`talosctl netstat`

Talos API was extended to support retrieving a list of network connections (sockets) from the node and pods. talosctl netstat command was added to retrieve the list of network connections.

`talosctl reset`

Talos now supports resetting user disks through the Reset API, the list of disks to wipe can be passed using the --user-disks-to-wipe flag to the talosctl reset command.

Miscellaneous

Registry Mirror Catch-All Option

Talos now supports a catch-all option for registry mirrors:

machine:
    registries:
        mirrors:
            docker.io:
                - https://registry-1.docker.io/
            "*":
                - https://my-registry.example.com/

Talos API `os:operator` role

Talos now supports a new os:operator role for the Talos API. This role allows everything os:reader role allows plus access to maintenance APIs: rebooting, shutting down a node, accessing packet capture, etcd alarm APIs, etcd backup, etc.

VMware Platform

Talos now supports loading network configuration on VMWare platform from the metadata key. See CAPV IPAM Support and Talos issue 6708 for details.

Component Updates

Linux: 6.1.24
containerd: v1.6.20
runc: v1.1.5
Kubernetes: v1.27.1
etcd: v3.5.8
CoreDNS: v1.10.1
Flannel: v0.21.4

Talos is built with Go 1.20.3.

1.6 - Support Matrix

Table of supported Talos Linux versions and respective platforms.

Talos Version	1.4	1.3
Release Date	2023-04-18	2022-12-15 (1.3.0)
End of Community Support	1.5.0 release (2023-08-15)	1.4.0 release (2023-04-18)
Enterprise Support	offered by Sidero Labs Inc.	offered by Sidero Labs Inc.
Kubernetes	1.27, 1.26, 1.25	1.26, 1.25, 1.24
Architecture	amd64, arm64	amd64, arm64
Platforms
- cloud	AWS, GCP, Azure, Digital Ocean, Exoscale, Hetzner, OpenStack, Oracle Cloud, Scaleway, Vultr, Upcloud	AWS, GCP, Azure, Digital Ocean, Exoscale, Hetzner, OpenStack, Oracle Cloud, Scaleway, Vultr, Upcloud
- bare metal	x86: BIOS, UEFI; arm64: UEFI; boot: ISO, PXE, disk image	x86: BIOS, UEFI; arm64: UEFI; boot: ISO, PXE, disk image
- virtualized	VMware, Hyper-V, KVM, Proxmox, Xen	VMware, Hyper-V, KVM, Proxmox, Xen
- SBCs	Banana Pi M64, Jetson Nano, Libre Computer Board ALL-H3-CC, Nano Pi R4S, Pine64, Pine64 Rock64, Radxa ROCK Pi 4c, Raspberry Pi 4B, Raspberry Pi Compute Module 4	Banana Pi M64, Jetson Nano, Libre Computer Board ALL-H3-CC, Nano Pi R4S, Pine64, Pine64 Rock64, Radxa ROCK Pi 4c, Raspberry Pi 4B, Raspberry Pi Compute Module 4
- local	Docker, QEMU	Docker, QEMU
Cluster API
CAPI Bootstrap Provider Talos	>= 0.6.0	>= 0.5.6
CAPI Control Plane Provider Talos	>= 0.4.10	>= 0.4.10
Sidero	>= 0.6.0	>= 0.5.7

Platform Tiers

Tier 1: Automated tests, high-priority fixes.
Tier 2: Tested from time to time, medium-priority bugfixes.
Tier 3: Not tested by core Talos team, community tested.

Tier 1

Metal
AWS
GCP

Tier 2

Azure
Digital Ocean
OpenStack
VMWare

Tier 3

Exoscale
Hetzner
nocloud
Oracle Cloud
Scaleway
Vultr
Upcloud

2 - Talos Linux Guides

Documentation on how to manage Talos Linux

2.1 - Installation

How to install Talos Linux on various platforms

2.1.1 - Bare Metal Platforms

Installation of Talos Linux on various bare-metal platforms.

2.1.1.1 - Digital Rebar

In this guide we will create an Kubernetes cluster with 1 worker node, and 2 controlplane nodes using an existing digital rebar deployment.

Prerequisites

3 nodes (please see hardware requirements)
Loadbalancer
Digital Rebar Server
Talosctl access (see talosctl setup)

Creating a Cluster

In this guide we will create an Kubernetes cluster with 1 worker node, and 2 controlplane nodes. We assume an existing digital rebar deployment, and some familiarity with iPXE.

We leave it up to the user to decide if they would like to use static networking, or DHCP. The setup and configuration of DHCP will not be covered.

Create the Machine Configuration Files

Generating Base Configurations

Using the DNS name of the load balancer, generate the base configuration files for the Talos machines:

$ talosctl gen config talos-k8s-metal-tutorial https://<load balancer IP or DNS>:<port>
created controlplane.yaml
created worker.yaml
created talosconfig

The loadbalancer is used to distribute the load across multiple controlplane nodes. This isn’t covered in detail, because we assume some loadbalancing knowledge before hand. If you think this should be added to the docs, please create a issue.

At this point, you can modify the generated configs to your liking. Optionally, you can specify --config-patch with RFC6902 jsonpatch which will be applied during the config generation.

Validate the Configuration Files

$ talosctl validate --config controlplane.yaml --mode metal
controlplane.yaml is valid for metal mode
$ talosctl validate --config worker.yaml --mode metal
worker.yaml is valid for metal mode

Publishing the Machine Configuration Files

Digital Rebar has a built-in fileserver, which means we can use this feature to expose the talos configuration files. We will place controlplane.yaml, and worker.yaml into Digital Rebar file server by using the drpcli tools.

Copy the generated files from the step above into your Digital Rebar installation.

drpcli file upload <file>.yaml as <file>.yaml

Replacing <file> with controlplane or worker.

Download the boot files

Download a recent version of boot.tar.gz from github.

Upload to DRB:

$ drpcli isos upload boot.tar.gz as talos.tar.gz
{
  "Path": "talos.tar.gz",
  "Size": 96470072
}

We have some Digital Rebar example files in the Git repo you can use to provision Digital Rebar with drpcli.

To apply these configs you need to create them, and then apply them as follow:

$ drpcli bootenvs create talos
{
  "Available": true,
  "BootParams": "",
  "Bundle": "",
  "Description": "",
  "Documentation": "",
  "Endpoint": "",
  "Errors": [],
  "Initrds": [],
  "Kernel": "",
  "Meta": {},
  "Name": "talos",
  "OS": {
    "Codename": "",
    "Family": "",
    "IsoFile": "",
    "IsoSha256": "",
    "IsoUrl": "",
    "Name": "",
    "SupportedArchitectures": {},
    "Version": ""
  },
  "OnlyUnknown": false,
  "OptionalParams": [],
  "ReadOnly": false,
  "RequiredParams": [],
  "Templates": [],
  "Validated": true
}

drpcli bootenvs update talos - < bootenv.yaml

You need to do this for all files in the example directory. If you don’t have access to the drpcli tools you can also use the webinterface.

It’s important to have a corresponding SHA256 hash matching the boot.tar.gz

Bootenv BootParams

We’re using some of Digital Rebar built in templating to make sure the machine gets the correct role assigned.

talos.platform=metal talos.config={{ .ProvisionerURL }}/files/{{.Param \"talos/role\"}}.yaml"

This is why we also include a params.yaml in the example directory to make sure the role is set to one of the following:

controlplane
worker

The {{.Param \"talos/role\"}} then gets populated with one of the above roles.

Boot the Machines

In the UI of Digital Rebar you need to select the machines you want to provision. Once selected, you need to assign to following:

Profile
Workflow

This will provision the Stage and Bootenv with the talos values. Once this is done, you can boot the machine.

Bootstrap Etcd

To configure talosctl we will need the first control plane node’s IP:

Set the endpoints and nodes:

talosctl --talosconfig talosconfig config endpoint <control plane 1 IP>
talosctl --talosconfig talosconfig config node <control plane 1 IP>

Bootstrap etcd:

talosctl --talosconfig talosconfig bootstrap

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl --talosconfig talosconfig kubeconfig .

2.1.1.2 - Equinix Metal

Creating Talos clusters with Equinix Metal.

You can create a Talos Linux cluster on Equinix Metal in a variety of ways, such as through the EM web UI, the metal command line too, or through PXE booting. Talos Linux is a supported OS install option on Equinix Metal, so it’s an easy process.

Regardless of the method, the process is:

Create a DNS entry for your Kubernetes endpoint.
Generate the configurations using talosctl.
Provision your machines on Equinix Metal.
Push the configurations to your servers (if not done as part of the machine provisioning).
configure your Kubernetes endpoint to point to the newly created control plane nodes
bootstrap the cluster

Define the Kubernetes Endpoint

There are a variety of ways to create an HA endpoint for the Kubernetes cluster. Some of the ways are:

DNS
Load Balancer
BGP

Whatever way is chosen, it should result in an IP address/DNS name that routes traffic to all the control plane nodes. We do not know the control plane node IP addresses at this stage, but we should define the endpoint DNS entry so that we can use it in creating the cluster configuration. After the nodes are provisioned, we can use their addresses to create the endpoint A records, or bind them to the load balancer, etc.

Create the Machine Configuration Files

Generating Configurations

Using the DNS name of the loadbalancer defined above, generate the base configuration files for the Talos machines:

$ talosctl gen config talos-k8s-em-tutorial https://<load balancer IP or DNS>:<port>
created controlplane.yaml
created worker.yaml
created talosconfig

The port used above should be 6443, unless your load balancer maps a different port to port 6443 on the control plane nodes.

Validate the Configuration Files

talosctl validate --config controlplane.yaml --mode metal
talosctl validate --config worker.yaml --mode metal

Note: Validation of the install disk could potentially fail as validation is performed on your local machine and the specified disk may not exist.

Passing in the configuration as User Data

You can use the metadata service provide by Equinix Metal to pass in the machines configuration. It is required to add a shebang to the top of the configuration file.

The convention we use is #!talos.

Provision the machines in Equinix Metal

Using the Equinix Metal UI

Simply select the location and type of machines in the Equinix Metal web interface. Select Talos as the Operating System, then select the number of servers to create, and name them (in lowercase only.) Under optional settings, you can optionally paste in the contents of controlplane.yaml that was generated, above (ensuring you add a first line of #!talos).

You can repeat this process to create machines of different types for control plane and worker nodes (although you would pass in worker.yaml for the worker nodes, as user data).

If you did not pass in the machine configuration as User Data, you need to provide it to each machine, with the following command:

talosctl apply-config --insecure --nodes <Node IP> --file ./controlplane.yaml

Creating a Cluster via the Equinix Metal CLI

This guide assumes the user has a working API token,and the Equinix Metal CLI installed.

Because Talos Linux is a supported operating system, Talos Linux machines can be provisioned directly via the CLI, using the -O talos_v1 parameter (for Operating System).

Note: Ensure you have prepended #!talos to the controlplane.yaml file.

metal device create \
  --project-id $PROJECT_ID \
  --facility $FACILITY \
  --operating-system "talos_v1" \
  --plan $PLAN\
  --hostname $HOSTNAME\
  --userdata-file controlplane.yaml

e.g. metal device create -p <projectID> -f da11 -O talos_v1 -P c3.small.x86 -H steve.test.11 --userdata-file ./controlplane.yaml

Repeat this to create each control plane node desired: there should usually be 3 for a HA cluster.

Network Booting via iPXE

You may install Talos over the network using TFTP and iPXE. You would first need a working TFTP and iPXE server.

In general this requires a Talos kernel vmlinuz and initramfs. These assets can be downloaded from a given release.

PXE Boot Kernel Parameters

The following is a list of kernel parameters required by Talos:

talos.platform: set this to equinixMetal
init_on_alloc=1: required by KSPP
slab_nomerge: required by KSPP
pti=on: required by KSPP

Create the Control Plane Nodes

metal device create \
  --project-id $PROJECT_ID \
  --facility $FACILITY \
  --ipxe-script-url $PXE_SERVER \
  --operating-system "custom_ipxe" \
  --plan $PLAN\
  --hostname $HOSTNAME\
  --userdata-file controlplane.yaml

Note: Repeat this to create each control plane node desired: there should usually be 3 for a HA cluster.

Create the Worker Nodes

metal device create \
  --project-id $PROJECT_ID \
  --facility $FACILITY \
  --ipxe-script-url $PXE_SERVER \
  --operating-system "custom_ipxe" \
  --plan $PLAN\
  --hostname $HOSTNAME\
  --userdata-file worker.yaml

Update the Kubernetes endpoint

Now our control plane nodes have been created, and we know their IP addresses, we can associate them with the Kubernetes endpoint. Configure your load balancer to route traffic to these nodes, or add A records to your DNS entry for the endpoint, for each control plane node. e.g.

host endpoint.mydomain.com
endpoint.mydomain.com has address 145.40.90.201
endpoint.mydomain.com has address 147.75.109.71
endpoint.mydomain.com has address 145.40.90.177

Bootstrap Etcd

Set the endpoints and nodes for talosctl:

talosctl --talosconfig talosconfig config endpoint <control plane 1 IP>
talosctl --talosconfig talosconfig config node <control plane 1 IP>

Bootstrap etcd:

talosctl --talosconfig talosconfig bootstrap

This only needs to be issued to one control plane node.

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl --talosconfig talosconfig kubeconfig .

2.1.1.3 - ISO

Booting Talos on bare-metal with ISO.

Talos can be installed on bare-metal machine using an ISO image. ISO images for amd64 and arm64 architectures are available on the Talos releases page.

Talos doesn’t install itself to disk when booted from an ISO until the machine configuration is applied.

Please follow the getting started guide for the generic steps on how to install Talos.

Note: If there is already a Talos installation on the disk, the machine will boot into that installation when booting from a Talos ISO. The boot order should prefer disk over ISO, or the ISO should be removed after the installation to make Talos boot from disk.

See kernel parameters reference for the list of kernel parameters supported by Talos.

2.1.1.4 - Matchbox

In this guide we will create an HA Kubernetes cluster with 3 worker nodes using an existing load balancer and matchbox deployment.

Creating a Cluster

In this guide we will create an HA Kubernetes cluster with 3 worker nodes. We assume an existing load balancer, matchbox deployment, and some familiarity with iPXE.

We leave it up to the user to decide if they would like to use static networking, or DHCP. The setup and configuration of DHCP will not be covered.

Create the Machine Configuration Files

Generating Base Configurations

Using the DNS name of the load balancer, generate the base configuration files for the Talos machines:

$ talosctl gen config talos-k8s-metal-tutorial https://<load balancer IP or DNS>:<port>
created controlplane.yaml
created worker.yaml
created talosconfig

At this point, you can modify the generated configs to your liking. Optionally, you can specify --config-patch with RFC6902 jsonpatch which will be applied during the config generation.

Validate the Configuration Files

$ talosctl validate --config controlplane.yaml --mode metal
controlplane.yaml is valid for metal mode
$ talosctl validate --config worker.yaml --mode metal
worker.yaml is valid for metal mode

Publishing the Machine Configuration Files

In bare-metal setups it is up to the user to provide the configuration files over HTTP(S). A special kernel parameter (talos.config) must be used to inform Talos about where it should retrieve its configuration file. To keep things simple we will place controlplane.yaml, and worker.yaml into Matchbox’s assets directory. This directory is automatically served by Matchbox.

Create the Matchbox Configuration Files

The profiles we will create will reference vmlinuz, and initramfs.xz. Download these files from the release of your choice, and place them in /var/lib/matchbox/assets.

Profiles

Control Plane Nodes

{
  "id": "control-plane",
  "name": "control-plane",
  "boot": {
    "kernel": "/assets/vmlinuz",
    "initrd": ["/assets/initramfs.xz"],
    "args": [
      "initrd=initramfs.xz",
      "init_on_alloc=1",
      "slab_nomerge",
      "pti=on",
      "console=tty0",
      "console=ttyS0",
      "printk.devkmsg=on",
      "talos.platform=metal",
      "talos.config=http://matchbox.talos.dev/assets/controlplane.yaml"
    ]
  }
}

Note: Be sure to change http://matchbox.talos.dev to the endpoint of your matchbox server.

Worker Nodes

{
  "id": "default",
  "name": "default",
  "boot": {
    "kernel": "/assets/vmlinuz",
    "initrd": ["/assets/initramfs.xz"],
    "args": [
      "initrd=initramfs.xz",
      "init_on_alloc=1",
      "slab_nomerge",
      "pti=on",
      "console=tty0",
      "console=ttyS0",
      "printk.devkmsg=on",
      "talos.platform=metal",
      "talos.config=http://matchbox.talos.dev/assets/worker.yaml"
    ]
  }
}

Groups

Now, create the following groups, and ensure that the selectors are accurate for your specific setup.

{
  "id": "control-plane-1",
  "name": "control-plane-1",
  "profile": "control-plane",
  "selector": {
    ...
  }
}

{
  "id": "control-plane-2",
  "name": "control-plane-2",
  "profile": "control-plane",
  "selector": {
    ...
  }
}

{
  "id": "control-plane-3",
  "name": "control-plane-3",
  "profile": "control-plane",
  "selector": {
    ...
  }
}

{
  "id": "default",
  "name": "default",
  "profile": "default"
}

Boot the Machines

Now that we have our configuration files in place, boot all the machines. Talos will come up on each machine, grab its configuration file, and bootstrap itself.

Bootstrap Etcd

Set the endpoints and nodes:

talosctl --talosconfig talosconfig config endpoint <control plane 1 IP>
talosctl --talosconfig talosconfig config node <control plane 1 IP>

Bootstrap etcd:

talosctl --talosconfig talosconfig bootstrap

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl --talosconfig talosconfig kubeconfig .

2.1.1.5 - Network Configuration

In this guide we will describe how network can be configured on bare-metal platforms.

By default, Talos will run DHCP client on all interfaces which have a link, and that might be enough for most of the cases. If some advanced network configuration is required, it can be done via the machine configuration file.

But sometimes it is required to apply network configuration even before the machine configuration can be fetched from the network.

Kernel Command Line

Talos supports some kernel command line parameters to configure network before the machine configuration is fetched.

Note: Kernel command line parameters are not persisted after Talos installation, so proper network configuration should be done via the machine configuration.

Address, default gateway and DNS servers can be configured via ip= kernel command line parameter:

ip=172.20.0.2::172.20.0.1:255.255.255.0::eth0.100:::::

Bonding can be configured via bond= kernel command line parameter:

bond=bond0:eth0,eth1:balance-rr

VLANs can be configured via vlan= kernel command line parameter:

vlan=eth0.100:eth0

See kernel parameters reference for more details.

Platform Network Configuration

Some platforms (e.g. AWS, Google Cloud, etc.) have their own network configuration mechanisms, which can be used to perform the initial network configuration. There is no such mechanism for bare-metal platforms, so Talos provides a way to use platform network config on the metal platform to submit the initial network configuration.

The platform network configuration is a YAML document which contains resource specifications for various network resources. For the metal platform, the interactive dashboard can be used to edit the platform network configuration.

The current value of the platform network configuration can be retrieved using the MetaKeys resource (key 0xa):

talosctl get meta 0xa

The platform network configuration can be updated using the talosctl meta command for the running node:

talosctl meta write 0xa '{"externalIPs": ["1.2.3.4"]}'
talosctl meta delete 0xa

The initial platform network configuration for the metal platform can be also included into the generated Talos image:

docker run --rm -i ghcr.io/siderolabs/imager:v1.4.8 iso --arch amd64 --tar-to-stdout --meta 0xa='{...}' | tar xz
docker run --rm -i --privileged ghcr.io/siderolabs/imager:v1.4.8 image --platform metal --arch amd64 --tar-to-stdout --meta 0xa='{...}' | tar xz

The platform network configuration gets merged with other sources of network configuration, the details can be found in the network resources guide.

2.1.1.6 - PXE

Booting Talos over the network on bare-metal with PXE.

Talos can be installed on bare-metal using PXE service. There are two more detailed guides for PXE booting using Matchbox and Digital Rebar.

This guide describes generic steps for PXE booting Talos on bare-metal.

First, download the vmlinuz and initramfs assets from the Talos releases page. Set up the machines to PXE boot from the network (usually by setting the boot order in the BIOS). There might be options specific to the hardware being used, booting in BIOS or UEFI mode, using iPXE, etc.

Talos requires the following kernel parameters to be set on the initial boot:

talos.platform=metal
slab_nomerge
pti=on

When booted from the network without machine configuration, Talos will start in maintenance mode.

Please follow the getting started guide for the generic steps on how to install Talos.

See kernel parameters reference for the list of kernel parameters supported by Talos.

Note: If there is already a Talos installation on the disk, the machine will boot into that installation when booting from network. The boot order should prefer disk over network.

Talos can automatically fetch the machine configuration from the network on the initial boot using talos.config kernel parameter. A metadata service (HTTP service) can be implemented to deliver customized configuration to each node for example by using the MAC address of the node:

talos.config=https://metadata.service/talos/config?mac=${mac}

Note: The talos.config kernel parameter supports other substitution variables, see kernel parameters reference for the full list.

2.1.1.7 - Sidero Metal

Sidero Metal is a project created by the Talos team that has native support for Talos.

Sidero Metal is a project created by the Talos team that provides a bare metal installer for Cluster API, and that has native support for Talos Linux. It can be easily installed using clusterctl. The best way to get started with Sidero Metal is to visit the website.

2.1.2 - Virtualized Platforms

Installation of Talos Linux for virtualization platforms.

2.1.2.1 - Hyper-V

Creating a Talos Kubernetes cluster using Hyper-V.

Pre-requisities

Download the latest talos-amd64.iso ISO from github releases page
Create a New-TalosVM folder in any of your PS Module Path folders $env:PSModulePath -split ';' and save the New-TalosVM.psm1 there

Plan Overview

Here we will create a basic 3 node cluster with a single control-plane node and two worker nodes. The only difference between control plane and worker node is the amount of RAM and an additional storage VHD. This is personal preference and can be configured to your liking.

We are using a VMNamePrefix argument for a VM Name prefix and not the full hostname. This command will find any existing VM with that prefix and “+1” the highest suffix it finds. For example, if VMs talos-cp01 and talos-cp02 exist, this will create VMs starting from talos-cp03, depending on NumberOfVMs argument.

Setup a Control Plane Node

Use the following command to create a single control plane node:

New-TalosVM -VMNamePrefix talos-cp -CPUCount 2 -StartupMemory 4GB -SwitchName LAB -TalosISOPath C:\ISO\talos-amd64.iso -NumberOfVMs 1 -VMDestinationBasePath 'D:\Virtual Machines\Test VMs\Talos'

This will create talos-cp01 VM and power it on.

Setup Worker Nodes

Use the following command to create 2 worker nodes:

New-TalosVM -VMNamePrefix talos-worker -CPUCount 4 -StartupMemory 8GB -SwitchName LAB -TalosISOPath C:\ISO\talos-amd64.iso -NumberOfVMs 2 -VMDestinationBasePath 'D:\Virtual Machines\Test VMs\Talos' -StorageVHDSize 50GB

This will create two VMs: talos-worker01 and talos-wworker02 and attach an additional VHD of 50GB for storage (which in my case will be passed to Mayastor).

Pushing Config to the Nodes

Now that our VMs are ready, find their IP addresses from console of VM. With that information, push config to the control plane node with:

# set control plane IP variable
$CONTROL_PLANE_IP='10.10.10.x'

# Generate talos config
talosctl gen config talos-cluster https://$($CONTROL_PLANE_IP):6443 --output-dir .

# Apply config to control plane node
talosctl apply-config --insecure --nodes $CONTROL_PLANE_IP --file .\controlplane.yaml

Pushing Config to Worker Nodes

Similarly, for the workers:

talosctl apply-config --insecure --nodes 10.10.10.x --file .\worker.yaml

Apply the config to both nodes.

Bootstrap Cluster

Now that our nodes are ready, we are ready to bootstrap the Kubernetes cluster.

# Use following command to set node and endpoint permanantly in config so you dont have to type it everytime
talosctl config endpoint $CONTROL_PLANE_IP
talosctl config node $CONTROL_PLANE_IP

# Bootstrap cluster
talosctl bootstrap

# Generate kubeconfig
talosctl kubeconfig .

This will generate the kubeconfig file, you can use to connect to the cluster.

2.1.2.2 - KVM

Talos is known to work on KVM.

We don’t yet have a documented guide specific to KVM; however, you can have a look at our Vagrant & Libvirt guide which uses KVM for virtualization.

If you run into any issues, our community can probably help!

2.1.2.3 - Proxmox

Creating Talos Kubernetes cluster using Proxmox.

In this guide we will create a Kubernetes cluster using Proxmox.

Video Walkthrough

To see a live demo of this writeup, visit Youtube here:

Installation

How to Get Proxmox

It is assumed that you have already installed Proxmox onto the server you wish to create Talos VMs on. Visit the Proxmox downloads page if necessary.

Install talosctl

You can download talosctl via

curl -sL https://talos.dev/install | sh

Download ISO Image

In order to install Talos in Proxmox, you will need the ISO image from the Talos release page. You can download talos-amd64.iso via github.com/siderolabs/talos/releases

mkdir -p _out/
curl https://github.com/siderolabs/talos/releases/download/<version>/talos-<arch>.iso -L -o _out/talos-<arch>.iso

For example version v1.4.8 for linux platform:

mkdir -p _out/
curl https://github.com/siderolabs/talos/releases/download/v1.4.8/talos-amd64.iso -L -o _out/talos-amd64.iso

Upload ISO

From the Proxmox UI, select the “local” storage and enter the “Content” section. Click the “Upload” button:

Select the ISO you downloaded previously, then hit “Upload”

Create VMs

Before starting, familiarise yourself with the system requirements for Talos and assign VM resources accordingly.

Create a new VM by clicking the “Create VM” button in the Proxmox UI:

Fill out a name for the new VM:

In the OS tab, select the ISO we uploaded earlier:

Keep the defaults set in the “System” tab.

Keep the defaults in the “Hard Disk” tab as well, only changing the size if desired.

In the “CPU” section, give at least 2 cores to the VM:

Note: As of Talos v1.0 (which requires the x86-64-v2 microarchitecture), prior to Proxmox V8.0, booting with the default Processor Type kvm64 will not work. You can enable the required CPU features after creating the VM by adding the following line in the corresponding /etc/pve/qemu-server/<vmid>.conf file:
args: -cpu kvm64,+cx16,+lahf_lm,+popcnt,+sse3,+ssse3,+sse4.1,+sse4.2
Alternatively, you can set the Processor Type to host if your Proxmox host supports these CPU features, this however prevents using live VM migration.

Verify that the RAM is set to at least 2GB:

Keep the default values for networking, verifying that the VM is set to come up on the bridge interface:

Finish creating the VM by clicking through the “Confirm” tab and then “Finish”.

Repeat this process for a second VM to use as a worker node. You can also repeat this for additional nodes desired.

Note: Talos doesn’t support memory hot plugging, if creating the VM programmatically don’t enable memory hotplug on your Talos VM’s. Doing so will cause Talos to be unable to see all available memory and have insufficient memory to complete installation of the cluster.

Start Control Plane Node

Once the VMs have been created and updated, start the VM that will be the first control plane node. This VM will boot the ISO image specified earlier and enter “maintenance mode”.

With DHCP server

Once the machine has entered maintenance mode, there will be a console log that details the IP address that the node received. Take note of this IP address, which will be referred to as $CONTROL_PLANE_IP for the rest of this guide. If you wish to export this IP as a bash variable, simply issue a command like export CONTROL_PLANE_IP=1.2.3.4.

Without DHCP server

To apply the machine configurations in maintenance mode, VM has to have IP on the network. So you can set it on boot time manually.

Press e on the boot time. And set the IP parameters for the VM. Format is:

ip=<client-ip>:<srv-ip>:<gw-ip>:<netmask>:<host>:<device>:<autoconf>

For example $CONTROL_PLANE_IP will be 192.168.0.100 and gateway 192.168.0.1

linux /boot/vmlinuz init_on_alloc=1 slab_nomerge pti=on panic=0 consoleblank=0 printk.devkmsg=on earlyprintk=ttyS0 console=tty0 console=ttyS0 talos.platform=metal ip=192.168.0.100::192.168.0.1:255.255.255.0::eth0:off

Then press Ctrl-x or F10

Generate Machine Configurations

With the IP address above, you can now generate the machine configurations to use for installing Talos and Kubernetes. Issue the following command, updating the output directory, cluster name, and control plane IP as you see fit:

talosctl gen config talos-vbox-cluster https://$CONTROL_PLANE_IP:6443 --output-dir _out

This will create several files in the _out directory: controlplane.yaml, worker.yaml, and talosconfig.

Note: The Talos config by default will install to /dev/sda. Depending on your setup the virtual disk may be mounted differently Eg: /dev/vda. You can check for disks running the following command:
talosctl disks --insecure --nodes $CONTROL_PLANE_IP
Update controlplane.yaml and worker.yaml config files to point to the correct disk location.

Create Control Plane Node

Using the controlplane.yaml generated above, you can now apply this config using talosctl. Issue:

talosctl apply-config --insecure --nodes $CONTROL_PLANE_IP --file _out/controlplane.yaml

You should now see some action in the Proxmox console for this VM. Talos will be installed to disk, the VM will reboot, and then Talos will configure the Kubernetes control plane on this VM.

Note: This process can be repeated multiple times to create an HA control plane.

Create Worker Node

Create at least a single worker node using a process similar to the control plane creation above. Start the worker node VM and wait for it to enter “maintenance mode”. Take note of the worker node’s IP address, which will be referred to as $WORKER_IP

Issue:

talosctl apply-config --insecure --nodes $WORKER_IP --file _out/worker.yaml

Note: This process can be repeated multiple times to add additional workers.

Using the Cluster

Once the cluster is available, you can make use of talosctl and kubectl to interact with the cluster. For example, to view current running containers, run talosctl containers for a list of containers in the system namespace, or talosctl containers -k for the k8s.io namespace. To view the logs of a container, use talosctl logs <container> or talosctl logs -k <container>.

First, configure talosctl to talk to your control plane node by issuing the following, updating paths and IPs as necessary:

export TALOSCONFIG="_out/talosconfig"
talosctl config endpoint $CONTROL_PLANE_IP
talosctl config node $CONTROL_PLANE_IP

Bootstrap Etcd

talosctl bootstrap

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl kubeconfig .

Cleaning Up

To cleanup, simply stop and delete the virtual machines from the Proxmox UI.

2.1.2.4 - Vagrant & Libvirt

Pre-requisities

Linux OS
Vagrant installed
vagrant-libvirt plugin installed
talosctl installed
kubectl installed

Overview

We will use Vagrant and its libvirt plugin to create a KVM-based cluster with 3 control plane nodes and 1 worker node.

For this, we will mount Talos ISO into the VMs using a virtual CD-ROM, and configure the VMs to attempt to boot from the disk first with the fallback to the CD-ROM.

We will also configure a virtual IP address on Talos to achieve high-availability on kube-apiserver.

Preparing the environment

First, we download the latest talos-amd64.iso ISO from GitHub releases into the /tmp directory.

wget --timestamping https://github.com/siderolabs/talos/releases/download/v1.4.8/talos-amd64.iso -O /tmp/talos-amd64.iso

Create a Vagrantfile with the following contents:

Vagrant.configure("2") do |config|
  config.vm.define "control-plane-node-1" do |vm|
    vm.vm.provider :libvirt do |domain|
      domain.cpus = 2
      domain.memory = 2048
      domain.serial :type => "file", :source => {:path => "/tmp/control-plane-node-1.log"}
      domain.storage :file, :device => :cdrom, :path => "/tmp/talos-amd64.iso"
      domain.storage :file, :size => '4G', :type => 'raw'
      domain.boot 'hd'
      domain.boot 'cdrom'
    end
  end

  config.vm.define "control-plane-node-2" do |vm|
    vm.vm.provider :libvirt do |domain|
      domain.cpus = 2
      domain.memory = 2048
      domain.serial :type => "file", :source => {:path => "/tmp/control-plane-node-2.log"}
      domain.storage :file, :device => :cdrom, :path => "/tmp/talos-amd64.iso"
      domain.storage :file, :size => '4G', :type => 'raw'
      domain.boot 'hd'
      domain.boot 'cdrom'
    end
  end

  config.vm.define "control-plane-node-3" do |vm|
    vm.vm.provider :libvirt do |domain|
      domain.cpus = 2
      domain.memory = 2048
      domain.serial :type => "file", :source => {:path => "/tmp/control-plane-node-3.log"}
      domain.storage :file, :device => :cdrom, :path => "/tmp/talos-amd64.iso"
      domain.storage :file, :size => '4G', :type => 'raw'
      domain.boot 'hd'
      domain.boot 'cdrom'
    end
  end

  config.vm.define "worker-node-1" do |vm|
    vm.vm.provider :libvirt do |domain|
      domain.cpus = 1
      domain.memory = 1024
      domain.serial :type => "file", :source => {:path => "/tmp/worker-node-1.log"}
      domain.storage :file, :device => :cdrom, :path => "/tmp/talos-amd64.iso"
      domain.storage :file, :size => '4G', :type => 'raw'
      domain.boot 'hd'
      domain.boot 'cdrom'
    end
  end
end

Bring up the nodes

Check the status of vagrant VMs:

vagrant status

You should see the VMs in “not created” state:

Current machine states:

control-plane-node-1      not created (libvirt)
control-plane-node-2      not created (libvirt)
control-plane-node-3      not created (libvirt)
worker-node-1             not created (libvirt)

Bring up the vagrant environment:

vagrant up --provider=libvirt

Check the status again:

vagrant status

Now you should see the VMs in “running” state:

Current machine states:

control-plane-node-1      running (libvirt)
control-plane-node-2      running (libvirt)
control-plane-node-3      running (libvirt)
worker-node-1             running (libvirt)

Find out the IP addresses assigned by the libvirt DHCP by running:

virsh list | grep vagrant | awk '{print $2}' | xargs -t -L1 virsh domifaddr

Output will look like the following:

virsh domifaddr vagrant_control-plane-node-2
 Name       MAC address          Protocol     Address
-------------------------------------------------------------------------------
 vnet0      52:54:00:f9:10:e5    ipv4         192.168.121.119/24

virsh domifaddr vagrant_control-plane-node-1
 Name       MAC address          Protocol     Address
-------------------------------------------------------------------------------
 vnet1      52:54:00:0f:ae:59    ipv4         192.168.121.203/24

virsh domifaddr vagrant_worker-node-1
 Name       MAC address          Protocol     Address
-------------------------------------------------------------------------------
 vnet2      52:54:00:6f:28:95    ipv4         192.168.121.69/24

virsh domifaddr vagrant_control-plane-node-3
 Name       MAC address          Protocol     Address
-------------------------------------------------------------------------------
 vnet3      52:54:00:03:45:10    ipv4         192.168.121.125/24

Our control plane nodes have the IPs: 192.168.121.203, 192.168.121.119, 192.168.121.125 and the worker node has the IP 192.168.121.69.

Now you should be able to interact with Talos nodes that are in maintenance mode:

talosctl -n 192.168.121.203 disks --insecure

Sample output:

DEV        MODEL   SERIAL   TYPE   UUID   WWID   MODALIAS                    NAME   SIZE     BUS_PATH
/dev/vda   -       -        HDD    -      -      virtio:d00000002v00001AF4   -      8.6 GB   /pci0000:00/0000:00:03.0/virtio0/

Installing Talos

Pick an endpoint IP in the vagrant-libvirt subnet but not used by any nodes, for example 192.168.121.100.

Generate a machine configuration:

talosctl gen config my-cluster https://192.168.121.100:6443 --install-disk /dev/vda

Edit controlplane.yaml to add the virtual IP you picked to a network interface under .machine.network.interfaces, for example:

machine:
  network:
    interfaces:
      - interface: eth0
        dhcp: true
        vip:
          ip: 192.168.121.100

Apply the configuration to the initial control plane node:

talosctl -n 192.168.121.203 apply-config --insecure --file controlplane.yaml

You can tail the logs of the node:

sudo tail -f /tmp/control-plane-node-1.log

Set up your shell to use the generated talosconfig and configure its endpoints (use the IPs of the control plane nodes):

export TALOSCONFIG=$(realpath ./talosconfig)
talosctl config endpoint 192.168.121.203 192.168.121.119 192.168.121.125

Bootstrap the Kubernetes cluster from the initial control plane node:

talosctl -n 192.168.121.203 bootstrap

Finally, apply the machine configurations to the remaining nodes:

talosctl -n 192.168.121.119 apply-config --insecure --file controlplane.yaml
talosctl -n 192.168.121.125 apply-config --insecure --file controlplane.yaml
talosctl -n 192.168.121.69 apply-config --insecure --file worker.yaml

After a while, you should see that all the members have joined:

talosctl -n 192.168.121.203 get members

The output will be like the following:

NODE              NAMESPACE   TYPE     ID                      VERSION   HOSTNAME                MACHINE TYPE   OS               ADDRESSES
192.168.121.203   cluster     Member   talos-192-168-121-119   1         talos-192-168-121-119   controlplane   Talos (v1.1.0)   ["192.168.121.119"]
192.168.121.203   cluster     Member   talos-192-168-121-69    1         talos-192-168-121-69    worker         Talos (v1.1.0)   ["192.168.121.69"]
192.168.121.203   cluster     Member   talos-192-168-121-203   6         talos-192-168-121-203   controlplane   Talos (v1.1.0)   ["192.168.121.100","192.168.121.203"]
192.168.121.203   cluster     Member   talos-192-168-121-125   1         talos-192-168-121-125   controlplane   Talos (v1.1.0)   ["192.168.121.125"]

Interacting with Kubernetes cluster

Retrieve the kubeconfig from the cluster:

talosctl -n 192.168.121.203 kubeconfig ./kubeconfig

List the nodes in the cluster:

kubectl --kubeconfig ./kubeconfig get node -owide

You will see an output similar to:

NAME                    STATUS   ROLES                  AGE     VERSION   INTERNAL-IP       EXTERNAL-IP   OS-IMAGE         KERNEL-VERSION   CONTAINER-RUNTIME
talos-192-168-121-203   Ready    control-plane,master   3m10s   v1.24.2   192.168.121.203   <none>        Talos (v1.1.0)   5.15.48-talos    containerd://1.6.6
talos-192-168-121-69    Ready    <none>                 2m25s   v1.24.2   192.168.121.69    <none>        Talos (v1.1.0)   5.15.48-talos    containerd://1.6.6
talos-192-168-121-119   Ready    control-plane,master   8m46s   v1.24.2   192.168.121.119   <none>        Talos (v1.1.0)   5.15.48-talos    containerd://1.6.6
talos-192-168-121-125   Ready    control-plane,master   3m11s   v1.24.2   192.168.121.125   <none>        Talos (v1.1.0)   5.15.48-talos    containerd://1.6.6

Congratulations, you have a highly-available Talos cluster running!

Cleanup

You can destroy the vagrant environment by running:

vagrant destroy -f

And remove the ISO image you downloaded:

sudo rm -f /tmp/talos-amd64.iso

2.1.2.5 - VMware

Creating Talos Kubernetes cluster using VMware.

Creating a Cluster via the `govc` CLI

In this guide we will create an HA Kubernetes cluster with 2 worker nodes. We will use the govc cli which can be downloaded here.

Prereqs/Assumptions

This guide will use the virtual IP (“VIP”) functionality that is built into Talos in order to provide a stable, known IP for the Kubernetes control plane. This simply means the user should pick an IP on their “VM Network” to designate for this purpose and keep it handy for future steps.

Create the Machine Configuration Files

Generating Base Configurations

Using the VIP chosen in the prereq steps, we will now generate the base configuration files for the Talos machines. This can be done with the talosctl gen config ... command. Take note that we will also use a JSON6902 patch when creating the configs so that the control plane nodes get some special information about the VIP we chose earlier, as well as a daemonset to install vmware tools on talos nodes.

First, download cp.patch.yaml to your local machine and edit the VIP to match your chosen IP. You can do this by issuing: curl -fsSLO https://raw.githubusercontent.com/siderolabs/talos/master/website/content/v1.4/talos-guides/install/virtualized-platforms/vmware/cp.patch.yaml. It’s contents should look like the following:

- op: add
  path: /machine/network
  value:
    interfaces:
    - interface: eth0
      dhcp: true
      vip:
        ip: <VIP>
- op: replace
  path: /cluster/extraManifests
  value:
    - "https://raw.githubusercontent.com/mologie/talos-vmtoolsd/master/deploy/unstable.yaml"

With the patch in hand, generate machine configs with:

$ talosctl gen config vmware-test https://<VIP>:<port> --config-patch-control-plane @cp.patch.yaml
created controlplane.yaml
created worker.yaml
created talosconfig

At this point, you can modify the generated configs to your liking if needed. Optionally, you can specify additional patches by adding to the cp.patch.yaml file downloaded earlier, or create your own patch files.

Validate the Configuration Files

$ talosctl validate --config controlplane.yaml --mode cloud
controlplane.yaml is valid for cloud mode
$ talosctl validate --config worker.yaml --mode cloud
worker.yaml is valid for cloud mode

Set Environment Variables

govc makes use of the following environment variables

export GOVC_URL=<vCenter url>
export GOVC_USERNAME=<vCenter username>
export GOVC_PASSWORD=<vCenter password>

Note: If your vCenter installation makes use of self signed certificates, you’ll want to export GOVC_INSECURE=true.

There are some additional variables that you may need to set:

export GOVC_DATACENTER=<vCenter datacenter>
export GOVC_RESOURCE_POOL=<vCenter resource pool>
export GOVC_DATASTORE=<vCenter datastore>
export GOVC_NETWORK=<vCenter network>

Choose Install Approach

As part of this guide, we have a more automated install script that handles some of the complexity of importing OVAs and creating VMs. If you wish to use this script, we will detail that next. If you wish to carry out the manual approach, simply skip ahead to the “Manual Approach” section.

Scripted Install

Download the vmware.sh script to your local machine. You can do this by issuing curl -fsSLO "https://raw.githubusercontent.com/siderolabs/talos/master/website/content/v1.4/talos-guides/install/virtualized-platforms/vmware/vmware.sh". This script has default variables for things like Talos version and cluster name that may be interesting to tweak before deploying.

Import OVA

To create a content library and import the Talos OVA corresponding to the mentioned Talos version, simply issue:

./vmware.sh upload_ova

Create Cluster

With the OVA uploaded to the content library, you can create a 5 node (by default) cluster with 3 control plane and 2 worker nodes:

./vmware.sh create

This step will create a VM from the OVA, edit the settings based on the env variables used for VM size/specs, then power on the VMs.

You may now skip past the “Manual Approach” section down to “Bootstrap Cluster”.

Manual Approach

Import the OVA into vCenter

A talos.ova asset is published with each release. We will refer to the version of the release as $TALOS_VERSION below. It can be easily exported with export TALOS_VERSION="v0.3.0-alpha.10" or similar.

curl -LO https://github.com/siderolabs/talos/releases/download/$TALOS_VERSION/talos.ova

Create a content library (if needed) with:

govc library.create <library name>

Import the OVA to the library with:

govc library.import -n talos-${TALOS_VERSION} <library name> /path/to/downloaded/talos.ova

Create the Bootstrap Node

We’ll clone the OVA to create the bootstrap node (our first control plane node).

govc library.deploy <library name>/talos-${TALOS_VERSION} control-plane-1

Talos makes use of the guestinfo facility of VMware to provide the machine/cluster configuration. This can be set using the govc vm.change command. To facilitate persistent storage using the vSphere cloud provider integration with Kubernetes, disk.enableUUID=1 is used.

govc vm.change \
  -e "guestinfo.talos.config=$(cat controlplane.yaml | base64)" \
  -e "disk.enableUUID=1" \
  -vm control-plane-1

Update Hardware Resources for the Bootstrap Node

-c is used to configure the number of cpus
-m is used to configure the amount of memory (in MB)

govc vm.change \
  -c 2 \
  -m 4096 \
  -vm control-plane-1

The following can be used to adjust the EPHEMERAL disk size.

govc vm.disk.change -vm control-plane-1 -disk.name disk-1000-0 -size 10G

govc vm.power -on control-plane-1

Create the Remaining Control Plane Nodes

govc library.deploy <library name>/talos-${TALOS_VERSION} control-plane-2
govc vm.change \
  -e "guestinfo.talos.config=$(base64 controlplane.yaml)" \
  -e "disk.enableUUID=1" \
  -vm control-plane-2

govc library.deploy <library name>/talos-${TALOS_VERSION} control-plane-3
govc vm.change \
  -e "guestinfo.talos.config=$(base64 controlplane.yaml)" \
  -e "disk.enableUUID=1" \
  -vm control-plane-3

govc vm.change \
  -c 2 \
  -m 4096 \
  -vm control-plane-2

govc vm.change \
  -c 2 \
  -m 4096 \
  -vm control-plane-3

govc vm.disk.change -vm control-plane-2 -disk.name disk-1000-0 -size 10G

govc vm.disk.change -vm control-plane-3 -disk.name disk-1000-0 -size 10G

govc vm.power -on control-plane-2

govc vm.power -on control-plane-3

Update Settings for the Worker Nodes

govc library.deploy <library name>/talos-${TALOS_VERSION} worker-1
govc vm.change \
  -e "guestinfo.talos.config=$(base64 worker.yaml)" \
  -e "disk.enableUUID=1" \
  -vm worker-1

govc library.deploy <library name>/talos-${TALOS_VERSION} worker-2
govc vm.change \
  -e "guestinfo.talos.config=$(base64 worker.yaml)" \
  -e "disk.enableUUID=1" \
  -vm worker-2

govc vm.change \
  -c 4 \
  -m 8192 \
  -vm worker-1

govc vm.change \
  -c 4 \
  -m 8192 \
  -vm worker-2

govc vm.disk.change -vm worker-1 -disk.name disk-1000-0 -size 10G

govc vm.disk.change -vm worker-2 -disk.name disk-1000-0 -size 10G

govc vm.power -on worker-1

govc vm.power -on worker-2

Bootstrap Cluster

In the vSphere UI, open a console to one of the control plane nodes. You should see some output stating that etcd should be bootstrapped. This text should look like:

"etcd is waiting to join the cluster, if this node is the first node in the cluster, please run `talosctl bootstrap` against one of the following IPs:

Take note of the IP mentioned here and issue:

talosctl --talosconfig talosconfig bootstrap -e <control plane IP> -n <control plane IP>

Keep this IP handy for the following steps as well.

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl --talosconfig talosconfig config endpoint <control plane IP>
talosctl --talosconfig talosconfig config node <control plane IP>
talosctl --talosconfig talosconfig kubeconfig .

Configure `talos-vmtoolsd`

The talos-vmtoolsd application was deployed as a daemonset as part of the cluster creation; however, we must now provide a talos credentials file for it to use.

Create a new talosconfig with:

talosctl --talosconfig talosconfig -n <control plane IP> config new vmtoolsd-secret.yaml --roles os:admin

Create a secret from the talosconfig:

kubectl -n kube-system create secret generic talos-vmtoolsd-config \
  --from-file=talosconfig=./vmtoolsd-secret.yaml

Clean up the generated file from local system:

rm vmtoolsd-secret.yaml

Once configured, you should now see these daemonset pods go into “Running” state and in vCenter, you will now see IPs and info from the Talos nodes present in the UI.

2.1.2.6 - Xen

Talos is known to work on Xen. We don’t yet have a documented guide specific to Xen; however, you can follow the General Getting Started Guide. If you run into any issues, our community can probably help!

2.1.3 - Cloud Platforms

Installation of Talos Linux on many cloud platforms.

2.1.3.1 - AWS

Creating a cluster via the AWS CLI.

Creating a Cluster via the AWS CLI

In this guide we will create an HA Kubernetes cluster with 3 worker nodes. We assume an existing VPC, and some familiarity with AWS. If you need more information on AWS specifics, please see the official AWS documentation.

Set the needed info

Change to your desired region:

REGION="us-west-2"
aws ec2 describe-vpcs --region $REGION

VPC="(the VpcId from the above command)"

Create the Subnet

Use a CIDR block that is present on the VPC specified above.

aws ec2 create-subnet \
    --region $REGION \
    --vpc-id $VPC \
    --cidr-block ${CIDR_BLOCK}

Note the subnet ID that was returned, and assign it to a variable for ease of later use:

SUBNET="(the subnet ID of the created subnet)"

Official AMI Images

Official AMI image ID can be found in the cloud-images.json file attached to the Talos release:

AMI=`curl -sL https://github.com/siderolabs/talos/releases/download/v1.4.8/cloud-images.json | \
    jq -r '.[] | select(.region == "'$REGION'") | select (.arch == "amd64") | .id'`
echo $AMI

Replace amd64 in the line above with the desired architecture. Note the AMI id that is returned is assigned to an environment variable: it will be used later when booting instances.

If using the official AMIs, you can skip to Creating the Security group

Create your own AMIs

The use of the official Talos AMIs are recommended, but if you wish to build your own AMIs, follow the procedure below.

Create the S3 Bucket

aws s3api create-bucket \
    --bucket $BUCKET \
    --create-bucket-configuration LocationConstraint=$REGION \
    --acl private

Create the `vmimport` Role

In order to create an AMI, ensure that the vmimport role exists as described in the official AWS documentation.

Note that the role should be associated with the S3 bucket we created above.

Create the Image Snapshot

First, download the AWS image from a Talos release:

curl -L https://github.com/siderolabs/talos/releases/download/v1.4.8/aws-amd64.tar.gz | tar -xv

Copy the RAW disk to S3 and import it as a snapshot:

aws s3 cp disk.raw s3://$BUCKET/talos-aws-tutorial.raw
aws ec2 import-snapshot \
    --region $REGION \
    --description "Talos kubernetes tutorial" \
    --disk-container "Format=raw,UserBucket={S3Bucket=$BUCKET,S3Key=talos-aws-tutorial.raw}"

Save the SnapshotId, as we will need it once the import is done. To check on the status of the import, run:

aws ec2 describe-import-snapshot-tasks \
    --region $REGION \
    --import-task-ids

Once the SnapshotTaskDetail.Status indicates completed, we can register the image.

Register the Image

aws ec2 register-image \
    --region $REGION \
    --block-device-mappings "DeviceName=/dev/xvda,VirtualName=talos,Ebs={DeleteOnTermination=true,SnapshotId=$SNAPSHOT,VolumeSize=4,VolumeType=gp2}" \
    --root-device-name /dev/xvda \
    --virtualization-type hvm \
    --architecture x86_64 \
    --ena-support \
    --name talos-aws-tutorial-ami

We now have an AMI we can use to create our cluster. Save the AMI ID, as we will need it when we create EC2 instances.

AMI="(AMI ID of the register image command)"

Create a Security Group

aws ec2 create-security-group \
    --region $REGION \
    --group-name talos-aws-tutorial-sg \
    --description "Security Group for EC2 instances to allow ports required by Talos"

SECURITY_GROUP="(security group id that is returned)"

Using the security group from above, allow all internal traffic within the same security group:

aws ec2 authorize-security-group-ingress \
    --region $REGION \
    --group-name talos-aws-tutorial-sg \
    --protocol all \
    --port 0 \
    --source-group talos-aws-tutorial-sg

and expose the Talos and Kubernetes APIs:

aws ec2 authorize-security-group-ingress \
    --region $REGION \
    --group-name talos-aws-tutorial-sg \
    --protocol tcp \
    --port 6443 \
    --cidr 0.0.0.0/0

aws ec2 authorize-security-group-ingress \
    --region $REGION \
    --group-name talos-aws-tutorial-sg \
    --protocol tcp \
    --port 50000-50001 \
    --cidr 0.0.0.0/0

Create a Load Balancer

aws elbv2 create-load-balancer \
    --region $REGION \
    --name talos-aws-tutorial-lb \
    --type network --subnets $SUBNET

Take note of the DNS name and ARN. We will need these soon.

LOAD_BALANCER_ARN="(arn of the load balancer)"

aws elbv2 create-target-group \
    --region $REGION \
    --name talos-aws-tutorial-tg \
    --protocol TCP \
    --port 6443 \
    --target-type ip \
    --vpc-id $VPC

Also note the TargetGroupArn that is returned.

TARGET_GROUP_ARN="(target group arn)"

Create the Machine Configuration Files

Using the DNS name of the loadbalancer created earlier, generate the base configuration files for the Talos machines.

Note that the port used here is the externally accessible port configured on the load balancer - 443 - not the internal port of 6443:

$ talosctl gen config talos-k8s-aws-tutorial https://<load balancer DNS>:<port> --with-examples=false --with-docs=false
created controlplane.yaml
created worker.yaml
created talosconfig

Note that the generated configs are too long for AWS userdata field if the --with-examples and --with-docs flags are not passed.

At this point, you can modify the generated configs to your liking.

Optionally, you can specify --config-patch with RFC6902 jsonpatch which will be applied during the config generation.

Validate the Configuration Files

$ talosctl validate --config controlplane.yaml --mode cloud
controlplane.yaml is valid for cloud mode
$ talosctl validate --config worker.yaml --mode cloud
worker.yaml is valid for cloud mode

Create the EC2 Instances

change the instance type if desired. Note: There is a known issue that prevents Talos from running on T2 instance types. Please use T3 if you need burstable instance types.

Create the Control Plane Nodes

CP_COUNT=1
while [[ "$CP_COUNT" -lt 4 ]]; do
  aws ec2 run-instances \
    --region $REGION \
    --image-id $AMI \
    --count 1 \
    --instance-type t3.small \
    --user-data file://controlplane.yaml \
    --subnet-id $SUBNET \
    --security-group-ids $SECURITY_GROUP \
    --associate-public-ip-address \
    --tag-specifications "ResourceType=instance,Tags=[{Key=Name,Value=talos-aws-tutorial-cp-$CP_COUNT}]"
  ((CP_COUNT++))
done

Make a note of the resulting PrivateIpAddress from the controlplane nodes for later use.

Create the Worker Nodes

aws ec2 run-instances \
    --region $REGION \
    --image-id $AMI \
    --count 3 \
    --instance-type t3.small \
    --user-data file://worker.yaml \
    --subnet-id $SUBNET \
    --security-group-ids $SECURITY_GROUP
    --tag-specifications "ResourceType=instance,Tags=[{Key=Name,Value=talos-aws-tutorial-worker}]"

Configure the Load Balancer

Now, using the load balancer target group’s ARN, and the PrivateIpAddress from the controlplane instances that you created :

aws elbv2 register-targets \
    --region $REGION \
    --target-group-arn $TARGET_GROUP_ARN \
    --targets Id=$CP_NODE_1_IP  Id=$CP_NODE_2_IP  Id=$CP_NODE_3_IP

Using the ARNs of the load balancer and target group from previous steps, create the listener:

aws elbv2 create-listener \
    --region $REGION \
    --load-balancer-arn $LOAD_BALANCER_ARN \
    --protocol TCP \
    --port 443 \
    --default-actions Type=forward,TargetGroupArn=$TARGET_GROUP_ARN

Bootstrap Etcd

Set the endpoints (the control plane node to which talosctl commands are sent) and nodes (the nodes that the command operates on):

talosctl --talosconfig talosconfig config endpoint <control plane 1 PUBLIC IP>
talosctl --talosconfig talosconfig config node <control plane 1 PUBLIC IP>

Bootstrap etcd:

talosctl --talosconfig talosconfig bootstrap

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl --talosconfig talosconfig kubeconfig .

The different control plane nodes should sendi/receive traffic via the load balancer, notice that one of the control plane has intiated the etcd cluster, and the others should join. You can now watch as your cluster bootstraps, by using

talosctl --talosconfig talosconfig  health

You can also watch the performance of a node, via:

talosctl  --talosconfig talosconfig dashboard

And use standard kubectl commands.

2.1.3.2 - Azure

Creating a cluster via the CLI on Azure.

Creating a Cluster via the CLI

In this guide we will create an HA Kubernetes cluster with 1 worker node. We assume existing Blob Storage, and some familiarity with Azure. If you need more information on Azure specifics, please see the official Azure documentation.

Environment Setup

We’ll make use of the following environment variables throughout the setup. Edit the variables below with your correct information.

# Storage account to use
export STORAGE_ACCOUNT="StorageAccountName"

# Storage container to upload to
export STORAGE_CONTAINER="StorageContainerName"

# Resource group name
export GROUP="ResourceGroupName"

# Location
export LOCATION="centralus"

# Get storage account connection string based on info above
export CONNECTION=$(az storage account show-connection-string \
                    -n $STORAGE_ACCOUNT \
                    -g $GROUP \
                    -o tsv)

Create the Image

First, download the Azure image from a Talos release. Once downloaded, untar with tar -xvf /path/to/azure-amd64.tar.gz

Upload the VHD

Once you have pulled down the image, you can upload it to blob storage with:

az storage blob upload \
  --connection-string $CONNECTION \
  --container-name $STORAGE_CONTAINER \
  -f /path/to/extracted/talos-azure.vhd \
  -n talos-azure.vhd

Register the Image

Now that the image is present in our blob storage, we’ll register it.

az image create \
  --name talos \
  --source https://$STORAGE_ACCOUNT.blob.core.windows.net/$STORAGE_CONTAINER/talos-azure.vhd \
  --os-type linux \
  -g $GROUP

Network Infrastructure

Virtual Networks and Security Groups

Once the image is prepared, we’ll want to work through setting up the network. Issue the following to create a network security group and add rules to it.

# Create vnet
az network vnet create \
  --resource-group $GROUP \
  --location $LOCATION \
  --name talos-vnet \
  --subnet-name talos-subnet

# Create network security group
az network nsg create -g $GROUP -n talos-sg

# Client -> apid
az network nsg rule create \
  -g $GROUP \
  --nsg-name talos-sg \
  -n apid \
  --priority 1001 \
  --destination-port-ranges 50000 \
  --direction inbound

# Trustd
az network nsg rule create \
  -g $GROUP \
  --nsg-name talos-sg \
  -n trustd \
  --priority 1002 \
  --destination-port-ranges 50001 \
  --direction inbound

# etcd
az network nsg rule create \
  -g $GROUP \
  --nsg-name talos-sg \
  -n etcd \
  --priority 1003 \
  --destination-port-ranges 2379-2380 \
  --direction inbound

# Kubernetes API Server
az network nsg rule create \
  -g $GROUP \
  --nsg-name talos-sg \
  -n kube \
  --priority 1004 \
  --destination-port-ranges 6443 \
  --direction inbound

Load Balancer

We will create a public ip, load balancer, and a health check that we will use for our control plane.

# Create public ip
az network public-ip create \
  --resource-group $GROUP \
  --name talos-public-ip \
  --allocation-method static

# Create lb
az network lb create \
  --resource-group $GROUP \
  --name talos-lb \
  --public-ip-address talos-public-ip \
  --frontend-ip-name talos-fe \
  --backend-pool-name talos-be-pool

# Create health check
az network lb probe create \
  --resource-group $GROUP \
  --lb-name talos-lb \
  --name talos-lb-health \
  --protocol tcp \
  --port 6443

# Create lb rule for 6443
az network lb rule create \
  --resource-group $GROUP \
  --lb-name talos-lb \
  --name talos-6443 \
  --protocol tcp \
  --frontend-ip-name talos-fe \
  --frontend-port 6443 \
  --backend-pool-name talos-be-pool \
  --backend-port 6443 \
  --probe-name talos-lb-health

Network Interfaces

In Azure, we have to pre-create the NICs for our control plane so that they can be associated with our load balancer.

for i in $( seq 0 1 2 ); do
  # Create public IP for each nic
  az network public-ip create \
    --resource-group $GROUP \
    --name talos-controlplane-public-ip-$i \
    --allocation-method static


  # Create nic
  az network nic create \
    --resource-group $GROUP \
    --name talos-controlplane-nic-$i \
    --vnet-name talos-vnet \
    --subnet talos-subnet \
    --network-security-group talos-sg \
    --public-ip-address talos-controlplane-public-ip-$i\
    --lb-name talos-lb \
    --lb-address-pools talos-be-pool
done

# NOTES:
# Talos can detect PublicIPs automatically if PublicIP SKU is Basic.
# Use `--sku Basic` to set SKU to Basic.

Cluster Configuration

With our networking bits setup, we’ll fetch the IP for our load balancer and create our configuration files.

LB_PUBLIC_IP=$(az network public-ip show \
              --resource-group $GROUP \
              --name talos-public-ip \
              --query [ipAddress] \
              --output tsv)

talosctl gen config talos-k8s-azure-tutorial https://${LB_PUBLIC_IP}:6443

Compute Creation

We are now ready to create our azure nodes. Azure allows you to pass Talos machine configuration to the virtual machine at bootstrap time via user-data or custom-data methods.

Talos supports only custom-data method, machine configuration is available to the VM only on the first boot.

# Create availability set
az vm availability-set create \
  --name talos-controlplane-av-set \
  -g $GROUP

# Create the controlplane nodes
for i in $( seq 0 1 2 ); do
  az vm create \
    --name talos-controlplane-$i \
    --image talos \
    --custom-data ./controlplane.yaml \
    -g $GROUP \
    --admin-username talos \
    --generate-ssh-keys \
    --verbose \
    --boot-diagnostics-storage $STORAGE_ACCOUNT \
    --os-disk-size-gb 20 \
    --nics talos-controlplane-nic-$i \
    --availability-set talos-controlplane-av-set \
    --no-wait
done

# Create worker node
  az vm create \
    --name talos-worker-0 \
    --image talos \
    --vnet-name talos-vnet \
    --subnet talos-subnet \
    --custom-data ./worker.yaml \
    -g $GROUP \
    --admin-username talos \
    --generate-ssh-keys \
    --verbose \
    --boot-diagnostics-storage $STORAGE_ACCOUNT \
    --nsg talos-sg \
    --os-disk-size-gb 20 \
    --no-wait

# NOTES:
# `--admin-username` and `--generate-ssh-keys` are required by the az cli,
# but are not actually used by talos
# `--os-disk-size-gb` is the backing disk for Kubernetes and any workload containers
# `--boot-diagnostics-storage` is to enable console output which may be necessary
# for troubleshooting

Bootstrap Etcd

You should now be able to interact with your cluster with talosctl. We will need to discover the public IP for our first control plane node first.

CONTROL_PLANE_0_IP=$(az network public-ip show \
                    --resource-group $GROUP \
                    --name talos-controlplane-public-ip-0 \
                    --query [ipAddress] \
                    --output tsv)

Set the endpoints and nodes:

talosctl --talosconfig talosconfig config endpoint $CONTROL_PLANE_0_IP
talosctl --talosconfig talosconfig config node $CONTROL_PLANE_0_IP

Bootstrap etcd:

talosctl --talosconfig talosconfig bootstrap

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl --talosconfig talosconfig kubeconfig .

2.1.3.3 - DigitalOcean

Creating a cluster via the CLI on DigitalOcean.

Creating a Talos Linux Cluster on Digital Ocean via the CLI

In this guide we will create an HA Kubernetes cluster with 1 worker node, in the NYC region. We assume an existing Space, and some familiarity with DigitalOcean. If you need more information on DigitalOcean specifics, please see the official DigitalOcean documentation.

Create the Image

Download the DigitalOcean image digital-ocean-amd64.raw.gz from the latest Talos release.

Note: the minimum version of Talos required to support Digital Ocean is v1.3.3.

Using an upload method of your choice (doctl does not have Spaces support), upload the image to a space. (It’s easy to drag the image file to the space using DigitalOcean’s web console.)

Note: Make sure you upload the file as public.

Now, create an image using the URL of the uploaded image:

export REGION=nyc3

doctl compute image create \
    --region $REGION \
    --image-description talos-digital-ocean-tutorial \
    --image-url https://$SPACENAME.$REGION.digitaloceanspaces.com/digital-ocean-amd64.raw.gz \
    Talos

Save the image ID. We will need it when creating droplets.

Create a Load Balancer

doctl compute load-balancer create \
    --region $REGION \
    --name talos-digital-ocean-tutorial-lb \
    --tag-name talos-digital-ocean-tutorial-control-plane \
    --health-check protocol:tcp,port:6443,check_interval_seconds:10,response_timeout_seconds:5,healthy_threshold:5,unhealthy_threshold:3 \
    --forwarding-rules entry_protocol:tcp,entry_port:443,target_protocol:tcp,target_port:6443

Note the returned ID of the load balancer.

We will need the IP of the load balancer. Using the ID of the load balancer, run:

doctl compute load-balancer get --format IP <load balancer ID>

Note that it may take a few minutes before the load balancer is provisioned, so repeat this command until it returns with the IP address.

Create the Machine Configuration Files

Using the IP address (or DNS name, if you have created one) of the loadbalancer, generate the base configuration files for the Talos machines. Also note that the load balancer forwards port 443 to port 6443 on the associated nodes, so we should use 443 as the port in the config definition:

$ talosctl gen config talos-k8s-digital-ocean-tutorial https://<load balancer IP or DNS>:443
created controlplane.yaml
created worker.yaml
created talosconfig

Create the Droplets

Create a dummy SSH key

Although SSH is not used by Talos, DigitalOcean requires that an SSH key be associated with a droplet during creation. We will create a dummy key that can be used to satisfy this requirement.

doctl compute ssh-key create --public-key "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDbl0I1s/yOETIKjFr7mDLp8LmJn6OIZ68ILjVCkoN6lzKmvZEqEm1YYeWoI0xgb80hQ1fKkl0usW6MkSqwrijoUENhGFd6L16WFL53va4aeJjj2pxrjOr3uBFm/4ATvIfFTNVs+VUzFZ0eGzTgu1yXydX8lZMWnT4JpsMraHD3/qPP+pgyNuI51LjOCG0gVCzjl8NoGaQuKnl8KqbSCARIpETg1mMw+tuYgaKcbqYCMbxggaEKA0ixJ2MpFC/kwm3PcksTGqVBzp3+iE5AlRe1tnbr6GhgT839KLhOB03j7lFl1K9j1bMTOEj5Io8z7xo/XeF2ZQKHFWygAJiAhmKJ dummy@dummy.local" dummy

Note the ssh key ID that is returned - we will use it in creating the droplets.

Create the Control Plane Nodes

Run the following commands to create three control plane nodes:

doctl compute droplet create \
    --region $REGION \
    --image <image ID> \
    --size s-2vcpu-4gb \
    --enable-private-networking \
    --tag-names talos-digital-ocean-tutorial-control-plane \
    --user-data-file controlplane.yaml \
    --ssh-keys <ssh key ID> \
    talos-control-plane-1
doctl compute droplet create \
    --region $REGION \
    --image <image ID> \
    --size s-2vcpu-4gb \
    --enable-private-networking \
    --tag-names talos-digital-ocean-tutorial-control-plane \
    --user-data-file controlplane.yaml \
    --ssh-keys <ssh key ID> \
    talos-control-plane-2
doctl compute droplet create \
    --region $REGION \
    --image <image ID> \
    --size s-2vcpu-4gb \
    --enable-private-networking \
    --tag-names talos-digital-ocean-tutorial-control-plane \
    --user-data-file controlplane.yaml \
    --ssh-keys <ssh key ID> \
    talos-control-plane-3

Note the droplet ID returned for the first control plane node.

Create the Worker Nodes

Run the following to create a worker node:

doctl compute droplet create \
    --region $REGION \
    --image <image ID> \
    --size s-2vcpu-4gb \
    --enable-private-networking \
    --user-data-file worker.yaml \
    --ssh-keys <ssh key ID>  \
    talos-worker-1

Bootstrap Etcd

To configure talosctl we will need the first control plane node’s IP:

doctl compute droplet get --format PublicIPv4 <droplet ID>

Set the endpoints and nodes:

talosctl --talosconfig talosconfig config endpoint <control plane 1 IP>
talosctl --talosconfig talosconfig config node <control plane 1 IP>

Bootstrap etcd:

talosctl --talosconfig talosconfig bootstrap

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl --talosconfig talosconfig kubeconfig .

We can also watch the cluster bootstrap via:

talosctl --talosconfig talosconfig health

2.1.3.4 - Exoscale

Creating a cluster via the CLI using exoscale.com

Talos is known to work on exoscale.com; however, it is currently undocumented.

2.1.3.5 - GCP

Creating a cluster via the CLI on Google Cloud Platform.

Creating a Cluster via the CLI

In this guide, we will create an HA Kubernetes cluster in GCP with 1 worker node. We will assume an existing Cloud Storage bucket, and some familiarity with Google Cloud. If you need more information on Google Cloud specifics, please see the official Google documentation.

jq and talosctl also needs to be installed

Manual Setup

Environment Setup

We’ll make use of the following environment variables throughout the setup. Edit the variables below with your correct information.

# Storage account to use
export STORAGE_BUCKET="StorageBucketName"
# Region
export REGION="us-central1"

Create the Image

First, download the Google Cloud image from a Talos release. These images are called gcp-$ARCH.tar.gz.

Upload the Image

Once you have downloaded the image, you can upload it to your storage bucket with:

gsutil cp /path/to/gcp-amd64.tar.gz gs://$STORAGE_BUCKET

Register the image

Now that the image is present in our bucket, we’ll register it.

gcloud compute images create talos \
 --source-uri=gs://$STORAGE_BUCKET/gcp-amd64.tar.gz \
 --guest-os-features=VIRTIO_SCSI_MULTIQUEUE

Network Infrastructure

Load Balancers and Firewalls

Once the image is prepared, we’ll want to work through setting up the network. Issue the following to create a firewall, load balancer, and their required components.

130.211.0.0/22 and 35.191.0.0/16 are the GCP Load Balancer IP ranges

# Create Instance Group
gcloud compute instance-groups unmanaged create talos-ig \
  --zone $REGION-b

# Create port for IG
gcloud compute instance-groups set-named-ports talos-ig \
    --named-ports tcp6443:6443 \
    --zone $REGION-b

# Create health check
gcloud compute health-checks create tcp talos-health-check --port 6443

# Create backend
gcloud compute backend-services create talos-be \
    --global \
    --protocol TCP \
    --health-checks talos-health-check \
    --timeout 5m \
    --port-name tcp6443

# Add instance group to backend
gcloud compute backend-services add-backend talos-be \
    --global \
    --instance-group talos-ig \
    --instance-group-zone $REGION-b

# Create tcp proxy
gcloud compute target-tcp-proxies create talos-tcp-proxy \
    --backend-service talos-be \
    --proxy-header NONE

# Create LB IP
gcloud compute addresses create talos-lb-ip --global

# Forward 443 from LB IP to tcp proxy
gcloud compute forwarding-rules create talos-fwd-rule \
    --global \
    --ports 443 \
    --address talos-lb-ip \
    --target-tcp-proxy talos-tcp-proxy

# Create firewall rule for health checks
gcloud compute firewall-rules create talos-controlplane-firewall \
     --source-ranges 130.211.0.0/22,35.191.0.0/16 \
     --target-tags talos-controlplane \
     --allow tcp:6443

# Create firewall rule to allow talosctl access
gcloud compute firewall-rules create talos-controlplane-talosctl \
  --source-ranges 0.0.0.0/0 \
  --target-tags talos-controlplane \
  --allow tcp:50000

Cluster Configuration

With our networking bits setup, we’ll fetch the IP for our load balancer and create our configuration files.

LB_PUBLIC_IP=$(gcloud compute forwarding-rules describe talos-fwd-rule \
               --global \
               --format json \
               | jq -r .IPAddress)

talosctl gen config talos-k8s-gcp-tutorial https://${LB_PUBLIC_IP}:443

Additionally, you can specify --config-patch with RFC6902 jsonpatch which will be applied during the config generation.

Compute Creation

We are now ready to create our GCP nodes.

# Create the control plane nodes.
for i in $( seq 1 3 ); do
  gcloud compute instances create talos-controlplane-$i \
    --image talos \
    --zone $REGION-b \
    --tags talos-controlplane \
    --boot-disk-size 20GB \
    --metadata-from-file=user-data=./controlplane.yaml
    --tags talos-controlplane-$i
done

# Add control plane nodes to instance group
for i in $( seq 1 3 ); do
  gcloud compute instance-groups unmanaged add-instances talos-ig \
      --zone $REGION-b \
      --instances talos-controlplane-$i
done

# Create worker
gcloud compute instances create talos-worker-0 \
  --image talos \
  --zone $REGION-b \
  --boot-disk-size 20GB \
  --metadata-from-file=user-data=./worker.yaml
  --tags talos-worker-$i

Bootstrap Etcd

You should now be able to interact with your cluster with talosctl. We will need to discover the public IP for our first control plane node first.

CONTROL_PLANE_0_IP=$(gcloud compute instances describe talos-controlplane-0 \
                     --zone $REGION-b \
                     --format json \
                     | jq -r '.networkInterfaces[0].accessConfigs[0].natIP')

Set the endpoints and nodes:

talosctl --talosconfig talosconfig config endpoint $CONTROL_PLANE_0_IP
talosctl --talosconfig talosconfig config node $CONTROL_PLANE_0_IP

Bootstrap etcd:

talosctl --talosconfig talosconfig bootstrap

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl --talosconfig talosconfig kubeconfig .

Cleanup

# cleanup VM's
gcloud compute instances delete \
  talos-worker-0 \
  talos-controlplane-0 \
  talos-controlplane-1 \
  talos-controlplane-2

# cleanup firewall rules
gcloud compute firewall-rules delete \
  talos-controlplane-talosctl \
  talos-controlplane-firewall

# cleanup forwarding rules
gcloud compute forwarding-rules delete \
  talos-fwd-rule

# cleanup addresses
gcloud compute addresses delete \
  talos-lb-ip

# cleanup proxies
gcloud compute target-tcp-proxies delete \
  talos-tcp-proxy

# cleanup backend services
gcloud compute backend-services delete \
  talos-be

# cleanup health checks
gcloud compute health-checks delete \
  talos-health-check

# cleanup unmanaged instance groups
gcloud compute instance-groups unmanaged delete \
  talos-ig

# cleanup Talos image
gcloud compute images delete \
  talos

Using GCP Deployment manager

Using GCP deployment manager automatically creates a Google Storage bucket and uploads the Talos image to it. Once the deployment is complete the generated talosconfig and kubeconfig files are uploaded to the bucket.

By default this setup creates a three node control plane and a single worker in us-west1-b

First we need to create a folder to store our deployment manifests and perform all subsequent operations from that folder.

mkdir -p talos-gcp-deployment
cd talos-gcp-deployment

Getting the deployment manifests

We need to download two deployment manifests for the deployment from the Talos github repository.

curl -fsSLO "https://raw.githubusercontent.com/siderolabs/talos/master/website/content/v1.4/talos-guides/install/cloud-platforms/gcp/config.yaml"
curl -fsSLO "https://raw.githubusercontent.com/siderolabs/talos/master/website/content/v1.4/talos-guides/install/cloud-platforms/gcp/talos-ha.jinja"
# if using ccm
curl -fsSLO "https://raw.githubusercontent.com/siderolabs/talos/master/website/content/v1.4/talos-guides/install/cloud-platforms/gcp/gcp-ccm.yaml"

Updating the config

Now we need to update the local config.yaml file with any required changes such as changing the default zone, Talos version, machine sizes, nodes count etc.

An example config.yaml file is shown below:

imports:
  - path: talos-ha.jinja

resources:
  - name: talos-ha
    type: talos-ha.jinja
    properties:
      zone: us-west1-b
      talosVersion: v1.4.8
      externalCloudProvider: false
      controlPlaneNodeCount: 5
      controlPlaneNodeType: n1-standard-1
      workerNodeCount: 3
      workerNodeType: n1-standard-1
outputs:
  - name: bucketName
    value: $(ref.talos-ha.bucketName)

Enabling external cloud provider

Note: The externalCloudProvider property is set to false by default. The manifest used for deploying the ccm (cloud controller manager) is currently using the GCP ccm provided by openshift since there are no public images for the ccm yet.

Since the routes controller is disabled while deploying the CCM, the CNI pods needs to be restarted after the CCM deployment is complete to remove the node.kubernetes.io/network-unavailable taint. See Nodes network-unavailable taint not removed after installing ccm for more information

Use a custom built image for the ccm deployment if required.

Creating the deployment

Now we are ready to create the deployment. Confirm with y for any prompts. Run the following command to create the deployment:

# use a unique name for the deployment, resources are prefixed with the deployment name
export DEPLOYMENT_NAME="<deployment name>"
gcloud deployment-manager deployments create "${DEPLOYMENT_NAME}" --config config.yaml

Retrieving the outputs

First we need to get the deployment outputs.

# first get the outputs
OUTPUTS=$(gcloud deployment-manager deployments describe "${DEPLOYMENT_NAME}" --format json | jq '.outputs[]')

BUCKET_NAME=$(jq -r '. | select(.name == "bucketName").finalValue' <<< "${OUTPUTS}")
# used when cloud controller is enabled
SERVICE_ACCOUNT=$(jq -r '. | select(.name == "serviceAccount").finalValue' <<< "${OUTPUTS}")
PROJECT=$(jq -r '. | select(.name == "project").finalValue' <<< "${OUTPUTS}")

Note: If cloud controller manager is enabled, the below command needs to be run to allow the controller custom role to access cloud resources

gcloud projects add-iam-policy-binding \
    "${PROJECT}" \
    --member "serviceAccount:${SERVICE_ACCOUNT}" \
    --role roles/iam.serviceAccountUser

gcloud projects add-iam-policy-binding \
    "${PROJECT}" \
    --member serviceAccount:"${SERVICE_ACCOUNT}" \
    --role roles/compute.admin

gcloud projects add-iam-policy-binding \
    "${PROJECT}" \
    --member serviceAccount:"${SERVICE_ACCOUNT}" \
    --role roles/compute.loadBalancerAdmin

Downloading talos and kube config

In addition to the talosconfig and kubeconfig files, the storage bucket contains the controlplane.yaml and worker.yaml files used to join additional nodes to the cluster.

gsutil cp "gs://${BUCKET_NAME}/generated/talosconfig" .
gsutil cp "gs://${BUCKET_NAME}/generated/kubeconfig" .

Deploying the cloud controller manager

kubectl \
  --kubeconfig kubeconfig \
  --namespace kube-system \
  apply \
  --filename gcp-ccm.yaml
#  wait for the ccm to be up
kubectl \
  --kubeconfig kubeconfig \
  --namespace kube-system \
  rollout status \
  daemonset cloud-controller-manager

If the cloud controller manager is enabled, we need to restart the CNI pods to remove the node.kubernetes.io/network-unavailable taint.

# restart the CNI pods, in this case flannel
kubectl \
  --kubeconfig kubeconfig \
  --namespace kube-system \
  rollout restart \
  daemonset kube-flannel
# wait for the pods to be restarted
kubectl \
  --kubeconfig kubeconfig \
  --namespace kube-system \
  rollout status \
  daemonset kube-flannel

Check cluster status

kubectl \
  --kubeconfig kubeconfig \
  get nodes

Cleanup deployment

Warning: This will delete the deployment and all resources associated with it.

Run below if cloud controller manager is enabled

gcloud projects remove-iam-policy-binding \
    "${PROJECT}" \
    --member "serviceAccount:${SERVICE_ACCOUNT}" \
    --role roles/iam.serviceAccountUser

gcloud projects remove-iam-policy-binding \
    "${PROJECT}" \
    --member serviceAccount:"${SERVICE_ACCOUNT}" \
    --role roles/compute.admin

gcloud projects remove-iam-policy-binding \
    "${PROJECT}" \
    --member serviceAccount:"${SERVICE_ACCOUNT}" \
    --role roles/compute.loadBalancerAdmin

Now we can finally remove the deployment

# delete the objects in the bucket first
gsutil -m rm -r "gs://${BUCKET_NAME}"
gcloud deployment-manager deployments delete "${DEPLOYMENT_NAME}" --quiet

2.1.3.6 - Hetzner

Creating a cluster via the CLI (hcloud) on Hetzner.

Upload image

Hetzner Cloud does not support uploading custom images. You can email their support to get a Talos ISO uploaded by following issues:3599 or you can prepare image snapshot by yourself.

There are two options to upload your own.

Run an instance in rescue mode and replace the system OS with the Talos image
Use Hashicorp packer to prepare an image

Rescue mode

Create a new Server in the Hetzner console. Enable the Hetzner Rescue System for this server and reboot. Upon a reboot, the server will boot a special minimal Linux distribution designed for repair and reinstall. Once running, login to the server using ssh to prepare the system disk by doing the following:

# Check that you in Rescue mode
df

### Result is like:
# udev                   987432         0    987432   0% /dev
# 213.133.99.101:/nfs 308577696 247015616  45817536  85% /root/.oldroot/nfs
# overlay                995672      8340    987332   1% /
# tmpfs                  995672         0    995672   0% /dev/shm
# tmpfs                  398272       572    397700   1% /run
# tmpfs                    5120         0      5120   0% /run/lock
# tmpfs                  199132         0    199132   0% /run/user/0

# Download the Talos image
cd /tmp
wget -O /tmp/talos.raw.xz https://github.com/siderolabs/talos/releases/download/v1.4.8/hcloud-amd64.raw.xz
# Replace system
xz -d -c /tmp/talos.raw.xz | dd of=/dev/sda && sync
# shutdown the instance
shutdown -h now

To make sure disk content is consistent, it is recommended to shut the server down before taking an image (snapshot). Once shutdown, simply create an image (snapshot) from the console. You can now use this snapshot to run Talos on the cloud.

Packer

Install packer to the local machine.

Create a config file for packer to use:

# hcloud.pkr.hcl

packer {
  required_plugins {
    hcloud = {
      version = ">= 1.0.0"
      source  = "github.com/hashicorp/hcloud"
    }
  }
}

variable "talos_version" {
  type    = string
  default = "v1.4.8"
}

locals {
  image = "https://github.com/siderolabs/talos/releases/download/${var.talos_version}/hcloud-amd64.raw.xz"
}

source "hcloud" "talos" {
  rescue       = "linux64"
  image        = "debian-11"
  location     = "hel1"
  server_type  = "cx11"
  ssh_username = "root"

  snapshot_name = "talos system disk"
  snapshot_labels = {
    type    = "infra",
    os      = "talos",
    version = "${var.talos_version}",
  }
}

build {
  sources = ["source.hcloud.talos"]

  provisioner "shell" {
    inline = [
      "apt-get install -y wget",
      "wget -O /tmp/talos.raw.xz ${local.image}",
      "xz -d -c /tmp/talos.raw.xz | dd of=/dev/sda && sync",
    ]
  }
}

Create a new image by issuing the commands shown below. Note that to create a new API token for your Project, switch into the Hetzner Cloud Console choose a Project, go to Access → Security, and create a new token.

# First you need set API Token
export HCLOUD_TOKEN=${TOKEN}

# Upload image
packer init .
packer build .
# Save the image ID
export IMAGE_ID=<image-id-in-packer-output>

After doing this, you can find the snapshot in the console interface.

Creating a Cluster via the CLI

This section assumes you have the hcloud console utility on your local machine.

# Set hcloud context and api key
hcloud context create talos-tutorial

Create a Load Balancer

Create a load balancer by issuing the commands shown below. Save the IP/DNS name, as this info will be used in the next step.

hcloud load-balancer create --name controlplane --network-zone eu-central --type lb11 --label 'type=controlplane'

### Result is like:
# LoadBalancer 484487 created
# IPv4: 49.12.X.X
# IPv6: 2a01:4f8:X:X::1

hcloud load-balancer add-service controlplane \
    --listen-port 6443 --destination-port 6443 --protocol tcp
hcloud load-balancer add-target controlplane \
    --label-selector 'type=controlplane'

Create the Machine Configuration Files

Generating Base Configurations

Using the IP/DNS name of the loadbalancer created earlier, generate the base configuration files for the Talos machines by issuing:

$ talosctl gen config talos-k8s-hcloud-tutorial https://<load balancer IP or DNS>:6443
created controlplane.yaml
created worker.yaml
created talosconfig

At this point, you can modify the generated configs to your liking. Optionally, you can specify --config-patch with RFC6902 jsonpatches which will be applied during the config generation.

Validate the Configuration Files

Validate any edited machine configs with:

$ talosctl validate --config controlplane.yaml --mode cloud
controlplane.yaml is valid for cloud mode
$ talosctl validate --config worker.yaml --mode cloud
worker.yaml is valid for cloud mode

Create the Servers

We can now create our servers. Note that you can find IMAGE_ID in the snapshot section of the console: https://console.hetzner.cloud/projects/$PROJECT_ID/servers/snapshots.

Create the Control Plane Nodes

Create the control plane nodes with:

export IMAGE_ID=<your-image-id>

hcloud server create --name talos-control-plane-1 \
    --image ${IMAGE_ID} \
    --type cx21 --location hel1 \
    --label 'type=controlplane' \
    --user-data-from-file controlplane.yaml

hcloud server create --name talos-control-plane-2 \
    --image ${IMAGE_ID} \
    --type cx21 --location fsn1 \
    --label 'type=controlplane' \
    --user-data-from-file controlplane.yaml

hcloud server create --name talos-control-plane-3 \
    --image ${IMAGE_ID} \
    --type cx21 --location nbg1 \
    --label 'type=controlplane' \
    --user-data-from-file controlplane.yaml

Create the Worker Nodes

Create the worker nodes with the following command, repeating (and incrementing the name counter) as many times as desired.

hcloud server create --name talos-worker-1 \
    --image ${IMAGE_ID} \
    --type cx21 --location hel1 \
    --label 'type=worker' \
    --user-data-from-file worker.yaml

Bootstrap Etcd

To configure talosctl we will need the first control plane node’s IP. This can be found by issuing:

hcloud server list | grep talos-control-plane

Set the endpoints and nodes for your talosconfig with:

talosctl --talosconfig talosconfig config endpoint <control-plane-1-IP>
talosctl --talosconfig talosconfig config node <control-plane-1-IP>

Bootstrap etcd on the first control plane node with:

talosctl --talosconfig talosconfig bootstrap

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl --talosconfig talosconfig kubeconfig .

2.1.3.7 - Nocloud

Creating a cluster via the CLI using qemu.

Talos supports nocloud data source implementation.

There are two ways to configure Talos server with nocloud platform:

via SMBIOS “serial number” option
using CDROM or USB-flash filesystem

Note: This requires the nocloud image which can be found on the Github Releases page.

SMBIOS Serial Number

This method requires the network connection to be up (e.g. via DHCP). Configuration is delivered from the HTTP server.

ds=nocloud-net;s=http://10.10.0.1/configs/;h=HOSTNAME

After the network initialization is complete, Talos fetches:

the machine config from http://10.10.0.1/configs/user-data
the network config (if available) from http://10.10.0.1/configs/network-config

SMBIOS: QEMU

Add the following flag to qemu command line when starting a VM:

qemu-system-x86_64 \
  ...\
  -smbios type=1,serial=ds=nocloud-net;s=http://10.10.0.1/configs/

SMBIOS: Proxmox

Set the source machine config through the serial number on Proxmox GUI.

The Proxmox stores the VM config at /etc/pve/qemu-server/$ID.conf ($ID - VM ID number of virtual machine), you will see something like:

...
smbios1: uuid=ceae4d10,serial=ZHM9bm9jbG91ZC1uZXQ7cz1odHRwOi8vMTAuMTAuMC4xL2NvbmZpZ3Mv,base64=1
...

Where serial holds the base64-encoded string version of ds=nocloud-net;s=http://10.10.0.1/configs/.

CDROM/USB

Talos can also get machine config from local attached storage without any prior network connection being established.

You can provide configs to the server via files on a VFAT or ISO9660 filesystem. The filesystem volume label must be cidata or CIDATA.

Example: QEMU

Create and prepare Talos machine config:

export CONTROL_PLANE_IP=192.168.1.10

talosctl gen config talos-nocloud https://$CONTROL_PLANE_IP:6443 --output-dir _out

Prepare cloud-init configs:

mkdir -p iso
mv _out/controlplane.yaml iso/user-data
echo "local-hostname: controlplane-1" > iso/meta-data
cat > iso/network-config << EOF
version: 1
config:
   - type: physical
     name: eth0
     mac_address: "52:54:00:12:34:00"
     subnets:
        - type: static
          address: 192.168.1.10
          netmask: 255.255.255.0
          gateway: 192.168.1.254
EOF

Create cloud-init iso image

cd iso && genisoimage -output cidata.iso -V cidata -r -J user-data meta-data network-config

Start the VM

qemu-system-x86_64 \
    ...
    -cdrom iso/cidata.iso \
    ...

Example: Proxmox

Proxmox can create cloud-init disk for you. Edit the cloud-init config information in Proxmox as follows, substitute your own information as necessary:

and then update cicustom param at /etc/pve/qemu-server/$ID.conf.

cicustom: user=local:snippets/controlplane-1.yml
ipconfig0: ip=192.168.1.10/24,gw=192.168.10.254
nameserver: 1.1.1.1
searchdomain: local

Note: snippets/controlplane-1.yml is Talos machine config. It is usually located at /var/lib/vz/snippets/controlplane-1.yml. This file must be placed to this path manually, as Proxmox does not support snippet uploading via API/GUI.

Click on Regenerate Image button after the above changes are made.

2.1.3.8 - OpenStack

Creating a cluster via the CLI on OpenStack.

Creating a Cluster via the CLI

In this guide, we will create an HA Kubernetes cluster in OpenStack with 1 worker node. We will assume an existing some familiarity with OpenStack. If you need more information on OpenStack specifics, please see the official OpenStack documentation.

Environment Setup

You should have an existing openrc file. This file will provide environment variables necessary to talk to your OpenStack cloud. See here for instructions on fetching this file.

Create the Image

First, download the OpenStack image from a Talos release. These images are called openstack-$ARCH.tar.gz. Untar this file with tar -xvf openstack-$ARCH.tar.gz. The resulting file will be called disk.raw.

Upload the Image

Once you have the image, you can upload to OpenStack with:

openstack image create --public --disk-format raw --file disk.raw talos

Network Infrastructure

Load Balancer and Network Ports

Once the image is prepared, you will need to work through setting up the network. Issue the following to create a load balancer, the necessary network ports for each control plane node, and associations between the two.

Creating loadbalancer:

# Create load balancer, updating vip-subnet-id if necessary
openstack loadbalancer create --name talos-control-plane --vip-subnet-id public

# Create listener
openstack loadbalancer listener create --name talos-control-plane-listener --protocol TCP --protocol-port 6443 talos-control-plane

# Pool and health monitoring
openstack loadbalancer pool create --name talos-control-plane-pool --lb-algorithm ROUND_ROBIN --listener talos-control-plane-listener --protocol TCP
openstack loadbalancer healthmonitor create --delay 5 --max-retries 4 --timeout 10 --type TCP talos-control-plane-pool

Creating ports:

# Create ports for control plane nodes, updating network name if necessary
openstack port create --network shared talos-control-plane-1
openstack port create --network shared talos-control-plane-2
openstack port create --network shared talos-control-plane-3

# Create floating IPs for the ports, so that you will have talosctl connectivity to each control plane
openstack floating ip create --port talos-control-plane-1 public
openstack floating ip create --port talos-control-plane-2 public
openstack floating ip create --port talos-control-plane-3 public

Note: Take notice of the private and public IPs associated with each of these ports, as they will be used in the next step. Additionally, take node of the port ID, as it will be used in server creation.

Associate port’s private IPs to loadbalancer:

# Create members for each port IP, updating subnet-id and address as necessary.
openstack loadbalancer member create --subnet-id shared-subnet --address <PRIVATE IP OF talos-control-plane-1 PORT> --protocol-port 6443 talos-control-plane-pool
openstack loadbalancer member create --subnet-id shared-subnet --address <PRIVATE IP OF talos-control-plane-2 PORT> --protocol-port 6443 talos-control-plane-pool
openstack loadbalancer member create --subnet-id shared-subnet --address <PRIVATE IP OF talos-control-plane-3 PORT> --protocol-port 6443 talos-control-plane-pool

Security Groups

This example uses the default security group in OpenStack. Ports have been opened to ensure that connectivity from both inside and outside the group is possible. You will want to allow, at a minimum, ports 6443 (Kubernetes API server) and 50000 (Talos API) from external sources. It is also recommended to allow communication over all ports from within the subnet.

Cluster Configuration

With our networking bits setup, we’ll fetch the IP for our load balancer and create our configuration files.

LB_PUBLIC_IP=$(openstack loadbalancer show talos-control-plane -f json | jq -r .vip_address)

talosctl gen config talos-k8s-openstack-tutorial https://${LB_PUBLIC_IP}:6443

Additionally, you can specify --config-patch with RFC6902 jsonpatch which will be applied during the config generation.

Compute Creation

We are now ready to create our OpenStack nodes.

Create control plane:

# Create control planes 2 and 3, substituting the same info.
for i in $( seq 1 3 ); do
  openstack server create talos-control-plane-$i --flavor m1.small --nic port-id=talos-control-plane-$i --image talos --user-data /path/to/controlplane.yaml
done

Create worker:

# Update network name as necessary.
openstack server create talos-worker-1 --flavor m1.small --network shared --image talos --user-data /path/to/worker.yaml

Note: This step can be repeated to add more workers.

Bootstrap Etcd

You should now be able to interact with your cluster with talosctl. We will use one of the floating IPs we allocated earlier. It does not matter which one.

Set the endpoints and nodes:

talosctl --talosconfig talosconfig config endpoint <control plane 1 IP>
talosctl --talosconfig talosconfig config node <control plane 1 IP>

Bootstrap etcd:

talosctl --talosconfig talosconfig bootstrap

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl --talosconfig talosconfig kubeconfig .

2.1.3.9 - Oracle

Creating a cluster via the CLI (oci) on OracleCloud.com.

Upload image

Oracle Cloud at the moment does not have a Talos official image. So you can use Bring Your Own Image (BYOI) approach.

Once the image is uploaded, set the Boot volume type to Paravirtualized mode.

OracleCloud has highly available NTP service, it can be enabled in Talos machine config with:

machine:
  time:
    servers:
      - 169.254.169.254

Creating a Cluster via the CLI

Create a network

export cidr_block=10.0.0.0/16
export subnet_block=10.0.0.0/24
export compartment_id=<substitute-value-of-compartment_id> # https://docs.cloud.oracle.com/en-us/iaas/tools/oci-cli/latest/oci_cli_docs/cmdref/network/vcn/create.html#cmdoption-compartment-id

export vcn_id=$(oci network vcn create --cidr-block $cidr_block --display-name talos-example --compartment-id $compartment_id --query data.id --raw-output)
export rt_id=$(oci network subnet create --cidr-block $subnet_block --display-name kubernetes --compartment-id $compartment_id --vcn-id $vcn_id --query data.route-table-id --raw-output)
export ig_id=$(oci network internet-gateway create --compartment-id $compartment_id --is-enabled true --vcn-id $vcn_id --query data.id --raw-output)

oci network route-table update --rt-id $rt_id --route-rules "[{\"cidrBlock\":\"0.0.0.0/0\",\"networkEntityId\":\"$ig_id\"}]" --force

# disable firewall
export sl_id=$(oci network vcn list --compartment-id $compartment_id --query 'data[0]."default-security-list-id"' --raw-output)

oci network security-list update --security-list-id $sl_id --egress-security-rules '[{"destination": "0.0.0.0/0", "protocol": "all", "isStateless": false}]' --ingress-security-rules '[{"source": "0.0.0.0/0", "protocol": "all", "isStateless": false}]' --force

Create a Load Balancer

Create a load balancer by issuing the commands shown below. Save the IP/DNS name, as this info will be used in the next step.

export subnet_id=$(oci network subnet list --compartment-id=$compartment_id --display-name kubernetes --query data[0].id --raw-output)
export network_load_balancer_id=$(oci nlb network-load-balancer create --compartment-id $compartment_id --display-name controlplane-lb --subnet-id $subnet_id --is-preserve-source-destination false --is-private false --query data.id --raw-output)

cat <<EOF > talos-health-checker.json
{
  "intervalInMillis": 10000,
  "port": 50000,
  "protocol": "TCP"
}
EOF

oci nlb backend-set create --health-checker file://talos-health-checker.json --name talos --network-load-balancer-id $network_load_balancer_id --policy TWO_TUPLE --is-preserve-source false
oci nlb listener create --default-backend-set-name talos --name talos --network-load-balancer-id $network_load_balancer_id --port 50000 --protocol TCP

cat <<EOF > controlplane-health-checker.json
{
  "intervalInMillis": 10000,
  "port": 6443,
  "protocol": "HTTPS",
  "returnCode": 401,
  "urlPath": "/readyz"
}
EOF

oci nlb backend-set create --health-checker file://controlplane-health-checker.json --name controlplane --network-load-balancer-id $network_load_balancer_id --policy TWO_TUPLE --is-preserve-source false
oci nlb listener create --default-backend-set-name controlplane --name controlplane --network-load-balancer-id $network_load_balancer_id --port 6443 --protocol TCP

# Save the external IP
oci nlb network-load-balancer list --compartment-id $compartment_id --display-name controlplane-lb --query 'data.items[0]."ip-addresses"'

Create the Machine Configuration Files

Generating Base Configurations

Using the IP/DNS name of the loadbalancer created earlier, generate the base configuration files for the Talos machines by issuing:

$ talosctl gen config talos-k8s-oracle-tutorial https://<load balancer IP or DNS>:6443 --additional-sans <load balancer IP or DNS>
created controlplane.yaml
created worker.yaml
created talosconfig

At this point, you can modify the generated configs to your liking. Optionally, you can specify --config-patch with RFC6902 jsonpatches which will be applied during the config generation.

Validate the Configuration Files

Validate any edited machine configs with:

$ talosctl validate --config controlplane.yaml --mode cloud
controlplane.yaml is valid for cloud mode
$ talosctl validate --config worker.yaml --mode cloud
worker.yaml is valid for cloud mode

Create the Servers

Create the Control Plane Nodes

Create the control plane nodes with:

export shape='VM.Standard.A1.Flex'
export subnet_id=$(oci network subnet list --compartment-id=$compartment_id --display-name kubernetes --query data[0].id --raw-output)
export image_id=$(oci compute image list --compartment-id $compartment_id --shape $shape --operating-system Talos --limit 1 --query data[0].id --raw-output)
export availability_domain=$(oci iam availability-domain list --compartment-id=$compartment_id --query data[0].name --raw-output)
export network_load_balancer_id=$(oci nlb network-load-balancer list --compartment-id $compartment_id --display-name controlplane-lb --query 'data.items[0].id' --raw-output)

cat <<EOF > shape.json
{
  "memoryInGBs": 4,
  "ocpus": 1
}
EOF

export instance_id=$(oci compute instance launch --shape $shape --shape-config file://shape.json --availability-domain $availability_domain --compartment-id $compartment_id --image-id $image_id --subnet-id $subnet_id --display-name controlplane-1 --private-ip 10.0.0.11 --assign-public-ip true --launch-options '{"networkType":"PARAVIRTUALIZED"}' --user-data-file controlplane.yaml --query 'data.id' --raw-output)

oci nlb backend create --backend-set-name talos --network-load-balancer-id $network_load_balancer_id --port 50000 --target-id $instance_id
oci nlb backend create --backend-set-name controlplane --network-load-balancer-id $network_load_balancer_id --port 6443 --target-id $instance_id

export instance_id=$(oci compute instance launch --shape $shape --shape-config file://shape.json --availability-domain $availability_domain --compartment-id $compartment_id --image-id $image_id --subnet-id $subnet_id --display-name controlplane-2 --private-ip 10.0.0.12 --assign-public-ip true --launch-options '{"networkType":"PARAVIRTUALIZED"}' --user-data-file controlplane.yaml --query 'data.id' --raw-output)

oci nlb backend create --backend-set-name talos --network-load-balancer-id $network_load_balancer_id --port 50000 --target-id $instance_id
oci nlb backend create --backend-set-name controlplane --network-load-balancer-id $network_load_balancer_id --port 6443 --target-id $instance_id

export instance_id=$(oci compute instance launch --shape $shape --shape-config file://shape.json --availability-domain $availability_domain --compartment-id $compartment_id --image-id $image_id --subnet-id $subnet_id --display-name controlplane-3 --private-ip 10.0.0.13 --assign-public-ip true --launch-options '{"networkType":"PARAVIRTUALIZED"}' --user-data-file controlplane.yaml --query 'data.id' --raw-output)

oci nlb backend create --backend-set-name talos --network-load-balancer-id $network_load_balancer_id --port 50000 --target-id $instance_id
oci nlb backend create --backend-set-name controlplane --network-load-balancer-id $network_load_balancer_id --port 6443 --target-id $instance_id

Create the Worker Nodes

Create the worker nodes with the following command, repeating (and incrementing the name counter) as many times as desired.

export subnet_id=$(oci network subnet list --compartment-id=$compartment_id --display-name kubernetes --query data[0].id --raw-output)
export image_id=$(oci compute image list --compartment-id $compartment_id --operating-system Talos --limit 1 --query data[0].id --raw-output)
export availability_domain=$(oci iam availability-domain list --compartment-id=$compartment_id --query data[0].name --raw-output)
export shape='VM.Standard.E2.1.Micro'

oci compute instance launch --shape $shape --availability-domain $availability_domain --compartment-id $compartment_id --image-id $image_id --subnet-id $subnet_id --display-name worker-1 --assign-public-ip true --user-data-file worker.yaml

oci compute instance launch --shape $shape --availability-domain $availability_domain --compartment-id $compartment_id --image-id $image_id --subnet-id $subnet_id --display-name worker-2 --assign-public-ip true --user-data-file worker.yaml

oci compute instance launch --shape $shape --availability-domain $availability_domain --compartment-id $compartment_id --image-id $image_id --subnet-id $subnet_id --display-name worker-3 --assign-public-ip true --user-data-file worker.yaml

Bootstrap Etcd

To configure talosctl we will need the first control plane node’s IP. This can be found by issuing:

export instance_id=$(oci compute instance list --compartment-id $compartment_id --display-name controlplane-1 --query 'data[0].id' --raw-output)

oci compute instance list-vnics --instance-id $instance_id --query 'data[0]."private-ip"' --raw-output

Set the endpoints and nodes for your talosconfig with:

talosctl --talosconfig talosconfig config endpoint <load balancer IP or DNS>
talosctl --talosconfig talosconfig config node <control-plane-1-IP>

Bootstrap etcd on the first control plane node with:

talosctl --talosconfig talosconfig bootstrap

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl --talosconfig talosconfig kubeconfig .

2.1.3.10 - Scaleway

Creating a cluster via the CLI (scw) on scaleway.com.

Talos is known to work on scaleway.com; however, it is currently undocumented.

2.1.3.11 - UpCloud

Creating a cluster via the CLI (upctl) on UpCloud.com.

In this guide we will create an HA Kubernetes cluster 3 control plane nodes and 1 worker node. We assume some familiarity with UpCloud. If you need more information on UpCloud specifics, please see the official UpCloud documentation.

Create the Image

The best way to create an image for UpCloud, is to build one using Hashicorp packer, with the upcloud-amd64.raw.xz image found on the Talos Releases. Using the general ISO is also possible, but the UpCloud image has some UpCloud specific features implemented, such as the fetching of metadata and user data to configure the nodes.

To create the cluster, you need a few things locally installed:

NOTE: Make sure your account allows API connections. To do so, log into UpCloud control panel and go to People -> Account -> Permissions -> Allow API connections checkbox. It is recommended to create a separate subaccount for your API access and only set the API permission.

To use the UpCloud CLI, you need to create a config in $HOME/.config/upctl.yaml

username: your_upcloud_username
password: your_upcloud_password

To use the UpCloud packer plugin, you need to also export these credentials to your environment variables, by e.g. putting the following in your .bashrc or .zshrc

export UPCLOUD_USERNAME="<username>"
export UPCLOUD_PASSWORD="<password>"

Next create a config file for packer to use:

# upcloud.pkr.hcl

packer {
  required_plugins {
    upcloud = {
      version = ">=v1.0.0"
      source  = "github.com/UpCloudLtd/upcloud"
    }
  }
}

variable "talos_version" {
  type    = string
  default = "v1.4.8"
}

locals {
  image = "https://github.com/siderolabs/talos/releases/download/${var.talos_version}/upcloud-amd64.raw.xz"
}

variable "username" {
  type        = string
  description = "UpCloud API username"
  default     = "${env("UPCLOUD_USERNAME")}"
}

variable "password" {
  type        = string
  description = "UpCloud API password"
  default     = "${env("UPCLOUD_PASSWORD")}"
  sensitive   = true
}

source "upcloud" "talos" {
  username        = "${var.username}"
  password        = "${var.password}"
  zone            = "us-nyc1"
  storage_name    = "Debian GNU/Linux 11 (Bullseye)"
  template_name   = "Talos (${var.talos_version})"
}

build {
  sources = ["source.upcloud.talos"]

  provisioner "shell" {
    inline = [
      "apt-get install -y wget xz-utils",
      "wget -q -O /tmp/talos.raw.xz ${local.image}",
      "xz -d -c /tmp/talos.raw.xz | dd of=/dev/vda",
    ]
  }

  provisioner "shell-local" {
      inline = [
      "upctl server stop --type hard custom",
      ]
  }
}

Now create a new image by issuing the commands shown below.

packer init .
packer build .

After doing this, you can find the custom image in the console interface under storage.

Creating a Cluster via the CLI

Create an Endpoint

To communicate with the Talos cluster you will need a single endpoint that is used to access the cluster. This can either be a loadbalancer that will sit in front of all your control plane nodes, a DNS name with one or more A or AAAA records pointing to the control plane nodes, or directly the IP of a control plane node.

Which option is best for you will depend on your needs. Endpoint selection has been further documented here.

After you decide on which endpoint to use, note down the domain name or IP, as we will need it in the next step.

Create the Machine Configuration Files

Generating Base Configurations

Using the DNS name of the endpoint created earlier, generate the base configuration files for the Talos machines:

$ talosctl gen config talos-upcloud-tutorial https://<load balancer IP or DNS>:<port> --install-disk /dev/vda
created controlplane.yaml
created worker.yaml
created talosconfig

At this point, you can modify the generated configs to your liking. Depending on the Kubernetes version you want to run, you might need to select a different Talos version, as not all versions are compatible. You can find the support matrix here.

Optionally, you can specify --config-patch with RFC6902 jsonpatch or yamlpatch which will be applied during the config generation.

Validate the Configuration Files

$ talosctl validate --config controlplane.yaml --mode cloud
controlplane.yaml is valid for cloud mode
$ talosctl validate --config worker.yaml --mode cloud
worker.yaml is valid for cloud mode

Create the Servers

Create the Control Plane Nodes

Run the following to create three total control plane nodes:

for ID in $(seq 3); do
    upctl server create \
      --zone us-nyc1 \
      --title talos-us-nyc1-master-$ID \
      --hostname talos-us-nyc1-master-$ID \
      --plan 2xCPU-4GB \
      --os "Talos (v1.4.8)" \
      --user-data "$(cat controlplane.yaml)" \
      --enable-metada
done

Note: modify the zone and OS depending on your preferences. The OS should match the template name generated with packer in the previous step.

Note the IP address of the first control plane node, as we will need it later.

Create the Worker Nodes

Run the following to create a worker node:

upctl server create \
  --zone us-nyc1 \
  --title talos-us-nyc1-worker-1 \
  --hostname talos-us-nyc1-worker-1 \
  --plan 2xCPU-4GB \
  --os "Talos (v1.4.8)" \
  --user-data "$(cat worker.yaml)" \
  --enable-metada

Bootstrap Etcd

To configure talosctl we will need the first control plane node’s IP, as noted earlier. We only add one node IP, as that is the entry into our cluster against which our commands will be run. All requests to other nodes are proxied through the endpoint, and therefore not all nodes need to be manually added to the config. You don’t want to run your commands against all nodes, as this can destroy your cluster if you are not careful (further documentation).

Set the endpoints and nodes:

talosctl --talosconfig talosconfig config endpoint <control plane 1 IP>
talosctl --talosconfig talosconfig config node <control plane 1 IP>

Bootstrap etcd:

talosctl --talosconfig talosconfig bootstrap

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl --talosconfig talosconfig kubeconfig

It will take a few minutes before Kubernetes has been fully bootstrapped, and is accessible.

You can check if the nodes are registered in Talos by running

talosctl --talosconfig talosconfig get members

To check if your nodes are ready, run

kubectl get nodes

2.1.3.12 - Vultr

Creating a cluster via the CLI (vultr-cli) on Vultr.com.

Creating a Cluster using the Vultr CLI

This guide will demonstrate how to create a highly-available Kubernetes cluster with one worker using the Vultr cloud provider.

Vultr have a very well documented REST API, and an open-source CLI tool to interact with the API which will be used in this guide. Make sure to follow installation and authentication instructions for the vultr-cli tool.

Upload image

First step is to make the Talos ISO available to Vultr by uploading the latest release of the ISO to the Vultr ISO server.

vultr-cli iso create --url https://github.com/siderolabs/talos/releases/download/v1.4.8/talos-amd64.iso

Make a note of the ID in the output, it will be needed later when creating the instances.

Create a Load Balancer

A load balancer is needed to serve as the Kubernetes endpoint for the cluster.

vultr-cli load-balancer create \
   --region $REGION \
   --label "Talos Kubernetes Endpoint" \
   --port 6443 \
   --protocol tcp \
   --check-interval 10 \
   --response-timeout 5 \
   --healthy-threshold 5 \
   --unhealthy-threshold 3 \
   --forwarding-rules frontend_protocol:tcp,frontend_port:443,backend_protocol:tcp,backend_port:6443

Make a note of the ID of the load balancer from the output of the above command, it will be needed after the control plane instances are created.

vultr-cli load-balancer get $LOAD_BALANCER_ID | grep ^IP

Make a note of the IP address, it will be needed later when generating the configuration.

Create the Machine Configuration

Generate Base Configuration

Using the IP address (or DNS name if one was created) of the load balancer created above, generate the machine configuration files for the new cluster.

talosctl gen config talos-kubernetes-vultr https://$LOAD_BALANCER_ADDRESS

Once generated, the machine configuration can be modified as necessary for the new cluster, for instance updating disk installation, or adding SANs for the certificates.

Validate the Configuration Files

talosctl validate --config controlplane.yaml --mode cloud
talosctl validate --config worker.yaml --mode cloud

Create the Nodes

Create the Control Plane Nodes

First a control plane needs to be created, with the example below creating 3 instances in a loop. The instance type (noted by the --plan vc2-2c-4gb argument) in the example is for a minimum-spec control plane node, and should be updated to suit the cluster being created.

for id in $(seq 3); do
    vultr-cli instance create \
        --plan vc2-2c-4gb \
        --region $REGION \
        --iso $TALOS_ISO_ID \
        --host talos-k8s-cp${id} \
        --label "Talos Kubernetes Control Plane" \
        --tags talos,kubernetes,control-plane
done

Make a note of the instance IDs, as they are needed to attach to the load balancer created earlier.

vultr-cli load-balancer update $LOAD_BALANCER_ID --instances $CONTROL_PLANE_1_ID,$CONTROL_PLANE_2_ID,$CONTROL_PLANE_3_ID

Once the nodes are booted and waiting in maintenance mode, the machine configuration can be applied to each one in turn.

talosctl --talosconfig talosconfig apply-config --insecure --nodes $CONTROL_PLANE_1_ADDRESS --file controlplane.yaml
talosctl --talosconfig talosconfig apply-config --insecure --nodes $CONTROL_PLANE_2_ADDRESS --file controlplane.yaml
talosctl --talosconfig talosconfig apply-config --insecure --nodes $CONTROL_PLANE_3_ADDRESS --file controlplane.yaml

Create the Worker Nodes

Now worker nodes can be created and configured in a similar way to the control plane nodes, the difference being mainly in the machine configuration file. Note that like with the control plane nodes, the instance type (here set by --plan vc2-1-1gb) should be changed for the actual cluster requirements.

for id in $(seq 1); do
    vultr-cli instance create \
        --plan vc2-1c-1gb \
        --region $REGION \
        --iso $TALOS_ISO_ID \
        --host talos-k8s-worker${id} \
        --label "Talos Kubernetes Worker" \
        --tags talos,kubernetes,worker
done

Once the worker is booted and in maintenance mode, the machine configuration can be applied in the following manner.

talosctl --talosconfig talosconfig apply-config --insecure --nodes $WORKER_1_ADDRESS --file worker.yaml

Bootstrap etcd

Once all the cluster nodes are correctly configured, the cluster can be bootstrapped to become functional. It is important that the talosctl bootstrap command be executed only once and against only a single control plane node.

talosctl --talosconfig talosconfig boostrap --endpoints $CONTROL_PLANE_1_ADDRESS --nodes $CONTROL_PLANE_1_ADDRESS

Configure Endpoints and Nodes

While the cluster goes through the bootstrapping process and beings to self-manage, the talosconfig can be updated with the endpoints and nodes.

talosctl --talosconfig talosconfig config endpoints $CONTROL_PLANE_1_ADDRESS $CONTROL_PLANE_2_ADDRESS $CONTROL_PLANE_3_ADDRESS
talosctl --talosconfig talosconfig config nodes $CONTROL_PLANE_1_ADDRESS $CONTROL_PLANE_2_ADDRESS $CONTROL_PLANE_3_ADDRESS WORKER_1_ADDRESS

Retrieve the `kubeconfig`

Finally, with the cluster fully running, the administrative kubeconfig can be retrieved from the Talos API to be saved locally.

talosctl --talosconfig talosconfig kubeconfig .

Now the kubeconfig can be used by any of the usual Kubernetes tools to interact with the Talos-based Kubernetes cluster as normal.

2.1.4 - Local Platforms

Installation of Talos Linux on local platforms, helpful for testing and developing.

2.1.4.1 - Docker

Creating Talos Kubernetes cluster using Docker.

In this guide we will create a Kubernetes cluster in Docker, using a containerized version of Talos.

Running Talos in Docker is intended to be used in CI pipelines, and local testing when you need a quick and easy cluster. Furthermore, if you are running Talos in production, it provides an excellent way for developers to develop against the same version of Talos.

Requirements

The follow are requirements for running Talos in Docker:

Docker 18.03 or greater
a recent version of talosctl

Caveats

Due to the fact that Talos will be running in a container, certain APIs are not available. For example upgrade, reset, and similar APIs don’t apply in container mode. Further, when running on a Mac in docker, due to networking limitations, VIPs are not supported.

Create the Cluster

Creating a local cluster is as simple as:

talosctl cluster create --wait

Once the above finishes successfully, your talosconfig(~/.talos/config) will be configured to point to the new cluster.

Note: Startup times can take up to a minute or more before the cluster is available.

Finally, we just need to specify which nodes you want to communicate with using talosctl. Talosctl can operate on one or all the nodes in the cluster – this makes cluster wide commands much easier.

talosctl config nodes 10.5.0.2 10.5.0.3

Using the Cluster

Cleaning Up

To cleanup, run:

talosctl cluster destroy

Running Talos in Docker Manually

To run Talos in a container manually, run:

docker run --rm -it \
  --name tutorial \
  --hostname talos-cp \
  --read-only \
  --privileged \
  --security-opt seccomp=unconfined \
  --mount type=tmpfs,destination=/run \
  --mount type=tmpfs,destination=/system \
  --mount type=tmpfs,destination=/tmp \
  --mount type=volume,destination=/system/state \
  --mount type=volume,destination=/var \
  --mount type=volume,destination=/etc/cni \
  --mount type=volume,destination=/etc/kubernetes \
  --mount type=volume,destination=/usr/libexec/kubernetes \
  --mount type=volume,destination=/usr/etc/udev \
  --mount type=volume,destination=/opt \
  -e PLATFORM=container \
  ghcr.io/siderolabs/talos:v1.4.8

2.1.4.2 - QEMU

Creating Talos Kubernetes cluster using QEMU VMs.

In this guide we will create a Kubernetes cluster using QEMU.

Video Walkthrough

To see a live demo of this writeup, see the video below:

Requirements

Linux
a kernel with
- KVM enabled (/dev/kvm must exist)
- CONFIG_NET_SCH_NETEM enabled
- CONFIG_NET_SCH_INGRESS enabled
at least CAP_SYS_ADMIN and CAP_NET_ADMIN capabilities
QEMU
bridge, static and firewall CNI plugins from the standard CNI plugins, and tc-redirect-tap CNI plugin from the awslabs tc-redirect-tap installed to /opt/cni/bin (installed automatically by talosctl)
iptables
/var/run/netns directory should exist

Installation

How to get QEMU

Install QEMU with your operating system package manager. For example, on Ubuntu for x86:

apt install qemu-system-x86 qemu-kvm

Install talosctl

Download talosctl via

curl -sL https://talos.dev/install | sh

Install Talos kernel and initramfs

QEMU provisioner depends on Talos kernel (vmlinuz) and initramfs (initramfs.xz). These files can be downloaded from the Talos release:

mkdir -p _out/
curl https://github.com/siderolabs/talos/releases/download/<version>/vmlinuz-<arch> -L -o _out/vmlinuz-<arch>
curl https://github.com/siderolabs/talos/releases/download/<version>/initramfs-<arch>.xz -L -o _out/initramfs-<arch>.xz

For example version v1.4.8:

curl https://github.com/siderolabs/talos/releases/download/v1.4.8/vmlinuz-amd64 -L -o _out/vmlinuz-amd64
curl https://github.com/siderolabs/talos/releases/download/v1.4.8/initramfs-amd64.xz -L -o _out/initramfs-amd64.xz

Create the Cluster

For the first time, create root state directory as your user so that you can inspect the logs as non-root user:

mkdir -p ~/.talos/clusters

Create the cluster:

sudo --preserve-env=HOME talosctl cluster create --provisioner qemu

Before the first cluster is created, talosctl will download the CNI bundle for the VM provisioning and install it to ~/.talos/cni directory.

Once the above finishes successfully, your talosconfig (~/.talos/config) will be configured to point to the new cluster, and kubeconfig will be downloaded and merged into default kubectl config location (~/.kube/config).

Cluster provisioning process can be optimized with registry pull-through caches.

Using the Cluster

Once the cluster is available, you can make use of talosctl and kubectl to interact with the cluster. For example, to view current running containers, run talosctl -n 10.5.0.2 containers for a list of containers in the system namespace, or talosctl -n 10.5.0.2 containers -k for the k8s.io namespace. To view the logs of a container, use talosctl -n 10.5.0.2 logs <container> or talosctl -n 10.5.0.2 logs -k <container>.

A bridge interface will be created, and assigned the default IP 10.5.0.1. Each node will be directly accessible on the subnet specified at cluster creation time. A loadbalancer runs on 10.5.0.1 by default, which handles loadbalancing for the Kubernetes APIs.

You can see a summary of the cluster state by running:

$ talosctl cluster show --provisioner qemu
PROVISIONER       qemu
NAME              talos-default
NETWORK NAME      talos-default
NETWORK CIDR      10.5.0.0/24
NETWORK GATEWAY   10.5.0.1
NETWORK MTU       1500

NODES:

NAME                           TYPE           IP         CPU    RAM      DISK
talos-default-controlplane-1   ControlPlane   10.5.0.2   1.00   1.6 GB   4.3 GB
talos-default-controlplane-2   ControlPlane   10.5.0.3   1.00   1.6 GB   4.3 GB
talos-default-controlplane-3   ControlPlane   10.5.0.4   1.00   1.6 GB   4.3 GB
talos-default-worker-1         Worker         10.5.0.5   1.00   1.6 GB   4.3 GB

Cleaning Up

To cleanup, run:

sudo --preserve-env=HOME talosctl cluster destroy --provisioner qemu

Note: In that case that the host machine is rebooted before destroying the cluster, you may need to manually remove ~/.talos/clusters/talos-default.

Manual Clean Up

The talosctl cluster destroy command depends heavily on the clusters state directory. It contains all related information of the cluster. The PIDs and network associated with the cluster nodes.

If you happened to have deleted the state folder by mistake or you would like to cleanup the environment, here are the steps how to do it manually:

Remove VM Launchers

Find the process of talosctl qemu-launch:

ps -elf | grep 'talosctl qemu-launch'

To remove the VMs manually, execute:

sudo kill -s SIGTERM <PID>

Example output, where VMs are running with PIDs 157615 and 157617

ps -elf | grep '[t]alosctl qemu-launch'
0 S root      157615    2835  0  80   0 - 184934 -     07:53 ?        00:00:00 talosctl qemu-launch
0 S root      157617    2835  0  80   0 - 185062 -     07:53 ?        00:00:00 talosctl qemu-launch
sudo kill -s SIGTERM 157615
sudo kill -s SIGTERM 157617

Stopping VMs

Find the process of qemu-system:

ps -elf | grep 'qemu-system'

To stop the VMs manually, execute:

sudo kill -s SIGTERM <PID>

Example output, where VMs are running with PIDs 158065 and 158216

ps -elf | grep qemu-system
2 S root     1061663 1061168 26  80   0 - 1786238 -    14:05 ?        01:53:56 qemu-system-x86_64 -m 2048 -drive format=raw,if=virtio,file=/home/username/.talos/clusters/talos-default/bootstrap-master.disk -smp cpus=2 -cpu max -nographic -netdev tap,id=net0,ifname=tap0,script=no,downscript=no -device virtio-net-pci,netdev=net0,mac=1e:86:c6:b4:7c:c4 -device virtio-rng-pci -no-reboot -boot order=cn,reboot-timeout=5000 -smbios type=1,uuid=7ec0a73c-826e-4eeb-afd1-39ff9f9160ca -machine q35,accel=kvm
2 S root     1061663 1061170 67  80   0 - 621014 -     21:23 ?        00:00:07 qemu-system-x86_64 -m 2048 -drive format=raw,if=virtio,file=/homeusername/.talos/clusters/talos-default/pxe-1.disk -smp cpus=2 -cpu max -nographic -netdev tap,id=net0,ifname=tap0,script=no,downscript=no -device virtio-net-pci,netdev=net0,mac=36:f3:2f:c3:9f:06 -device virtio-rng-pci -no-reboot -boot order=cn,reboot-timeout=5000 -smbios type=1,uuid=ce12a0d0-29c8-490f-b935-f6073ab916a6 -machine q35,accel=kvm
sudo kill -s SIGTERM 1061663
sudo kill -s SIGTERM 1061663

Remove load balancer

Find the process of talosctl loadbalancer-launch:

ps -elf | grep 'talosctl loadbalancer-launch'

To remove the LB manually, execute:

sudo kill -s SIGTERM <PID>

Example output, where loadbalancer is running with PID 157609

ps -elf | grep '[t]alosctl loadbalancer-launch'
4 S root      157609    2835  0  80   0 - 184998 -     07:53 ?        00:00:07 talosctl loadbalancer-launch --loadbalancer-addr 10.5.0.1 --loadbalancer-upstreams 10.5.0.2
sudo kill -s SIGTERM 157609

Remove DHCP server

Find the process of talosctl dhcpd-launch:

ps -elf | grep 'talosctl dhcpd-launch'

To remove the LB manually, execute:

sudo kill -s SIGTERM <PID>

Example output, where loadbalancer is running with PID 157609

ps -elf | grep '[t]alosctl dhcpd-launch'
4 S root      157609    2835  0  80   0 - 184998 -     07:53 ?        00:00:07 talosctl dhcpd-launch --state-path /home/username/.talos/clusters/talos-default --addr 10.5.0.1 --interface talosbd9c32bc
sudo kill -s SIGTERM 157609

Remove network

This is more tricky part as if you have already deleted the state folder. If you didn’t then it is written in the state.yaml in the ~/.talos/clusters/<cluster-name> directory.

sudo cat ~/.talos/clusters/<cluster-name>/state.yaml | grep bridgename
bridgename: talos<uuid>

If you only had one cluster, then it will be the interface with name talos<uuid>

46: talos<uuid>: <NO-CARRIER,BROADCAST,MULTICAST,UP> mtu 1500 qdisc noqueue state DOWN group default qlen 1000
    link/ether a6:72:f4:0a:d3:9c brd ff:ff:ff:ff:ff:ff
    inet 10.5.0.1/24 brd 10.5.0.255 scope global talos17c13299
       valid_lft forever preferred_lft forever
    inet6 fe80::a472:f4ff:fe0a:d39c/64 scope link
       valid_lft forever preferred_lft forever

To remove this interface:

sudo ip link del talos<uuid>

Remove state directory

To remove the state directory execute:

sudo rm -Rf /home/$USER/.talos/clusters/<cluster-name>

Troubleshooting

Logs

Inspect logs directory

sudo cat ~/.talos/clusters/<cluster-name>/*.log

Logs are saved under <cluster-name>-<role>-<node-id>.log

For example in case of k8s cluster name:

ls -la ~/.talos/clusters/k8s | grep log
-rw-r--r--. 1 root root      69415 Apr 26 20:58 k8s-master-1.log
-rw-r--r--. 1 root root      68345 Apr 26 20:58 k8s-worker-1.log
-rw-r--r--. 1 root root      24621 Apr 26 20:59 lb.log

Inspect logs during the installation

tail -f ~/.talos/clusters/<cluster-name>/*.log

2.1.4.3 - VirtualBox

Creating Talos Kubernetes cluster using VurtualBox VMs.

In this guide we will create a Kubernetes cluster using VirtualBox.

Video Walkthrough

To see a live demo of this writeup, visit Youtube here:

Installation

How to Get VirtualBox

Install VirtualBox with your operating system package manager or from the website. For example, on Ubuntu for x86:

apt install virtualbox

Install talosctl

You can download talosctl via

curl -sL https://talos.dev/install | sh

Download ISO Image

Download the ISO image from the Talos release page. You can download talos-amd64.iso via github.com/siderolabs/talos/releases

mkdir -p _out/
curl https://github.com/siderolabs/talos/releases/download/<version>/talos-<arch>.iso -L -o _out/talos-<arch>.iso

For example version v1.4.8 for linux platform:

mkdir -p _out/
curl https://github.com/siderolabs/talos/releases/download/v1.4.8/talos-amd64.iso -L -o _out/talos-amd64.iso

Create VMs

Start by creating a new VM by clicking the “New” button in the VirtualBox UI:

Supply a name for this VM, and specify the Type and Version:

Edit the memory to supply at least 2GB of RAM for the VM:

Proceed through the disk settings, keeping the defaults. You can increase the disk space if desired.

Once created, select the VM and hit “Settings”:

In the “System” section, supply at least 2 CPUs:

In the “Network” section, switch the network “Attached To” section to “Bridged Adapter”:

Finally, in the “Storage” section, select the optical drive and, on the right, select the ISO by browsing your filesystem:

Repeat this process for a second VM to use as a worker node. You can also repeat this for additional nodes desired.

Start Control Plane Node

Once the VMs have been created and updated, start the VM that will be the first control plane node. This VM will boot the ISO image specified earlier and enter “maintenance mode”. Once the machine has entered maintenance mode, there will be a console log that details the IP address that the node received. Take note of this IP address, which will be referred to as $CONTROL_PLANE_IP for the rest of this guide. If you wish to export this IP as a bash variable, simply issue a command like export CONTROL_PLANE_IP=1.2.3.4.

Generate Machine Configurations

talosctl gen config talos-vbox-cluster https://$CONTROL_PLANE_IP:6443 --output-dir _out

This will create several files in the _out directory: controlplane.yaml, worker.yaml, and talosconfig.

Create Control Plane Node

Using the controlplane.yaml generated above, you can now apply this config using talosctl. Issue:

talosctl apply-config --insecure --nodes $CONTROL_PLANE_IP --file _out/controlplane.yaml

You should now see some action in the VirtualBox console for this VM. Talos will be installed to disk, the VM will reboot, and then Talos will configure the Kubernetes control plane on this VM.

Note: This process can be repeated multiple times to create an HA control plane.

Create Worker Node

Issue:

talosctl apply-config --insecure --nodes $WORKER_IP --file _out/worker.yaml

Note: This process can be repeated multiple times to add additional workers.

Using the Cluster

First, configure talosctl to talk to your control plane node by issuing the following, updating paths and IPs as necessary:

export TALOSCONFIG="_out/talosconfig"
talosctl config endpoint $CONTROL_PLANE_IP
talosctl config node $CONTROL_PLANE_IP

Bootstrap Etcd

Set the endpoints and nodes:

talosctl --talosconfig $TALOSCONFIG config endpoint <control plane 1 IP>
talosctl --talosconfig $TALOSCONFIG config node <control plane 1 IP>

Bootstrap etcd:

talosctl --talosconfig $TALOSCONFIG bootstrap

Retrieve the `kubeconfig`

At this point we can retrieve the admin kubeconfig by running:

talosctl --talosconfig $TALOSCONFIG kubeconfig .

You can then use kubectl in this fashion:

kubectl get nodes

Cleaning Up

To cleanup, simply stop and delete the virtual machines from the VirtualBox UI.

2.1.5 - Single Board Computers

Installation of Talos Linux on single-board computers.

2.1.5.1 - Banana Pi M64

Installing Talos on Banana Pi M64 SBC using raw disk image.

Prerequisites

You will need

talosctl
an SD card

Download the latest talosctl.

curl -Lo /usr/local/bin/talosctl https://github.com/siderolabs/talos/releases/download/v1.4.8/talosctl-$(uname -s | tr "[:upper:]" "[:lower:]")-amd64
chmod +x /usr/local/bin/talosctl

Download the Image

Download the image and decompress it:

curl -LO https://github.com/siderolabs/talos/releases/download/v1.4.8/metal-bananapi_m64-arm64.img.xz
xz -d metal-bananapi_m64-arm64.img.xz

Writing the Image

The path to your SD card can be found using fdisk on Linux or diskutil on macOS. In this example, we will assume /dev/mmcblk0.

Now dd the image to your SD card:

sudo dd if=metal-bananapi_m64-arm64.img of=/dev/mmcblk0 conv=fsync bs=4M

Bootstrapping the Node

Insert the SD card to your board, turn it on and wait for the console to show you the instructions for bootstrapping the node. Following the instructions in the console output to connect to the interactive installer:

talosctl apply-config --insecure --mode=interactive --nodes <node IP or DNS name>

Once the interactive installation is applied, the cluster will form and you can then use kubectl.

Retrieve the `kubeconfig`

Retrieve the admin kubeconfig by running:

talosctl kubeconfig

2.1.5.2 - Friendlyelec Nano PI R4S

Installing Talos on a Nano PI R4S SBC using raw disk image.

Prerequisites

You will need

talosctl
an SD card

Download the latest talosctl.

curl -Lo /usr/local/bin/talosctl https://github.com/siderolabs/talos/releases/download/v1.4.8/talosctl-$(uname -s | tr "[:upper:]" "[:lower:]")-amd64
chmod +x /usr/local/bin/talosctl

Download the Image

Download the image and decompress it:

curl -LO https://github.com/siderolabs/talos/releases/download/v1.4.8/metal-rockpi_4-arm64.img.xz
xz -d metal-nanopi_r4s-arm64.img.xz

Writing the Image

The path to your SD card can be found using fdisk on Linux or diskutil on macOS. In this example, we will assume /dev/mmcblk0.

Now dd the image to your SD card:

sudo dd if=metal-nanopi_r4s-arm64.img of=/dev/mmcblk0 conv=fsync bs=4M

Bootstrapping the Node

talosctl apply-config --insecure --mode=interactive --nodes <node IP or DNS name>

Once the interactive installation is applied, the cluster will form and you can then use kubectl.

Retrieve the `kubeconfig`

Retrieve the admin kubeconfig by running:

talosctl kubeconfig

2.1.5.3 - Jetson Nano

Installing Talos on Jetson Nano SBC using raw disk image.

Prerequisites

You will need

talosctl
an SD card/USB drive
crane CLI

Download the latest talosctl.

curl -Lo /usr/local/bin/talosctl https://github.com/siderolabs/talos/releases/download/v1.4.8/talosctl-$(uname -s | tr "[:upper:]" "[:lower:]")-amd64
chmod +x /usr/local/bin/talosctl

Flashing the firmware to on-board SPI flash

Flashing the firmware only needs to be done once.

We will use the R32.7.2 release for the Jetson Nano. Most of the instructions is similar to this doc except that we’d be using a upstream version of u-boot with patches from NVIDIA u-boot so that USB boot also works.

Before flashing we need the following:

A USB-A to micro USB cable
A jumper wire to enable recovery mode
A HDMI monitor to view the logs if the USB serial adapter is not available
A USB to Serial adapter with 3.3V TTL (optional)
A 5V DC barrel jack

If you’re planning to use the serial console follow the documentation here

First start by downloading the Jetson Nano L4T release.

curl -SLO https://developer.nvidia.com/embedded/l4t/r32_release_v7.1/t210/jetson-210_linux_r32.7.2_aarch64.tbz2

Next we will extract the L4T release and replace the u-boot binary with the patched version.

tar xf jetson-210_linux_r32.6.1_aarch64.tbz2
cd Linux_for_Tegra
crane --platform=linux/arm64 export ghcr.io/siderolabs/u-boot:v1.3.0-alpha.0-25-g0ac7773 - | tar xf - --strip-components=1 -C bootloader/t210ref/p3450-0000/ jetson_nano/u-boot.bin

Next we will flash the firmware to the Jetson Nano SPI flash. In order to do that we need to put the Jetson Nano into Force Recovery Mode (FRC). We will use the instructions from here

Ensure that the Jetson Nano is powered off. There is no need for the SD card/USB storage/network cable to be connected
Connect the micro USB cable to the micro USB port on the Jetson Nano, don’t plug the other end to the PC yet
Enable Force Recovery Mode (FRC) by placing a jumper across the FRC pins on the Jetson Nano
- For board revision A02, these are pins 3 and 4 of header J40
- For board revision B01, these are pins 9 and 10 of header J50
Place another jumper across J48 to enable power from the DC jack and connect the Jetson Nano to the DC jack J25
Now connect the other end of the micro USB cable to the PC and remove the jumper wire from the FRC pins

Now the Jetson Nano is in Force Recovery Mode (FRC) and can be confirmed by running the following command

lsusb | grep -i "nvidia"

Now we can move on the flashing the firmware.

sudo ./flash p3448-0000-max-spi external

This will flash the firmware to the Jetson Nano SPI flash and you’ll see a lot of output. If you’ve connected the serial console you’ll also see the progress there. Once the flashing is done you can disconnect the USB cable and power off the Jetson Nano.

Download the Image

Download the image and decompress it:

curl -LO https://github.com/siderolabs/talos/releases/download/v1.4.8/metal-jetson_nano-arm64.img.xz
xz -d metal-jetson_nano-arm64.img.xz

Writing the Image

Now dd the image to your SD card/USB storage:

sudo dd if=metal-jetson_nano-arm64.img of=/dev/mmcblk0 conv=fsync bs=4M status=progress

| Replace /dev/mmcblk0 with the name of your SD card/USB storage.

Bootstrapping the Node

Insert the SD card/USB storage to your board, turn it on and wait for the console to show you the instructions for bootstrapping the node. Following the instructions in the console output to connect to the interactive installer:

talosctl apply-config --insecure --mode=interactive --nodes <node IP or DNS name>

Once the interactive installation is applied, the cluster will form and you can then use kubectl.

Retrieve the `kubeconfig`

Retrieve the admin kubeconfig by running:

talosctl kubeconfig

2.1.5.4 - Libre Computer Board ALL-H3-CC

Installing Talos on Libre Computer Board ALL-H3-CC SBC using raw disk image.

Prerequisites

You will need

talosctl
an SD card

Download the latest talosctl.

curl -Lo /usr/local/bin/talosctl https://github.com/siderolabs/talos/releases/download/v1.4.8/talosctl-$(uname -s | tr "[:upper:]" "[:lower:]")-amd64
chmod +x /usr/local/bin/talosctl

Download the Image

Download the image and decompress it:

curl -LO https://github.com/siderolabs/talos/releases/download/v1.4.8/metal-libretech_all_h3_cc_h5-arm64.img.xz
xz -d metal-libretech_all_h3_cc_h5-arm64.img.xz

Writing the Image

The path to your SD card can be found using fdisk on Linux or diskutil on macOS. In this example, we will assume /dev/mmcblk0.

Now dd the image to your SD card:

sudo dd if=metal-libretech_all_h3_cc_h5-arm64.img of=/dev/mmcblk0 conv=fsync bs=4M

Bootstrapping the Node

talosctl apply-config --insecure --mode=interactive --nodes <node IP or DNS name>

Once the interactive installation is applied, the cluster will form and you can then use kubectl.

Retrieve the `kubeconfig`

Retrieve the admin kubeconfig by running:

talosctl kubeconfig

2.1.5.5 - Pine64

Installing Talos on a Pine64 SBC using raw disk image.

Prerequisites

You will need

talosctl
an SD card

Download the latest talosctl.

curl -Lo /usr/local/bin/talosctl https://github.com/siderolabs/talos/releases/download/v1.4.8/talosctl-$(uname -s | tr "[:upper:]" "[:lower:]")-amd64
chmod +x /usr/local/bin/talosctl

Download the Image

Download the image and decompress it:

curl -LO https://github.com/siderolabs/talos/releases/download/v1.4.8/metal-pine64-arm64.img.xz
xz -d metal-pine64-arm64.img.xz

Writing the Image

The path to your SD card can be found using fdisk on Linux or diskutil on macOS. In this example, we will assume /dev/mmcblk0.

Now dd the image to your SD card:

sudo dd if=metal-pine64-arm64.img of=/dev/mmcblk0 conv=fsync bs=4M

Bootstrapping the Node

talosctl apply-config --insecure --mode=interactive --nodes <node IP or DNS name>

Once the interactive installation is applied, the cluster will form and you can then use kubectl.

Retrieve the `kubeconfig`

Retrieve the admin kubeconfig by running:

talosctl kubeconfig

2.1.5.6 - Pine64 Rock64

Installing Talos on Pine64 Rock64 SBC using raw disk image.

Prerequisites

You will need

talosctl
an SD card

Download the latest talosctl.

curl -Lo /usr/local/bin/talosctl https://github.com/siderolabs/talos/releases/download/v1.4.8/talosctl-$(uname -s | tr "[:upper:]" "[:lower:]")-amd64
chmod +x /usr/local/bin/talosctl

Download the Image

Download the image and decompress it:

curl -LO https://github.com/siderolabs/talos/releases/download/v1.4.8/metal-rock64-arm64.img.xz
xz -d metal-rock64-arm64.img.xz

Writing the Image

The path to your SD card can be found using fdisk on Linux or diskutil on macOS. In this example, we will assume /dev/mmcblk0.

Now dd the image to your SD card:

sudo dd if=metal-rock64-arm64.img of=/dev/mmcblk0 conv=fsync bs=4M

Bootstrapping the Node

talosctl apply-config --insecure --mode=interactive --nodes <node IP or DNS name>

Once the interactive installation is applied, the cluster will form and you can then use kubectl.

Retrieve the `kubeconfig`

Retrieve the admin kubeconfig by running:

talosctl kubeconfig

2.1.5.7 - Radxa ROCK PI 4

Installing Talos on Radxa ROCK PI 4a/4b SBC using raw disk image.

Prerequisites

You will need

talosctl
an SD card or an eMMC or USB drive or an nVME drive

Download the latest talosctl.

curl -Lo /usr/local/bin/talosctl https://github.com/siderolabs/talos/releases/download/v1.4.8/talosctl-$(uname -s | tr "[:upper:]" "[:lower:]")-amd64
chmod +x /usr/local/bin/talosctl

Download the Image

Download the image and decompress it:

curl -LO https://github.com/siderolabs/talos/releases/download/v1.4.8/metal-rockpi_4-arm64.img.xz
xz -d metal-rockpi_4-arm64.img.xz

Writing the Image

The path to your SD card/eMMC/USB/nVME can be found using fdisk on Linux or diskutil on macOS. In this example, we will assume /dev/mmcblk0.

Now dd the image to your SD card:

sudo dd if=metal-rockpi_4-arm64.img of=/dev/mmcblk0 conv=fsync bs=4M

The user has two options to proceed:

booting from a SD card or eMMC
booting from a USB or nVME (requires the RockPi board to have the SPI flash)

Booting from SD card or eMMC

Insert the SD card into the board, turn it on and proceed to bootstrapping the node.

Booting from USB or nVME

This requires the user to flash the RockPi SPI flash with u-boot.

This requires the user has access to crane CLI, a spare SD card and optionally access to the RockPi serial console.

Flash the Rock PI 4c variant of Debian to the SD card.
Boot into the debian image
Check that /dev/mtdblock0 exists otherwise the command will silently fail; e.g. lsblk.
Download u-boot image from talos u-boot:

mkdir _out
crane --platform=linux/arm64 export ghcr.io/siderolabs/u-boot:v1.3.0-alpha.0-25-g0ac7773 - | tar xf - --strip-components=1 -C _out rockpi_4/rkspi_loader.img
sudo dd if=rkspi_loader.img of=/dev/mtdblock0 bs=4K

Optionally, you can also write Talos image to the SSD drive right from your Rock PI board:

curl -LO https://github.com/siderolabs/talos/releases/download/v1.4.8/metal-rockpi_4-arm64.img.xz
xz -d metal-rockpi_4-arm64.img.xz
sudo dd if=metal-rockpi_4-arm64.img.xz of=/dev/nvme0n1

remove SD card and reboot.

After these steps, Talos will boot from the nVME/USB and enter maintenance mode. Proceed to bootstrapping the node.

Bootstrapping the Node

Wait for the console to show you the instructions for bootstrapping the node. Following the instructions in the console output to connect to the interactive installer:

talosctl apply-config --insecure --mode=interactive --nodes <node IP or DNS name>

Once the interactive installation is applied, the cluster will form and you can then use kubectl.

Retrieve the `kubeconfig`

Retrieve the admin kubeconfig by running:

talosctl kubeconfig

2.1.5.8 - Radxa ROCK PI 4C

Installing Talos on Radxa ROCK PI 4c SBC using raw disk image.

Prerequisites

You will need

talosctl
an SD card or an eMMC or USB drive or an nVME drive

Download the latest talosctl.

curl -Lo /usr/local/bin/talosctl https://github.com/siderolabs/talos/releases/download/v1.4.8/talosctl-$(uname -s | tr "[:upper:]" "[:lower:]")-amd64
chmod +x /usr/local/bin/talosctl

Download the Image

Download the image and decompress it:

curl -LO https://github.com/siderolabs/talos/releases/download/v1.4.8/metal-rockpi_4c-arm64.img.xz
xz -d metal-rockpi_4c-arm64.img.xz

Writing the Image

The path to your SD card/eMMC/USB/nVME can be found using fdisk on Linux or diskutil on macOS. In this example, we will assume /dev/mmcblk0.

Now dd the image to your SD card:

sudo dd if=metal-rockpi_4c-arm64.img of=/dev/mmcblk0 conv=fsync bs=4M

The user has two options to proceed:

booting from a SD card or eMMC
booting from a USB or nVME (requires the RockPi board to have the SPI flash)

Booting from SD card or eMMC

Insert the SD card into the board, turn it on and proceed to bootstrapping the node.

Booting from USB or nVME

This requires the user to flash the RockPi SPI flash with u-boot.

This requires the user has access to crane CLI, a spare SD card and optionally access to the RockPi serial console.

Flash the Rock PI 4c variant of Debian to the SD card.
Boot into the debian image
Check that /dev/mtdblock0 exists otherwise the command will silently fail; e.g. lsblk.
Download u-boot image from talos u-boot:

mkdir _out
crane --platform=linux/arm64 export ghcr.io/siderolabs/u-boot:v1.3.0-alpha.0-25-g0ac7773 - | tar xf - --strip-components=1 -C _out rockpi_4c/rkspi_loader.img
sudo dd if=rkspi_loader.img of=/dev/mtdblock0 bs=4K

Optionally, you can also write Talos image to the SSD drive right from your Rock PI board:

curl -LO https://github.com/siderolabs/talos/releases/download/v1.4.8/metal-rockpi_4c-arm64.img.xz
xz -d metal-rockpi_4c-arm64.img.xz
sudo dd if=metal-rockpi_4c-arm64.img.xz of=/dev/nvme0n1

remove SD card and reboot.

After these steps, Talos will boot from the nVME/USB and enter maintenance mode. Proceed to bootstrapping the node.

Bootstrapping the Node

Wait for the console to show you the instructions for bootstrapping the node. Following the instructions in the console output to connect to the interactive installer:

talosctl apply-config --insecure --mode=interactive --nodes <node IP or DNS name>

Once the interactive installation is applied, the cluster will form and you can then use kubectl.

Retrieve the `kubeconfig`

Retrieve the admin kubeconfig by running:

talosctl kubeconfig

2.1.5.9 - Raspberry Pi 4 Model B

Installing Talos on Rpi4 SBC using raw disk image.

The Raspberry Pi specific image is now deprecated and Talos will continue to use a generic image for the various Raspberry Pi models as supported by u-boot rpi_arm64_defconfig. Refer to the generic docs available here

Video Walkthrough

To see a live demo of this writeup, see the video below:

Prerequisites

You will need

talosctl
an SD card

Download the latest talosctl.

curl -Lo /usr/local/bin/talosctl https://github.com/siderolabs/talos/releases/download/v1.4.8/talosctl-$(uname -s | tr "[:upper:]" "[:lower:]")-amd64
chmod +x /usr/local/bin/talosctl

Updating the EEPROM

At least version v2020.09.03-138a1 of the bootloader (rpi-eeprom) is required. To update the bootloader we will need an SD card. Insert the SD card into your computer and use Raspberry Pi Imager to install the bootloader on it (select Operating System > Misc utility images > Bootloader > SD Card Boot). Alternatively, you can use the console on Linux or macOS. The path to your SD card can be found using fdisk on Linux or diskutil on macOS. In this example, we will assume /dev/mmcblk0.

curl -Lo rpi-boot-eeprom-recovery.zip https://github.com/raspberrypi/rpi-eeprom/releases/download/v2021.04.29-138a1/rpi-boot-eeprom-recovery-2021-04-29-vl805-000138a1.zip
sudo mkfs.fat -I /dev/mmcblk0
sudo mount /dev/mmcblk0p1 /mnt
sudo bsdtar rpi-boot-eeprom-recovery.zip -C /mnt

Remove the SD card from your local machine and insert it into the Raspberry Pi. Power the Raspberry Pi on, and wait at least 10 seconds. If successful, the green LED light will blink rapidly (forever), otherwise an error pattern will be displayed. If an HDMI display is attached to the port closest to the power/USB-C port, the screen will display green for success or red if a failure occurs. Power off the Raspberry Pi and remove the SD card from it.

Note: Updating the bootloader only needs to be done once.

Download the Image

Download the image and decompress it:

curl -LO https://github.com/siderolabs/talos/releases/download/v1.4.8/metal-rpi_4-arm64.img.xz
xz -d metal-rpi_4-arm64.img.xz

Writing the Image

Now dd the image to your SD card:

sudo dd if=metal-rpi_4-arm64.img of=/dev/mmcblk0 conv=fsync bs=4M

Bootstrapping the Node

talosctl apply-config --insecure --mode=interactive --nodes <node IP or DNS name>

Once the interactive installation is applied, the cluster will form and you can then use kubectl.

Note: if you have an HDMI display attached and it shows only a rainbow splash, please use the other HDMI port, the one closest to the power/USB-C port.

Retrieve the `kubeconfig`

Retrieve the admin kubeconfig by running:

talosctl kubeconfig

Troubleshooting

The following table can be used to troubleshoot booting issues:

Long Flashes	Short Flashes	Status
0	3	Generic failure to boot
0	4	start*.elf not found
0	7	Kernel image not found
0	8	SDRAM failure
0	9	Insufficient SDRAM
0	10	In HALT state
2	1	Partition not FAT
2	2	Failed to read from partition
2	3	Extended partition not FAT
2	4	File signature/hash mismatch - Pi 4
4	4	Unsupported board type
4	5	Fatal firmware error
4	6	Power failure type A
4	7	Power failure type B

2.1.5.10 - Raspberry Pi Series

Installing Talos on Raspberry Pi SBC’s using raw disk image.

Talos disk image for the Raspberry Pi generic should in theory work for the boards supported by u-boot rpi_arm64_defconfig. This has only been officialy tested on the Raspberry Pi 4 and community tested on one variant of the Compute Module 4 using Super 6C boards. If you have tested this on other Raspberry Pi boards, please let us know.

Video Walkthrough

To see a live demo of this writeup, see the video below:

Prerequisites

You will need

talosctl
an SD card

Download the latest talosctl.

curl -sL 'https://www.talos.dev/install' | bash

Updating the EEPROM

Use Raspberry Pi Imager to write an EEPROM update image to a spare SD card. Select Misc utility images under the Operating System tab.

Note: Updating the bootloader only needs to be done once.

Download the Image

Download the image and decompress it:

curl -LO https://github.com/siderolabs/talos/releases/download/v1.4.8/metal-rpi_generic-arm64.img.xz
xz -d metal-rpi_generic-arm64.img.xz

Writing the Image

Now dd the image to your SD card:

sudo dd if=metal-rpi_generic-arm64.img of=/dev/mmcblk0 conv=fsync bs=4M

Bootstrapping the Node

talosctl apply-config --insecure --mode=interactive --nodes <node IP or DNS name>

Once the interactive installation is applied, the cluster will form and you can then use kubectl.

Note: if you have an HDMI display attached and it shows only a rainbow splash, please use the other HDMI port, the one closest to the power/USB-C port.

Retrieve the `kubeconfig`

Retrieve the admin kubeconfig by running:

talosctl kubeconfig

Troubleshooting

The following table can be used to troubleshoot booting issues:

Long Flashes	Short Flashes	Status
0	3	Generic failure to boot
0	4	start*.elf not found
0	7	Kernel image not found
0	8	SDRAM failure
0	9	Insufficient SDRAM
0	10	In HALT state
2	1	Partition not FAT
2	2	Failed to read from partition
2	3	Extended partition not FAT
2	4	File signature/hash mismatch - Pi 4
4	4	Unsupported board type
4	5	Fatal firmware error
4	6	Power failure type A
4	7	Power failure type B

2.2 - Configuration

Guides on how to configure Talos Linux machines

2.2.1 - Configuration Patches

In this guide, we’ll patch the generated machine configuration.

Talos generates machine configuration for two types of machines: controlplane and worker machines. Many configuration options can be adjusted using talosctl gen config but not all of them. Configuration patching allows modifying machine configuration to fit it for the cluster or a specific machine.

Configuration Patch Formats

Talos supports two configuration patch formats:

strategic merge patches
RFC6902 (JSON patches)

Strategic merge patches are the easiest to use, but JSON patches allow more precise configuration adjustments.

Strategic Merge patches

Strategic merge patches look like incomplete machine configuration files:

machine:
  network:
    hostname: worker1

When applied to the machine configuration, the patch gets merged with the respective section of the machine configuration:

machine:
  network:
    interfaces:
      - interface: eth0
        addresses:
          - 10.0.0.2/24
    hostname: worker1

In general, machine configuration contents are merged with the contents of the strategic merge patch, with strategic merge patch values overriding machine configuration values. There are some special rules:

If the field value is a list, the patch value is appended to the list, with the following exceptions:
- values of the fields cluster.network.podSubnets and cluster.network.serviceSubnets are overwritten on merge
- network.interfaces section is merged with the value in the machine config if there is a match on interface: or deviceSelector: keys
- network.interfaces.vlans section is merged with the value in the machine config if there is a match on the vlanId: key

RFC6902 (JSON Patches)

JSON patches can be written either in JSON or YAML format. A proper JSON patch requires an op field that depends on the machine configuration contents: whether the path already exists or not.

For example, the strategic merge patch from the previous section can be written either as:

- op: replace
  path: /machine/network/hostname
  value: worker1

or:

- op: add
  path: /machine/network/hostname
  value: worker1

The correct op depends on whether the /machine/network/hostname section exists already in the machine config or not.

Examples

Machine Network

Base machine configuration:

# ...
machine:
  network:
    interfaces:
      - interface: eth0
        dhcp: false
        addresses:
          - 192.168.10.3/24

The goal is to add a virtual IP 192.168.10.50 to the eth0 interface and add another interface eth1 with DHCP enabled.

Strategic merge patch
JSON patch

machine:
  network:
    interfaces:
      - interface: eth0
        vip:
          ip: 192.168.10.50
      - interface: eth1
        dhcp: true

- op: add
  path: /machine/network/interfaces/0/vip
  value:
    ip: 192.168.10.50
- op: add
  path: /machine/network/interfaces/-
  value:
    interface: eth1
    dhcp: true

Patched machine configuration:

machine:
  network:
    interfaces:
      - interface: eth0
        dhcp: false
        addresses:
          - 192.168.10.3/24
        vip:
          ip: 192.168.10.50
      - interface: eth1
        dhcp: true

Cluster Network

Base machine configuration:

cluster:
  network:
    dnsDomain: cluster.local
    podSubnets:
      - 10.244.0.0/16
    serviceSubnets:
      - 10.96.0.0/12

The goal is to update pod and service subnets and disable default CNI (Flannel).

Strategic merge patch
JSON patch

cluster:
  network:
    podSubnets:
      - 192.168.0.0/16
    serviceSubnets:
      - 192.0.0.0/12
    cni:
      name: none

- op: replace
  path: /cluster/network/podSubnets
  value:
    - 192.168.0.0/16
- op: replace
  path: /cluster/network/serviceSubnets
  value:
    - 192.0.0.0/12
- op: add
  path: /cluster/network/cni
  value:
    name: none

Patched machine configuration:

cluster:
  network:
    dnsDomain: cluster.local
    podSubnets:
      - 192.168.0.0/16
    serviceSubnets:
      - 192.0.0.0/12
    cni:
      name: none

Kubelet

Base machine configuration:

# ...
machine:
  kubelet: {}

The goal is to set the kubelet node IP to come from the subnet 192.168.10.0/24.

Strategic merge patch
JSON patch

machine:
  kubelet:
    nodeIP:
      validSubnets:
        - 192.168.10.0/24

- op: add
  path: /machine/kubelet/nodeIP
  value:
    validSubnets:
      - 192.168.10.0/24

Patched machine configuration:

machine:
  kubelet:
    nodeIP:
      validSubnets:
        - 192.168.10.0/24

Admission Control: Pod Security Policy

Base machine configuration:

cluster:
  apiServer:
    admissionControl:
      - name: PodSecurity
        configuration:
          apiVersion: pod-security.admission.config.k8s.io/v1alpha1
          defaults:
            audit: restricted
            audit-version: latest
            enforce: baseline
            enforce-version: latest
            warn: restricted
            warn-version: latest
          exemptions:
            namespaces:
              - kube-system
            runtimeClasses: []
            usernames: []
          kind: PodSecurityConfiguration

The goal is to add an exemption for the namespace rook-ceph.

Strategic merge patch
JSON patch

cluster:
  apiServer:
    admissionControl:
      - name: PodSecurity
        configuration:
          exemptions:
            namespaces:
              - rook-ceph

- op: add
  path: /cluster/apiServer/admissionControl/0/configuration/exemptions/namespaces/-
  value: rook-ceph

Patched machine configuration:

cluster:
  apiServer:
    admissionControl:
      - name: PodSecurity
        configuration:
          apiVersion: pod-security.admission.config.k8s.io/v1alpha1
          defaults:
            audit: restricted
            audit-version: latest
            enforce: baseline
            enforce-version: latest
            warn: restricted
            warn-version: latest
          exemptions:
            namespaces:
              - kube-system
              - rook-ceph
            runtimeClasses: []
            usernames: []
          kind: PodSecurityConfiguration

Configuration Patching with `talosctl` CLI

Several talosctl commands accept config patches as command-line flags. Config patches might be passed either as an inline value or as a reference to a file with @file.patch syntax:

talosctl ... --patch '[{"op": "add", "path": "/machine/network/hostname", "value": "worker1"}]' --patch @file.patch

If multiple config patches are specified, they are applied in the order of appearance. The format of the patch (JSON patch or strategic merge patch) is detected automatically.

Talos machine configuration can be patched at the moment of generation with talosctl gen config:

talosctl gen config test-cluster https://172.20.0.1:6443 --config-patch @all.yaml --config-patch-control-plane @cp.yaml --config-patch-worker @worker.yaml

Generated machine configuration can also be patched after the fact with talosctl machineconfig patch

talosctl machineconfig patch worker.yaml --patch @patch.yaml -o worker1.yaml

Machine configuration on the running Talos node can be patched with talosctl patch:

talosctl patch mc --nodes 172.20.0.2 --patch @patch.yaml

2.2.2 - Containerd

Customize Containerd Settings

The base containerd configuration expects to merge in any additional configs present in /etc/cri/conf.d/20-customization.part.

Examples

Exposing Metrics

Patch the machine config by adding the following:

machine:
  files:
    - content: |
        [metrics]
          address = "0.0.0.0:11234"        
      path: /etc/cri/conf.d/20-customization.part
      op: create

Once the server reboots, metrics are now available:

$ curl ${IP}:11234/v1/metrics
# HELP container_blkio_io_service_bytes_recursive_bytes The blkio io service bytes recursive
# TYPE container_blkio_io_service_bytes_recursive_bytes gauge
container_blkio_io_service_bytes_recursive_bytes{container_id="0677d73196f5f4be1d408aab1c4125cf9e6c458a4bea39e590ac779709ffbe14",device="/dev/dm-0",major="253",minor="0",namespace="k8s.io",op="Async"} 0
container_blkio_io_service_bytes_recursive_bytes{container_id="0677d73196f5f4be1d408aab1c4125cf9e6c458a4bea39e590ac779709ffbe14",device="/dev/dm-0",major="253",minor="0",namespace="k8s.io",op="Discard"} 0
...
...

Pause Image

This change is often required for air-gapped environments, as containerd CRI plugin has a reference to the pause image which is used to create pods, and it can’t be controlled with Kubernetes pod definitions.

machine:
  files:
    - content: |
        [plugins]
          [plugins."io.containerd.grpc.v1.cri"]
            sandbox_image = "registry.k8s.io/pause:3.8"        
      path: /etc/cri/conf.d/20-customization.part
      op: create

Now the pause image is set to registry.k8s.io/pause:3.8:

$ talosctl containers --kubernetes
NODE         NAMESPACE   ID                                                              IMAGE                                                      PID    STATUS
172.20.0.5   k8s.io      kube-system/kube-flannel-6hfck                                  registry.k8s.io/pause:3.8                                  1773   SANDBOX_READY
172.20.0.5   k8s.io      └─ kube-system/kube-flannel-6hfck:install-cni:bc39fec3cbac      ghcr.io/siderolabs/install-cni:v1.3.0-alpha.0-2-gb155fa0   0      CONTAINER_EXITED
172.20.0.5   k8s.io      └─ kube-system/kube-flannel-6hfck:install-config:5c3989353b98   ghcr.io/siderolabs/flannel:v0.20.1                         0      CONTAINER_EXITED
172.20.0.5   k8s.io      └─ kube-system/kube-flannel-6hfck:kube-flannel:116c67b50da8     ghcr.io/siderolabs/flannel:v0.20.1                         2092   CONTAINER_RUNNING
172.20.0.5   k8s.io      kube-system/kube-proxy-xp7jq                                    registry.k8s.io/pause:3.8                                  1780   SANDBOX_READY
172.20.0.5   k8s.io      └─ kube-system/kube-proxy-xp7jq:kube-proxy:84fc77c59e17         registry.k8s.io/kube-proxy:v1.26.0-alpha.3                 1843   CONTAINER_RUNNING

2.2.3 - Custom Certificate Authorities

How to supply custom certificate authorities

Appending the Certificate Authority

Put into each machine the PEM encoded certificate:

machine:
  ...
  files:
    - content: |
        -----BEGIN CERTIFICATE-----
        ...
        -----END CERTIFICATE-----        
      permissions: 0644
      path: /etc/ssl/certs/ca-certificates
      op: append

2.2.4 - Disk Encryption

Guide on using system disk encryption

It is possible to enable encryption for system disks at the OS level. Currently, only STATE and EPHEMERAL partitions can be encrypted. STATE contains the most sensitive node data: secrets and certs. The EPHEMERAL partition may contain sensitive workload data. Data is encrypted using LUKS2, which is provided by the Linux kernel modules and cryptsetup utility. The operating system will run additional setup steps when encryption is enabled.

If the disk encryption is enabled for the STATE partition, the system will:

Save STATE encryption config as JSON in the META partition.
Before mounting the STATE partition, load encryption configs either from the machine config or from the META partition. Note that the machine config is always preferred over the META one.
Before mounting the STATE partition, format and encrypt it. This occurs only if the STATE partition is empty and has no filesystem.

If the disk encryption is enabled for the EPHEMERAL partition, the system will:

Get the encryption config from the machine config.
Before mounting the EPHEMERAL partition, encrypt and format it.

This occurs only if the EPHEMERAL partition is empty and has no filesystem.

Note: Talos Linux disk encryption is designed to guard against data being leaked or recovered from a drive that has been removed from a Talos Linux node. It uses the hardware characteristics of the machine in order to decrypt the data, so drives that have been removed, or recycled from a cloud environment or attached to a different virtual machine, will maintain their protection and encryption. It is not designed to protect against attacks where physical access to the machine, including the drive, is available.

Configuration

Disk encryption is disabled by default. To enable disk encryption you should modify the machine configuration with the following options:

machine:
  ...
  systemDiskEncryption:
    ephemeral:
      provider: luks2
      keys:
        - nodeID: {}
          slot: 0
    state:
      provider: luks2
      keys:
        - nodeID: {}
          slot: 0

Encryption Keys

Note: What the LUKS2 docs call “keys” are, in reality, a passphrase. When this passphrase is added, LUKS2 runs argon2 to create an actual key from that passphrase.

LUKS2 supports up to 32 encryption keys and it is possible to specify all of them in the machine configuration. Talos always tries to sync the keys list defined in the machine config with the actual keys defined for the LUKS2 partition. So if you update the keys list, keep at least one key that is not changed to be used for key management.

When you define a key you should specify the key kind and the slot:

machine:
  ...
  state:
    keys:
      - nodeID: {} # key kind
        slot: 1

  ephemeral:
    keys:
      - static:
          passphrase: supersecret
        slot: 0

Take a note that key order does not play any role on which key slot is used. Every key must always have a slot defined.

Encryption Key Kinds

Talos supports two kinds of keys:

nodeID which is generated using the node UUID and the partition label (note that if the node UUID is not really random it will fail the entropy check).
static which you define right in the configuration.

Note: Use static keys only if your STATE partition is encrypted and only for the EPHEMERAL partition. For the STATE partition it will be stored in the META partition, which is not encrypted.

Key Rotation

In order to completely rotate keys, it is necessary to do talosctl apply-config a couple of times, since there is a need to always maintain a single working key while changing the other keys around it.

So, for example, first add a new key:

machine:
  ...
  ephemeral:
    keys:
      - static:
          passphrase: oldkey
        slot: 0
      - static:
          passphrase: newkey
        slot: 1
  ...

Run:

talosctl apply-config -n <node> -f config.yaml

Then remove the old key:

machine:
  ...
  ephemeral:
    keys:
      - static:
          passphrase: newkey
        slot: 1
  ...

Run:

talosctl apply-config -n <node> -f config.yaml

Going from Unencrypted to Encrypted and Vice Versa

Ephemeral Partition

There is no in-place encryption support for the partitions right now, so to avoid losing data only empty partitions can be encrypted.

As such, migration from unencrypted to encrypted needs some additional handling, especially around explicitly wiping partitions.

apply-config should be called with --mode=staged.
Partition should be wiped after apply-config, but before the reboot.

Edit your machine config and add the encryption configuration:

vim config.yaml

Apply the configuration with --mode=staged:

talosctl apply-config -f config.yaml -n <node ip> --mode=staged

Wipe the partition you’re going to encrypt:

talosctl reset --system-labels-to-wipe EPHEMERAL -n <node ip> --reboot=true

That’s it! After you run the last command, the partition will be wiped and the node will reboot. During the next boot the system will encrypt the partition.

State Partition

Calling wipe against the STATE partition will make the node lose the config, so the previous flow is not going to work.

The flow should be to first wipe the STATE partition:

talosctl reset  --system-labels-to-wipe STATE -n <node ip> --reboot=true

Node will enter into maintenance mode, then run apply-config with --insecure flag:

talosctl apply-config --insecure -n <node ip> -f config.yaml

After installation is complete the node should encrypt the STATE partition.

2.2.5 - Editing Machine Configuration

How to edit and patch Talos machine configuration, with reboot, immediately, or stage update on reboot.

Talos node state is fully defined by machine configuration. Initial configuration is delivered to the node at bootstrap time, but configuration can be updated while the node is running.

Note: Be sure that config is persisted so that configuration updates are not overwritten on reboots. Configuration persistence was enabled by default since Talos 0.5 (persist: true in machine configuration).

There are three talosctl commands which facilitate machine configuration updates:

talosctl apply-config to apply configuration from the file
talosctl edit machineconfig to launch an editor with existing node configuration, make changes and apply configuration back
talosctl patch machineconfig to apply automated machine configuration via JSON patch

Each of these commands can operate in one of four modes:

apply change in automatic mode(default): reboot if the change can’t be applied without a reboot, otherwise apply the change immediately
apply change with a reboot (--mode=reboot): update configuration, reboot Talos node to apply configuration change
apply change immediately (--mode=no-reboot flag): change is applied immediately without a reboot, fails if the change contains any fields that can not be updated without a reboot
apply change on next reboot (--mode=staged): change is staged to be applied after a reboot, but node is not rebooted
apply change in the interactive mode (--mode=interactive; only for talosctl apply-config): launches TUI based interactive installer

Note: applying change on next reboot (--mode=staged) doesn’t modify current node configuration, so next call to talosctl edit machineconfig --mode=staged will not see changes

Additionally, there is also talosctl get machineconfig, which retrieves the current node configuration API resource and contains the machine configuration in the .spec field. It can be used to modify the configuration locally before being applied to the node.

The list of config changes allowed to be applied immediately in Talos v1.4.8:

.debug
.cluster
.machine.time
.machine.certCANs
.machine.install (configuration is only applied during install/upgrade)
.machine.network
.machine.nodeLabels
.machine.sysfs
.machine.sysctls
.machine.logging
.machine.controlplane
.machine.kubelet
.machine.pods
.machine.kernel
.machine.registries (CRI containerd plugin will not pick up the registry authentication settings without a reboot)
.machine.features.kubernetesTalosAPIAccess

`talosctl apply-config`

This command is traditionally used to submit initial machine configuration generated by talosctl gen config to the node.

It can also be used to apply configuration to running nodes. The initial YAML for this is typically obtained using talosctl get machineconfig -o yaml | yq eval .spec >machs.yaml. (We must use yq because for historical reasons, get returns the configuration as a full resource, while apply-config only accepts the raw machine config directly.)

Example:

talosctl -n <IP> apply-config -f config.yaml

Command apply-config can also be invoked as apply machineconfig:

talosctl -n <IP> apply machineconfig -f config.yaml

Applying machine configuration immediately (without a reboot):

talosctl -n IP apply machineconfig -f config.yaml --mode=no-reboot

Starting the interactive installer:

talosctl -n IP apply machineconfig --mode=interactive

Note: when a Talos node is running in the maintenance mode it’s necessary to provide --insecure (-i) flag to connect to the API and apply the config.

`taloctl edit machineconfig`

Command talosctl edit loads current machine configuration from the node and launches configured editor to modify the config. If config hasn’t been changed in the editor (or if updated config is empty), update is not applied.

Note: Talos uses environment variables TALOS_EDITOR, EDITOR to pick up the editor preference. If environment variables are missing, vi editor is used by default.

Example:

talosctl -n <IP> edit machineconfig

Configuration can be edited for multiple nodes if multiple IP addresses are specified:

talosctl -n <IP1>,<IP2>,... edit machineconfig

Applying machine configuration change immediately (without a reboot):

talosctl -n <IP> edit machineconfig --mode=no-reboot

`talosctl patch machineconfig`

Command talosctl patch works similar to talosctl edit command - it loads current machine configuration, but instead of launching configured editor it applies a set of JSON patches to the configuration and writes the result back to the node.

Example, updating kubelet version (in auto mode):

$ talosctl -n <IP> patch machineconfig -p '[{"op": "replace", "path": "/machine/kubelet/image", "value": "ghcr.io/siderolabs/kubelet:v1.27.4"}]'
patched mc at the node <IP>

Updating kube-apiserver version in immediate mode (without a reboot):

$ talosctl -n <IP> patch machineconfig --mode=no-reboot -p '[{"op": "replace", "path": "/cluster/apiServer/image", "value": "registry.k8s.io/kube-apiserver:v1.27.4"}]'
patched mc at the node <IP>

A patch might be applied to multiple nodes when multiple IPs are specified:

talosctl -n <IP1>,<IP2>,... patch machineconfig -p '[{...}]'

Patches can also be sourced from files using @file syntax:

talosctl -n <IP> patch machineconfig -p @kubelet-patch.json -p @manifest-patch.json

It might be easier to store patches in YAML format vs. the default JSON format. Talos can detect file format automatically:

# kubelet-patch.yaml
- op: replace
  path: /machine/kubelet/image
  value: ghcr.io/siderolabs/kubelet:v1.27.4

talosctl -n <IP> patch machineconfig -p @kubelet-patch.yaml

Recovering from Node Boot Failures

If a Talos node fails to boot because of wrong configuration (for example, control plane endpoint is incorrect), configuration can be updated to fix the issue.

2.2.6 - Logging

Dealing with Talos Linux logs.

Viewing logs

Kernel messages can be retrieved with talosctl dmesg command:

$ talosctl -n 172.20.1.2 dmesg

172.20.1.2: kern:    info: [2021-11-10T10:09:37.662764956Z]: Command line: init_on_alloc=1 slab_nomerge pti=on consoleblank=0 nvme_core.io_timeout=4294967295 printk.devkmsg=on ima_template=ima-ng ima_appraise=fix ima_hash=sha512 console=ttyS0 reboot=k panic=1 talos.shutdown=halt talos.platform=metal talos.config=http://172.20.1.1:40101/config.yaml
[...]

Service logs can be retrieved with talosctl logs command:

$ talosctl -n 172.20.1.2 services

NODE         SERVICE      STATE     HEALTH   LAST CHANGE   LAST EVENT
172.20.1.2   apid         Running   OK       19m27s ago    Health check successful
172.20.1.2   containerd   Running   OK       19m29s ago    Health check successful
172.20.1.2   cri          Running   OK       19m27s ago    Health check successful
172.20.1.2   etcd         Running   OK       19m22s ago    Health check successful
172.20.1.2   kubelet      Running   OK       19m20s ago    Health check successful
172.20.1.2   machined     Running   ?        19m30s ago    Service started as goroutine
172.20.1.2   trustd       Running   OK       19m27s ago    Health check successful
172.20.1.2   udevd        Running   OK       19m28s ago    Health check successful

$ talosctl -n 172.20.1.2 logs machined

172.20.1.2: [talos] task setupLogger (1/1): done, 106.109µs
172.20.1.2: [talos] phase logger (1/7): done, 564.476µs
[...]

Container logs for Kubernetes pods can be retrieved with talosctl logs -k command:

$ talosctl -n 172.20.1.2 containers -k
NODE         NAMESPACE   ID                                                              IMAGE                                                         PID    STATUS
172.20.1.2   k8s.io      kube-system/kube-flannel-dk6d5                                  registry.k8s.io/pause:3.6                                     1329   SANDBOX_READY
172.20.1.2   k8s.io      └─ kube-system/kube-flannel-dk6d5:install-cni:f1d4cf68feb9      ghcr.io/siderolabs/install-cni:v0.7.0-alpha.0-1-g2bb2efc      0      CONTAINER_EXITED
172.20.1.2   k8s.io      └─ kube-system/kube-flannel-dk6d5:install-config:bc39fec3cbac   quay.io/coreos/flannel:v0.13.0                                0      CONTAINER_EXITED
172.20.1.2   k8s.io      └─ kube-system/kube-flannel-dk6d5:kube-flannel:5c3989353b98     quay.io/coreos/flannel:v0.13.0                                1610   CONTAINER_RUNNING
172.20.1.2   k8s.io      kube-system/kube-proxy-gfkqj                                    registry.k8s.io/pause:3.5                                     1311   SANDBOX_READY
172.20.1.2   k8s.io      └─ kube-system/kube-proxy-gfkqj:kube-proxy:ad5e8ddc7e7f         registry.k8s.io/kube-proxy:v1.27.4                            1379   CONTAINER_RUNNING

$ talosctl -n 172.20.1.2 logs -k kube-system/kube-proxy-gfkqj:kube-proxy:ad5e8ddc7e7f
172.20.1.2: 2021-11-30T19:13:20.567825192Z stderr F I1130 19:13:20.567737       1 server_others.go:138] "Detected node IP" address="172.20.0.3"
172.20.1.2: 2021-11-30T19:13:20.599684397Z stderr F I1130 19:13:20.599613       1 server_others.go:206] "Using iptables Proxier"
[...]

Sending logs

Service logs

You can enable logs sendings in machine configuration:

machine:
  logging:
    destinations:
      - endpoint: "udp://127.0.0.1:12345/"
        format: "json_lines"
      - endpoint: "tcp://host:5044/"
        format: "json_lines"

Several destinations can be specified. Supported protocols are UDP and TCP. The only currently supported format is json_lines:

{
  "msg": "[talos] apply config request: immediate true, on reboot false",
  "talos-level": "info",
  "talos-service": "machined",
  "talos-time": "2021-11-10T10:48:49.294858021Z"
}

Messages are newline-separated when sent over TCP. Over UDP messages are sent with one message per packet. msg, talos-level, talos-service, and talos-time fields are always present; there may be additional fields.

Kernel logs

Kernel log delivery can be enabled with the talos.logging.kernel kernel command line argument, which can be specified in the .machine.installer.extraKernelArgs:

machine:
  install:
    extraKernelArgs:
      - talos.logging.kernel=tcp://host:5044/

Kernel log destination is specified in the same way as service log endpoint. The only supported format is json_lines.

Sample message:

{
  "clock":6252819, // time relative to the kernel boot time
  "facility":"user",
  "msg":"[talos] task startAllServices (1/1): waiting for 6 services\n",
  "priority":"warning",
  "seq":711,
  "talos-level":"warn", // Talos-translated `priority` into common logging level
  "talos-time":"2021-11-26T16:53:21.3258698Z" // Talos-translated `clock` using current time
}

extraKernelArgs in the machine configuration are only applied on Talos upgrades, not just by applying the config. (Upgrading to the same version is fine).

Filebeat example

To forward logs to other Log collection services, one way to do this is sending them to a Filebeat running in the cluster itself (in the host network), which takes care of forwarding it to other endpoints (and the necessary transformations).

If Elastic Cloud on Kubernetes is being used, the following Beat (custom resource) configuration might be helpful:

apiVersion: beat.k8s.elastic.co/v1beta1
kind: Beat
metadata:
  name: talos
spec:
  type: filebeat
  version: 7.15.1
  elasticsearchRef:
    name: talos
  config:
    filebeat.inputs:
      - type: "udp"
        host: "127.0.0.1:12345"
        processors:
          - decode_json_fields:
              fields: ["message"]
              target: ""
          - timestamp:
              field: "talos-time"
              layouts:
                - "2006-01-02T15:04:05.999999999Z07:00"
          - drop_fields:
              fields: ["message", "talos-time"]
          - rename:
              fields:
                - from: "msg"
                  to: "message"

  daemonSet:
    updateStrategy:
      rollingUpdate:
        maxUnavailable: 100%
    podTemplate:
      spec:
        dnsPolicy: ClusterFirstWithHostNet
        hostNetwork: true
        securityContext:
          runAsUser: 0
        containers:
          - name: filebeat
            ports:
              - protocol: UDP
                containerPort: 12345
                hostPort: 12345

The input configuration ensures that messages and timestamps are extracted properly. Refer to the Filebeat documentation on how to forward logs to other outputs.

Also note the hostNetwork: true in the daemonSet configuration.

This ensures filebeat uses the host network, and listens on 127.0.0.1:12345 (UDP) on every machine, which can then be specified as a logging endpoint in the machine configuration.

Fluent-bit example

First, we’ll create a value file for the fluentd-bit Helm chart.

# fluentd-bit.yaml

podAnnotations:
  fluentbit.io/exclude: 'true'

extraPorts:
  - port: 12345
    containerPort: 12345
    protocol: TCP
    name: talos

config:
  service: |
    [SERVICE]
      Flush         5
      Daemon        Off
      Log_Level     warn
      Parsers_File  custom_parsers.conf    

  inputs: |
    [INPUT]
      Name          tcp
      Listen        0.0.0.0
      Port          12345
      Format        json
      Tag           talos.*

    [INPUT]
      Name          tail
      Alias         kubernetes
      Path          /var/log/containers/*.log
      Parser        containerd
      Tag           kubernetes.*

    [INPUT]
      Name          tail
      Alias         audit
      Path          /var/log/audit/kube/*.log
      Parser        audit
      Tag           audit.*    

  filters: |
    [FILTER]
      Name                kubernetes
      Alias               kubernetes
      Match               kubernetes.*
      Kube_Tag_Prefix     kubernetes.var.log.containers.
      Use_Kubelet         Off
      Merge_Log           On
      Merge_Log_Trim      On
      Keep_Log            Off
      K8S-Logging.Parser  Off
      K8S-Logging.Exclude On
      Annotations         Off
      Labels              On

    [FILTER]
      Name          modify
      Match         kubernetes.*
      Add           source kubernetes
      Remove        logtag    

  customParsers: |
    [PARSER]
      Name          audit
      Format        json
      Time_Key      requestReceivedTimestamp
      Time_Format   %Y-%m-%dT%H:%M:%S.%L%z

    [PARSER]
      Name          containerd
      Format        regex
      Regex         ^(?<time>[^ ]+) (?<stream>stdout|stderr) (?<logtag>[^ ]*) (?<log>.*)$
      Time_Key      time
      Time_Format   %Y-%m-%dT%H:%M:%S.%L%z    

  outputs: |
    [OUTPUT]
      Name    stdout
      Alias   stdout
      Match   *
      Format  json_lines    

  # If you wish to ship directly to Loki from Fluentbit,
  # Uncomment the following output, updating the Host with your Loki DNS/IP info as necessary.
  # [OUTPUT]
  # Name loki
  # Match *
  # Host loki.loki.svc
  # Port 3100
  # Labels job=fluentbit
  # Auto_Kubernetes_Labels on

daemonSetVolumes:
  - name: varlog
    hostPath:
      path: /var/log

daemonSetVolumeMounts:
  - name: varlog
    mountPath: /var/log

tolerations:
  - operator: Exists
    effect: NoSchedule

Next, we will add the helm repo for FluentBit, and deploy it to the cluster.

helm repo add fluent https://fluent.github.io/helm-charts
helm upgrade -i --namespace=kube-system -f fluentd-bit.yaml fluent-bit fluent/fluent-bit

Now we need to find the service IP.

$ kubectl -n kube-system get svc -l app.kubernetes.io/name=fluent-bit

NAME         TYPE        CLUSTER-IP     EXTERNAL-IP   PORT(S)             AGE
fluent-bit   ClusterIP   10.200.0.138   <none>        2020/TCP,5170/TCP   108m

Finally, we will change talos log destination with the command talosctl edit mc.

machine:
  logging:
    destinations:
      - endpoint: "tcp://10.200.0.138:5170"
        format: "json_lines"

This example configuration was well tested with Cilium CNI, and it should work with iptables/ipvs based CNI plugins too.

Vector example

Vector is a lightweight observability pipeline ideal for a Kubernetes environment. It can ingest (source) logs from multiple sources, perform remapping on the logs (transform), and forward the resulting pipeline to multiple destinations (sinks). As it is an end to end platform, it can be run as a single-deployment ‘aggregator’ as well as a replicaSet of ‘Agents’ that run on each node.

As Talos can be set as above to send logs to a destination, we can run Vector as an Aggregator, and forward both kernel and service to a UDP socket in-cluster.

Below is an excerpt of a source/sink setup for Talos, with a ‘sink’ destination of an in-cluster Grafana Loki log aggregation service. As Loki can create labels from the log input, we have set up the Loki sink to create labels based on the host IP, service and facility of the inbound logs.

Note that a method of exposing the Vector service will be required which may vary depending on your setup - a LoadBalancer is a good option.

role: "Stateless-Aggregator"

# Sources
sources:
  talos_kernel_logs:
    address: 0.0.0.0:6050
    type: socket
    mode: udp
    max_length: 102400
    decoding:
      codec: json
    host_key: __host

  talos_service_logs:
    address: 0.0.0.0:6051
    type: socket
    mode: udp
    max_length: 102400
    decoding:
      codec: json
    host_key: __host

# Sinks
sinks:
  talos_kernel:
    type: loki
    inputs:
      - talos_kernel_logs_xform
    endpoint: http://loki.system-monitoring:3100
    encoding:
      codec: json
      except_fields:
        - __host
    batch:
      max_bytes: 1048576
    out_of_order_action: rewrite_timestamp
    labels:
      hostname: >-
                {{`{{ __host }}`}}
      facility: >-
                {{`{{ facility }}`}}

  talos_service:
    type: loki
    inputs:
      - talos_service_logs_xform
    endpoint: http://loki.system-monitoring:3100
    encoding:
      codec: json
      except_fields:
        - __host
    batch:
      max_bytes: 400000
    out_of_order_action: rewrite_timestamp
    labels:
      hostname: >-
                {{`{{ __host }}`}}
      service: >-
                {{`{{ "talos-service" }}`}}

2.2.7 - Managing Talos PKI

How to manage Public Key Infrastructure

Generating New Client Configuration

Using Controlplane Node

If you have a valid (not expired) talosconfig with os:admin role, a new client configuration file can be generated with talosctl config new against any controlplane node:

talosctl -n CP1 config new talosconfig-reader --roles os:reader --crt-ttl 24h

A specific role and certificate lifetime can be specified.

From Secrets Bundle

If a secrets bundle (secrets.yaml from talosctl gen secrets) was saved while generating machine configuration:

talosctl gen config --with-secrets secrets.yaml --output-types talosconfig -o talosconfig <cluster-name> https://<cluster-endpoint>

Note: <cluster-name> and <cluster-endpoint> arguments don’t matter, as they are not used for talosconfig.

From Control Plane Machine Configuration

In order to create a new key pair for client configuration, you will need the root Talos API CA. The base64 encoded CA can be found in the control plane node’s configuration file. Save the CA public key, and CA private key as ca.crt, and ca.key respectively:

yq eval .machine.ca.crt controlplane.yaml | base64 -d > ca.crt
yq eval .machine.ca.key controlplane.yaml | base64 -d > ca.key

Now, run the following commands to generate a certificate:

talosctl gen key --name admin
talosctl gen csr --key admin.key --ip 127.0.0.1
talosctl gen crt --ca ca --csr admin.csr --name admin

Put the base64-encoded files to the respective location to the talosconfig:

context: mycluster
contexts:
    mycluster:
        endpoints:
            - CP1
            - CP2
        ca: <base64-encoded ca.crt>
        crt: <base64-encoded admin.crt>
        key: <base64-encoded admin.key>

Renewing an Expired Administrator Certificate

By default admin talosconfig certificate is valid for 365 days, while cluster CAs are valid for 10 years. In order to prevent admin talosconfig from expiring, renew the client config before expiration using talosctl config new command described above.

If the talosconfig is expired or lost, you can still generate a new one using either the secrets.yaml secrets bundle or the control plane node’s configuration file using methods described above.

2.2.8 - NVIDIA Fabric Manager

In this guide we’ll follow the procedure to enable NVIDIA Fabric Manager.

NVIDIA GPUs that have nvlink support (for eg: A100) will need the nvidia-fabricmanager system extension also enabled in addition to the NVIDIA drivers. For more information on Fabric Manager refer https://docs.nvidia.com/datacenter/tesla/fabric-manager-user-guide/index.html

The published versions of the NVIDIA fabricmanager system extensions is available here

The nvidia-fabricmanager extension version has to match with the NVIDIA driver version in use.

Upgrading Talos and enabling the NVIDIA fabricmanager system extension

In addition to the patch defined in the NVIDIA drivers guide, we need to add the nvidia-fabricmanager system extension to the patch yaml gpu-worker-patch.yaml:

- op: add
  path: /machine/install/extensions
  value:
    - image: ghcr.io/siderolabs/nvidia-open-gpu-kernel-modules:530.41.03-v1.4.8
    - image: ghcr.io/siderolabs/nvidia-container-toolkit:530.41.03-v1.12.1
    - image: ghcr.io/siderolabs/nvidia-fabricmanager:525.85.12
- op: add
  path: /machine/kernel
  value:
    modules:
      - name: nvidia
      - name: nvidia_uvm
      - name: nvidia_drm
      - name: nvidia_modeset
- op: add
  path: /machine/sysctls
  value:
    net.core.bpf_jit_harden: 1

2.2.9 - NVIDIA GPU (OSS drivers)

In this guide we’ll follow the procedure to support NVIDIA GPU using OSS drivers on Talos.

Enabling NVIDIA GPU support on Talos is bound by NVIDIA EULA. The Talos published NVIDIA OSS drivers are bound to a specific Talos release. The extensions versions also needs to be updated when upgrading Talos.

The published versions of the NVIDIA system extensions can be found here:

Upgrading Talos and enabling the NVIDIA modules and the system extension

Make sure to use talosctl version v1.4.8 or later

First create a patch yaml gpu-worker-patch.yaml to update the machine config similar to below:

- op: add
  path: /machine/install/extensions
  value:
    - image: ghcr.io/siderolabs/nvidia-open-gpu-kernel-modules:530.41.03-v1.4.8
    - image: ghcr.io/siderolabs/nvidia-container-toolkit:530.41.03-v1.12.1
- op: add
  path: /machine/kernel
  value:
    modules:
      - name: nvidia
      - name: nvidia_uvm
      - name: nvidia_drm
      - name: nvidia_modeset
- op: add
  path: /machine/sysctls
  value:
    net.core.bpf_jit_harden: 1

Update the driver version and Talos release in the above patch yaml from the published versions if there is a newer one available. Make sure the driver version matches for both the nvidia-open-gpu-kernel-modules and nvidia-container-toolkit extensions. The nvidia-open-gpu-kernel-modules extension is versioned as <nvidia-driver-version>-<talos-release-version> and the nvidia-container-toolkit extension is versioned as <nvidia-driver-version>-<nvidia-container-toolkit-version>.

Now apply the patch to all Talos nodes in the cluster having NVIDIA GPU’s installed:

talosctl patch mc --patch @gpu-worker-patch.yaml

Now we can proceed to upgrading Talos to the same version to enable the system extension:

talosctl upgrade --image=ghcr.io/siderolabs/installer:v1.4.8

Once the node reboots, the NVIDIA modules should be loaded and the system extension should be installed.

This can be confirmed by running:

talosctl read /proc/modules

which should produce an output similar to below:

nvidia_uvm 1146880 - - Live 0xffffffffc2733000 (PO)
nvidia_drm 69632 - - Live 0xffffffffc2721000 (PO)
nvidia_modeset 1142784 - - Live 0xffffffffc25ea000 (PO)
nvidia 39047168 - - Live 0xffffffffc00ac000 (PO)

talosctl get extensions

which should produce an output similar to below:

NODE           NAMESPACE   TYPE              ID                                                                           VERSION   NAME                             VERSION
172.31.41.27   runtime     ExtensionStatus   000.ghcr.io-siderolabs-nvidia-container-toolkit-515.65.01-v1.10.0            1         nvidia-container-toolkit         515.65.01-v1.10.0
172.31.41.27   runtime     ExtensionStatus   000.ghcr.io-siderolabs-nvidia-open-gpu-kernel-modules-515.65.01-v1.2.0       1         nvidia-open-gpu-kernel-modules   515.65.01-v1.2.0

talosctl read /proc/driver/nvidia/version

which should produce an output similar to below:

NVRM version: NVIDIA UNIX x86_64 Kernel Module  515.65.01  Wed Mar 16 11:24:05 UTC 2022
GCC version:  gcc version 12.2.0 (GCC)

Deploying NVIDIA device plugin

First we need to create the RuntimeClass

Apply the following manifest to create a runtime class that uses the extension:

---
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
  name: nvidia
handler: nvidia

Install the NVIDIA device plugin:

helm repo add nvdp https://nvidia.github.io/k8s-device-plugin
helm repo update
helm install nvidia-device-plugin nvdp/nvidia-device-plugin --version=0.13.0 --set=runtimeClassName=nvidia

(Optional) Setting the default runtime class as `nvidia`

Do note that this will set the default runtime class to nvidia for all pods scheduled on the node.

Create a patch yaml nvidia-default-runtimeclass.yaml to update the machine config similar to below:

- op: add
  path: /machine/files
  value:
    - content: |
        [plugins]
          [plugins."io.containerd.grpc.v1.cri"]
            [plugins."io.containerd.grpc.v1.cri".containerd]
              default_runtime_name = "nvidia"        
      path: /etc/cri/conf.d/20-customization.part
      op: create

Now apply the patch to all Talos nodes in the cluster having NVIDIA GPU’s installed:

talosctl patch mc --patch @nvidia-default-runtimeclass.yaml

Testing the runtime class

Note the spec.runtimeClassName being explicitly set to nvidia in the pod spec.

Run the following command to test the runtime class:

kubectl run \
  nvidia-test \
  --restart=Never \
  -ti --rm \
  --image nvcr.io/nvidia/cuda:12.1.0-base-ubuntu22.04 \
  --overrides '{"spec": {"runtimeClassName": "nvidia"}}' \
  nvidia-smi

2.2.10 - NVIDIA GPU (Proprietary drivers)

In this guide we’ll follow the procedure to support NVIDIA GPU using proprietary drivers on Talos.

Enabling NVIDIA GPU support on Talos is bound by NVIDIA EULA.

The steps to enable NVIDIA support in Talos in v1.4.8 and later differ from previous versions:

For versions prior to v1.4.8 the steps require that the user build and maintain their own Talos installer image. After the Prerequisites jump to Building the installer image (Talos prior to v1.4.8) and after Upgrading Talos and enabling the NVIDIA modules and the system extension (Talos prior to v1.4.8) continue from Verifying the NVIDIA modules and the system extension.
for v1.4.8 and later versions building a custom Talos installer image is not required anymore and the new, prefered way to enable NVIDIA support is via an extension.

Prerequisites

This guide assumes the user has access to a container registry with push permissions, docker installed on the build machine and the Talos host has pull access to the container registry.

Set the local registry, username and version environment variables:

export USERNAME=<username>
export REGISTRY=<registry>
export TAG=v1.4.8-nvidia

For eg:

export USERNAME=talos-user
export REGISTRY=ghcr.io

The examples below will use the sample variables set above. Modify accordingly for your environment.

Building the NVIDIA extensions

Instead of building the extensions yourself, you can use the extensions published by SideroLabs in the pkgs repo here and here

Start by cloning the release-1.5 branch extensions repository.

git clone --depth=1 --branch=release-1.5 https://github.com/siderolabs/extensions.git

Lookup the version of pkgs used for the particular Talos version here

Replace v1.4.8 with the Talos version you are using.

Now run the following command to build and push custom NVIDIA extension.

make nonfree-kmod-nvidia PKGS=<pkgs-version-looked-up-above> PLATFORM=linux/amd64 PUSH=true

Replace the platform with linux/arm64 if building for ARM64 Make sure to use talosctl version v1.4.8 or later

Upgrading Talos and enabling the NVIDIA modules and the system extension

First create a patch yaml gpu-worker-patch.yaml to update the machine config similar to below:

- op: add
  path: /machine/install/extensions
  value:
    - image: ghcr.io/siderolabs/nonfree-kmod-nvidia:530.41.03-v1.4.8
    - image: ghcr.io/siderolabs/nvidia-container-toolkit:530.41.03-v1.12.1
- op: add
  path: /machine/kernel
  value:
    modules:
      - name: nvidia
      - name: nvidia_uvm
      - name: nvidia_drm
      - name: nvidia_modeset
- op: add
  path: /machine/sysctls
  value:
    net.core.bpf_jit_harden: 1

Now apply the patch to all Talos nodes in the cluster having NVIDIA GPU’s installed:

talosctl patch mc --patch @gpu-worker-patch.yaml

Now we can proceed to upgrading Talos to the same version to enable the system extension:

talosctl upgrade --image=ghcr.io/siderolabs/installer:v1.4.8

Verifying the NVIDIA modules and the system extension

Once the node reboots, the NVIDIA modules should be loaded and the system extension should be installed.

This can be confirmed by running:

talosctl read /proc/modules

which should produce an output similar to below:

nvidia_uvm 1146880 - - Live 0xffffffffc2733000 (PO)
nvidia_drm 69632 - - Live 0xffffffffc2721000 (PO)
nvidia_modeset 1142784 - - Live 0xffffffffc25ea000 (PO)
nvidia 39047168 - - Live 0xffffffffc00ac000 (PO)

talosctl get extensions

which should produce an output similar to below:

NODE           NAMESPACE   TYPE              ID                                                                 VERSION   NAME                       VERSION
172.31.41.27   runtime     ExtensionStatus   000.ghcr.io-frezbo-nvidia-container-toolkit-510.60.02-v1.9.0       1         nvidia-container-toolkit   510.60.02-v1.9.0

talosctl read /proc/driver/nvidia/version

which should produce an output similar to below:

NVRM version: NVIDIA UNIX x86_64 Kernel Module  510.60.02  Wed Mar 16 11:24:05 UTC 2022
GCC version:  gcc version 11.2.0 (GCC)

Deploying NVIDIA device plugin

First we need to create the RuntimeClass

Apply the following manifest to create a runtime class that uses the extension:

---
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
  name: nvidia
handler: nvidia

Install the NVIDIA device plugin:

helm repo add nvdp https://nvidia.github.io/k8s-device-plugin
helm repo update
helm install nvidia-device-plugin nvdp/nvidia-device-plugin --version=0.13.0 --set=runtimeClassName=nvidia

(Optional) Setting the default runtime class as `nvidia`

Do note that this will set the default runtime class to nvidia for all pods scheduled on the node.

Create a patch yaml nvidia-default-runtimeclass.yaml to update the machine config similar to below:

- op: add
  path: /machine/files
  value:
    - content: |
        [plugins]
          [plugins."io.containerd.grpc.v1.cri"]
            [plugins."io.containerd.grpc.v1.cri".containerd]
              default_runtime_name = "nvidia"        
      path: /etc/cri/conf.d/20-customization.part
      op: create

Now apply the patch to all Talos nodes in the cluster having NVIDIA GPU’s installed:

talosctl patch mc --patch @nvidia-default-runtimeclass.yaml

Testing the runtime class

Note the spec.runtimeClassName being explicitly set to nvidia in the pod spec.

Run the following command to test the runtime class:

kubectl run \
  nvidia-test \
  --restart=Never \
  -ti --rm \
  --image nvcr.io/nvidia/cuda:12.1.0-base-ubuntu22.04 \
  --overrides '{"spec": {"runtimeClassName": "nvidia"}}' \
  nvidia-smi

Building the installer image (Talos prior to v1.4.8)

Start by cloning the pkgs repository.

Now run the following command to build and push custom Talos kernel image and the NVIDIA image with the NVIDIA kernel modules signed by the kernel built along with it.

make kernel nonfree-kmod-nvidia PLATFORM=linux/amd64 PUSH=true

Replace the platform with linux/arm64 if building for ARM64

Now we need to create a custom Talos installer image.

Start by creating a Dockerfile with the following content:

FROM scratch as customization
COPY --from=ghcr.io/talos-user/nonfree-kmod-nvidia:v1.4.8-nvidia /lib/modules /lib/modules

FROM ghcr.io/siderolabs/installer:v1.4.8
COPY --from=ghcr.io/talos-user/kernel:v1.4.8-nvidia /boot/vmlinuz /usr/install/${TARGETARCH}/vmlinuz

Now build the image and push it to the registry.

DOCKER_BUILDKIT=0 docker build --squash --build-arg RM="/lib/modules" -t ghcr.io/talos-user/installer:v1.4.8-nvidia .
docker push ghcr.io/talos-user/installer:v1.4.8-nvidia

Note: buildkit has a bug #816, to disable it use DOCKER_BUILDKIT=0 Replace the platform with linux/arm64 if building for ARM64

Upgrading Talos and enabling the NVIDIA modules and the system extension (Talos prior to v1.4.8)

Make sure to use talosctl version v1.4.8 or later

First create a patch yaml gpu-worker-patch.yaml to update the machine config similar to below:

- op: add
  path: /machine/install/extensions
  value:
    - image: ghcr.io/siderolabs/nvidia-container-toolkit:530.41.03-v1.12.1
- op: add
  path: /machine/kernel
  value:
    modules:
      - name: nvidia
      - name: nvidia_uvm
      - name: nvidia_drm
      - name: nvidia_modeset
- op: add
  path: /machine/sysctls
  value:
    net.core.bpf_jit_harden: 1

Now apply the patch to all Talos nodes in the cluster having NVIDIA GPU’s installed:

talosctl patch mc --patch @gpu-worker-patch.yaml

Now we can proceed to upgrading Talos with the installer built previously:

talosctl upgrade --image=ghcr.io/talos-user/installer:v1.4.8-nvidia

2.2.11 - Pull Through Image Cache

How to set up local transparent container images caches.

In this guide we will create a set of local caching Docker registry proxies to minimize local cluster startup time.

When running Talos locally, pulling images from container registries might take a significant amount of time. We spin up local caching pass-through registries to cache images and configure a local Talos cluster to use those proxies. A similar approach might be used to run Talos in production in air-gapped environments. It can be also used to verify that all the images are available in local registries.

Video Walkthrough

To see a live demo of this writeup, see the video below:

Requirements

The follow are requirements for creating the set of caching proxies:

Docker 18.03 or greater
Local cluster requirements for either docker or QEMU.

Launch the Caching Docker Registry Proxies

Talos pulls from docker.io, registry.k8s.io, gcr.io, and ghcr.io by default. If your configuration is different, you might need to modify the commands below:

docker run -d -p 5000:5000 \
    -e REGISTRY_PROXY_REMOTEURL=https://registry-1.docker.io \
    --restart always \
    --name registry-docker.io registry:2

docker run -d -p 5001:5000 \
    -e REGISTRY_PROXY_REMOTEURL=https://registry.k8s.io \
    --restart always \
    --name registry-registry.k8s.io registry:2

docker run -d -p 5003:5000 \
    -e REGISTRY_PROXY_REMOTEURL=https://gcr.io \
    --restart always \
    --name registry-gcr.io registry:2

docker run -d -p 5004:5000 \
    -e REGISTRY_PROXY_REMOTEURL=https://ghcr.io \
    --restart always \
    --name registry-ghcr.io registry:2

Note: Proxies are started as docker containers, and they’re automatically configured to start with Docker daemon.

As a registry container can only handle a single upstream Docker registry, we launch a container per upstream, each on its own host port (5000, 5001, 5002, 5003 and 5004).

Using Caching Registries with `QEMU` Local Cluster

With a QEMU local cluster, a bridge interface is created on the host. As registry containers expose their ports on the host, we can use bridge IP to direct proxy requests.

sudo talosctl cluster create --provisioner qemu \
    --registry-mirror docker.io=http://10.5.0.1:5000 \
    --registry-mirror registry.k8s.io=http://10.5.0.1:5001 \
    --registry-mirror gcr.io=http://10.5.0.1:5003 \
    --registry-mirror ghcr.io=http://10.5.0.1:5004

The Talos local cluster should now start pulling via caching registries. This can be verified via registry logs, e.g. docker logs -f registry-docker.io. The first time cluster boots, images are pulled and cached, so next cluster boot should be much faster.

Note: 10.5.0.1 is a bridge IP with default network (10.5.0.0/24), if using custom --cidr, value should be adjusted accordingly.

Using Caching Registries with `docker` Local Cluster

With a docker local cluster we can use docker bridge IP, default value for that IP is 172.17.0.1. On Linux, the docker bridge address can be inspected with ip addr show docker0.

talosctl cluster create --provisioner docker \
    --registry-mirror docker.io=http://172.17.0.1:5000 \
    --registry-mirror registry.k8s.io=http://172.17.0.1:5001 \
    --registry-mirror gcr.io=http://172.17.0.1:5003 \
    --registry-mirror ghcr.io=http://172.17.0.1:5004

Machine Configuration

The caching registries can be configured via machine configuration patch, equivalent to the command line flags above:

machine:
  registries:
    mirrors:
      docker.io:
        endpoints:
          - http://10.5.0.1:5000
      gcr.io:
        endpoints:
          - http://10.5.0.1:5003
      ghcr.io:
        endpoints:
          - http://10.5.0.1:5004
      registry.k8s.io:
        endpoints:
          - http://10.5.0.1:5001

Cleaning Up

To cleanup, run:

docker rm -f registry-docker.io
docker rm -f registry-registry.k8s.io
docker rm -f registry-gcr.io
docker rm -f registry-ghcr.io

Note: Removing docker registry containers also removes the image cache. So if you plan to use caching registries, keep the containers running.

Using Harbor as a Caching Registry

Harbor is an open source container registry that can be used as a caching proxy. Harbor supports configuring multiple upstream registries, so it can be used to cache multiple registries at once behind a single endpoint.

Harbor Endpoints

Harbor Projects

As Harbor puts a registry name in the pull image path, we need to set overridePath: true to prevent Talos and containerd from appending /v2 to the path.

machine:
  registries:
    mirrors:
      docker.io:
        endpoints:
          - http://harbor/v2/proxy-docker.io
        overridePath: true
      ghcr.io:
        endpoints:
          - http://harbor/v2/proxy-ghcr.io
        overridePath: true
      gcr.io:
        endpoints:
          - http://harbor/v2/proxy-gcr.io
        overridePath: true
      registry.k8s.io:
        endpoints:
          - http://harbor/v2/proxy-registry.k8s.io
        overridePath: true

The Harbor external endpoint (http://harbor in this example) can be configured with authentication or custom TLS:

machine:
  registries:
    config:
      harbor:
        auth:
          username: admin
          password: password

2.2.12 - Role-based access control (RBAC)

Set up RBAC on the Talos Linux API.

Talos v0.11 introduced initial support for role-based access control (RBAC). This guide will explain what that is and how to enable it without losing access to the cluster.

RBAC in Talos

Talos uses certificates to authorize users. The certificate subject’s organization field is used to encode user roles. There is a set of predefined roles that allow access to different API methods:

os:admin grants access to all methods;
os:operator grants everything os:reader role does, plus additional methods: rebooting, shutting down, etcd backup, etcd alarm management, and so on;
os:reader grants access to “safe” methods (for example, that includes the ability to list files, but does not include the ability to read files content);
os:etcd:backup grants access to /machine.MachineService/EtcdSnapshot method.

Roles in the current talosconfig can be checked with the following command:

$ talosctl config info

[...]
Roles:               os:admin
[...]

RBAC is enabled by default in new clusters created with talosctl v0.11+ and disabled otherwise.

Enabling RBAC

First, both the Talos cluster and talosctl tool should be upgraded. Then the talosctl config new command should be used to generate a new client configuration with the os:admin role. Additional configurations and certificates for different roles can be generated by passing --roles flag:

talosctl config new --roles=os:reader reader

That command will create a new client configuration file reader with a new certificate with os:reader role.

After that, RBAC should be enabled in the machine configuration:

machine:
  features:
    rbac: true

2.2.13 - System Extensions

Customizing the Talos Linux immutable root file system.

System extensions allow extending the Talos root filesystem, which enables a variety of features, such as including custom container runtimes, loading additional firmware, etc.

System extensions are only activated during the installation or upgrade of Talos Linux. With system extensions installed, the Talos root filesystem is still immutable and read-only.

Configuration

System extensions are configured in the .machine.install section:

machine:
  install:
    extensions:
      - image: ghcr.io/siderolabs/gvisor:33f613e

During the initial install (e.g. when PXE booting or booting from an ISO), Talos will pull down container images for system extensions, validate them, and include them into the Talos initramfs image. System extensions will be activated on boot and overlaid on top of the Talos root filesystem.

In order to update the system extensions for a running instance, update .machine.install.extensions and upgrade Talos. (Note: upgrading to the same version of Talos is fine).

Building a Talos Image with System Extensions

System extensions can be installed into the Talos disk image (e.g. AWS AMI or VMWare OVF) by running the following command to generate the image from the Talos source tree:

make image-metal IMAGER_SYSTEM_EXTENSIONS="ghcr.io/siderolabs/amd-ucode:20220411 ghcr.io/siderolabs/gvisor:20220405.0-v1.0.0-10-g82b41ad"

Authoring System Extensions

A Talos system extension is a container image with the specific folder structure. System extensions can be built and managed using any tool that produces container images, e.g. docker build.

Sidero Labs maintains a repository of system extensions.

Resource Definitions

Use talosctl get extensions to get a list of system extensions:

$ talosctl get extensions
NODE         NAMESPACE   TYPE              ID                                              VERSION   NAME          VERSION
172.20.0.2   runtime     ExtensionStatus   000.ghcr.io-talos-systems-gvisor-54b831d        1         gvisor        20220117.0-v1.0.0
172.20.0.2   runtime     ExtensionStatus   001.ghcr.io-talos-systems-intel-ucode-54b831d   1         intel-ucode   microcode-20210608-v1.0.0

Use YAML or JSON format to see additional details about the extension:

$ talosctl -n 172.20.0.2 get extensions 001.ghcr.io-talos-systems-intel-ucode-54b831d -o yaml
node: 172.20.0.2
metadata:
    namespace: runtime
    type: ExtensionStatuses.runtime.talos.dev
    id: 001.ghcr.io-talos-systems-intel-ucode-54b831d
    version: 1
    owner: runtime.ExtensionStatusController
    phase: running
    created: 2022-02-10T18:25:04Z
    updated: 2022-02-10T18:25:04Z
spec:
    image: 001.ghcr.io-talos-systems-intel-ucode-54b831d.sqsh
    metadata:
        name: intel-ucode
        version: microcode-20210608-v1.0.0
        author: Spencer Smith
        description: |
            This system extension provides Intel microcode binaries.
        compatibility:
            talos:
                version: '>= v1.0.0'

Example: gVisor

See readme of the gVisor extension.

2.3 - How Tos

How to guide for common tasks in Talos Linux

2.3.1 - How to enable workers on your control plane nodes

How to enable workers on your control plane nodes.

By default, Talos Linux taints control plane nodes so that workloads are not schedulable on them.

In order to allow workloads to run on the control plane nodes (useful for single node clusters, or non-production clusters), follow the procedure below.

Modify the MachineConfig for the controlplane nodes to add allowSchedulingOnControlPlanes: true:

cluster:
    allowSchedulingOnControlPlanes: true

This may be done via editing the controlplane.yaml file before it is applied to the controlplane nodes, by talosctl edit machineconfig, or by patching the machine config.

Note: if you edit or patch the machine config on a running control plane node to set allowSchedulingOnControlPlanes: true, it will be applied immediately, but will not have any effect until the next reboot. You may reboot the nodes via talosctl reboot.

You may also immediately make the control plane nodes schedulable by running the below:

kubectl taint nodes --all  node-role.kubernetes.io/control-plane-

Note that unless allowSchedulingOnControlPlanes: true is set in the machine config, the nodes will be tainted again on next reboot.

2.3.2 - How to scale down a Talos cluster

How to remove nodes from a Talos Linux cluster.

To remove nodes from a Talos Linux cluster:

talosctl -n <IP.of.node.to.remove> reset
kubectl delete node <nodename>

The command talosctl reset will cordon and drain the node, leaving etcd if required, and then erase its disks and power down the system.

This command will also remove the node from registration with the discovery service, so it will no longer show up in talosctl get members.

It is still necessary to remove the node from Kubernetes, as noted above.

2.3.3 - How to scale up a Talos cluster

How to add more nodes to a Talos Linux cluster.

To add more nodes to a Talos Linux cluster, follow the same procedure as when initially creating the cluster:

boot the new machines to install Talos Linux
apply the worker.yaml or controlplane.yaml configuration files to the new machines

You need the controlplane.yaml and worker.yaml that were created when you initially deployed your cluster. These contain the certificates that enable new machines to join.

Once you have the IP address, you can then apply the correct configuration for each machine you are adding, either worker or controlplane.

  talosctl apply-config --insecure \
    --nodes [NODE IP] \
    --file controlplane.yaml

The insecure flag is necessary because the PKI infrastructure has not yet been made available to the node.

You do not need to bootstrap the new node. Regardless of whether you are adding a control plane or worker node, it will now join the cluster in its role.

2.4 - Network

Set up networking layers for Talos Linux

2.4.1 - Corporate Proxies

How to configure Talos Linux to use proxies in a corporate environment

Appending the Certificate Authority of MITM Proxies

Put into each machine the PEM encoded certificate:

machine:
  ...
  files:
    - content: |
        -----BEGIN CERTIFICATE-----
        ...
        -----END CERTIFICATE-----        
      permissions: 0644
      path: /etc/ssl/certs/ca-certificates
      op: append

Configuring a Machine to Use the Proxy

To make use of a proxy:

machine:
  env:
    http_proxy: <http proxy>
    https_proxy: <https proxy>
    no_proxy: <no proxy>

Additionally, configure the DNS nameservers, and NTP servers:

machine:
  env:
  ...
  time:
    servers:
      - <server 1>
      - <server ...>
      - <server n>
  ...
  network:
    nameservers:
      - <ip 1>
      - <ip ...>
      - <ip n>

2.4.2 - Network Device Selector

How to configure network devices by selecting them using hardware information

Configuring Network Device Using Device Selector

deviceSelector is an alternative method of configuring a network device:

machine:
  ...
  network:
    interfaces:
      - deviceSelector:
          driver: virtio
          hardwareAddr: "00:00:*"
        address: 192.168.88.21

Selector has the following traits:

qualifiers match a device by reading the hardware information in /sys/class/net/...
qualifiers are applied using logical AND
machine.network.interfaces.deviceConfig option is mutually exclusive with machine.network.interfaces.interface
the selector is invalid when it matches multiple devices, the controller will fail and won’t create any devices for the malformed selector

The available hardware information used in the selector can be observed in the LinkStatus resource (works in maintenance mode):

# talosctl get links eth0 -o yaml
spec:
  ...
  hardwareAddr: 4e:95:8e:8f:e4:47
  busPath: 0000:06:00.0
  driver: alx
  pciID: 1969:E0B1

Using Device Selector for Bonding

Device selectors can be used to configure bonded interfaces:

machine:
  ...
  network:
    interfaces:
      - interface: bond0
        bond:
          mode: balance-rr
          deviceSelectors:
            - hardwareAddr: '00:50:56:8e:8f:e4'
            - hardwareAddr: '00:50:57:9c:2c:2d'

In this example, the bond0 interface will be created and bonded using two devices with the specified hardware addresses.

Use Case

machine.network.interfaces.interface name is generated by the Linux kernel and can be changed after a reboot. Device names can change when the system has several interfaces of the same kind, e.g: eth0, eth1.

In that case pinning it to hardwareAddress will make Talos reliably configure the device even when interface name changes.

2.4.3 - Virtual (shared) IP

Using Talos Linux to set up a floating virtual IP address for cluster access.

One of the pain points when building a high-availability controlplane is giving clients a single IP or URL at which they can reach any of the controlplane nodes. The most common approaches - reverse proxy, load balancer, BGP, and DNS - all require external resources, and add complexity in setting up Kubernetes.

To simplify cluster creation, Talos Linux supports a “Virtual” IP (VIP) address to access the Kubernetes API server, providing high availability with no other resources required.

What happens is that the controlplane machines vie for control of the shared IP address using etcd elections. There can be only one owner of the IP address at any given time. If that owner disappears or becomes non-responsive, another owner will be chosen, and it will take up the IP address.

Requirements

The controlplane nodes must share a layer 2 network, and the virtual IP must be assigned from that shared network subnet. In practical terms, this means that they are all connected via a switch, with no router in between them. Note that the virtual IP election depends on etcd being up, as Talos uses etcd for elections and leadership (control) of the IP address.

The virtual IP is not restricted by ports - you can access any port that the control plane nodes are listening on, on that IP address. Thus it is possible to access the Talos API over the VIP, but it is not recommended, as you cannot access the VIP when etcd is down - and then you could not access the Talos API to recover etcd.

Video Walkthrough

To see a live demo of this writeup, see the video below:

Choose your Shared IP

The Virtual IP should be a reserved, unused IP address in the same subnet as your controlplane nodes. It should not be assigned or assignable by your DHCP server.

For our example, we will assume that the controlplane nodes have the following IP addresses:

192.168.0.10
192.168.0.11
192.168.0.12

We then choose our shared IP to be:

192.168.0.15

Configure your Talos Machines

The shared IP setting is only valid for controlplane nodes.

For the example above, each of the controlplane nodes should have the following Machine Config snippet:

machine:
  network:
    interfaces:
    - interface: eth0
      dhcp: true
      vip:
        ip: 192.168.0.15

Virtual IP’s can also be configured on a VLAN interface.

machine:
  network:
    interfaces:
    - interface: eth0
      dhcp: true
      vip:
        ip: 192.168.0.15
      vlans:
        - vlanId: 100
          dhcp: true
          vip:
            ip: 192.168.1.15

For your own environment, the interface and the DHCP setting may differ, or you may use static addressing (cidr) instead of DHCP.

Caveats

Since VIP functionality relies on etcd for elections, the shared IP will not come alive until after you have bootstrapped Kubernetes. This does mean that you cannot use the shared IP when issuing the talosctl bootstrap command (although, as noted above, it is not recommended to access the Talos API via the VIP). Instead, the bootstrap command will need to target one of the controlplane nodes directly.

2.4.4 - Wireguard Network

A guide on how to set up Wireguard network using Kernel module.

Configuring Wireguard Network

Quick Start

The quickest way to try out Wireguard is to use talosctl cluster create command:

talosctl cluster create --wireguard-cidr 10.1.0.0/24

It will automatically generate Wireguard network configuration for each node with the following network topology:

Where all controlplane nodes will be used as Wireguard servers which listen on port 51111. All controlplanes and workers will connect to all controlplanes. It also sets PersistentKeepalive to 5 seconds to establish controlplanes to workers connection.

After the cluster is deployed it should be possible to verify Wireguard network connectivity. It is possible to deploy a container with hostNetwork enabled, then do kubectl exec <container> /bin/bash and either do:

ping 10.1.0.2

Or install wireguard-tools package and run:

wg show

Wireguard show should output something like this:

interface: wg0
  public key: OMhgEvNIaEN7zeCLijRh4c+0Hwh3erjknzdyvVlrkGM=
  private key: (hidden)
  listening port: 47946

peer: 1EsxUygZo8/URWs18tqB5FW2cLVlaTA+lUisKIf8nh4=
  endpoint: 10.5.0.2:51111
  allowed ips: 10.1.0.0/24
  latest handshake: 1 minute, 55 seconds ago
  transfer: 3.17 KiB received, 3.55 KiB sent
  persistent keepalive: every 5 seconds

It is also possible to use generated configuration as a reference by pulling generated config files using:

talosctl read -n 10.5.0.2 /system/state/config.yaml > controlplane.yaml
talosctl read -n 10.5.0.3 /system/state/config.yaml > worker.yaml

Manual Configuration

All Wireguard configuration can be done by changing Talos machine config files. As an example we will use this official Wireguard quick start tutorial.

Key Generation

This part is exactly the same:

wg genkey | tee privatekey | wg pubkey > publickey

Setting up Device

Inline comments show relations between configs and wg quickstart tutorial commands:

...
network:
  interfaces:
    ...
      # ip link add dev wg0 type wireguard
    - interface: wg0
      mtu: 1500
      # ip address add dev wg0 192.168.2.1/24
      addresses:
        - 192.168.2.1/24
      # wg set wg0 listen-port 51820 private-key /path/to/private-key peer ABCDEF... allowed-ips 192.168.88.0/24 endpoint 209.202.254.14:8172
      wireguard:
        privateKey: <privatekey file contents>
        listenPort: 51820
        peers:
          allowedIPs:
            - 192.168.88.0/24
          endpoint: 209.202.254.14.8172
          publicKey: ABCDEF...
...

When networkd gets this configuration it will create the device, configure it and will bring it up (equivalent to ip link set up dev wg0).

All supported config parameters are described in the Machine Config Reference.

2.5 - Discovery Service

Talos Linux Node discovery services

Talos Linux includes node-discovery capabilities that depend on a discovery registry. This allows you to see the members of your cluster, and the associated IP addresses of the nodes.

talosctl get members
NODE       NAMESPACE   TYPE     ID                             VERSION   HOSTNAME                       MACHINE TYPE   OS               ADDRESSES
10.5.0.2   cluster     Member   talos-default-controlplane-1   1         talos-default-controlplane-1   controlplane   Talos (v1.2.3)   ["10.5.0.2"]
10.5.0.2   cluster     Member   talos-default-worker-1         1         talos-default-worker-1         worker         Talos (v1.2.3)   ["10.5.0.3"]

There are currently two supported discovery services: a Kubernetes registry (which stores data in the cluster’s etcd service) and an external registry service. Sidero Labs runs a public external registry service, which is enabled by default. The Kubernetes registry service is disabled by default. The advantage of the external registry service is that it is not dependent on etcd, and thus can inform you of cluster membership even when Kubernetes is down.

Video Walkthrough

To see a live demo of Cluster Discovery, see the video below:

Registries

Peers are aggregated from enabled registries. By default, Talos will use the service registry, while the kubernetes registry is disabled. To disable a registry, set disabled to true (this option is the same for all registries): For example, to disable the service registry:

cluster:
  discovery:
    enabled: true
    registries:
      service:
        disabled: true

Disabling all registries effectively disables member discovery altogether.

An enabled discovery service is required for KubeSpan to function correctly.

The Kubernetes registry uses Kubernetes Node resource data and additional Talos annotations:

$ kubectl describe node <nodename>
Annotations:        cluster.talos.dev/node-id: Utoh3O0ZneV0kT2IUBrh7TgdouRcUW2yzaaMl4VXnCd
                    networking.talos.dev/assigned-prefixes: 10.244.0.0/32,10.244.0.1/24
                    networking.talos.dev/self-ips: 172.20.0.2,fd83:b1f7:fcb5:2802:8c13:71ff:feaf:7c94
...

The Service registry by default uses a public external Discovery Service to exchange encrypted information about cluster members.

Discovery Service

Sidero Labs maintains a public discovery service at https://discovery.talos.dev/ whereby cluster members use a shared key that is globally unique to coordinate basic connection information (i.e. the set of possible “endpoints”, or IP:port pairs). We call this data “affiliate data.”

Note: If KubeSpan is enabled the data has the addition of the WireGuard public key.

Data sent to the discovery service is encrypted with AES-GCM encryption and endpoint data is separately encrypted with AES in ECB mode so that endpoints coming from different sources can be deduplicated server-side. Each node submits its own data, plus the endpoints it sees from other peers, to the discovery service. The discovery service aggregates the data, deduplicates the endpoints, and sends updates to each connected peer. Each peer receives information back from the discovery service, decrypts it and uses it to drive KubeSpan and cluster discovery.

Data is stored in memory only. The cluster ID is used as a key to select the affiliates (so that different clusters see different affiliates).

To summarize, the discovery service knows the client version, cluster ID, the number of affiliates, some encrypted data for each affiliate, and a list of encrypted endpoints. The discovery service doesn’t see actual node information – it only stores and updates encrypted blobs. Discovery data is encrypted/decrypted by the clients – the cluster members. The discovery service does not have the encryption key.

The discovery service may, with a commercial license, be operated by your organization and can be downloaded here. In order for nodes to communicate to the discovery service, they must be able to connect to it on TCP port 443.

Resource Definitions

Talos provides seven resources that can be used to introspect the new discovery and KubeSpan features.

Discovery

Identities

The node’s unique identity (base62 encoded random 32 bytes) can be obtained with:

Note: Using base62 allows the ID to be URL encoded without having to use the ambiguous URL-encoding version of base64.

$ talosctl get identities -o yaml
...
spec:
    nodeId: Utoh3O0ZneV0kT2IUBrh7TgdouRcUW2yzaaMl4VXnCd

Node identity is used as the unique Affiliate identifier.

Node identity resource is preserved in the STATE partition in node-identity.yaml file. Node identity is preserved across reboots and upgrades, but it is regenerated if the node is reset (wiped).

Affiliates

An affiliate is a proposed member attributed to the fact that the node has the same cluster ID and secret.

$ talosctl get affiliates
ID                                             VERSION   HOSTNAME                       MACHINE TYPE   ADDRESSES
2VfX3nu67ZtZPl57IdJrU87BMjVWkSBJiL9ulP9TCnF    2         talos-default-controlplane-2   controlplane   ["172.20.0.3","fd83:b1f7:fcb5:2802:986b:7eff:fec5:889d"]
6EVq8RHIne03LeZiJ60WsJcoQOtttw1ejvTS6SOBzhUA   2         talos-default-worker-1         worker         ["172.20.0.5","fd83:b1f7:fcb5:2802:cc80:3dff:fece:d89d"]
NVtfu1bT1QjhNq5xJFUZl8f8I8LOCnnpGrZfPpdN9WlB   2         talos-default-worker-2         worker         ["172.20.0.6","fd83:b1f7:fcb5:2802:2805:fbff:fe80:5ed2"]
Utoh3O0ZneV0kT2IUBrh7TgdouRcUW2yzaaMl4VXnCd    4         talos-default-controlplane-1   controlplane   ["172.20.0.2","fd83:b1f7:fcb5:2802:8c13:71ff:feaf:7c94"]
b3DebkPaCRLTLLWaeRF1ejGaR0lK3m79jRJcPn0mfA6C   2         talos-default-controlplane-3   controlplane   ["172.20.0.4","fd83:b1f7:fcb5:2802:248f:1fff:fe5c:c3f"]

One of the Affiliates with the ID matching node identity is populated from the node data, other Affiliates are pulled from the registries. Enabled discovery registries run in parallel and discovered data is merged to build the list presented above.

Details about data coming from each registry can be queried from the cluster-raw namespace:

$ talosctl get affiliates --namespace=cluster-raw
ID                                                     VERSION   HOSTNAME                       MACHINE TYPE   ADDRESSES
k8s/2VfX3nu67ZtZPl57IdJrU87BMjVWkSBJiL9ulP9TCnF        3         talos-default-controlplane-2   controlplane   ["172.20.0.3","fd83:b1f7:fcb5:2802:986b:7eff:fec5:889d"]
k8s/6EVq8RHIne03LeZiJ60WsJcoQOtttw1ejvTS6SOBzhUA       2         talos-default-worker-1         worker         ["172.20.0.5","fd83:b1f7:fcb5:2802:cc80:3dff:fece:d89d"]
k8s/NVtfu1bT1QjhNq5xJFUZl8f8I8LOCnnpGrZfPpdN9WlB       2         talos-default-worker-2         worker         ["172.20.0.6","fd83:b1f7:fcb5:2802:2805:fbff:fe80:5ed2"]
k8s/b3DebkPaCRLTLLWaeRF1ejGaR0lK3m79jRJcPn0mfA6C       3         talos-default-controlplane-3   controlplane   ["172.20.0.4","fd83:b1f7:fcb5:2802:248f:1fff:fe5c:c3f"]
service/2VfX3nu67ZtZPl57IdJrU87BMjVWkSBJiL9ulP9TCnF    23        talos-default-controlplane-2   controlplane   ["172.20.0.3","fd83:b1f7:fcb5:2802:986b:7eff:fec5:889d"]
service/6EVq8RHIne03LeZiJ60WsJcoQOtttw1ejvTS6SOBzhUA   26        talos-default-worker-1         worker         ["172.20.0.5","fd83:b1f7:fcb5:2802:cc80:3dff:fece:d89d"]
service/NVtfu1bT1QjhNq5xJFUZl8f8I8LOCnnpGrZfPpdN9WlB   20        talos-default-worker-2         worker         ["172.20.0.6","fd83:b1f7:fcb5:2802:2805:fbff:fe80:5ed2"]
service/b3DebkPaCRLTLLWaeRF1ejGaR0lK3m79jRJcPn0mfA6C   14        talos-default-controlplane-3   controlplane   ["172.20.0.4","fd83:b1f7:fcb5:2802:248f:1fff:fe5c:c3f"]

Each Affiliate ID is prefixed with k8s/ for data coming from the Kubernetes registry and with service/ for data coming from the discovery service.

Members

A member is an affiliate that has been approved to join the cluster. The members of the cluster can be obtained with:

$ talosctl get members
ID                             VERSION   HOSTNAME                       MACHINE TYPE   OS                ADDRESSES
talos-default-controlplane-1   2         talos-default-controlplane-1   controlplane   Talos (v1.4.8)   ["172.20.0.2","fd83:b1f7:fcb5:2802:8c13:71ff:feaf:7c94"]
talos-default-controlplane-2   1         talos-default-controlplane-2   controlplane   Talos (v1.4.8)   ["172.20.0.3","fd83:b1f7:fcb5:2802:986b:7eff:fec5:889d"]
talos-default-controlplane-3   1         talos-default-controlplane-3   controlplane   Talos (v1.4.8)   ["172.20.0.4","fd83:b1f7:fcb5:2802:248f:1fff:fe5c:c3f"]
talos-default-worker-1         1         talos-default-worker-1         worker         Talos (v1.4.8)   ["172.20.0.5","fd83:b1f7:fcb5:2802:cc80:3dff:fece:d89d"]
talos-default-worker-2         1         talos-default-worker-2         worker         Talos (v1.4.8)   ["172.20.0.6","fd83:b1f7:fcb5:2802:2805:fbff:fe80:5ed2"]

2.6 - Interactive Dashboard

A tool to inspect the running Talos machine state on the physical video console.

Interactive dashboard is enabled for all Talos platforms except for SBC images. The dashboard can be disabled with kernel parameter talos.dashboard.disabled=1.

The dashboard runs only on the physical video console (not serial console) on the 2nd virtual TTY. The first virtual TTY shows kernel logs same as in Talos <1.4.0. The virtual TTYs can be switched with <Alt+F1> and <Alt+F2> keys.

Keys <F1> - <Fn> can be used to switch between different screens of the dashboard.

The dashboard is using either UEFI framebuffer or VGA/VESA framebuffer (for legacy BIOS boot). For legacy BIOS boot screen resolution can be controlled with the vga= kernel parameter.

Summary Screen (`F1`)

Interactive Dashboard Summary Screen

The header shows brief information about the node:

hostname
Talos version
uptime
CPU and memory hardware information
CPU and memory load, number of processes

Table view presents summary information about the machine:

UUID (from SMBIOS data)
Cluster name (when the machine config is available)
Machine stage: Installing, Upgrading, Booting, Maintenance, Running, Rebooting, Shutting down, etc.
Machine stage readiness: checks Talos service status, static pod status, etc. (for Running stage)
Machine type: controlplane/worker
Number of members discovered in the cluster
Kubernetes version
Status of Kubernetes components: kubelet and Kubernetes controlplane components (only on controlplane machines)
Network information: Hostname, Addresses, Gateway, Connectivity, DNS and NTP servers

Bottom part of the screen shows kernel logs, same as on the virtual TTY 1.

Monitor Screen (`F2`)

Interactive Dashboard Monitor Screen

Monitor screen provides live view of the machine resource usage: CPU, memory, disk, network and processes.

Network Config Screen (`F3`)

Note: network config screen is only available for metal platform.

Interactive Dashboard Network Config Screen

Network config screen provides editing capabilities for the metal platform network configuration.

The screen is split into three sections:

the leftmost section provides a way to enter network configuration: hostname, DNS and NTP servers, configure the network interface either via DHCP or static IP address, etc.
the middle section shows the current network configuration.
the rightmost section shows the network configuration which will be applied after pressing “Save” button.

Once the platform network configuration is saved, it is immediately applied to the machine.

2.7 - Resetting a Machine

Steps on how to reset a Talos Linux machine to a clean state.

From time to time, it may be beneficial to reset a Talos machine to its “original” state. Bear in mind that this is a destructive action for the given machine. Doing this means removing the machine from Kubernetes, Etcd (if applicable), and clears any data on the machine that would normally persist a reboot.

CLI

WARNING: Running a talosctl reset on cloud VM’s might result in the VM being unable to boot as this wipes the entire disk. It might be more useful to just wipe the STATE and EPHEMERAL partitions on a cloud VM if not booting via iPXE. talosctl reset --system-labels-to-wipe STATE --system-labels-to-wipe EPHEMERAL

The API command for doing this is talosctl reset. There are a couple of flags as part of this command:

Flags:
      --graceful                        if true, attempt to cordon/drain node and leave etcd (if applicable) (default true)
      --reboot                          if true, reboot the node after resetting instead of shutting down
      --system-labels-to-wipe strings   if set, just wipe selected system disk partitions by label but keep other partitions intact keep other partitions intact

The graceful flag is especially important when considering HA vs. non-HA Talos clusters. If the machine is part of an HA cluster, a normal, graceful reset should work just fine right out of the box as long as the cluster is in a good state. However, if this is a single node cluster being used for testing purposes, a graceful reset is not an option since Etcd cannot be “left” if there is only a single member. In this case, reset should be used with --graceful=false to skip performing checks that would normally block the reset.

Kernel Parameter

Another way to reset a machine is to specify talos.experimental.wipe=system kernel parameter. If the machine got stuck in the boot loop and you access to the console you can use GRUB to specify this kernel argument. Then when Talos boots for the next time it will reset system disk and reboot.

Next steps can be to install Talos either using PXE boot or by mounting an ISO.

2.8 - Upgrading Talos Linux

Guide to upgrading a Talos Linux machine.

OS upgrades are effected by an API call, which can be sent via the talosctl CLI utility.

The upgrade API call passes a node the installer image to use to perform the upgrade. Each Talos version has a corresponding installer image, listed on the release page for the version, for example v1.4.8.

Upgrades use an A-B image scheme in order to facilitate rollbacks. This scheme retains the previous Talos kernel and OS image following each upgrade. If an upgrade fails to boot, Talos will roll back to the previous version. Likewise, Talos may be manually rolled back via API (or talosctl rollback), which will update the boot reference and reboot.

Unless explicitly told to preserve data, an upgrade will cause the node to wipe the EPHEMERAL partition, remove itself from the etcd cluster (if it is a controlplane node), and make itself as pristine as is possible. (This is the desired behavior except in specialised use cases such as single-node clusters.)

Note An upgrade of the Talos Linux OS will not (since v1.0) apply an upgrade to the Kubernetes version by default. Kubernetes upgrades should be managed separately per upgrading kubernetes.

Supported Upgrade Paths

Because Talos Linux is image based, an upgrade is almost the same as installing Talos, with the difference that the system has already been initialized with a configuration. The supported configuration may change between versions. The upgrade process should handle such changes transparently, but this migration is only tested between adjacent minor releases. Thus the recommended upgrade path is to always upgrade to the latest patch release of all intermediate minor releases.

For example, if upgrading from Talos 1.0 to Talos 1.2.4, the recommended upgrade path would be:

upgrade from 1.0 to latest patch of 1.0 - to v1.0.6
upgrade from v1.0.6 to latest patch of 1.1 - to v1.1.2
upgrade from v1.1.2 to v1.2.4

Before Upgrade to v1.4.8

There are no specific actions to be taken before an upgrade.

Video Walkthrough

To see a live demo of an upgrade of Talos Linux, see the video below:

After Upgrade to v1.4.8

There are no specific actions to be taken after an upgrade.

`talosctl upgrade`

To upgrade a Talos node, specify the node’s IP address and the installer container image for the version of Talos to upgrade to.

For instance, if your Talos node has the IP address 10.20.30.40 and you want to install the current version, you would enter a command such as:

  $ talosctl upgrade --nodes 10.20.30.40 \
      --image ghcr.io/siderolabs/installer:v1.4.8

There is an option to this command: --preserve, which will explicitly tell Talos to keep ephemeral data intact. In most cases, it is correct to let Talos perform its default action of erasing the ephemeral data. However, for a single-node control-plane, make sure that --preserve=true.

Rarely, an upgrade command will fail due to a process holding a file open on disk. In these cases, you can use the --stage flag. This puts the upgrade artifacts on disk, and adds some metadata to a disk partition that gets checked very early in the boot process, then reboots the node. On the reboot, Talos sees that it needs to apply an upgrade, and will do so immediately. Because this occurs in a just rebooted system, there will be no conflict with any files being held open. After the upgrade is applied, the node will reboot again, in order to boot into the new version. Note that because Talos Linux reboots via the kexec syscall, the extra reboot adds very little time.

Machine Configuration Changes

.machine.network.interfaces.bond now supports network device selectors for picking up the devices to bond.

Upgrade Sequence

When a Talos node receives the upgrade command, it cordons itself in Kubernetes, to avoid receiving any new workload. It then starts to drain its existing workload.

NOTE: If any of your workloads are sensitive to being shut down ungracefully, be sure to use the lifecycle.preStop Pod spec.

Once all of the workload Pods are drained, Talos will start shutting down its internal processes. If it is a control node, this will include etcd. If preserve is not enabled, Talos will leave etcd membership. (Talos ensures the etcd cluster is healthy and will remain healthy after our node leaves the etcd cluster, before allowing a control plane node to be upgraded.)

Once all the processes are stopped and the services are shut down, the filesystems will be unmounted. This allows Talos to produce a very clean upgrade, as close as possible to a pristine system. We verify the disk and then perform the actual image upgrade. We set the bootloader to boot once with the new kernel and OS image, then we reboot.

After the node comes back up and Talos verifies itself, it will make the bootloader change permanent, rejoin the cluster, and finally uncordon itself to receive new workloads.

FAQs

Q. What happens if an upgrade fails?

A. Talos Linux attempts to safely handle upgrade failures.

The most common failure is an invalid installer image reference. In this case, Talos will fail to download the upgraded image and will abort the upgrade.

Sometimes, Talos is unable to successfully kill off all of the disk access points, in which case it cannot safely unmount all filesystems to effect the upgrade. In this case, it will abort the upgrade and reboot. (upgrade --stage can ensure that upgrades can occur even when the filesytems cannot be unmounted.)

It is possible (especially with test builds) that the upgraded Talos system will fail to start. In this case, the node will be rebooted, and the bootloader will automatically use the previous Talos kernel and image, thus effectively rolling back the upgrade.

Lastly, it is possible that Talos itself will upgrade successfully, start up, and rejoin the cluster but your workload will fail to run on it, for whatever reason. This is when you would use the talosctl rollback command to revert back to the previous Talos version.

Q. Can upgrades be scheduled?

A. Because the upgrade sequence is API-driven, you can easily tie it in to your own business logic to schedule and coordinate your upgrades.

Q. Can the upgrade process be observed?

A. Yes, using the talosctl dmesg -f command. You can also use talosctl upgrade --wait, and optionally talosctl upgrade --wait --debug to observe kernel logs

Q. Are worker node upgrades handled differently from control plane node upgrades?

A. Short answer: no.

Long answer: Both node types follow the same set procedure. From the user’s standpoint, however, the processes are identical. However, since control plane nodes run additional services, such as etcd, there are some extra steps and checks performed on them. For instance, Talos will refuse to upgrade a control plane node if that upgrade would cause a loss of quorum for etcd. If multiple control plane nodes are asked to upgrade at the same time, Talos will protect the Kubernetes cluster by ensuring only one control plane node actively upgrades at any time, via checking etcd quorum. If running a single-node cluster, and you want to force an upgrade despite the loss of quorum, you can set preserve to true.

Q. Can I break my cluster by upgrading everything at once?

A. Possibly - it’s not recommended.

Nothing prevents the user from sending near-simultaneous upgrades to each node of the cluster - and while Talos Linux and Kubernetes can generally deal with this situation, other components of the cluster may not be able to recover from more than one node rebooting at a time. (e.g. any software that maintains a quorum or state across nodes, such as Rook/Ceph)

3 - Kubernetes Guides

Management of a Kubernetes Cluster hosted by Talos Linux

3.1 - Configuration

How to configure components of the Kubernetes cluster itself.

3.1.1 - Azure Cloud Controller Manager and CSI driver for storage

Guide on how to install the Azure Cloud Controller Manager and Container Storage Interface driver in Kubernetes

This is a guide for installing the Azure Cloud Provider and Azure CSI.

The cloud-provider-azure module is used for interacting with Azure cloud resources through Kubernetes and this guide will also walk through setting up the CSI storage component to set up a StorageClass for workloads to use on the cluster.

The steps in this guide could be used for any Kubernetes cluster with the addition of the patch applied to a Talos cluster.

Pre -requisites

This guide assumes a Talos cluster is already available and the user has an Azure account set up.

Instructions for installing Talos can be found in Talos Docs (Installation).
Instructions for installing talosctl and kubectl can be found in Talos Docs (Quickstart).

The applications in this guide will be installed using Helm.

Instructions for install helm can be found in the Helm Documentation.

Apply patch to Talos

There is an option in the Talos machine config to tell the control-plane to use an external controller manager.

This will apply an uninitialized label to a node when it registers to make it impossible to schedule workloads until the CCM has discovered that there is a new node in the cluster.

This configuration is referenced in Talos Docs (Machine Controller Manager).

To apply this to the Talos cluster, create a patch file or edit the machineconfig.

To create a patch file:

vim patch.yaml

Add the following to the patch.yaml file:

cluster:
  controllerManager:
    extraArgs:
      cloud-provider: external

Then, apply the patch with:

talosctl machineconfig patch patch.yaml

More information on applying machinconfig patches can be found at Talos Docs (Machine Config Patch).

Azure Configuration File

The Azure Cloud Controller Manager requires a configuration file to gain permissions on the cluster which will require gathering a few values from the Azure Portal and creating an app registration to give the CCM the permissions it needs.

This file is usually placed on the filesystem, but this guide will cover creating a secret to store this configuration instead.

App Registration

The App Registration is what we will use to authenticate to Azure for uploading blobs and creating resources.

For more information not in this guide or to see changes made to the app registration process, Azure’s documentation can be found here:

Azure Documentation (App Registration)

To create an App Registration in Azure:

Search for and Select Azure Active Directory.
Select App registrations, then select New registration.
Name the application, for example “example-app”.
Select a supported account type, which determines who can use the application.
Under Redirect URI, select Web for the type of application and enter the URI where the access token is sent to.
Select Register.

Collect the following values from Azure, as they will be needed for the Azure CCM configuration file.

Tenant ID
Subscription ID
Client ID
Client Secret

Add permissions for App Registration

The App registration only needs permissions to the Compute Gallery and the Storage Account.

Select the Resource Group the Talos cluster is deployed in
Select Access control (IAM)
Select Add role assignment
Select the role needed for the account.

NOTE: This will vary depending on what the CCM is being used for, but Virtual Machine Contributor is enough for the purposes if this installation guide.

Collect additional information

In the Azure Portal, collected the following values to be used in the configuration file, specific to the cluster the CCM is being installed on:

Resource Group
Location
Virtual Network name
Route Table name

Create the configuration file

Create a configuration file named azure.cfg

vim cloud.conf

Add the following to the azure.cfg file, but replace the values with the values gathered at the beginning of this guide.

{
  "cloud":"AzurePublicCloud",
  "tenantId": "${TENANT_ID}$",
  "subscriptionId": "${SUBSCRIPTION_ID}$",
  "aadClientId": "${CLIENT_ID}$",
  "aadClientSecret": "${CLIENT_SECRET}$",
  "resourceGroup": "${RESOURCE_GROUP}$",
  "location": "${LOCATION}",
  "loadBalancerSku": "standard",
  "securityGroupName": "${SECURITY_GROUP_NAME}",
  "vnetName": "${VIRTUAL_NETWORK_NAME}",
  "routeTableName": "${ROUTE_TABLE_NAME}"
}

Additional configurations can be found in the CCM docs here: Cloud Provider Azure configs.

A secret can be created in Kubernetes using the following command:

NOTE: This secret is created in the kube-system namespace because that is where the CCM and CSI components will be installed.

kubectl create secret generic azure-cloud-provider --from-file=cloud-config=./cloud.conf -n kube-system

Install the Azure Cloud Controller Manager

Find the version compatible with the Kubernetes version installed with the Talos cluster https://github.com/kubernetes-sigs/cloud-provider-azure/blob/master/README.md

To use the latest release add the following helm repo:

NOTE: To use a release specific to the Kubernetes version other than the latest version, replace master with the branch name specified in the version matrix above.

helm repo add cloud-provider-azure https://raw.githubusercontent.com/kubernetes-sigs/cloud-provider-azure/master/helm/repo

Update helm repositories:

helm repo update

Install the helm chart for cloud-provider-azure:

helm install azure-ccm cloud-provider-azure/cloud-provider-azure \
--set cloud-provider-azure.infra.clusterName="christian-tf" \
--set cloud-provider-azure.cloudControllerManager.cloudConfig='' \
--set cloud-provider-azure.cloudControllerManager.cloudConfigSecretName="azure-cloud-provider" \
--set cloud-provider-azure.cloudControllerManager.enableDynamicReloading="true" \
--set cloud-provider-azure.cloudControllerManager.configureCloudRoutes="true" \
--set cloud-provider-azure.cloudControllerManager.allocateNodeCidrs="true" \
--set cloud-provider-azure.cloudControllerManager.imageRepository="mcr.microsoft.com/oss/kubernetes"

Install the Azure CSI Driver

dependencies:

name: azuredisk-csi-driver repository: https://raw.githubusercontent.com/kubernetes-sigs/azuredisk-csi-driver/master/charts version: v1.27.1

Add the Azure CSI helm repo:

helm repo add azuredisk-csi-driver https://raw.githubusercontent.com/kubernetes-sigs/azuredisk-csi-driver/master/charts

Update helm repositories

helm repo update

helm install azure-csi azuredisk-csi-driver/azuredisk-csi-driver -n kube-system

Lastly, create a file for a StorageClass to use the CSI:

vim azure-ssd-lrs.yaml

Add the following contents to the file:

apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: azuredisk-standard-ssd-lrs
provisioner: disk.csi.azure.com
parameters:
  skuName: StandardSSD_LRS
reclaimPolicy: Delete
volumeBindingMode: Immediate
allowVolumeExpansion: true

Create the storageclass:

kubectl apply -f azure-ssd-lrs.yaml

Persistent Volume Claims can now be created for workloads in the cluster using the StorageClass created.

3.1.2 - Ceph Storage cluster with Rook

Guide on how to create a simple Ceph storage cluster with Rook for Kubernetes

Preparation

Talos Linux reserves an entire disk for the OS installation, so machines with multiple available disks are needed for a reliable Ceph cluster with Rook and Talos Linux. Rook requires that the block devices or partitions used by Ceph have no partitions or formatted filesystems before use. Rook also requires a minimum Kubernetes version of v1.16 and Helm v3.0 for installation of charts. It is highly recommended that the Rook Ceph overview is read and understood before deploying a Ceph cluster with Rook.

Installation

Creating a Ceph cluster with Rook requires two steps; first the Rook Operator needs to be installed which can be done with a Helm Chart. The example below installs the Rook Operator into the rook-ceph namespace, which is the default for a Ceph cluster with Rook.

$ helm repo add rook-release https://charts.rook.io/release
"rook-release" has been added to your repositories

$ helm install --create-namespace --namespace rook-ceph rook-ceph rook-release/rook-ceph
W0327 17:52:44.277830   54987 warnings.go:70] policy/v1beta1 PodSecurityPolicy is deprecated in v1.21+, unavailable in v1.25+
W0327 17:52:44.612243   54987 warnings.go:70] policy/v1beta1 PodSecurityPolicy is deprecated in v1.21+, unavailable in v1.25+
NAME: rook-ceph
LAST DEPLOYED: Sun Mar 27 17:52:42 2022
NAMESPACE: rook-ceph
STATUS: deployed
REVISION: 1
TEST SUITE: None
NOTES:
The Rook Operator has been installed. Check its status by running:
  kubectl --namespace rook-ceph get pods -l "app=rook-ceph-operator"

Visit https://rook.io/docs/rook/latest for instructions on how to create and configure Rook clusters

Important Notes:
- You must customize the 'CephCluster' resource in the sample manifests for your cluster.
- Each CephCluster must be deployed to its own namespace, the samples use `rook-ceph` for the namespace.
- The sample manifests assume you also installed the rook-ceph operator in the `rook-ceph` namespace.
- The helm chart includes all the RBAC required to create a CephCluster CRD in the same namespace.
- Any disk devices you add to the cluster in the 'CephCluster' must be empty (no filesystem and no partitions).

Once that is complete, the Ceph cluster can be installed with the official Helm Chart. The Chart can be installed with default values, which will attempt to use all nodes in the Kubernetes cluster, and all unused disks on each node for Ceph storage, and make available block storage, object storage, as well as a shared filesystem. Generally more specific node/device/cluster configuration is used, and the Rook documentation explains all the available options in detail. For this example the defaults will be adequate.

$ helm install --create-namespace --namespace rook-ceph rook-ceph-cluster --set operatorNamespace=rook-ceph rook-release/rook-ceph-cluster
NAME: rook-ceph-cluster
LAST DEPLOYED: Sun Mar 27 18:12:46 2022
NAMESPACE: rook-ceph
STATUS: deployed
REVISION: 1
TEST SUITE: None
NOTES:
The Ceph Cluster has been installed. Check its status by running:
  kubectl --namespace rook-ceph get cephcluster

Visit https://rook.github.io/docs/rook/latest/ceph-cluster-crd.html for more information about the Ceph CRD.

Important Notes:
- You can only deploy a single cluster per namespace
- If you wish to delete this cluster and start fresh, you will also have to wipe the OSD disks using `sfdisk`

Now the Ceph cluster configuration has been created, the Rook operator needs time to install the Ceph cluster and bring all the components online. The progression of the Ceph cluster state can be followed with the following command.

$ watch kubectl --namespace rook-ceph get cephcluster rook-ceph
Every 2.0s: kubectl --namespace rook-ceph get cephcluster rook-ceph

NAME        DATADIRHOSTPATH   MONCOUNT   AGE   PHASE         MESSAGE                 HEALTH   EXTERNAL
rook-ceph   /var/lib/rook     3          57s   Progressing   Configuring Ceph Mons

Depending on the size of the Ceph cluster and the availability of resources the Ceph cluster should become available, and with it the storage classes that can be used with Kubernetes Physical Volumes.

$ kubectl --namespace rook-ceph get cephcluster rook-ceph
NAME        DATADIRHOSTPATH   MONCOUNT   AGE   PHASE   MESSAGE                        HEALTH      EXTERNAL
rook-ceph   /var/lib/rook     3          40m   Ready   Cluster created successfully   HEALTH_OK

$ kubectl  get storageclass
NAME                   PROVISIONER                     RECLAIMPOLICY   VOLUMEBINDINGMODE   ALLOWVOLUMEEXPANSION   AGE
ceph-block (default)   rook-ceph.rbd.csi.ceph.com      Delete          Immediate           true                   77m
ceph-bucket            rook-ceph.ceph.rook.io/bucket   Delete          Immediate           false                  77m
ceph-filesystem        rook-ceph.cephfs.csi.ceph.com   Delete          Immediate           true                   77m

Talos Linux Considerations

It is important to note that a Rook Ceph cluster saves cluster information directly onto the node (by default dataDirHostPath is set to /var/lib/rook). If running only a single mon instance, cluster management is little bit more involved, as any time a Talos Linux node is reconfigured or upgraded, the partition that stores the /var file system is wiped, but the --preserve option of talosctl upgrade will ensure that doesn’t happen.

By default, Rook configues Ceph to have 3 mon instances, in which case the data stored in dataDirHostPath can be regenerated from the other mon instances. So when performing maintenance on a Talos Linux node with a Rook Ceph cluster (e.g. upgrading the Talos Linux version), it is imperative that care be taken to maintain the health of the Ceph cluster. Before upgrading, you should always check the health status of the Ceph cluster to ensure that it is healthy.

$ kubectl --namespace rook-ceph get cephclusters.ceph.rook.io rook-ceph
NAME        DATADIRHOSTPATH   MONCOUNT   AGE   PHASE   MESSAGE                        HEALTH      EXTERNAL
rook-ceph   /var/lib/rook     3          98m   Ready   Cluster created successfully   HEALTH_OK

If it is, you can begin the upgrade process for the Talos Linux node, during which time the Ceph cluster will become unhealthy as the node is reconfigured. Before performing any other action on the Talos Linux nodes, the Ceph cluster must return to a healthy status.

$ talosctl upgrade --nodes 172.20.15.5 --image ghcr.io/talos-systems/installer:v0.14.3
NODE          ACK                        STARTED
172.20.15.5   Upgrade request received   2022-03-27 20:29:55.292432887 +0200 CEST m=+10.050399758

$ kubectl --namespace rook-ceph get cephclusters.ceph.rook.io
NAME        DATADIRHOSTPATH   MONCOUNT   AGE   PHASE         MESSAGE                   HEALTH        EXTERNAL
rook-ceph   /var/lib/rook     3          99m   Progressing   Configuring Ceph Mgr(s)   HEALTH_WARN

$ kubectl --namespace rook-ceph wait --timeout=1800s --for=jsonpath='{.status.ceph.health}=HEALTH_OK' rook-ceph
cephcluster.ceph.rook.io/rook-ceph condition met

The above steps need to be performed for each Talos Linux node undergoing maintenance, one at a time.

Cleaning Up

Rook Ceph Cluster Removal

Removing a Rook Ceph cluster requires a few steps, starting with signalling to Rook that the Ceph cluster is really being destroyed. Then all Persistent Volumes (and Claims) backed by the Ceph cluster must be deleted, followed by the Storage Classes and the Ceph storage types.

$ kubectl --namespace rook-ceph patch cephcluster rook-ceph --type merge -p '{"spec":{"cleanupPolicy":{"confirmation":"yes-really-destroy-data"}}}'
cephcluster.ceph.rook.io/rook-ceph patched

$ kubectl delete storageclasses ceph-block ceph-bucket ceph-filesystem
storageclass.storage.k8s.io "ceph-block" deleted
storageclass.storage.k8s.io "ceph-bucket" deleted
storageclass.storage.k8s.io "ceph-filesystem" deleted

$ kubectl --namespace rook-ceph delete cephblockpools ceph-blockpool
cephblockpool.ceph.rook.io "ceph-blockpool" deleted

$ kubectl --namespace rook-ceph delete cephobjectstore ceph-objectstore
cephobjectstore.ceph.rook.io "ceph-objectstore" deleted

$ kubectl --namespace rook-ceph delete cephfilesystem ceph-filesystem
cephfilesystem.ceph.rook.io "ceph-filesystem" deleted

Once that is complete, the Ceph cluster itself can be removed, along with the Rook Ceph cluster Helm chart installation.

$ kubectl --namespace rook-ceph delete cephcluster rook-ceph
cephcluster.ceph.rook.io "rook-ceph" deleted

$ helm --namespace rook-ceph uninstall rook-ceph-cluster
release "rook-ceph-cluster" uninstalled

If needed, the Rook Operator can also be removed along with all the Custom Resource Definitions that it created.

$ helm --namespace rook-ceph uninstall rook-ceph
W0328 12:41:14.998307  147203 warnings.go:70] policy/v1beta1 PodSecurityPolicy is deprecated in v1.21+, unavailable in v1.25+
These resources were kept due to the resource policy:
[CustomResourceDefinition] cephblockpools.ceph.rook.io
[CustomResourceDefinition] cephbucketnotifications.ceph.rook.io
[CustomResourceDefinition] cephbuckettopics.ceph.rook.io
[CustomResourceDefinition] cephclients.ceph.rook.io
[CustomResourceDefinition] cephclusters.ceph.rook.io
[CustomResourceDefinition] cephfilesystemmirrors.ceph.rook.io
[CustomResourceDefinition] cephfilesystems.ceph.rook.io
[CustomResourceDefinition] cephfilesystemsubvolumegroups.ceph.rook.io
[CustomResourceDefinition] cephnfses.ceph.rook.io
[CustomResourceDefinition] cephobjectrealms.ceph.rook.io
[CustomResourceDefinition] cephobjectstores.ceph.rook.io
[CustomResourceDefinition] cephobjectstoreusers.ceph.rook.io
[CustomResourceDefinition] cephobjectzonegroups.ceph.rook.io
[CustomResourceDefinition] cephobjectzones.ceph.rook.io
[CustomResourceDefinition] cephrbdmirrors.ceph.rook.io
[CustomResourceDefinition] objectbucketclaims.objectbucket.io
[CustomResourceDefinition] objectbuckets.objectbucket.io

release "rook-ceph" uninstalled

$ kubectl delete crds cephblockpools.ceph.rook.io cephbucketnotifications.ceph.rook.io cephbuckettopics.ceph.rook.io \
                      cephclients.ceph.rook.io cephclusters.ceph.rook.io cephfilesystemmirrors.ceph.rook.io \
                      cephfilesystems.ceph.rook.io cephfilesystemsubvolumegroups.ceph.rook.io \
                      cephnfses.ceph.rook.io cephobjectrealms.ceph.rook.io cephobjectstores.ceph.rook.io \
                      cephobjectstoreusers.ceph.rook.io cephobjectzonegroups.ceph.rook.io cephobjectzones.ceph.rook.io \
                      cephrbdmirrors.ceph.rook.io objectbucketclaims.objectbucket.io objectbuckets.objectbucket.io
customresourcedefinition.apiextensions.k8s.io "cephblockpools.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephbucketnotifications.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephbuckettopics.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephclients.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephclusters.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephfilesystemmirrors.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephfilesystems.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephfilesystemsubvolumegroups.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephnfses.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephobjectrealms.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephobjectstores.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephobjectstoreusers.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephobjectzonegroups.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephobjectzones.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "cephrbdmirrors.ceph.rook.io" deleted
customresourcedefinition.apiextensions.k8s.io "objectbucketclaims.objectbucket.io" deleted
customresourcedefinition.apiextensions.k8s.io "objectbuckets.objectbucket.io" deleted

Talos Linux Rook Metadata Removal

If the Rook Operator is cleanly removed following the above process, the node metadata and disks should be clean and ready to be re-used. In the case of an unclean cluster removal, there may be still a few instances of metadata stored on the system disk, as well as the partition information on the storage disks. First the node metadata needs to be removed, make sure to update the nodeName with the actual name of a storage node that needs cleaning, and path with the Rook configuration dataDirHostPath set when installing the chart. The following will need to be repeated for each node used in the Rook Ceph cluster.

$ cat <<EOF | kubectl apply -f -
apiVersion: v1
kind: Pod
metadata:
  name: disk-clean
spec:
  restartPolicy: Never
  nodeName: <storage-node-name>
  volumes:
  - name: rook-data-dir
    hostPath:
      path: <dataDirHostPath>
  containers:
  - name: disk-clean
    image: busybox
    securityContext:
      privileged: true
    volumeMounts:
    - name: rook-data-dir
      mountPath: /node/rook-data
    command: ["/bin/sh", "-c", "rm -rf /node/rook-data/*"]
EOF
pod/disk-clean created

$ kubectl wait --timeout=900s --for=jsonpath='{.status.phase}=Succeeded' pod disk-clean
pod/disk-clean condition met

$ kubectl delete pod disk-clean
pod "disk-clean" deleted

Lastly, the disks themselves need the partition and filesystem data wiped before they can be reused. Again, the following as to be repeated for each node and disk used in the Rook Ceph cluster, updating nodeName and of= in the command as needed.

$ cat <<EOF | kubectl apply -f -
apiVersion: v1
kind: Pod
metadata:
  name: disk-wipe
spec:
  restartPolicy: Never
  nodeName: <storage-node-name>
  containers:
  - name: disk-wipe
    image: busybox
    securityContext:
      privileged: true
    command: ["/bin/sh", "-c", "dd if=/dev/zero bs=1M count=100 oflag=direct of=<device>"]
EOF
pod/disk-wipe created

$ kubectl wait --timeout=900s --for=jsonpath='{.status.phase}=Succeeded' pod disk-wipe
pod/disk-wipe condition met

$ kubectl delete pod disk-clean
pod "disk-wipe" deleted

3.1.3 - Cluster Endpoint

How to explicitly set up an endpoint for the cluster API

In this section, we will step through the configuration of a Talos based Kubernetes cluster. There are three major components we will configure:

apid and talosctl
the controlplane nodes
the worker nodes

Talos enforces a high level of security by using mutual TLS for authentication and authorization.

We recommend that the configuration of Talos be performed by a cluster owner. A cluster owner should be a person of authority within an organization, perhaps a director, manager, or senior member of a team. They are responsible for storing the root CA, and distributing the PKI for authorized cluster administrators.

Recommended settings

Talos runs great out of the box, but if you tweak some minor settings it will make your life a lot easier in the future. This is not a requirement, but rather a document to explain some key settings.

Endpoint

To configure the talosctl endpoint, it is recommended you use a resolvable DNS name. This way, if you decide to upgrade to a multi-controlplane cluster you only have to add the ip address to the hostname configuration. The configuration can either be done on a Loadbalancer, or simply trough DNS.

For example:

This is in the config file for the cluster e.g. controlplane.yaml and worker.yaml. for more details, please see: v1alpha1 endpoint configuration

.....
cluster:
  controlPlane:
    endpoint: https://endpoint.example.local:6443
.....

If you have a DNS name as the endpoint, you can upgrade your talos cluster with multiple controlplanes in the future (if you don’t have a multi-controlplane setup from the start) Using a DNS name generates the corresponding Certificates (Kubernetes and Talos) for the correct hostname.

3.1.4 - Deploying Metrics Server

In this guide you will learn how to set up metrics-server.

Metrics Server enables use of the Horizontal Pod Autoscaler and Vertical Pod Autoscaler. It does this by gathering metrics data from the kubelets in a cluster. By default, the certificates in use by the kubelets will not be recognized by metrics-server. This can be solved by either configuring metrics-server to do no validation of the TLS certificates, or by modifying the kubelet configuration to rotate its certificates and use ones that will be recognized by metrics-server.

Node Configuration

To enable kubelet certificate rotation, all nodes should have the following Machine Config snippet:

machine:
  kubelet:
    extraArgs:
      rotate-server-certificates: true

Install During Bootstrap

We will want to ensure that new certificates for the kubelets are approved automatically. This can easily be done with the Kubelet Serving Certificate Approver, which will automatically approve the Certificate Signing Requests generated by the kubelets.

We can have Kubelet Serving Certificate Approver and metrics-server installed on the cluster automatically during bootstrap by adding the following snippet to the Cluster Config of the node that will be handling the bootstrap process:

cluster:
  extraManifests:
    - https://raw.githubusercontent.com/alex1989hu/kubelet-serving-cert-approver/main/deploy/standalone-install.yaml
    - https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml

Install After Bootstrap

If you choose not to use extraManifests to install Kubelet Serving Certificate Approver and metrics-server during bootstrap, you can install them once the cluster is online using kubectl:

kubectl apply -f https://raw.githubusercontent.com/alex1989hu/kubelet-serving-cert-approver/main/deploy/standalone-install.yaml
kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml

3.1.5 - iSCSI Storage with Synology CSI

Automatically provision iSCSI volumes on a Synology NAS with the synology-csi driver.

Background

Synology is a company that specializes in Network Attached Storage (NAS) devices. They provide a number of features within a simple web OS, including an LDAP server, Docker support, and (perhaps most relevant to this guide) function as an iSCSI host. The focus of this guide is to allow a Kubernetes cluster running on Talos to provision Kubernetes storage (both dynamic or static) on a Synology NAS using a direct integration, rather than relying on an intermediary layer like Rook/Ceph or Maystor.

This guide assumes a very basic familiarity with iSCSI terminology (LUN, iSCSI target, etc.).

Prerequisites

Synology NAS running DSM 7.0 or above
Provisioned Talos cluster running Kubernetes v1.20 or above
(Optional) Both Volume Snapshot CRDs and the common snapshot controller must be installed in your Kubernetes cluster if you want to use the Snapshot feature

Setting up the Synology user account

The synology-csi controller interacts with your NAS in two different ways: via the API and via the iSCSI protocol. Actions such as creating a new iSCSI target or deleting an old one are accomplished via the Synology API, and require administrator access. On the other hand, mounting the disk to a pod and reading from / writing to it will utilize iSCSI. Because you can only authenticate with one account per DSM configured, that account needs to have admin privileges. In order to minimize access in the case of these credentials being compromised, you should configure the account with the lease possible amount of access – explicitly specify “No Access” on all volumes when configuring the user permissions.

Setting up the Synology CSI

Note: this guide is paraphrased from the Synology CSI readme. Please consult the readme for more in-depth instructions and explanations.

Clone the git repository.

git clone https://github.com/zebernst/synology-csi-talos.git

While Synology provides some automated scripts to deploy the CSI driver, they can be finicky especially when making changes to the source code. We will be configuring and deploying things manually in this guide.

The relevant files we will be touching are in the following locations:

.
├── Dockerfile
├── Makefile
├── config
│   └── client-info-template.yml
└── deploy
    └── kubernetes
        └── v1.20
            ├── controller.yml
            ├── csi-driver.yml
            ├── namespace.yml
            ├── node.yml
            ├── snapshotter
            │   ├── snapshotter.yaml
            │   └── volume-snapshot-class.yml
            └── storage-class.yml

Configure connection info

Use config/client-info-template.yml as an example to configure the connection information for DSM. You can specify one or more storage systems on which the CSI volumes will be created. See below for an example:

---
clients:
- host: 192.168.1.1   # ipv4 address or domain of the DSM
  port: 5000          # port for connecting to the DSM
  https: false        # set this true to use https. you need to specify the port to DSM HTTPS port as well
  username: username  # username
  password: password  # password

Create a Kubernetes secret using the client information config file.

kubectl create secret -n synology-csi generic client-info-secret --from-file=config/client-info.yml

Note that if you rename the secret to something other than client-info-secret, make sure you update the corresponding references in the deployment manifests as well.

Build the Talos-compatible image

Modify the Makefile so that the image is built and tagged under your GitHub Container Registry username:

REGISTRY_NAME=ghcr.io/<username>

When you run make docker-build or make docker-build-multiarch, it will push the resulting image to ghcr.io/<username>/synology-csi:v1.1.0. Ensure that you find and change any reference to synology/synology-csi:v1.1.0 to point to your newly-pushed image within the deployment manifests.

Configure the CSI driver

By default, the deployment manifests include one storage class and one volume snapshot class. See below for examples:

---
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  annotations:
    storageclass.kubernetes.io/is-default-class: "false"
  name: syno-storage
provisioner: csi.san.synology.com
parameters:
  fsType: 'ext4'
  dsm: '192.168.1.1'
  location: '/volume1'
reclaimPolicy: Retain
allowVolumeExpansion: true
---
apiVersion: snapshot.storage.k8s.io/v1
kind: VolumeSnapshotClass
metadata:
  name: syno-snapshot
  annotations:
    storageclass.kubernetes.io/is-default-class: "false"
driver: csi.san.synology.com
deletionPolicy: Delete
parameters:
  description: 'Kubernetes CSI'

It can be useful to configure multiple different StorageClasses. For example, a popular strategy is to create two nearly identical StorageClasses, with one configured with reclaimPolicy: Retain and the other with reclaimPolicy: Delete. Alternately, a workload may require a specific filesystem, such as ext4. If a Synology NAS is going to be the most common way to configure storage on your cluster, it can be convenient to add the storageclass.kubernetes.io/is-default-class: "true" annotation to one of your StorageClasses.

The following table details the configurable parameters for the Synology StorageClass.

Name	Type	Description	Default	Supported protocols
dsm	string	The IPv4 address of your DSM, which must be included in the `client-info.yml` for the CSI driver to log in to DSM	-	iSCSI, SMB
location	string	The location (/volume1, /volume2, …) on DSM where the LUN for PersistentVolume will be created	-	iSCSI, SMB
fsType	string	The formatting file system of the PersistentVolumes when you mount them on the pods. This parameter only works with iSCSI. For SMB, the fsType is always ‘cifs‘.	`ext4`	iSCSI
protocol	string	The backing storage protocol. Enter ‘iscsi’ to create LUNs or ‘smb‘ to create shared folders on DSM.	`iscsi`	iSCSI, SMB
csi.storage.k8s.io/node-stage-secret-name	string	The name of node-stage-secret. Required if DSM shared folder is accessed via SMB.	-	SMB
csi.storage.k8s.io/node-stage-secret-namespace	string	The namespace of node-stage-secret. Required if DSM shared folder is accessed via SMB.	-	SMB

The VolumeSnapshotClass can be similarly configured with the following parameters:

Name	Type	Description	Default	Supported protocols
description	string	The description of the snapshot on DSM	-	iSCSI
is_locked	string	Whether you want to lock the snapshot on DSM	`false`	iSCSI, SMB

Apply YAML manifests

Once you have created the desired StorageClass(es) and VolumeSnapshotClass(es), the final step is to apply the Kubernetes manifests against the cluster. The easiest way to apply them all at once is to create a kustomization.yaml file in the same directory as the manifests and use Kustomize to apply:

kubectl apply -k path/to/manifest/directory

Alternately, you can apply each manifest one-by-one:

kubectl apply -f <file>

Run performance tests

In order to test the provisioning, mounting, and performance of using a Synology NAS as Kubernetes persistent storage, use the following command:

kubectl apply -f speedtest.yaml

Content of speedtest.yaml (source)

kind: PersistentVolumeClaim
apiVersion: v1
metadata:
  name: test-claim
spec:
#  storageClassName: syno-storage
  accessModes:
  - ReadWriteMany
  resources:
    requests:
      storage: 5G
---
apiVersion: batch/v1
kind: Job
metadata:
  name: read
spec:
  template:
    metadata:
      name: read
      labels:
        app: speedtest
        job: read
    spec:
      containers:
      - name: read
        image: ubuntu:xenial
        command: ["dd","if=/mnt/pv/test.img","of=/dev/null","bs=8k"]
        volumeMounts:
        - mountPath: "/mnt/pv"
          name: test-volume
      volumes:
      - name: test-volume
        persistentVolumeClaim:
          claimName: test-claim
      restartPolicy: Never
---
apiVersion: batch/v1
kind: Job
metadata:
  name: write
spec:
  template:
    metadata:
      name: write
      labels:
        app: speedtest
        job: write
    spec:
      containers:
      - name: write
        image: ubuntu:xenial
        command: ["dd","if=/dev/zero","of=/mnt/pv/test.img","bs=1G","count=1","oflag=dsync"]
        volumeMounts:
        - mountPath: "/mnt/pv"
          name: test-volume
      volumes:
      - name: test-volume
        persistentVolumeClaim:
          claimName: test-claim
      restartPolicy: Never

If these two jobs complete successfully, use the following commands to get the results of the speed tests:

# Pod logs for read test:
kubectl logs -l app=speedtest,job=read

# Pod logs for write test:
kubectl logs -l app=speedtest,job=write

When you’re satisfied with the results of the test, delete the artifacts created from the speedtest:

kubectl delete -f speedtest.yaml

3.1.6 - Local Storage

Using local storage with OpenEBS Jiva

If you want to use replicated storage leveraging disk space from a local disk with Talos Linux installed, OpenEBS Jiva is a great option. This requires installing the iscsi-tools system extension.

Since OpenEBS Jiva is a replicated storage, it’s recommended to have at least three nodes where sufficient local disk space is available. The documentation will follow installing OpenEBS Jiva via the offical Helm chart. Since Talos is different from standard Operating Systems, the OpenEBS components need a little tweaking after the Helm installation. Refer to the OpenEBS Jiva documentation if you need further customization.

NB: Also note that the Talos nodes need to be upgraded with --preserve set while running OpenEBS Jiva, otherwise you risk losing data. Even though it’s possible to recover data from other replicas if the node is wiped during an upgrade, this can require extra operational knowledge to recover, so it’s highly recommended to use --preserve to avoid data loss.

Preparing the nodes

Create a machine config patch with the contents below and save as patch.yaml

- op: add
  path: /machine/install/extensions
  value:
    - image: ghcr.io/siderolabs/iscsi-tools:v0.1.4
- op: add
  path: /machine/kubelet/extraMounts
  value:
    - destination: /var/openebs/local
      type: bind
      source: /var/openebs/local
      options:
        - bind
        - rshared
        - rw

Apply the machine config to all the nodes using talosctl:

talosctl -e <endpoint ip/hostname> -n <node ip/hostname> patch mc -p @patch.yaml

To install the system extension, the node needs to be upgraded. If there is no new release of Talos, the node can be upgraded to the same version as the existing Talos version.

Run the following command on each nodes subsequently:

talosctl -e <endpoint ip/hostname> -n <node ip/hostname> upgrade --image=ghcr.io/siderolabs/installer:v1.4.8

Once the node has upgraded and booted successfully the extension status can be verfied by running the following command:

talosctl -e <endpoint ip/hostname> -n <node ip/hostname> get extensions

An output similar to below can be observed:

NODE            NAMESPACE   TYPE              ID                                          VERSION   NAME          VERSION
192.168.20.61   runtime     ExtensionStatus   000.ghcr.io-siderolabs-iscsi-tools-v0.1.1   1         iscsi-tools   v0.1.1

The service status can be checked by running the following command:

talosctl -e <endpoint ip/hostname> -n <node ip/hostname> services

You should see that the ext-tgtd and the ext-iscsid services are running.

NODE            SERVICE      STATE     HEALTH   LAST CHANGE     LAST EVENT
192.168.20.51   apid         Running   OK       64h57m15s ago   Health check successful
192.168.20.51   containerd   Running   OK       64h57m23s ago   Health check successful
192.168.20.51   cri          Running   OK       64h57m20s ago   Health check successful
192.168.20.51   etcd         Running   OK       64h55m29s ago   Health check successful
192.168.20.51   ext-iscsid   Running   ?        64h57m19s ago   Started task ext-iscsid (PID 4040) for container ext-iscsid
192.168.20.51   ext-tgtd     Running   ?        64h57m19s ago   Started task ext-tgtd (PID 3999) for container ext-tgtd
192.168.20.51   kubelet      Running   OK       38h14m10s ago   Health check successful
192.168.20.51   machined     Running   ?        64h57m29s ago   Service started as goroutine
192.168.20.51   trustd       Running   OK       64h57m19s ago   Health check successful
192.168.20.51   udevd        Running   OK       64h57m21s ago   Health check successful

Install OpenEBS Jiva

helm repo add openebs-jiva https://openebs.github.io/jiva-operator
helm repo update
helm upgrade --install --create-namespace --namespace openebs --version 3.2.0 openebs-jiva openebs-jiva/jiva

This will create a storage class named openebs-jiva-csi-default which can be used for workloads. The storage class named openebs-hostpath is used by jiva to create persistent volumes backed by local storage and then used for replicated storage by the jiva controller.

Patching the Namespace

when using the default Pod Security Admissions created by Talos you need the following labels on your namespace:

    pod-security.kubernetes.io/audit: privileged
    pod-security.kubernetes.io/enforce: privileged
    pod-security.kubernetes.io/warn: privileged

or via kubectl:

kubectl label ns openebs pod-security.kubernetes.io/audit=privileged pod-security.kubernetes.io/enforce=privileged pod-security.kubernetes.io/warn=privileged

Number of Replicas

By Default Jiva uses 3 replicas if your cluster consists of lesser nodes consider setting defaultPolicy.replicas to the number of nodes in your cluster e.g. 2.

Patching the jiva installation

Since Jiva assumes iscisd to be running natively on the host and not as a Talos extension service, we need to modify the CSI node daemonset to enable it to find the PID of the iscsid service. The default config map used by Jiva also needs to be modified so that it can execute iscsiadm commands inside the PID namespace of the iscsid service.

Start by creating a configmap definition named config.yaml as below:

apiVersion: v1
kind: ConfigMap
metadata:
  labels:
    app.kubernetes.io/managed-by: pulumi
  name: openebs-jiva-csi-iscsiadm
  namespace: openebs
data:
  iscsiadm: |
    #!/bin/sh
    iscsid_pid=$(pgrep iscsid)

    nsenter --mount="/proc/${iscsid_pid}/ns/mnt" --net="/proc/${iscsid_pid}/ns/net" -- /usr/local/sbin/iscsiadm "$@"

Replace the existing config map with the above config map by running the following command:

kubectl --namespace openebs apply --filename config.yaml

Now we need to update the jiva CSI daemonset to run with hostPID: true so it can find the PID of the iscsid service, by running the following command:

kubectl --namespace openebs patch daemonset openebs-jiva-csi-node --type=json --patch '[{"op": "add", "path": "/spec/template/spec/hostPID", "value": true}]'

Testing a simple workload

In order to test the Jiva installation, let’s first create a PVC referencing the openebs-jiva-csi-default storage class:

kind: PersistentVolumeClaim
apiVersion: v1
metadata:
  name: example-jiva-csi-pvc
spec:
  storageClassName: openebs-jiva-csi-default
  accessModes:
    - ReadWriteOnce
  resources:
    requests:
      storage: 4Gi

and then create a deployment using the above PVC:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: fio
spec:
  selector:
    matchLabels:
      name: fio
  replicas: 1
  strategy:
    type: Recreate
    rollingUpdate: null
  template:
    metadata:
      labels:
        name: fio
    spec:
      containers:
      - name: perfrunner
        image: openebs/tests-fio
        command: ["/bin/bash"]
        args: ["-c", "while true ;do sleep 50; done"]
        volumeMounts:
        - mountPath: /datadir
          name: fio-vol
      volumes:
      - name: fio-vol
        persistentVolumeClaim:
          claimName: example-jiva-csi-pvc

You can clean up the test resources by running the following command:

kubectl delete deployment fio
kubectl delete pvc example-jiva-csi-pvc

3.1.7 - Pod Security

Enabling Pod Security Admission plugin to configure Pod Security Standards.

Kubernetes deprecated Pod Security Policy as of v1.21, and it is going to be removed in v1.25. Pod Security Policy was replaced with Pod Security Admission. Pod Security Admission is alpha in v1.22 (requires a feature gate) and beta in v1.23 (enabled by default).

In this guide we are going to enable and configure Pod Security Admission in Talos.

Configuration

Talos provides default Pod Security Admission in the machine configuration:

apiVersion: pod-security.admission.config.k8s.io/v1alpha1
kind: PodSecurityConfiguration
defaults:
    enforce: "baseline"
    enforce-version: "latest"
    audit: "restricted"
    audit-version: "latest"
    warn: "restricted"
    warn-version: "latest"
exemptions:
    usernames: []
    runtimeClasses: []
    namespaces: [kube-system]

This is a cluster-wide configuration for the Pod Security Admission plugin:

by default baseline Pod Security Standard profile is enforced
more strict restricted profile is not enforced, but API server warns about found issues

This default policy can be modified by updating the generated machine configuration before the cluster is created or on the fly by using the talosctl CLI utility.

Verify current admission plugin configuration with:

$ talosctl get admissioncontrolconfigs.kubernetes.talos.dev admission-control -o yaml
node: 172.20.0.2
metadata:
    namespace: controlplane
    type: AdmissionControlConfigs.kubernetes.talos.dev
    id: admission-control
    version: 1
    owner: config.K8sControlPlaneController
    phase: running
    created: 2022-02-22T20:28:21Z
    updated: 2022-02-22T20:28:21Z
spec:
    config:
        - name: PodSecurity
          configuration:
            apiVersion: pod-security.admission.config.k8s.io/v1alpha1
            defaults:
                audit: restricted
                audit-version: latest
                enforce: baseline
                enforce-version: latest
                warn: restricted
                warn-version: latest
            exemptions:
                namespaces:
                    - kube-system
                runtimeClasses: []
                usernames: []
            kind: PodSecurityConfiguration

Usage

Create a deployment that satisfies the baseline policy but gives warnings on restricted policy:

$ kubectl create deployment nginx --image=nginx
Warning: would violate PodSecurity "restricted:latest": allowPrivilegeEscalation != false (container "nginx" must set securityContext.allowPrivilegeEscalation=false), unrestricted capabilities (container "nginx" must set securityContext.capabilities.drop=["ALL"]), runAsNonRoot != true (pod or container "nginx" must set securityContext.runAsNonRoot=true), seccompProfile (pod or container "nginx" must set securityContext.seccompProfile.type to "RuntimeDefault" or "Localhost")
deployment.apps/nginx created
$ kubectl get pods
NAME                     READY   STATUS    RESTARTS   AGE
nginx-85b98978db-j68l8   1/1     Running   0          2m3s

Create a daemonset which fails to meet requirements of the baseline policy:

apiVersion: apps/v1
kind: DaemonSet
metadata:
  labels:
    app: debug-container
  name: debug-container
  namespace: default
spec:
  revisionHistoryLimit: 10
  selector:
    matchLabels:
      app: debug-container
  template:
    metadata:
      creationTimestamp: null
      labels:
        app: debug-container
    spec:
      containers:
      - args:
        - "360000"
        command:
        - /bin/sleep
        image: ubuntu:latest
        imagePullPolicy: IfNotPresent
        name: debug-container
        resources: {}
        securityContext:
          privileged: true
        terminationMessagePath: /dev/termination-log
        terminationMessagePolicy: File
      dnsPolicy: ClusterFirstWithHostNet
      hostIPC: true
      hostPID: true
      hostNetwork: true
      restartPolicy: Always
      schedulerName: default-scheduler
      securityContext: {}
      terminationGracePeriodSeconds: 30
  updateStrategy:
    rollingUpdate:
      maxSurge: 0
      maxUnavailable: 1
    type: RollingUpdate

$ kubectl apply -f debug.yaml
Warning: would violate PodSecurity "restricted:latest": host namespaces (hostNetwork=true, hostPID=true, hostIPC=true), privileged (container "debug-container" must not set securityContext.privileged=true), allowPrivilegeEscalation != false (container "debug-container" must set securityContext.allowPrivilegeEscalation=false), unrestricted capabilities (container "debug-container" must set securityContext.capabilities.drop=["ALL"]), runAsNonRoot != true (pod or container "debug-container" must set securityContext.runAsNonRoot=true), seccompProfile (pod or container "debug-container" must set securityContext.seccompProfile.type to "RuntimeDefault" or "Localhost")
daemonset.apps/debug-container created

Daemonset debug-container gets created, but no pods are scheduled:

$ kubectl get ds
NAME              DESIRED   CURRENT   READY   UP-TO-DATE   AVAILABLE   NODE SELECTOR   AGE
debug-container   0         0         0       0            0           <none>          34s

Pod Security Admission plugin errors are in the daemonset events:

$ kubectl describe ds debug-container
...
  Warning  FailedCreate  92s                daemonset-controller  Error creating: pods "debug-container-kwzdj" is forbidden: violates PodSecurity "baseline:latest": host namespaces (hostNetwork=true, hostPID=true, hostIPC=true), privileged (container "debug-container" must not set securityContext.privileged=true)

Pod Security Admission configuration can also be overridden on a namespace level:

$ kubectl label ns default pod-security.kubernetes.io/enforce=privileged
namespace/default labeled
$ kubectl get ds
NAME              DESIRED   CURRENT   READY   UP-TO-DATE   AVAILABLE   NODE SELECTOR   AGE
debug-container   2         2         0       2            0           <none>          4s

As enforce policy was updated to the privileged for the default namespace, debug-container is now successfully running.

3.1.8 - Seccomp Profiles

Using custom Seccomp Profiles with Kubernetes workloads.

Seccomp stands for secure computing mode and has been a feature of the Linux kernel since version 2.6.12. It can be used to sandbox the privileges of a process, restricting the calls it is able to make from userspace into the kernel.

Refer the Kubernetes Seccomp Guide for more details.

In this guide we are going to configure a custom Seccomp Profile that logs all syscalls made by the workload.

Preparing the nodes

Create a machine config path with the contents below and save as patch.yaml

machine:
  seccompProfiles:
    - name: audit.json
      value:
        defaultAction: SCMP_ACT_LOG

Apply the machine config to all the nodes using talosctl:

talosctl -e <endpoint ip/hostname> -n <node ip/hostname> patch mc -p @patch.yaml

This would create a seccomp profile name audit.json on the node at /var/lib/kubelet/seccomp/profiles.

The profiles can be used by Kubernetes pods by specfying the pod securityContext as below:

spec:
  securityContext:
    seccompProfile:
      type: Localhost
      localhostProfile: profiles/audit.json

Note that the localhostProfile uses the name of the profile created under profiles directory. So make sure to use path as profiles/<profile-name.json>

This can be verfied by running the below commands:

talosctl -e <endpoint ip/hostname> -n <node ip/hostname> get seccompprofiles

An output similar to below can be observed:

NODE       NAMESPACE   TYPE             ID           VERSION
10.5.0.3   cri         SeccompProfile   audit.json   1

The content of the seccomp profile can be viewed by running the below command:

talosctl -e <endpoint ip/hostname> -n <node ip/hostname> read /var/lib/kubelet/seccomp/profiles/audit.json

An output similar to below can be observed:

{"defaultAction":"SCMP_ACT_LOG"}

Create a Kubernetes workload that uses the custom Seccomp Profile

Here we’ll be using an example workload from the Kubernetes documentation.

First open up a second terminal and run the following talosctl command so that we can view the Syscalls being logged in realtime:

talosctl -e <endpoint ip/hostname> -n <node ip/hostname> dmesg --follow --tail

Now deploy the example workload from the Kubernetes documentation:

kubectl apply -f https://k8s.io/examples/pods/security/seccomp/ga/audit-pod.yaml

Once the pod starts running the terminal running talosctl dmesg command from above should log similar to below:

10.5.0.3: kern:    info: [2022-07-28T11:49:42.489473063Z]: cni0: port 1(veth32488a86) entered blocking state
10.5.0.3: kern:    info: [2022-07-28T11:49:42.490852063Z]: cni0: port 1(veth32488a86) entered disabled state
10.5.0.3: kern:    info: [2022-07-28T11:49:42.492470063Z]: device veth32488a86 entered promiscuous mode
10.5.0.3: kern:    info: [2022-07-28T11:49:42.503105063Z]: IPv6: ADDRCONF(NETDEV_CHANGE): eth0: link becomes ready
10.5.0.3: kern:    info: [2022-07-28T11:49:42.503944063Z]: IPv6: ADDRCONF(NETDEV_CHANGE): veth32488a86: link becomes ready
10.5.0.3: kern:    info: [2022-07-28T11:49:42.504764063Z]: cni0: port 1(veth32488a86) entered blocking state
10.5.0.3: kern:    info: [2022-07-28T11:49:42.505423063Z]: cni0: port 1(veth32488a86) entered forwarding state
10.5.0.3: kern: warning: [2022-07-28T11:49:44.873616063Z]: kauditd_printk_skb: 14 callbacks suppressed
10.5.0.3: kern:  notice: [2022-07-28T11:49:44.873619063Z]: audit: type=1326 audit(1659008985.445:25): auid=4294967295 uid=0 gid=0 ses=4294967295 pid=2784 comm="runc:[2:INIT]" exe="/" sig=0 arch=c000003e syscall=3 compat=0 ip=0x55ec0657bd3b code=0x7ffc0000
10.5.0.3: kern:  notice: [2022-07-28T11:49:44.876609063Z]: audit: type=1326 audit(1659008985.445:26): auid=4294967295 uid=0 gid=0 ses=4294967295 pid=2784 comm="runc:[2:INIT]" exe="/" sig=0 arch=c000003e syscall=3 compat=0 ip=0x55ec0657bd3b code=0x7ffc0000
10.5.0.3: kern:  notice: [2022-07-28T11:49:44.878789063Z]: audit: type=1326 audit(1659008985.449:27): auid=4294967295 uid=0 gid=0 ses=4294967295 pid=2784 comm="runc:[2:INIT]" exe="/" sig=0 arch=c000003e syscall=257 compat=0 ip=0x55ec0657bdaa code=0x7ffc0000
10.5.0.3: kern:  notice: [2022-07-28T11:49:44.886693063Z]: audit: type=1326 audit(1659008985.461:28): auid=4294967295 uid=0 gid=0 ses=4294967295 pid=2784 comm="runc:[2:INIT]" exe="/" sig=0 arch=c000003e syscall=202 compat=0 ip=0x55ec06532b43 code=0x7ffc0000
10.5.0.3: kern:  notice: [2022-07-28T11:49:44.888764063Z]: audit: type=1326 audit(1659008985.461:29): auid=4294967295 uid=0 gid=0 ses=4294967295 pid=2784 comm="runc:[2:INIT]" exe="/" sig=0 arch=c000003e syscall=202 compat=0 ip=0x55ec06532b43 code=0x7ffc0000
10.5.0.3: kern:  notice: [2022-07-28T11:49:44.891009063Z]: audit: type=1326 audit(1659008985.461:30): auid=4294967295 uid=0 gid=0 ses=4294967295 pid=2784 comm="runc:[2:INIT]" exe="/" sig=0 arch=c000003e syscall=1 compat=0 ip=0x55ec0657bd3b code=0x7ffc0000
10.5.0.3: kern:  notice: [2022-07-28T11:49:44.893162063Z]: audit: type=1326 audit(1659008985.461:31): auid=4294967295 uid=0 gid=0 ses=4294967295 pid=2784 comm="runc:[2:INIT]" exe="/" sig=0 arch=c000003e syscall=3 compat=0 ip=0x55ec0657bd3b code=0x7ffc0000
10.5.0.3: kern:  notice: [2022-07-28T11:49:44.895365063Z]: audit: type=1326 audit(1659008985.461:32): auid=4294967295 uid=0 gid=0 ses=4294967295 pid=2784 comm="runc:[2:INIT]" exe="/" sig=0 arch=c000003e syscall=39 compat=0 ip=0x55ec066eb68b code=0x7ffc0000
10.5.0.3: kern:  notice: [2022-07-28T11:49:44.898306063Z]: audit: type=1326 audit(1659008985.461:33): auid=4294967295 uid=0 gid=0 ses=4294967295 pid=2784 comm="runc:[2:INIT]" exe="/" sig=0 arch=c000003e syscall=59 compat=0 ip=0x55ec0657be16 code=0x7ffc0000
10.5.0.3: kern:  notice: [2022-07-28T11:49:44.901518063Z]: audit: type=1326 audit(1659008985.473:34): auid=4294967295 uid=0 gid=0 ses=4294967295 pid=2784 comm="http-echo" exe="/http-echo" sig=0 arch=c000003e syscall=158 compat=0 ip=0x455f35 code=0x7ffc0000

Cleanup

You can clean up the test resources by running the following command:

kubectl delete pod audit-pod

3.1.9 - Storage

Setting up storage for a Kubernetes cluster

In Kubernetes, using storage in the right way is well-facilitated by the API. However, unless you are running in a major public cloud, that API may not be hooked up to anything. This frequently sends users down a rabbit hole of researching all the various options for storage backends for their platform, for Kubernetes, and for their workloads. There are a lot of options out there, and it can be fairly bewildering.

For Talos, we try to limit the options somewhat to make the decision-making easier.

Public Cloud

If you are running on a major public cloud, use their block storage. It is easy and automatic.

Storage Clusters

Sidero Labs recommends having separate disks (apart from the Talos install disk) to be used for storage.

Redundancy, scaling capabilities, reliability, speed, maintenance load, and ease of use are all factors you must consider when managing your own storage.

Running a storage cluster can be a very good choice when managing your own storage, and there are two projects we recommend, depending on your situation.

If you need vast amounts of storage composed of more than a dozen or so disks, we recommend you use Rook to manage Ceph. Also, if you need both mount-once and mount-many capabilities, Ceph is your answer. Ceph also bundles in an S3-compatible object store. The down side of Ceph is that there are a lot of moving parts.

Please note that most people should never use mount-many semantics. NFS is pervasive because it is old and easy, not because it is a good idea. While it may seem like a convenience at first, there are all manner of locking, performance, change control, and reliability concerns inherent in any mount-many situation, so we strongly recommend you avoid this method.

If your storage needs are small enough to not need Ceph, use Mayastor.

Rook/Ceph

Ceph is the grandfather of open source storage clusters. It is big, has a lot of pieces, and will do just about anything. It scales better than almost any other system out there, open source or proprietary, being able to easily add and remove storage over time with no downtime, safely and easily. It comes bundled with RadosGW, an S3-compatible object store; CephFS, a NFS-like clustered filesystem; and RBD, a block storage system.

With the help of Rook, the vast majority of the complexity of Ceph is hidden away by a very robust operator, allowing you to control almost everything about your Ceph cluster from fairly simple Kubernetes CRDs.

So if Ceph is so great, why not use it for everything?

Ceph can be rather slow for small clusters. It relies heavily on CPUs and massive parallelisation to provide good cluster performance, so if you don’t have much of those dedicated to Ceph, it is not going to be well-optimised for you. Also, if your cluster is small, just running Ceph may eat up a significant amount of the resources you have available.

Troubleshooting Ceph can be difficult if you do not understand its architecture. There are lots of acronyms and the documentation assumes a fair level of knowledge. There are very good tools for inspection and debugging, but this is still frequently seen as a concern.

Mayastor

Mayastor is an OpenEBS project built in Rust utilising the modern NVMEoF system. (Despite the name, Mayastor does not require you to have NVME drives.) It is fast and lean but still cluster-oriented and cloud native. Unlike most of the other OpenEBS project, it is not built on the ancient iSCSI system.

Unlike Ceph, Mayastor is just a block store. It focuses on block storage and does it well. It is much less complicated to set up than Ceph, but you probably wouldn’t want to use it for more than a few dozen disks.

Mayastor is new, maybe too new. If you’re looking for something well-tested and battle-hardened, this is not it. However, if you’re looking for something lean, future-oriented, and simpler than Ceph, it might be a great choice.

Video Walkthrough

To see a live demo of this section, see the video below:

Prep Nodes

Either during initial cluster creation or on running worker nodes, several machine config values should be edited. (This information is gathered from the Mayastor documentation.) We need to set the vm.nr_hugepages sysctl and add openebs.io/engine=mayastor labels to the nodes which are meant to be storage nodes. This can be done with talosctl patch machineconfig or via config patches during talosctl gen config.

Some examples are shown below: modify as needed.

First create a config patch file named mayastor-patch.yaml with the following contents:

- op: add
  path: /machine/sysctls
  value:
    vm.nr_hugepages: "1024"
- op: add
  path: /machine/nodeLabels
  value:
    openebs.io/engine: mayastor

Using gen config

talosctl gen config my-cluster https://mycluster.local:6443 --config-patch @mayastor-patch.yaml

Patching an existing node

talosctl patch --mode=no-reboot machineconfig -n <node ip> --patch @mayastor-patch.yaml

Note: If you are adding/updating the vm.nr_hugepages on a node which already had the openebs.io/engine=mayastor label set, you’d need to restart kubelet so that it picks up the new value, by issuing the following command

talosctl -n <node ip> service kubelet restart

Deploy Mayastor

Continue setting up Mayastor using the official documentation.

Piraeus / LINSTOR

Install Piraeus Operator V2 (recommended, when starting from scratch!)

There is already a how-to for Talos: Link

machine:
  install:
    extensions:
      - image: ghcr.io/siderolabs/drbd:9.2.2-v1.4.8
  kernel:
    modules:
      - name: drbd
      - name: drbd_transport_tcp

* op: add
  path: /machine/install/extensions/-
  value:
    * image: ghcr.io/siderolabs/drbd:9.2.2-v1.4.8
* op: add
  path: /machine/kernel/modules/-
  value:
    * name: drbd
    * name: drbd_transport_tcp

# Apply config update on node
talosctl patch mc --patch-file install-drbd.yml

# Start upgrade of Talos with with current installed version to enable the extension
talosctl upgrade --image=ghcr.io/siderolabs/installer:v1.4.8

# Create dedicated namespace for piraeus
kubectl create namespace piraeus
kubectl label ns piraeus pod-security.kubernetes.io/enforce=privileged
kubectl label ns piraeus pod-security.kubernetes.io/auth=privileged
kubectl label ns piraeus pod-security.kubernetes.io/warn=privileged

# Install Piraeus with Helm chart from GitHub repository
git clone --branch master https://github.com/piraeusdatastore/piraeus-operator.git
cd piraeus-operator
helm install piraeus-op ./charts/piraeus \
  --namespace piraeus \
  --set operator.satelliteSet.kernelModuleInjectionMode=None \ # Deprecated, but necessary!
  --set etcd.enabled=false \
  --set operator.controller.dbConnectionURL=k8s

Create first storage pool and PVC

Before proceeding, install linstor plugin for kubectl: https://github.com/piraeusdatastore/kubectl-linstor

Or use krew: kubectl krew install linstor

# Create device pool on a blank (no partitation table!) disk on node01
kubectl linstor physical-storage create-device-pool --pool-name nvme_lvm_pool LVM node01 /dev/nvme0n1 --storage-pool nvme_pool

piraeus-sc.yml

apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: simple-nvme
parameters:
  csi.storage.k8s.io/fstype: xfs
  linstor.csi.linbit.com/autoPlace: "3"
  linstor.csi.linbit.com/storagePool: nvme_pool
provisioner: linstor.csi.linbit.com
volumeBindingMode: WaitForFirstConsumer

# Create storage class
kubectl apply -f piraeus-sc.yml

NFS

NFS is an old pack animal long past its prime. NFS is slow, has all kinds of bottlenecks involving contention, distributed locking, single points of service, and more. However, it is supported by a wide variety of systems. You don’t want to use it unless you have to, but unfortunately, that “have to” is too frequent.

The NFS client is part of the kubelet image maintained by the Talos team. This means that the version installed in your running kubelet is the version of NFS supported by Talos. You can reduce some of the contention problems by parceling Persistent Volumes from separate underlying directories.

Object storage

Ceph comes with an S3-compatible object store, but there are other options, as well. These can often be built on top of other storage backends. For instance, you may have your block storage running with Mayastor but assign a Pod a large Persistent Volume to serve your object store.

One of the most popular open source add-on object stores is MinIO.

Others (iSCSI)

The most common remaining systems involve iSCSI in one form or another. These include the original OpenEBS, Rancher’s Longhorn, and many proprietary systems. iSCSI in Linux is facilitated by open-iscsi. This system was designed long before containers caught on, and it is not well suited to the task, especially when coupled with a read-only host operating system.

iSCSI support in Talos is now supported via the iscsi-tools system extension installed. The extension enables compatibility with OpenEBS Jiva - refer to the local storage installation guide for more information.

3.2 - Network

Managing the Kubernetes cluster networking

3.2.1 - Deploying Cilium CNI

In this guide you will learn how to set up Cilium CNI on Talos.

Cilium can be installed either via the cilium cli or using helm.

This documentation will outline installing Cilium CNI v1.13.0 on Talos in six different ways. Adhering to Talos principles we’ll deploy Cilium with IPAM mode set to Kubernetes, and using the cgroupv2 mount that talos already provides. As Talos does not allow loading kernel modules by Kubernetes workloads, SYS_MODULE capability needs to be dropped from the Cilium default set of values, this override can be seen in the helm/cilium cli install commands. Each method can either install Cilium using kube proxy (default) or without: Kubernetes Without kube-proxy

Machine config preparation

When generating the machine config for a node set the CNI to none. For example using a config patch:

Create a patch.yaml file with the following contents:

cluster:
  network:
    cni:
      name: none

talosctl gen config \
    my-cluster https://mycluster.local:6443 \
    --config-patch @patch.yaml

Or if you want to deploy Cilium in strict mode without kube-proxy, you also need to disable kube proxy:

Create a patch.yaml file with the following contents:

cluster:
  network:
    cni:
      name: none
  proxy:
    disabled: true

talosctl gen config \
    my-cluster https://mycluster.local:6443 \
    --config-patch @patch.yaml

Installation using Cilium CLI

Note: It is recommended to template the cilium manifest using helm and use it as part of Talos machine config, but if you want to install Cilium using the Cilium CLI, you can follow the steps below.

Install the Cilium CLI following the steps here.

With kube-proxy

cilium install \
    --helm-set=ipam.mode=kubernetes \
    --helm-set=kubeProxyReplacement=disabled \
    --helm-set=securityContext.capabilities.ciliumAgent="{CHOWN,KILL,NET_ADMIN,NET_RAW,IPC_LOCK,SYS_ADMIN,SYS_RESOURCE,DAC_OVERRIDE,FOWNER,SETGID,SETUID}" \
    --helm-set=securityContext.capabilities.cleanCiliumState="{NET_ADMIN,SYS_ADMIN,SYS_RESOURCE}" \
    --helm-set=cgroup.autoMount.enabled=false \
    --helm-set=cgroup.hostRoot=/sys/fs/cgroup

Without kube-proxy

export KUBERNETES_API_SERVER_ADDRESS=<replace with api server endpoint here> # e.g. 10.96.0.1
export KUBERNETES_API_SERVER_PORT=6443

cilium install \
    --helm-set=ipam.mode=kubernetes \
    --helm-set=kubeProxyReplacement=strict \
    --helm-set=securityContext.capabilities.ciliumAgent="{CHOWN,KILL,NET_ADMIN,NET_RAW,IPC_LOCK,SYS_ADMIN,SYS_RESOURCE,DAC_OVERRIDE,FOWNER,SETGID,SETUID}" \
    --helm-set=securityContext.capabilities.cleanCiliumState="{NET_ADMIN,SYS_ADMIN,SYS_RESOURCE}" \
    --helm-set=cgroup.autoMount.enabled=false \
    --helm-set=cgroup.hostRoot=/sys/fs/cgroup \
    --helm-set=k8sServiceHost="${KUBERNETES_API_SERVER_ADDRESS}" \
    --helm-set=k8sServicePort="${KUBERNETES_API_SERVER_PORT}"

Installation using Helm

Refer to Installing with Helm for more information.

First we’ll need to add the helm repo for Cilium.

helm repo add cilium https://helm.cilium.io/
helm repo update

Method 1: Helm install

After applying the machine config and bootstrapping Talos will appear to hang on phase 18/19 with the message: retrying error: node not ready. This happens because nodes in Kubernetes are only marked as ready once the CNI is up. As there is no CNI defined, the boot process is pending and will reboot the node to retry after 10 minutes, this is expected behavior.

During this window you can install Cilium manually by running the following:

helm install \
    cilium \
    cilium/cilium \
    --version 1.13.0 \
    --namespace kube-system \
    --set ipam.mode=kubernetes \
    --set=kubeProxyReplacement=disabled \
    --set=securityContext.capabilities.ciliumAgent="{CHOWN,KILL,NET_ADMIN,NET_RAW,IPC_LOCK,SYS_ADMIN,SYS_RESOURCE,DAC_OVERRIDE,FOWNER,SETGID,SETUID}" \
    --set=securityContext.capabilities.cleanCiliumState="{NET_ADMIN,SYS_ADMIN,SYS_RESOURCE}" \
    --set=cgroup.autoMount.enabled=false \
    --set=cgroup.hostRoot=/sys/fs/cgroup

Or if you want to deploy Cilium in strict mode without kube-proxy, also set some extra paramaters:

export KUBERNETES_API_SERVER_ADDRESS=<replace with api server endpoint here> # e.g. 10.96.0.1
export KUBERNETES_API_SERVER_PORT=6443

helm install \
    cilium \
    cilium/cilium \
    --version 1.13.0 \
    --namespace kube-system \
    --set ipam.mode=kubernetes \
    --set=kubeProxyReplacement=strict \
    --set=securityContext.capabilities.ciliumAgent="{CHOWN,KILL,NET_ADMIN,NET_RAW,IPC_LOCK,SYS_ADMIN,SYS_RESOURCE,DAC_OVERRIDE,FOWNER,SETGID,SETUID}" \
    --set=securityContext.capabilities.cleanCiliumState="{NET_ADMIN,SYS_ADMIN,SYS_RESOURCE}" \
    --set=cgroup.autoMount.enabled=false \
    --set=cgroup.hostRoot=/sys/fs/cgroup \
    --set=k8sServiceHost="${KUBERNETES_API_SERVER_ADDRESS}" \
    --set=k8sServicePort="${KUBERNETES_API_SERVER_PORT}"

After Cilium is installed the boot process should continue and complete successfully.

Method 2: Helm manifests install

Instead of directly installing Cilium you can instead first generate the manifest and then apply it:

helm template \
    cilium \
    cilium/cilium \
    --version 1.13.0 \
    --namespace kube-system \
    --set ipam.mode=kubernetes \
    --set=kubeProxyReplacement=disabled \
    --set=securityContext.capabilities.ciliumAgent="{CHOWN,KILL,NET_ADMIN,NET_RAW,IPC_LOCK,SYS_ADMIN,SYS_RESOURCE,DAC_OVERRIDE,FOWNER,SETGID,SETUID}" \
    --set=securityContext.capabilities.cleanCiliumState="{NET_ADMIN,SYS_ADMIN,SYS_RESOURCE}" \
    --set=cgroup.autoMount.enabled=false \
    --set=cgroup.hostRoot=/sys/fs/cgroup > cilium.yaml

kubectl apply -f cilium.yaml

Without kube-proxy:

export KUBERNETES_API_SERVER_ADDRESS=<replace with api server endpoint here> # e.g. 10.96.0.1
export KUBERNETES_API_SERVER_PORT=6443

helm template \
    cilium \
    cilium/cilium \
    --version 1.13.0 \
    --namespace kube-system \
    --set ipam.mode=kubernetes \
    --set=kubeProxyReplacement=strict \
    --set=securityContext.capabilities.ciliumAgent="{CHOWN,KILL,NET_ADMIN,NET_RAW,IPC_LOCK,SYS_ADMIN,SYS_RESOURCE,DAC_OVERRIDE,FOWNER,SETGID,SETUID}" \
    --set=securityContext.capabilities.cleanCiliumState="{NET_ADMIN,SYS_ADMIN,SYS_RESOURCE}" \
    --set=cgroup.autoMount.enabled=false \
    --set=cgroup.hostRoot=/sys/fs/cgroup \
    --set=k8sServiceHost="${KUBERNETES_API_SERVER_ADDRESS}" \
    --set=k8sServicePort="${KUBERNETES_API_SERVER_PORT}" > cilium.yaml

kubectl apply -f cilium.yaml

Method 3: Helm manifests hosted install

After generating cilium.yaml using helm template, instead of applying this manifest directly during the Talos boot window (before the reboot timeout). You can also host this file somewhere and patch the machine config to apply this manifest automatically during bootstrap. To do this patch your machine configuration to include this config instead of the above:

Create a patch.yaml file with the following contents:

cluster:
  network:
    cni:
      name: custom
      urls:
        - https://server.yourdomain.tld/some/path/cilium.yaml

talosctl gen config \
    my-cluster https://mycluster.local:6443 \
    --config-patch @patch.yaml

However, beware of the fact that the helm generated Cilium manifest contains sensitive key material. As such you should definitely not host this somewhere publicly accessible.

Method 4: Helm manifests inline install

A more secure option would be to include the helm template output manifest inside the machine configuration. The machine config should be generated with CNI set to none

Create a patch.yaml file with the following contents:

cluster:
  network:
    cni:
      name: none

talosctl gen config \
    my-cluster https://mycluster.local:6443 \
    --config-patch @patch.yaml

if deploying Cilium with kube-proxy disabled, you can also include the following:

Create a patch.yaml file with the following contents:

cluster:
  network:
    cni:
      name: none
  proxy:
    disabled: true

talosctl gen config \
    my-cluster https://mycluster.local:6443 \
    --config-patch @patch.yaml

To do so patch this into your machine configuration:

cluster:
  inlineManifests:
    - name: cilium
      contents: |
        --
        # Source: cilium/templates/cilium-agent/serviceaccount.yaml
        apiVersion: v1
        kind: ServiceAccount
        metadata:
          name: "cilium"
          namespace: kube-system
        ---
        # Source: cilium/templates/cilium-operator/serviceaccount.yaml
        apiVersion: v1
        kind: ServiceAccount
        -> Your cilium.yaml file will be pretty long....

This will install the Cilium manifests at just the right time during bootstrap.

Beware though:

Changing the namespace when templating with Helm does not generate a manifest containing the yaml to create that namespace. As the inline manifest is processed from top to bottom make sure to manually put the namespace yaml at the start of the inline manifest.
Only add the Cilium inline manifest to the control plane nodes machine configuration.
Make sure all control plane nodes have an identical configuration.
If you delete any of the generated resources they will be restored whenever a control plane node reboots.
As a safety measure, Talos only creates missing resources from inline manifests, it never deletes or updates anything.
If you need to update a manifest make sure to first edit all control plane machine configurations and then run talosctl upgrade-k8s as it will take care of updating inline manifests.

Known issues

There are some gotchas when using Talos and Cilium on the Google cloud platform when using internal load balancers. For more details: GCP ILB support / support scope local routes to be configured

Other things to know

Talos has full kernel module support for eBPF, See:

3.2.2 - KubeSpan

Learn to use KubeSpan to connect Talos Linux machines securely across networks.

KubeSpan is a feature of Talos that automates the setup and maintenance of a full mesh WireGuard network for your cluster, giving you the ability to operate hybrid Kubernetes clusters that can span the edge, datacenter, and cloud. Management of keys and discovery of peers can be completely automated for a zero-touch experience that makes it simple and easy to create hybrid clusters.

KubeSpan consists of client code in Talos Linux, as well as a discovery service that enables clients to securely find each other. Sidero Labs operates a free Discovery Service, but the discovery service may be operated by your organization and can be downloaded here.

Video Walkthrough

To learn more about KubeSpan, see the video below:

To see a live demo of KubeSpan, see one the videos below:

Enabling

Creating a New Cluster

To generate configuration files for a new cluster, we can use the --with-kubespan flag in talosctl gen config. This will enable peer discovery and KubeSpan.

machine:
    network:
        kubespan:
            enabled: true # Enable the KubeSpan feature.
cluster:
    discovery:
        enabled: true
        # Configure registries used for cluster member discovery.
        registries:
            kubernetes: # Kubernetes registry is problematic with KubeSpan, if the control plane endpoint is routeable itself via KubeSpan.
              disabled: true
            service: {}

The default discovery service is an external service hosted for free by Sidero Labs. The default value is https://discovery.talos.dev/. Contact Sidero Labs if you need to run this service privately.

Enabling for an Existing Cluster

In order to enable KubeSpan for an existing cluster, enable kubespan and discovery settings in the machine config for each machine in the cluster (discovery is enabled by default):

machine:
  network:
    kubespan:
      enabled: true
cluster:
  discovery:
    enabled: true

Configuration

KubeSpan will automatically discovery all cluster members, exchange Wireguard public keys and establish a full mesh network.

There are a few configuration options available to fine-tune the feature:

machine:
  network:
    kubespan:
      enabled: false
      advertiseKubernetesNetworks: false
      allowDownPeerBypass: false
      mtu: 1420
      filters:
        endpoints:
          - 0.0.0.0/0
          - ::/0

The setting advertiseKubernetesNetworks controls whether the node will advertise Kubernetes service and pod networks to other nodes in the cluster over KubeSpan. It defaults to being disabled, which means KubeSpan only controls the node-to-node traffic, while pod-to-pod traffic is routed and encapsulated by CNI. This setting should not be enabled with Calico and Cilium CNI plugins, as they do their own pod IP allocation which is not visible to KubeSpan.

The setting allowDownPeerBypass controls whether the node will allow traffic to bypass WireGuard if the destination is not connected over KubeSpan. If enabled, there is a risk that traffic will be routed unencrypted if the destination is not connected over KubeSpan, but it allows a workaround for the case where a node is not connected to the KubeSpan network, but still needs to access the cluster.

The mtu setting configures the Wireguard MTU, which defaults to 1420. This default value of 1420 is safe to use when the underlying network MTU is 1500, but if the underlying network MTU is smaller, the KubeSpanMTU should be adjusted accordingly: KubeSpanMTU = UnderlyingMTU - 80.

The filters setting allows to hide some endpoints from being advertised over KubeSpan. This is useful when some endpoints are known to be unreachable between the nodes, so that KubeSpan doesn’t try to establish a connection to them. Another use-case is hiding some endpoints if nodes can connect on multiple networks, and some of the networks are more preferable than others.

Resource Definitions

KubeSpanIdentities

A node’s WireGuard identities can be obtained with:

$ talosctl get kubespanidentities -o yaml
...
spec:
    address: fd83:b1f7:fcb5:2802:8c13:71ff:feaf:7c94/128
    subnet: fd83:b1f7:fcb5:2802::/64
    privateKey: gNoasoKOJzl+/B+uXhvsBVxv81OcVLrlcmQ5jQwZO08=
    publicKey: NzW8oeIH5rJyY5lefD9WRoHWWRr/Q6DwsDjMX+xKjT4=

Talos automatically configures unique IPv6 address for each node in the cluster-specific IPv6 ULA prefix.

Wireguard private key is generated for the node, private key never leaves the node while public key is published through the cluster discovery.

KubeSpanIdentity is persisted across reboots and upgrades in STATE partition in the file kubespan-identity.yaml.

KubeSpanPeerSpecs

A node’s WireGuard peers can be obtained with:

$ talosctl get kubespanpeerspecs
ID                                             VERSION   LABEL                          ENDPOINTS
06D9QQOydzKrOL7oeLiqHy9OWE8KtmJzZII2A5/FLFI=   2         talos-default-controlplane-2   ["172.20.0.3:51820"]
THtfKtfNnzJs1nMQKs5IXqK0DFXmM//0WMY+NnaZrhU=   2         talos-default-controlplane-3   ["172.20.0.4:51820"]
nVHu7l13uZyk0AaI1WuzL2/48iG8af4WRv+LWmAax1M=   2         talos-default-worker-2         ["172.20.0.6:51820"]
zXP0QeqRo+CBgDH1uOBiQ8tA+AKEQP9hWkqmkE/oDlc=   2         talos-default-worker-1         ["172.20.0.5:51820"]

The peer ID is the Wireguard public key. KubeSpanPeerSpecs are built from the cluster discovery data.

KubeSpanPeerStatuses

The status of a node’s WireGuard peers can be obtained with:

$ talosctl get kubespanpeerstatuses
ID                                             VERSION   LABEL                          ENDPOINT           STATE   RX         TX
06D9QQOydzKrOL7oeLiqHy9OWE8KtmJzZII2A5/FLFI=   63        talos-default-controlplane-2   172.20.0.3:51820   up      15043220   17869488
THtfKtfNnzJs1nMQKs5IXqK0DFXmM//0WMY+NnaZrhU=   62        talos-default-controlplane-3   172.20.0.4:51820   up      14573208   18157680
nVHu7l13uZyk0AaI1WuzL2/48iG8af4WRv+LWmAax1M=   60        talos-default-worker-2         172.20.0.6:51820   up      130072     46888
zXP0QeqRo+CBgDH1uOBiQ8tA+AKEQP9hWkqmkE/oDlc=   60        talos-default-worker-1         172.20.0.5:51820   up      130044     46556

KubeSpan peer status includes following information:

the actual endpoint used for peer communication
link state:
- unknown: the endpoint was just changed, link state is not known yet
- up: there is a recent handshake from the peer
- down: there is no handshake from the peer
number of bytes sent/received over the Wireguard link with the peer

If the connection state goes down, Talos will be cycling through the available endpoints until it finds the one which works.

Peer status information is updated every 30 seconds.

KubeSpanEndpoints

A node’s WireGuard endpoints (peer addresses) can be obtained with:

$ talosctl get kubespanendpoints
ID                                             VERSION   ENDPOINT           AFFILIATE ID
06D9QQOydzKrOL7oeLiqHy9OWE8KtmJzZII2A5/FLFI=   1         172.20.0.3:51820   2VfX3nu67ZtZPl57IdJrU87BMjVWkSBJiL9ulP9TCnF
THtfKtfNnzJs1nMQKs5IXqK0DFXmM//0WMY+NnaZrhU=   1         172.20.0.4:51820   b3DebkPaCRLTLLWaeRF1ejGaR0lK3m79jRJcPn0mfA6C
nVHu7l13uZyk0AaI1WuzL2/48iG8af4WRv+LWmAax1M=   1         172.20.0.6:51820   NVtfu1bT1QjhNq5xJFUZl8f8I8LOCnnpGrZfPpdN9WlB
zXP0QeqRo+CBgDH1uOBiQ8tA+AKEQP9hWkqmkE/oDlc=   1         172.20.0.5:51820   6EVq8RHIne03LeZiJ60WsJcoQOtttw1ejvTS6SOBzhUA

The endpoint ID is the base64 encoded WireGuard public key.

The observed endpoints are submitted back to the discovery service (if enabled) so that other peers can try additional endpoints to establish the connection.

3.3 - Upgrading Kubernetes

Guide on how to upgrade the Kubernetes cluster from Talos Linux.

This guide covers upgrading Kubernetes on Talos Linux clusters.

For a list of Kubernetes versions compatible with each Talos release, see the Support Matrix.

For upgrading the Talos Linux operating system, see Upgrading Talos

Video Walkthrough

To see a demo of this process, watch this video:

Automated Kubernetes Upgrade

The recommended method to upgrade Kubernetes is to use the talosctl upgrade-k8s command. This will automatically update the components needed to upgrade Kubernetes safely. Upgrading Kubernetes is non-disruptive to the cluster workloads.

To trigger a Kubernetes upgrade, issue a command specifiying the version of Kubernetes to ugprade to, such as:

talosctl --nodes <controlplane node> upgrade-k8s --to 1.27.4

Note that the --nodes parameter specifies the control plane node to send the API call to, but all members of the cluster will be upgraded.

To check what will be upgraded you can run talosctl upgrade-k8s with the --dry-run flag:

$ talosctl --nodes <controlplane node> upgrade-k8s --to 1.27.4 --dry-run
WARNING: found resources which are going to be deprecated/migrated in the version 1.27.4
RESOURCE                                                               COUNT
validatingwebhookconfigurations.v1beta1.admissionregistration.k8s.io   4
mutatingwebhookconfigurations.v1beta1.admissionregistration.k8s.io     3
customresourcedefinitions.v1beta1.apiextensions.k8s.io                 25
apiservices.v1beta1.apiregistration.k8s.io                             54
leases.v1beta1.coordination.k8s.io                                     4
automatically detected the lowest Kubernetes version 1.26.3
checking for resource APIs to be deprecated in version 1.27.4
discovered controlplane nodes ["172.20.0.2" "172.20.0.3" "172.20.0.4"]
discovered worker nodes ["172.20.0.5" "172.20.0.6"]
updating "kube-apiserver" to version "1.27.4"
 > "172.20.0.2": starting update
 > update kube-apiserver: v1.26.3 -> 1.27.4
 > skipped in dry-run
 > "172.20.0.3": starting update
 > update kube-apiserver: v1.26.3 -> 1.27.4
 > skipped in dry-run
 > "172.20.0.4": starting update
 > update kube-apiserver: v1.26.3 -> 1.27.4
 > skipped in dry-run
updating "kube-controller-manager" to version "1.27.4"
 > "172.20.0.2": starting update
 > update kube-controller-manager: v1.26.3 -> 1.27.4
 > skipped in dry-run
 > "172.20.0.3": starting update

<snip>

updating manifests
 > apply manifest Secret bootstrap-token-3lb63t
 > apply skipped in dry run
 > apply manifest ClusterRoleBinding system-bootstrap-approve-node-client-csr
 > apply skipped in dry run
<snip>

To upgrade Kubernetes from v1.26.3 to v1.27.4 run:

$ talosctl --nodes <controlplane node> upgrade-k8s --to 1.27.4
automatically detected the lowest Kubernetes version 1.26.3
checking for resource APIs to be deprecated in version 1.27.4
discovered controlplane nodes ["172.20.0.2" "172.20.0.3" "172.20.0.4"]
discovered worker nodes ["172.20.0.5" "172.20.0.6"]
updating "kube-apiserver" to version "1.27.4"
 > "172.20.0.2": starting update
 > update kube-apiserver: v1.26.3 -> 1.27.4
 > "172.20.0.2": machine configuration patched
 > "172.20.0.2": waiting for API server state pod update
 < "172.20.0.2": successfully updated
 > "172.20.0.3": starting update
 > update kube-apiserver: v1.26.3 -> 1.27.4
<snip>

This command runs in several phases:

Every control plane node machine configuration is patched with the new image version for each control plane component. Talos renders new static pod definitions on the configuration update which is picked up by the kubelet. The command waits for the change to propagate to the API server state.
The command updates the kube-proxy daemonset with the new image version.
On every node in the cluster, the kubelet version is updated. The command then waits for the kubelet service to be restarted and become healthy. The update is verified by checking the Node resource state.
Kubernetes bootstrap manifests are re-applied to the cluster. Updated bootstrap manifests might come with a new Talos version (e.g. CoreDNS version update), or might be the result of machine configuration change. Note: The upgrade-k8s command never deletes any resources from the cluster: they should be deleted manually.

If the command fails for any reason, it can be safely restarted to continue the upgrade process from the moment of the failure.

Manual Kubernetes Upgrade

Kubernetes can be upgraded manually by following the steps outlined below. They are equivalent to the steps performed by the talosctl upgrade-k8s command.

Kubeconfig

In order to edit the control plane, you need a working kubectl config. If you don’t already have one, you can get one by running:

talosctl --nodes <controlplane node> kubeconfig

API Server

Patch machine configuration using talosctl patch command:

$ talosctl -n <CONTROL_PLANE_IP_1> patch mc --mode=no-reboot -p '[{"op": "replace", "path": "/cluster/apiServer/image", "value": "registry.k8s.io/kube-apiserver:v1.27.4"}]'
patched mc at the node 172.20.0.2

The JSON patch might need to be adjusted if current machine configuration is missing .cluster.apiServer.image key.

Also the machine configuration can be edited manually with talosctl -n <IP> edit mc --mode=no-reboot.

Capture the new version of kube-apiserver config with:

$ talosctl -n <CONTROL_PLANE_IP_1> get kcpc kube-apiserver -o yaml
node: 172.20.0.2
metadata:
    namespace: config
    type: KubernetesControlPlaneConfigs.config.talos.dev
    id: kube-apiserver
    version: 5
    phase: running
spec:
    image: registry.k8s.io/kube-apiserver:v1.27.4
    cloudProvider: ""
    controlPlaneEndpoint: https://172.20.0.1:6443
    etcdServers:
        - https://127.0.0.1:2379
    localPort: 6443
    serviceCIDR: 10.96.0.0/12
    extraArgs: {}
    extraVolumes: []

In this example, the new version is 5. Wait for the new pod definition to propagate to the API server state (replace talos-default-controlplane-1 with the node name):

$ kubectl get pod -n kube-system -l k8s-app=kube-apiserver --field-selector spec.nodeName=talos-default-controlplane-1 -o jsonpath='{.items[0].metadata.annotations.talos\.dev/config\-version}'
5

Check that the pod is running:

$ kubectl get pod -n kube-system -l k8s-app=kube-apiserver --field-selector spec.nodeName=talos-default-controlplane-1
NAME                                    READY   STATUS    RESTARTS   AGE
kube-apiserver-talos-default-controlplane-1   1/1     Running   0          16m

Repeat this process for every control plane node, verifying that state got propagated successfully between each node update.

Controller Manager

Patch machine configuration using talosctl patch command:

$ talosctl -n <CONTROL_PLANE_IP_1> patch mc --mode=no-reboot -p '[{"op": "replace", "path": "/cluster/controllerManager/image", "value": "registry.k8s.io/kube-controller-manager:v1.27.4"}]'
patched mc at the node 172.20.0.2

The JSON patch might need be adjusted if current machine configuration is missing .cluster.controllerManager.image key.

Capture new version of kube-controller-manager config with:

$ talosctl -n <CONTROL_PLANE_IP_1> get kcpc kube-controller-manager -o yaml
node: 172.20.0.2
metadata:
    namespace: config
    type: KubernetesControlPlaneConfigs.config.talos.dev
    id: kube-controller-manager
    version: 3
    phase: running
spec:
    image: registry.k8s.io/kube-controller-manager:v1.27.4
    cloudProvider: ""
    podCIDR: 10.244.0.0/16
    serviceCIDR: 10.96.0.0/12
    extraArgs: {}
    extraVolumes: []

In this example, new version is 3. Wait for the new pod definition to propagate to the API server state (replace talos-default-controlplane-1 with the node name):

$ kubectl get pod -n kube-system -l k8s-app=kube-controller-manager --field-selector spec.nodeName=talos-default-controlplane-1 -o jsonpath='{.items[0].metadata.annotations.talos\.dev/config\-version}'
3

Check that the pod is running:

$ kubectl get pod -n kube-system -l k8s-app=kube-controller-manager --field-selector spec.nodeName=talos-default-controlplane-1
NAME                                             READY   STATUS    RESTARTS   AGE
kube-controller-manager-talos-default-controlplane-1   1/1     Running   0          35m

Repeat this process for every control plane node, verifying that state propagated successfully between each node update.

Scheduler

Patch machine configuration using talosctl patch command:

$ talosctl -n <CONTROL_PLANE_IP_1> patch mc --mode=no-reboot -p '[{"op": "replace", "path": "/cluster/scheduler/image", "value": "registry.k8s.io/kube-scheduler:v1.27.4"}]'
patched mc at the node 172.20.0.2

JSON patch might need be adjusted if current machine configuration is missing .cluster.scheduler.image key.

Capture new version of kube-scheduler config with:

$ talosctl -n <CONTROL_PLANE_IP_1> get kcpc kube-scheduler -o yaml
node: 172.20.0.2
metadata:
    namespace: config
    type: KubernetesControlPlaneConfigs.config.talos.dev
    id: kube-scheduler
    version: 3
    phase: running
spec:
    image: registry.k8s.io/kube-scheduler:v1.27.4
    extraArgs: {}
    extraVolumes: []

In this example, new version is 3. Wait for the new pod definition to propagate to the API server state (replace talos-default-controlplane-1 with the node name):

$ kubectl get pod -n kube-system -l k8s-app=kube-scheduler --field-selector spec.nodeName=talos-default-controlplane-1 -o jsonpath='{.items[0].metadata.annotations.talos\.dev/config\-version}'
3

Check that the pod is running:

$ kubectl get pod -n kube-system -l k8s-app=kube-scheduler --field-selector spec.nodeName=talos-default-controlplane-1
NAME                                    READY   STATUS    RESTARTS   AGE
kube-scheduler-talos-default-controlplane-1   1/1     Running   0          39m

Repeat this process for every control plane node, verifying that state got propagated successfully between each node update.

Proxy

In the proxy’s DaemonSet, change:

kind: DaemonSet
...
spec:
  ...
  template:
    ...
    spec:
      containers:
        - name: kube-proxy
          image: registry.k8s.io/kube-proxy:v1.27.4
      tolerations:
        - ...

to:

kind: DaemonSet
...
spec:
  ...
  template:
    ...
    spec:
      containers:
        - name: kube-proxy
          image: registry.k8s.io/kube-proxy:v1.27.4
      tolerations:
        - ...
        - key: node-role.kubernetes.io/control-plane
          operator: Exists
          effect: NoSchedule

To edit the DaemonSet, run:

kubectl edit daemonsets -n kube-system kube-proxy

Bootstrap Manifests

Bootstrap manifests can be retrieved in a format which works for kubectl with the following command:

talosctl -n <controlplane IP> get manifests -o yaml | yq eval-all '.spec | .[] | splitDoc' - > manifests.yaml

Diff the manifests with the cluster:

kubectl diff -f manifests.yaml

Apply the manifests:

kubectl apply -f manifests.yaml

Note: if some bootstrap resources were removed, they have to be removed from the cluster manually.

kubelet

For every node, patch machine configuration with new kubelet version, wait for the kubelet to restart with new version:

$ talosctl -n <IP> patch mc --mode=no-reboot -p '[{"op": "replace", "path": "/machine/kubelet/image", "value": "ghcr.io/siderolabs/kubelet:v1.27.4"}]'
patched mc at the node 172.20.0.2

Once kubelet restarts with the new configuration, confirm upgrade with kubectl get nodes <name>:

$ kubectl get nodes talos-default-controlplane-1
NAME                           STATUS   ROLES                  AGE    VERSION
talos-default-controlplane-1   Ready    control-plane          123m   v1.27.4

4 - Advanced Guides

4.1 - Advanced Networking

How to configure advanced networking options on Talos Linux.

Static Addressing

Static addressing is comprised of specifying addresses, routes ( remember to add your default gateway ), and interface. Most likely you’ll also want to define the nameservers so you have properly functioning DNS.

machine:
  network:
    hostname: talos
    nameservers:
      - 10.0.0.1
    interfaces:
      - interface: eth0
        addresses:
          - 10.0.0.201/8
        mtu: 8765
        routes:
          - network: 0.0.0.0/0
            gateway: 10.0.0.1
      - interface: eth1
        ignore: true
  time:
    servers:
      - time.cloudflare.com

Additional Addresses for an Interface

In some environments you may need to set additional addresses on an interface. In the following example, we set two additional addresses on the loopback interface.

machine:
  network:
    interfaces:
      - interface: lo
        addresses:
          - 192.168.0.21/24
          - 10.2.2.2/24

Bonding

The following example shows how to create a bonded interface.

machine:
  network:
    interfaces:
      - interface: bond0
        dhcp: true
        bond:
          mode: 802.3ad
          lacpRate: fast
          xmitHashPolicy: layer3+4
          miimon: 100
          updelay: 200
          downdelay: 200
          interfaces:
            - eth0
            - eth1

Setting Up a Bridge

The following example shows how to set up a bridge between two interfaces with an assigned static address.

machine:
  network:
    interfaces:
      - interface: br0
        addresses:
          - 192.168.0.42/24
        bridge:
          stp:
            enabled: true
          interfaces:
              - eth0
              - eth1

VLANs

To setup vlans on a specific device use an array of VLANs to add. The master device may be configured without addressing by setting dhcp to false.

machine:
  network:
    interfaces:
      - interface: eth0
        dhcp: false
        vlans:
          - vlanId: 100
            addresses:
              - "192.168.2.10/28"
            routes:
              - network: 0.0.0.0/0
                gateway: 192.168.2.1

4.2 - Air-gapped Environments

Setting up Talos Linux to work in environments with no internet access.

In this guide we will create a Talos cluster running in an air-gapped environment with all the required images being pulled from an internal registry. We will use the QEMU provisioner available in talosctl to create a local cluster, but the same approach could be used to deploy Talos in bigger air-gapped networks.

Requirements

The follow are requirements for this guide:

Docker 18.03 or greater
Requirements for the Talos QEMU cluster

Identifying Images

In air-gapped environments, access to the public Internet is restricted, so Talos can’t pull images from public Docker registries (docker.io, ghcr.io, etc.) We need to identify the images required to install and run Talos. The same strategy can be used for images required by custom workloads running on the cluster.

The talosctl images command provides a list of default images used by the Talos cluster (with default configuration settings). To print the list of images, run:

talosctl images

This list contains images required by a default deployment of Talos. There might be additional images required for the workloads running on this cluster, and those should be added to this list.

Preparing the Internal Registry

As access to the public registries is restricted, we have to run an internal Docker registry. In this guide, we will launch the registry on the same machine using Docker:

$ docker run -d -p 6000:5000 --restart always --name registry-airgapped registry:2
1bf09802bee1476bc463d972c686f90a64640d87dacce1ac8485585de69c91a5

This registry will be accepting connections on port 6000 on the host IPs. The registry is empty by default, so we have fill it with the images required by Talos.

First, we pull all the images to our local Docker daemon:

$ for image in `talosctl images`; do docker pull $image; done
v0.15.1: Pulling from coreos/flannel
Digest: sha256:9a296fbb67790659adc3701e287adde3c59803b7fcefe354f1fc482840cdb3d9
...

All images are now stored in the Docker daemon store:

$ docker images
REPOSITORY                               TAG                                        IMAGE ID       CREATED         SIZE
gcr.io/etcd-development/etcd             v3.5.3                                     604d4f022632   6 days ago      181MB
ghcr.io/siderolabs/install-cni           v1.0.0-2-gc5d3ab0                          4729e54f794d   6 days ago      76MB
...

Now we need to re-tag them so that we can push them to our local registry. We are going to replace the first component of the image name (before the first slash) with our registry endpoint 127.0.0.1:6000:

$ for image in `talosctl images`; do \
    docker tag $image `echo $image | sed -E 's#^[^/]+/#127.0.0.1:6000/#'`; \
  done

As the next step, we push images to the internal registry:

$ for image in `talosctl images`; do \
    docker push `echo $image | sed -E 's#^[^/]+/#127.0.0.1:6000/#'`; \
  done

We can now verify that the images are pushed to the registry:

$ curl http://127.0.0.1:6000/v2/_catalog
{"repositories":["coredns/coredns","coreos/flannel","etcd-development/etcd","kube-apiserver","kube-controller-manager","kube-proxy","kube-scheduler","pause","siderolabs/install-cni","siderolabs/installer","siderolabs/kubelet"]}

Note: images in the registry don’t have the registry endpoint prefix anymore.

Launching Talos in an Air-gapped Environment

For Talos to use the internal registry, we use the registry mirror feature to redirect all image pull requests to the internal registry. This means that the registry endpoint (as the first component of the image reference) gets ignored, and all pull requests are sent directly to the specified endpoint.

We are going to use a QEMU-based Talos cluster for this guide, but the same approach works with Docker-based clusters as well. As QEMU-based clusters go through the Talos install process, they can be used better to model a real air-gapped environment.

Identify all registry prefixes from talosctl images, for example:

docker.io
gcr.io
ghcr.io
registry.k8s.io

The talosctl cluster create command provides conveniences for common configuration options. The only required flag for this guide is --registry-mirror <endpoint>=http://10.5.0.1:6000 which redirects every pull request to the internal registry, this flag needs to be repeated for each of the identified registry prefixes above. The endpoint being used is 10.5.0.1, as this is the default bridge interface address which will be routable from the QEMU VMs (127.0.0.1 IP will be pointing to the VM itself).

$ sudo --preserve-env=HOME talosctl cluster create --provisioner=qemu --install-image=ghcr.io/siderolabs/installer:v1.4.8 \
  --registry-mirror docker.io=http://10.5.0.1:6000 \
  --registry-mirror gcr.io=http://10.5.0.1:6000 \
  --registry-mirror ghcr.io=http://10.5.0.1:6000 \
  --registry-mirror registry.k8s.io=http://10.5.0.1:6000 \
validating CIDR and reserving IPs
generating PKI and tokens
creating state directory in "/home/user/.talos/clusters/talos-default"
creating network talos-default
creating load balancer
creating dhcpd
creating master nodes
creating worker nodes
waiting for API
...

Note: --install-image should match the image which was copied into the internal registry in the previous step.

You can be verify that the cluster is air-gapped by inspecting the registry logs: docker logs -f registry-airgapped.

Closing Notes

Running in an air-gapped environment might require additional configuration changes, for example using custom settings for DNS and NTP servers.

When scaling this guide to the bare-metal environment, following Talos config snippet could be used as an equivalent of the --registry-mirror flag above:

machine:
  ...
  registries:
      mirrors:
        docker.io:
          endpoints:
          - http://10.5.0.1:6000/
        gcr.io:
          endpoints:
          - http://10.5.0.1:6000/
        ghcr.io:
          endpoints:
          - http://10.5.0.1:6000/
        registry.k8s.io:
          endpoints:
          - http://10.5.0.1:6000/
...

Other implementations of Docker registry can be used in place of the Docker registry image used above to run the registry. If required, auth can be configured for the internal registry (and custom TLS certificates if needed).

Please see pull-through cache guide for an example using Harbor container registry with Talos.

4.3 - Building Talos Images

How to build Talos images from source.

There might be several reasons to build Talos images from source:

verifying the image integrity
building an image with custom configuration

Checkout Talos Source

git clone https://github.com/siderolabs/talos.git

If building for a specific release, checkout the corresponding tag:

git checkout v1.4.8

Set up the Build Environment

See Developing Talos for details on setting up the buildkit builder.

Architectures

By default, Talos builds for linux/amd64, but you can customize that by passing PLATFORM variable to make:

make <target> PLATFORM=linux/arm64 # build for arm64 only
make <target> PLATFORM=linux/arm64,linux/amd64 # build for arm64 and amd64, container images will be multi-arch

Customizations

Some of the build parameters can be customized by passing environment variables to make, e.g. GOAMD64=v1 can be used to build Talos images compatible with old AMD64 CPUs:

make <target> GOAMD64=v1

Building Kernel and Initramfs

The most basic boot assets can be built with:

make kernel initramfs

Build result will be stored as _out/vmlinuz-<arch> and _out/initramfs-<arch>.xz.

Building Container Images

Talos container images should be pushed to the registry as the result of the build process.

The default settings are:

IMAGE_REGISTRY is set to ghcr.io
USERNAME is set to the siderolabs (or value of environment variable USERNAME if it is set)

The image can be pushed to any registry you have access to, but the access credentials should be stored in ~/.docker/config.json file (e.g. with docker login).

Building and pushing the image can be done with:

make installer PUSH=true IMAGE_REGISTRY=docker.io USERNAME=<username> # ghcr.io/siderolabs/installer
make imager PUSH=true IMAGE_REGISTRY=docker.io USERNAME=<username> # ghcr.io/siderolabs/installer

Building ISO

The ISO image is built with the help of imager container image, by default ghcr.io/siderolabs/imager will be used with the matching tag:

make iso

The ISO image will be stored as _out/talos-<arch>.iso.

If ISO image should be built with the custom imager image, it can be specified with IMAGE_REGISTRY/USERNAME variables:

make iso IMAGE_REGISTRY=docker.io USERNAME=<username>

Building Disk Images

The disk image is built with the help of imager container image, by default ghcr.io/siderolabs/imager will be used with the matching tag:

make image-metal

Available disk images are encoded in the image-% target, e.g. make image-aws. Same as with ISO image, the custom imager image can be specified with IMAGE_REGISTRY/USERNAME variables.

4.4 - Customizing the Kernel

Guide on how to customize the kernel used by Talos Linux.

The installer image contains ONBUILD instructions that handle the following:

the decompression, and unpacking of the initramfs.xz
the unsquashing of the rootfs
the copying of new rootfs files
the squashing of the new rootfs
and the packing, and compression of the new initramfs.xz

When used as a base image, the installer will perform the above steps automatically with the requirement that a customization stage be defined in the Dockerfile.

Build and push your own kernel:

git clone https://github.com/talos-systems/pkgs.git
cd pkgs
make kernel-menuconfig USERNAME=_your_github_user_name_

docker login ghcr.io --username _your_github_user_name_
make kernel USERNAME=_your_github_user_name_ PUSH=true

Using a multi-stage Dockerfile we can define the customization stage and build FROM the installer image:

FROM scratch AS customization
COPY --from=<custom kernel image> /lib/modules /lib/modules

FROM ghcr.io/siderolabs/installer:latest
COPY --from=<custom kernel image> /boot/vmlinuz /usr/install/${TARGETARCH}/vmlinuz

When building the image, the customization stage will automatically be copied into the rootfs. The customization stage is not limited to a single COPY instruction. In fact, you can do whatever you would like in this stage, but keep in mind that everything in / will be copied into the rootfs.

To build the image, run:

DOCKER_BUILDKIT=0 docker build --build-arg RM="/lib/modules" -t installer:kernel .

Note: buildkit has a bug #816, to disable it use DOCKER_BUILDKIT=0

Now that we have a custom installer we can build Talos for the specific platform we wish to deploy to.

4.5 - Customizing the Root Filesystem

How to add your own content to the immutable root file system of Talos Linux.

The installer image contains ONBUILD instructions that handle the following:

the decompression, and unpacking of the initramfs.xz
the unsquashing of the rootfs
the copying of new rootfs files
the squashing of the new rootfs
and the packing, and compression of the new initramfs.xz

When used as a base image, the installer will perform the above steps automatically with the requirement that a customization stage be defined in the Dockerfile.

For example, say we have an image that contains the contents of a library we wish to add to the Talos rootfs. We need to define a stage with the name customization:

FROM scratch AS customization
COPY --from=<name|index> <src> <dest>

Using a multi-stage Dockerfile we can define the customization stage and build FROM the installer image:

FROM scratch AS customization
COPY --from=<name|index> <src> <dest>

FROM ghcr.io/siderolabs/installer:latest

Note: <dest> is the path relative to the rootfs that you wish to place the contents of <src>.

To build the image, run:

docker build --squash -t <organization>/installer:latest .

In the case that you need to perform some cleanup before adding additional files to the rootfs, you can specify the RM build-time variable:

docker build --squash --build-arg RM="[<path> ...]" -t <organization>/installer:latest .

This will perform a rm -rf on the specified paths relative to the rootfs.

Note: RM must be a whitespace delimited list.

The resulting image can be used to:

generate an image for any of the supported providers
perform bare-metall installs
perform upgrades

We will step through common customizations in the remainder of this section.

4.6 - Developing Talos

Learn how to set up a development environment for local testing and hacking on Talos itself!

This guide outlines steps and tricks to develop Talos operating systems and related components. The guide assumes Linux operating system on the development host. Some steps might work under Mac OS X, but using Linux is highly advised.

Prepare

Check out the Talos repository.

Try running make help to see available make commands. You would need Docker and buildx installed on the host.

Note: Usually it is better to install up to date Docker from Docker apt repositories, e.g. Ubuntu instructions.
If buildx plugin is not available with OS docker packages, it can be installed as a plugin from GitHub releases.

Set up a builder with access to the host network:

 docker buildx create --driver docker-container  --driver-opt network=host --name local1 --buildkitd-flags '--allow-insecure-entitlement security.insecure' --use

Note: network=host allows buildx builder to access host network, so that it can push to a local container registry (see below).

Make sure the following steps work:

make talosctl
make initramfs kernel

Set up a local docker registry:

docker run -d -p 5005:5000 \
    --restart always \
    --name local registry:2

Try to build and push to local registry an installer image:

make installer IMAGE_REGISTRY=127.0.0.1:5005 PUSH=true

Record the image name output in the step above.

Note: it is also possible to force a stable image tag by using TAG variable: make installer IMAGE_REGISTRY=127.0.0.1:5005 TAG=v1.0.0-alpha.1 PUSH=true.

Running Talos cluster

Set up local caching docker registries (this speeds up Talos cluster boot a lot), script is in the Talos repo:

bash hack/start-registry-proxies.sh

Start your local cluster with:

sudo --preserve-env=HOME _out/talosctl-linux-amd64 cluster create \
    --provisioner=qemu \
    --cidr=172.20.0.0/24 \
    --registry-mirror docker.io=http://172.20.0.1:5000 \
    --registry-mirror registry.k8s.io=http://172.20.0.1:5001  \
    --registry-mirror gcr.io=http://172.20.0.1:5003 \
    --registry-mirror ghcr.io=http://172.20.0.1:5004 \
    --registry-mirror 127.0.0.1:5005=http://172.20.0.1:5005 \
    --install-image=127.0.0.1:5005/siderolabs/installer:<RECORDED HASH from the build step> \
    --controlplanes 3 \
    --workers 2 \
    --with-bootloader=false

--provisioner selects QEMU vs. default Docker
custom --cidr to make QEMU cluster use different network than default Docker setup (optional)
--registry-mirror uses the caching proxies set up above to speed up boot time a lot, last one adds your local registry (installer image was pushed to it)
--install-image is the image you built with make installer above
--controlplanes & --workers configure cluster size, choose to match your resources; 3 controlplanes give you HA control plane; 1 controlplane is enough, never do 2 controlplanes
--with-bootloader=false disables boot from disk (Talos will always boot from _out/vmlinuz-amd64 and _out/initramfs-amd64.xz). This speeds up development cycle a lot - no need to rebuild installer and perform install, rebooting is enough to get new code.

Note: as boot loader is not used, it’s not necessary to rebuild installer each time (old image is fine), but sometimes it’s needed (when configuration changes are done and old installer doesn’t validate the config).
talosctl cluster create derives Talos machine configuration version from the install image tag, so sometimes early in the development cycle (when new minor tag is not released yet), machine config version can be overridden with --talos-version=v1.4.

If the --with-bootloader=false flag is not enabled, for Talos cluster to pick up new changes to the code (in initramfs), it will require a Talos upgrade (so new installer should be built). With --with-bootloader=false flag, Talos always boots from initramfs in _out/ directory, so simple reboot is enough to pick up new code changes.

If the installation flow needs to be tested, --with-bootloader=false shouldn’t be used.

Console Logs

Watching console logs is easy with tail:

tail -F ~/.talos/clusters/talos-default/talos-default-*.log

Interacting with Talos

Once talosctl cluster create finishes successfully, talosconfig and kubeconfig will be set up automatically to point to your cluster.

Start playing with talosctl:

talosctl -n 172.20.0.2 version
talosctl -n 172.20.0.3,172.20.0.4 dashboard
talosctl -n 172.20.0.4 get members

Same with kubectl:

kubectl get nodes -o wide

You can deploy some Kubernetes workloads to the cluster.

You can edit machine config on the fly with talosctl edit mc --immediate, config patches can be applied via --config-patch flags, also many features have specific flags in talosctl cluster create.

Quick Reboot

To reboot whole cluster quickly (e.g. to pick up a change made in the code):

for socket in ~/.talos/clusters/talos-default/talos-default-*.monitor; do echo "q" | sudo socat - unix-connect:$socket; done

Sending q to a single socket allows to reboot a single node.

Note: This command performs immediate reboot (as if the machine was powered down and immediately powered back up), for normal Talos reboot use talosctl reboot.

Development Cycle

Fast development cycle:

bring up a cluster
make code changes
rebuild initramfs with make initramfs
reboot a node to pick new initramfs
verify code changes
more code changes…

Some aspects of Talos development require to enable bootloader (when working on installer itself), in that case quick development cycle is no longer possible, and cluster should be destroyed and recreated each time.

Running Integration Tests

If integration tests were changed (or when running them for the first time), first rebuild the integration test binary:

rm -f  _out/integration-test-linux-amd64; make _out/integration-test-linux-amd64

Running short tests against QEMU provisioned cluster:

_out/integration-test-linux-amd64 \
    -talos.provisioner=qemu \
    -test.v \
    -talos.crashdump=false \
    -test.short \
    -talos.talosctlpath=$PWD/_out/talosctl-linux-amd64

Whole test suite can be run removing -test.short flag.

Specfic tests can be run with -test.run=TestIntegration/api.ResetSuite.

Build Flavors

make <something> WITH_RACE=1 enables Go race detector, Talos runs slower and uses more memory, but memory races are detected.

make <something> WITH_DEBUG=1 enables Go profiling and other debug features, useful for local development.

Destroying Cluster

sudo --preserve-env=HOME ../talos/_out/talosctl-linux-amd64 cluster destroy --provisioner=qemu

This command stops QEMU and helper processes, tears down bridged network on the host, and cleans up cluster state in ~/.talos/clusters.

Note: if the host machine is rebooted, QEMU instances and helpers processes won’t be started back. In that case it’s required to clean up files in ~/.talos/clusters/<cluster-name> directory manually.

Optional

Set up cross-build environment with:

docker run --rm --privileged multiarch/qemu-user-static --reset -p yes

Note: the static qemu binaries which come with Ubuntu 21.10 seem to be broken.

Unit tests

Unit tests can be run in buildx with make unit-tests, on Ubuntu systems some tests using loop devices will fail because Ubuntu uses low-index loop devices for snaps.

Most of the unit-tests can be run standalone as well, with regular go test, or using IDE integration:

go test -v ./internal/pkg/circular/

This provides much faster feedback loop, but some tests require either elevated privileges (running as root) or additional binaries available only in Talos rootfs (containerd tests).

Running tests as root can be done with -exec flag to go test, but this is risky, as test code has root access and can potentially make undesired changes:

go test -exec sudo  -v ./internal/app/machined/pkg/controllers/network/...

Go Profiling

Build initramfs with debug enabled: make initramfs WITH_DEBUG=1.

Launch Talos cluster with bootloader disabled, and use go tool pprof to capture the profile and show the output in your browser:

go tool pprof http://172.20.0.2:9982/debug/pprof/heap

The IP address 172.20.0.2 is the address of the Talos node, and port :9982 depends on the Go application to profile:

9981: apid
9982: machined
9983: trustd

Testing Air-gapped Environments

There is a hidden talosctl debug air-gapped command which launches two components:

HTTP proxy capable of proxying HTTP and HTTPS requests
HTTPS server with a self-signed certificate

The command also writes down Talos machine configuration patch to enable the HTTP proxy and add a self-signed certificate to the list of trusted certificates:

$ talosctl debug air-gapped --advertised-address 172.20.0.1
2022/08/04 16:43:14 writing config patch to air-gapped-patch.yaml
2022/08/04 16:43:14 starting HTTP proxy on :8002
2022/08/04 16:43:14 starting HTTPS server with self-signed cert on :8001

The --advertised-address should match the bridge IP of the Talos node.

Generated machine configuration patch looks like:

machine:
    files:
        - content: |
            -----BEGIN CERTIFICATE-----
            MIIBijCCAS+gAwIBAgIBATAKBggqhkjOPQQDAjAUMRIwEAYDVQQKEwlUZXN0IE9u
            bHkwHhcNMjIwODA0MTI0MzE0WhcNMjIwODA1MTI0MzE0WjAUMRIwEAYDVQQKEwlU
            ZXN0IE9ubHkwWTATBgcqhkjOPQIBBggqhkjOPQMBBwNCAAQfOJdaOFSOI1I+EeP1
            RlMpsDZJaXjFdoo5zYM5VYs3UkLyTAXAmdTi7JodydgLhty0pwLEWG4NUQAEvip6
            EmzTo3IwcDAOBgNVHQ8BAf8EBAMCBaAwHQYDVR0lBBYwFAYIKwYBBQUHAwEGCCsG
            AQUFBwMCMA8GA1UdEwEB/wQFMAMBAf8wHQYDVR0OBBYEFCwxL+BjG0pDwaH8QgKW
            Ex0J2mVXMA8GA1UdEQQIMAaHBKwUAAEwCgYIKoZIzj0EAwIDSQAwRgIhAJoW0z0D
            JwpjFcgCmj4zT1SbBFhRBUX64PHJpAE8J+LgAiEAvfozZG8Or6hL21+Xuf1x9oh4
            /4Hx3jozbSjgDyHOLk4=
            -----END CERTIFICATE-----            
          permissions: 0o644
          path: /etc/ssl/certs/ca-certificates
          op: append
    env:
        http_proxy: http://172.20.0.1:8002
        https_proxy: http://172.20.0.1:8002
        no_proxy: 172.20.0.1/24
cluster:
    extraManifests:
        - https://172.20.0.1:8001/debug.yaml

The first section appends a self-signed certificate of the HTTPS server to the list of trusted certificates, followed by the HTTP proxy setup (in-cluster traffic is excluded from the proxy). The last section adds an extra Kubernetes manifest hosted on the HTTPS server.

The machine configuration patch can now be used to launch a test Talos cluster:

talosctl cluster create ... --config-patch @air-gapped-patch.yaml

The following lines should appear in the output of the talosctl debug air-gapped command:

CONNECT discovery.talos.dev:443: the HTTP proxy is used to talk to the discovery service
http: TLS handshake error from 172.20.0.2:53512: remote error: tls: bad certificate: an expected error on Talos side, as self-signed cert is not written yet to the file
GET /debug.yaml: Talos successfully fetches the extra manifest successfully

There might be more output depending on the registry caches being used or not.

4.7 - Disaster Recovery

Procedure for snapshotting etcd database and recovering from catastrophic control plane failure.

etcd database backs Kubernetes control plane state, so if the etcd service is unavailable, the Kubernetes control plane goes down, and the cluster is not recoverable until etcd is recovered. etcd builds around the consensus protocol Raft, so highly-available control plane clusters can tolerate the loss of nodes so long as more than half of the members are running and reachable. For a three control plane node Talos cluster, this means that the cluster tolerates a failure of any single node, but losing more than one node at the same time leads to complete loss of service. Because of that, it is important to take routine backups of etcd state to have a snapshot to recover the cluster from in case of catastrophic failure.

Backup

Snapshotting `etcd` Database

Create a consistent snapshot of etcd database with talosctl etcd snapshot command:

$ talosctl -n <IP> etcd snapshot db.snapshot
etcd snapshot saved to "db.snapshot" (2015264 bytes)
snapshot info: hash c25fd181, revision 4193, total keys 1287, total size 3035136

Note: filename db.snapshot is arbitrary.

This database snapshot can be taken on any healthy control plane node (with IP address <IP> in the example above), as all etcd instances contain exactly same data. It is recommended to configure etcd snapshots to be created on some schedule to allow point-in-time recovery using the latest snapshot.

Disaster Database Snapshot

If the etcd cluster is not healthy (for example, if quorum has already been lost), the talosctl etcd snapshot command might fail. In that case, copy the database snapshot directly from the control plane node:

talosctl -n <IP> cp /var/lib/etcd/member/snap/db .

This snapshot might not be fully consistent (if the etcd process is running), but it allows for disaster recovery when latest regular snapshot is not available.

Machine Configuration

Machine configuration might be required to recover the node after hardware failure. Backup Talos node machine configuration with the command:

talosctl -n IP get mc v1alpha1 -o yaml | yq eval '.spec' -

Recovery

Before starting a disaster recovery procedure, make sure that etcd cluster can’t be recovered:

get etcd cluster member list on all healthy control plane nodes with talosctl -n IP etcd members command and compare across all members.
query etcd health across control plane nodes with talosctl -n IP service etcd.

If the quorum can be restored, restoring quorum might be a better strategy than performing full disaster recovery procedure.

Latest Etcd Snapshot

Get hold of the latest etcd database snapshot. If a snapshot is not fresh enough, create a database snapshot (see above), even if the etcd cluster is unhealthy.

Init Node

Make sure that there are no control plane nodes with machine type init:

$ talosctl -n <IP1>,<IP2>,... get machinetype
NODE         NAMESPACE   TYPE          ID             VERSION   TYPE
172.20.0.2   config      MachineType   machine-type   2         controlplane
172.20.0.4   config      MachineType   machine-type   2         controlplane
172.20.0.3   config      MachineType   machine-type   2         controlplane

Init node type is deprecated, and are incompatible with etcd recovery procedure. init node can be converted to controlplane type with talosctl edit mc --mode=staged command followed by node reboot with talosctl reboot command.

Preparing Control Plane Nodes

If some control plane nodes experienced hardware failure, replace them with new nodes.

Use machine configuration backup to re-create the nodes with the same secret material and control plane settings to allow workers to join the recovered control plane.

If a control plane node is up but etcd isn’t, wipe the node’s EPHEMERAL partition to remove the etcd data directory (make sure a database snapshot is taken before doing this):

talosctl -n <IP> reset --graceful=false --reboot --system-labels-to-wipe=EPHEMERAL

At this point, all control plane nodes should boot up, and etcd service should be in the Preparing state.

The Kubernetes control plane endpoint should be pointed to the new control plane nodes if there were changes to the node addresses.

Recovering from the Backup

Make sure all etcd service instances are in Preparing state:

$ talosctl -n <IP> service etcd
NODE     172.20.0.2
ID       etcd
STATE    Preparing
HEALTH   ?
EVENTS   [Preparing]: Running pre state (17s ago)
         [Waiting]: Waiting for service "cri" to be "up", time sync (18s ago)
         [Waiting]: Waiting for service "cri" to be "up", service "networkd" to be "up", time sync (20s ago)

Execute the bootstrap command against any control plane node passing the path to the etcd database snapshot:

$ talosctl -n <IP> bootstrap --recover-from=./db.snapshot
recovering from snapshot "./db.snapshot": hash c25fd181, revision 4193, total keys 1287, total size 3035136

Note: if database snapshot was copied out directly from the etcd data directory using talosctl cp, add flag --recover-skip-hash-check to skip integrity check on restore.

Talos node should print matching information in the kernel log:

recovering etcd from snapshot: hash c25fd181, revision 4193, total keys 1287, total size 3035136
{"level":"info","msg":"restoring snapshot","path":"/var/lib/etcd.snapshot","wal-dir":"/var/lib/etcd/member/wal","data-dir":"/var/lib/etcd","snap-dir":"/var/li}
{"level":"info","msg":"restored last compact revision","meta-bucket-name":"meta","meta-bucket-name-key":"finishedCompactRev","restored-compact-revision":3360}
{"level":"info","msg":"added member","cluster-id":"a3390e43eb5274e2","local-member-id":"0","added-peer-id":"eb4f6f534361855e","added-peer-peer-urls":["https:/}
{"level":"info","msg":"restored snapshot","path":"/var/lib/etcd.snapshot","wal-dir":"/var/lib/etcd/member/wal","data-dir":"/var/lib/etcd","snap-dir":"/var/lib/etcd/member/snap"}

Now etcd service should become healthy on the bootstrap node, Kubernetes control plane components should start and control plane endpoint should become available. Remaining control plane nodes join etcd cluster once control plane endpoint is up.

Single Control Plane Node Cluster

This guide applies to the single control plane clusters as well. In fact, it is much more important to take regular snapshots of the etcd database in single control plane node case, as loss of the control plane node might render the whole cluster irrecoverable without a backup.

4.8 - etcd Maintenance

Operational instructions for etcd database.

etcd database backs Kubernetes control plane state, so etcd health is critical for Kubernetes availability.

Space Quota

etcd default database space quota is set to 2 GiB by default. If the database size exceeds the quota, etcd will stop operations until the issue is resolved.

This condition can be checked with talosctl etcd alarm list command:

$ talosctl -n <IP> etcd alarm list
NODE         MEMBER             ALARM
172.20.0.2   a49c021e76e707db   NOSPACE

If the Kubernetes database contains lots of resources, space quota can be increased to match the actual usage. The recommended maximum size is 8 GiB.

To increase the space quota, edit the etcd section in the machine configuration:

cluster:
  etcd:
    extraArgs:
      quota-backend-bytes: 4294967296 # 4 GiB

Once the node is rebooted with the new configuration, use talosctl etcd alarm disarm to clear the NOSPACE alarm.

Defragmentation

etcd database can become fragmented over time if there are lots of writes and deletes. Kubernetes API server performs automatic compaction of the etcd database, which marks deleted space as free and ready to be reused. However, the space is not actually freed until the database is defragmented.

If the database is heavily fragmented (in use/db size ratio is less than 0.5), defragmentation might increase the performance. If the database runs over the space quota (see above), but the actual in use database size is small, defragmentation is required to bring the on-disk database size below the limit.

Current database size can be checked with talosctl etcd status command:

$ talosctl -n <CP1>,<CP2>,<CP3> etcd status
NODE         MEMBER             DB SIZE   IN USE            LEADER             RAFT INDEX   RAFT TERM   RAFT APPLIED INDEX   LEARNER   ERRORS
172.20.0.3   ecebb05b59a776f1   21 MB     6.0 MB (29.08%)   ecebb05b59a776f1   53391        4           53391                false
172.20.0.2   a49c021e76e707db   17 MB     4.5 MB (26.10%)   ecebb05b59a776f1   53391        4           53391                false
172.20.0.4   eb47fb33e59bf0e2   20 MB     5.9 MB (28.96%)   ecebb05b59a776f1   53391        4           53391                false

If any of the nodes are over database size quota, alarms will be printed in the ERRORS column.

To defragment the database, run talosctl etcd defrag command:

talosctl -n <CP1> etcd defrag

Note: defragmentation is a resource-intensive operation, so it is recommended to run it on a single node at a time. Defragmentation to a live member blocks the system from reading and writing data while rebuilding its state.

Once the defragmentation is complete, the database size will match closely to the in use size:

$ talosctl -n <CP1> etcd status
NODE         MEMBER             DB SIZE   IN USE             LEADER             RAFT INDEX   RAFT TERM   RAFT APPLIED INDEX   LEARNER   ERRORS
172.20.0.2   a49c021e76e707db   4.5 MB    4.5 MB (100.00%)   ecebb05b59a776f1   56065        4           56065                false

Snapshotting

Regular backups of etcd database should be performed to ensure that the cluster can be restored in case of a failure. This procedure is described in the disaster recovery guide.

4.9 - Extension Services

Use extension services in Talos Linux.

Talos provides a way to run additional system services early in the Talos boot process. Extension services should be included into the Talos root filesystem (e.g. using system extensions). Extension services run as privileged containers with ephemeral root filesystem located in the Talos root filesystem.

Extension services can be used to use extend core features of Talos in a way that is not possible via static pods or Kubernetes DaemonSets.

Potential extension services use-cases:

storage: Open iSCSI, software RAID, etc.
networking: BGP FRR, etc.
platform integration: VMWare open VM tools, etc.

Configuration

Talos on boot scans directory /usr/local/etc/containers for *.yaml files describing the extension services to run. Format of the extension service config:

name: hello-world
container:
  entrypoint: ./hello-world
  environment:
    - XDG_RUNTIME_DIR=/run
  args:
     - -f
  mounts:
     - # OCI Mount Spec
depends:
   - service: cri
   - path: /run/machined/machined.sock
   - network:
       - addresses
       - connectivity
       - hostname
       - etcfiles
   - time: true
restart: never|always|untilSuccess

`name`

Field name sets the service name, valid names are [a-z0-9-_]+. The service container root filesystem path is derived from the name: /usr/local/lib/containers/<name>. The extension service will be registered as a Talos service under an ext-<name> identifier.

`container`

entrypoint defines the container entrypoint relative to the container root filesystem (/usr/local/lib/containers/<name>)
environment defines the container environment variables
args defines the additional arguments to pass to the entrypoint
mounts defines the volumes to be mounted into the container root

`container.mounts`

The section mounts uses the standard OCI spec:

- source: /var/log/audit
  destination: /var/log/audit
  type: bind
  options:
    - rshared
    - bind
    - ro

All requested directories will be mounted into the extension service container mount namespace. If the source directory doesn’t exist in the host filesystem, it will be created (only for writable paths in the Talos root filesystem).

`container.security`

The section security follows this example:

maskedPaths:
  - "/should/be/masked"
readonlyPaths:
  - "/path/that/should/be/readonly"
  - "/another/readonly/path"
writeableRootfs: true
writeableSysfs: true

The rootfs is readonly by default unless writeableRootfs: true is set.
The sysfs is readonly by default unless writeableSysfs: true is set.
Masked paths if not set defaults to containerd defaults. Masked paths will be mounted to /dev/null. To set empty masked paths use:
container:
  security:
    maskedPaths: []
Read Only paths if not set defaults to containerd defaults. Read-only paths will be mounted to /dev/null. To set empty read only paths use:
container:
  security:
    readonlyPaths: []

`depends`

The depends section describes extension service start dependencies: the service will not be started until all dependencies are met.

Available dependencies:

service: <name>: wait for the service <name> to be running and healthy
path: <path>: wait for the <path> to exist
network: [addresses, connectivity, hostname, etcfiles]: wait for the specified network readiness checks to succeed
time: true: wait for the NTP time sync

`restart`

Field restart defines the service restart policy, it allows to either configure an always running service or a one-shot service:

always: restart service always
never: start service only once and never restart
untilSuccess: restart failing service, stop restarting on successful run

Example

Example layout of the Talos root filesystem contents for the extension service:

/
└── usr
    └── local
        ├── etc
        │   └── containers
        │       └── hello-world.yaml
        └── lib
            └── containers
                └── hello-world
                    ├── hello
                    └── config.ini

Talos discovers the extension service configuration in /usr/local/etc/containers/hello-world.yaml:

name: hello-world
container:
  entrypoint: ./hello
  args:
    - --config
    - config.ini
depends:
  - network:
    - addresses
restart: always

Talos starts the container for the extension service with container root filesystem at /usr/local/lib/containers/hello-world:

/
├── hello
└── config.ini

Extension service is registered as ext-hello-world in talosctl services:

$ talosctl service ext-hello-world
NODE     172.20.0.5
ID       ext-hello-world
STATE    Running
HEALTH   ?
EVENTS   [Running]: Started task ext-hello-world (PID 1100) for container ext-hello-world (2m47s ago)
         [Preparing]: Creating service runner (2m47s ago)
         [Preparing]: Running pre state (2m47s ago)
         [Waiting]: Waiting for service "containerd" to be "up" (2m48s ago)
         [Waiting]: Waiting for service "containerd" to be "up", network (2m49s ago)

An extension service can be started, restarted and stopped using talosctl service ext-hello-world start|restart|stop. Use talosctl logs ext-hello-world to get the logs of the service.

Complete example of the extension service can be found in the extensions repository.

4.10 - Metal Network Configuration

How to use META-based network configuration on Talos metal platform.

Note: This is an advanced feature which requires deep understanding of Talos and Linux network configuration.

Talos Linux when running on a cloud platform (e.g. AWS or Azure), uses the platform-provided metadata server to provide initial network configuration to the node. When running on bare-metal, there is no metadata server, so there are several options to provide initial network configuration (before machine configuration is acquired):

use automatic network configuration via DHCP (Talos default)
use initial boot kernel command line parameters to configure networking
use automatic network configuration via DHCP just enough to fetch machine configuration and then use machine configuration to set desired advanced configuration.

If DHCP option is available, it is by far the easiest way to configure networking. The initial boot kernel command line parameters are not very flexible, and they are not persisted after initial Talos installation.

Talos starting with version 1.4.0 offers a new option to configure networking on bare-metal: META-based network configuration.

Note: META-based network configuration is only available on Talos Linux metal platform.

Talos dashboard provides a way to configure META-based network configuration for a machine using the console, but it doesn’t support all kinds of network configuration.

Network Configuration Format

Talos META-based network configuration is a YAML file with the following format:

addresses:
    - address: 147.75.61.43/31
      linkName: bond0
      family: inet4
      scope: global
      flags: permanent
      layer: platform
    - address: 2604:1380:45f2:6c00::1/127
      linkName: bond0
      family: inet6
      scope: global
      flags: permanent
      layer: platform
    - address: 10.68.182.1/31
      linkName: bond0
      family: inet4
      scope: global
      flags: permanent
      layer: platform
links:
    - name: eth0
      up: true
      masterName: bond0
      slaveIndex: 0
      layer: platform
    - name: eth1
      up: true
      masterName: bond0
      slaveIndex: 1
      layer: platform
    - name: bond0
      logical: true
      up: true
      mtu: 0
      kind: bond
      type: ether
      bondMaster:
        mode: 802.3ad
        xmitHashPolicy: layer3+4
        lacpRate: slow
        arpValidate: none
        arpAllTargets: any
        primaryReselect: always
        failOverMac: 0
        miimon:

Welcome

Welcome

Open Source

Community

Office Hours

Enterprise

1 - Introduction

1.1 - What is Talos?

Why Talos

1.2 - Quickstart

Local Docker Cluster

Prerequisites

talosctl

kubectl

Create the Cluster

Note

Destroy the Cluster

1.3 - Getting Started

Prerequisites

talosctl

Acquire the installation image

Alternative Booting

Decide the Kubernetes Endpoint

Dedicated Load-balancer

Layer 2 Shared IP

DNS records

Decide how to access the Talos API

Configure Talos

Controlplane and Worker

Modifying the Machine configs

Customizing Machine Configuration

Machine Configs as Templates

Apply Configuration

Understand talosctl, endpoints and nodes

Endpoints

Nodes

Default configuration file

Kubernetes Bootstrap

1.4 - System Requirements

Minimum Requirements

Recommended

Storage

1.5 - What's New in Talos 1.4

Interactive Dashboard

Boot Process

GRUB Menu Wipe Options

Kernel Modules

Kernel Modules Tree

Kernel Argument talos.environment

Kernel Argument talos.experimental.wipe

Networking

Bond Device Selectors

VLAN Machine Configuration

talosctl CLI

talosctl etcd

talosctl containers

talosctl dashboard

talosctl logs

talosctl netstat

talosctl reset

Miscellaneous

Registry Mirror Catch-All Option

Talos API os:operator role

VMware Platform

Component Updates

1.6 - Support Matrix

Platform Tiers

Tier 1

Tier 2

Tier 3

2 - Talos Linux Guides

2.1 - Installation

2.1.1 - Bare Metal Platforms

2.1.1.1 - Digital Rebar

Prerequisites

Creating a Cluster

Create the Machine Configuration Files

Generating Base Configurations

Validate the Configuration Files

Publishing the Machine Configuration Files

`talosctl`

`kubectl`

`talosctl`

Kernel Argument `talos.environment`

Kernel Argument `talos.experimental.wipe`

`talosctl` CLI

`talosctl etcd`

`talosctl containers`

`talosctl dashboard`

`talosctl logs`

`talosctl netstat`

`talosctl reset`

Talos API `os:operator` role

Retrieve the `kubeconfig`

Retrieve the `kubeconfig`

Retrieve the `kubeconfig`

Retrieve the `kubeconfig`