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| K3s is a simplified version of [[Kubernetes]]. It bundles all components for a kubernetes cluster into a few of small binaries. | | [https://k3s.io/ K3s] is a simplified Kubernetes version that bundles Kubernetes cluster components into a few small binaries optimized for Edge and IoT devices. |
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| == Single node setup ==
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| <syntaxHighlight lang=nix>
| | NixOS's K3s documentation is available at: |
| {
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| networking.firewall.allowedTCPPorts = [
| | https://github.com/NixOS/nixpkgs/blob/master/pkgs/applications/networking/cluster/k3s/README.md |
| 6443 # k3s: required so that pods can reach the API server (running on port 6443 by default)
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| # 2379 # k3s, etcd clients: required if using a "High Availability Embedded etcd" configuration
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| # 2380 # k3s, etcd peers: required if using a "High Availability Embedded etcd" configuration
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| ];
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| networking.firewall.allowedUDPPorts = [
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| # 8472 # k3s, flannel: required if using multi-node for inter-node networking
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| ];
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| services.k3s.enable = true;
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| services.k3s.role = "server";
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| services.k3s.extraFlags = toString [
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| # "--kubelet-arg=v=4" # Optionally add additional args to k3s
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| ];
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| environment.systemPackages = [ pkgs.k3s ];
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| }
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| </syntaxHighlight>
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| After enabling, you can access your cluster through <code>sudo k3s kubectl</code> i.e. <code>sudo k3s kubectl cluster-info</code>, or by using the generated kubeconfig file in <code>/etc/rancher/k3s/k3s.yaml</code>
| | [[Category:Container]] |
| | |
| == Multi-node setup ==
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| it is simple to create a cluster of multiple nodes in a highly available setup (all nodes are in the control-plane and are a part of the etcd cluster).
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| The first node is configured like this:
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| <syntaxHighlight lang=nix>
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| {
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| services.k3s = {
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| enable = true;
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| role = "server";
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| token = "<randomized common secret>";
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| clusterInit = true;
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| };
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| }
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| </syntaxHighlight>
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| Any other subsequent nodes can be added with a sligtly different config:
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| <syntaxHighlight lang=nix>
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| {
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| services.k3s = {
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| enable = true;
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| role = "server";
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| token = "<randomized common secret>";
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| serverAddr = "https://<ip of first node>:6443";
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| };
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| }
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| </syntaxHighlight>
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| For this to work you need to open the aforementioned API, etcd, and flannel ports in the firewall. Note that it is [https://etcd.io/docs/v3.3/faq/#why-an-odd-number-of-cluster-members recommended] to use an odd number of nodes in such a cluster.
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| Or see this [https://github.com/Mic92/doctor-cluster-config/tree/master/modules/k3s real world example]. You might want to ignore some parts of it i.e. the monitoring as this is specific to our setup.
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| The K3s server needs to import <code>modules/k3s/server.nix</code> and an agent <code>modules/k3s/agent.nix</code>.
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| Tip: You might run into issues with coredns not being reachable from agent nodes. Right now, we disable the NixOS firewall all together until we find a better solution.
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| == ZFS support ==
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| K3s's builtin containerd does not support the zfs snapshotter. However, it is possible to configure it to use an external containerd:
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| <syntaxHighlight lang=nix>
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| virtualisation.containerd = {
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| enable = true;
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| settings =
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| let
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| fullCNIPlugins = pkgs.buildEnv {
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| name = "full-cni";
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| paths = with pkgs;[
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| cni-plugins
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| cni-plugin-flannel
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| ];
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| };
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| in {
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| plugins."io.containerd.grpc.v1.cri".cni = {
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| bin_dir = "${fullCNIPlugins}/bin";
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| conf_dir = "/var/lib/rancher/k3s/agent/etc/cni/net.d/";
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| };
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| };
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| };
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| # TODO describe how to enable zfs snapshotter in containerd
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| services.k3s.extraFlags = toString [
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| "--container-runtime-endpoint unix:///run/containerd/containerd.sock"
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| ];
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| </syntaxHighlight>
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| == Network policies ==
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| The current k3s derivation doesn't include <code>ipset</code> package, which is required by the network policy controller.
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| k3s logs
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| <syntaxHighlight lang=text>
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| level=warning msg="Skipping network policy controller start, ipset unavailable: ipset utility not found"
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| </syntaxHighlight>
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| There is an open pull request to fix it https://github.com/NixOS/nixpkgs/pull/176520#pullrequestreview-1304593562. Until then, the package can be added to k3s's path as follows
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| <syntaxHighlight lang=nix>
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| systemd.services.k3s.path = [ pkgs.ipset ];
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| </syntaxHighlight>
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| == Nvidia support ==
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| To use Nvidia GPU in the cluster the nvidia-container-runtime and runc are needed. To get the two components it suffices to add the following to the configuration
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| <syntaxHighlight lang=nix>
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| virtualisation.docker = {
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| enable = true;
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| enableNvidia = true;
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| };
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| environment.systemPackages = with pkgs; [ docker runc ];
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| </syntaxHighlight>
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| Note, using docker here is a workaround, it will install nvidia-container-runtime and that will cause it to be accessible via "/run/current-system/sw/bin/nvidia-container-runtime", currently its not directly accessible in nixpkgs.
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| You now need to create a new file in <code>/var/lib/rancher/k3s/agent/etc/containerd/config.toml.tmpl</code> with the following
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| <syntaxHighlight lang=toml>
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| {{ template "base" . }}
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| [plugins."io.containerd.grpc.v1.cri".containerd.runtimes.nvidia]
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| privileged_without_host_devices = false
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| runtime_engine = ""
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| runtime_root = ""
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| runtime_type = "io.containerd.runc.v2"
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| [plugins."io.containerd.grpc.v1.cri".containerd.runtimes.nvidia.options]
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| BinaryName = "/run/current-system/sw/bin/nvidia-container-runtime"
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| </syntaxHighlight>
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| Note here we are pointing the nvidia runtime to "/run/current-system/sw/bin/nvidia-container-runtime".
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| Now apply the following runtime class to k3s cluster:
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| <syntaxHighlight lang=yaml>
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| apiVersion: node.k8s.io/v1
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| handler: nvidia
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| kind: RuntimeClass
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| metadata:
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| labels:
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| app.kubernetes.io/component: gpu-operator
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| name: nvidia
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| </syntaxHighlight>
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| Following [https://github.com/NVIDIA/k8s-device-plugin#deployment-via-helm k8s-device-plugin] install the helm chart with <code>runtimeClassName: nvidia</code> set. In order to passthrough the nvidia card into the container, your deployments spec must contain
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| - runtimeClassName: nvidia
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| - env:
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| - name: NVIDIA_VISIBLE_DEVICES
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| value: all
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| - name: NVIDIA_DRIVER_CAPABILITIES
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| value: all
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| to test its working exec onto a pod and run <code>nvidia-smi </code>. For more configurability of nvidia related matters in k3s look in [https://docs.k3s.io/advanced#nvidia-container-runtime-support k3s-docs]
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| == Troubleshooting ==
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| === Raspberry Pi not working ===
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| If the k3s.service/k3s server does not start and gives you the error <code>FATA[0000] failed to find memory cgroup (v2)</code> Here's the github issue: https://github.com/k3s-io/k3s/issues/2067 .
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| To fix the problem, you can add these things to your configuration.nix.
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| <source lang="nix"> boot.kernelParams = [
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| "cgroup_enable=cpuset" "cgroup_memory=1" "cgroup_enable=memory"
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| ];
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| </source>
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| [[Category:Applications]]
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| [[Category:Server]]
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| [[Category:orchestration]] | |
