Kubernetes on Raspberry Pi with k3s
raspberrypikubernetesk3s2019-07-25 - carpie

For a long time I've been interested in building a Kubernetes cluster out of a stack of inexpensive Raspberry Pis. Following along with various tutorials on the web I was able to get Kubernetes installed and working in a 3 Pi cluster. However, the RAM and CPU requirements on the master node overwhelmed my Pi. This caused poor performance when doing various Kubernetes tasks. It also made an in-place upgrade of Kubernetes impossible.

As a result, I was very excited to see the k3s project from Rancher Labs. K3s is billed as a lightweight Kubernetes for use in resource constrained environments. It is also optimized for ARM processors. This makes running a Raspberry Pi-based Kubernetes cluster much more feasible. In fact, we are going to create one in this article.

Materials needed

To create the Kubernetes cluster described in this article, we are going to need:

  • At least one Raspberry Pi (with SD card and power adapter)
  • Ethernet cables
  • A switch or router to connect all our Pis together

We will be installing k3s from the internet, so they will need to be able to access the internet through the router.

An overview of our cluster

For this cluster, we are going to use three Raspberry Pis. The first we'll name kmaster and assign a static IP of (since our local network is The first worker node (the second Pi) we'll name knode1 and assign an IP of The final worker node we'll name knode2 and assign an IP of

Obviously, if you have a different network layout, you may use any network/IPs you have available. Just substitute your own values anywhere IPs are used in this article.

So that we don't have to keep refering to each node by IP, let's add their host names to our /etc/hosts file on our PC.

echo -e "\tkmaster" | sudo tee -a /etc/hosts
echo -e "\tknode1" | sudo tee -a /etc/hosts
echo -e "\tknode2" | sudo tee -a /etc/hosts

Installing the master node

Now we're ready to install the master node. The first step is to install the latest Raspbian image. I am not going to explain that here, but I have a detailed article on how to do this if you need it. So please go install Raspbian, enable the SSH server, set the hostname to kmaster, and assign a static IP of

Now that Raspbian is installed on the master node, let's boot our master Pi and ssh into it.

ssh pi@kmaster

In recent versions of Raspberry Pi OS (formerly Raspbian), the memory cgroup is disabled by default. k3s requires this to run. We can enable it by editing /boot/cmdline.txt and adding

cgroup_memory=1 cgroup_enable=memory

to the end of the line. Once we've done that, we need to reboot the Pi and ssh to it again when it comes back up.

sudo reboot
ssh pi@kmaster

Now we're ready to install k3s. Rancher Labs have made this really, really simple. On the master Pi, run:

curl -sfL https://get.k3s.io | sh -

When the command finishes, we already have a single node cluster set up and running! Let's check it out. Still on the Pi, run:

sudo kubectl get nodes

You should see something similar to:

kmaster   Ready    master    2m13s    v1.14.3-k3s.1

Extracting the join token

We want to add a couple of worker nodes. When installing k3s on those nodes we will need a join token. The join token exists on the master node's filesystem. Let's copy that and save it somewhere we can get to it later.

sudo cat /var/lib/rancher/k3s/server/node-token

Installing the worker nodes

Grab some SD cards for the two worker nodes and install Raspbian on each. For one, set the hostname to knode1 and assign an IP of For the other, set the hostname to knode2 and assign an IP of Now, let's install k3s.

Boot your first worker node and ssh into it:

ssh pi@knode1

On the Pi, we'll install k3s as before, but we will give the installer extra parameters to let it know that we are installing a worker node and that we'd like to join the existing cluster:

curl -sfL http://get.k3s.io | K3S_URL= \
K3S_TOKEN=join_token_we_copied_earlier sh -

Replace join_token_we_copied_earlier with the token from the Extracting the join token section.

Repeat these steps for knode2.

Access the cluster from our PC

It'd be annoying to have to ssh to the master node to run kubectl anytime we wanted to inspect or modify our cluster. So, we want to put kubectl on our PC. But first, let's get the configuration information we need from our master node. ssh into kmaster and run:

sudo cat /etc/rancher/k3s/k3s.yaml

Copy this configuration information and return to your PC. Make a directory for the config:

mkdir ~/.kube

Save the copied configuration as ~/.kube/config. Now edit the file and change the line:

    server: https://localhost:6443

to be:

    server: https://kmaster:6443

For security purpose, limit the file's read/write permissions to just yourself:

chmod 600 ~/.kube/config

Now let's install kubectl on our PC (if you don't already have it). The Kubernetes site has instructions for doing this for various platforms. Since I'm running Linux Mint, an Ubuntu derivative, I'll show the Ubuntu instructions here.

sudo apt update && sudo apt install -y apt-transport-https
curl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add -
echo "deb https://apt.kubernetes.io/ kubernetes-xenial main" | \
  sudo tee -a /etc/apt/sources.list.d/kubernetes.list
sudo apt update && sudo apt install kubectl

If you're not familiar, the above commands add a Debian repository for Kubernetes, grab it's GPG key for security, and then update the list of packages and install kubectl. Now, we'll get notifications of any updates for kubectl through the standard software update mechanism.

Now we can check out our cluster from our PC! Run:

kubectl get nodes

You should see something like:

kmaster   Ready    master    12m      v1.14.3-k3s.1
knode1    Ready    worker    103s     v1.14.3-k3s.1
knode2    Ready    worker    68s      v1.14.3-k3s.1

Congratulations! You have a working 3-node Kubernetes cluster!

The k3s bonus

If you run kubectl get pods --all-namespaces, you will see some extra pods for Traefik. Traefik is a reverse proxy and load balancer that we can use to direct traffic into our cluster from a single entry point. Kubernetes allows for this but doesn't provide such a service directly. Having Traefik installed by default is a nice touch by Rancher Labs. This makes a default k3s install fully complete and immediately usable!

We're going to explore using Traefik through Kubernetes ingress rules and deploy all kinds of goodies to our cluster in future articles. Stay tuned!