How to Build a Raspberry Pi Kubernetes Cluster

Learning Kubernetes doesn’t require expensive server hardware. Building a Raspberry Pi Kubernetes cluster gives you a genuine multi-node environment to practice real orchestration concepts — scheduling, scaling, self-healing — on a handful of inexpensive boards that together draw less power than a single light bulb.

Why Use Raspberry Pi for Kubernetes

• Low cost of entry – several Raspberry Pi boards together often cost less than a single used enterprise server
• True multi-node practice – unlike running Kubernetes on a single machine, a Pi cluster forces you to think about actual distributed scheduling and node failure scenarios
• Minimal power draw – an entire cluster of 3–4 Raspberry Pi boards typically consumes under 20 watts combined
• Portable and quiet – small enough to fit on a desk shelf, completely silent since there are no fans

Hardware Requirements

For a functional cluster, plan for:

• 3–5 Raspberry Pi boards (Pi 4 or Pi 5 recommended, with at least 4GB RAM each — 2GB models will work but limit how much you can run per node)
• microSD cards or USB SSDs – USB SSDs offer noticeably better performance and reliability than microSD cards for sustained workloads
• A small network switch – to connect all Pi boards on the same local network
• A cluster case or mounting rack – keeps everything organized and improves airflow around each board

Choosing a Lightweight Kubernetes Distribution

Full upstream Kubernetes is too resource-heavy for Raspberry Pi hardware. Instead, homelab users typically choose:

• K3s – a lightweight, certified Kubernetes distribution by Rancher, specifically designed for resource-constrained environments like ARM boards
• MicroK8s – Canonical’s lightweight Kubernetes distribution, also well-suited to Raspberry Pi hardware

K3s is generally the more popular choice for Pi clusters due to its especially small footprint and straightforward installation process.

Preparing Each Raspberry Pi

1. Flash Raspberry Pi OS Lite (headless, no desktop environment) onto each board’s storage using the Raspberry Pi Imager tool.
2. Enable SSH access during the imaging process so you can configure each board remotely without needing a monitor attached.
3. Assign a static IP address to each Pi on your network, making it easier to reliably reference each node later.

Installing K3s on the Control Node

On the Pi designated as your control (master) node:

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

Retrieve the node token needed for other Pi boards to join the cluster:

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

Joining Worker Nodes to the Cluster

On each remaining Raspberry Pi, join it to the cluster using the control node’s IP address and the token retrieved above:

curl -sfL https://get.k3s.io | K3S_URL=https://<control-node-ip>:6443 K3S_TOKEN=<node-token> sh -

Verifying the Cluster

Back on the control node, confirm all Pi boards have successfully joined as cluster nodes:

sudo kubectl get nodes

You should see every Raspberry Pi listed with a “Ready” status.

What to Deploy on Your Pi Cluster

Once running, good beginner projects to practice real Kubernetes concepts include:

• A simple web app deployment scaled across multiple replicas
• Pi-hole running as a Kubernetes deployment with a persistent volume
• Practicing rolling updates and observing how pods reschedule when a node is intentionally powered off

Final Thoughts

Building a Raspberry Pi Kubernetes cluster turns abstract orchestration concepts into something you can physically see and touch — literally pulling the power cord on one node and watching Kubernetes reschedule its workloads elsewhere. For anyone learning Kubernetes for career purposes or simply curious about container orchestration, a small Pi cluster remains one of the most affordable, hands-on ways to build real experience.