Building Your Own Home Kubernetes Cluster with k0s and Remote Access

Kubernetes is the powerhouse of modern container orchestration, but setting it up at home or on minimal infrastructure can feel daunting. In this blog, I will walk you through creating a lightweight, fully functional Kubernetes cluster using k0s, complete with a control plane and a worker node, and make it accessible remotely via a Pangolin tunnel.

By the end, you will have a cluster you can experiment on from anywhere.

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Why k0s?

k0s is a lightweight, all-in-one Kubernetes distribution that simplifies the setup process:

• Single binary for control plane and worker.

• Minimal resource usage: ideal for home servers or VMs.

• Easy to manage, yet fully compliant with Kubernetes APIs.

• Perfect for learning, experimentation, or small production projects.

This makes it ideal for our goal: a home lab cluster with remote access.

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Step 1: Setting Up the Control Plane

The control plane is the “brain” of the Kubernetes cluster: it manages nodes, schedules workloads, and exposes the API server.

Install k0s

sudo apt update && sudo apt install curl -y
curl -sSLf https://get.k0s.sh | sudo bash
k0s version

Next, install the controller and start it:

sudo k0s install controller
sudo k0s start
sudo k0s status

Output example:

Version: v1.34.1+k0s.1
Role: controller
Workloads: false
SingleNode: false

This confirms the control plane is running.

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Step 2: Configure kubectl on the Control Plane

To interact with Kubernetes, we need kubectl, the CLI tool.

1. Generate your kubeconfig:

mkdir -p ~/.kube
sudo k0s kubeconfig admin > ~/.kube/config
chmod 600 ~/.kube/config

2. Install kubectl:

curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"
sudo install -o root -g root -m 0755 kubectl /usr/local/bin/kubectl

3. Verify the cluster is reachable:

kubectl get nodes

At this point, you have a single-node control plane ready.

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Step 3: Add a Worker Node

The worker node is where your workloads (pods, deployments, services) will actually run.

1. On the control plane, generate a token for the worker:

sudo k0s token create --role=worker

2. On the worker machine:

sudo apt update && sudo apt install curl -y
curl -sSLf https://get.k0s.sh | sudo bash
nano tokenfile  # paste the token from control plane
sudo k0s install worker --token-file tokenfile
sudo k0s start
sudo systemctl enable --now k0sworker
sudo journalctl -fu k0sworker

3. Back on the control plane, verify the worker joined:

kubectl get nodes -o wide

Output:

NAME                STATUS   ROLES    AGE   VERSION       INTERNAL-IP     EXTERNAL-IP   OS-IMAGE             KERNEL-VERSION     CONTAINER-RUNTIME
ubuntu-workernode   Ready    <none>   20m   v1.34.1+k0s   192.168.29.39   <none>        Ubuntu 24.04.3 LTS   6.8.0-87-generic   containerd://1.7.28

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Step 4: Accessing Your Cluster Remotely

One of the most exciting parts is accessing your cluster from outside your network. For this, we will use a Pangolin tunnel to expose the control plane.

You can follow my previous blog regarding Pangolin setup:

https://blog.nyzex.in/self-hosting-pangolin-newt-on-your-own-server

1. Copy your kubeconfig to your remote machine.

#first create the kubeconfig file in the controlplane vm
sudo k0s kubeconfig admin > ~/.kube/config
chmod 600 ~/.kube/config
cat ~/.kube/config

2. Update the server: field to your Pangolin hostname (after copying this config to our remote machine):

clusters:
- cluster:
    server: https://tunnel.nyzex.in:6443
    insecure-skip-tls-verify: true
  name: local

Note: insecure-skip-tls-verify: true bypasses the TLS hostname check since our certificate is for internal names. This is fine for personal labs, but not recommended for production.

3. Set your kubeconfig and verify:

export KUBECONFIG=$(pwd)/kubeconfig
kubectl get nodes -o wide

You should see both the control plane and worker node, now accessible remotely.

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Step 5: How It Works

Here’s a simple view of the setup:

• Control Plane: API server and cluster management.

• Worker Node: Runs workloads.

• Remote Machine: Access via Pangolin tunnel.

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What to do next?

• For production-grade security, generate a certificate that includes your external hostname instead of skipping TLS verification.

• Add more workers to scale your cluster.

• Deploy your first workloads and explore Kubernetes features.

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Conclusion

With a few steps, you now have a home Kubernetes lab:

• Control plane + worker node cluster.

• Remote kubectl access via Pangolin tunnel.

• Fully functional, ready to deploy workloads.

This setup is perfect for experimenting with Kubernetes, testing CI/CD pipelines, or just learning cluster management hands-on.