A local Kubernetes setup from scratch

This is one of the most interesting experiments I've done with Kubernetes. I had three linux machines lying around and I decided to create a Kubernetes cluster from scratch. This was a great learning experience and I highly recommend you try this out if you have the resources. I wanted everything to be interconnected over my home wifi network. This is how I did it:

Machines used

3 laptops running Ubuntu 22.04 LTS. These laptops had Docker installed on them and were connected to the same wifi network.

Common setup

Install Docker on all machines

I followed the official Docker documentation here. Here are some points to note to ease the process:

  1. If the apt-get update fails with an error in reading from the docker.list file, make sure that the url in the file ends with ubuntu and not with debian.
  2. Follow the post installation instructions to run Docker as a non-root user. Restart the machine after this step, you'll be able to run Docker commands without sudo.

Install CRI-Dockerd on all machines

This is a Kubernetes requirement. It's important to have the Container Runtime Interface (CRI) installed on all machines. I used the following method to install CRI-Dockerd:

  1. Open the Terminal and run the following command to download the deb package:
wget https://github.com/Mirantis/cri-dockerd/releases/download/v0.3.14/cri-dockerd_0.3.14.3-0.ubuntu-jammy_amd64.deb
  1. Install the package by running
sudo dpkg -i  cri-dockerd_0.3.14.3-0.ubuntu-jammy_amd64.deb
  1. After the installation is complete, run 
sudo systemctl enable cri-docker
sudo systemctl start cri-docker
  1. Verify the installation by running 
sudo systemctl status cri-docker

Now that the container runtime is installed on all machines, we can proceed to set up the Kubernetes cluster.

Install kubeadm, kubelet, and kubectl on all machines

First turn off swap on all machines by running 

sudo swapoff -a

Go to the official installation instructions and follow the steps to install kubeadm, kubelet, and kubectl on all machines.


At this point we've set up the common requirements on all machines. Now we can proceed to set up the Kubernetes cluster.

Setting up the Master Node

  1. Run the following command to initialize the master node:
kubeadm init --cri-socket=unix:///var/run/cri-dockerd.sock --pod-network-cidr=192.168.0.0/16

The --cri-socket=unix:///var/run/cri-dockerd.sock is used to specify which CRI to use. Since we're using CRI-Dockerd, we need to specify the socket path.

The --pod-network-cidr=192.168.0.0/16 is used to specify the range of IP addresses that pods can use. This is a pool of 65,536 IP addresses that Kubernetes can assign to pods.

  1. After the command completes, you'll see a message like this:

  2. Next, we'll install Calico as the CNI plugin. A CNI plugin is used to provide networking and security services to pods. Calico is a popular choice for Kubernetes clusters. This plugin is used to assign IP addresses to pods and provide network policies. Head on here and setup Calico on the Kubernetes cluster.

Great! Now our master node is set up. Let's move on to setting up the worker nodes. Instead of running kubeadm init on the worker nodes, we have to run kubeadm join to join the worker nodes to the master node. To get the join command, run the following command on the master node:

kubeadm token create --print-join-command

This will print the join command. Copy this command.

Setting up the Worker Nodes

  1. Add the parameter --cri-socket=unix:///var/run/cri-dockerd.sock to the join command and run it on the worker nodes with sudo. This will join the worker nodes to the master node.
  2. Verify that the worker nodes have joined the cluster by running 
kubectl get nodes

This will show the master node and the worker nodes.

$ kubectl get nodes
NAME      STATUS   ROLES           AGE     VERSION
master    Ready    control-plane   4h3m    v1.30.2
worker1   Ready    <none>          3h53m   v1.30.2
worker2   Ready    <none>          3h52m   v1.30.2

And that's it! We have a Kubernetes cluster up and running from scratch. You can now deploy applications to this cluster and experiment with Kubernetes.

From now on, I'll be using this setup to demonstrate various Kubernetes concepts, but you can use the three node Minikube cluster as mentioned here to simulate this setup.