How to Install Kubernetes on Ubuntu

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How to Install Kubernetes on Ubuntu

In this tutorial, we will learn how to install Kubernetes on Ubuntu the hard way.

We will specify all the command to get a fully functionating Kubernetes cluster and describe their roles.

To perform this demo, we will use an Amazon Web Service EC2 Virtual machines of type t2.large that will provide us 2 CPU and 8 RAM.

The installation is the same on the cloud or on your local machine: the main difference here is that a machine in AWS has two IPs: a public IP and a private IP. So, we need an extra setup to generate certificates for both IPs while bootstrapping the cluster in a cloud hosted VM, while for the local VM, you can simply escape this setup.

Before  you begin

Before installing Kubernetes, your VMs must respect a set of conditions first:

  • Your ubuntu machines must run Ubuntu 16.04+ / Debian 9+
  • 2 or more CPU and RAM.
  • Full public or private network connectivity between all machines in the cluster.
  • Kubernetes custom port allowed on your security group and your firewall.
  • Swap disabled for the service to work properly.

 

If you are using CentOS based distribution, please check Install Kubernetes on CentOS.

To check your release, you can us:

cat /etc/*-release
VM distribution
VM distribution

You can check your resources with the command “htop”

VM Resources
VM Resources

If you’re machine has swap, you can disable it by deleting the swap definition line in the file “ /etc/fstab” and then disable it by using:

sudo swapoff -a

To be able to run Kubernetes, you must make sure that br_netfilter module is loaded.

To enable it, you can use the following command:

sudo modprobe br_netfilter

In addition to that, you must let iptables see bridged traffic: to do so, you must set net.bridge.bridge-nf-call-iptables is set to 1 in your sysctl config. You do that with:

cat <<EOF | sudo tee /etc/sysctl.d/k8s.conf
net.bridge.bridge-nf-call-ip6tables = 1
net.bridge.bridge-nf-call-iptables = 1
EOF
sudo sysctl --system
setting iptables
setting iptables

 

And now there is a full list of the ports you must allow to install Kubernetes on Ubuntu:

For the master nodes:

 

Protocol Port
TCP Inbound 6443*
TCP Inbound 2379-2380
TCP Inbound 10250
TCP Inbound 10251
TCP Inbound 10252

 

For worker nodes:

Protocol Port
TCP Inbound 10250
TCP Inbound 30000-32767

 

Installing container runtime:

To use Kubernetes, your machine must firstly have a working container runtime, but in our example we will be using you can check this tutorial if you haven’t installed docker yet.

docker version
docker version

 

Now all is set, and we are ready to install Kubernetes on Ubuntu.

Installing Kubernetes on Ubuntu:

Actually, to install Kubernetes, we need to install the following three packages:

    • kubeadm: the command to create or destroy the cluster.
    • kubelet: the component/service that runs on all of the machines in the cluster and manages them.
    • kubectl: the CLI used to control the cluster.

We need to install the dependencies that we will need through the installation

sudo apt-get update && sudo apt-get install -y apt-transport-https curl

We need to add the Kubernetes official repository to the repositories list:

sudo curl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
cat <<EOF >/etc/apt/sources.list.d/kubernetes.list
deb https://apt.kubernetes.io/ kubernetes-xenial main
EOF

 

Now we will update the repositories’ list to load the last version of the packages then we will install kubelet, kubeadm and kubectl

sudo apt-get update && sudo apt-get install -y kubelet kubeadm kubectl

And other good move to do is to disable the update of these packages, especially in production: new versions can modify some functionalities that your already deployed apps need causing them to fail. We can disable the update with:

sudo apt-mark hold kubelet kubeadm kubectl

we can check for the installed version:

kubectl version
kubectl version

Kubelet will be on crash loop waiting for kubeadm to initiate or join a cluster.

kubelet logs
kubelet logs

Configuring cgroup

By default, docker uses “cgroupfs” as cgroup driver. However, kubelet recommends “systemd”. So, we need to change docker cgroup with:

cat <<EOF | sudo tee /etc/docker/daemon.json
{  "exec-opts": ["native.cgroupdriver=systemd"],
   "log-driver": "json-file",
   "log-opts": {
      "max-size": "100m"
    },
    "storage-driver": "overlay2"
}
EOF
sudo mkdir -p /etc/systemd/system/docker.service.d
sudo systemctl daemon-reload
sudo systemctl restart docker

So now, all the machines of the cluster must be equipped with Kubernetes installed the way described above.

For me, I will clone the created machine to create two other VMs with Kubernetes already installed. We will name them to node1 and node2 and the main VM will be the master.

cluster infrastructure
cluster infrastructure

Once the infrastructure is ready, we can bootstrap a Kubernetes cluster:

We need first to create a new cluster in the master using the init command in the master machine:

sudo kubeadm init

But this will create a locally available cluster. Since my cluster will be hosted on AWS cloud, it needs to be available through both private and public ip, to do so we will use the “–apiserver-cert-extra-sans” flag.

If you are running a cluster on your local VM, just use the previous command, you don’t need this flag.

sudo kubeadm init --apiserver-cert-extra-sans=<PrivateIP>,<PublicIP>
cluster initiation
cluster initiation

Once the new cluster ready, we will get the commands that we must run to use the cluster with the CLI kubectl: kubectl always check the directory “$HOME/.kube” for the config file so we need to create that directory and copy the config file that kubeadm generated. And then change the ownership of this file to our user so he can use the CLI without root privileges. So you must run these commands in the master machine

cluster setup
cluster setup

Then we should join the worker nodes to the cluster using the join command in the worker nodes:

Note that kubeadm must be ran with root privileges:

joining nodes to the cluster
joining nodes to the cluster

If we check the list of nodes with this command in the master node:

kubectl get nodes
checking nodes status
checking nodes status

PS: if you want a single node cluster where the master is the control plane and the worker node in the same time, you need to taint the master.

To do so, you simply need to use the following command in the master node:

kubectl taint nodes --all node-role.kubernetes.io/master-

All the nodes joined the cluster successfully, but they are not ready: the reason is that Kubernetes needs a third-party network plugin that will allow the Pods to communicate and there’s no plugin installed yet.

Here is a list of some plugins that Kubernetes supports:

supported plugins
supported plugins

In this tutorial, we will use WeaveNet, so to install it just this command on any node of the cluster that is able to use kubectl:

kubectl apply -f "https://cloud.weave.works/k8s/net?k8s-version=$(kubectl version | base64 | tr -d '\n')"

 

installing weavenet
installing weavenet

We will check if the nodes are now ready:

checking nodes status
checking nodes status

To test if the cluster is working perfectly, we will test it through deploying Nginx on it.

This can be applied on any node of the cluster that is able to use kubectl:

First of all, we will deploy a Nginx app using:

kubectl create deployment nginx --image=nginx

after that, we will create a service that will expose that deployment

kubectl create service nodeport nginx --tcp=80:80

Now if we check our deployed app and service, we can figure out the port the app is running on:

deploying a nginx for test
deploying a nginx for test

If we check the browser on the specific port, we can find Nginx running perfectly:

checking the app on the browser
checking the app on the browser

In this tutorial, we had the chance to install Kubernetes on Ubuntu, and we have also initiated a multi node cluster.

In the next tutorial, we will learn to deploy different apps and projects on Kubernetes.

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