Introduction

In this tutorial, we will guide you on how to set up a Kubernetes cluster using Amazon Web Services (AWS) Elastic Kubernetes Service (EKS). Kubernetes is an open-source platform for automating deployment, scaling, and management of containerized applications. AWS EKS is a managed service that makes it easy to run Kubernetes on AWS without needing to install, operate, and maintain your own Kubernetes control plane or worker nodes.

By the end of this tutorial, you will learn how to:

• Set up and configure an AWS EKS Cluster
• Deploy a simple application on the Kubernetes cluster
• Monitor and scale your application

Prerequisites:

Before starting, you should have the following:

• An AWS account
• AWS CLI installed and configured
• kubectl installed (this is the Kubernetes command-line tool)
• Knowledge of basic Kubernetes principles

Step-by-Step Guide

Step 1: Setting up the EKS cluster

First, we need to create a VPC (Virtual Private Cloud) for our EKS Cluster. You can do this by navigating to the VPC section in the AWS Management Console and creating a new VPC.

Next, we need to create an IAM role for our EKS cluster. Navigate to the IAM section in the AWS Management Console and create a new role. Attach the AmazonEKSClusterPolicy to this role.

Now, we are ready to create our EKS cluster. Navigate to the EKS section in the AWS Management Console and click on 'Create EKS Cluster'. Fill in the details, select the VPC and IAM role we created, and create the cluster.

Step 2: Configuring kubectl

After the EKS Cluster is active, we need to configure kubectl to interact with our cluster. Run the following command to update the kubeconfig file:

aws eks --region region update-kubeconfig --name cluster_name

Replace region with your AWS region and cluster_name with the name of your EKS Cluster.

Step 3: Deploying an Application

Now, let's deploy a simple nginx application on our cluster. Create a file named nginx-deployment.yaml and add the following content:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: nginx-deployment
spec:
  replicas: 3
  selector:
    matchLabels:
      app: nginx
  template:
    metadata:
      labels:
        app: nginx
    spec:
      containers:
      - name: nginx
        image: nginx:1.14.2
        ports:
        - containerPort: 80

Run the following command to deploy the application:

kubectl apply -f nginx-deployment.yaml

Code Examples

We've already seen a few code examples above. Let's go through them in a bit more detail:

• aws eks --region region update-kubeconfig --name cluster_name: This command updates the kubeconfig file for kubectl to interact with our EKS Cluster.

• kubectl apply -f nginx-deployment.yaml: This command tells kubectl to create the resources defined in the nginx-deployment.yaml file. In this case, it creates a Deployment with 3 replicas of the nginx server.

Summary

In this tutorial, we've seen how to set up and configure an AWS EKS Cluster, and how to deploy a simple nginx server on it. It's important to remember that this is just the start - Kubernetes offers a wide range of features for managing and scaling applications.

For further learning, consider exploring how to set up a CI/CD pipeline for your Kubernetes applications, or how to monitor your applications using services like AWS CloudWatch or Prometheus.

Practice Exercises

1. Deploy a different application on your Kubernetes cluster.
2. Try scaling the number of replicas in your Deployment and observe what happens.
3. Try deleting a Pod created by your Deployment and observe what happens.

Solutions

1. The process to deploy a different application is the same as deploying the nginx server. You just need to replace the image name in the containers section of your Deployment yaml.
2. You can scale your Deployment by updating the replicas field in your Deployment yaml and reapplying it using kubectl apply. Kubernetes will automatically create or delete Pods to match the desired number.
3. If you delete a Pod created by your Deployment, Kubernetes will automatically create a new Pod to replace it. This is because a Deployment ensures that a certain number of Pods are always running.