💡 Introduction:

Welcome to the world of DevOps! In this blog, we’ll embark on an exciting journey to build a full-fledged CI/CD project from scratch. We’ll start by creating an EC2 instance to serve as our working environment. From there, we’ll clone a Voting Application project from a GitHub repository and set up the necessary tools, including Docker and Kind (a lightweight Kubernetes tool). We’ll then install ArgoCD in the cluster to implement Continuous Delivery, enabling seamless automated deployments whenever we make changes to the code. By the end of this tutorial, you’ll have hands-on experience with modern DevOps workflows and a fully functional pipeline for deploying containerized applications.

Let’s get started!

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💡 Pre-requisites

Before diving into this project, let’s make sure we have the basics covered. A little preparation goes a long way in making the process smooth and enjoyable. Here’s what you should have a basic understanding of:

• AWS EC2: Familiarity with launching and managing EC2 instances will help you set up the working environment.

• Docker and Kind (Kubernetes): Understanding containerization with Docker and how Kind creates Kubernetes clusters locally will make the deployment process easier to follow.

• ArgoCD: A basic idea of what ArgoCD is and how it manages continuous delivery will help you grasp its role in automating application updates.

If you’re new to any of these, don’t worry! We’ll guide you through the steps, and you’ll pick things up as we progress.

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💡 Setting Up the EC2 Instance

To kickstart our project, we need an AWS EC2 instance with a bit more compute power to support our Kubernetes cluster (which includes a control plane and two worker nodes). Let’s create a t2.medium instance by following these steps:

1. Navigate to the AWS EC2 dashboard and click on Launch Instance.

2. Provide a name for your instance, such as k8s-voting-app.

3. Select Ubuntu as the AMI (Amazon Machine Image).

   

4. In the Network settings, allow HTTP (port 80) and HTTPS (port 443) for web traffic.

5. Set up a key pair for secure access. If you already have one, select it. Otherwise, generate a new key pair and download it—it will be required to log in to your instance via SSH.

   

Once the instance is created:

1. Make the key executable by running:

    chmod +x <your_key.pem>
   

2. Use the SSH command provided in the SSH Client tab of the instance’s Connect page to log in:

    ssh -i <your_key.pem> ubuntu@<your_instance_public_ip>
   

After logging into the server:

1. Update the system:

    sudo apt update
   

2. Install Docker:

    sudo apt install docker.io -y
   

3. Add the current user (default is ubuntu) to the Docker group so you can run Docker commands without sudo:

    sudo usermod -aG docker $USER
   

4. Reboot the instance to apply the changes:

    sudo reboot
   

Once the instance reboots, reconnect using the same SSH command. After logging back in, verify Docker installation by running:

docker --version

With Docker installed and ready to use, we’re now set to proceed with setting up Kind for our Kubernetes cluster.

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💡 Installing Kind and Kubectl

With Docker installed on the EC2 instance, the next step is to set up Kind (Kubernetes in Docker) to create our lightweight Kubernetes cluster. Additionally, we’ll install kubectl, the Kubernetes command-line tool, to interact with the cluster.

Installing Kind

To install Kind, run the following commands on the EC2 instance:

[ $(uname -m) = x86_64 ] && curl -Lo ./kind https://kind.sigs.k8s.io/dl/v0.20.0/kind-linux-amd64  
chmod +x ./kind  
sudo cp ./kind /usr/local/bin/kind  
rm -rf kind

This downloads the Kind binary, makes it executable, and moves it to a system-wide path for easy access.

Installing Kubectl

To simplify the kubectl installation, we’ll create a script file. Follow these steps:

1. Create a file named install_kubectl.sh:

    nano install_kubectl.sh
   

2. Paste the following script into the file:

    #!/bin/bash  
   
    # Variables  
    VERSION="v1.30.0"  
    URL="https://dl.k8s.io/release/${VERSION}/bin/linux/amd64/kubectl"  
    INSTALL_DIR="/usr/local/bin"  
   
    # Download and install kubectl  
    curl -LO "$URL"  
    chmod +x kubectl  
    sudo mv kubectl $INSTALL_DIR/  
    kubectl version --client  
   
    # Clean up  
    rm -f kubectl  
   
    echo "kubectl installation complete."
   

3. Save and close the file, then make it executable:

    chmod +x install_kubectl.sh
   

4. Run the script to install kubectl:

    ./install_kubectl.sh
   

   

After the installation is complete, you can verify that kubectl is installed correctly by checking its version:

kubectl version --client

With Kind and kubectl installed, your EC2 instance is now ready to create and manage a Kubernetes cluster. Let’s move on to setting up the cluster!

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💡 Creating a Kubernetes Cluster with Kind

With Kind and kubectl installed, we can now create a Kubernetes cluster tailored to our needs. This involves creating a configuration file that defines the cluster structure and then using Kind to deploy the cluster.

Step 1: Create the Configuration File

Start by creating a file named config.yaml:

nano config.yaml

Add the following content to the file:

kind: Cluster  
apiVersion: kind.x-k8s.io/v1alpha4  

nodes:  
- role: control-plane  
  image: kindest/node:v1.30.0  
- role: worker  
  image: kindest/node:v1.30.0  
- role: worker  
  image: kindest/node:v1.30.0

Explanation of config.yaml:

1. kind: Specifies that we are defining a Kubernetes cluster.

2. apiVersion: Indicates the Kind API version being used.

3. nodes: Defines the cluster’s nodes and their roles:

   • control-plane: The node that runs the Kubernetes control plane, managing the cluster.

   • worker: Nodes that will run application workloads.

4. image: Specifies the version of the Kind node image to use (v1.30.0 in this case).

This configuration creates a cluster with one control plane and two worker nodes.

Step 2: Create the Cluster

Run the following command to create the cluster based on the configuration:

kind create cluster --config=config.yaml --name my-cluster

This command initializes a cluster named my-cluster with the nodes and roles defined in the configuration file. The process may take a few minutes as Kind pulls the required images and sets up the cluster.

Step 3: Set the Kubernetes Context

Once the cluster is created, you’ll need to set the current context of kubectl to your new cluster:

kubectl cluster-info --context kind-my-cluster

This ensures that all subsequent kubectl commands interact with the my-cluster Kind cluster.

At this stage, you now have a fully functional Kubernetes cluster running locally on your EC2 instance, ready for deploying and managing applications. Next, we’ll move on to deploying the Voting App!

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💡 Installing ArgoCD in the Kubernetes Cluster

With our Kind cluster up and running, the next step is to set up ArgoCD, a powerful continuous delivery tool for Kubernetes. ArgoCD will enable automated deployment and management of our applications.

Step 1: Create a Namespace for ArgoCD

ArgoCD runs in its own namespace. Let’s create it:

kubectl create namespace argocd

This command sets up a dedicated namespace named argocd in the cluster.

Step 2: Install ArgoCD

To install ArgoCD, apply its manifests directly from the official repository:

kubectl apply -n argocd -f https://raw.githubusercontent.com/argoproj/argo-cd/stable/manifests/install.yaml

This will install all the necessary components, including the ArgoCD server, controller, and related services.

Step 3: Check the ArgoCD Services

Once all argocd pods are running, verify that the ArgoCD services have been deployed successfully:k

kubectl get svc -n argocd

You should see a list of services, including the argocd-server, which will act as the entry point to the ArgoCD dashboard.

Step 4: Expose the ArgoCD Server

By default, the ArgoCD server runs as a ClusterIP service, meaning it’s only accessible from within the cluster. To make it accessible externally, we’ll change it to a NodePort service:

kubectl patch svc argocd-server -n argocd -p '{"spec": {"type": "NodePort"}}'

This exposes the ArgoCD server on a port that can be accessed from outside the cluster.

Step 5: Port Forward the ArgoCD Server

To access the ArgoCD dashboard locally, use port forwarding:

kubectl port-forward -n argocd service/argocd-server 8443:443 &

Make sure to open port 8443 in your security group.

This maps the cluster’s ArgoCD server to port 8443 on your EC2 instance, allowing you to access the dashboard using the instance's public IP.

Accessing the ArgoCD Dashboard

Open your web browser and navigate to:

https://<your_instance_public_ip>:8443

You’ll need login credentials for the dashboard. By default:

• Username: admin

• Password: The name of the ArgoCD server pod (you can retrieve it using kubectl get secret -n argocd argocd-initial-admin-secret -o jsonpath="{.data.password}" | base64 -d && echo).

  

Once logged in, ArgoCD is ready to manage your applications! Next, we’ll configure it to deploy our Voting App.

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💡 Deploying the Voting App with ArgoCD

With ArgoCD installed and accessible via the dashboard, we are ready to deploy our Voting App. Let’s configure and deploy the app step by step.

Step 1: Create a New Application in ArgoCD

1. Log in to the ArgoCD dashboard using your credentials.

2. Click on New App to create a new application.

3. Fill out the application details as follows:

   • Application Name: voting-app

   • Project Name: default

   • Sync Policy: Set to Automatic and enable both Prune Resources and Self Heal options to ensure ArgoCD keeps your application’s state consistent with the repository.

   • Repository URL: https://github.com/Pravesh-Sudha/k8s-kind-voting-app.git (You can fork the repository and use that)

   • Revision: main (specifying the branch).

   • Path: k8s-specifications (path to the Kubernetes manifests in the repository).

   • Cluster URL: Use the default cluster URL.

   • Namespace: Use the default namespace.

4. Click Create App.

ArgoCD will begin deploying the application into the cluster based on the Kubernetes manifests in the specified repository path.

Step 2: Verify Application Deployment

Wait for the application to synchronize. Once all the pods are deployed and show a Healthy status in the ArgoCD dashboard, the application is live in your Kind cluster. You can fork the repo and make changes to the deployment file (like changing the replica count) and it will be reflected in the argocd dashboard.

Step 3: Expose the Application Services

To make the Voting App accessible externally, expose the vote and result services using the following commands:

kubectl port-forward service/vote 5000:5000 --address=0.0.0.0 &  
kubectl port-forward service/result 5001:5001 --address=0.0.0.0 &

These commands forward traffic from your EC2 instance’s public IP to the services running in the Kind cluster.

Step 4: Update Security Groups

Ensure that ports 5000 and 5001 are open in your EC2 instance’s security group to allow external access.

Step 5: Access the Application

• Open your browser and go to:

  • Voting App: http://<your-public-ip>:5000

    

  • Results App: http://<your-public-ip>:5001

    

You’ll now see the Voting App up and running! Users can vote via the app, and you can monitor the results on the Results page.

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💡 Visualizing the Cluster with Kubernetes Dashboard

To gain a graphical view of your Kind cluster and manage it efficiently, we’ll deploy the Kubernetes Dashboard. Follow these steps to set it up and access it securely.

Step 1: Deploy Kubernetes Dashboard

Apply the official Kubernetes Dashboard manifests to your cluster:

kubectl apply -f https://raw.githubusercontent.com/kubernetes/dashboard/v2.7.0/aio/deploy/recommended.yaml

This deploys the Dashboard components, including the service and pod necessary for the UI.

Step 2: Create a Service Account

To access the Dashboard with administrative privileges, we’ll create a service account. Create a manifest file named admin-user.yaml:

nano admin-user.yaml

Add the following content:

apiVersion: v1  
kind: ServiceAccount  
metadata:  
  name: admin-user  
  namespace: kubernetes-dashboard  
---  
apiVersion: rbac.authorization.k8s.io/v1  
kind: ClusterRoleBinding  
metadata:  
  name: admin-user  
roleRef:  
  apiGroup: rbac.authorization.k8s.io  
  kind: ClusterRole  
  name: cluster-admin  
subjects:  
- kind: ServiceAccount  
  name: admin-user  
  namespace: kubernetes-dashboard

Apply the manifest to create the service account and bind it to the cluster-admin role:

kubectl apply -f admin-user.yaml

Step 3: Generate Access Token

Generate a token to authenticate the admin-user:

kubectl -n kubernetes-dashboard create token admin-user

Copy the generated token and save it securely—you’ll need it to log in to the Dashboard.

Step 4: Expose the Kubernetes Dashboard

Expose the Dashboard service using port-forwarding:

kubectl port-forward svc/kubernetes-dashboard -n kubernetes-dashboard 8080:443 --address=0.0.0.0

Ensure that port 8080 is open in the EC2 security group to allow external access.

Step 5: Access the Dashboard

1. Open your browser and navigate to:

    https://<your-ec2-public-ip>:8080
   

2. Enter the token generated in Step 3 when prompted.

   

Step 6: Explore the Dashboard

Once logged in, you’ll have a graphical interface to:

• View cluster resources like nodes, pods, and services.

• Monitor workloads and deployments.

• Manage namespaces, roles, and service accounts.

  

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💡 Conclusion

In this blog, we embarked on an exciting journey to build a fully functional DevOps pipeline from scratch using AWS EC2, Kind, and ArgoCD. Starting with provisioning an EC2 instance, we set up essential tools like Docker, Kind, and kubectl to create a Kubernetes cluster. We then deployed a Voting App, automated its continuous delivery using ArgoCD, and enhanced cluster management with the Kubernetes Dashboard.

This project demonstrates how seamlessly DevOps tools can integrate to simplify deployment workflows and provide real-time monitoring. By leveraging GitOps principles with ArgoCD, we ensured that our application stays synchronized with its source code repository, offering reliability and efficiency in managing deployments.

Whether you are a student, an aspiring DevOps engineer, or a seasoned professional, this hands-on approach to deploying and managing Kubernetes applications equips you with valuable insights into the world of CI/CD pipelines and container orchestration.

Now it’s your turn to try this project and explore further possibilities with Kubernetes and DevOps tools. Remember, the only limit is your curiosity and willingness to learn!

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Till then, Happy Coding!!

Happy Learning! 🎉