E-Commerce Web Application

Overview

This project serves as a practical exercise to test your DevOps skills. It involves working with a sample e-commerce web application that allows users to browse and purchase kids' beds. Your task is to apply DevOps practices to containerize the application, set up CI/CD pipelines, and ensure proper validation and testing.

Project Tasks

1. Fork the Repository

   • Begin by forking this repository to your own GitHub account.

2. Ansible Automation (Same Local Machine)

   • Use Ansible to automate app deployment and updates:
     • Create ansible/ folder with host file: [local] 127.0.0.1 ansible_connection=local
     • install and verify basics tools for this repo e.g. git and docker

3. Clone and create a Separate Branch

   • Clone and create a new branch named devops-branch in your forked repository. This branch will be used for all your DevOps-related tasks.

4. Containerize the Application

   • Write a Dockerfile to containerize the e-commerce web application. Ensure that the Dockerfile is properly configured to build an image for the application. Apply best practices in Dockerfile creation, such as:
     • Minimizing the number of layers
     • Using a small base image
     • Caching dependencies effectively
     • Cleaning up unnecessary files to reduce the image size

5. Set Up Docker Compose

   • Create a docker-compose.yml file to deploy the application using Docker Compose. Although PostgreSQL is not used in this application, ensure that the Docker Compose setup is properly configured for the application container.

6. Kubernetes (Local with Minikube or Kind)

   • Deploy your app in a local Kubernetes cluster:
   • Create:
     • k8s/deployment.yaml
     • k8s/service.yaml
   • Start Minikube or Kind and apply:
     • kubectl apply -f k8s/
     • kubectl port-forward svc/ecommerce-service 8080:80

7. Deploy Using CI/CD Pipeline

   • Use the Dockerfile to deploy the application by setting up a CI/CD pipeline. This pipeline should be configured to run only for the devops-branch, not for the master branch.
   • Optionally
     • Create new branches named compose-branch and k8s-branch in your forked repository. These branch will be used for all your docker compose and Kubernetes related tasks.
     • Use the docker-compose.yml to deploy the application by setting up a CI/CD pipeline. This pipeline should be configured to run only for the compose-branch, not for the master branch.
     • Use the deployment.yaml and service.yaml to deploy the application by setting up a CI/CD pipeline. This pipeline should be configured to run only for the k8s-branch, not for the master branch.

8. Validation and Testing

   • Add necessary validation and testing in your CI/CD to confirm that the application runs correctly on a specific port. Ensure that all functionalities are working as expected and the deployment is stable.

9. Prometheus & Grafana Monitoring

   • Monitor Docker containers and host system locally:
   • Create monitoring/docker-compose.yml with:
     • prometheus
     • node_exporter
     • grafana

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What I Did

1. Ansible - Installing Git and Docker

Created an Ansible setup to automate the installation of Git and Docker on the local machine.

Files Created:

• ansible/hosts - Inventory file for local connection
• ansible/setup.yml - Playbook to install and verify tools

Hosts file content:

[local]
127.0.0.1 ansible_connection=local

Commands to run:

# Install Ansible (if not installed)
sudo apt install ansible

# Run the playbook
ansible-playbook -i ansible/hosts ansible/setup.yml

# Or run with verbose output
ansible-playbook -i ansible/hosts ansible/setup.yml -v

The playbook performs:

• Updates apt package cache
• Installs Git and verifies installation
• Installs Docker and verifies installation

---

2. Dockerfile

Created a Dockerfile to containerize the e-commerce web application using Nginx Alpine (minimal image).

Dockerfile content:

FROM nginx:alpine

COPY . /usr/share/nginx/html/

EXPOSE 80

CMD ["nginx", "-g", "daemon off;"]

Commands:

# Build the Docker image
docker build -t my-ecommerce-app .

# Run the container
docker run -d -p 8080:80 my-ecommerce-app

# Access the application at http://localhost:8080

---

3. Docker Compose

Created a docker-compose.yml file for easy deployment of the application.

docker-compose.yml content:

version: '3.8'

services:
  app:
    container_name: loving_wing
    build: .
    ports:
      - "8080:80"
    restart: always

Commands:

# Start the application
docker compose up -d --build

# View running containers
docker compose ps

# Stop the application
docker compose down

# View logs
docker compose logs -f

---

4. Kubernetes

Created Kubernetes manifests for deploying the application in a local cluster (Minikube or Kind).

Files Created:

• kubernetes/deployment.yml - Deployment with 2 replicas
• kubernetes/service.yml - Service to expose the application

Commands:

# Start Minikube (if using Minikube)
minikube start

# Build and load image (for Kind)
docker build -t my-ecommerce-app:latest .
kind load docker-image my-ecommerce-app:latest

# Apply Kubernetes manifests
kubectl apply -f kubernetes/

# Check pod status
kubectl get pods

# Check service status
kubectl get svc

# Port forward to access the application
kubectl port-forward svc/ecommerce-service 8080:80

# Access the application at http://localhost:8080

---

5. CI/CD Workflows (GitHub Actions)

Created three separate CI/CD pipelines for different deployment methods.

Files Created:

• .github/workflows/docker-pipeline.yml - Runs on devops branch
• .github/workflows/compose-pipeline.yml - Runs on compose-branch
• .github/workflows/k8s-pipeline.yml - Runs on kubernetes-branch

Docker Pipeline (devops branch):

• Builds Docker image
• Runs container on port 8080
• Validates application is responding

Docker Compose Pipeline (compose-branch):

• Runs docker compose up
• Verifies containers are running
• Validates application on port 8080

Kubernetes Pipeline (kubernetes-branch):

• Creates Kind cluster
• Builds and loads image into cluster
• Deploys to Kubernetes
• Port forwards and validates on port 8081

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6. Monitoring (Prometheus & Grafana)

Created monitoring setup using Prometheus for metrics collection and Grafana for visualization.

Files Created:

• monitoring/monitoring-compose.yml - Docker Compose for monitoring stack
• monitoring/prometheus.yml - Prometheus configuration

Services:

• Prometheus - Metrics collection (Port 9090)
• Node Exporter - Host metrics (Port 9100)
• Grafana - Visualization dashboard (Port 3001)

Commands:

# Navigate to monitoring directory
cd monitoring

# Start monitoring stack
docker compose -f monitoring-compose.yml up -d

# Access services:
# Prometheus: http://localhost:9090
# Grafana: http://localhost:3001 (admin/admin)

# Stop monitoring stack
docker compose -f monitoring-compose.yml down

Grafana Setup:

1. Login with admin/admin
2. Add Prometheus data source: http://prometheus:9090
3. Import Node Exporter dashboard (ID: 1860)