🚀 End-to-End CI/CD Pipeline with Jenkins, Docker, Terraform & AWS

This project demonstrates a complete end-to-end CI/CD pipeline that automates the process from code commit to production deployment on AWS.
It reflects a real-world DevOps workflow used in production environments.

📌 Project Overview

When a developer pushes code to the repository, the pipeline automatically:

1. Triggers a Jenkins build
2. Builds a Docker image
3. Pushes the image to a private Docker registry
4. Provisions AWS infrastructure using Terraform
5. Pulls the Docker image on an AWS EC2 instance
6. Deploys the Docker container and makes the application live

🏗️ Architecture Flow Diagram

🛠️ Tech Stack

• GitHub – Source code management
• Jenkins – CI/CD automation (hosted on AWS EC2 instance)
• Docker – Containerization
• Private Docker Registry – Secure image storage
• Terraform – Infrastructure as Code (IaC)
• AWS – VPC & EC2

⚙️ CI/CD Pipeline Workflow

1️⃣ Code Push

• Developer pushes code to the GitHub repository.

2️⃣ Jenkins Trigger

• GitHub webhook triggers the Jenkins pipeline automatically.

3️⃣ Docker Image Build & Push

• Jenkins builds a Docker image from the application.
• Image is pushed to a private Docker registry.

4️⃣ Infrastructure Provisioning

• Terraform creates required AWS resources:
  • VPC
  • Subnets
  • Security Groups
  • EC2 Instance

5️⃣ Deployment

• EC2 instance pulls the Docker image from the private registry.
• Docker container is started and the application goes live.

📚 What I Learned

• Core concepts of Jenkins pipelines
• Writing and managing Terraform configurations
• Infrastructure provisioning using IaC
• Secure handling of Docker images
• How real-world production CI/CD pipelines work
• End-to-end automation from development to deployment

🎯 Key Takeaways

• CI/CD automation reduces manual effort and deployment risks
• Infrastructure as Code makes environments reproducible and scalable
• Jenkins, Docker, and Terraform together form a powerful DevOps toolchain
• Building projects end to end is the best way to understand production systems

🚧 Future Improvements

• Add Application Load Balancer
• Implement Auto Scaling
• Migrate deployment to Amazon EKS
• Add Monitoring & Logging (CloudWatch / Prometheus)
• Improve security with IAM best practices

🔚 Closing Remarks

This project gave me hands-on experience with a production-grade CI/CD pipeline and strengthened my understanding of modern DevOps practices.
I look forward to extending this setup with more advanced cloud-native features and continuing to build scalable, automated systems.

Happy Automating 🚀