Building an End-to-End DevOps Pipeline on AWS with Jenkins, Docker, Kubernetes, Terraform & Ansible

In this blog post, I’ll walk you through how I built a complete, production-grade DevOps automation setup from scratch—featuring Terraform, Ansible, Docker, Jenkins, Kubernetes (EKS), and AWS. This is more than just a project—it's a blueprint for real-world CI/CD automation, using best practices and cost-effective resources.

🧭 Project Overview

• Project Name: Scalable AI Chatbot Deployment Pipeline

• Tech Stack: AWS, Terraform, Ansible, Jenkins, Docker, Kubernetes (EKS), GitHub, Nginx Ingress

• Objective: Automate infrastructure provisioning, application configuration, containerization, and continuous deployment on Kubernetes.

📌 Architecture Diagram

🔧 Tools and Services Used

🏗️ Step-by-Step Implementation

1. Terraform: Infrastructure as Code

I created the following using Terraform:

• Custom VPC with public subnets

• EC2 instance for Jenkins (t3.medium)

• IAM roles and policies

• EKS cluster & node group

2. Ansible: EC2 Configuration

I automated software installation on the EC2 (Jenkins host) using Ansible:

• Docker

• Jenkins

• kubectl

• AWS CLI

3. Docker & Django App

• Containerized a Django-based chatbot using a multi-stage Dockerfile

• Reduced image size to ~400MB

• Docker image pushed to Docker Hub

4. Jenkins: CI/CD Pipeline

• Jenkinsfile automates the pipeline:

  • Checks out code from GitHub

  • Builds & pushes Docker image

  • Deploys the app to EKS

  • Triggers via GitHub Webhooks

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5. Kubernetes (EKS) Deployment

• Used deployment.yml, service.yml, and ingress.yml

• Secrets (.env) injected via Kubernetes Secrets

• Exposed app using Nginx Ingress

6. GitHub Webhooks for Automated Deployments

• Any commit to main triggers a Jenkins pipeline

• Jenkins builds, tests, pushes image & deploys it to EKS seamlessly

✅ Final Output

• A scalable, secure, and automated CI/CD pipeline

• A chatbot running on Kubernetes backed by Docker, Terraform & Jenkins

• No manual steps in deployment after commit!

💡 Key Learnings

• Real-world integration of all major DevOps tools

• Importance of cost-optimization (e.g., t2.micro for test, t3.medium for Jenkins)

• Building lightweight Docker images using multi-stage builds

• Using GitHub webhooks to trigger Jenkins jobs for CI/CD

Contact Me:

🔗 GitHub

🔗 LinkedIn

🔗 Portfolio

🔚 Conclusion

This project was a complete hands-on experience in designing and implementing a DevOps pipeline like those used in production. From provisioning infrastructure with Terraform, to configuring servers with Ansible, to automating deployments with Jenkins and Docker—this pipeline reflects a real-world DevOps lifecycle.