Devops

A containerized Spring Boot application with Kafka messaging and PostgreSQL database, demonstrating modern DevOps practices.

🚀 Quick Start

Services :

• Application: http://localhost:8080
• PostgreSQL: localhost:5336
• Kafka: localhost:9092

🏗️ Architecture

Stack: Spring Boot (Java 21) + PostgreSQL 15 + Kafka 3.4 + Zookeeper

Services:

• Spring Boot application for business logic
• PostgreSQL for data persistence
• Kafka for event streaming
• Zookeeper for Kafka coordination

🎯 Key Design Decisions

1. Multi-Stage Dockerfile

Why: Reduce image size by ~70% and improve security.

• Stage 1 (Build): Maven build with dependency caching
• Stage 2 (Runtime): Alpine Linux + OpenJDK 21 only

Benefits: Smaller images, faster deployments, no build tools in production.

2. Docker Compose Setup

Why: Simple local development with service orchestration.

• Health checks prevent startup race conditions
• Custom ports avoid conflicts (PostgreSQL: 5336)
• Named volumes for data persistence
• Dependency management (Kafka waits for Zookeeper)

3. CI/CD Pipeline (GitHub Actions)

Why: Automated testing and deployment on every commit.

Flow:

Push/PR → Build Image → Push to ECR → Pull & Test → Cleanup

Features:

• Git SHA tagging for immutable artifacts
• AWS ECR for private registry
• BuildKit cache for faster builds
• Automatic testing with full stack

4. Image Tagging Strategy

Format: {ECR_DOMAIN}/spring-kafka-service:{GIT_SHA}

Why: Enables precise rollbacks, audit trails, and avoids "latest" ambiguity.

5. Makefile Automation

Why: Simplify complex Docker/AWS commands and ensure consistency.

Key Commands:

make build-image      # Build Docker images
make build-image-push # Push to ECR
make up               # Start services
make down             # Stop and cleanup

🔄 CI/CD Pipeline

Triggers: Push to main or any Pull Request

Stages:

1. Build: Multi-stage Docker build → Push to ECR with Git SHA
2. Test: Pull image → Spin up stack → Run tests → Cleanup

Required Secrets:

• AWS_ACCESS_KEY_ID
• AWS_SECRET_ACCESS_KEY
• AWS_DEFAULT_REGION

☁️ Infrastructure as Code (Terraform)

Provisions:

• ECR repository for images
• EKS for Deployment
• VPC for security
• IAM roles

Usage:

cd terraform/
terraform init
terraform apply

📁 Project Structure

├── .github/workflows/     # CI/CD pipelines
├── src/                   # Spring Boot source
├── terraform/             # IaC configurations
├── k8s/                   # Kubernetes manifests
├── Dockerfile             # Multi-stage build
├── docker-compose.yml     # Local orchestration
├── Makefile              # Build automation
└── pom.xml               # Maven dependencies

📝 Summary

This project demonstrates:

• ✅ Multi-stage Dockerfile (optimized builds)
• ✅ Docker Compose (local development)
• ✅ Kubernetes manifests (production deployment)
• ✅ GitHub Actions CI/CD (automated pipeline)
• ✅ Terraform IaC (AWS infrastructure)