A complete serverless image processing pipeline built with AWS services, orchestrated by Terraform and deployed on Amazon EKS. This project automatically processes images uploaded to S3, creates thumbnails, and provides monitoring and alerting capabilities.

This project implements a modern, scalable image processing pipeline using the following AWS services:

• Amazon S3: Storage for original images and generated thumbnails
• AWS Lambda: Triggered by S3 events to publish notifications
• Amazon SNS: Message publishing and error alerting
• Amazon SQS: Message queuing for reliable processing
• Amazon EKS: Kubernetes cluster running the image processing application
• Amazon ECR: Container registry for Docker images
• Amazon CloudWatch: Monitoring, logging, and alerting
• AWS IAM: Security and access management

Before deploying this infrastructure, ensure you have:

• AWS CLI configured with appropriate credentials
• Terraform (v1.0+) installed
• Docker installed and running
• kubectl installed for Kubernetes management
• Node.js (v18+) for local development
• Git for version control

Your AWS user/role needs permissions for:

• EKS cluster management
• ECR repository operations
• S3 bucket operations
• Lambda function deployment
• SNS/SQS operations
• CloudWatch monitoring
• IAM role/policy management
• VPC and networking operations

# Deploy the complete infrastructure
./1.deploy-infra.sh

This script will:

• Initialize Terraform
• Create all AWS resources
• Configure kubectl for the EKS cluster
• Display deployment outputs

# Build and push Docker image to ECR
./2.deploy-to-ecr.sh

# Deploy application to EKS cluster
./3.deploy.sh

# Test the complete pipeline with a sample image
./4.test-pipeline.sh

# Remove all AWS resources to avoid charges
./5.cleanup.sh