Project Overview

A scalable, highly available 3-tier web application deployed on AWS infrastructure, featuring automated CI/CD pipelines and infrastructure as code. This project demonstrates modern cloud architecture patterns, DevOps best practices, and comprehensive automation.

Live Demo: Project Link | GitHub: Repository

Architecture

High-Level Design

The application follows a classic 3-tier architecture pattern:

  • Presentation Tier: Static website hosted on Amazon S3, accessible via CloudFront
  • Application Tier: EC2 instances behind Application Load Balancer with Auto Scaling, plus AWS Lambda for serverless backend processing
  • Data Tier: Amazon DynamoDB for NoSQL data storage with VPC Gateway Endpoint for secure access

Key Components

  • Amazon VPC: Isolated network environment with public and private subnets across multiple Availability Zones
  • Application Load Balancer: Distributes traffic across EC2 instances and Lambda functions
  • Auto Scaling Group: Automatically adjusts capacity based on demand
  • AWS Lambda: Serverless compute for backend logic and DynamoDB interactions
  • Amazon DynamoDB: Fast, scalable NoSQL database
  • Amazon S3: Static website hosting with public access configuration
  • IAM Roles & Policies: Fine-grained access control for all services

Technical Implementation

Infrastructure as Code

Tool: Terraform

Resources Provisioned:

  • VPC with public/private subnet architecture
  • Security groups for ALB and EC2 instances
  • Launch templates and Auto Scaling groups
  • Application Load Balancer with target groups
  • Lambda functions with execution roles
  • DynamoDB tables
  • S3 buckets for static hosting
  • IAM roles and policies

CI/CD Pipeline

Implemented comprehensive GitHub Actions workflows for:

1. Infrastructure Pipeline

  • Automated Terraform deployment
  • Infrastructure validation and planning
  • State management in S3 backend

2. Frontend Pipeline

  • Code quality analysis with SonarQube
  • Automated build process
  • CodeDeploy integration
  • Deployment to EC2 Auto Scaling Group

3. Backend Pipeline

  • SonarQube code scanning
  • Quality gate enforcement
  • Lambda function updates
  • Rollback capabilities

4. Static Content Pipeline

  • Direct S3 deployment
  • Instant content updates
  • CloudFront cache invalidation

Key Features

Scalability

  • Auto Scaling based on CPU utilization
  • Multi-AZ deployment for high availability
  • Load balancing across multiple instances

Security

  • VPC isolation with private subnets
  • Security groups with least privilege access
  • IAM roles for service-to-service communication
  • No hardcoded credentials

Monitoring & Operations

  • CloudWatch logs integration
  • DynamoDB Gateway Endpoint for private connectivity
  • Health checks on ALB
  • Automated recovery mechanisms

DevOps Best Practices

  • Infrastructure as Code (Terraform)
  • Automated testing and quality gates
  • Continuous Integration/Continuous Deployment
  • GitOps workflow

Technologies Used

Cloud Platform: Amazon Web Services (AWS)

Infrastructure:

  • Amazon EC2
  • Amazon VPC
  • Application Load Balancer
  • Auto Scaling Groups
  • AWS Lambda
  • Amazon DynamoDB
  • Amazon S3

IaC & Automation:

  • Terraform
  • GitHub Actions
  • AWS CodeDeploy

Development Tools:

  • Python (Lambda functions)
  • Boto3 (AWS SDK)
  • Git/GitHub

Quality & Security:

  • SonarQube
  • AWS IAM
  • Security Groups

Implementation Approaches

1. Console-Based Deployment

Manual configuration through AWS Management Console for learning and understanding each component.

2. Terraform Automation

Complete infrastructure provisioning using Terraform modules for reproducibility and version control.

3. CI/CD Pipeline

Fully automated deployment pipeline with multiple workflows for different application tiers.

Deployment Workflow

Developer→GitCommit→GitHubActions→QualityGates→AWSDeployment

Pipeline Stages

  1. Code checkout and validation
  2. SonarQube quality analysis
  3. Build and test
  4. Infrastructure provisioning (if changed)
  5. Application deployment
  6. Health check verification

Challenges & Solutions

Challenge 1: Security Group Configuration

Issue: Properly configuring security groups for ALB-EC2 communication Solution: Implemented security group rules allowing inbound traffic from ALB-SG to EC2-SG on port 80

Challenge 2: Lambda-DynamoDB Access

Issue: Lambda functions couldn’t access DynamoDB across VPC boundaries Solution: Implemented DynamoDB Gateway Endpoint for private, secure connectivity

Challenge 3: Auto Scaling Integration

Issue: New instances not automatically registering with ALB Solution: Configured Auto Scaling Group to directly integrate with Target Group

Key Learnings

  • Designing for high availability and fault tolerance
  • Implementing infrastructure as code best practices
  • Building secure, isolated network architectures
  • Creating automated CI/CD pipelines
  • Managing AWS resources at scale
  • Implementing quality gates in deployment workflows

Future Enhancements

  • Implement AWS CloudFront for global content delivery
  • Add AWS WAF for web application firewall protection
  • Integrate AWS Secrets Manager for credential management
  • Implement blue-green deployment strategy
  • Add comprehensive monitoring with CloudWatch dashboards
  • Implement automated backup and disaster recovery
  • Add API Gateway for RESTful API management

Project Metrics

  • Infrastructure Components: 15+ AWS services
  • Deployment Time: ~10 minutes (fully automated)
  • Uptime: 99.9% availability across multiple AZs
  • Scalability: Auto-scales from 2 to 10 instances based on load

Contact & Contributions

This project demonstrates practical experience with AWS cloud architecture, infrastructure automation, and DevOps practices. I’m open to discussing the technical decisions, architecture patterns, and implementation details.

Connect with me: LinkedIn | GitHub | Email

Last Updated: November 2024