About This App

This application showcases my ability to design, build, and deploy an end-to-end, AI-powered, cloud-native full-stack application on AWS.

It features a responsive frontend built with Next.js and a serverless backend on AWS using Lambda and API Gateway.

Data is managed with DynamoDB and S3, while CloudFront helps optimize global content delivery through caching and low-latency distribution.

The application integrates AI via AWS Comprehend to analyze user input and dynamically generate personalized music and visual experiences, including mood-driven playback and adaptive UI behavior.

A CI/CD pipeline powered by GitHub Actions and AWS CodePipeline enables automated building and deployment, reflecting real-world DevOps practices.

The system also incorporates production-ready practices such as input validation, rate limiting, and edge-level protection via AWS WAF.

Key Features

  • • Mood-driven playback with dynamic play/pause based on user sentiment
  • • Real-time mood analysis from free-text input using NLP
  • • Adaptive UI with background visuals that respond to detected mood
  • • AI-powered emotion detection to match music and visuals
  • • Serverless architecture on AWS (Lambda, API Gateway, DynamoDB, S3)
  • • Auto-scaling serverless infrastructure
  • • CI/CD pipeline using GitHub Actions and AWS CodePipeline
  • • Containerized deployment with Docker and AWS ECR
  • • Optimized global content delivery via AWS CloudFront (low latency & caching)
  • • Secure input handling with validation and sanitization
  • • Multi-layer rate limiting for system protection:
    • - Edge-level protection via AWS WAF (CloudFront)
    • - Backend rate limiting on API endpoints
  • • Automated deployment pipeline with real-time status tracking

For detailed technical information, check: