Fitness Tracker Microservices Platform Built a production-ready, secure fitness tracking ecosystem from the ground up using modern microservice architecture. Designed and implemented user registration, activity logging, and real-time AI workout recommendations, integrating the Gemini API for intelligent, personalized guidance. Authentication & Security: Implemented robust OAuth2 authentication flow with Keycloak + PKCE, ensuring secure, scalable user access. End-to-End Data Flow: Connected PostgreSQL (user data) and MongoDB (activity logs) across Spring Boot microservices, with real-time inter-service communication via RabbitMQ. AI-Driven Recommendations: Developed an AI-service leveraging Google Gemini API, enabling instant, user-specific fitness advice based on activity patterns. Distributed Queuing & Service Discovery: Integrated RabbitMQ for asynchronous, resilient activity queuing, and Eureka for dynamic registration and discovery of all microservices, boosting scalability and fault tolerance. Modern Frontend: Crafted a fast, responsive frontend in React + Vite with PKCE-based login and intuitive activity dashboards. API Gateway: Centralized security, token propagation, and smart routing across all APIs for a unified developer and user experience. Built to demonstrate expertise in scalable backend systems, secure authentication, real-time AI integration, robust inter-service communication, and full DevOps pipelines. Easily extensible for monitoring (Prometheus) and future cloud deployments. Core Tech: Spring Boot (Java), React, RabbitMQ, Keycloak, PostgreSQL, MongoDB, Google Gemini API, Docker, Eureka