This FitnessApp architecture uses Java Full Stack and React. User authentication is managed by Keycloak. The system is built with microservices handling user and activity data, stored in MySQL and MongoDB. RabbitMQ manages messaging, while AI services integrate with Google’s Gemini. Config and Eureka servers support service discovery.

A fitness app which is based on microservices architecture in spring boot using a gemini ai api

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learning microservices with this project

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Fitness AI Platform built using microservices architecture with Spring Boot, Kafka, Keycloak, and AI integration (Google Gemini). The system handles secure authentication, user activity tracking, real-time event processing, and AI-powered fitness insights through a scalable and cloud-ready design.

Building a fitnessApp backend using microservices architecture in Spring Boot

FitnessApp Microservice Project is a scalable backend system built with Spring Boot and microservices architecture. It manages users, workouts, nutrition, progress tracking, and service communication efficiently. Designed with modular services, API gateway, service discovery, and database integration for modern fitness applications.