Fitness Application Microservices + MicroFrontends Architecture

Overview

This project implements a microservices-based fitness application with an API Gateway pattern. The system consists of three main services and a Nginx-based API Gateway for routing and load balancing.

Architecture

Services

1. User Management Service

   • Port: 3000
   • Endpoint: /api/users/
   • Handles user authentication, registration, and profile management
   • Rate limit: 10 requests/second with burst of 20

2. Training Session Management Service

   • Port: 3001
   • Endpoint: /api/sessions/
   • Manages training sessions and schedules
   • Rate limit: 10 requests/second with burst of 20

3. Workout Recommendation Service

   • Port: 8000
   • Endpoint: /api/recommendations/
   • Provides workout recommendations and calorie calculations
   • Rate limit: 10 requests/second with burst of 20

API Gateway (Nginx)

• Handles routing to microservices
• Implements rate limiting
• Provides error handling
• Enables GZIP compression
• Manages request body size limits (100MB max)
• Health check endpoint available

API Endpoints

User Management

• GET/POST /api/users/ - User operations
• Common endpoints include login, register, profile management

Training Sessions

• GET/POST /api/sessions/ - Session operations
• Manages training schedules and session data

Workout Recommendations

• GET/POST /api/recommendations/ - Recommendation operations
• POST /api/recommendations/get-calories - Calorie calculation endpoint

System

• GET /health - Health check endpoint
• Returns {"status":"UP"} when system is operational

Technical Features

Security & Performance

• Rate limiting implemented for all services
• GZIP compression for text and JSON responses
• Request size limits configured
• Proxy headers for proper client IP forwarding
• Upgrade-capable WebSocket connections supported

Error Handling

• Custom JSON responses for common HTTP errors
• 404 Not Found - Returns JSON error message
• 500 Server Error - Returns JSON error message

Getting Started

Prerequisites

• Docker and Docker Compose
• Nginx
• Node.js (for user and training services)
• Python (for workout recommendation service)

Running the Application

1. Clone the repository
2. Navigate to the project directory
3. Start the services:

   docker-compose up

4. Access the services through:

   http://localhost/api/{service-endpoint}
   

Health Check

Verify the system is running by accessing:

This project implements a microservices-based fitness application with an API Gateway pattern. The system consists of three main services and a Nginx-based API Gateway for routing and load balancing.

Architecture

Services

1. User Management Service

   • Port: 3000
   • Endpoint: /api/users/
   • Handles user authentication, registration, and profile management
   • Rate limit: 10 requests/second with burst of 20

2. Training Session Management Service

   • Port: 3001
   • Endpoint: /api/sessions/
   • Manages training sessions and schedules
   • Rate limit: 10 requests/second with burst of 20

3. Workout Recommendation Service

   • Port: 8000
   • Endpoint: /api/recommendations/
   • Provides workout recommendations and calorie calculations
   • Rate limit: 10 requests/second with burst of 20

API Gateway (Nginx)

• Handles routing to microservices
• Implements rate limiting
• Provides error handling
• Enables GZIP compression
• Manages request body size limits (100MB max)
• Health check endpoint available

API Endpoints

User Management

• GET/POST /api/users/ - User operations
• Common endpoints include login, register, profile management

Training Sessions

• GET/POST /api/sessions/ - Session operations
• Manages training schedules and session data

Workout Recommendations

• GET/POST /api/recommendations/ - Recommendation operations
• POST /api/recommendations/get-calories - Calorie calculation endpoint

System

• GET /health - Health check endpoint
• Returns {"status":"UP"} when system is operational

Technical Features

Security & Performance

• Rate limiting implemented for all services
• GZIP compression for text and JSON responses
• Request size limits configured
• Proxy headers for proper client IP forwarding
• Upgrade-capable WebSocket connections supported

Error Handling

• Custom JSON responses for common HTTP errors
• 404 Not Found - Returns JSON error message
• 500 Server Error - Returns JSON error message

Getting Started

Prerequisites

• Docker and Docker Compose
• Nginx
• Node.js (for user and training services)
• Python (for workout recommendation service)

Running the Application

1. Clone the repository
2. Navigate to the project directory
3. Start the services:

   docker-compose up

4. Access the services through:

   http://localhost/api/{service-endpoint}
   

Health Check

Verify the system is running by accessing: