Billion-User Chat Application

A scalable chat application designed to support a billion users, built with Java.

System Architecture

This application follows a microservices architecture to ensure scalability, reliability, and maintainability:

• API Gateway: Entry point for all client requests, handles authentication, rate limiting, and request routing
• User Service: Manages user accounts, profiles, and authentication
• Chat Service: Handles message processing and delivery
• Presence Service: Tracks online/offline status of users
• Notification Service: Manages push notifications
• Media Service: Handles file sharing and media processing

Technology Stack

• Backend: Java, Spring Boot, Spring Cloud
• Messaging: Apache Kafka, WebSockets
• Databases: PostgreSQL (user data), Cassandra (messages), Redis (caching)
• Deployment: Docker, Kubernetes
• Monitoring: Prometheus, Grafana

Scalability Strategies

• Horizontal scaling of stateless services
• Database sharding and partitioning
• Multi-level caching
• Asynchronous processing
• Load balancing

Getting Started

Prerequisites

• Java 17+
• Maven 3.8+
• Docker and Docker Compose

Setup and Installation

1. Clone the repository
2. Run mvn clean install to build all services
3. Use Docker Compose to start the development environment: docker-compose up

Project Structure

├── api-gateway/           # API Gateway service
├── user-service/          # User management service
├── chat-service/          # Message handling service
├── presence-service/      # Online status tracking service
├── notification-service/  # Push notification service
├── media-service/         # File and media handling service
├── common/                # Shared libraries and utilities
└── docker/                # Docker configuration files

Key Features

• Real-time messaging with WebSockets
• End-to-end encryption
• Group chats and channels
• Media sharing
• Message persistence
• Offline message delivery
• Read receipts
• Typing indicators

Performance Considerations

• Connection pooling
• Message batching
• Lazy loading of chat history
• Efficient data serialization
• Optimized database queries

Security Measures

• End-to-end encryption
• TLS for all communications
• Rate limiting to prevent abuse
• Input validation and sanitization
• Regular security audits

Author

Saurabh Kushwaha
🔗 Portfolio
📧 Saurabh@wearl.co.in
🔗 LinkedIn
🔗 Instagram Dev Page

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License

This project is licensed under the MIT License.

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