Design 1: Designing a Chat System like WhatsApp

Let’s walk through the step-by-step system design of a messaging platform similar to WhatsApp.

Step 1: Define Functional Requirements

  • Real-time messaging (text, voice, and video)
  • Group chat support
  • Status sharing (text, photo, video)
  • End-to-end encryption
  • Voice and video calls
  • File/media/document sharing

Step 2: Define Non-Functional Requirements

  • Scalability: System must handle billions of users
  • Reliability: High uptime and minimal failure
  • Security: Data encryption and secure communication
  • Low Latency: Near-instant message delivery
  • Cross-Platform Support: Web, Android, iOS, etc.
  • Massive data storage and retrieval

Step 3: Estimate Traffic

  • User base: 2 billion
  • Active users: ~500 million (25%)
  • Average messages/user/day: 30
  • Total messages/day: 500M × 30 = 1.5 billion

Step 4: Estimate Storage

  • Average message size: 50 KB
  • Total storage/day: 1.5B × 50 KB = 75 PB
  • Undelivered message storage (10%): 7.5 PB/day
  • Retention (30 days): 7.5 PB × 30 = 225 PB

Step 5: Define API Services

  • User Authentication (login, registration, OTP, profile)
  • Message CRUD operations
  • Media upload/download APIs
  • Search and filtering APIs
  • Push notification APIs

Step 6: High-Level Architecture

  • Client App: Sends and receives messages using persistent WebSocket connections
  • API Gateway: Manages requests for user authentication, message history, and media operations
  • Auth Service: Handles registration, login, and token validation
  • Messaging Service: Orchestrates chat flow and forwards real-time messages via WebSocket
  • Presence Service: Tracks online/offline status and last seen
  • Media Service: Uploads, stores, and serves media using object storage (e.g., AWS S3)
  • Message Queue: (Kafka/RabbitMQ) Enables async delivery and retry handling
  • NoSQL Database: Stores chat messages and metadata (e.g., DynamoDB or Cassandra)
  • Search Index: Enables message and user search (e.g., Elasticsearch)

Step 7: Key Architectural Decisions

  • Database: Use scalable NoSQL DB (e.g., Cassandra, DynamoDB) for messages
  • Media Storage: Use object storage like AWS S3 or GCP Cloud Storage
  • Real-Time: Use WebSockets or MQTT for real-time messaging
  • Encryption: End-to-end encryption using protocols like Signal
  • Scalability: Use load balancers, CDN, and horizontal scaling for services

Step 8: Additional Considerations

  • Message queues (e.g., Kafka, RabbitMQ) for asynchronous processing
  • Rate limiting and spam detection
  • Monitoring and logging with observability stack
  • Data retention and GDPR compliance

Conclusion

Designing a large-scale chat system requires careful planning of architecture, scalability, data management, and real-time performance. Every decision has trade-offs, and understanding the scale and use case is crucial.