Design an Online Multiplayer Chess Game

Question

Design a real-time online chess platform. Cover game state management, matchmaking with ELO ratings, move validation, spectator mode, and handling network disconnections gracefully.

Codemia · Accepted Answer

### Functional Requirements
1. **Real-Time Game State Management**: The system must maintain the game state for each chess match, including player moves, timer, and game status (ongoing, check, checkmate, stalemate).
2. **Matchmaking**: Players should be matched based on their ELO ratings, ensuring balanced games.
3. **Move Validation**: The system should validate moves according to chess rules before applying them to the game state.
4. **Spectator Mode**: Allow users to spectate ongoing matches with real-time updates on the game state.
5. **Network Disconnection Handling**: Implement mechanisms to save game state and allow players to reconnect without losing progress.

### Non-Functional Requirements
1. **Scalability**: The system should support thousands of concurrent games and users.
2. **Latency**: Game state updates should be sent to players with minimal latency (under 100ms).
3. **Reliability**: The system should have high availability, ideally 99.99% uptime.
4. **Security**: Protect against cheating, such as move manipulation or unauthorized access.

Assuming each game lasts approximately 30 minutes and each game has 2 players:
- **Concurrent Games**: Targeting 10,000 concurrent games at peak times.
- **Total Users**: Assuming 60% of players are active at any given time, we estimate 12,000 concurrent users (10,000 players + 2,000 spectators).
- **Data Throughput**: Each game sends approximately 5 messages per minute (move updates, game state) leading to:
  - 10,000 games * 5 messages = 50,000 messages per minute.
- **Storage Requirements**: Assuming each game has a state size of 1KB, for 10,000 games:
  - 10,000 games * 1KB = 10MB for game states. 
  - If we store 7 days of game history, we need 10MB * 10,000 games * 7 days = ~700GB.

### Component Diagram
- **Client Applications**: Web and mobile clients for users to play and spectate.
- **WebSocket Server**: Handles real-time communication for game state updates, implemented using Node.js with Socket.IO for low-latency messaging.
- **Game Logic Service**: A dedicated microservice that manages game state, validation, and ELO calculation, built using Python (Flask).
- **Matchmaking Service**: Responsible for pairing players based on ELO ratings, implemented in Go for performance.
- **Database**: Firebase Firestore for real-time data storage, allowing quick access to game states and user profiles.
- **Caching Layer**: Redis for caching game states and ELO ratings to reduce database load and improve response times.

### Schema Design
- **User Table**:  
  - `user_id` (string, primary key)  
  - `username` (string, unique)  
  - `elo_rating` (integer)  
  - `games_played` (integer)

- **Game Table**:  
  - `game_id` (string, primary key)  
  - `white_player_id` (string, foreign key to User)  
  - `black_player_id` (string, foreign key to User)  
  - `board_state` (string, serialized chess board state)  
  - `status` (enum: ongoing, check, checkmate, stalemate)  
  - `timestamp` (datetime)

- **Move History Table**:  
  - `move_id` (string, primary key)  
  - `game_id` (string, foreign key to Game)  
  - `player_id` (string, foreign key to User)  
  - `move` (string, notation of the move)  
  - `move_number` (integer)  
  - `timestamp` (datetime)

1. **Real-Time vs. Consistency**: Using WebSockets for real-time updates may introduce challenges in ensuring consistency across distributed systems. We must balance the need for fast updates while ensuring the game state remains accurate.
2. **Microservices vs. Monolith**: Choosing microservices allows for individual scaling and deployment, but adds complexity in inter-service communication. A monolith could simplify deployment but would be harder to scale.
3. **Database Choice**: Using Firebase Firestore allows for real-time updates but may not scale in terms of complex queries. We could opt for a relational database (like PostgreSQL) for complex relationships but sacrifice real-time capabilities.
4. **Caching Strategy**: Caching game states and ELO ratings in Redis improves performance but requires careful management of cache invalidation to ensure players see the most accurate data.

Design an Online Multiplayer Chess Game

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