Requirements and game rules in LLD - Scalability & System Analysis

Scalability Analysis - Requirements and game rules

Growth Table: Users and System Changes

Scale	Users	Key Changes
Small	100 users	Basic game logic runs on a single server. Simple rules enforcement. Minimal latency. No complex scaling needed.
Medium	10,000 users	Multiple game sessions run concurrently. Need load balancing. Game state stored in memory or fast DB. Basic matchmaking introduced.
Large	1,000,000 users	Distributed game servers. Sharded game state storage. Advanced matchmaking and player ranking. Real-time synchronization challenges.
Very Large	100,000,000 users	Global data centers. CDN for static assets. Complex sharding and caching. Eventual consistency for some game states. High availability and fault tolerance.

First Bottleneck

At around 10,000 users, the first bottleneck is the game state management. The server's memory and CPU struggle to keep all active game sessions updated and consistent in real-time. This happens because game rules require frequent state changes and validations, which are CPU and memory intensive.

Scaling Solutions

• Horizontal scaling: Add more game servers to distribute player sessions and reduce load per server.
• State sharding: Partition game state by player groups or regions to reduce data size per server.
• Caching: Use in-memory caches for frequently accessed game rules and player data to speed up validation.
• Load balancing: Distribute incoming player connections evenly to avoid server overload.
• Asynchronous processing: Offload non-critical game rule checks to background jobs to reduce latency.

Back-of-Envelope Cost Analysis

• Requests per second: For 10,000 users playing actively, estimate ~50,000 game state updates per second (5 updates per user per second).
• Storage: Game state storage depends on game complexity; estimate 1 KB per player state -> 10 MB for 10,000 users in memory.
• Bandwidth: Each update ~500 bytes -> 25 MB/s outbound bandwidth needed at 10,000 users.

Interview Tip

When discussing scalability for game rules and requirements, start by clarifying the game's real-time needs and user concurrency. Identify the critical path where game state updates happen. Then, explain how you would scale the system step-by-step: from single server to distributed servers, state sharding, caching, and load balancing. Always justify your choices based on the bottleneck you identify.

Self Check

Your database handles 1000 queries per second (QPS). Game traffic grows 10x to 10,000 QPS. What do you do first?

Answer: Add read replicas and implement caching for frequently read game data to reduce load on the primary database. Also, consider sharding the database by player regions or game sessions to distribute write load.

Key Result

Game state management becomes the first bottleneck at medium scale (~10K users) due to CPU and memory load from frequent updates; scaling requires horizontal server scaling, state sharding, caching, and load balancing.