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Meta·Software Engineer·Onsite - System Design / Architecture·Staff

Staff
May 2026

Summary

Got a system design question for an EM role at Meta. Pretty open-ended, which I guess is the point.

Questions Asked (1)

Q1

How would you design chess.com?

System DesignTechnical Trade-offsProduct Sense & Ideation
Author's notes

This is deceptively wide.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scope with the interviewer, then focus on the core real-time gameplay and matchmaking systems, and finally discuss scalability, trade-offs, and product features. Structure your answer around high-level architecture, data models, and key components, while continuously justifying design decisions.

Pro tip: Emphasize the real-time, low-latency nature of chess and how you would handle concurrency and consistency, as these are critical for a seamless user experience. Also, show product sense by mentioning features like puzzles, tournaments, and social aspects that drive engagement.

1. Clarify Requirements and Scope

Ask questions to understand expected scale (DAU, concurrent games), core features (real-time play, matchmaking, ratings, social), and non-functional requirements (latency, consistency, availability).

2. High-Level Architecture

Outline the main components: client apps, API gateway, game service, matchmaking service, user service, and data stores. Explain how they interact to support real-time gameplay.

3. Deep Dive into Core Components

Detail the design of critical parts: real-time communication (WebSockets), game state management, matchmaking algorithm (ELO-based), and move validation/anti-cheat.

4. Data Model and Storage

Describe how to store user profiles, game history, and ratings. Discuss choices like SQL vs NoSQL, caching, and sharding for scalability.

5. Scalability, Trade-offs, and Product Features

Address scaling to millions of users, handling peak loads, and trade-offs (e.g., consistency vs latency). Also mention additional features like puzzles, tournaments, and social integration.

Key Points to Mention

  • Real-time communication using WebSockets or long polling for low-latency moves
  • Matchmaking service with ELO rating system and queue management
  • Game state management and move validation to prevent cheating
  • Database design for user profiles, game history, and leaderboards (e.g., using Redis for caching, Cassandra for scalability)
  • Scalability considerations: horizontal scaling, load balancing, and handling concurrent games
  • Product features: puzzles, tournaments, social sharing, and spectating to enhance engagement

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.