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

SeniorPrefer not to say
Jul 2026

Summary

Meta system design round, one big question about WhatsApp architecture with a follow-up on scale and reliability. Pretty open-ended, which I wasn't fully prepared for.

Questions Asked (1)

Q1

Design the system architecture for WhatsApp, and walk through how you'd handle scale, performance, and reliability.

System DesignTechnical Trade-offs
Author's notes

I started with the messaging flow and worked outward but spent way too long on the client-server handshake before even touching storage or delivery guarantees.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale (e.g., 2B users, 100B messages/day), then design a high-level architecture covering client, edge, and backend services. Deep dive into critical components like message delivery, storage, and real-time communication, explaining trade-offs for scale, performance, and reliability.

Pro tip: Emphasize the end-to-end message flow and how you ensure exactly-once delivery and ordering, as this is the core challenge. Show awareness of Meta's specific infrastructure (e.g., TAO, Memcached, Haystack) to demonstrate domain knowledge.

1. Requirements and Scale Estimation

Clarify functional (1:1 chat, group chat, media, presence) and non-functional (latency, availability, consistency) requirements. Estimate scale: 2B users, 100B messages/day, peak QPS, storage needs.

2. High-Level Architecture

Outline major components: clients (mobile/web), edge (CDN, load balancers), API gateways, chat servers, message queues, storage (message DB, media storage), and push notification services.

3. Deep Dive into Critical Components

Focus on message delivery: how messages are routed, stored, and delivered in real-time. Discuss WebSocket connections, message queues (Kafka), and storage choices (e.g., HBase, Cassandra) for durability and low latency.

4. Scale, Performance, and Reliability

Explain scaling strategies: sharding by user ID, replication for fault tolerance, caching for presence and recent messages. Discuss performance optimizations (batching, compression) and reliability (retries, idempotency, exactly-once semantics).

5. Trade-offs and Wrap-up

Summarize key trade-offs (e.g., consistency vs. availability, latency vs. durability) and how you'd monitor and iterate. Mention potential bottlenecks and future improvements.

Key Points to Mention

  • End-to-end message flow: client -> edge -> chat server -> queue -> storage -> recipient
  • Use of WebSockets for real-time bidirectional communication and fallback to long polling
  • Sharding and replication strategies for message storage (e.g., by user ID or chat ID)
  • Exactly-once delivery and message ordering using sequence numbers and idempotent processing
  • Caching and CDN for media (images, videos) to reduce latency and backend load
  • Presence and last-seen using a distributed cache with eventual consistency

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