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

Senior
Apr 2026

Summary

System design round at Meta for a software engineer role, focused entirely on designing Instagram with the home feed as the main feature. Pretty deep dive, lots of back and forth on tradeoffs.

Questions Asked (1)

Q1

Design Instagram, with the home feed as the primary feature. Walk through how you'd handle posts, follows, and serving a personalized feed to hundreds of millions of users.

System DesignTechnical Trade-offsData Modeling
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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then design the data model and core APIs for posts and follows. Focus on the feed generation strategy, comparing fan-out on write vs. read, and propose a hybrid approach with caching and ranking. Finally, discuss trade-offs, bottlenecks, and how to handle scale.

Pro tip: Show awareness of the read-heavy nature of the feed and the importance of precomputation and caching. Mention that you'd start with a simple solution and iterate, demonstrating pragmatism.

1. Clarify Requirements and Scale

Ask questions to understand functional and non-functional requirements: number of users, read/write ratio, latency expectations, and features like ranking and media handling.

2. Design Data Model and APIs

Define schemas for users, posts, follows, and feeds. Outline key APIs for creating posts, following users, and fetching the home feed.

3. Choose Feed Generation Strategy

Compare fan-out on write (push) vs. fan-out on read (pull) and propose a hybrid approach for scalability and freshness.

4. Address Storage and Caching

Select databases for different needs (e.g., graph for follows, wide-column for feeds) and design caching layers to reduce latency.

5. Discuss Trade-offs and Scaling

Highlight trade-offs (e.g., consistency vs. availability, latency vs. cost) and how to handle bottlenecks like hot users and media storage.

Key Points to Mention

  • Fan-out on write vs. fan-out on read and hybrid approach for celebrities
  • Use of graph database for social graph and wide-column store for feed cache
  • Ranking algorithm (e.g., EdgeRank) and personalization based on user interactions
  • Caching strategies (Redis, Memcached) and CDN for media
  • Sharding and replication for scalability and fault tolerance
  • Handling media uploads and storage (S3, blob storage) with transcoding

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