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

IntermediatePrefer not to say
Jun 2026

Summary

Meta system design round for a software engineer role. One question, Instagram, but it sprawled into a bunch of follow-ups and I left feeling like I'd covered the right ground in the wrong order.

Questions Asked (1)

Q1

Design Instagram, covering core features like posting, news feeds, likes, and comments.

System DesignTechnical Trade-offs
Author's notes

I knew this type of question was coming and still managed to fumble the structure.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale (e.g., 1B users, 100M daily posts), then design the core data model and high-level architecture. Focus on the feed generation strategy (fan-out on write vs. read) and how to handle likes/comments at scale, discussing trade-offs and bottlenecks.

Pro tip: Proactively discuss the trade-offs between fan-out on write and fan-out on read, and propose a hybrid approach for celebrities. This shows you understand real-world constraints and can make pragmatic decisions.

1. Clarify Requirements and Scale

Ask about functional requirements (posting, feed, likes, comments) and non-functional requirements (latency, availability, consistency). Estimate scale: number of users, posts per day, read/write ratio.

2. High-Level Architecture

Sketch the main components: clients, API gateway, services (user, post, feed, like, comment), databases (SQL/NoSQL), cache, message queue, and CDN for media. Explain data flow for posting and viewing feed.

3. Data Model and Storage

Define schemas for users, posts, follows, likes, comments. Choose appropriate databases: e.g., graph DB for social graph, wide-column for posts, and caching for hot data. Discuss sharding and replication.

4. Feed Generation and Ranking

Explain feed generation: fan-out on write vs. read, and hybrid approach. Discuss ranking algorithm (e.g., chronological vs. algorithmic) and how to handle celebrities. Mention caching and precomputation.

5. Scaling and Trade-offs

Address bottlenecks: hot keys, thundering herd, consistency vs. availability. Discuss trade-offs in like/comment counts (eventual consistency), media storage (CDN), and real-time updates (WebSockets vs. polling).

Key Points to Mention

  • Fan-out on write vs. fan-out on read for feed generation, and hybrid approach for celebrities
  • Use of caching (Redis/Memcached) for feed and hot data to reduce latency
  • Sharding and replication strategies for databases (e.g., shard by user ID)
  • Eventual consistency for likes/comments counts and use of counters (e.g., Redis INCR)
  • Media storage and delivery via CDN, with separate service for image/video processing
  • Handling of social graph (follows) using graph database or optimized relational tables

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