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

Senior
Jun 2026

Summary

Meta system design round for a SWE role. One question, no fluff, just 'design Instagram' and then you're on your own for the next 45 minutes.

Questions Asked (1)

Q1

Design Instagram.

System DesignTechnical Trade-offsData Modeling
Author's notes

Broad enough to go in a dozen directions and that's kind of the problem.

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AI HintsAI Generated

Suggested Approach

Start by clarifying functional and non-functional requirements, then estimate scale (e.g., 1B users, 100M daily photo uploads). Propose a high-level architecture covering client, API, storage, and CDN, then deep dive into 2-3 critical components like feed generation and media storage. Discuss trade-offs (e.g., push vs. pull for feeds, SQL vs. NoSQL for metadata) and justify your choices.

Pro tip: Focus on the unique challenges of Instagram: massive read-heavy workload, media storage at scale, and low-latency feed generation. Show you understand the difference between the write path (upload) and read path (feed) and how to optimize each.

1. Clarify Requirements and Scale

Ask about functional requirements (photo upload, feed, follow, likes, comments) and non-functional (availability, latency, consistency). Estimate scale: 1B users, 500M DAU, 100M photos/day, read:write ratio 100:1.

2. High-Level Architecture

Sketch the main components: mobile clients, load balancers, API gateway, microservices (user, media, feed, social graph), databases, object storage (S3), CDN, and caching layers (Redis). Explain data flow for upload and feed retrieval.

3. Deep Dive into Key Components

Choose 2-3 areas to detail: media storage (blob storage, CDN, image processing), feed generation (push vs. pull, fan-out on write vs. read), and data modeling (sharding, denormalization). Discuss trade-offs and justify choices.

4. Address Bottlenecks and Trade-offs

Identify potential bottlenecks (hot users, celebrity problem, storage costs) and propose solutions (hybrid feed approach, caching, sharding). Discuss consistency vs. availability (CAP theorem) and latency vs. cost.

5. Summarize and Wrap Up

Recap the design, highlighting how it meets requirements and scales. Mention potential future improvements (e.g., ML for feed ranking, multi-region deployment) and ask if the interviewer wants to explore any area further.

Key Points to Mention

  • Media storage: use object storage (e.g., S3) for photos/videos, with CDN for fast global delivery and image processing pipeline for resizing/compression.
  • Feed generation: hybrid approach—fan-out on write for normal users, fan-out on read for celebrities to avoid write amplification.
  • Data modeling: use a graph database or wide-column store (e.g., Cassandra) for social graph; shard by user ID; denormalize for read efficiency.
  • Caching: use Redis/Memcached for hot data (feeds, user profiles) to reduce database load and latency.
  • Scalability: horizontal scaling with sharding, replication, and microservices; use async processing (e.g., Kafka) for likes, comments, and notifications.
  • Trade-offs: consistency vs. availability (e.g., eventual consistency for feed), push vs. pull for feeds, SQL vs. NoSQL for different data types.

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