Start by clarifying requirements and scale (e.g., number of users, read/write ratio, latency goals). Then propose a high-level architecture that separates feed generation (fan-out on write vs. read) from per-user read status tracking, and detail storage, caching layers (CDN, edge, hot-article), and trade-offs. Conclude by discussing how to handle hot articles and ensure scalability.
Pro tip: Emphasize the trade-off between fan-out on write and fan-out on read, and propose a hybrid approach for celebrities/hot articles. Also, mention that read status can be tracked efficiently using a distributed set or bitmap per user, and that CDN and edge caching are crucial for reducing latency for static assets and popular articles.
Ask about user base size, daily active users, read/write patterns, latency requirements, and consistency needs. Establish assumptions for the design.
Outline the main components: feed generation service, storage for feeds and read status, caching layers, and CDN. Decide on fan-out strategy (write vs. read) and justify.
Design schemas for articles, user feeds, and read status. Choose appropriate databases (e.g., Cassandra for feeds, Redis for read status) and discuss partitioning and replication.
Detail CDN for static assets, edge caching for dynamic content, and hot-article caches (e.g., Redis) to handle viral content. Explain cache invalidation and TTLs.
Discuss trade-offs (e.g., consistency vs. latency, storage cost vs. speed) and how the design scales horizontally. Mention monitoring and failure handling.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.