Start by clarifying requirements and scale, then design the system in stages: ingestion, deduplication, storage/ranking, and feed serving. Emphasize trade-offs and how you'd handle failures and freshness at scale.
Pro tip: Proactively discuss how you'd measure and monitor freshness and deduplication accuracy, and how you'd handle API rate limits and failures with backoff and circuit breakers.
Ask about number of sources, article volume, update frequency, latency requirements, and ranking criteria. Establish assumptions for QPS, storage, and freshness.
Outline a scheduled, scalable ingestion system using workers, queues, and API clients with rate limiting, retries, and backoff. Consider incremental fetching and handling API pagination.
Describe deduplication techniques (e.g., content hashing, SimHash, MinHash) and storage choices (e.g., NoSQL for articles, search index for ranking). Discuss metadata and versioning.
Explain how to rank articles (e.g., recency, relevance, engagement) and generate a unified feed. Consider precomputation vs. on-the-fly ranking and caching strategies.
Design the feed serving layer with low latency, using CDN, caching, and read replicas. Discuss sharding, partitioning, and how to handle peak loads.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.