E-commerce recommendation shelf
Design a recommendation system for an e-commerce homepage serving 80M monthly active users and a catalog of 50M items. The 'recommended for you' shelf must return within a 150ms p99 budget at ~30k requests/sec, blend recency of browsing behavior with long-term preferences, and exclude already-purchased or out-of-stock items. Walk through retrieval, scoring, the data model for user/item signals, and how you keep recommendations fresh as the catalog and user behavior change.
What a strong answer looks like
Clarify scale and constraints first. Propose a clean component breakdown, then go deep on the hard parts (data model, bottlenecks, consistency, failure modes) and name the trade-offs you are making.
Clarify5:00 left
Estimate5:00 planned
Design15:00 planned
Deep dive12:00 planned
Failure8:00 planned
Which questions mattered is sealed until you submit. Telling you now would just be handing over the edge cases.
Run or narrate your approach, then ask the coach.