System designHardsd-g089

Subject Model servingLevel Senior–Staff~45 minCommon in ML systems interviewsIndustries Technology

Question

Design the online serving stack for a video recommendation feed that must return a personalized ranked list of 20 items in under 100ms p99 for 200M daily users, drawing from a catalog of 500M videos. Candidate generation must surface fresh content (uploaded in the last hour) alongside long-tail personalization. Walk through the two-stage retrieval+ranking architecture, how you keep tail latency bounded, and how a freshly uploaded video gets a chance to be served before it has any engagement signal.

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.

Learn the concepts

Narrate your design

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Run or narrate your approach, then ask the coach.