Code RoomShadow deployment for fraud models
MediumPrep Room Coding #3492

Shadow deployment for fraud models

System designML systemsMid–Senior~40 min

Design a shadow-deployment and validation harness for promoting a new fraud-scoring model to production, where you can't just A/B it freely because a worse model means real fraud losses or wrongly-blocked legitimate payments — both costly. You need confidence the new model behaves correctly on live traffic before it makes any real decision. Walk through how shadow mode works, what you compare to gain confidence, and how you close the gap between offline-eval results and live behavior.

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.

Clarify4:30 left
Estimate4:30 planned
Design13:30 planned
Deep dive10:30 planned
Failure7:00 planned
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Which questions mattered is sealed until you submit. Telling you now would just be handing over the edge cases.