Your question is Indexing Trade-offs for High-Traffic Features. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Discuss the trade-offs of different database indexing strategies for high-traffic features.
Consider the implications for an online ML feature store and model-serving path. Explain how you would choose among primary-key, composite, secondary, range, inverted, and approximate nearest-neighbor indexes, including read latency, write amplification, storage cost, consistency, hot keys, and operational complexity. Address how your choice would change for batch features versus online features, and how you would validate and monitor it.