Your question is High-Frequency Updates Architecture. 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).
How would you architect a feature to handle high-frequency data updates without sacrificing performance?
Discuss the end-to-end design for an ML-backed feature, including update ingestion, storage, online inference, caching, consistency, and failure handling. Explain how you would choose between synchronous updates, streaming pipelines, micro-batching, and periodic batch recomputation. Cover how you would evaluate freshness, latency, correctness, and resource usage in production.