Your question is Ensuring Data Consistency. 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 do you ensure data consistency across distributed systems?
Discuss the question in the context of an end-to-end ML platform, including data ingestion, offline training, feature storage, model deployment, and online inference. Explain how you would choose consistency guarantees, detect divergence, handle partial failures, and prevent training-serving skew. Address how your approach changes with scale, latency, availability, and cost constraints.