Your question is Event-Driven Design Approach. 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 approach an event-driven design pattern?
Discuss how you would decompose a machine learning system into producers, durable event transport, stream processors, model-serving components, and consumers. Explain how you would handle event schemas, ordering, retries, idempotency, backpressure, observability, and the distinction between real-time and batch processing. Address how predictions and user feedback return to the training pipeline, including feature drift and training-serving skew.