Your question is Deploying Models to Production. 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).
Can you explain how you would deploy a model into a production environment?
Discuss the complete lifecycle from validating the trained artifact and preprocessing pipeline through serving predictions, monitoring behavior, detecting data or concept drift, and safely rolling back. Address how you would choose between batch and online inference, manage model versions, prevent training-serving skew, and define operational and model-quality success criteria.