Your question is Monitoring After Deployment. 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 monitor your ML model after deployment?
Explain a practical monitoring framework for a production model. Cover data quality, feature and prediction drift, model performance, calibration, operational health, and business outcomes. Describe how you would handle delayed or incomplete ground-truth labels, define alert thresholds, investigate alerts, and decide when to retrain, recalibrate, roll back, or replace the model.