Model Monitoring and Evaluation Questions

Designing observability and evaluation practices to detect model degradation and to iterate responsibly in production. Topics include choosing health and quality metrics, drift detection and data distribution monitoring, alerting and diagnostic tooling, strategies for retraining and model rollback, offline to online evaluation gaps, and how to use A and B testing frameworks to validate improvements. Candidates should explain how to instrument models, interpret signals, and prioritize fixes in a production environment.