Model Monitor

Amazon SageMaker Model Monitor continuously detects deviations in deployed model behavior, covering data quality drift, model quality degradation, bias drift, and feature attribution drift. It captures inference requests and responses, compares live distributions against a baseline computed from a reference dataset, and raises CloudWatch alerts when thresholds are exceeded. The key exam distinction is Model Monitor versus SageMaker Clarify: Clarify runs bias and explainability analysis during development and as baseline jobs, while Model Monitor applies those checks continuously in production. A model that performs well at launch but degrades months later signals drift detection — Model Monitor’s job, not Clarify’s.