Q77 — AWS AIF-C01 Ch.2

Question 77 of 100 | ← Chapter 2

A company has deployed a computer vision model. It wants to continuously monitor model performance and detect any drift or degradation over time. Which AWS service or feature satisfies these requirements?

Correct Answer: B. Amazon SageMaker Model Monitor

Explanation

Analysis: A. Amazon SageMaker Clarify detects bias in data and ML models and suggests mitigation strategies—but it is not designed for continuous model performance tracking. B. Amazon SageMaker Model Monitor is a fully managed service that continuously monitors ML model quality, data quality, and concept/data drift—and provides actionable alerts and insights. This directly fulfills the company’s needs. C. Amazon Augmented AI (A2I) integrates human review into ML workflows to improve model quality and trustworthiness—but it does not provide automated, continuous performance monitoring. D. AWS CloudTrail logs AWS account activity and API calls—it is not intended for monitoring individual ML model performance. For continuous tracking and detection of drift or degradation in a computer vision model, Amazon SageMaker Model Monitor is the optimal choice. It collects real-time inference data, computes key metrics (e.g., accuracy, data distribution shifts), and triggers alerts upon anomalies—ensuring models operate as expected. Compared to manual monitoring, Model Monitor automates and scales model monitoring across the ML lifecycle.