AIF-C01 Practice Question: Security, Compliance, and Governance for AI Solutions
A company needs to govern the lifecycle of ML models, including versioning, monitoring for drift, and decommissioning outdated models. Which TWO services should they use? (Choose 2)
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Amazon SageMaker Model Registry
SageMaker Model Registry handles versioning and model approval; SageMaker Model Monitor tracks drift and performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
AWS CloudTrail
Why it's wrong here
CloudTrail logs API calls but does not govern model lifecycle.
- ✓
Amazon SageMaker Model Registry
Why this is correct
Model Registry manages model versions, approvals, and lifecycle stages.
- ✓
Amazon SageMaker Model Monitor
Why this is correct
Model Monitor detects drift and performance degradation.
- ✗
Amazon S3
Why it's wrong here
S3 stores artifacts but does not provide lifecycle governance.
- ✗
AWS CodePipeline
Why it's wrong here
CodePipeline is for CI/CD, not model governance.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AIF-C01 exam.