MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A data science team wants to track the lineage of models, including datasets, training jobs, and endpoints, for reproducibility and audit. They need a solution that captures relationships between artifacts automatically during training and deployment. Which service should they use?
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
✓
SageMaker ML Lineage Tracking
SageMaker ML Lineage Tracking automatically records the relationships between artifacts (datasets, jobs, models, endpoints) and tracks the provenance of ML workflows.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon S3 object versioning
Why it's wrong here
Versioning tracks changes but does not capture ML workflow lineage.
- ✗
SageMaker Experiments
Why it's wrong here
Experiments track trials and parameters but not full lineage across steps.
- ✗
SageMaker Model Registry
Why it's wrong here
Model Registry manages model versions and approvals, not lineage tracking.
- ✓
SageMaker ML Lineage Tracking
Why this is correct
Captures artifact relationships and lineage automatically.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLA-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 MLA-C01 exam.