MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A company wants to track the lineage of their ML models for reproducibility and auditability. Which THREE services or features should they use together to achieve this? (Choose THREE.)
⚠ Common exam trap
Many exam-takers confuse AWS CloudTrail or AWS Config with lineage tracking because both deal with 'tracking' and 'auditing,' but they operate at the infrastructure/API level, not at the ML experiment and artifact relationship level required for model lineage.
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 S3 versioning
Amazon S3 versioning is correct because it preserves every version of an object stored in an S3 bucket, including model artifacts, datasets, and configuration files. By enabling versioning, you can retrieve and revert to any previous version of a model artifact, which is essential for reproducibility and auditability. This directly supports tracking the lineage of ML models by ensuring that the exact input data and model binaries used in a specific experiment are never overwritten or lost.
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 versioning
Why this is correct
Versioning enables tracking changes to datasets and model artifacts over time.
- ✓
SageMaker Experiments
Why this is correct
Tracks trials, parameters, and metrics for model development.
- ✗
AWS CloudTrail
Why it's wrong here
CloudTrail logs API calls but does not provide ML-specific lineage relationships.
- ✓
SageMaker ML Lineage Tracking
Why this is correct
Core service for tracking artifacts, actions, and contexts.
- ✗
AWS Config
Why it's wrong here
AWS Config tracks resource configuration changes but not ML lineage.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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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.