- A
Enable SageMaker ML Lineage Tracking
Lineage tracking automatically records artifacts, actions, and contexts.
- B
Register all models in the SageMaker Model Registry
Model Registry tracks model versions and metadata.
- C
Store trained models in a public S3 bucket
Why wrong: Public access is insecure and unnecessary for reproducibility.
- D
Use SageMaker Experiments to organize training runs
Why wrong: Experiments track runs but are not the primary tool for lineage across full ML lifecycle.
- E
Tag all resources with metadata such as project ID and training run ID
Tags help associate resources with lineage and improve searchability.
Question 136 of 1,000
MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
This MLA-C01 practice question tests your understanding of ml solution monitoring, maintenance, and security. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data science team uses SageMaker to train and deploy models. They need to track model lineage, including datasets, training jobs, and model versions, to ensure reproducibility. Which THREE actions should they take? (Select THREE)
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
✓
Enable SageMaker ML Lineage Tracking
A is correct because SageMaker ML Lineage Tracking automatically captures the relationships between datasets, training jobs, and model versions, creating a directed acyclic graph (DAG) of the ML workflow. This enables full reproducibility by allowing you to trace which data and code produced a specific model, without manual intervention.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Enable SageMaker ML Lineage Tracking
Why this is correct
Lineage tracking automatically records artifacts, actions, and contexts.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Register all models in the SageMaker Model Registry
Why this is correct
Model Registry tracks model versions and metadata.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Store trained models in a public S3 bucket
Why it's wrong here
Public access is insecure and unnecessary for reproducibility.
- ✗
Use SageMaker Experiments to organize training runs
Why it's wrong here
Experiments track runs but are not the primary tool for lineage across full ML lifecycle.
- ✓
Tag all resources with metadata such as project ID and training run ID
Why this is correct
Tags help associate resources with lineage and improve searchability.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse SageMaker Experiments (which tracks metrics and parameters) with ML Lineage Tracking (which tracks the full provenance graph), leading them to select D instead of A, even though Experiments alone does not capture the inter-resource relationships needed for reproducibility.
Detailed technical explanation
How to think about this question
SageMaker ML Lineage Tracking uses the concept of 'artifacts' (datasets, models), 'actions' (training jobs, processing jobs), and 'contexts' (experiments, projects) to build a provenance graph. Under the hood, it stores lineage metadata in Amazon SageMaker's internal graph database, which you can query via the SageMaker API or SDK to answer questions like 'which training job produced this model version?' or 'which dataset was used to train this model?'. This is critical for audit compliance in regulated industries such as healthcare or finance.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
ML Solution Monitoring, Maintenance, and Security — This question tests ML Solution Monitoring, Maintenance, and Security — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable SageMaker ML Lineage Tracking — A is correct because SageMaker ML Lineage Tracking automatically captures the relationships between datasets, training jobs, and model versions, creating a directed acyclic graph (DAG) of the ML workflow. This enables full reproducibility by allowing you to trace which data and code produced a specific model, without manual intervention.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
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.
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