- A
Set up Amazon CloudWatch alarms on the endpoint's invocation latency metric.
Why wrong: Latency monitoring is for performance, not data drift.
- B
Enable data capture on the SageMaker endpoint to store inference data in Amazon S3.
Data capture is necessary to collect the inference data for monitoring.
- C
Configure Amazon SageMaker Model Monitor to run hourly monitoring schedules.
Model Monitor executes the drift analysis on a schedule using the captured data and baseline.
- D
Deploy a shadow endpoint to compare predictions from the current model and a challenger model.
Why wrong: Shadow endpoints are used for A/B testing, not data drift monitoring.
- E
Create a baseline from the training data to serve as a reference distribution.
Why wrong: Creating a baseline is a one-time prerequisite, not an ongoing monitoring action.
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. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 machine learning team has deployed a model using Amazon SageMaker and wants to set up continuous monitoring for data drift. Which TWO actions are essential for ongoing data drift detection?
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 data capture on the SageMaker endpoint to store inference data in Amazon S3.
Option A (Enable data capture) is essential because data capture collects inference requests and responses, which are required for monitoring. Option C (Configure Model Monitor to run hourly) is essential because Model Monitor analyzes the captured data against a baseline to detect drift. Option B is a prerequisite but not an ongoing action. Options D and E are unrelated to data drift monitoring.
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.
- ✗
Set up Amazon CloudWatch alarms on the endpoint's invocation latency metric.
Why it's wrong here
Latency monitoring is for performance, not data drift.
- ✓
Enable data capture on the SageMaker endpoint to store inference data in Amazon S3.
Why this is correct
Data capture is necessary to collect the inference data for monitoring.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Configure Amazon SageMaker Model Monitor to run hourly monitoring schedules.
Why this is correct
Model Monitor executes the drift analysis on a schedule using the captured data and baseline.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Deploy a shadow endpoint to compare predictions from the current model and a challenger model.
Why it's wrong here
Shadow endpoints are used for A/B testing, not data drift monitoring.
- ✗
Create a baseline from the training data to serve as a reference distribution.
Why it's wrong here
Creating a baseline is a one-time prerequisite, not an ongoing monitoring action.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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.
Identify which MLA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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ML Solution Monitoring, Maintenance and Security — study guide chapter
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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 data capture on the SageMaker endpoint to store inference data in Amazon S3. — Option A (Enable data capture) is essential because data capture collects inference requests and responses, which are required for monitoring. Option C (Configure Model Monitor to run hourly) is essential because Model Monitor analyzes the captured data against a baseline to detect drift. Option B is a prerequisite but not an ongoing action. Options D and E are unrelated to data drift monitoring.
What should I do if I get this MLA-C01 question wrong?
Identify which MLA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 23, 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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