- A
Check AWS CloudTrail logs for API errors.
Why wrong: CloudTrail logs API calls, not performance metrics.
- B
Use Amazon SageMaker Debugger to analyze inference performance.
Why wrong: SageMaker Debugger is for training jobs, not inference endpoints.
- C
Review Amazon CloudWatch metrics for the endpoint, such as CPUUtilization and Invocations.
CloudWatch metrics can indicate resource saturation and latency.
- D
Retrain the model with more training data.
Why wrong: Retraining may not improve inference latency if capacity is the issue.
Quick Answer
The correct first step is to review Amazon CloudWatch metrics for the endpoint, such as CPUUtilization and Invocations. This is because CloudWatch provides real-time performance data that directly reveals whether the endpoint is overloaded—high CPUUtilization combined with rising Invocations and elevated ModelLatency indicates insufficient instance capacity, while metrics like MemoryUtilization can further confirm resource saturation. On the AWS Certified Machine Learning Engineer Associate MLA-C01 exam, this question tests your ability to distinguish between monitoring tools: CloudWatch is for inference performance metrics, CloudTrail is for API auditing, and SageMaker Debugger is for training debugging only. A common trap is confusing Debugger’s training role with inference diagnostics, so remember that inference latency always starts with CloudWatch endpoint metrics. Memory tip: “Watch the Cloud for inference load.”
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. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
After deploying a model to a SageMaker endpoint, the operations team notices high inference latency. They suspect it is due to insufficient instance capacity. Which first step should they take to diagnose the issue?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"first"Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
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
Review Amazon CloudWatch metrics for the endpoint, such as CPUUtilization and Invocations.
Option C is correct because CloudWatch metrics like Invocations, ModelLatency, and CPUUtilization can help identify if the endpoint is overloaded. Option A (retrain) doesn't address capacity. Option B (CloudTrail) does not provide performance metrics. Option D (SageMaker Debugger) is for training debugging, not inference.
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.
- ✗
Check AWS CloudTrail logs for API errors.
Why it's wrong here
CloudTrail logs API calls, not performance metrics.
- ✗
Use Amazon SageMaker Debugger to analyze inference performance.
Why it's wrong here
SageMaker Debugger is for training jobs, not inference endpoints.
- ✓
Review Amazon CloudWatch metrics for the endpoint, such as CPUUtilization and Invocations.
Why this is correct
CloudWatch metrics can indicate resource saturation and latency.
Clue confirmation
The clue word "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Retrain the model with more training data.
Why it's wrong here
Retraining may not improve inference latency if capacity is the issue.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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: Review Amazon CloudWatch metrics for the endpoint, such as CPUUtilization and Invocations. — Option C is correct because CloudWatch metrics like Invocations, ModelLatency, and CPUUtilization can help identify if the endpoint is overloaded. Option A (retrain) doesn't address capacity. Option B (CloudTrail) does not provide performance metrics. Option D (SageMaker Debugger) is for training debugging, not inference.
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.
Are there clue words in this question I should notice?
Yes — watch for: "first". Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
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: 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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