- A
Latency and ModelLatency
Why wrong: Total Latency includes both ModelLatency and OverheadLatency, but does not separate them. Need OverheadLatency as well.
- B
Invocations and 4XXError
Why wrong: Invocations count requests, and 4XXError indicates client errors, not latency breakdown.
- C
5XXError and MemoryUtilization
Why wrong: 5XXError indicates server errors, and MemoryUtilization shows memory usage, not latency breakdown.
- D
ModelLatency and OverheadLatency
ModelLatency shows inference time inside the container; OverheadLatency shows SageMaker overhead. Comparing them pinpoints the latency source.
Question 784 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 machine learning engineer notices that the latency of a SageMaker endpoint has increased over time. They need to identify which component (model inference vs. pre/post-processing) contributes most to the latency. Which CloudWatch metrics should they examine?
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
✓
ModelLatency and OverheadLatency
SageMaker endpoints emit CloudWatch metrics that break down total latency into model inference time (ModelLatency) and the time spent in pre/post-processing (OverheadLatency). By comparing these two metrics, the engineer can pinpoint whether the bottleneck is in the inference code or in the custom preprocessing/postprocessing logic. Option D directly provides both metrics needed for this root-cause analysis.
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.
- ✗
Latency and ModelLatency
Why it's wrong here
Total Latency includes both ModelLatency and OverheadLatency, but does not separate them. Need OverheadLatency as well.
- ✗
Invocations and 4XXError
Why it's wrong here
Invocations count requests, and 4XXError indicates client errors, not latency breakdown.
- ✗
5XXError and MemoryUtilization
Why it's wrong here
5XXError indicates server errors, and MemoryUtilization shows memory usage, not latency breakdown.
- ✓
ModelLatency and OverheadLatency
Why this is correct
ModelLatency shows inference time inside the container; OverheadLatency shows SageMaker overhead. Comparing them pinpoints the latency source.
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 the total Latency metric with a breakdown metric, assuming it alone can identify the bottleneck, when in fact only the pair of ModelLatency and OverheadLatency provides the necessary decomposition.
Trap categories for this question
Command / output trap
5XXError indicates server errors, and MemoryUtilization shows memory usage, not latency breakdown.
Detailed technical explanation
How to think about this question
Under the hood, SageMaker records ModelLatency as the time from when the container receives the request to when it returns the response, while OverheadLatency captures the time spent in the SageMaker infrastructure (e.g., network I/O, request routing, and any custom pre/post-processing scripts). In a real-world scenario, if OverheadLatency grows due to a memory leak in a custom preprocessing function, the engineer would see a rising OverheadLatency trend while ModelLatency remains stable, directly pointing to the preprocessing code as the culprit.
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 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.
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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: ModelLatency and OverheadLatency — SageMaker endpoints emit CloudWatch metrics that break down total latency into model inference time (ModelLatency) and the time spent in pre/post-processing (OverheadLatency). By comparing these two metrics, the engineer can pinpoint whether the bottleneck is in the inference code or in the custom preprocessing/postprocessing logic. Option D directly provides both metrics needed for this root-cause analysis.
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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