- A
OverheadLatency
Time spent on SageMaker infrastructure overhead.
- B
Invocations
Why wrong: Count of requests, not latency.
- C
ModelLatency
Time taken by the model to perform inference.
- D
MemoryUtilization
Why wrong: Custom metric, not a standard SageMaker latency metric.
- E
Latency
Total time from request receipt to response sent.
Question 873 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 company is deploying a SageMaker real-time endpoint and needs to monitor inference latency. Which THREE metrics are available from SageMaker for this purpose? (Choose 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
✓
OverheadLatency
OverheadLatency is a SageMaker metric that measures the time taken by the SageMaker infrastructure to process the request before and after invoking the model, including network overhead and framework overhead. It is one of the three metrics specifically designed to monitor inference latency for real-time endpoints.
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.
- ✓
OverheadLatency
Why this is correct
Time spent on SageMaker infrastructure overhead.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Invocations
Why it's wrong here
Count of requests, not latency.
- ✓
ModelLatency
Why this is correct
Time taken by the model to perform inference.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
MemoryUtilization
Why it's wrong here
Custom metric, not a standard SageMaker latency metric.
- ✓
Latency
Why this is correct
Total time from request receipt to response sent.
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 often confuse Invocations (a request count metric) or MemoryUtilization (a resource utilization metric) with latency metrics, but SageMaker specifically provides three distinct latency-focused metrics: Latency, ModelLatency, and OverheadLatency.
Detailed technical explanation
How to think about this question
SageMaker publishes three latency metrics for real-time endpoints: ModelLatency (time spent in the model container processing the request), OverheadLatency (time spent in the SageMaker infrastructure for request handling, serialization, and deserialization), and Latency (the total end-to-end time from when SageMaker receives the request to when it sends the response, which is the sum of ModelLatency and OverheadLatency). These metrics are emitted to CloudWatch every 60 seconds by default and can be used to set up alarms for performance degradation.
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 healthcare organisation deploys an application with a public-facing web tier and a private database tier. The database subnet has no public IP and only accepts connections from the web tier's security group. Questions like this test whether you can design cloud network isolation using VNets/VPCs, subnets, and security group rules.
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: OverheadLatency — OverheadLatency is a SageMaker metric that measures the time taken by the SageMaker infrastructure to process the request before and after invoking the model, including network overhead and framework overhead. It is one of the three metrics specifically designed to monitor inference latency for real-time endpoints.
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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