MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
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.)
⚠ Common exam trap
Watch out — 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.
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.
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.
- ✗
Invocations
Why it's wrong here
Count of requests, not latency.
- ✓
ModelLatency
Why this is correct
Time taken by the model to perform inference.
- ✗
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.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.