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ML Solution Monitoring, Maintenance, and SecuritymediumMultiple ChoiceObjective-mapped

MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security

A team is monitoring a SageMaker endpoint and notices that the average latency (ModelLatency) is increasing over time, but the number of invocations is steady. They suspect that the model's inference code is becoming slower due to memory leaks. Which metric should they also examine to confirm this hypothesis?

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

MemoryUtilization metric (if custom)

SageMaker publishes memory utilization metrics if the container emits them via CloudWatch. A memory leak would show increasing memory usage over time, correlating with increasing latency.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Invocations metric

    Why it's wrong here

    Steady, as stated, does not explain latency increase.

  • OverheadLatency metric

    Why it's wrong here

    Overhead latency is SageMaker infrastructure, not model inference.

  • 5XXError metric

    Why it's wrong here

    Errors may occur but not directly indicate memory leaks.

  • MemoryUtilization metric (if custom)

    Why this is correct

    Increasing memory usage suggests a leak, which can cause latency growth.

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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.