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ML Solution Monitoring, Maintenance, and SecuritymediumMultiple ChoiceObjective-mapped

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

A company uses SageMaker Inference Recommender to select the optimal endpoint configuration. After running the recommender, they receive a recommendation for a specific instance type and initial instance count. What should they do next to optimize costs over time?

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

Set up auto-scaling with a target tracking policy based on the recommended metric

SageMaker Inference Recommender provides a baseline configuration. To optimize costs, they should apply auto-scaling with a target tracking policy based on the recommended metric, such as invocation count or 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.

  • Use the recommended configuration without changes, as it is already optimal

    Why it's wrong here

    The recommendation is static; traffic may vary, so scaling is needed.

  • Purchase a Savings Plan for the recommended instance type to reduce hourly cost

    Why it's wrong here

    Savings Plans reduce cost per instance hour, but do not address over-provisioning; auto-scaling is needed first.

  • Set up auto-scaling with a target tracking policy based on the recommended metric

    Why this is correct

    Auto-scaling adjusts capacity to demand, minimizing cost while meeting performance.

  • Manually adjust the instance count daily based on observed traffic

    Why it's wrong here

    Manual adjustment is not automated and may not react quickly.

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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.