MLS-C01 Modeling Practice Question
A machine learning engineer is deploying a model using Amazon SageMaker and wants to automatically scale the endpoint based on the number of incoming requests. Which scaling policy should be used?
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
✓
Target tracking scaling
Amazon SageMaker endpoints support Application Auto Scaling. A target tracking scaling policy (Option C) is the recommended approach when you want to automatically scale based on a metric like InvocationsPerInstance. It adjusts capacity to maintain the target value of the metric. Step scaling (Option A) requires defining step adjustments and thresholds. Simple scaling is no longer recommended by AWS. Scheduled scaling (Option B) is for predictable traffic patterns. Therefore, Option C is correct.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Step scaling
Why it's wrong here
Step scaling is unsuitable for automatically scaling a SageMaker endpoint based on the number of incoming requests because it scales in predefined increments when metric thresholds are breached, rather than dynamically adjusting to maintain a specific target value. While it allows for granular control over scaling actions at different metric levels, such as adding varying numbers of instances for distinct CPU utilisation percentages, it lacks the continuous, target-oriented adjustment mechanism required to optimise for a fluctuating request load.
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Scheduled scaling
Why it's wrong here
Scheduled scaling is for predictable traffic.
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Target tracking scaling
Why this is correct
Target tracking automatically adjusts capacity based on a target metric.
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Simple scaling
Why it's wrong here
Simple scaling requires manual thresholds.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-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 MLS-C01 exam.