MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A team has deployed a real-time inference endpoint and wants to automatically scale based on CPU utilization. Which scaling policy type should they use with Application Auto Scaling for SageMaker endpoints?
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
Target tracking scaling adjusts the number of instances based on a target metric value (e.g., CPU utilization at 50%). Step scaling uses step adjustments, and simple scaling is deprecated. Predictive scaling is not supported for SageMaker 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.
- ✓
Target tracking scaling
Why this is correct
Target tracking scaling automatically maintains a target metric value, such as average CPU utilization.
- ✗
Step scaling
Why it's wrong here
Step scaling uses step adjustments based on breach magnitude, not a target metric value.
- ✗
Predictive scaling
Why it's wrong here
Predictive scaling forecasts future load, but it is not supported for SageMaker endpoints.
- ✗
Simple scaling
Why it's wrong here
Simple scaling is deprecated and not recommended for production use.
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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.