MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A company uses SageMaker endpoints for real-time inference. They want to automatically scale the number of instances based on the number of outstanding requests. Which auto-scaling policy type should they choose?
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 instance count to maintain a target metric value (e.g., average invocation count per instance). Step scaling uses predefined scaling adjustments based on alarm breaches but does not directly track a target. Simple scaling is not recommended for production. Scheduled scaling is for predictable patterns, not dynamic.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Scheduled scaling
Why it's wrong here
Scheduled scaling is for predictable load patterns, not dynamic request surges.
- ✗
Step scaling
Why it's wrong here
Step scaling uses incremental adjustments but does not track a target metric.
- ✓
Target tracking scaling
Why this is correct
Target tracking automatically adjusts capacity to keep the specified metric at the target value.
- ✗
Simple scaling
Why it's wrong here
Simple scaling is not supported by SageMaker endpoint auto-scaling.
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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.