MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A company wants to reduce costs for a SageMaker real-time endpoint that has variable traffic. Which feature allows the endpoint to automatically adjust instance count based on demand?
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
✓
Auto Scaling for SageMaker endpoints
Application Auto Scaling for SageMaker endpoints allows dynamic adjustment of instance count based on CloudWatch metrics such as CPU utilization or invocations per instance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
SageMaker Savings Plans
Why it's wrong here
Savings Plans offer discounted pricing for consistent usage, not dynamic scaling.
- ✗
SageMaker Inference Recommender
Why it's wrong here
Inference Recommender helps choose instance type and configuration, not auto-scaling.
- ✗
SageMaker Model Monitor
Why it's wrong here
Model Monitor is for drift detection, not cost optimization.
- ✓
Auto Scaling for SageMaker endpoints
Why this is correct
Auto Scaling adjusts instance count based on demand using target tracking or step scaling policies.
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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.