MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A company wants to reduce costs for a production SageMaker endpoint that has predictable traffic patterns. They have purchased a Savings Plan. What additional step can they take to further optimize costs while maintaining performance?
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
✓
Use SageMaker Inference Recommender to right-size the endpoint
SageMaker Inference Recommender provides instance type and configuration recommendations to right-size endpoints, balancing cost and performance. It is the appropriate tool for cost optimization beyond a Savings Plan.
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 SageMaker Inference Recommender to right-size the endpoint
Why this is correct
Inference Recommender tests different instance types and configurations to find the most cost-effective option for the workload.
- ✗
Reduce the number of instances to one, regardless of load
Why it's wrong here
Arbitrarily reducing instances may cause performance degradation and throttling.
- ✗
Switch from real-time to batch inference
Why it's wrong here
Batch inference is not suitable for real-time, low-latency requirements.
- ✗
Disable auto-scaling
Why it's wrong here
Disabling auto-scaling may result in over-provisioning or under-provisioning, increasing costs or harming performance.
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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.