MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A company wants to reduce costs for a SageMaker real-time endpoint that receives predictable traffic patterns: high during business hours and low at night. The model is a small PyTorch model. Which cost-saving strategy is most suitable?
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
✓
Configure auto-scaling with a scheduled scaling policy to add instances during business hours and reduce at night
Auto-scaling with a schedule can adjust instance count based on time, matching capacity to demand. This is more efficient than manual scaling or using a larger 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.
- ✗
Use a single large instance to handle peak load
Why it's wrong here
Overprovisioned for low traffic, wasting cost.
- ✗
Use a multi-model endpoint with multiple models
Why it's wrong here
Does not directly address cost for a single model.
- ✓
Configure auto-scaling with a scheduled scaling policy to add instances during business hours and reduce at night
Why this is correct
Matches capacity to predictable demand, minimizing cost.
- ✗
Switch to batch transform jobs and run nightly
Why it's wrong here
Real-time endpoint is required for low-latency predictions.
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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.