- A
Use a single large instance to handle peak load
Why wrong: Overprovisioned for low traffic, wasting cost.
- B
Use a multi-model endpoint with multiple models
Why wrong: Does not directly address cost for a single model.
- C
Configure auto-scaling with a scheduled scaling policy to add instances during business hours and reduce at night
Matches capacity to predictable demand, minimizing cost.
- D
Switch to batch transform jobs and run nightly
Why wrong: Real-time endpoint is required for low-latency predictions.
Question 908 of 1,000
MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
This MLA-C01 practice question tests your understanding of ml solution monitoring, maintenance, and security. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Switch to batch transform jobs and run nightly
Why it's wrong here
Real-time endpoint is required for low-latency predictions.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which MLA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
ML Solution Monitoring, Maintenance, and Security — This question tests ML Solution Monitoring, Maintenance, and Security — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: 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.
What should I do if I get this MLA-C01 question wrong?
Identify which MLA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
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.
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