- A
Use SageMaker Inference Recommender to find the optimal instance type and count
Inference Recommender provides recommendations to avoid over-provisioning.
- B
Enable auto-scaling to adjust the number of instances based on demand
Auto-scaling ensures you only pay for capacity needed.
- C
Create a CloudWatch dashboard to monitor endpoint latency
Why wrong: Monitoring latency is operational, not a direct cost optimization action.
- D
Use SageMaker Managed Spot Training for endpoint instances
Why wrong: Spot instances are not supported for real-time endpoints.
- E
Purchase SageMaker Savings Plans for a discounted rate
Savings Plans reduce cost in exchange for a usage commitment.
Question 698 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. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
An ML team uses SageMaker to deploy a model for real-time inference. They want to monitor and improve cost efficiency. Which THREE actions should they take? (Select THREE.)
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 find the optimal instance type and count
SageMaker Inference Recommender runs load tests against your model to generate instance type and count recommendations that balance performance and cost. By selecting the optimal configuration, you avoid over-provisioned instances that waste money or under-provisioned ones that degrade user experience, directly improving cost efficiency.
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 SageMaker Inference Recommender to find the optimal instance type and count
Why this is correct
Inference Recommender provides recommendations to avoid over-provisioning.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Enable auto-scaling to adjust the number of instances based on demand
Why this is correct
Auto-scaling ensures you only pay for capacity needed.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Create a CloudWatch dashboard to monitor endpoint latency
Why it's wrong here
Monitoring latency is operational, not a direct cost optimization action.
- ✗
Use SageMaker Managed Spot Training for endpoint instances
Why it's wrong here
Spot instances are not supported for real-time endpoints.
- ✓
Purchase SageMaker Savings Plans for a discounted rate
Why this is correct
Savings Plans reduce cost in exchange for a usage commitment.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse monitoring (Option C) with cost optimization, or they mistakenly apply Spot Training (Option D) to inference endpoints, not realizing that Spot instances are only supported for training and not for real-time inference due to interruption risk.
Detailed technical explanation
How to think about this question
SageMaker Inference Recommender uses a combination of synthetic payloads and real-time metrics (e.g., latency, throughput, CPU/memory utilization) to model your workload. It then cross-references these results against SageMaker instance pricing to output a cost-optimized configuration. In practice, a team serving a BERT model might find that a single ml.c5.xlarge instance handles 100 TPS at 50ms latency, whereas two ml.c5.large instances cost 20% more for the same throughput, revealing an immediate savings opportunity.
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.
TExam Day Tips
- 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.
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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: Use SageMaker Inference Recommender to find the optimal instance type and count — SageMaker Inference Recommender runs load tests against your model to generate instance type and count recommendations that balance performance and cost. By selecting the optimal configuration, you avoid over-provisioned instances that waste money or under-provisioned ones that degrade user experience, directly improving cost efficiency.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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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