MLS-C01 Practice Question: Machine Learning Implementation and Operations
A company deploys a SageMaker model for inference. After a few days, response times increase significantly. CloudWatch metrics show high CPU utilization and memory usage. The model is a large ensemble. What is the most cost-effective solution?
⚠ Common exam trap
Many candidates choose manual scaling (Option B) or vertical scaling (Option D) because they seem simpler, but the exam tests the understanding that automatic horizontal scaling is the most cost-effective and operationally efficient approach for handling variable inference workloads in SageMaker.
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 SageMaker automatic scaling based on CPU utilization
SageMaker automatic scaling based on CPU utilization is the most cost-effective solution because it dynamically adjusts the number of inference instances in response to real-time demand, adding capacity only when CPU usage is high and removing it when demand drops. This avoids over-provisioning while maintaining performance for the large ensemble model, which is compute-intensive. Other options either introduce manual overhead, are unsuitable for large models, or incur unnecessary cost by permanently using larger instances.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Configure SageMaker automatic scaling based on CPU utilization
Why this is correct
Auto scaling dynamically adjusts instance count to handle load cost-effectively.
- ✗
Use CloudWatch alarms to notify the team, who manually launch additional endpoints
Why it's wrong here
Manual intervention is slow and not cost-effective.
- ✗
Migrate the model to AWS Lambda with provisioned concurrency
Why it's wrong here
Lambda has memory and timeout limits unsuitable for large ensemble models.
- ✗
Replace the current instance type with a larger one
Why it's wrong here
Vertical scaling is less cost-effective than horizontal scaling for variable loads.
Go deeper
Related to this question
About these practice questions
This MLS-C01 question is part of Courseiva's 1,672-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-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 MLS-C01 exam.