MLS-C01 Modeling Practice Question
A company is using Amazon SageMaker to deploy a model for real-time inference. The model has a latency requirement of less than 100 milliseconds. During testing, the latency is around 150 milliseconds. Which action can most likely reduce the latency to meet the requirement?
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 a larger instance type for the endpoint.
Enabling data capture adds overhead and increases latency. Using a larger instance type would provide more compute and reduce latency, but may increase cost. Reducing the batch size for inference (if batching is used) can reduce latency because the model processes fewer requests at once. However, the question implies a real-time endpoint which typically processes one request at a time; batch size might be 1. Increasing the variant weight for the production variant is for traffic routing, not latency. The most direct is to use a more powerful instance type. But also consider that increasing batch size (if using multi-record) increases latency. Reducing batch size reduces latency. However, for a real-time endpoint, the instance type is key. I'll go with using a larger instance type.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Reduce the batch size for inference.
Why it's wrong here
If the endpoint is already processing one request at a time, reducing batch size may not apply. But if batching is used, reducing batch size can reduce latency. However, typically for real-time endpoints, batch size is 1. So this may not help.
- ✗
Enable data capture for the endpoint.
Why it's wrong here
Enabling data capture adds logging overhead, increasing latency.
- ✗
Increase the initial variant weight for the production variant.
Why it's wrong here
Variant weight is for A/B testing traffic distribution, not latency.
- ✓
Use a larger instance type for the endpoint.
Why this is correct
A larger instance type provides more compute resources, reducing inference latency.
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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.