Question 1,114 of 1,672
MLS-C01 Modeling Practice Question
A machine learning engineer needs to deploy a model that makes real-time predictions with latency under 100ms. The model is a small ensemble of decision trees. Which AWS service 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
✓
Amazon SageMaker endpoint
Amazon SageMaker provides real-time endpoints with low latency for model inference, and can host the ensemble as a single endpoint.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon EMR with Spark Streaming
Why it's wrong here
EMR is for big data processing, not low-latency real-time inference.
- ✗
AWS Glue
Why it's wrong here
Glue is for ETL, not real-time model serving.
- ✓
Amazon SageMaker endpoint
Why this is correct
SageMaker endpoints are designed for real-time inference with low latency.
- ✗
AWS Lambda with custom container
Why it's wrong here
Lambda has a 15-minute timeout but cold starts may add latency; less suited for real-time ML.
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Last reviewed: Jun 20, 2026
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.
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