MLS-C01 Modeling Practice Question
A machine learning team needs to deploy a model that makes real-time predictions with latency under 100 ms. The model is a deep neural network with 500 MB of parameters. Which AWS service should they use?
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 real-time endpoint
Amazon SageMaker real-time endpoints are purpose-built for low-latency inference and can host large models like this 500 MB deep neural network by using appropriate instance types or multi-model endpoints. Option A (AWS Glue) is an ETL service, not for real-time inference. Option B (AWS Lambda) has a 250 MB deployment package limit and cold start latency that would exceed the 100 ms requirement for a 500 MB model. Option D (Amazon EMR) is designed for big data processing with Hadoop/Spark, not for real-time predictions. Therefore, the correct choice is Amazon SageMaker real-time 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.
- ✗
AWS Glue
Why it's wrong here
Glue is for ETL, not real-time inference.
- ✗
AWS Lambda with a container image
Why it's wrong here
Lambda has a 250 MB package limit and cold start latency >100 ms for large models.
- ✓
Amazon SageMaker real-time endpoint
Why this is correct
SageMaker real-time endpoints provide low-latency inference for large models.
- ✗
Amazon EMR
Why it's wrong here
EMR is for distributed data processing, not real-time inference.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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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.