MLS-C01 Practice Question: Machine Learning Implementation and Operations
A data scientist needs to deploy a model with a custom inference container. Which THREE requirements must the container meet for SageMaker hosting?
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
✓
Implement a /ping endpoint for health checks
SageMaker requires custom inference containers to implement the /ping endpoint for health checks (C), serve on port 8080 (D), and implement the /invocations endpoint for predictions (E). Option A is for training containers, not inference. Option B is unnecessary; the container can load the model using any method.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Provide a training script at /opt/ml/input/data
Why it's wrong here
Training script location is for training jobs, not hosting.
- ✗
Use the SageMaker Python SDK to load the model
Why it's wrong here
The SDK is not required; any framework can be used.
- ✓
Implement a /ping endpoint for health checks
Why this is correct
SageMaker uses /ping to check container health.
- ✓
Serve on port 8080
Why this is correct
SageMaker expects the container to listen on port 8080.
- ✓
Implement a /invocations endpoint for predictions
Why this is correct
SageMaker sends inference requests to /invocations.
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.