MLS-C01 Practice Question: Machine Learning Implementation and Operations
A data scientist needs to deploy a trained model to Amazon SageMaker for real-time inference. The model is stored as a .tar.gz file in Amazon S3. Which AWS service is used to create a SageMaker endpoint?
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
✓
SageMaker Model and Endpoint Configuration
To create a SageMaker endpoint, you must first create a SageMaker Model (which points to the model artifact in S3 and the inference code) and then create an Endpoint Configuration (which specifies the model variant, instance type, and initial instance count). These are done using the SageMaker Model and Endpoint Configuration services. AWS Lambda, CloudFormation, and ECS are not directly used for creating the endpoint; they could be part of deployment automation but are not required.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
SageMaker Model and Endpoint Configuration
Why this is correct
You create a Model, then EndpointConfig, then Endpoint.
- ✗
AWS Lambda
Why it's wrong here
Lambda is not used to create SageMaker endpoints.
- ✗
AWS CloudFormation
Why it's wrong here
CloudFormation can deploy SageMaker resources but is not the direct service.
- ✗
Amazon ECS
Why it's wrong here
ECS is for container orchestration, not SageMaker endpoints.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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