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MLA-C01 Practice Question: A machine learning team deploys a custom…
A machine learning team deploys a custom container image for an Amazon SageMaker training job. The container needs to access an S3 bucket that contains sensitive data. The team wants to follow the principle of least privilege. How should the team grant access?
⚠ Common exam trap
Candidates often confuse SageMaker's execution role mechanism with EC2 instance profiles, assuming you can attach an IAM role directly to the underlying instance, but SageMaker abstracts instance management and only supports execution roles for granting permissions.
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
✓
Create an IAM role with S3 access and assign it as the SageMaker execution role for the training job.
SageMaker training jobs use an IAM execution role to grant permissions to AWS services like S3. By creating a dedicated IAM role with only the necessary S3 actions (e.g., s3:GetObject, s3:PutObject) and assigning it as the SageMaker execution role, the team follows the principle of least privilege. SageMaker automatically assumes this role via AWS Security Token Service (STS) to access the S3 bucket on behalf of the container, without embedding credentials.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Create an IAM role with S3 access and assign it as the SageMaker execution role for the training job.
Why this is correct
This is the standard secure method.
- ✗
Attach an IAM instance profile to the training instance with permissions to the bucket.
Why it's wrong here
SageMaker training jobs don't use instance profiles; they use execution roles.
- ✗
Configure an S3 bucket policy that grants access to the training job's ARN.
Why it's wrong here
SageMaker training jobs don't have ARNs that can be used in bucket policies; roles are used.
- ✗
Store AWS access keys in the container image and use them to access the bucket.
Why it's wrong here
Hardcoding credentials is insecure and against best practices.
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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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLA-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 MLA-C01 exam.