hardMultiple ChoiceObjective-mapped
MLA-C01 Practice Question: A company deploys a model using SageMaker and…
A company deploys a model using SageMaker and enables data capture for monitoring. After a week, they notice that the captured data is not being written to the specified S3 bucket. The endpoint is running and invocations are successful. What is the most likely cause?
⚠ Common exam trap
Many candidates assume data capture fails due to endpoint misconfiguration (like missing CaptureOptions) or regional restrictions, when in fact the root cause is almost always an IAM permissions issue with the S3 bucket.
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
✓
The IAM role used for the endpoint does not have s3:PutObject permission for the capture bucket.
The most likely cause is that the IAM role associated with the SageMaker endpoint lacks the `s3:PutObject` permission for the target S3 bucket. Without this permission, the endpoint cannot write the captured inference data to S3, even though invocations succeed because the model itself does not require S3 write access to serve predictions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The IAM role used for the endpoint does not have s3:PutObject permission for the capture bucket.
Why this is correct
Without write permission, data capture fails silently.
- ✗
The capture bucket is in a different region.
Why it's wrong here
Cross-region capture is possible with proper permissions and bucket policy.
- ✗
The endpoint is using a multi-model endpoint which does not support data capture.
Why it's wrong here
Multi-model endpoints do support data capture.
- ✗
The DataCaptureConfig parameter in the endpoint configuration is missing the "CaptureOptions" field.
Why it's wrong here
Missing CaptureOptions would cause an error during endpoint creation, not silent failure.
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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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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