MLA-C01 Practice Question: Refer to the exhibit

Network Topology

Refer to the exhibit. A team has configured data capture for a SageMaker endpoint. The endpoint is returning predictions but no captured data appears in the S3 bucket. What is the most likely cause?

⚠ Common exam trap

The trap here is that candidates often focus on sampling percentages or traffic volume, but the core issue is almost always an IAM permissions misconfiguration when predictions succeed but data capture fails silently.

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 for the endpoint does not have s3:PutObject permission.

The most likely cause is that the IAM role associated with the SageMaker endpoint lacks the `s3:PutObject` permission. Without this permission, the endpoint can generate capture data internally but cannot write it to the specified S3 bucket, resulting in no captured data appearing even though predictions are returned successfully.

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 InitialSamplingPercentage is too low.
Why it's wrong here
A low InitialSamplingPercentage reduces captured request volume but still records some data, so it cannot produce an entirely empty S3 bucket. It is tempting because sampling genuinely governs capture volume, and would be correct if captures appeared but were sparser than expected.
✓
The IAM role for the endpoint does not have s3:PutObject permission.
Why this is correct
Without s3:PutObject on the endpoint's execution role, SageMaker cannot write captured inference records to the target bucket, so requests succeed while capture silently fails. The stem's constraint is predictions returning normally yet no objects landing in S3, which isolates the fault to the write permission rather than the capture configuration itself.
✗
The capture status is 'Configured' but not 'Running'.
Why it's wrong here
A 'Configured' status means capture settings exist but are not active, so no data is written; the endpoint still serves predictions. It is tempting because configuration is the prerequisite step, and it would be the answer if capture had never been set up rather than left unstarted.
✗
The endpoint is not receiving any traffic.
Why it's wrong here
Zero traffic would mean no inferences to capture, but the stem states the endpoint returns predictions, so requests are arriving. It is tempting because idle endpoints genuinely produce no captured data, and it would be correct if the endpoint had received no invocations at all.

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

Go deeper

MLA-C01 Practice Question: Refer to the exhibit

Why each option matters

Option-by-option breakdown

AWS S3 Storage Class Comparison

Related to this question