MLA-C01 Practice Question: A machine learning engineer observes that a…

Exhibit

Refer to the exhibit.

```
Training Job Name: my-training-job
Status: Failed
Failure Reason: ClientError: Data download failed. Unable to locate credentials. Please configure your SageMaker Execution Role with the necessary permissions.
```
This is the output from `aws sagemaker describe-training-job --training-job-name my-training-job`.

A machine learning engineer observes that a SageMaker training job fails with the error shown in the exhibit. What is the most likely cause of the failure?

⚠ Common exam trap

It's easy for candidates to confuse an access-denied error with a VPC or region issue, but the specific error message 'AccessDenied' (or similar) directly points to an IAM permissions problem, not a network or configuration mismatch.

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 SageMaker execution role does not have an IAM policy that grants read access to the S3 bucket containing the training data.

The error shown in the exhibit is a standard SageMaker access-denied error, which occurs when the SageMaker execution role lacks the necessary IAM permissions to read the training data from the S3 bucket. SageMaker uses the execution role's IAM policy to determine access to S3 resources; without a policy granting s3:GetObject (and optionally s3:ListBucket) on the bucket and objects, the training job fails at the data-loading stage.

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 SageMaker execution role does not have an IAM policy that grants read access to the S3 bucket containing the training data.
Why this is correct
SageMaker training jobs assume an execution role whose IAM policy must permit s3:GetObject on the training data bucket. Without that read permission, the job cannot download the dataset and fails immediately, matching the access-denied error in the exhibit.
✗
The training data is stored in an unsupported format like Parquet.
Why it's wrong here
SageMaker's built-in algorithms and frameworks read Parquet natively, so an unsupported-format error would not surface this way. Format mismatches matter when a specific algorithm's training channel rejects the file type, which the exhibit's error does not indicate.
✗
The training job is using an incorrect AWS Region for the S3 bucket.
Why it's wrong here
SageMaker training jobs and S3 buckets can reside in different Regions; the job accesses S3 via its regional endpoint, so a Region mismatch alone does not produce this failure. Region selection is decisive when configuring cross-Region data access or endpoint quotas, not here.
✗
The VPC configuration prevents the training job from reaching the S3 bucket.
Why it's wrong here
A VPC-attached training job reaches S3 through an S3 gateway endpoint or NAT gateway; the exhibit's error would name a network timeout or endpoint failure, not the actual cause shown. VPC configuration is genuinely the culprit when a job in a private subnet lacks egress routing to S3.

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: A machine learning engineer observes that a…

Exhibit

Why each option matters

Option-by-option breakdown

AWS S3 Storage Class Comparison

Related to this question