Question 916 of 1,672
MLS-C01 Practice Question: Machine Learning Implementation and Operations
A data scientist is training a model using Amazon SageMaker. The training dataset is 500 GB and is stored in S3. The data scientist wants to use Pipe input mode to stream data directly from S3 to the training container. However, the training job fails with an error indicating that the container cannot read the data. What is the most likely cause?
⚠ Common exam trap
It's easy for candidates to confuse Pipe mode with File mode and assume all algorithms can use Pipe mode, but SageMaker explicitly requires the algorithm to support streaming input, and many custom containers do not.
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 training algorithm does not support Pipe mode
Pipe mode in SageMaker streams data directly from S3 to the training container via a FIFO pipe, but the training algorithm must be specifically designed to read from a pipe (e.g., via stdin or a named pipe). If the algorithm expects random access to files or uses libraries that require seekable file handles (like many image-processing or custom Python scripts using `open()`), it will fail because a pipe is a sequential, non-seekable stream. SageMaker’s built-in algorithms like BlazingText and XGBoost support Pipe mode, but custom algorithms often do not unless explicitly coded for it.
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 training instance does not have enough memory
Why it's wrong here
Pipe mode streams data, memory is not the direct issue.
- ✗
The IAM role does not have s3:GetObject permission
Why it's wrong here
If permissions are missing, that would be the error, but the error indicates reading issue.
- ✗
The data is compressed and Pipe mode cannot handle compressed data
Why it's wrong here
Pipe mode can handle compressed data.
- ✗
The S3 bucket is in a different Region
Why it's wrong here
Cross-region access is possible.
- ✓
The training algorithm does not support Pipe mode
Why this is correct
Not all algorithms support Pipe input; they need to read from a pipe.
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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Last reviewed: Jul 4, 2026
This MLS-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 MLS-C01 exam.
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