MLS-C01 Practice Question: Machine Learning Implementation and Operations
A company uses Amazon SageMaker to train a model using a custom Docker container. The training job fails with an error: "Unable to write to /opt/ml/output/data". The data scientist checks the container and finds that the /opt/ml directory is not writable. What is the MOST likely cause?
⚠ Common exam trap
It's easy for candidates to confuse a permission error with a missing library or resource constraint, but the specific 'not writable' message directly points to filesystem permissions, not dependencies or memory.
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 container runs as a non-root user that lacks write permissions to /opt/ml.
The error 'Unable to write to /opt/ml/output/data' indicates a permission issue. By default, SageMaker training containers run as a non-root user (uid 1000) for security reasons. If the Docker image is built with /opt/ml owned by root and without world-writable permissions, the non-root user cannot write to that directory, causing the failure.
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 Docker image is built from a base image that does not have the required libraries.
Why it's wrong here
Missing libraries would cause import errors, not write permission errors.
- ✓
The container runs as a non-root user that lacks write permissions to /opt/ml.
Why this is correct
SageMaker mounts volumes as root by default; if the container runs as a different user, it may not have write access.
- ✗
The SageMaker training job is configured with insufficient memory.
Why it's wrong here
Insufficient memory would cause out-of-memory errors, not write permission errors.
- ✗
The training script is not copying the model to /opt/ml/model.
Why it's wrong here
The error is about writing to /opt/ml/output/data, not copying model.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.