The answer is that the container’s user lacks write permission to /opt/ml/model. This is the likely cause because SageMaker mounts the /opt/ml/model directory as a writable location where the training script must save the final model artifact; if the Docker container runs under a non-root user that does not have write access to that directory, the script will fail with a 'Permission denied' error even though it runs locally. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of SageMaker’s custom container contract and filesystem permissions—a common trap is assuming the error stems from missing dependencies or network issues, but the core concept is that SageMaker expects the container to write to /opt/ml/model, and the container’s user must have the necessary permissions. To remember this, think: “Model goes to /opt/ml/model—if your user can’t write there, you’ll get a permission scare.”
MLS-C01 Practice Question: Machine Learning Implementation and Operations
This MLS-C01 practice question tests your understanding of machine learning implementation and operations. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A machine learning team is using SageMaker to train a model with a custom Docker container. The training script runs locally but fails on SageMaker with a 'Permission denied' error when writing to /opt/ml/model. What is the likely cause?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The container's user does not have write permission to /opt/ml/model
SageMaker expects the container to write the model artifact to /opt/ml/model. If the user in the container lacks write permissions, it fails. Option C is correct. Option A is unrelated. Option B would cause different errors. Option D is about reading data.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 container's user does not have write permission to /opt/ml/model
Why this is correct
SageMaker mounts /opt/ml/model as a volume; the user must have write access.
Related concept
Read the scenario before looking for a memorised answer.
✗
The Docker image is too large
Why it's wrong here
Image size limits cause push or pull errors, not permission denied during training.
✗
The training script is trying to read from /opt/ml/input/data instead of /opt/ml/input/data/training
Why it's wrong here
Reading from wrong path would cause file not found, not permission denied.
✗
The training data is not in the correct S3 bucket
Why it's wrong here
Data access issues cause different errors, not permission denied on /opt/ml.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Machine Learning Implementation and Operations — This question tests Machine Learning Implementation and Operations — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The container's user does not have write permission to /opt/ml/model — SageMaker expects the container to write the model artifact to /opt/ml/model. If the user in the container lacks write permissions, it fails. Option C is correct. Option A is unrelated. Option B would cause different errors. Option D is about reading data.
What should I do if I get this MLS-C01 question wrong?
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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