- A
Set the KMS key in the endpoint configuration's ProductionVariant
Why wrong: Endpoint configuration does not have a KMS key parameter for model encryption.
- B
Enable default encryption on the S3 bucket containing the model artifacts
Why wrong: Bucket encryption does not guarantee encryption during model deployment; SageMaker must use the key.
- C
Use SageMaker Studio's KMS integration
Why wrong: Studio encryption is for notebooks, not model artifacts.
- D
Set the KMS key when creating the model using the CreateModel API
The CreateModel API accepts a KMS key parameter to encrypt the model artifacts in S3 and at rest.
Question 321 of 1,000
MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
This MLA-C01 practice question tests your understanding of ml solution monitoring, maintenance, and security. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 engineer is deploying a model using a SageMaker endpoint and needs to ensure that the model artifacts are encrypted at rest using a customer-managed KMS key. Which configuration should they set?
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
✓
Set the KMS key when creating the model using the CreateModel API
Option D is correct because the `CreateModel` API in SageMaker accepts a `ModelKmsKeyId` parameter that specifies a customer-managed KMS key for encrypting the model artifacts at rest. This key is used when SageMaker copies the artifacts from S3 to the inference instance's Amazon EBS volume, ensuring encryption at rest. The other options either apply to different resources or do not control the encryption of the model artifacts themselves.
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.
- ✗
Set the KMS key in the endpoint configuration's ProductionVariant
Why it's wrong here
Endpoint configuration does not have a KMS key parameter for model encryption.
- ✗
Enable default encryption on the S3 bucket containing the model artifacts
Why it's wrong here
Bucket encryption does not guarantee encryption during model deployment; SageMaker must use the key.
- ✗
Use SageMaker Studio's KMS integration
Why it's wrong here
Studio encryption is for notebooks, not model artifacts.
- ✓
Set the KMS key when creating the model using the CreateModel API
Why this is correct
The CreateModel API accepts a KMS key parameter to encrypt the model artifacts in S3 and at rest.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse S3 bucket encryption (Option B) with model artifact encryption at rest on the endpoint, or they mistakenly think the endpoint configuration's `ProductionVariant` (Option A) can set a KMS key, when in fact the key is set at the model resource level.
Detailed technical explanation
How to think about this question
When you create a model with `CreateModel`, SageMaker copies the model artifacts from S3 to the inference instance's EBS volume. The `ModelKmsKeyId` you specify encrypts that EBS volume, and SageMaker uses the same key to decrypt the artifacts during loading. If you do not set a KMS key, SageMaker uses an AWS-managed key by default. A subtle behavior: if the S3 bucket uses SSE-KMS with a different key, SageMaker must have permission to decrypt using that S3 key before it can re-encrypt with the model's KMS key.
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.
TExam Day Tips
- 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.
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 |
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
ML Solution Monitoring, Maintenance, and Security — This question tests ML Solution Monitoring, Maintenance, and Security — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Set the KMS key when creating the model using the CreateModel API — Option D is correct because the `CreateModel` API in SageMaker accepts a `ModelKmsKeyId` parameter that specifies a customer-managed KMS key for encrypting the model artifacts at rest. This key is used when SageMaker copies the artifacts from S3 to the inference instance's Amazon EBS volume, ensuring encryption at rest. The other options either apply to different resources or do not control the encryption of the model artifacts themselves.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
This MLA-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 MLA-C01 exam.
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