The answer is enabling AWS KMS encryption for the SageMaker notebook and training job, combined with an S3 bucket that has default encryption using AWS KMS. This configuration is required because it ensures end-to-end encryption for training data at rest and in transit: KMS provides envelope encryption for data stored within SageMaker and S3, while SageMaker automatically enforces TLS for data in transit when KMS is enabled, protecting sensitive customer data throughout the entire pipeline. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of how SageMaker integrates with KMS for both at-rest and in-transit encryption, often appearing as a scenario where a common trap is to assume that enabling encryption only on the S3 bucket is sufficient—but you must also explicitly enable KMS on the SageMaker notebook and training job to cover the SageMaker-managed infrastructure. A helpful memory tip is "KMS covers both sides: the notebook and the job for transit, the bucket for rest."
MLS-C01 Modeling Practice Question
This MLS-C01 practice question tests your understanding of modeling. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 company uses SageMaker to train a model that processes sensitive customer data. Due to compliance, the training data must be encrypted at rest and in transit, and the model artifacts must be stored in a secured S3 bucket with encryption. Which combination of actions is REQUIRED?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Enable AWS KMS encryption for the SageMaker notebook and training job, and use an S3 bucket with default encryption using AWS KMS
Option D is correct because it ensures end-to-end encryption: AWS KMS encryption for the SageMaker notebook and training job encrypts data in transit and at rest within the SageMaker environment, while an S3 bucket with default encryption using AWS KMS encrypts the training data and model artifacts at rest. This combination meets compliance requirements for encryption at rest and in transit, as KMS provides envelope encryption with customer-managed keys, and SageMaker automatically uses TLS for data in transit when KMS is enabled.
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.
✗
Store data in an S3 bucket with AWS CloudHSM integration
Why it's wrong here
CloudHSM integration is complex and not standard for SageMaker.
✗
Use an S3 bucket with SSE-S3 and enable SageMaker Internet-facing mode
Why it's wrong here
Internet-facing mode does not add encryption.
✗
Use an S3 bucket with default encryption (SSE-S3) and enable SSL for all connections
Why it's wrong here
SSE-S3 encrypts at rest but does not use KMS; SSL encrypts in transit. However, compliance may require KMS.
✓
Enable AWS KMS encryption for the SageMaker notebook and training job, and use an S3 bucket with default encryption using AWS KMS
Why this is correct
KMS encryption ensures encryption at rest and in transit for SageMaker and S3.
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 often assume SSE-S3 alone is sufficient for compliance, but it does not cover encryption in transit or SageMaker-specific encryption, and they overlook the requirement for KMS to encrypt the SageMaker environment itself.
Detailed technical explanation
How to think about this question
Under the hood, AWS KMS uses envelope encryption where a customer master key (CMK) encrypts data keys, which then encrypt the actual data; SageMaker integrates KMS to encrypt EBS volumes attached to notebook instances and training jobs, as well as data in transit via TLS. A subtle behavior is that when using KMS for S3 default encryption, SageMaker must have IAM permissions to use the KMS key, and the bucket policy must allow kms:Decrypt for the SageMaker execution role, which is often overlooked in real-world deployments.
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.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Modeling — This question tests Modeling — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable AWS KMS encryption for the SageMaker notebook and training job, and use an S3 bucket with default encryption using AWS KMS — Option D is correct because it ensures end-to-end encryption: AWS KMS encryption for the SageMaker notebook and training job encrypts data in transit and at rest within the SageMaker environment, while an S3 bucket with default encryption using AWS KMS encrypts the training data and model artifacts at rest. This combination meets compliance requirements for encryption at rest and in transit, as KMS provides envelope encryption with customer-managed keys, and SageMaker automatically uses TLS for data in transit when KMS is enabled.
What should I do if I get this MLS-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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Question Discussion
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