The correct answer is to use HTTPS endpoints for invoking the SageMaker model and to configure the SageMaker notebook instance to use a KMS key for encryption at rest. HTTPS ensures encryption in transit by leveraging TLS, which protects model artifacts as they travel between clients and the endpoint, while a KMS key encrypts the EBS storage volume attached to the notebook instance, securing artifacts at rest during development. On the AWS Certified Machine Learning Engineer Associate MLA-C01 exam, this question tests your understanding of the shared responsibility model within SageMaker pipelines, often appearing as a two-part security scenario where you must distinguish between encryption at rest (storage-level) and in transit (network-level). A common trap is selecting S3 server-side encryption alone, which only covers storage, not the notebook’s ephemeral volumes. Memory tip: think “TLS for travel, KMS for keep”—HTTPS secures data moving, KMS secures data staying.
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. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 building a CI/CD pipeline for model deployment using Amazon SageMaker. They need to ensure that all model artifacts are encrypted at rest and in transit, and that access to the models is controlled via IAM. Which TWO actions should the team take to meet these requirements? (Choose TWO.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Configure the SageMaker notebook instance to use a KMS key for encryption
Option D is correct because configuring a SageMaker notebook instance to use a KMS key ensures that data at rest on the notebook's storage volume (e.g., EBS) is encrypted. This directly addresses the requirement for encryption at rest for model artifacts during development. Option E is correct because using HTTPS endpoints for invoking the SageMaker model ensures encryption in transit via TLS, protecting data as it moves between clients and the model endpoint.
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 SageMaker model's 'EnableNetworkIsolation' parameter to true
Why it's wrong here
Network isolation restricts internet access, not encryption.
✗
Enable default encryption on the S3 bucket that stores model artifacts
Why it's wrong here
Default encryption is SSE-S3, not KMS; KMS is needed for customer-managed keys.
✗
Enable AWS CloudTrail to log all API calls to SageMaker
Why it's wrong here
CloudTrail provides auditing, not encryption.
✓
Configure the SageMaker notebook instance to use a KMS key for encryption
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 confuse network isolation (Option A) with encryption or access control, or they assume S3 default encryption (Option B) alone satisfies all encryption requirements, ignoring the need for encryption in transit and IAM-based access control for the models themselves.
Detailed technical explanation
How to think about this question
Under the hood, SageMaker notebook instances use EBS volumes for storage; attaching a KMS key encrypts these volumes using AES-256 encryption, ensuring data at rest is protected even if the volume is detached or snapshotted. For encryption in transit, SageMaker endpoints support HTTPS using TLS 1.2, which encrypts the payload between the client and the endpoint; this is enforced by the SageMaker API, which rejects non-HTTPS requests. In a real-world scenario, a financial services team might use a customer-managed KMS key to meet compliance requirements like PCI-DSS, and enforce HTTPS to prevent man-in-the-middle attacks during real-time inference.
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.
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: Configure the SageMaker notebook instance to use a KMS key for encryption — Option D is correct because configuring a SageMaker notebook instance to use a KMS key ensures that data at rest on the notebook's storage volume (e.g., EBS) is encrypted. This directly addresses the requirement for encryption at rest for model artifacts during development. Option E is correct because using HTTPS endpoints for invoking the SageMaker model ensures encryption in transit via TLS, protecting data as it moves between clients and the model endpoint.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.