- A
Enable AWS CloudTrail for SageMaker Feature Store API calls.
CloudTrail logs all API calls, providing an audit trail for changes.
- B
Use SageMaker Feature Store offline store with record identifier and event time.
Why wrong: This helps with time-based queries but does not inherently log definition changes.
- C
Enable feature group versioning to track changes to feature definitions.
Versioning tracks changes and provides immutability for definitions.
- D
Implement feature store online store with TTL to automatically expire data.
Why wrong: TTL manages data lifecycle, not immutability or change logging.
- E
Use AWS Config to track changes to Feature Store resources.
Why wrong: Config tracks resource configurations, not specific feature definition changes.
AIF-C01 Practice Question: Security, Compliance and Governance for AI Solutions
This AIF-C01 practice question tests your understanding of security, compliance and governance for ai solutions. 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 financial services company uses Amazon SageMaker Feature Store to manage features for machine learning models. The compliance auditor requires that all changes to feature definitions are logged and that feature data is immutable once written. Which TWO approaches should the team implement? (Choose two.)
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
Enable AWS CloudTrail for SageMaker Feature Store API calls.
Option A is correct because enabling AWS CloudTrail for SageMaker Feature Store API calls provides a detailed audit log of all operations, including changes to feature definitions (e.g., CreateFeatureGroup, UpdateFeatureGroup). This satisfies the compliance requirement for logging all changes. Option C is correct because enabling feature group versioning in SageMaker Feature Store allows you to track and manage changes to feature definitions over time, ensuring a historical record of modifications.
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.
- ✓
Enable AWS CloudTrail for SageMaker Feature Store API calls.
Why this is correct
CloudTrail logs all API calls, providing an audit trail for changes.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use SageMaker Feature Store offline store with record identifier and event time.
Why it's wrong here
This helps with time-based queries but does not inherently log definition changes.
- ✓
Enable feature group versioning to track changes to feature definitions.
Why this is correct
Versioning tracks changes and provides immutability for definitions.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Implement feature store online store with TTL to automatically expire data.
Why it's wrong here
TTL manages data lifecycle, not immutability or change logging.
- ✗
Use AWS Config to track changes to Feature Store resources.
Why it's wrong here
Config tracks resource configurations, not specific feature definition changes.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse AWS Config (which tracks resource configuration changes) with AWS CloudTrail (which logs API calls), or they mistakenly think the offline store's point-in-time query capability inherently enforces data immutability, when in fact immutability requires explicit design choices.
Detailed technical explanation
How to think about this question
Under the hood, SageMaker Feature Store's offline store uses an S3 bucket and an AWS Glue Data Catalog, where data is stored in Parquet format partitioned by event time. Immutability in this context means that once a feature record is written with a specific record identifier and event time, it should never be overwritten or deleted; this is typically enforced by application logic or by using append-only writes. Feature group versioning creates a new version of the feature group definition each time you update it, preserving the schema and metadata history, which is separate from the data immutability requirement.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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.
- →
Security, Compliance and Governance for AI Solutions — study guide chapter
Learn the concepts, then practise the questions
- →
Security, Compliance and Governance for AI Solutions practice questions
Targeted practice on this topic area only
- →
All AIF-C01 questions
500 questions across all exam domains
- →
AWS Certified AI Practitioner AIF-C01 study guide
Full concept coverage aligned to exam objectives
- →
AIF-C01 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related AIF-C01 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Applications of Foundation Models practice questions
Practise AIF-C01 questions linked to Applications of Foundation Models.
Fundamentals of AI and ML practice questions
Practise AIF-C01 questions linked to Fundamentals of AI and ML.
Fundamentals of Generative AI practice questions
Practise AIF-C01 questions linked to Fundamentals of Generative AI.
Guidelines for Responsible AI practice questions
Practise AIF-C01 questions linked to Guidelines for Responsible AI.
Security, Compliance and Governance for AI Solutions practice questions
Practise AIF-C01 questions linked to Security, Compliance and Governance for AI Solutions.
AIF-C01 fundamentals practice questions
Practise AIF-C01 questions linked to AIF-C01 fundamentals.
AIF-C01 scenario practice questions
Practise AIF-C01 questions linked to AIF-C01 scenario.
AIF-C01 troubleshooting practice questions
Practise AIF-C01 questions linked to AIF-C01 troubleshooting.
Practice this exam
Start a free AIF-C01 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this AIF-C01 question test?
Security, Compliance and Governance for AI Solutions — This question tests Security, Compliance and Governance for AI Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable AWS CloudTrail for SageMaker Feature Store API calls. — Option A is correct because enabling AWS CloudTrail for SageMaker Feature Store API calls provides a detailed audit log of all operations, including changes to feature definitions (e.g., CreateFeatureGroup, UpdateFeatureGroup). This satisfies the compliance requirement for logging all changes. Option C is correct because enabling feature group versioning in SageMaker Feature Store allows you to track and manage changes to feature definitions over time, ensuring a historical record of modifications.
What should I do if I get this AIF-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 →
Last reviewed: Jun 25, 2026
This AIF-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 AIF-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.