- A
Enable SageMaker Data Capture on the endpoint
Data Capture logs requests and responses to S3 automatically.
- B
Add a custom Lambda function using a container
Why wrong: Lambda is not needed; Data Capture is built-in and simpler.
- C
Use SageMaker Debugger to monitor inference
Why wrong: Debugger is for training, not inference logging.
- D
Enable CloudTrail for the endpoint
Why wrong: CloudTrail logs API calls, not inference payloads.
Question 5 of 1,000
MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
This MLA-C01 practice question tests your understanding of deployment and orchestration of ml workflows. 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 team needs to deploy a model that has compliance requirements to log all inference requests and responses for auditing. The model will be served using a real-time endpoint. How can they achieve this without custom code?
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 SageMaker Data Capture on the endpoint
SageMaker Data Capture is the native, no-code feature that automatically logs inference requests and responses for real-time endpoints. It captures payload data to an S3 bucket without requiring any custom code, directly meeting the compliance requirement for audit logging.
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 SageMaker Data Capture on the endpoint
Why this is correct
Data Capture logs requests and responses to S3 automatically.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Add a custom Lambda function using a container
Why it's wrong here
Lambda is not needed; Data Capture is built-in and simpler.
- ✗
Use SageMaker Debugger to monitor inference
Why it's wrong here
Debugger is for training, not inference logging.
- ✗
Enable CloudTrail for the endpoint
Why it's wrong here
CloudTrail logs API calls, not inference payloads.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse CloudTrail (which logs API calls) with Data Capture (which logs payloads), or they assume Debugger can be repurposed for inference logging, but Debugger only works during training.
Detailed technical explanation
How to think about this question
When Data Capture is enabled on a real-time endpoint, SageMaker automatically captures a configurable percentage of inference requests and responses, storing them as JSON Lines files in a specified S3 bucket. This feature integrates with SageMaker Model Monitor to detect data drift and can be used with AWS Athena or Glue for querying audit logs. The capture includes metadata like timestamps and model variants, ensuring a complete audit trail without any custom code.
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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
Deployment and Orchestration of ML Workflows — This question tests Deployment and Orchestration of ML Workflows — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable SageMaker Data Capture on the endpoint — SageMaker Data Capture is the native, no-code feature that automatically logs inference requests and responses for real-time endpoints. It captures payload data to an S3 bucket without requiring any custom code, directly meeting the compliance requirement for audit logging.
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
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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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