- A
Enable SageMaker endpoint data capture to the S3 bucket.
Data capture is built-in and efficient.
- B
Configure CloudWatch Logs to export to S3.
Why wrong: CloudWatch Logs is for logs, not prediction data.
- C
Modify the inference code to write logs to S3.
Why wrong: Custom code requires maintenance and adds latency.
- D
Use Amazon Kinesis Data Firehose to stream predictions to S3.
Why wrong: Firehose adds unnecessary complexity for simple logging.
Question 922 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. 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 model deployed on a SageMaker endpoint is returning predictions. The team wants to log all predictions to an S3 bucket for auditing. What is the most efficient way to achieve this?
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 endpoint data capture to the S3 bucket.
SageMaker endpoint data capture is the native, most efficient way to log predictions to S3 because it automatically captures input payloads and output predictions for all requests to the endpoint, storing them directly in the specified S3 bucket without any custom code or additional infrastructure. This feature is designed specifically for auditing and monitoring, requiring only a DataCaptureConfig to be set on the 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.
- ✓
Enable SageMaker endpoint data capture to the S3 bucket.
Why this is correct
Data capture is built-in and efficient.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Configure CloudWatch Logs to export to S3.
Why it's wrong here
CloudWatch Logs is for logs, not prediction data.
- ✗
Modify the inference code to write logs to S3.
Why it's wrong here
Custom code requires maintenance and adds latency.
- ✗
Use Amazon Kinesis Data Firehose to stream predictions to S3.
Why it's wrong here
Firehose adds unnecessary complexity for simple logging.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates overcomplicate the solution by choosing a streaming or custom logging approach (like Kinesis or code modification), not realizing that SageMaker provides a built-in, zero-code feature (Data Capture) specifically designed for this auditing requirement.
Detailed technical explanation
How to think about this question
SageMaker data capture works by intercepting requests and responses at the endpoint level, serializing them as JSON lines, and writing them to S3 in a partitioned structure (e.g., s3://bucket/prefix/yyyy/mm/dd/hh/). It supports sampling (e.g., 0-100% of requests) and can capture both input and output, making it ideal for compliance audits. A subtle behavior is that data capture is asynchronous—it does not block inference—so it has no impact on endpoint latency, but captured data may take a few minutes to appear in S3.
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: Enable SageMaker endpoint data capture to the S3 bucket. — SageMaker endpoint data capture is the native, most efficient way to log predictions to S3 because it automatically captures input payloads and output predictions for all requests to the endpoint, storing them directly in the specified S3 bucket without any custom code or additional infrastructure. This feature is designed specifically for auditing and monitoring, requiring only a DataCaptureConfig to be set on the 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.
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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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