MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
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?
⚠ Common exam trap
Test-takers frequently 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.
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.
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.
- ✗
Add a custom Lambda function using a container
Why it's wrong here
Adding a custom Lambda function with a container introduces custom code, which directly violates the question’s explicit constraint to achieve logging “without custom code.” This option is tempting because Lambda container support is often used to package custom runtimes or dependencies for inference preprocessing; however, the requirement demands a no-code solution, so the correct approach would use an AWS service like CloudTrail or an endpoint-level logging configuration that captures requests and responses automatically, not a developer-written function.
- ✗
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.
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 |
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.