MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A company has deployed a machine learning model on Amazon SageMaker and wants to automatically detect when the distribution of input features deviates significantly from the training data distribution. Which SageMaker feature should they use?
⚠ Common exam trap
Candidates often confuse 'Data Quality Monitoring' with 'Model Quality Monitoring', mistakenly thinking that monitoring prediction accuracy covers input distribution drift, whereas Data Quality Monitoring is explicitly for input features and Model Quality Monitoring is for output predictions.
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
✓
SageMaker Model Monitor – Data Quality Monitoring
SageMaker Model Monitor – Data Quality Monitoring is the correct choice because it is specifically designed to detect deviations in the distribution of input features compared to the training data distribution. It continuously monitors incoming inference requests and compares statistical properties (e.g., mean, variance, or histogram) against a baseline computed from the training dataset, alerting when drift is detected.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
SageMaker Clarify
Why it's wrong here
SageMaker Clarify is used for bias detection and explainability, not data drift detection.
- ✗
SageMaker Edge Manager
Why it's wrong here
Edge Manager is for managing models on edge devices, not for monitoring data drift.
- ✗
SageMaker Model Monitor – Model Quality Monitoring
Why it's wrong here
Model quality monitoring tracks prediction accuracy against ground truth, not input data drift.
- ✓
SageMaker Model Monitor – Data Quality Monitoring
Why this is correct
Data quality monitoring detects schema drift and statistical drift by comparing live data to a baseline.
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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.