MLS-C01 Practice Question: Machine Learning Implementation and Operations
A company wants to monitor a deployed model for data drift. Which AWS service should they use?
⚠ Common exam trap
Many candidates confuse SageMaker Clarify (bias/explainability) with Model Monitor (drift/quality), as both involve analyzing model behavior but serve fundamentally different purposes.
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
✓
Amazon SageMaker Model Monitor
Amazon SageMaker Model Monitor is the correct service because it is specifically designed to continuously monitor deployed machine learning models for data drift and quality issues. It automatically detects deviations in the input data distribution compared to a baseline, triggering alerts when drift exceeds defined thresholds, which directly addresses the company's requirement.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon SageMaker Ground Truth
Why it's wrong here
Ground Truth is for labeling data.
- ✗
Amazon CloudWatch Logs
Why it's wrong here
CloudWatch can monitor logs but not detect drift.
- ✗
Amazon SageMaker Clarify
Why it's wrong here
Clarify is for bias and explainability, not drift.
- ✓
Amazon SageMaker Model Monitor
Why this is correct
Model Monitor checks for data and model drift.
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