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MLA-C01 Practice Question: A data science team is using Amazon SageMaker to…
A data science team is using Amazon SageMaker to train and deploy a binary classification model. They want to continuously monitor the model for data drift in production. Which combination of AWS services and SageMaker features should they use to implement automated drift detection with minimal operational overhead?
⚠ Common exam trap
Many candidates confuse SageMaker Debugger (training debugging) with SageMaker Model Monitor (production drift detection), or they overcomplicate the solution by adding unnecessary services like Lambda or Config when the native integration with CloudWatch already provides automated alerting.
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 and Amazon CloudWatch
SageMaker Model Monitor is the native SageMaker feature designed specifically for continuously monitoring deployed models for data drift, bias drift, and feature attribution drift. It automatically captures inference requests and responses, computes statistics, and publishes metrics to Amazon CloudWatch, which can trigger alarms for drift detection. This combination provides automated drift detection with minimal operational overhead because it requires no custom infrastructure or manual scheduling.
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 Debugger and Amazon SNS
Why it's wrong here
SageMaker Debugger monitors training jobs, not inference.
- ✗
SageMaker Pipelines and AWS Lambda
Why it's wrong here
SageMaker Pipelines is a CI/CD service, not for monitoring.
- ✗
SageMaker Clarify and AWS Config
Why it's wrong here
SageMaker Clarify is for bias detection and explainability, not drift.
- ✓
SageMaker Model Monitor and Amazon CloudWatch
Why this is correct
SageMaker Model Monitor detects drift and sends metrics to CloudWatch for alerting.
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