MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A machine learning engineer needs to automatically retrain a model whenever SageMaker Model Monitor detects data drift. Which combination of services should be used to trigger the retraining pipeline?
⚠ Common exam trap
A common mix-up: candidates assume SageMaker Model Monitor can directly trigger retraining via EventBridge or Step Functions, but the exam expects the CloudWatch Alarms → SNS → Lambda chain because Model Monitor metrics are published to CloudWatch, not directly to EventBridge for retraining triggers.
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
✓
CloudWatch Alarms → SNS → Lambda → SageMaker Processing job
SageMaker Model Monitor publishes metrics to CloudWatch, and when data drift is detected, a CloudWatch Alarm triggers an SNS notification, which invokes a Lambda function to start a SageMaker Processing job for retraining. This architecture decouples monitoring from retraining and uses native AWS services for event-driven automation.
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 Ground Truth → Lambda → SageMaker Training job
Why it's wrong here
Ground Truth is for labeling, not drift detection.
- ✓
CloudWatch Alarms → SNS → Lambda → SageMaker Processing job
Why this is correct
Model Monitor publishes metrics to CloudWatch. A CloudWatch Alarm on drift metric triggers an SNS topic, which invokes a Lambda function that starts a SageMaker Processing job for retraining.
- ✗
SageMaker Model Monitor → EventBridge → Step Functions → SageMaker Training job
Why it's wrong here
Model Monitor does not directly emit events to EventBridge; it uses CloudWatch metrics.
- ✗
SageMaker Data Wrangler → SNS → SageMaker Training job
Why it's wrong here
Data Wrangler is for data preparation, not drift monitoring.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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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.