MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A company wants to implement a retraining pipeline that automatically triggers when SageMaker Model Monitor detects data drift. The retraining job should use the latest approved pipeline version in SageMaker Pipelines. Which approach meets these requirements?
⚠ Common exam trap
Many exam-takers think SageMaker Model Monitor can directly invoke Lambda or update the model registry, but in reality, it only emits events to EventBridge, and the integration requires an intermediate Lambda function to orchestrate the pipeline execution.
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
✓
Create an EventBridge rule that listens for SageMaker Model Monitor violation events and triggers a Lambda function that starts the pipeline
It uses an EventBridge rule to listen for SageMaker Model Monitor violation events (e.g., `aws.sagemaker.model-monitoring-violation`), which then triggers a Lambda function that starts the latest approved pipeline version in SageMaker Pipelines. This creates an automated, event-driven retraining pipeline without manual intervention or scheduled polling.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a scheduled EventBridge rule to run the pipeline every day
Why it's wrong here
Scheduled retraining does not respond to drift events; it runs on a fixed schedule regardless of drift.
- ✗
Use SageMaker Model Monitor to update the model registry and trigger a deployment
Why it's wrong here
Model Monitor does not update the model registry or trigger deployments; it only monitors and outputs violations.
- ✗
Configure SageMaker Model Monitor to directly invoke a Lambda function on violation
Why it's wrong here
SageMaker Model Monitor does not directly invoke Lambda; it publishes violations to CloudWatch, which can trigger an alarm or event.
- ✓
Create an EventBridge rule that listens for SageMaker Model Monitor violation events and triggers a Lambda function that starts the pipeline
Why this is correct
Model Monitor violations are captured as CloudWatch events; EventBridge can route those events to a Lambda function that starts the retraining pipeline.
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 |
Go deeper
Related to this question
About these practice questions
Courseiva writes every MLA-C01 question from scratch — 835 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
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.