MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
A machine learning engineer is setting up a retraining pipeline that triggers when concept drift is detected. They plan to use CloudWatch Alarms to monitor the model's accuracy metric. When drift is detected, they want to automatically start a SageMaker training job. Which architecture should they use?
⚠ Common exam trap
Candidates often assume CloudWatch Alarms can directly trigger Lambda or SageMaker, but AWS documentation explicitly limits alarm actions to SNS, Auto Scaling, EC2, and Systems Manager, requiring an intermediary like SNS for Lambda invocation.
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 Alarm → SNS → Lambda → SageMaker Training Job
CloudWatch Alarms cannot directly invoke SageMaker training jobs; they require an intermediary like SNS to trigger a Lambda function, which then calls the SageMaker API to start the training job. This pattern ensures reliable decoupling and allows the Lambda function to handle any preprocessing or conditional logic before launching the job.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
CloudWatch Alarm → SQS → Lambda → SageMaker Training Job
Why it's wrong here
SQS (queue) is unnecessary; SNS is the standard target for CloudWatch Alarms to trigger actions.
- ✗
CloudWatch Alarm → EventBridge → SageMaker Training Job
Why it's wrong here
EventBridge cannot directly invoke a SageMaker training job; it requires a Lambda or Step Functions target.
- ✓
CloudWatch Alarm → SNS → Lambda → SageMaker Training Job
Why this is correct
This architecture allows the alarm to trigger a notification, which Lambda processes to start a training job.
- ✗
CloudWatch Alarm → Lambda directly (without SNS)
Why it's wrong here
CloudWatch Alarms cannot directly invoke Lambda; they must go through SNS or another service.
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.