- A
Use SageMaker Model Monitor to directly invoke a SageMaker Pipeline when drift is detected
Why wrong: Model Monitor cannot directly invoke pipelines; it only publishes metrics and violations to CloudWatch.
- B
Use EventBridge to schedule retraining daily regardless of drift
Why wrong: Scheduled retraining does not react to drift events; it runs on a fixed schedule.
- C
Configure a CloudWatch Alarm on drift metric → SNS topic → Lambda function that starts the SageMaker Pipeline execution
This chain fully automates retraining on drift detection without manual intervention.
- D
Create an EventBridge rule that triggers on Model Monitor drift events to start the pipeline
Why wrong: Model Monitor does not emit custom events to EventBridge; it uses CloudWatch metrics/alarms.
MLA-C01 Practice Question: ML Solution Monitoring, Maintenance, and Security
This MLA-C01 practice question tests your understanding of ml solution monitoring, maintenance, and security. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A machine learning team uses SageMaker Pipelines and wants to automatically retrain a model when data drift is detected. They have set up Model Monitor to publish drift violations to CloudWatch. Which approach provides a COMPLETE serverless retraining pipeline triggered by drift detection?
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
Configure a CloudWatch Alarm on drift metric → SNS topic → Lambda function that starts the SageMaker Pipeline execution
The recommended pattern: CloudWatch Alarm triggers on drift metric → SNS message → Lambda function (receives SNS) → starts SageMaker Pipeline execution. EventBridge could also trigger on SNS events, but Lambda is simplest. EventBridge can schedule retraining but does not directly react to specific drift alarms. Step Functions would add unnecessary complexity.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 SageMaker Model Monitor to directly invoke a SageMaker Pipeline when drift is detected
Why it's wrong here
Model Monitor cannot directly invoke pipelines; it only publishes metrics and violations to CloudWatch.
- ✗
Use EventBridge to schedule retraining daily regardless of drift
Why it's wrong here
Scheduled retraining does not react to drift events; it runs on a fixed schedule.
- ✓
Configure a CloudWatch Alarm on drift metric → SNS topic → Lambda function that starts the SageMaker Pipeline execution
Why this is correct
This chain fully automates retraining on drift detection without manual intervention.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Create an EventBridge rule that triggers on Model Monitor drift events to start the pipeline
Why it's wrong here
Model Monitor does not emit custom events to EventBridge; it uses CloudWatch metrics/alarms.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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 |
What to study next
Got this wrong? Here's your next step.
Identify which MLA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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ML Solution Monitoring, Maintenance, and Security — study guide chapter
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
ML Solution Monitoring, Maintenance, and Security — This question tests ML Solution Monitoring, Maintenance, and Security — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Configure a CloudWatch Alarm on drift metric → SNS topic → Lambda function that starts the SageMaker Pipeline execution — The recommended pattern: CloudWatch Alarm triggers on drift metric → SNS message → Lambda function (receives SNS) → starts SageMaker Pipeline execution. EventBridge could also trigger on SNS events, but Lambda is simplest. EventBridge can schedule retraining but does not directly react to specific drift alarms. Step Functions would add unnecessary complexity.
What should I do if I get this MLA-C01 question wrong?
Identify which MLA-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jul 4, 2026
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.
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