- A
CloudWatch Alarm → SQS → Lambda → SageMaker Training Job
Why wrong: SQS (queue) is unnecessary; SNS is the standard target for CloudWatch Alarms to trigger actions.
- B
CloudWatch Alarm → EventBridge → SageMaker Training Job
Why wrong: EventBridge cannot directly invoke a SageMaker training job; it requires a Lambda or Step Functions target.
- C
CloudWatch Alarm → SNS → Lambda → SageMaker Training Job
This architecture allows the alarm to trigger a notification, which Lambda processes to start a training job.
- D
CloudWatch Alarm → Lambda directly (without SNS)
Why wrong: CloudWatch Alarms cannot directly invoke Lambda; they must go through SNS or another service.
Question 560 of 1,000
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. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 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?
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
Option C is correct because 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.
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.
- ✗
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.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
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.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates 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.
Detailed technical explanation
How to think about this question
Under the hood, CloudWatch Alarms use a state machine that transitions between OK, ALARM, and INSUFFICIENT_DATA states; when entering ALARM, they publish to an SNS topic, which then fans out to subscribed endpoints like Lambda. The Lambda function receives the alarm payload (including metric name, threshold, and new state) and uses the boto3 SageMaker client to call `create_training_job` with the appropriate hyperparameters and data source. A real-world scenario might involve monitoring a production model's accuracy dropping below 0.85, triggering a retraining job with fresh data from S3, where the Lambda function also logs the drift event to CloudWatch Logs for audit trails.
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.
TExam Day Tips
- 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 exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
- →
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: CloudWatch Alarm → SNS → Lambda → SageMaker Training Job — Option C is correct because 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.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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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