- A
SageMaker (training jobs or pipelines)
SageMaker executes the actual retraining.
- B
Amazon EventBridge
EventBridge captures events such as new data arrival in S3.
- C
AWS Lambda
Lambda can process the event and trigger the retraining pipeline.
- D
AWS Glue
Why wrong: Glue is for ETL, not typically used for event-driven retraining triggers.
- E
Amazon CloudWatch Logs
Why wrong: CloudWatch Logs is for monitoring, not part of the event-driven trigger.
Question 724 of 1,000
MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
This MLA-C01 practice question tests your understanding of deployment and orchestration of ml workflows. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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.
An organization wants to automate ML retraining using an event-driven architecture. Which THREE services should they combine? (Select THREE.)
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
✓
SageMaker (training jobs or pipelines)
Amazon SageMaker provides the training jobs and pipelines that execute the ML retraining workflow. Amazon EventBridge acts as the event bus that triggers retraining based on events such as new data arrival or model drift detection. AWS Lambda serves as the lightweight compute layer that can preprocess events, invoke SageMaker APIs, or orchestrate conditional logic before starting a training 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.
- ✓
SageMaker (training jobs or pipelines)
Why this is correct
SageMaker executes the actual retraining.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Amazon EventBridge
Why this is correct
EventBridge captures events such as new data arrival in S3.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
AWS Lambda
Why this is correct
Lambda can process the event and trigger the retraining pipeline.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
AWS Glue
Why it's wrong here
Glue is for ETL, not typically used for event-driven retraining triggers.
- ✗
Amazon CloudWatch Logs
Why it's wrong here
CloudWatch Logs is for monitoring, not part of the event-driven trigger.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse AWS Glue as a compute trigger for ML retraining, but Glue is designed for batch ETL and lacks the event-driven, low-latency invocation capabilities required for this architecture.
Detailed technical explanation
How to think about this question
Under the hood, EventBridge uses a default event bus or custom rules to match events from sources like S3 (PutObject), and then routes them to targets such as Lambda functions or SageMaker Pipeline executions. The Lambda function can parse the event payload, validate conditions (e.g., file size, schema), and call the SageMaker CreateTrainingJob API with a boto3 client. A real-world scenario is a data lake where new CSV files land in S3 hourly; EventBridge detects the S3 event, triggers a Lambda that checks for a drift threshold in CloudWatch Metrics, and if exceeded, starts a SageMaker retraining pipeline.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
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.
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Deployment and Orchestration of ML Workflows — study guide chapter
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FAQ
Questions learners often ask
What does this MLA-C01 question test?
Deployment and Orchestration of ML Workflows — This question tests Deployment and Orchestration of ML Workflows — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: SageMaker (training jobs or pipelines) — Amazon SageMaker provides the training jobs and pipelines that execute the ML retraining workflow. Amazon EventBridge acts as the event bus that triggers retraining based on events such as new data arrival or model drift detection. AWS Lambda serves as the lightweight compute layer that can preprocess events, invoke SageMaker APIs, or orchestrate conditional logic before starting a training 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
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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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