- A
AWS Step Functions
Step Functions orchestrates the retraining pipeline.
- B
AWS Lambda
Lambda can evaluate model performance metrics and decide to start the retraining.
- C
Amazon EventBridge
EventBridge can listen for S3 events to trigger the workflow.
- D
Amazon CloudWatch Logs
Why wrong: CloudWatch Logs is for log storage, not for triggering workflows based on new data.
- E
SageMaker Model Registry
Why wrong: Model Registry manages model versions but does not trigger retraining based on performance degradation.
Question 932 of 1,000
Event-Driven Model Retraining with Step Functions, Lambda, and EventBridge
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.
A company is using AWS Step Functions to orchestrate their ML retraining pipeline. They want to trigger retraining when new data arrives, but only if the model's performance has degraded below a threshold. Which THREE AWS services should they use together to achieve this? (Choose 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
✓
AWS Step Functions
A solution: Amazon EventBridge detects S3 events (new data), invokes a Lambda function that checks model performance (e.g., via SageMaker Model Monitor or custom metrics), and then starts a Step Functions workflow if degradation is detected. The other services: SageMaker Pipelines could replace Step Functions but is not listed as an option; SageMaker Model Monitor can track performance but is not an event source; CloudWatch Logs is not directly involved in the trigger logic.
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.
- ✓
AWS Step Functions
Why this is correct
Step Functions orchestrates the retraining pipeline.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
AWS Lambda
Why this is correct
Lambda can evaluate model performance metrics and decide to start the retraining.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Amazon EventBridge
Why this is correct
EventBridge can listen for S3 events to trigger the workflow.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon CloudWatch Logs
Why it's wrong here
CloudWatch Logs is for log storage, not for triggering workflows based on new data.
- ✗
SageMaker Model Registry
Why it's wrong here
Model Registry manages model versions but does not trigger retraining based on performance degradation.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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.
- →
Deployment and Orchestration of ML Workflows — study guide chapter
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Deployment and Orchestration of ML Workflows practice questions
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AWS Certified Machine Learning Engineer Associate MLA-C01 study guide
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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: AWS Step Functions — A solution: Amazon EventBridge detects S3 events (new data), invokes a Lambda function that checks model performance (e.g., via SageMaker Model Monitor or custom metrics), and then starts a Step Functions workflow if degradation is detected. The other services: SageMaker Pipelines could replace Step Functions but is not listed as an option; SageMaker Model Monitor can track performance but is not an event source; CloudWatch Logs is not directly involved in the trigger logic.
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 →
Same concept, more angles
1 more ways this is tested on MLA-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company wants to trigger a model retraining pipeline whenever new training data arrives in an S3 bucket. They also need to send a notification to a Slack channel when the retraining completes. Which TWO AWS services should they use to implement this event-driven workflow? (Select TWO.)
easy- A.Amazon SQS
- ✓ B.AWS Lambda
- C.AWS CloudTrail
- ✓ D.Amazon EventBridge
- E.SageMaker Model Registry
Why B: AWS Lambda is correct because it can be triggered directly by S3 events (e.g., s3:ObjectCreated) to invoke the model retraining pipeline. Amazon EventBridge is correct because it can capture completion events from the retraining pipeline (e.g., SageMaker training job state changes) and route them to a target like a Slack webhook via Lambda or SNS, enabling the notification workflow.
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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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