Quick Answer
AWS Step Functions is the correct choice because it orchestrates the automated deployment workflow triggered by a SageMaker Model Registry approval event. Step Functions natively integrates with SageMaker via its service integrations, allowing you to chain approval checks, model creation, and endpoint deployment without writing custom glue code. On the AWS Certified Machine Learning Engineer Associate MLA-C01 exam, this scenario tests your understanding of event-driven MLOps pipelines—specifically how to automate model deployment from SageMaker Model Registry approval using a state machine that listens for model version state changes. A common trap is choosing Amazon EventBridge alone, but EventBridge only routes the event; Step Functions provides the orchestration logic to call SageMaker APIs for creating models and updating endpoints. Remember the memory tip: “EventBridge triggers the bell, but Step Functions rings the whole tune.”
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 ML team uses SageMaker Model Registry to manage model versions. They want to automatically deploy a model to a staging endpoint when a new version is approved. Which AWS service can orchestrate this?
Amazon EventBridge
Why wrong: EventBridge can trigger actions but lacks complex workflow orchestration with approval steps.
AWS Lambda
Why wrong: Lambda is for single-purpose functions, not multi-step workflows.
SageMaker Pipelines
Why wrong: Pipelines are for training workflows, not for approval-driven deployment.
AWS Step Functions
Step Functions can coordinate multiple steps including approval and deployment.
Answer choices
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
AWS Step Functions is the correct choice because it can orchestrate a workflow that triggers on a Model Registry event (e.g., model version approval) and then deploys the model to a staging endpoint using SageMaker SDK calls. Step Functions provides built-in integration with SageMaker via service integrations, allowing you to chain approval checks, model creation, and endpoint deployment without custom code.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Amazon EventBridge
Why it's wrong here
EventBridge can trigger actions but lacks complex workflow orchestration with approval steps.
AWS Lambda
Why it's wrong here
Lambda is for single-purpose functions, not multi-step workflows.
SageMaker Pipelines
Why it's wrong here
Pipelines are for training workflows, not for approval-driven deployment.
AWS Step Functions
Why this is correct
Step Functions can coordinate multiple steps including approval and deployment.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates often pick SageMaker Pipelines (Option C) because it is associated with model workflows, but Pipelines is for training and registration, not for post-approval deployment orchestration, which requires a state machine like Step Functions.
Detailed technical explanation
Step Functions uses Amazon States Language (ASL) to define state machines that can call SageMaker APIs directly (e.g., CreateModel, CreateEndpointConfig, CreateEndpoint) via service integrations. A common pattern is to use EventBridge to detect the ModelRegistryStateChange event (status: Approved) and route it to a Step Functions execution, which then handles the deployment with built-in error handling and rollback logic. In production, you might also include a canary deployment step or integration with CloudWatch alarms to validate the staging endpoint before promoting to production.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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.
What to study next
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FAQ
Deployment and Orchestration of ML Workflows — This question tests Deployment and Orchestration of ML Workflows — Read the scenario before looking for a memorised answer..
The correct answer is: AWS Step Functions — AWS Step Functions is the correct choice because it can orchestrate a workflow that triggers on a Model Registry event (e.g., model version approval) and then deploys the model to a staging endpoint using SageMaker SDK calls. Step Functions provides built-in integration with SageMaker via service integrations, allowing you to chain approval checks, model creation, and endpoint deployment without custom code.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 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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