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MLA-C01 Practice Question: A company uses SageMaker Pipelines to train and…
A company uses SageMaker Pipelines to train and register models. They want to automate the deployment of approved models from the model registry to a staging endpoint. Which service should they use to orchestrate the deployment workflow?
⚠ Common exam trap
AWS often tests the distinction between orchestration (Step Functions) and event routing (EventBridge) or CI/CD (CodePipeline), leading candidates to pick EventBridge because they confuse event-driven triggers with the need for sequential workflow coordination.
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
AWS Step Functions is the correct choice because it is a serverless orchestration service designed to coordinate multiple AWS services into flexible, event-driven workflows. For SageMaker Pipelines, Step Functions can trigger model deployment from the registry to a staging endpoint by chaining actions like invoking a Lambda function for approval checks, calling SageMaker's CreateEndpoint API, and handling rollback logic on failure.
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 can orchestrate SageMaker API calls and integrate with Model Registry.
- ✗
AWS CloudFormation
Why it's wrong here
CloudFormation is for infrastructure as code.
- ✗
Amazon EventBridge
Why it's wrong here
EventBridge triggers simple events, not complex workflows.
- ✗
AWS CodePipeline
Why it's wrong here
CodePipeline is for CI/CD of source code, not specific to ML model deployment workflows.
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 |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.