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MLA-C01 Practice Question: An ML team uses AWS Step Functions to orchestrate…
An ML team uses AWS Step Functions to orchestrate a multi-step inference pipeline: data preprocessing, model inference, and postprocessing. The pipeline runs on demand for single records. The team notices that the pipeline occasionally fails due to timeouts in the preprocessing step. They want to implement retries with exponential backoff and a maximum retry count of 3 for that step. How should they configure this?
⚠ Common exam trap
Many exam-takers assume retry logic must be coded inside the Lambda function (Option A) or that a Catch block (Option D) is the correct way to handle failures, but Step Functions provides a declarative Retry mechanism that is more robust and easier to maintain for orchestrated workflows.
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
✓
Modify the Step Functions state machine definition to add a Retry field on the preprocessing state with a maximum retry count of 3 and an exponential backoff rate of 2.0.
AWS Step Functions natively supports retry logic with exponential backoff directly in the state machine definition. By adding a `Retry` field on the preprocessing state with `MaxAttempts: 3` and `BackoffRate: 2.0`, the service automatically retries the step on specified errors (e.g., `States.Timeout` or `Lambda.ServiceException`) with exponentially increasing wait times, without requiring custom code or external orchestration.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Implement retry logic inside the preprocessing Lambda function code.
Why it's wrong here
While possible, this mixes orchestration logic with application logic and is harder to monitor than Step Functions retry.
- ✓
Modify the Step Functions state machine definition to add a Retry field on the preprocessing state with a maximum retry count of 3 and an exponential backoff rate of 2.0.
Why this is correct
Step Functions Retry field automatically implements exponential backoff and retry logic.
- ✗
Wrap the preprocessing step in a SageMaker Pipeline step with retry policy.
Why it's wrong here
SageMaker Pipeline is for model training and batch inference, not for integrate with Step Functions for real-time workflows.
- ✗
Add a Catch in the state machine to rerun the entire pipeline if preprocessing fails.
Why it's wrong here
Rerunning the entire pipeline is inefficient and could cause duplicate work; retry only the failed step.
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.