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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
Hand-coding retries inside the Lambda function duplicates Step Functions' native Retry field, loses visibility of attempts in the state machine, and cannot apply exponential backoff declaratively. It tempts developers wanting fine-grained control, but the Retry block with MaxAttempts 3 and BackoffRate is the intended mechanism.
- ✓
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 handles transient failures declaratively via the Retry field on a state. Setting MaxAttempts to 3 with BackoffRate 2.0 applies exponential backoff to the preprocessing state, satisfying the required retry count without custom error-handling code.
- ✗
Wrap the preprocessing step in a SageMaker Pipeline step with retry policy.
Why it's wrong here
SageMaker Pipelines orchestrates training and batch processing jobs, not per-record Step Functions state transitions; its retry policy cannot attach to an existing state machine task. It would suit retrying a standalone pipeline execution, but here the retry belongs on the preprocessing state itself.
- ✗
Add a Catch in the state machine to rerun the entire pipeline if preprocessing fails.
Why it's wrong here
A Catch only defines fallback handling after a state fails; it does not retry the failed preprocessing step, and rerunning the whole pipeline repeats inference and postprocessing for a single record. Catch suits compensating or notifying on terminal failure, not exponential-backoff retries of one state.
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.