- A
Implement retry logic inside the preprocessing Lambda function code.
Why wrong: While possible, this mixes orchestration logic with application logic and is harder to monitor than Step Functions retry.
- B
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.
Step Functions Retry field automatically implements exponential backoff and retry logic.
- C
Wrap the preprocessing step in a SageMaker Pipeline step with retry policy.
Why wrong: SageMaker Pipeline is for model training and batch inference, not for integrate with Step Functions for real-time workflows.
- D
Add a Catch in the state machine to rerun the entire pipeline if preprocessing fails.
Why wrong: Rerunning the entire pipeline is inefficient and could cause duplicate work; retry only the failed step.
Quick Answer
The correct answer is to modify the Step Functions state machine definition by adding a Retry field on the preprocessing state with a maximum retry count of 3 and an exponential backoff rate of 2.0. This is correct because AWS Step Functions natively supports retry with exponential backoff directly within the state machine definition, allowing you to specify `MaxAttempts` and `BackoffRate` without writing custom code or using external orchestration. On the AWS Certified Machine Learning Engineer Associate MLA-C01 exam, this tests your understanding of how to handle transient failures in ML inference pipelines using built-in Step Functions error handling, often appearing as a scenario where candidates mistakenly try to implement retry logic in Lambda code or a separate orchestration service. A common trap is forgetting that the `BackoffRate` of 2.0 doubles the wait time between retries, while `MaxAttempts` counts the total attempts including the initial try. Memory tip: think "3 strikes, double the wait" for MaxAttempts of 3 and BackoffRate of 2.0.
MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
This MLA-C01 practice question tests your understanding of deployment and orchestration of ml workflows. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 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?
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.
Option B is correct because 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.
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.
- ✗
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.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
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.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often 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.
Detailed technical explanation
How to think about this question
Under the hood, Step Functions' `Retry` field evaluates the `ErrorEquals` condition (e.g., `States.Timeout` or `Lambda.ServiceException`) and applies the `IntervalSeconds`, `BackoffRate`, and `MaxAttempts` to compute the delay before each retry. A subtle behavior is that the `IntervalSeconds` is the base delay for the first retry, and subsequent delays are multiplied by the `BackoffRate` (e.g., 1s, 2s, 4s for rate 2.0), but the actual wait time may also include jitter if `JitterStrategy` is set. In a real-world scenario, if the preprocessing step depends on an external API that experiences transient throttling, this retry configuration prevents cascading failures without overloading the downstream service.
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.
TExam Day Tips
- 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 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
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: 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. — Option B is correct because 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.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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