DVA-C02 Step Functions execution limit Practice Question
A company runs a data processing pipeline using AWS Step Functions. The pipeline starts with a task that reads a CSV file from Amazon S3 and then fans out to multiple parallel Lambda functions for data transformation. The final step aggregates the results and writes to an Amazon DynamoDB table. Recently, the pipeline has been failing intermittently with 'StateMachineExecutionLimitExceeded' errors. The development team has already increased the execution history limit to the maximum. The pipeline runs about 500 executions per day. Meanwhile, the operations team reports that some executions are timing out after 5 minutes, even though each Lambda function completes within 30 seconds. The Step Function definition uses a Map state with a max concurrency of 20. The developer needs to fix both issues. Which combination of actions should the developer take? (Choose the BEST option.)
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
✓
Split the pipeline into multiple smaller Step Functions and chain them together.
StateMachineExecutionLimitExceeded indicates that the number of concurrent executions for this state machine exceeds its limit. Since the execution history limit is already maximized, the only way to reduce concurrency is to distribute executions across multiple state machines. Splitting the pipeline into smaller Step Functions and chaining them together reduces the number of concurrent executions per state machine, resolving the limit error. The timeout issue is mitigated because each smaller state machine can have its own timeout, preventing the overall pipeline from exceeding 5 minutes. Option B is the only combination that addresses both problems.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Reduce the max concurrency of the Map state and increase the task execution timeout in the Step Function definition.
Why it's wrong here
Reducing the max concurrency of the Map state does not reduce the number of concurrent state machine executions; it only reduces parallelism within an execution, potentially increasing duration and worsening timeouts. Increasing task timeout does not fix the limit error. Thus, this does not solve the StateMachineExecutionLimitExceeded issue.
- ✓
Split the pipeline into multiple smaller Step Functions and chain them together.
Why this is correct
Splitting the pipeline into multiple smaller Step Functions and chaining them together distributes executions across different state machines, each with its own concurrency limit, preventing the limit error. Additionally, each smaller state machine can have its own timeout settings, allowing the pipeline to complete within the 5-minute limit. This combination addresses both issues correctly.
- ✗
Increase the max concurrency of the Map state and add a retry policy.
Why it's wrong here
Increasing Map state concurrency would increase parallel processing, exacerbating the concurrency issue. Adding a retry policy does not prevent the limit error; it only handles transient failures after the error occurs. Therefore, this is not a solution.
- ✗
Set a Lambda reserved concurrency for the transformation functions to 100.
Why it's wrong here
Setting Lambda reserved concurrency limits Lambda invocations but does not affect Step Functions execution concurrency. The limit error is specific to Step Functions, not Lambda, so this does not resolve the issue.
Visual reference
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DVA-C02 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 DVA-C02 exam.