SAP-C02 Design for New Solutions Practice Question
A media company is building a new video transcoding pipeline. Source files arrive in an Amazon S3 bucket, and a workflow must fan out to several processing steps, retry failed steps with backoff, and pause for manual approval before publishing. A solutions architect is evaluating AWS Step Functions. Which two statements are correct about using Step Functions for this design? (Choose two.)
⚠ Common exam trap
The trap here is treating the two workflow types as interchangeable, when the duration limit and execution semantics differ in ways that decide the design.
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
✓
A Standard workflow can run for up to one year and supports exactly-once execution semantics, which suits long-running transcoding jobs and audit requirements.
Standard workflows provide durable, exactly-once, up-to-one-year executions with recorded history, while Express workflows provide at-least-once, up-to-five-minute executions for high-volume short tasks. Choosing between them depends on job duration and the need for exactly-once semantics, and both types support state-level retry configuration and service integrations without Lambda wrappers.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Retries and backoff must be coded inside each Lambda function because Step Functions cannot define retry behavior at the state level.
Why it's wrong here
Step Functions state machines support Retry and Catch fields on individual states, allowing configurable retry intervals, maximum attempts, and exponential backoff without any code. Implementing retries inside Lambda functions duplicates logic across functions, hides failures from the execution history, and makes the workflow harder to observe and audit.
- ✗
Step Functions can invoke AWS Lambda functions but cannot call other AWS services directly, so every transcoding step must be wrapped in a Lambda function.
Why it's wrong here
Step Functions integrates directly with many AWS services through optimized service integrations, including Amazon ECS, AWS Batch, Amazon SNS, Amazon SQS, and DynamoDB, without a Lambda wrapper. Requiring a Lambda function for every step would add unnecessary code, cost, and the fifteen-minute Lambda timeout constraint to long transcoding operations.
- ✓
A Standard workflow can run for up to one year and supports exactly-once execution semantics, which suits long-running transcoding jobs and audit requirements.
Why this is correct
Standard workflows are designed for durable, long-running processes and can execute for up to one year, with execution history retained so each state transition is recorded. They provide exactly-once semantics for state transitions, which is important for auditable approval steps and for jobs whose duration exceeds the five-minute limit of the other workflow type.
- ✓
An Express workflow can run for up to five minutes and provides at-least-once execution, making it suitable for high-volume, short-lived event processing.
Why this is correct
Express workflows are optimized for high event rates and short durations, with a maximum execution time of five minutes, and they provide at-least-once execution semantics. That makes them a good fit for rapidly triggered, idempotent processing steps, but not for long transcoding jobs or for steps that require exactly-once guarantees.
- ✗
Manual approval steps are implemented by polling a DynamoDB table in a loop until a reviewer updates a record, because Step Functions has no built-in callback mechanism.
Why it's wrong here
Step Functions supports a task token callback pattern where a state waits for an external system to call SendTaskSuccess or SendTaskFailure, and it also offers an optimized integration for human approval via Amazon SNS. Polling a DynamoDB table in a loop wastes state transitions and adds latency compared with the native callback approach.
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 and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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