step-functions

Orchestrate AWS workflows by defining state machines with branching, concurrency, and retries.

Updated Feb 16, 2026

Search Tags:#aws #error handling #workflow orchestration #parallel execution #state machine #step functions #map state

Ready to run

npx skills add https://github.com/aurainfosec/cloud-review-automation-poc --skill step-functions-aurainfosec

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: step-functions
Source: https://github.com/aurainfosec/cloud-review-automation-poc/tree/main/skills/step-functions
Command: npx skills add https://github.com/aurainfosec/cloud-review-automation-poc --skill step-functions-aurainfosec

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

AWS Step Functions helps you coordinate multi-step, cross-service workflows without writing complex glue code, while supporting retries, branching, and reliable execution patterns.

Core Features & Use Cases

Workflow orchestration with state machines: Coordinate tasks across AWS services using Standard and Express workflows.
State-based control flow: Implement branching with Choice, concurrent work with Parallel, and batch/iteration with Map.
Operational robustness: Add Retry/Catch error handling and use execution history to debug failed runs.

Use case: An order-processing workflow that validates inputs, routes high-value vs. standard orders, runs independent fulfillment and notification steps in parallel, and iterates over items with Map while handling transient failures safely.

Quick Start

Ask: "Using AWS Step Functions, propose a state machine definition for an order workflow with Choice branching, Parallel fulfillment steps, Map item processing, and retry/catch error handling, then list the exact CLI commands to deploy it."

Frequently Asked Questions about step-functions

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I orchestrate multi-step AWS workflows with branching and parallel execution?▼

You orchestrate multi-step AWS workflows by defining state machines using the Amazon States Language. State machines manage branching with Choice states, concurrent work with Parallel states, and batch processing with Map states for reliable task execution.

How do I add error handling and retries to an AWS Step Functions state machine?▼

Error handling in AWS Step Functions is configured using Retry and Catch blocks within your state machine definition. These mechanisms allow workflows to automatically retry failed tasks during transient errors or route execution to fallback states when failures occur.

What is the best way to debug a failed Step Functions execution?▼

The best way to debug a failed Step Functions execution is by reviewing the execution history. This history provides a detailed visual timeline and diagnostic logs of each state transition, helping pinpoint exactly where and why a workflow failed.

Can I use AWS Step Functions for high-volume, short-lived event processing?▼

AWS Step Functions supports both Standard and Express workflows. Express workflows are specifically designed for high-volume, short-lived event processing, offering higher throughput rates compared to Standard workflows, which are built for long-running, durable executions.

How do I deploy and manage Step Functions state machines using the AWS CLI?▼

You deploy and manage state machines using the AWS CLI by executing specific commands to create, update, and start executions. This requires a YAML or ASL-ready workflow definition file and proper IAM permissions to interact with the Step Functions API.

When should I use Map state for iteration instead of Parallel state in workflow orchestration?▼

Use Map state when you need to iterate over a batch of items and run the same set of tasks on each item independently. Use Parallel state when you need to execute multiple different, independent branches of tasks concurrently within a single workflow.