Orchestrating Workflows with AWS Step Functions

Introduction

AWS Step Functions allow composing serverless functions into fault-tolerant workflows with visual monitoring.

Prerequisites

• AWS CLI configured
• State Machine IAM role

Step 1: Define State Machine

Create state-machine.json:

{
  "Comment": "Example Step Function",
  "StartAt": "TaskA",
  "States": {
    "TaskA": {
      "Type": "Task",
      "Resource": "arn:aws:lambda:us-east-1:123456789012:function:TaskA",
      "Next": "ChoiceState"
    },
    "ChoiceState": {
      "Type": "Choice",
      "Choices": [
        {"Variable": "$.status","StringEquals": "SUCCESS","Next": "TaskB"}
      ],
      "Default": "FailState"
    },
    "TaskB": {"Type":"Task","Resource":"arn:aws:lambda:us-east-1:123456789012:function:TaskB","End":true},
    "FailState": {"Type":"Fail","Cause":"Task A failed"}
  }
}

Step 2: Create State Machine

aws stepfunctions create-state-machine \
  --name MyStateMachine \
  --definition file://state-machine.json \
  --role-arn arn:aws:iam::123456789012:role/StepFunctionsRole

Step 3: Execute and Monitor

Start execution:

aws stepfunctions start-execution --state-machine-arn arn:aws:states:us-east-1:123456789012:stateMachine:MyStateMachine

Monitor in Step Functions console for graphical view.

Summary

Step Functions enable robust orchestration with retries, error handling, and parallelism using JSON-defined state machines.