Building State Machines
Design and implement various state machine types (Standard, Express) for different use cases, integrating with Lambda and other services.
Building State Machines is a free Serverless Backend with AWS Lambda & API Gateway lesson on CoddyKit — lesson 2 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Serverless Backend with AWS Lambda & API Gateway learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Build Your First Workflow
Welcome back! In the previous lesson, we learned what AWS Step Functions are. Now, let's dive into building them!
You'll learn how to define different steps (states) and connect them to create powerful, automated workflows. We'll also explore the two main types of workflows: Standard and Express.
Anatomy of a State Machine
A Step Functions state machine is a workflow that defines a series of steps, called states. Each state performs a specific task or makes a decision.
- States: The individual steps in your workflow.
- Transitions: Rules that determine which state comes next.
- Input/Output: Data passed between states.
Think of it like a flowchart, but executed by AWS!
Common State Types
Step Functions offers various state types to build your logic:
- Task: Performs work by calling a service (e.g., Lambda, ECS).
- Pass: Passes its input to its output without performing work. Useful for debugging or structuring.
- Choice: Adds branching logic (if/else).
- Wait: Pauses the execution for a specified time or until a specific time.
- Succeed/Fail: Stops the execution successfully or with an error.
- Parallel: Executes multiple branches in parallel.
Defining a Simple Pass State
Let's start with a simple Pass state. This state simply takes its input and passes it as output. It's often used for testing or structuring your state machine.
State machines are defined using Amazon States Language (ASL), which is a JSON-based structure.
Pass State ASL Example
Here's how a Pass state looks in ASL. It defines the state name, its type, and where to go next.
{ "Comment": "A simple Pass state machine",
"StartAt": "HelloWorld",
"States": {
"HelloWorld": {
"Type": "Pass",
"Result": {
"message": "Hello from Step Functions!"
},
"End": true
}
}
}Standard Workflows: The Durable Choice
AWS Step Functions offers two workflow types: Standard and Express.
Standard Workflows are ideal for long-running, durable, and auditable workflows. They can run for up to a year!
- Durability: Retains full execution history for up to 90 days.
- Auditability: Easy to track every step and input/output.
- Use Cases: Order fulfillment, data processing pipelines, human approvals.
Express Workflows: Speed and Scale
Express Workflows are designed for high-volume, event-driven workloads. They are much faster and more cost-effective for short-duration tasks.
- Speed: Can complete thousands of executions per second.
- Cost: Priced per execution and duration, often cheaper for short tasks.
- History: Execution history is limited (up to 90 days in CloudWatch Logs, not directly in Step Functions console).
- Use Cases: Microservice orchestration, real-time streaming data processing, mobile backend processing.
Integrating Lambda: The Task State
One of the most common ways to perform work in a state machine is using a Task state to invoke an AWS Lambda function.
The Resource field in the ASL specifies the ARN of the Lambda function to call.
Example Lambda for Step Functions
This simple Python Lambda function receives an event (input from Step Functions) and returns a modified message. Step Functions will pass its output to the next state.
import json
def lambda_handler(event, context):
print(f"Received event: {json.dumps(event)}")
name = event.get('name', 'World')
return {
'statusCode': 200,
'body': f"Hello, {name}! This is from Lambda."
}Workflow Type Challenge
You need to build a workflow for processing thousands of incoming IoT sensor readings every minute. Each reading takes less than 1 second to process.
Recap: Building Workflows
Great job! You've learned the fundamentals of building AWS Step Functions state machines:
- State machines are defined by a series of states and transitions.
- Key state types include Task, Pass, Choice, and Wait.
- Standard Workflows are for long-running, auditable processes.
- Express Workflows are for high-volume, short-duration tasks.
- You can integrate Lambda functions using a
Taskstate.
Next, we'll explore orchestrating complex workflows!
Frequently asked questions
Is the “Building State Machines” lesson free?
Yes — the full text of “Building State Machines” is free to read here on the web, and the Serverless Backend with AWS Lambda & API Gateway course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Serverless Backend with AWS Lambda & API Gateway course, upgrade to CoddyKit PRO.
What will I learn in “Building State Machines”?
Design and implement various state machine types (Standard, Express) for different use cases, integrating with Lambda and other services. You practise Serverless Backend with AWS Lambda & API Gateway with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Serverless Backend with AWS Lambda & API Gateway?
No prior experience is required. Serverless Backend with AWS Lambda & API Gateway on CoddyKit is structured for beginners through advanced learners; this is — lesson 2 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Building State Machines” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Serverless Backend with AWS Lambda & API Gateway lesson?
Yes. Every Serverless Backend with AWS Lambda & API Gateway lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.