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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.

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!

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.

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.

Here's how a Pass state looks in ASL. It defines the state name, its type, and where to go next.

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 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.

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.

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.

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.

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 Task state.

Next, we'll explore orchestrating complex workflows!