Introduction

AWS Step Functions is a powerful tool for automating complex workflows. It allows you to define a series of steps that can be executed in parallel or sequentially. In this lesson, we will explore how to use Parallel States with AWS Step Functions. We will look at how to define and execute Parallel States, as well as how to use them to deploy infrastructure using AWS CDK with Typescript.

What are Parallel States?

Parallel States are a type of state in AWS Step Functions that allow you to execute multiple tasks in parallel. This is useful for tasks that can be broken down into smaller, independent tasks that can be executed in parallel. For example, if you need to deploy a complex infrastructure, you can use Parallel States to deploy each component in parallel, rather than sequentially.

How to Define a Parallel State

When defining a Parallel State in AWS Step Functions, you must specify the tasks that will be executed in parallel. This is done by defining a “Parallel” field in the state definition. The “Parallel” field is an array of objects, each of which defines a task to be executed in parallel. Each object must contain a “StartAt” field, which specifies the name of the state that will be executed, and a “Next” field, which specifies the name of the state that will be executed after the current state.

For example, if you wanted to deploy a web server and a database server in parallel, you could define a Parallel State like this:

{
  "StartAt": "DeployWebServer",
  "Parallel": [
    {
      "StartAt": "DeployWebServer",
      "Next": "DeployDatabaseServer"
    },
    {
      "StartAt": "DeployDatabaseServer",
      "Next": "DeployComplete"
    }
  ],
  "Next": "DeployComplete"
}

In this example, the “DeployWebServer” and “DeployDatabaseServer” states will be executed in parallel, and the “DeployComplete” state will be executed after both tasks have completed.

How to Execute a Parallel State

Once you have defined a Parallel State, you can execute it using the AWS CLI or the AWS SDK. To execute a Parallel State using the AWS CLI, you must specify the name of the state and the name of the state machine. For example, if you wanted to execute the Parallel State defined above, you could use the following command:

aws stepfunctions start-execution --state-machine-name MyStateMachine --name MyParallelState

How to Use Parallel States to Deploy Infrastructure

Parallel States can be used to deploy complex infrastructure using AWS CDK with Typescript. To do this, you must define a series of states that will be executed in parallel. Each state should contain a “StartAt” field that specifies the name of the state to be executed, and a “Next” field that specifies the name of the state to be executed after the current state.

For example, if you wanted to deploy a web server and a database server in parallel, you could define a Parallel State like this:

{
  "StartAt": "DeployWebServer",
  "Parallel": [
    {
      "StartAt": "DeployWebServer",
      "Next": "DeployDatabaseServer"
    },
    {
      "StartAt": "DeployDatabaseServer",
      "Next": "DeployComplete"
    }
  ],
  "Next": "DeployComplete"
}

In this example, the “DeployWebServer” and “DeployDatabaseServer” states will be executed in parallel, and the “DeployComplete” state will be executed after both tasks have completed.

How to Use Parallel States with AWS CLI

Parallel States can also be used with the AWS CLI. To do this, you must specify the name of the state and the name of the state machine when executing the command. For example, if you wanted to execute the Parallel State defined above, you could use the following command:

aws stepfunctions start-execution --state-machine-name MyStateMachine --name MyParallelState

Conclusion

In this lesson, we explored how to use Parallel States with AWS Step Functions. We looked at how to define and execute Parallel States, as well as how to use them to deploy infrastructure using AWS CDK with Typescript or the AWS CLI. By using Parallel States, you can break down complex tasks into smaller, independent tasks that can be executed in parallel. This can help you automate complex workflows and deploy complex infrastructure more quickly and efficiently.