Process high-volume messages from Amazon SQS with Step Functions Express workflows - AWS Step Functions
Step 1: Create the state machineStep 2: Trigger the state machine execution

Process high-volume messages from Amazon SQS with Step Functions Express workflows

This sample project demonstrates how to use an AWS Step Functions Express Workflow to process messages or data from a high-volume event source, such as Amazon Simple Queue Service (Amazon SQS). Because Express Workflows can be started at a very high rate, they are ideal for high-volume event processing or streaming data workloads.

Here are two commonly used methods to execute your state machine from an event source:

  • Configure an Amazon CloudWatch Events rule to start a state machine execution whenever the event source emits an event. For more information, see Creating a CloudWatch Events Rule That Triggers on an Event.

  • Map the event source to a Lambda function, and write function code to execute your state machine. The AWS Lambda function is invoked each time your event source emits an event, in turn starting a state machine execution. For more information see Using AWS Lambda with Amazon SQS.

This sample project uses the second method to start an execution each time the Amazon SQS queue sends a message. You can use a similar configuration to trigger Express Workflows execution from other event sources, such as Amazon Simple Storage Service (Amazon S3), Amazon DynamoDB, and Amazon Kinesis.

For more information about Express Workflows and Step Functions service integrations, see the following:

Step 1: Create the state machine

  1. Open the Step Functions console and choose Create state machine.

  2. Find and choose the starter template you want to work with. Choose Next to continue.

  3. Choose Run a demo to create a read-only and ready-to-deploy workflow, or choose Build on it to create an editable state machine definition that you can build on and later deploy.

  4. Choose Use template to continue with your selection.

Next steps depend on your previous choice:

  1. Run a demo – You can review the state machine before you create a read-only project with resources deployed by AWS CloudFormation to your AWS account.

    You can view the state machine definition, and when you are ready, choose Deploy and run to deploy the project and create the resources.

    Deploying can take up to 10 minutes to create resources and permissions. You can use the Stack ID link to monitor progress in AWS CloudFormation.

    After deploy completes, you should see your new state machine in the console.

  2. Build on it – You can review and edit the workflow definition. You might need to set values for placeholders in the sample project before attemping to run your custom workflow.

Note

Standard charges might apply for services deployed to your account.

Step 2: Trigger the state machine execution

  1. Open the Amazon SQS console.

  2. Select the queue that was created by the sample project.

    The name will be similar to Example-SQSQueue-wJalrXUtnFEMI.

  3. In the Queue Actions list, select Send a Message.

  4. Use the copy button to copy the following message, and on the Send a Message window, enter it, and choose Send Message.

    Note

    In this sample message, the input: line has been formatted with line breaks to fit the page. Use the copy button or otherwise ensure that it is entered as a single line with no breaks. 

    {
      "input": "QW5kIGxpa2UgdGhlIGJhc2VsZXNzIGZhYnJpYyBvZiB0aGlzIHZpc2lvbiwgVGhlIGNsb3VkLWNhcHBlZCB0b3dlcnMsIHRoZSBnb3JnZW
                91cyBwYWxhY2VzLCBUaGUgc29sZW1uIHRlbXBsZXMsIHRoZSBncmVhdCBnbG9iZSBpdHNlbGbigJQgWWVhLCBhbGwgd2hpY2ggaXQgaW5o
                ZXJpdOKAlHNoYWxsIGRpc3NvbHZlLCBBbmQgbGlrZSB0aGlzIGluc3Vic3RhbnRpYWwgcGFnZWFudCBmYWRlZCwgTGVhdmUgbm90IGEgcm
                FjayBiZWhpbmQuIFdlIGFyZSBzdWNoIHN0dWZmIEFzIGRyZWFtcyBhcmUgbWFkZSBvbiwgYW5kIG91ciBsaXR0bGUgbGlmZSBJcyByb3Vu
                ZGVkIHdpdGggYSBzbGVlcC4gU2lyLCBJIGFtIHZleGVkLiBCZWFyIHdpdGggbXkgd2Vha25lc3MuIE15IG9sZCBicmFpbiBpcyB0cm91Ym
                xlZC4gQmUgbm90IGRpc3R1cmJlZCB3aXRoIG15IGluZmlybWl0eS4gSWYgeW91IGJlIHBsZWFzZWQsIHJldGlyZSBpbnRvIG15IGNlbGwg
                QW5kIHRoZXJlIHJlcG9zZS4gQSB0dXJuIG9yIHR3byBJ4oCZbGwgd2FsayBUbyBzdGlsbCBteSBiZWF0aW5nIG1pbmQu"
}

  5. Choose Close.

  6. Open the Step Functions console.

  7. Go to your Amazon CloudWatch Logs log group and inspect the logs. The name of the log group will look like example-ExpressLogGroup-wJalrXUtnFEMI.