![]() ![]() This is important to understand because we’re about to go into a state that chooses one of two options based on the result of our first task. In the next part of this series, we’ll look at passing data into and out of individual task states. If you’d like to learn more about this feature of Step Functions, please refer to the Step Functions documentation. IBMSecureRandom Examples Add An Example Sample code invoking the randomize function Tag Example The following example calls the Randomize function to seed the random number generator and generates 10 random numbers. The examples in the AWS Playbox application don’t invoke AWS services directly. This opens up some powerful options in Step Functions workflows, particularly when, for example, you are running a workflow over a large batch of data files that should be processed by a machine learning toolset on SageMaker, or when you have a Docker image running inside of Elastic Container Service that will perform complex tax calculations on a set of passed-in data. Instead of having to write a simple Lambda function to publish a message to SNS, you can do that directly from your Step Functions workflow code. Here’s what this workflow looks like in the Amazon States Language, which is how you declare (write) a Step Functions workflow: ![]() It also indicates if a cryptographically strong. End the workflow and return the results of the analysis to the calling environment. Generates a string of pseudo-random bytes, with the number of bytes determined by the length parameter.If the random number generated in step 2 is above 50, choose image 2.If the random number generated in step 2 is less than or equal to 50, choose image 1.Generate a random number between 1 and 100.This first example Step Function workflow is pretty simple. ![]() Rekognition is a machine vision service that allows you to perform all sorts of analysis on the content of an image or video. Default: CFMXCOMPAT The algorithm to use to generated the random number. I covered AWS Rekognition in a previous blog series, so if you’re not familiar with what Rekognition is, please review that series first. Remember that the full code for everything I talk about in this series is in my AWSPlaybox application. The first of these workflows is a relatively simple workflow that analyzes one of two randomly chosen images using AWS Rekognition. The rest of the series will examine two different Step Functions workflows. In the first post in this series, I introduced Step Functions and described the critical role they play in building serverless applications, not just functions. Home RSS Using AWS Step Functions in CFML: The First Example Workflow and an Exploration of Task States Posted 25 April 2019 Using AWS Step Functions in CFML: The First Example Workflow and an Exploration of Task States | Brian Klaas Brian Klaas AWS. ![]()
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |