You can make a AWS step functions workflow with GUI and export/import JSON/YAML.

Genomics Workflows on AWS

[Book-2019] Pragmatic AI: An Introduction to Cloud-based Machine Learning

The Asynchronous Messaging Workshop is a collection of individual labs covering different aspects and patterns of asynchronous messaging.

Emulate step functions locally when developing your Serverless project

This tool automates restoration of RDS database instances from snapshots into any dev, staging or production environments. It supports individual RDS Snapshot as well as cluster snapshot restore operations.

The elegance of Airflow + the power of AWS

This application uses a Synchronous Express workflow to analyse a contact form submission and provide customers with a case reference number.

Schedule future emails with AWS Lambda and Step Functions

This repository contains all the example code to help you build a content aggregator like serverless land. It is split into 2 components: Part 1: The front-end, an auto-building static website. Part 2: The backend, am automaed content aggregation workflow.

VSCode extension to visualize AWS step functions

Techniques for Scraping the Web in Python

Example application using the new Step Functions integration with API Gateway. It developers to call API Gateway REST APIs and API Gateway from a Step Functions workflow.

Clojure AWS Step Functions library

Stepper allows you to write AWS Step Functions using a higher level programmatic language.

Utility to create AWS Step Function activities out of command line programs

AWS Step Function Implementation in JS, so you can run your Node.js lambda handlers in your test environments. Made to support Serverless JS testing.

A Numpy based step function library for analysis and profit. More than just taking you up and down.

Deprecated, renamed and maintained at https://github.com/coinbase/odin

With Amazon Rekognition Custom Labels, you can easily build and deploy Machine Learning (ML) models to identify custom objects which are specific to your business domain in images without requiring advanced ML knowledge. When combined with Amazon Augmented AI (A2I), you can quickly integrate a ML workflow to capture and label images with a human workforce for model training. As ML lifecycle is an iterative and repetitive process, you need to implement an effective workflow that can provide for continuous model training with new data and automated deployment. Your workflow also needs to be flexible enough to allow for changes without requiring development rework as your business objectives change. Operationalizing an effective and flexible workflow can be resource intensive, especially for customers who have limited machine learning capabilities. In this post, we will use AWS Step Functions, AWS Lambda, and AWS System Manager Parameter Store to automate a configurable ML workflow for Rekognition Custom Labels and A2I. We will provide an overview of the solution and instructions to deploy it with AWS CloudFormation.

Serverless Offline Plugin to Support Step Functions for Local Development

LocalStack demo of a fully-serverless auditor project for discounts.

AWS services backup using Step functions

Patterns for running Amazon ECS/AWS Fargate tasks resiliently with AWS Step Functions

This project contains source code and supporting files for a serverless application which can be used for Computer Vision inferencing using Amazon Lookout for Vision

The CloudFormation Resource Provider Package For AWS Step Functions

Encrypt EBS volumes from AWS EC2 instances with a serverless StepFunctions machine

Deployment/Orchestration of Apache Spark applications on Amazon EMR.