AWS Step Functions is a serverless function orchestrator that makes it easy to sequence AWS Lambda functions and multiple AWS services into business-critical applications. Through its visual interface, you can create and run a series of checkpointed and event-driven workflows that maintain the application state. The output of one step acts as an input to the next. Each step in your application executes in order, as defined by your business logic.
Orchestrating a series of individual serverless applications, managing retries, and debugging failures can be challenging. As your distributed applications become more complex, the complexity of managing them also grows. With its built-in operational controls, Step Functions manages sequencing, error handling, retry logic, and state, removing a significant operational burden from your team.
Build and update apps quickly
AWS Step Functions lets you build visual workflows that enable fast translation of business requirements into technical requirements. You can build applications in a matter of minutes, and when needs change, you can swap or reorganize components without customizing any code.
AWS Step Functions manages state, checkpoints and restarts for you to make sure that your application executes in order and as expected. Built-in try/catch, retry and rollback capabilities deal with errors and exceptions automatically.
Write less code
AWS Step Functions manages the logic of your application for you, and implements basic primitives such as branching, parallel execution, and timeouts. This removes extra code that may be repeated in your microservices and functions.
How it works
Step Functions can help ensure that long-running, multiple ETL jobs execute in order and complete successfully, instead of manually orchestrating those jobs or maintaining a separate application. You can also use Step Functions to standardize a machine learning training workflow to improve the accuracy of machine learning models.
Step Functions provides auditable automation of routine deployments, upgrades, installations, and migrations. You can use Step Functions to easily automate recurring tasks such as patch management, infrastructure selection, and data synchronization, and Step Functions will automatically scale, respond to timeouts, and retry failed tasks.
Modernize a monolith
By using Step Functions to carve off a few tasks from the rest of your codebase, you can tackle the transformation of monolithic applications into microservices as a series of small steps. This allows you to untangle business-critical code safely and at your own pace, without disrupting operations and while you continue to deliver new features.
Use Step Functions to combine multiple AWS Lambda functions into responsive serverless applications and microservices, without having to write code for workflow logic, parallel processes, error handling, timeouts or retries. You can also orchestrate data and services that run on Amazon EC2 instances, containers, or on-premises servers.
Serverless Deployment Pipeline
Hear how Coinbase uses AWS Step Functions and AWS Lambda to perform hundreds of deployments a day, and how Step Functions and Lambda have enabled the team to achieve a 97% success rate for deployments.
VPC mass creation
Greg Campion, Systems Admin at Paessler AG, shares how they use AWS Lambda and AWS Step Functions to conduct and monitor VPC mass creation for their PRTG Network Monitoring product.
Refreshing SAP S/4HANA
Sunil Kumar from Zalora explains how their serverless automation with AWS Step Functions, AWS System Manager, and AWS Lambda has reduced their SAP system refresh time from 5 days to 2 days.
Serverless lead management
Hear how Trulia Rentals adopted a serverless approach to accepting, processing, and analyzing customer leads as they migrate from their legacy customer leads system.
Elastic machine learning
Yu Yamada, Big Data Architect, explains how they built automated, scalable and robust machine learning pipelines with AWS Lambda, AWS Step Functions, AWS Batch and Amazon DynamoDB.
Media supply chains
Fox Network shared media processing workloads across their existing facility and AWS to dynamically provision and scale resources and automate the flow of their entire media supply chain.
Security event processing
ClearDATA built a solution that provides their customers additional AWS security controls to check that changes made on the customer's account are in accordance with their security policy.
Serverless website archival
MirrorWeb addressed the challenges on long running tasks during a website archival process by leveraging Step Functions and Lambda to launch and delegate a task to an EC2 instance or Docker container via ECS.
nib health funds
Auditable access pipelines
Regulated workloads need more than rock solid security to be compliant. Adam from CMD Solutions and Mat from nib health funds share a clever way to use Step Functions to automatically spin up as well tear down security posture.
Automated data processing
Zapproved helps customers in the legal industry streamline e-discovery. Lee from Zapproved demonstrates how they use Step Functions, Lambda, and SQS to automate data processing. To learn more, read the case study.
Agronomy on the cloud
Encirca Services by DuPont Pioneer partners with farmers in the field to help them deliver optimal crop yields. They built a cloud based collaborative platform for farmers to simulate crop growth and manage soil nitrogen levels.
Introducing AWS Step Functions Express Workflows
Express Workflows are a new type of AWS Step Functions workflow type that cost-effectively orchestrate AWS compute, database, and messaging services at event rates greater than 100,000 events per second.
AWS Step Functions Adds Support for Dynamic Parallelism in Workflows
AWS Step Functions now supports dynamic parallelism, so you can optimize the performance and efficiency of application workflows.
AWS Step Functions Adds Support for Nested Workflows
AWS Step Functions now allows you to orchestrate more complex processes by composing modular, reusable workflows.