It’s common for modern cloud applications to be composed of many services and components. As applications grow, an increasing amount of code needs to be written to coordinate the interaction of all components. With AWS Step Functions, you can focus on defining the component interactions, rather than writing all the software to make the interactions work.
AWS Step Functions integrates with the AWS services listed below. You can directly call API actions from the Amazon States Language in AWS Step Functions and pass parameters to the APIs of these services:
- Compute services (AWS Lambda, Amazon ECS, Amazon EKS, and AWS Fargate)
- Database services (Amazon DynamoDB)
- Messaging services (Amazon SNS and Amazon SQS)
- Data processing and analytics services (Amazon Athena, AWS Batch, AWS Glue, Amazon EMR, and AWS Glue DataBrew)
- Machine learning services (Amazon SageMaker)
- APIs created by API Gateway
You can configure your AWS Step Functions workflow to call other AWS services using AWS Step Functions service tasks.
Step Functions: State machine
A state machine is an object that has a set number of operating conditions that depend on its previous condition to determine output.
A common example of a state machine is the soda vending machine. The machine starts in the operating state (waiting for a transaction), and then moves to soda selection when money is added. After that, it enters a vending state, where the soda is deployed to the customer. After completion, the state returns back to operating.
Build workflows using state types
States are elements in your state machine. A state is referred to by its name, which can be any string, but must be unique within the scope of the entire state machine.
States can perform a variety of functions in your state machine:
- Do some work in your state machine (a Task state)
- Make a choice between different branches to run (a Choice state)
- Stop with a failure or success (a Fail or Succeed state)
- Pass its input to its output or inject some fixed data (a Pass state)
- Provide a delay for a certain amount of time or until a specified time or date (a Wait state)
- Begin parallel branches (a Parallel state)
- Dynamically iterate steps (a Map state)
Orchestration of complex distributed workflows
Express Workflows are ideal for high-volume, event-processing workloads such as IoT data ingestion, streaming data processing and transformation, and mobile application backends. They can run for up to 5 minutes. Express Workflows employ an at-least-once model, where there is a possibility that a code might be run more than once. This makes them ideal for orchestrating idempotent actions such as transforming input data and storing using PUT in DynamoDB. Express Workflow executions are billed by the number of executions, the duration of execution, and the memory consumed.
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Osama
Technology Geek 