The primary purpose of AWS Step Functions is to orchestrate workflows by defining a series of steps, known as states, and the transitions between them based on the outcomes of each step.

In AWS Step Functions, the workflow and transitions between states are defined by a state machine, which is a JSON-based definition that specifies the sequence of steps and conditions for transitioning between them.

AWS Step Functions offer a visual workflow editor and built-in error handling, simplifying workflow management compared to traditional methods.

AWS Step Functions provide built-in error handling capabilities, allowing you to define how to handle different types of errors and automatically retry failed steps based on configured retry policies.

In AWS Step Functions, a state machine is a visual representation of a workflow, defining the sequence of steps and transitions between them.

AWS Step Functions handles long-running tasks by maintaining the state of the workflow execution, allowing it to persist even if they take hours, days, or weeks to complete.

AWS Step Functions is recommended for orchestrating complex workflows involving multiple microservices, coordinating their execution, and handling error scenarios.

AWS Step Functions can integrate with AWS Lambda for serverless orchestration, allowing you to coordinate multiple AWS services as part of your workflows.

Lambda@Edge functions can be used to add security headers to HTTP responses at the edge, enhancing security and compliance.

AWS Step Functions support parallelism, allowing you to run tasks concurrently and synchronize the results, which can improve workflow efficiency.