Primitives

1. Modularity and Clarity: State machines provide a modular and clear representation of complex workflows by breaking them into distinct states. This enhances readability and makes it easier to understand the logic.
2. Scalability: State machines are well-suited for scenarios with multiple paths or stages, allowing for scalability and the addition of new states without significant redesign.
3. Error Handling: The “Terminate Workflow” activity is crucial for handling critical errors. It helps prevent the execution of subsequent activities when an error occurs, enabling graceful error handling and logging.
4. Workflow Control: It provides explicit control over the flow of the workflow, allowing developers to stop execution based on specific conditions or exceptions.
5. Data Transformation: Assignments facilitate data transformation, enabling the manipulation and preparation of data for further processing.
6. Dynamic Values: Assignments allow the dynamic updating of variable values based on changing conditions, enhancing flexibility in workflow execution.
7. Parallel Processing: It is beneficial in scenarios involving parallel processing, providing the ability to handle cancellations in specific branches without affecting the entire workflow.