Exception Handling
The defined detection, management, recovery and escalation of errors or unexpected conditions in software and automated processes.
Good exception handling keeps failures contained, protects data integrity and gives teams clear signals to fix issues, which is critical for payments, integrations and automated workflows.
An AWS Step Functions workflow retries a failed invoice API call twice with exponential backoff, then routes the case to a fallback state that writes the error to a queue and creates a ticket for the finance team.
Catching every error and continuing can hide real failures and corrupt data. Retries without idempotency can duplicate actions, and too many layers of handlers make code and workflows harder to understand and test.
Code or workflow engines detect errors and pass control to handlers. In code, try, catch and finally blocks catch specific exception types, clean up resources and rethrow when the caller must know. In workflows, retry policies set attempts, intervals and backoff, and catch rules route unresolved errors to fallback steps. Handlers should log context and leave state consistent.
Systems Architecture
Microsoft Learn — Best practices for exceptions — https://learn.microsoft.com/en-us/dotnet/standard/exceptions/best-practices-for-exceptions; AWS Step Functions — Handling errors in Step Functions workflows — https://docs.aws.amazon.com/step-functions/latest/dg/concepts-error-handling.html