Saga Pattern Over Distributed Transactions: Handling Partial Failures Safely

Distributed systems frequently face partial failures when one service in a multi-step workflow succeeds while a downstream service fails, leaving data in an inconsistent state. A common example is a payment being processed before an inventory reservation fails, resulting in a customer being charged but receiving nothing. Developers often attempt to solve this with distributed transactions like Two-Phase Commit, but these require cross-service database locks that hurt throughput and create single points of failure. A more resilient approach is the orchestration-based Saga pattern, where a central orchestrator tracks each workflow step and automatically triggers compensating actions, such as refunds, if any step fails. Designing explicitly for failure scenarios rather than only the happy path is essential to maintaining data integrity in production microservices environments.