When a single database holds all your data, transactions are straightforward: begin, commit, rollback. But in a microservices architecture, where
Continue readingThe Saga Pattern: Distributed Transactions Without the Pain
Network requests fail. Timeouts happen. Retries are inevitable. If your API charges a customer’s credit card twice because a TCP
Continue readingBuild APIs That Survive Retries: Idempotency Keys in Go
Most applications store data the same way: overwrite the current state and move on. A customer changes their address? Update
Event-driven architecture is the default for most microservices systems today. Services communicate by publishing events to a message broker —
Continue readingThe Outbox Pattern: Solving the Dual-Write Problem in Event-Driven Microservices