Most applications start with a simple mental model: one database, one set of tables, and CRUD operations that read and
Continue readingCQRS in Practice: Splitting Reads and Writes for Scalable Systems
Most microservice architectures still rely on an outdated security model: trust everything inside the network, and defend the perimeter. The
Continue readingZero Trust Microservices: Implementing mTLS in Go
Networks are unreliable. Clients retry requests. Messages get delivered twice. In a distributed system, the question isn’t whether a duplicate
Continue readingImplementing Idempotency in Go: Keys, Stores, and Patterns for Reliable APIs
Every developer who has worked with microservices eventually hits the same wall: a single business operation needs to touch multiple
When one service in a distributed system starts failing, the cascade can bring down everything downstream. A slow database connection
CQRS and Event Sourcing: Building an Order System from Scratch in Go Most of us build CRUD services by default:
Continue readingCQRS and Event Sourcing: Building an Order System from Scratch in Go
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