Most systems today use CRUD: read the current state, modify a row, write it back. The database remembers where things
Continue readingEvent Sourcing in Practice: Building a System That Never Forgets
Docker image builds are one of those things that quietly accumulate technical debt. You start with a simple Dockerfile, and
Continue readingFaster Docker Builds with BuildKit: Cache Mounts, Remote Caching, and Bake
Automated tests that hit real databases, live APIs, and production file systems are slow, flaky, and expensive to maintain. The
Continue readingTest Doubles Demystified: Stubs, Spies, Mocks, and Fakes in Go
Microservices promised us smaller, more maintainable codebases. They delivered — along with a debugging nightmare. When a request flows through
Continue readingOpenTelemetry in Go: From Zero to Distributed Tracing
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
Constructors in Go are simple when a type has one or two fields. But the moment you start building something
Continue readingMastering the Functional Options Pattern in Go
Most microservice architectures still rely on an outdated security model: trust everything inside the network, and defend the perimeter.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
Go’s error handling gets a lot of attention — and a lot of criticism. The familiar if err != nil
Continue readingEffective Error Handling in Go: From `if err != nil` to `errors.AsType`
Every developer who has worked with microservices eventually hits the same wall: a single business operation needs to touch multiple