For years, adding tracing to a Go service meant wrapping every handler, decorating every client, and threading context through every
Continue readingDistributed Tracing in Go with OpenTelemetry: A Setup That Actually Holds Together
Ask most Go developers how the garbage collector works and you’ll get one of two answers: “it’s concurrent and low-pause”
Rate limiting looks like a solved problem until the day your API runs on more than one machine. The in-memory
Continue readingDistributed Rate Limiting in Go: Token Buckets, Redis, and the Fail-Open Decision
Here is one of the oldest bugs in distributed systems, still shipping to production every week: a service commits a
Every Go service that talks to PostgreSQL ends up managing a pool of database connections, and almost every team gets
Sooner or later every API team hits the wall: a client depends on behavior you need to change. The field
Every high-concurrency server you have ever deployed eventually bottoms out at the same place: a call that says “tell me
Replica lag is one of those distributed-systems facts everyone accepts in the abstract and nobody plans for in the code.
Every codebase has a logging moment of reckoning. It arrives when someone has to debug a production incident at 2
Continue readingStructured Logging in Go: A Practical slog Field Guide
Every Go program you have ever shipped is a swarm of goroutines multiplexed onto a handful of operating system threads.
Continue readingInside the Go Scheduler: G, M, P, Work Stealing, and Why Goroutines Block Cheaply