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
Every Go service that talks to PostgreSQL ends up managing a pool of database connections, and almost every team gets
Every Tokio application eventually meets the same mystery: a task that looks harmless in code review brings an entire runtime
One Tuesday your API’s most popular endpoint works fine. Two Tuesdays later, a mobile app that has been calling it
Your microservice takes eleven seconds to answer a request that used to take two hundred milliseconds. The on-call engineer opens
Getting a request into your system is the easy part. The hard question arrives at hop two: when the order
Every API with more than a handful of consumers eventually faces the same problem: an endpoint or field you designed
Continue readingDeprecating API Endpoints Without Breaking Consumers: Deprecation and Sunset Headers
When a request crosses five services and the latency budget blows up, a single log line rarely tells you where
Continue readingDistributed Tracing in Go with OpenTelemetry
A message arrives that your consumer cannot parse. Maybe the producer shipped a new schema without telling anyone, maybe the
Continue readingDead Letter Queues in Kafka: Stop Poison Pills Before They Stop You
Almost every service that survives its own traffic eventually grows a cache. The idea is simple: the database is slow