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 production rate limiter has two layers. The first layer is the algorithm: token bucket, leaky bucket, fixed window, sliding
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
Every public API has a ceiling. Whether you’re running a SaaS platform, a microservice cluster, or a simple REST endpoint,
Every production service eventually faces the same question: how do you protect it from being overwhelmed? Whether it’s a sudden
Continue readingThe Art of Rate Limiting: 4 Algorithms Every Engineer Should Know