Writing archive

"Kafka is fast" is correct but too abstract. Here is the concrete version: four cheap operations that explain why Kafka handles millions of messages without breaking a sweat.

Learn load balancing from scratch: build a production-ready load balancer with sticky sessions in Go. Complete with WebSocket support, health checking, rate limiting, and real-world deployment strategies.

Prompting is cheap, understanding is expensive, and each skipped review makes the next one harder. This is how AI-assisted velocity can quietly decouple teams from their own codebases.

What actually happens between bytes arriving on a socket and your gRPC handler running? This article walks one real request through every parsing layer — TCP, HTTP/2 frames, HPACK, gRPC envelope, protobuf — so the magic disappears.

Most explanations of queues and pub/sub start with buzzwords and skip the only question that matters: why did engineers invent these tools? This article starts from the problem, not the tool.