import chaos

The goal of this article is to build a robust concurrent leaderboard in Go that can handle thousands of simultaneous updates from multiple goroutines, serve frequent Top-N queries efficiently, and maintain predictable snapshots of scores despite concurrent writes. We will balance theory with hands-on implementation, so you will not only see the code but also understand why each design decision matters under concurrent workloads.

For my blog posts, I often need to create diagrams and flowcharts. I like using Mermaid for this, but I just couldn't find a free online tool without limitations, so I built one myself.

Ffetch v1.2 is out. It's a lightweight, production-ready TypeScript-first drop-in replacement for native fetch.

Go channels are one of the language's signature features. They provide a structured way for goroutines to communicate and coordinate. Instead of manually sharing memory and managing locks, channels let goroutines send and receive values directly, ensuring that data is transferred correctly and synchronization is handled automatically.

Concurrency is Go's crown jewel - goroutines and channels make concurrent programming feel almost magical. But not every problem belongs in a channel. Many developers fall into the trap of overusing channels or misusing mutexes, resulting in slow, buggy, or unmaintainable code. In this article, we'll demystify **when to use channels and when to use mutexes**, and why blindly following Go concurrency patterns can backfire.