Go Concurrency Hack to Handle 1M Requests/Second

The counterintuitive truth: spawning fewer goroutines actually handles more requests. Here’s the worker pool pattern that reduced our… Go Concurrency Hack to Handle 1M Requests/Second The counterintuitive truth: spawning fewer goroutines actually handles more requests. Here’s the worker pool pattern that reduced our memory usage by 85% while boosting throughput 40x. Most Go developers think more goroutines equal better performance. I believed this too — until our payment processing service crashed under Black Friday traffic, spawning 800,000+ goroutines and consuming 12GB of RAM to handle what should have been routine load. The wake-up call came when our “optimized” concurrent service performed worse than its synchronous predecessor. After diving deep into Go’s runtime mechanics and conducting extensive benchmarks, I discovered a fundamental misunderstanding that’s costing developers massive performance gains. The Million Goroutine Myth Here’s what every Go tutorial teaches: goroutines