Patterns and Techniques for Writing High-Performance Applications with Go

Every Go developer eventually hits the same wall: your code works, but it's not fast enough. You've optimized your algorithms, removed unnecessary loops, and still—something's off. More often than not, the culprit is hiding in plain sight: excessive heap allocations. In this guide, I'll show you exactly how Go decides where to put your variables, why it matters for performance, and how to fix the most common allocation mistakes I've seen in production codebases. The Hidden Cost of Memory Allo

Learn more about why developers end up with deeply recursive Go code and what can be done to mitigate stack exhaustion issues.

The Integrity Data Platform team at Grab rewrote a QPS-heavy Golang microservice in Rust, achieving 70% infrastructure savings while maintaining similar performance. This initiative explored the ROI of adopting Rust for production services, balancing efficiency gains against challenges like Rust’s steep learning curve and the risks of rewriting legacy systems. The blog delves into the selection process, approach, pitfalls, and the ultimate business value of the rewrite.

Performance comparison of different fan-in implementations in Golang

Patterns and Techniques for Writing High-Performance Applications with Go

In this article we will look into optimizing memory usage and CPU performance by designing our Go structs with the CPU word size and cache line size in mind.

Or, speeding up writing binary data in Go by 14x. Code here.

I’m going to show you how I took a very simple program and made it run almost 5 times faster, with very minimal adjustments. You may know…