2x Performance, $300k Savings: A Case Study in Rewriting a Critical Service in Rust
In the world of high-traffic systems, success often brings its own set of challenges. During my internship at TikTok, one of our core payment services—a reliable workhorse built in Go—began showing signs of strain. As TikTok LIVE’s user base grew, the CPU load on this service climbed relentlessly, and we were confronted with incessant stability alarms from services hitting CPU thresholds. We faced a classic engineering dilemma: how do you squeeze more performance out of a critical system without compromising stability or breaking the bank? This is the story of how I tackled that challenge by selectively rewriting a performance bottleneck in Rust, resulting in a 2x performance gain and nearly $300,000 in projected annual savings in cloud costs.
Our core payment service is the backbone of our financial operations. Originally written in Go, it served us exceptionally well for years. Golang’s simplicity, concurrency model, and fast compile times make it a fantastic choice for building and iterating on the majority of our microservices.
