The Problem We Were Actually Solving
We were trying to build an event-driven system that would allow users to create, manage, and execute treasure hunts. These treasure hunts were essentially complex games with various challenges and clues that users had to solve in a set order. Our engine was responsible for receiving the events triggered by user actions, processing them, and updating the game state accordingly.
However, as our system grew in complexity, it became increasingly hard to manage. We were using a mix of Node.js and a custom-built event store, which made it difficult to reason about our system's behavior. We were getting event handling errors, timeouts were being triggered, and our users were getting frustrated.
What We Tried First (And Why It Failed)
We tried to add more event listeners to our code, thinking that this would improve our system's responsiveness. We also attempted to implement a caching layer to reduce the load on our database. But these attempts only made things worse. Our code became more complex, our errors more cryptic, and our latency numbers remained stuck at unacceptable levels.
We also tried to blame the database for our troubles, thinking that it was the bottleneck in our system. We implemented some complex query optimization techniques and even upgraded our database engine, but these changes only yielded minor improvements. We were stuck in a vicious cycle of adding more complexity to our system without making any meaningful progress.
The Architecture Decision
It was then that we realized that our real problem wasn't the database or the event store. It was our language and our architecture. We were using Node.js, which, while great for building small-scale applications, wasn't the best choice for a complex, event-driven system like ours. We decided to switch to Rust, a language that would allow us to write more concurrent, more memory-safe, and more composable code.
We also decided to adopt a more functional programming style, which would enable us to write more predictable and composable code. We chose to use the Tokio event loop library, which would give us a high-level abstraction for handling asynchronous events. These changes were not without cost, however. We had to relearn a new language and architecture, and our development pace slowed significantly.
What The Numbers Said After
After switching to Rust and adopting a more functional programming style, our system's performance improved dramatically. Our latency numbers dropped from an average of 3 seconds to under 200 milliseconds, and our error rates plummeted. We were able to handle 5,000 concurrent users without breaking a sweat.
Our metrics for event handling improved as well. We saw a 90% reduction in event handling errors and a 95% reduction in timeouts. Our users were happier, and our engineering team was relieved.
What I Would Do Differently
In hindsight, I would have switched to Rust and adopted a more functional programming style earlier. I would have also taken a more structured approach to event handling from the start, using a library like Tokio to handle asynchronous events. I would have also invested more time in learning how to write concurrent code in Rust, rather than using it as a last resort.
Our experience with the treasure hunt engine was a hard-won lesson in the importance of choosing the right language and architecture for a complex system. It's a lesson that I'll carry with me for the rest of my career.