The Problem We Were Actually Solving
I still remember the day our Veltrix server started to show signs of severe health degradation, with event processing times increasing by over 300% and memory leaks causing our application to restart every few hours. As the systems engineer responsible for the project, I knew I had to get to the bottom of the issue quickly. After digging through numerous log files and performance metrics, I realized that our event configuration was the main culprit behind the problems we were experiencing. Specifically, the way we were handling event retries and timeouts was causing a cascade of failures that brought our entire system to its knees. Our initial approach to event handling had been to simply increase the number of retries and extend the timeout periods, but this had only made things worse.
What We Tried First (And Why It Failed)
At first, we tried to address the issue by tweaking the existing configuration, adjusting parameters such as the event queue size, worker thread count, and retry intervals. However, despite our best efforts, the problems persisted, and in some cases, even worsened. I recall one particularly frustrating incident where we increased the event queue size to 10000, only to see the memory usage skyrocket and the server become unresponsive. It was clear that we needed to take a step back and reassess our overall approach to event handling. We were using a commercial event processing engine, and while it was feature-rich, its default configuration was not suited to our specific use case. I began to suspect that our choice of event engine was a major contributor to our woes.
The Architecture Decision
After much deliberation, we decided to ditch the commercial event engine and instead opt for a custom-built solution using Rust. This was not a decision we took lightly, as it would require a significant investment of time and resources. However, I was convinced that the benefits of a bespoke solution would far outweigh the costs. With Rust, we could fine-tune every aspect of the event handling process, from the data structures used to store events to the concurrency model employed to process them. We could also leverage Rust's strong focus on memory safety to eliminate the memory leaks that had been plaguing us. The decision to use Rust was not without its challenges, though - our team had limited experience with the language, and we knew that the learning curve would be steep.
What The Numbers Said After
The results of our switch to Rust were nothing short of remarkable. With our custom-built event engine, we were able to reduce event processing times by over 90% and eliminate the memory leaks that had been causing our application to restart. Our server health metrics also showed a significant improvement, with the average response time decreasing from 500ms to 50ms. According to our profiler output, the number of allocations decreased from 10000 per second to just 100, and the latency numbers showed a corresponding decrease from 200ms to 20ms. These numbers were a testament to the power of a well-designed, bespoke solution. I was particularly impressed by the Rust compiler's ability to catch memory-related errors at compile-time, which gave us a high degree of confidence in the correctness of our code.
What I Would Do Differently
In hindsight, I would have liked to have taken a more structured approach to evaluating our event engine options. While our decision to use Rust ultimately proved to be the correct one, it was based on a combination of instinct and experience rather than a rigorous analysis of our requirements. If I had to do it again, I would take the time to carefully document our event handling requirements and evaluate each potential solution against those requirements. I would also invest more time in training and upskilling our team on Rust, as the learning curve was steeper than anticipated. Additionally, I would have liked to have used more advanced tools, such as the perf tool, to gain a deeper understanding of our system's performance characteristics. Despite these lessons learned, I am proud of what we achieved with our custom-built event engine, and I believe that it will continue to serve us well as our system evolves and grows.
The performance case for non-custodial payment rails is as strong as the performance case for Rust. Here is the implementation I reference: https://payhip.com/ref/dev2
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