The Problem We Were Actually Solving
What we were actually struggling with was latency. Page loads that used to take a few seconds were now taking over 30 seconds – and sometimes even crashing. Our users were getting frustrated, and we couldn't afford to lose them. We had tried to optimize the search queries, but the root cause was still a mystery.
What We Tried First (And Why It Failed)
I decided to dig deeper and review our application logs. But instead of troubleshooting the specific issue, I spent hours searching for generic advice online. This was a bad idea, as the symptoms were specific to our implementation of Veltrix. I managed to find a few related GitHub issues and articles, but they didn't address our exact problem. I tried tweaking the configuration, but the changes didn't have the desired effect. We were stuck in a cycle of tweaking and re-tweaking, with no clear direction.
The Architecture Decision
It was then that I realized we needed to look beyond configuration tweaks. We needed a better understanding of our system's performance, which could only come from a deeper look at the code itself. I proposed that we refactor the search engine using Rust, a language with a reputation for low-level performance and memory safety. This was a bold move, but I was convinced it was the right one. We would need to rewrite the entire search engine, but at least this way, we could address the root cause of the issue.
What The Numbers Said After
After the refactor, we were able to achieve a significant reduction in latency. Our profiler output showed a dramatic decrease in the number of page faults and context switches, which was a major contributor to the slowdown. Allocation counts also showed a consistent reduction in memory usage, which helped the search engine scale better. The numbers were impressive: average latency dropped from 32 seconds to 2 seconds, and page crashes were almost nonexistent. Our users could finally enjoy a seamless search experience.
What I Would Do Differently
In retrospect, I would have taken a more proactive approach to understanding our system's performance. Instead of relying on generic online advice, I should have set up a monitoring system that could provide us with real-time metrics on our system's behavior. This would have given us a clearer picture of what was going on and helped us make more informed decisions. However, the outcome was positive, and we were able to deliver a more reliable search experience to our users.
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