The Problem We Were Actually Solving
What the documentation didn't tell us was that our system was going to be the bottleneck. We had thousands of concurrent users, and each user was making hundreds of requests per minute. The CPU utilization was through the roof, but the latency was still spiking to unacceptable levels during peak hours. We were stuck in a cycle of adding more servers, only to have them become overwhelmed as soon as the next growth inflection point was reached. The system was designed to scale horizontally, but it was not designed to scale cleanly.
What We Tried First (And Why It Failed)
We tried to throw more resources at the problem. We added more CPU, more memory, and more network bandwidth. We optimized our database queries, and we even rewrote the entire application in a new language that promised better performance out of the box. But no matter what we did, the system would still stall at the first growth inflection point. It wasn't until we started to dig deeper into the configuration of our caching layer that we began to understand what was really going on.
The Architecture Decision
We realized that our caching layer was not configured to handle the traffic properly. The cache expiration time was too short, and the cache size was too small. As a result, the cache was constantly being refilled, resulting in a cache thrashing scenario that was eating up all of our available CPU resources. We decided to change the caching layer to use a more robust configuration, one that would allow the cache to handle the traffic without becoming overwhelmed.
What The Numbers Said After
After making the change, our CPU utilization dropped by 30%, and our latency improved by 40%. We were able to handle twice as many concurrent users without any issues. The system was finally able to scale cleanly, without any major drops in performance. We had finally broken the cycle of adding more servers only to have them become overwhelmed as soon as the next growth inflection point was reached.
What I Would Do Differently
If I were to do it again, I would focus on the caching layer from the very beginning. I would make sure that the cache expiration time was set correctly, and that the cache size was large enough to handle the traffic. I would also make sure that the caching layer was properly configured to handle the traffic without becoming overwhelmed. By focusing on the caching layer from the start, we could have avoided the cycle of adding more servers and solving the problem at its root.
In the end, it was a hard lesson learned, but one that paid off in the end. We were able to create a system that was capable of handling the traffic without any major drops in performance. We were able to break the cycle of adding more servers only to have them become overwhelmed as soon as the next growth inflection point was reached. And we were able to do it all without breaking the bank.
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