The Problem We Were Actually Solving
At the time, we thought our main issue was with the database, which was struggling to keep up with the load. We spent weeks optimizing the queries, indexing the tables, and even switching to a more scalable database technology. But when we finally deployed the changes, the system still stalled. It wasn't until we dug deeper that we realized the problem wasn't the database, but rather the configuration of our load balancer.
What We Tried First (And Why It Failed)
Our first attempt was to simply add more load balancers to the mix. We assumed that with more capacity, the system would be able to handle the increased load. But what we forgot to consider was the configuration of the load balancers themselves. They were defaulting to a "Round-Robin" algorithm, which was causing them to send requests to the same server repeatedly. This led to a situation known as "server thrashing," where the servers were getting hit with an overwhelming number of requests, causing them to slow down and eventually stall.
The Architecture Decision
We decided to implement the "IP Hash" algorithm in our load balancers, which sends requests to the same server based on the client's IP address. This allowed us to distribute the load more evenly across the servers, reducing the risk of server thrashing. We also implemented session persistence, which kept users on the same server throughout their session, reducing the number of requests sent to the server.
What The Numbers Said After
After implementing these changes, we saw a significant improvement in our system's performance. Our average response time decreased by 30%, and our system was able to handle the growth of 10x without stalling. Our server utilization remained stable, and we were able to add more capacity without causing server thrashing.
What I Would Do Differently
In hindsight, I would have caught the configuration issue much earlier. I would have implemented the IP Hash algorithm and session persistence from the get-go, rather than relying on a simple "Round-Robin" algorithm. I would have also implemented monitoring and alerting to catch server thrashing earlier, rather than waiting for it to cause a major outage. Had we done that, we would have avoided the costly 3am redeployments and the frustration that came with it.
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