We found Kafka clusters waste up to 97% of data transfer and up to 60% of CPU, memory, and storage due to unoptimized client configurations.

Kafka isn't the problem anymore. Your apps are. And in this post, I’ll show you exactly how—and why—that’s the case.

The Myth of Server-Side Fixes

Back when I first started building high-velocity data systems, it was almost a rite of passage to blame Kafka brokers when something went sideways. Throughput issues? “Let’s add partitions.” High latencies? “Probably broker overload.” But as it turns out, we were often fixing the wrong end of the pipe.

There’s a persistent myth that is slowly being broken in the Kafka world: that performance problems are caused by infrastructure.

Another angle no one speaks about is efficiency. A bit of a vauge word that can be interpret differently by different people, but this is the front I care the most.

The inner system of Kafka Clients

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