Run Kafka Workloads for Cheap instead of Free

Apache Kafka has become synonymous with real-time data infrastructure. It is durable, performant, and highly scalable, capable of powering everything from financial transactions to fleet telemetry to industrial automation. It is also open source, which makes it attractive to teams seeking cost-effective ways to modernize their data pipelines. 

But “open source” and “low cost” are not the same. While Kafka itself is free to download and run, the total cost of operating Kafka at production scale is anything but negligible. From infrastructure provisioning and connector development to observability tooling and 24×7 on-call rotations, self-managed Kafka often becomes its own platform, with its own budget, its own backlog, and its own failure modes. 

This eBook explores the real economics of running Kafka in modern engineering teams. It draws from field data, internal benchmarks, and customer migration stories to illustrate what Kafka truly costs, both in terms of financial resources and engineering time. It also surfaces the risks of maintaining Kafka as infrastructure instead of building business outcomes on top of it. 

More importantly, this guide introduces a compelling alternative: Condense. Unlike Kafka distributions or hosted services, Condense is a Kafka-native, fully managed streaming platform designed for production use cases across industries like mobility, IIoT, financial services, and logistics. It runs directly inside the customer’s own cloud (BYOC), preserving data sovereignty while offering a radically simplified operating model.