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At Banzai Cloud we use Kafka internally a lot. We have some internal systems and customer reporting deployments where we rely heavily on Kafka deployed to Kubernetes. We practice what we preach and all these deployments (not just the external ones) are done using our application platform, Pipeline. There is one difference between regular Kafka deployments and ours (though it is not relevant to this post): we have removed Zookeeper and use etcd instead.

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Kubeless was designed to be a Kubernetes-native serverless framework, and, for PubSub functions, uses Apache Kafka behind the scenes. At Banzai Cloud we like cloud-native technologies, however, we weren’t happy about having to operate a Zookeeper cluster on Kubernetes, so we modified and open-sourced a version for Kafka in which we replaced Zookeeper with etcd, which was (and still is) a better fit. This post is part of our serverless series, which discusses deploying Kubeless, using Kafka on etcd with Pipeline, and deploying a so called PubSub function.

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At Banzai Cloud we are building a cloud agnostic, open source next generation CloudFoundry/Heroku-like PaaS, Pipeline, while running several big data workloads natively on Kubernetes. Apache Kafka is one of the cloud native workloads we support out-of-the-box, alongside Apache Spark and Apache Zeppelin. If you’re interested in running big data workloads on Kubernetes, please read the following blog series as well. Apache Kafka on Kubernetes series: Kafka on Kubernetes with Local Persistent Volumes Monitoring Apache Kafka with Prometheus

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This post is part of the Debug 101 series. If you missed the previous post in this series, check it out here: Nodes successfully joined, not! We’re in the middle of deploying Apache Kafka to Kubernetes the cloud native-way - by totally removing the Zookeeper dependency and using etcd, instead. This means that service registry/discovery and other internal Kafka to Zookeeper operations will be dispatched to a pre-existing etcd cluster.

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