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Leveraging a Cloud Native technology stack, Banzai Cloud Supertubes is the ultimate deployment tool for setting up and operating production-ready Kafka clusters on Kubernetes. While Supertubes installs and manages all the infrastructure components of a production-ready Kafka cluster on Kubernetes (like Zookeeper, the Banzai Cloud Kafka operator, Envoy, etc) it also includes several convenience components, like Schema Registry, multiple disaster recovery options, Cruise Control and lots more. The list of Supertubes features is very long and covers everything you need to self host and run a production-ready Kafka cluster on Kubernetes.
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tl;dr: The Supertubes approach to handling Kafka ACLs in Kubernetes provides a clearer way of seeing what’s actually happening by introducing a logical separation of ACL components under the names: KafkaACL, KafkaRole and KafkaResourceSelector. That way we get reusable parts that help maintain the system in the long term, allowing us to handle ACLs with a declarative approach, and overcoming the difficulties inherent in handling ACLs in a Kubernetes environment.
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If you are a frequent reader of our blog, or if you’ve been using the open source Banzai Cloud Kafka operator, you might already be familiar with Supertubes, our product that delivers Kafka as a service on Kubernetes.

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Running Kafka on Istio with mTLS is, in of itself, an interesting topic, but before we can talk about how Banzai Cloud’s Supertubes allows us to do that, let’s take a step back and look at how SSL works in Kafka. Maybe then we can answer the question, why do we need Kafka in Istio with mTLS at all? Supertubes is Banzai Cloud’s Kafka as a Service, which runs on Kubernetes inside an Istio service mesh.
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It’s no news that for quite a while our Kafka on Kubernetes take, Supertubes has been happily running inside an Istio-based service mesh, in both single or multi-cluster setups across hybrid clouds. While we have touched on several aspects of the advantages Istio gave us, this post’s aim is to collect some of the issues, cornerstones and benefits. We see the service mesh as a key component of every modern Cloud Native stack.
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It’s been some time since we open sourced our Kafka Operator, an operator designed from square one to take advantage of the full potential of Kafka on Kubernetes, and have built Supertubes on top to manage Kafka for our customers. One of the most requested enterprise feature has been the implementation of rolling upgrades. Built on the Banzai Cloud’s Kafka operator, Supertubes adds support and orchestrates these upgrades. Accordingly, in today’s blog we’re going to take a deep dive into the technical details of how the operator handles an update and how you can use Supertubes to seamlessly upgrade to the newest 2.
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In one of the earlier Kafka disaster recovery on Kubernetes with CSI post we discussed how brokers of an Apache Kafka clusters can be backed up and restored leveraging Kubernetes volume snapshots. While this solution provides a good enough disaster recovery option (and a super quick recovery), it doesn’t help when the entire Kubernetes cluster hosting the Kafka cluster is lost. In this post, we show you how to: back up a Kafka cluster to a remote Kafka cluster running on a separate Kubernetes cluster, and also how to recover the lost Kafka cluster with Supertubes.
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Apache Kafka was designed with a heavy emphasis on fault-tolerance and high-availability in mind, and thus provides different methods of ensuring enterprise-grade resiliency such as: replication factor - which defines how many partition replicas of a topic should be kept, each one being stored on a different broker. A replication factor of N allows for the loss of N-1 brokers. The new brokers will replace the lost brokers until the number of remaining broker(s) reaches the replication factor, or the number of copies of the partitions of a topic.
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Apache Kafka is a distributed streaming platform used to build reliable, scalable and high-throughput real-time streaming systems. Its capabilities, while impressive, can be further improved through the addition of Kubernetes. Accordingly, we’ve built an open-source Kafka operator and Supertubes to run and seamlessly operate Kafka on Kubernetes through its various features, like fine-grain broker configuration, metrics based scaling with rebalancing, rack awareness, and graceful rolling upgrades - just to name a few.
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