As Kafka evolves in your business, adopting best practices becomes a must. The GitOps methodology makes sure deployments match intended outcomes, anchored by a single source of truth. When integrating Apache Kafka with GitOps, many will think of Strimzi. Strimzi uses the Operator pattern for synchronization. This approach, whilst effective, primarily caters to Kubernetes-based Kafka resources (e.g. Topics). But this isn’t ideal.

Confluent has published official Docker containers for many years. They are the basis for deploying a cluster in Kubernetes using Confluent for Kubernetes (CFK), and one of the underpinning technologies behind Confluent Cloud. For testing, containers are convenient for quickly spinning up a local cluster with all the components required, such as Confluent Schema Registry or Confluent Control Center.

It was lovely to see so many of the community and hear about the latest data streaming initiatives at Kafka Summit this year. We always try to distill the sea of content from the industry’s premier event into a digestible blog post. This time we’ll do it slightly differently and summarize some broader learnings, not only from the sessions we saw, but the conversations we had across the two days.