Every enterprise is modernizing their business systems and applications to respond to real-time data. Within the next few years, we predict that most of an enterprise's data products will be built using a streaming fabric – a rich tapestry of real-time data, abstracted from the infrastructure it runs on. This streaming fabric spans not just one Apache Kafka cluster, but dozens, hundreds, maybe even thousands of them.

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.