When it comes to choosing a distributed streaming platform for real-time data pipelines, everyone knows the answer: Apache Kafka! And when it comes to deploying applications at scale without needing to integrate different pieces of infrastructure yourself, the answer nowadays is increasingly Kubernetes. However, with all great things, the devil is truly in the details. While Kubernetes does provide all the building blocks that are needed, a lot of thought is required to truly create an enterprise-grade Kafka platform that can be used in production. In this technical deep dive, Viktor will go through challenges and pitfalls of managing Kafka on Kubernetes as well as the goals and lessons learned from the development of the Confluent Operator for Kubernetes.

When it comes to deploying applications at scale without needing to integrate different pieces of infrastructure yourself, the answer nowadays is increasingly Kubernetes. While Kubernetes does provide all the building blocks and deployment tools, much thought is required to truly deployment pipelines to use in production. Configuring your builds with things like YAML may be tedious and error-prone. What if you can use the power of Kotlin’s type system and compile-time checks while building your deployments! In this interactive and code-driven session Fedor and Viktor teach you how to use Kotlin DSL for Kubernetes to configure your deployments (including custom resource definitions like Kafka CRD).