Chapter 3. Camel K

Red Hat Integration - Camel K is available as a Technology Preview feature in Red Hat Integration 2020-Q2. Camel K is a lightweight integration framework built from Apache Camel K that runs natively in the cloud on OpenShift. Camel K is specifically designed for serverless and microservice architectures. You can use Camel K to instantly run integration code written in Camel Domain Specific Language (DSL) directly on OpenShift.

Using Camel K with OpenShift Serverless and Knative, containers are automatically created only as needed and are autoscaled under load up and down to zero. This removes the overhead of server provisioning and maintenance and enables you to focus instead on application development.

Using Camel K with OpenShift Serverless and Knative Eventing, you can manage how components in your system communicate in an event-driven architecture for serverless applications. This provides flexibility and creates efficiencies using a publish/subscribe or event-streaming model with decoupled relationships between event producers and consumers.

Important

Technology Preview features are not supported with Red Hat production service-level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend implementing any Technology Preview features in production environments.

This Technology Preview feature provides early access to upcoming product innovations, enabling you to test functionality and provide feedback during the development process. For more information about support scope, see Technology Preview Features Support Scope.

3.1. Camel K features

The Camel K Technology Preview provides cloud-native integration with the following main features:

  • OpenShift Continer Platform 4.3
  • OpenShift Serverless 1.7
  • Knative Serving for autoscaling and scale-to-zero
  • Knative Eventing for event-driven architectures
  • Java 11
  • Performance optimizations using Quarkus 1.3 Java runtime
  • Camel integrations written in Java, XML, or YAML DSL
  • Development tooling with Visual Studio Code