Chapter 3. Technology previews

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Technology Preview features are not supported with Red Hat production service-level agreements (SLAs) and might not be functionally complete; therefore, 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. OAuth 2.0 authorization


This is a Technology Preview feature.

If you are using OAuth 2.0 for token-based authentication, you can now also use Keycloak to configure authorization rules to constrain client access to Kafka brokers.

Red Hat Single Sign-On 7.3 does not support this Technoloy Preview of OAuth 2.0 token-based authorization. If you wish to try this feature, it is tested for use in a development environment with Keycloak 8.0.2 as the authorization server.

AMQ Streams supports the use of OAuth 2.0 token-based authorization through Keycloak Authorization Services, which allows you to manage security policies and permissions centrally.

Security policies and permissions defined in Keycloak are used to grant access to resources on Kafka brokers. Users and clients are matched against policies that permit access to perform specific actions on Kafka brokers.

See Using OAuth 2.0 token-based authorization.

3.2. Service Registry


This is a Technology Preview feature.

You can use Service Registry as a centralized store of service schemas for data streaming. For Kafka, you can use Service Registry to store Apache Avro or JSON schema.

Service Registry provides a REST API and a Java REST client to register and query the schemas from client applications through server-side endpoints.

Using Service Registry decouples the process of managing schemas from the configuration of client applications. You enable an application to use a schema from the registry by specifying its URL in the client code.

For example, the schemas to serialize and deserialize messages can be stored in the registry, which are then referenced from the applications that use them to ensure that the messages that they send and receive are compatible with those schemas.

Kafka client applications can push or pull their schemas from Service Registry at runtime.

See Managing schemas with Service Registry.

3.3. MirrorMaker 2.0


This is a Technology Preview feature.

You can now use MirrorMaker 2.0 with AMQ Streams.

MirrorMaker 2.0 is based on the Kafka Connect framework, connectors managing the transfer of data between clusters.

MirrorMaker 2.0 uses:

  • Source cluster configuration to consume data from the source cluster
  • Target cluster configuration to output data to the target cluster

MirrorMaker 2.0 introduces an entirely new way of replicating data in clusters. If you choose to use MirrorMaker 2.0, there is currently no legacy support, so any resources must be manually converted into the new format.


For this Technology Preview, all connectors are currently restarted for every reconcile of the MirrorMaker 2.0 operator. This does not affect the functionality, but it does affect the performance.

See Using AMQ Streams with MirrorMaker 2.0.

3.4. OpenShift 4.x disconnected installation


This is a Technology Preview feature.

You can perform a disconnected installation of AMQ Streams when your OpenShift cluster is being used as a disconnected cluster on a restricted network.

For a disconnected installation, you obtain the required images and push them to your container registry locally. If you are using the Operator Lifecycle Manager (OLM) this means disabling the default sources used by the OperatorHub and creating local mirrors to install AMQ Streams from local sources.

See Using Operator Lifecycle Manager on restricted networks.

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