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Confluent and Red Hat Collaborate to Deliver a Cloud-Native Data in Motion Platform for Hybrid Cloud

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Today, we are delighted to announce Confluent’s collaboration with Red Hat. This results in a complete, cloud-native experience for application developers and platform operators to set data in motion everywhere they choose to run Red Hat OpenShift.

Confluent for Kubernetes relies on an underlying Kubernetes API and runtime to perform all of the complex orchestration under the hood so our users don’t have to. Managing Kubernetes to meet enterprise Day 1 and Day 2 requirements can be a challenging endeavor. To meet this challenge, Red Hat OpenShift offers a Kubernetes-powered hybrid cloud platform that streamlines operations, builds in security features, and enables enterprises to consistently and reliably deploy and run containerized workloads across private cloud, hybrid cloud, multi-cloud, and edge environments.

Confluent for Kubernetes is a certified Red Hat OpenShift operator, available in the Red Hat Ecosystem Catalog. This offers three major benefits:

  1. Our customers can have increased confidence that the intelligent automation built into Confluent for Kubernetes runs effectively and reliably on Red Hat OpenShift
  2. By integrating with Red Hat OpenShift’s Operator Lifecycle Manager, Confluent is immediately available to be installed at the click of a button, right from the OpenShift GUI
  3. Our customers can easily discover Confluent for Kubernetes releases and Confluent Platform container images, which are fully compatible and compliant with their Red Hat OpenShift deployments

Confluent and Red Hat marketecture

Learn how to install Confluent for Kubernetes on OpenShift with the tutorial video below.

To learn more about the Confluent OpenShift certification, visit the Red Hat Ecosystem Catalog.

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  • Amit Gupta is a group manager on Confluent’s Product Management team. Prior to joining Confluent, Amit was director of product management for platform at Pivotal. Amit holds a master’s degree in mathematics from the University of California, Berkeley.

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Watch demo: Kafka streaming in 10 minutes

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