Kubermatic Kubernetes Platform 2.16 Delivers on State of The-Art Policy Enforcement

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Kubermatic Kubernetes Platform 2.16 Delivers on State of The-Art Policy Enforcement

Kubermatic, a leading Kubernetes automation provider that simplifies cloud native operations at scale, today released Kubermatic Kubernetes Platform (KKP) 2.16. The open source platform gives IT teams the ability to fully automate the management of Kubernetes clusters across multi-cloud, on-premise, edge, and IoT environments. The 2.16 release introduces an out-of-the-box integration of the Open Policy Agent (OPA) for policy-based control across microservices, Kubernetes, CI/CD pipelines, API gateways, and more. OPA is an official CNCF project that graduated last week, thanks to its wide adoption in production by organizations such as Goldman Sachs, Netflix, T-Mobile, and many others.

“As enterprise cloud native adoption accelerates, it becomes increasingly essential for organizations across the globe to have access to policy enforcement tools that are particularly designed and built for cloud native environments. With the KKP 2.16 release, we are proud to deliver on our promise to always provide our customers with best-in-class open source technologies,” says Kubermatic CEO Sebastian Scheele. “Thanks to OPA’s streamlined policy language, our customers can now benefit from considerably facilitated policy enforcement across the entire stack.”

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In addition to that, KKP 2.16 features a number of improvements designed to bolster enterprise security, streamline operations and favour GitOps approaches, including:

  • Dynamic Data Centers and Other Enhanced Admin Configurations: Dynamic data centers and other improved Preset Management functionalities allow administrators to deliver a better and more secure user experience for everyone. All configurations can be adjusted in the KKP UI or via Infrastructure-as-Code, helping organizations to deliver on their GitOps approach.
  • Machine Learning the Cloud Native Way: Machine learning workloads will increasingly move towards the cloud for its ability to scale on demand. As the de facto standard for orchestrating containerized workloads in the cloud, Kubernetes is the perfect match for ML and data science. KKP 2.16 adds a Kubeflow integration to give operators the possibility to easily roll out the Kubeflow platform on top of KKP.
  • Optimized Infrastructure With ARM Support: ARM-powered data centers and edge scenarios are enjoying increasing popularity for their system optimization and cost reduction potential. KKP 2.16 enables ARM support so organizations can effortlessly deploy and manage ARM-based clusters from the central KKP interface.