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Simplifying the Management of Kubernetes with Docker Enterprise Edition

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Simplifying the Management of Kubernetes with Docker Enterprise Edition
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Back in October at DockerCon Europe, we announced that Docker will be delivering a  seamless and simplified integration of Kubernetes into the Docker platform. By integrating Kubernetes with Docker EE, we provide the choice to use Kubernetes and/or Docker Swarm for orchestration while maintaining the consistent developer to operator workflow users have come to expect from Docker. For users, this means they get an unmodified, conformant version of Kubernetes with the added value of the Docker platform including security, management, a familiar developer workflow and tooling, broad ecosystem compatibility and an adherence to industry standards including containerd and the OCI.

One of the biggest questions that we’ve been asked since we announced support for Kubernetes at  DockerCon EU –  what does this mean for an operations team that is already using Kubernetes to orchestrate containers within their enterprise? The answer is really fairly straightforward  –  Kubernetes teams using Docker EE will have the following:

  • Full access to the Kube API and all Kubernetes constructs
  • Native use of KubeCTL
  • If you are developing in Kube YML, seamless deployment
  • Ability to develop  in Docker with Compose and leverage your best practices around Kubernetes services

Docker Enterprise Edition with support for Kubernetes will be in beta this month and be generally available in February. Those who use Docker for Mac will get access to the first Docker CE edge release with Kubernetes support later this month. Docker for Windows will follow shortly thereafter.

Read the entire article here, Simplifying the Management of Kubernetes with Docker Enterprise Edition

Via the fine folks at Docker.

Categories:
Docker

Docker is an open-source project to easily create lightweight, portable, self-sufficient containers from any application. The same container that a developer builds and tests on a laptop can run at scale, in production, on VMs, bare metal, OpenStack clusters, public clouds and more.

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