Docker Engine - Enterprise on Windows Server 2019

Tidal Media Inc

Docker Engine - Enterprise on Windows Server 2019

Tidal Media Inc

Simplifies and accelerates your workflow, innovates each project

Docker Engine - Enterprise on Windows Server 2019

Docker Enterprise is the industry-leading platform for simplifying IT operations and running modern applications at scale, anywhere. On private clouds, public clouds, or bare metal. It’s a mature architecture for providing customizable, hardened, resilient, and manageable Kubernetes and/or Swarm container orchestration, where and when you need it.

This is the only enterprise-ready container platform that enables IT leaders to choose how to cost-effectively build and manage their entire application portfolio at their own pace without fear of architecture and infrastructure lock-in.

Docker container platform enables organizations to accelerate digital and multi-cloud initiatives by automating the delivery of legacy and modern applications using an agile operating model with integrated security.


Run anywhere

Docker Enterprise can run almost anywhere: on virtual machines, bare metal, or on any public cloud, and on a range of Linux and Windows operating systems.

Run securely

Built around Docker Engine – Enterprise, the enterprise version of the Docker Engine container runtime, Docker Enterprise is secure-by-default: equipped with industry-leading FIPS-140-2 encryption, and built-in Docker Content Trust, to prevent the execution of improperly-signed or unsigned container workloads.

Run Windows-native Docker container workloads

Docker Enterprise worker nodes can be deployed on Windows Server 2019 with Docker Engine – Enterprise for Windows. Easily tag and configure workloads for execution on appropriate node types, and run any mix of Windows and Linux worker nodes within the same Docker Enterprise environments.

Specialized hardware support

Docker Engine – Enterprise can easily be configured to make use of specialized hardware in bare metal and virtual environments, including FPGAs and GPUs, making them ideal for research, scientific computing, and machine learning.

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