Showing entries tagged [docker]

AMS Short Course on Reproducible Atmospheric Science Workflows

AMS

Unidata community members Ivo Jimenez and Dr. Carlos Maltzahn from the University of California, Santa Cruz, along with Kevin Tyle from the University at Albany, will be presenting an AMS Short Course titled Reproducible Atmospheric Science Workflows Using Open Source Tools: An Introduction to the Popper Experimentation Protocol. The course focuses on an exciting new open-source toolset developed by researchers at UC Santa Cruz with specific tie-ins to reproducible workflows in atmospheric science modeling using the Weather Research and Forecasting model (WRF), both in research and the classroom.

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CloudStream — An Application Streaming Docker Framework

In November of 2015, Unidata released CloudIDV, a cloud-optimized version of the IDV. Since then, our community has expressed interest in the underlying application-streaming technology. In the words of one developer, "We all have legacy software that we'd like to support on new devices." Motivated by this observation, we have released CloudStream. CloudStream allows a developer or scientist to easily package software and/or a custom linux environment in such a way that it becomes ready for use in the cloud. Thanks to Docker, building software for use with CloudStream is no more difficult than configuring and building software in any standard Linux environment.

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CloudIDV: the Integrated Data Viewer in your web browser

cloudIDV
A fully-interactive IDV in a web browser.

As part of the Unidata Program Center's continuing investigations into the use of Unidata technologies in cloud computing environments, UPC developers have created a version of the Integrated Data Viewer (IDV) that runs in a Docker container and displays the IDV interface in a web browser.

The CloudIDV container can be run on any computer that has the Docker containerization software installed — currently linux, MacOSX, and Windows versions of Docker are available. If you are already running Docker on your own system, you can easily experiment with the CloudIDV container. If you're new to Docker, read on for details on how to get started.

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