HelioCloud: A cloud-native platform for accelerating heliophysics research
, Posters

We present HelioCloud, a platform designed to offer an easy on-ramp for Heliophysics science users in the Amazon Web Services (AWS) compute environment. With the need to analyze big data, and with collaboration and Open Science becoming more of the currency of the community, it is important to find ways to facilitate the open analysis of larger data volumes in shared spaces. HelioCloud builds on a compute stack based on Pangeo, and greatly simplifies setting up a scientist-friendly AWS environment conducive to Heliophysics research. We are creating an open-source software-as-infrastructure mechanism that will allow institutions or groups to easily deploy a robust Heliophysics workbench complete with familiar code authoring tools, Jupyter Notebooks, simple and scalable parallel computing support, and data storage sharing capabilities that will foster collaboration within the community. We will present the internal architecture for HelioCloud instances, show how easy deployment can be, and how scientists can store and share data using the HelioCloud API.

See also: HelioCloud (1.2 MB)

Chris Jeschke is an Assistant Group Supervisor and Research Software Engineer within the Space Exploration Sector at Johns Hopkins Applied Physics lab, where he enjoys applying the latest in cloud technologies and software engineering tools to develop novel solutions that enable space science and exploration.