HAPI is a standard for serving time series data. It was developed with Heliophysics in mind, but has been kept as generic as possible and is likely useful in other areas of solar system exploration and astronomy. We present the basics of the standard (RESTful request and response interface with a streaming data format), and show how it has been adopted by various data centers in Heliophysics and Planetary Science, both in the US and Europe. We will also describe the various clients that are available for reading HAPI data. We aim to dialog with the astronomy community about the relevance of HAPI for serving time series data at various astronomical archives, as well as use of HAPI by astronomy software as a way to gain more uniform access to Heliophysics and other data sources.

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.