Advanced science.  Applied technology.


A Prototype Cloud-Based Space Science Operations Center, 15-R6277

Principal Investigators
Keith Pickens
Inclusive Dates 
07/01/22 - Current


A space science operations center (SOC) is where scientists and data come together to do research and/or manage operations of a spacecraft. Traditionally, data is available to be analyzed or downloaded to a user’s local system for analysis. As data volumes are increasing rapidly with new generations of sensors, the process of bringing the data to each scientist for analysis is becoming unsustainable. The purpose of this research is to invert the process and push analysis software to the data.


Through a novel process known as “containerization” (where a functional piece of a system is distilled into a recipe and stored into an image), and the emergence of cloud technology, it should be possible to do many, if not all, elements of a space science operations center using a cloud-based solution. Our existing data analysis, data mining, and visualization software are to be modernized and containerized, and then deployed on the cloud. To aid in our research, as well as for security and potentially keep elements proprietary, a locally available cluster will be utilized as a “pseudo-cloud”.  


We have modernized portions of our visualization system by migrating our build system from the old SCons build system to a new CMake build system. This will aid in future migrations as well as make it possible to more easily incorporate modern libraries also utilizing CMake, which is rapidly becoming the standard of build systems. Additionally, the ability to ingest data from the Heliophysics API (HAPI) was added allowing for future data sources to be visualized without modifying the software. The development platform was then containerized and can be enhanced on any computer containing the container software, such as Docker.

An existing cluster was upgraded and Kubernetes was installed allowing the ability to deploy the developed containers in a simulated cloud-computing like environment.

Other necessary pieces have also been containerized including our bug-tracking system, continuous integration system, a web-based generic SOC, and a currently functional SOC for MMS/HPCA for deployment on the cloud. By using the HPCA SOC, this enables us to test the functionality of the changes without impacting a working SOC. Over the next few months, we will test and further refine the process for deploying on the cloud as well as testing the data mining and image analysis software on the cloud.