Abstract
This work describes Live Monitor, the monitoring subsystem of SDDS - an automated system for space experiment data processing, storage, and distribution created at SINP MSU. Live Monitor allows operators and developers of satellite data centers to identify errors occurred in data processing quickly and to prevent further consequences caused by the errors. All activities of the whole data processing cycle are illustrated via a web interface in real-time. Notification messages are delivered to responsible people via emails and Telegram messenger service. The flexible monitoring mechanism implemented in Live Monitor allows us to dynamically change and control events being shown on the web interface on our demands. Physicists, whose space weather analysis models are functioning upon satellite data provided by SDDS, can use the developed RESTful API to monitor their own events and deliver customized notification messages by their needs.
Highlights
The ultimate goal of research in space weather is creating complex operational magnetosphereionosphere models which allow predicting the radiation risk for space satellites in different orbits, and estimating the occurrence risk of technological disasters due to magnetic storms and charged particle precipitations
We have developed a RESTful API so that physicists, whose space weather models are working based on the data supplied by SDDS, can use it to create their own monitoring scheme and deliver customized alerts to their customer
SDDS is the primary satellite data processing system being used at SINP MSU
Summary
The ultimate goal of research in space weather is creating complex operational magnetosphereionosphere models which allow predicting the radiation risk for space satellites in different orbits, and estimating the occurrence risk of technological disasters due to magnetic storms and charged particle precipitations. Solutions to the problem involve collecting data from all available satellites and ground stations, each of which measures a limited number of parameters of space weather, and generating forecasts based on the result of its analysis. Such task is challenging because data formats, storage methods, datasets and values of measured parameters differ between satellites. To achieve this goal an automated system called SDDS has been created at SINP MSU. We give a short resume of our completed work and describe our vision of the future perspective
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