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| Paper: |
Big Data Architectures for Logging and Monitoring the ASTRI Mini-Array |
| Volume: |
527, Astronomical Data Analysis Software and Systems XXIX |
| Page: |
335 |
| Authors: |
Sciacca, E.; Costa, A.; Tosti, G.; Schwarz, J.; Bruno, P.; Calanducci, A.; Grillo, A.; Vitello, F.; Becciani, U.; Riggi, S.; Conforti, V.; Gianotti, F. |
| Abstract: |
The ASTRI Mini-Array is being developed by INAF as a pathfinder array for Cherenkov astronomy in the TeV energy range.
The array is expected to produce a large volume of technical and logging data. In the last few years several “Big Data” technologies have been developed to deal with a huge amount of data, e.g. in the Internet of Things (IoT) framework.
We are comparing different stacks of Big Data/IoT architectures including high performance distributed messaging systems, time series databases, streaming systems, interactive data visualization. The main aim is to classify these technologies based on a set of use cases typically related to the data produced in the astronomical environment, with the objective to have a system that can be updated, maintained and customized with a minimal programming effort.
We present the preliminary results obtained, using different Big Data stack solution to manage some use cases related to quasi real-time collection, processing and storage of the technical data, logging and technical alert produced by the ASTRI Mini-Array. |
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