Speaker
Vincent Garonne
(CERN)
Description
This paper describes a user monitoring framework for very large data management systems that maintain high numbers of data movement transactions. The proposed framework prescribes a method for generating meaningful information from collected tracing data that allows the data management system to be queried on demand for specific user usage patterns in respect to source and destination locations, period intervals, and other searchable parameters.
The feasibility of such a system at the petabyte scale is demonstrated by describing
the implementation and operational experience of an enterprise information system employing the proposed framework that uses data movement traces collected by the ATLAS data management system for operations occurring on the Worldwide LHC Computing Grid (WLCG). Our observations suggest that the proposed user
monitoring framework is capable of scaling to meet the needs of very large data management systems.
Author
Collaboration Atlas
(Atlas)
Co-authors
Angelos Molfetas
(CERN)
Cedric Serfon
(Ludwig-Maximilians-Univ. Muenchen (DE))
Graeme Andrew Stewart
(CERN)
Mario Lassnig
(CERN)
Martin Barisits
(Vienna University of Technology (AT))
Vincent Garonne
(CERN)
