Predictive analytics tools to adjust and monitor performance metrics for the ATLAS Production System

Abstract

Having information such as an estimation of the processing time or possibility of system outage (abnormal behaviour) helps to assist to monitor system performance and to predict its next state. The current cyber-infrastructure of the ATLAS Production System presents computing conditions in which contention for resources among high-priority data analyses happens routinely, that might lead to significant workload and data handling interruptions. The lack of the possibility to monitor and to predict the behaviour of the analysis process (its duration) and system's state itself provides motivation for a focus on design of the built-in situational awareness analytic tools.

Original language	English
Article number	032051
Journal	Journal of Physics: Conference Series
Volume	1085
Issue number	3
DOIs	https://doi.org/10.1088/1742-6596/1085/3/032051
Publication status	Published - 18 Oct 2018
Externally published	Yes
Event	18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, ACAT 2017 - Seattle, United States Duration: 21 Aug 2017 → 25 Aug 2017

ASJC Scopus subject areas

Physics and Astronomy(all)

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Predictive analytics tools to adjust and monitor performance metrics for the ATLAS Production System. / Barreiro Megino, F. H.; Borodin, M.; Golubkov, D.; Grigorieva, M.; Gubin, M.; Klimentov, A.; Korchuganova, T.; Maeno, T.; Padolski, S.; Titov, M.

In: Journal of Physics: Conference Series, Vol. 1085, No. 3, 032051, 18.10.2018.

Research output: Contribution to journal › Conference article › peer-review

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abstract = "Having information such as an estimation of the processing time or possibility of system outage (abnormal behaviour) helps to assist to monitor system performance and to predict its next state. The current cyber-infrastructure of the ATLAS Production System presents computing conditions in which contention for resources among high-priority data analyses happens routinely, that might lead to significant workload and data handling interruptions. The lack of the possibility to monitor and to predict the behaviour of the analysis process (its duration) and system's state itself provides motivation for a focus on design of the built-in situational awareness analytic tools.",

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AU - Barreiro Megino, F. H.

AU - Borodin, M.

AU - Golubkov, D.

AU - Grigorieva, M.

AU - Gubin, M.

AU - Klimentov, A.

AU - Korchuganova, T.

AU - Maeno, T.

AU - Padolski, S.

AU - Titov, M.

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