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Predictive analytics tools to adjust and monitor performance metrics for the ATLAS Production System
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 presents computing conditions in which contention for resources among hig...
Autores principales: | , , , , , , , , , |
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Lenguaje: | eng |
Publicado: |
2017
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1088/1742-6596/1085/3/032051 http://cds.cern.ch/record/2290126 |
Sumario: | 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 presents computing conditions in which contention for resources among high-priority data analysis 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 caused to focus on design of the built-in situational awareness analytic tools. |
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