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BigData tools for the monitoring of the ATLAS EventIndex

The ATLAS EventIndex collects event information from data both at CERN and Grid sites. It uses the Hadoop system to store the results, and web services to access them. Its successful operation depends on a number of different components, that have to be monitored constantly to ensure continuous oper...

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Detalles Bibliográficos
Autores principales: Alexandrov, Evgeny, Kazymov, Andrei, Prokoshin, Fedor
Lenguaje:eng
Publicado: 2018
Materias:
Acceso en línea:http://cds.cern.ch/record/2649121
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author Alexandrov, Evgeny
Kazymov, Andrei
Prokoshin, Fedor
author_facet Alexandrov, Evgeny
Kazymov, Andrei
Prokoshin, Fedor
author_sort Alexandrov, Evgeny
collection CERN
description The ATLAS EventIndex collects event information from data both at CERN and Grid sites. It uses the Hadoop system to store the results, and web services to access them. Its successful operation depends on a number of different components, that have to be monitored constantly to ensure continuous operation of the system. Each component has completely different sets of parameters and states and requires a special approach. A scheduler runs monitoring tasks, which gather information by various methods: querying databases, web sites and storage systems, parsing logs and using CERN host monitoring services. Information is then fed to Grafana dashboards via InfluxDB. Using this platform allowed much faster performance and flexibility compared to the previously used Kibana system.
id cern-2649121
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2018
record_format invenio
spelling cern-26491212019-09-30T06:29:59Zhttp://cds.cern.ch/record/2649121engAlexandrov, EvgenyKazymov, AndreiProkoshin, FedorBigData tools for the monitoring of the ATLAS EventIndexParticle Physics - ExperimentThe ATLAS EventIndex collects event information from data both at CERN and Grid sites. It uses the Hadoop system to store the results, and web services to access them. Its successful operation depends on a number of different components, that have to be monitored constantly to ensure continuous operation of the system. Each component has completely different sets of parameters and states and requires a special approach. A scheduler runs monitoring tasks, which gather information by various methods: querying databases, web sites and storage systems, parsing logs and using CERN host monitoring services. Information is then fed to Grafana dashboards via InfluxDB. Using this platform allowed much faster performance and flexibility compared to the previously used Kibana system.ATL-SOFT-PROC-2018-040oai:cds.cern.ch:26491212018-11-27
spellingShingle Particle Physics - Experiment
Alexandrov, Evgeny
Kazymov, Andrei
Prokoshin, Fedor
BigData tools for the monitoring of the ATLAS EventIndex
title BigData tools for the monitoring of the ATLAS EventIndex
title_full BigData tools for the monitoring of the ATLAS EventIndex
title_fullStr BigData tools for the monitoring of the ATLAS EventIndex
title_full_unstemmed BigData tools for the monitoring of the ATLAS EventIndex
title_short BigData tools for the monitoring of the ATLAS EventIndex
title_sort bigdata tools for the monitoring of the atlas eventindex
topic Particle Physics - Experiment
url http://cds.cern.ch/record/2649121
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AT kazymovandrei bigdatatoolsforthemonitoringoftheatlaseventindex
AT prokoshinfedor bigdatatoolsforthemonitoringoftheatlaseventindex