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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...
Autores principales: | , , |
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Lenguaje: | eng |
Publicado: |
2018
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2649121 |
_version_ | 1780960716464848896 |
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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 |
work_keys_str_mv | AT alexandrovevgeny bigdatatoolsforthemonitoringoftheatlaseventindex AT kazymovandrei bigdatatoolsforthemonitoringoftheatlaseventindex AT prokoshinfedor bigdatatoolsforthemonitoringoftheatlaseventindex |