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Preparing distributed computing operations for HL-LHC era with Operational Intelligence

The Operational Intelligence (OpInt) project is a joint effort from various WLCG communities aimed at increasing the level of automation in computing operations and reducing human interventions. The currently deployed systems have proven to be mature and capable of meeting the experiment goals, by a...

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Autores principales: Di Girolamo, Alessandro, Legger, Federica, Paparrigopoulos, Panos, Schovancova, Jaroslava, Beermann, Thomas Alfons, Boehler, Michael, Bonacorsi, Daniele, Clissa, Luca, Diotalevi, Tommaso, Giommi, Luca, Giordano, Domenico, Hohn, David, Javurek, Tomas, Jezequel, Stephane, Kuznetsov, Valentin Y, Lassnig, Mario, Olocco, Micol, Padolski, Siarhei, Rinaldi, Lorenzo, Sharma, Mayank, Nikodemas, Tuckus, Decker de Sousa, Leticia, Grigorieva, Maria, Mageirakos, Vasilis
Lenguaje:eng
Publicado: 2021
Materias:
Acceso en línea:http://cds.cern.ch/record/2752591
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author Di Girolamo, Alessandro
Legger, Federica
Paparrigopoulos, Panos
Schovancova, Jaroslava
Beermann, Thomas Alfons
Boehler, Michael
Bonacorsi, Daniele
Clissa, Luca
Diotalevi, Tommaso
Giommi, Luca
Giordano, Domenico
Hohn, David
Javurek, Tomas
Jezequel, Stephane
Kuznetsov, Valentin Y
Lassnig, Mario
Olocco, Micol
Padolski, Siarhei
Rinaldi, Lorenzo
Sharma, Mayank
Nikodemas, Tuckus
Decker de Sousa, Leticia
Grigorieva, Maria
Mageirakos, Vasilis
author_facet Di Girolamo, Alessandro
Legger, Federica
Paparrigopoulos, Panos
Schovancova, Jaroslava
Beermann, Thomas Alfons
Boehler, Michael
Bonacorsi, Daniele
Clissa, Luca
Diotalevi, Tommaso
Giommi, Luca
Giordano, Domenico
Hohn, David
Javurek, Tomas
Jezequel, Stephane
Kuznetsov, Valentin Y
Lassnig, Mario
Olocco, Micol
Padolski, Siarhei
Rinaldi, Lorenzo
Sharma, Mayank
Nikodemas, Tuckus
Decker de Sousa, Leticia
Grigorieva, Maria
Mageirakos, Vasilis
author_sort Di Girolamo, Alessandro
collection CERN
description The Operational Intelligence (OpInt) project is a joint effort from various WLCG communities aimed at increasing the level of automation in computing operations and reducing human interventions. The currently deployed systems have proven to be mature and capable of meeting the experiment goals, by allowing timely delivery of scientific results. However, a substantial number of interventions from software developers, shifters and operational teams is needed to efficiently manage such heterogeneous infrastructures. Under the scope of the OpInt project experts from most of the relevant areas have gathered to propose and work on “smart” solutions. Machine learning, data mining, log analysis, and anomaly detection are only some of the tools we have evaluated for our use cases. Discussions have led to a number of ideas on how to achieve our goals and the development of solutions has started. In this contribution, we will report on the development of a suite of OpInt services to cover various use cases: workload management, data management, and site operations.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2021
record_format invenio
spelling cern-27525912022-08-23T09:03:32Zhttp://cds.cern.ch/record/2752591engDi Girolamo, AlessandroLegger, FedericaPaparrigopoulos, PanosSchovancova, JaroslavaBeermann, Thomas AlfonsBoehler, MichaelBonacorsi, DanieleClissa, LucaDiotalevi, TommasoGiommi, LucaGiordano, DomenicoHohn, DavidJavurek, TomasJezequel, StephaneKuznetsov, Valentin YLassnig, MarioOlocco, MicolPadolski, SiarheiRinaldi, LorenzoSharma, MayankNikodemas, TuckusDecker de Sousa, LeticiaGrigorieva, MariaMageirakos, VasilisPreparing distributed computing operations for HL-LHC era with Operational IntelligenceParticle Physics - ExperimentThe Operational Intelligence (OpInt) project is a joint effort from various WLCG communities aimed at increasing the level of automation in computing operations and reducing human interventions. The currently deployed systems have proven to be mature and capable of meeting the experiment goals, by allowing timely delivery of scientific results. However, a substantial number of interventions from software developers, shifters and operational teams is needed to efficiently manage such heterogeneous infrastructures. Under the scope of the OpInt project experts from most of the relevant areas have gathered to propose and work on “smart” solutions. Machine learning, data mining, log analysis, and anomaly detection are only some of the tools we have evaluated for our use cases. Discussions have led to a number of ideas on how to achieve our goals and the development of solutions has started. In this contribution, we will report on the development of a suite of OpInt services to cover various use cases: workload management, data management, and site operations.ATL-SOFT-PROC-2021-001oai:cds.cern.ch:27525912021-02-19
spellingShingle Particle Physics - Experiment
Di Girolamo, Alessandro
Legger, Federica
Paparrigopoulos, Panos
Schovancova, Jaroslava
Beermann, Thomas Alfons
Boehler, Michael
Bonacorsi, Daniele
Clissa, Luca
Diotalevi, Tommaso
Giommi, Luca
Giordano, Domenico
Hohn, David
Javurek, Tomas
Jezequel, Stephane
Kuznetsov, Valentin Y
Lassnig, Mario
Olocco, Micol
Padolski, Siarhei
Rinaldi, Lorenzo
Sharma, Mayank
Nikodemas, Tuckus
Decker de Sousa, Leticia
Grigorieva, Maria
Mageirakos, Vasilis
Preparing distributed computing operations for HL-LHC era with Operational Intelligence
title Preparing distributed computing operations for HL-LHC era with Operational Intelligence
title_full Preparing distributed computing operations for HL-LHC era with Operational Intelligence
title_fullStr Preparing distributed computing operations for HL-LHC era with Operational Intelligence
title_full_unstemmed Preparing distributed computing operations for HL-LHC era with Operational Intelligence
title_short Preparing distributed computing operations for HL-LHC era with Operational Intelligence
title_sort preparing distributed computing operations for hl-lhc era with operational intelligence
topic Particle Physics - Experiment
url http://cds.cern.ch/record/2752591
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