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1.
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WLCG Dashboards with Unified Monitoring
/ Andrade, Pedro (CERN) ; Aimar, Alberto (CERN) ; Brundu, Simone (CERN) ; Bear, Borja Garrido (CERN) ; Borge, Gonzalo Menendez (CERN) ; Magnoni, Luca (CERN) ; Nicolau, Diogo Lima (CERN) ; Tsvetkov, Nikolay (CERN)
Monitoring of the CERN Data Centres and the WLCG infrastructure is now largely based on the new monitoring infrastructure provided by CERN IT. This is the result of the migration from several old in-house developed monitoring tools into a common monitoring infrastructure based on open source technologies such as Collectd, Flume, Kafka, Spark, InfluxDB, Grafana and others. [...]
2020 - 6 p.
- Published in : EPJ Web Conf. 245 (2020) 07049
Fulltext from publisher: PDF;
In : 24th International Conference on Computing in High Energy and Nuclear Physics, Adelaide, Australia, 4 - 8 Nov 2019, pp.07049
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2.
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Erratic server behavior detection using machine learning on streams of monitoring data
/ Adam, Martin (ASCR, Prague) ; Magnoni, Luca (CERN) ; Pilát, Martin (Charles U., Prague (main)) ; Adamová, Dagmar (ASCR, Prague)
With the explosion of the number of distributed applications, a new dynamic server environment emerged grouping servers into clusters, utilization of which depends on the current demand for the application. To provide reliable and smooth services it is crucial to detect and fix possible erratic behavior of individual servers in these clusters. [...]
2020 - 8 p.
- Published in : EPJ Web Conf. 245 (2020) 07002
Fulltext: PDF;
In : 24th International Conference on Computing in High Energy and Nuclear Physics, Adelaide, Australia, 4 - 8 Nov 2019, pp.07002
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3.
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4.
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5.
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MONIT: Monitoring the CERN Data Centres and the WLCG Infrastructure
/ Aimar, Alberto (CERN) ; Aguado Corman, Asier (Oviedo U.) ; Andrade, Pedro (CERN) ; Delgado Fernandez, Javier (CERN) ; Garrido Bear, Borja (CERN) ; Karavakis, Edward (CERN) ; Kulikowski, Dominik Marek (Wroclaw Tech. U.) ; Magnoni, Luca (CERN)
The new unified monitoring architecture (MONIT) for the CERN Data Centres and for the WLCG Infrastructure is based on established open source technologies to collect, stream, store and access monitoring data. The previous solutions, based on in-house development and commercial software, have been replaced with widely- recognized technologies such as Collectd, Kafka, Spark, Elasticsearch, InfluxDB, Grafana and others. [...]
2019 - 8 p.
- Published in : EPJ Web Conf. 214 (2019) 08031
Fulltext from publisher: PDF;
In : 23rd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2018, Sofia, Bulgaria, 9 - 13 Jul 2018, pp.08031
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6.
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Detection of erratic behavior in load balanced clusters of servers using a machine learning based method
/ Adam, Martin (ASCR, Prague ; CERN) ; Magnoni, Luca (CERN) ; Pilát, Martin (Charles U.) ; Adamová, Dagmar (ASCR, Prague)
With the explosion of the number of distributed applications, a new dynamic server environment emerged grouping servers into clusters, whose utilization depends on the current demand for the application. To provide reliable and smooth services it is crucial to detect and fix possible erratic behavior of individual servers in these clusters. [...]
2019 - 6 p.
- Published in : EPJ Web Conf. 214 (2019) 08030
Fulltext from publisher: PDF;
In : 23rd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2018, Sofia, Bulgaria, 9 - 13 Jul 2018, pp.08030
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7.
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8.
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9.
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Unified Monitoring Architecture for IT and grid services
/ Aimar, A (CERN) ; Aguado Corman, A (CERN) ; Andrade, P (CERN) ; Belov, S (Dubna, JINR) ; Delgado Fernandez, J (CERN) ; Garrido Bear, B (CERN) ; Georgiou, M (CERN) ; Karavakis, E (CERN) ; Magnoni, L (CERN) ; Rama Ballesteros, R (CERN) et al.
This paper provides a detailed overview of the Unified Monitoring Architecture (UMA) that aims at merging the monitoring of the CERN IT data centres and the WLCG monitoring using common and widely-adopted open source technologies such as Flume, Elasticsearch, Hadoop, Spark, Kibana, Grafana and Zeppelin. It provides insights and details on the lessons learned, explaining the work performed in order to monitor the CERN IT data centres and the WLCG computing activities such as the job processing, data access and transfers, and the status of sites and services..
2017 - 7 p.
- Published in : J. Phys.: Conf. Ser. 898 (2017) 092033
Fulltext: PDF;
In : 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.092033
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10.
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Real-time complex event processing for cloud resources
/ Adam, M (CERN ; ASCR, Prague) ; Cordeiro, C (CERN) ; Field, L (CERN) ; Giordano, D (CERN) ; Magnoni, L (CERN)
The ongoing integration of clouds into the WLCG raises the need for detailed health and performance monitoring of the virtual resources in order to prevent problems of degraded service and interruptions due to undetected failures. When working in scale, the existing monitoring diversity can lead to a metric overflow whereby the operators need to manually collect and correlate data from several monitoring tools and frameworks, resulting in tens of different metrics to be constantly interpreted and analyzed per virtual machine. [...]
2017 - 8 p.
- Published in : J. Phys.: Conf. Ser. 898 (2017) 042020
Fulltext: PDF;
In : 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016, pp.042020
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