CERN Accelerating science

CMS Note
Report number	CMS-CR-2012-041
Title	The CMS Online Cluster: Setup, Operation and Maintenance of an Evolving Cluster
Author(s)	Coarasa, Jose Antonio (CERN) ; Bauer, Gerry (MIT) ; Behrens, Ulf (DESY) ; Bouffet, Olivier (CERN) ; Branson, James G (UC, San Diego) ; Bukowiec, Sebastian (CERN) ; Chaze, Olivier (CERN) ; Ciganek, Marek (CERN) ; Cittolin, Sergio (UC, San Diego) ; Deldicque, Christian (CERN) ; Dobson, Marc (CERN) ; Dupon, Aymeric (CERN) ; Erhan, Samim (UCLA) ; Gigi, Dominique (CERN) ; Glege, Frank (CERN) ; Gomez-Reino, Robert (CERN) ; Hartl, Christian (CERN) ; Holzner, André (UC, San Diego) ; Masetti, Lorenzo (CERN) ; Meijers, Frans (CERN) ; Meschi, Emilio (CERN) ; Mommsen, Remigius K (Fermilab) ; Nunez-Barranco-Fernandez, Carlos (CERN) ; O'Dell, Vivian (Fermilab) ; Orsini, Luciano (CERN) ; Paus, Christoph (MIT) ; Petrucci, Andrea (CERN) ; Pieri, Marco (UC, San Diego) ; Polese, Giovanni (CERN) ; Racz, Attila (CERN) ; Raginel, Olivier (MIT) ; Sakulin, Hannes (CERN) ; Sani, Matteo (UC, San Diego) ; Schwick, Christoph (CERN) ; Simon, Michal (CERN) ; Spataru, Andrei Cristian (CERN) ; Stoeckli, Fabian (MIT) ; Sumorok, Konstanty (MIT)
Publication	2012
Imprint	07 Mar 2012
Number of pages	13
In:	PoS ISGC 2012 (2012) pp.023
In:	International Symposium on Grids and Clouds, Taipei, Taiwan, 26 Feb - 2 Mar 2012, pp.023
Subject category	Detectors and Experimental Techniques
Accelerator/Facility, Experiment	CERN LHC ; CMS
Abstract	The CMS online cluster consists of more than 2700 computers running about 15000 application instances. These applications implement the necessary services to run the data acquisition of the CMS experiment. In this paper the IT solutions employed on the cluster are reviewed. Details are given on the adopted solutions which include the following topics: implementation of a redundant and load balanced network and core IT services; deployment and configuration management infrastructure and its customization; a new monitoring infrastructure. Special emphasis will be put on the scalable approach allowing to increase the size of the cluster with no administration overhead. Finally, the lessons learnt from the two years of running will be presented.
Copyright/License	Publication: (License: CC-BY-NC-SA-3.0)

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