CERN Accelerating science

CMS Note
Report number	CMS-CR-2015-060
Title	A scalable monitoring for the CMS Filter Farm based on elasticsearch
Related title	A scalable monitoring for the CMS Filter Farm based on elastic search
Author(s)	Andre, Jean-marc Olivier (Fermilab) ; Andronidis, Anastasios (Ioannina U.) ; Behrens, Ulf (DESY) ; Branson, James (UC, San Diego) ; Chaze, Olivier (CERN) ; Cittolin, Sergio (UC, San Diego) ; Darlea, Georgiana Lavinia (MIT) ; Deldicque, Christian (CERN) ; Dobson, Marc (CERN) ; Dupont, Aymeric (CERN) ; Erhan, Samim (UCLA) ; Gigi, Dominique (CERN) ; Glege, Frank (CERN) ; Gomez Ceballos, Guillelmo (MIT) ; Hegeman, Jeroen Guido (CERN) ; Holzner, Andre Georg (UC, San Diego) ; Jimenez Estupinan, Raul (CERN) ; Masetti, Lorenzo (CERN) ; Meijers, Franciscus (CERN) ; Meschi, Emilio (CERN) ; Mommsen, Remigius (Fermilab) ; Morovic, Srecko (CERN) ; Nunez Barranco Fernandez, Carlos (CERN) ; O'Dell, Vivian (Fermilab) ; Orsini, Luciano (CERN) ; Paus, Christoph Maria Ernst (MIT) ; Petrucci, Andrea (CERN) ; Pieri, Marco (UC, San Diego) ; Racz, Attila (CERN) ; Roberts, Penelope Amelia (CERN) ; Sakulin, Hannes (CERN) ; Schwick, Christoph (CERN) ; Stieger, Benjamin Bastian (CERN) ; Sumorok, Konstanty (MIT) ; Veverka, Jan (MIT) ; Zaza, Salvatore (CERN) ; Zejdl, Petr (Fermilab)
Publication	2015
Imprint	11 May 2015
Number of pages	9
In:	J. Phys.: Conf. Ser. 664 (2015) 082036
In:	21st International Conference on Computing in High Energy and Nuclear Physics, Okinawa, Japan, 13 - 17 Apr 2015, pp.082036
DOI	10.1088/1742-6596/664/8/082036
Subject category	Detectors and Experimental Techniques
Accelerator/Facility, Experiment	CERN LHC ; CMS
Abstract	A flexible monitoring system has been designed for the CMS File-based Filter Farm making use of modern data mining and analytics components. All the metadata and monitoring information concerning data flow and execution of the HLT are generated locally in the form of small "documents" using the JSON encoding. These documents are indexed into a hierarchy of elasticsearch (es) clusters along with process and system log information. Elasticsearch is a search server based on Apache Lucene. It provides a distributed, multitenant-capable search and aggregation engine. Since es is schema-free, any new information can be added seamlessly and the unstructured information can be queried in non-predetermined ways.The leaf es clusters consist of the very same nodes that form the Filter Farm thus providing "natural" horizontal scaling. A separate "central" es cluster is used to collect and index aggregated information. The fine-grained information, all the way to individual processes, remains available in the leaf clusters.The central es cluster provides quasi-real-time high-level monitoring information to any kind of client. Historical data can be retrieved to analyse past problems or correlate them with external information. We discuss the design and performance of this system in the context of the CMS DAQ commissioning for LHC Run 2.
Copyright/License	publication: © 2015-2025 The Author(s) (License: CC-BY-3.0)

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