CERN Accelerating science

ATLAS Note
Report number	ATL-DAQ-PROC-2018-038
Title	Integrated automation for configuration management and operations in the ATLAS online computing farm
Author(s)	Amirkhanov, Artem (Novosibirsk, IYF) ; Ballestrero, Sergio (Johannesburg U.) ; Brasolin, Franco (INFN, Bologna) ; Lee, Christopher Jon (Johannesburg U.) ; Du Plessis, Haydn Dean (Johannesburg U.) ; Mitrogeorgos, Konstantinos (Aristotle U., Thessaloniki) ; Pernigotti, Marco (CERN) ; Sanchez Pineda, Arturo Rodolfo (INFN, Udine ; Udine U.) ; Scannicchio, Diana Alessandra (UC, Irvine (main)) ; Twomey, Matthew Shaun (U. Washington, Seattle (main))
Publication	2019
Imprint	27 Nov 2018
Number of pages	8
In:	EPJ Web Conf. 214 (2019) 08022
In:	23rd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2018, Sofia, Bulgaria, 9 - 13 Jul 2018, pp.08022
DOI	10.1051/epjconf/201921408022
Subject category	Particle Physics - Experiment
Accelerator/Facility, Experiment	CERN LHC ; ATLAS
Free keywords	Automation ; Monitoring ; Farm Management
Abstract	The online farm of the ATLAS experiment at the LHC, consisting of nearly 4000 PCs with various characteristics, provides configuration and control of the detector and performs the collection, processing, selection, and conveyance of event data from the front-end electronics to mass storage. Different aspects of the farm management are already accessible via several tools. The status and health of each node are monitored by a system based on Icinga 2 and Ganglia. PuppetDB gathers centrally all the status information from Puppet, the configuration management tool used to ensure configuration consistency of every node. The in-house Configuration Database (ConfDB) controls DHCP and PXE, while also integrating external information sources. In these proceedings we present our roadmap for integrating these and other data sources and systems, and building a higher level of abstraction on top of this foundation. An automation and orchestration tool will be able to use these systems and replace lengthy manual procedures, some of which also require interactions with other systems and teams, e.g. for the repair of a faulty node. Finally, an inventory and tracking system will complement the available data sources, keep track of node history, and improve the evaluation of long-term lifecycle management and purchase strategies.
Related document	Slides ATL-DAQ-SLIDE-2018-803
Copyright/License	publication: © 2019-2024 The Authors (License: CC-BY-4.0) preprint: © 2018-2024 CERN for the benefit of the ATLAS Collaboration (License: CC-BY-4.0)

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