CERN Accelerating science

ATLAS Slides
Report number	ATL-SOFT-SLIDE-2021-130
Title	Seamless integration of commercial Clouds with ATLAS Distributed Computing
Author(s)	Elmsheuser, Johannes (Brookhaven National Laboratory (US)) ; Barreiro Megino, Fernando Harald (University of Texas at Arlington (US)) ; Bawa, Harinder Singh (California State University (US)) ; De, Kaushik (University of Texas at Arlington (US)) ; Klimentov, Alexei (Brookhaven National Laboratory (US)) ; Lassnig, Mario (CERN) ; Serfon, Cedric (Brookhaven National Laboratory (US)) ; Wegner, Tobias (Bergische Universitaet Wuppertal (DE))
Corporate author(s)	The ATLAS collaboration
Collaboration	ATLAS Collaboration
Submitted to	25th International Conference on Computing in High-Energy and Nuclear Physics (CHEP), Online, Online, 17 - 21 May 2021
Submitted by	[email protected] on 29 Apr 2021
Subject category	Particle Physics - Experiment
Accelerator/Facility, Experiment	CERN LHC ; ATLAS
Abstract	The CERN ATLAS Experiment successfully uses a worldwide distributed computing Grid infrastructure to support its physics programme at the Large Hadron Collider (LHC). The Grid workflow system PanDA routinely manages up to 700'000 concurrently running production and analysis jobs to process simulation and detector data. In total more than 500 PB of data is distributed over more than 150 sites in the WLCG and handled by the ATLAS data management system Rucio. To prepare for the ever growing data rate in future LHC runs new developments are underway to embrace industry accepted protocols and technologies, and utilize opportunistic resources in a standard way. This paper reviews how the Google and Amazon Cloud computing services have been seamlessly integrated as a Grid site within PanDA and Rucio. Performance and brief cost evaluations will be discussed. Such setups could offer advanced Cloud tool-sets and provide added value for analysis facilities that are under discussions for LHC Run-4.