Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
---|---|---|
Article Number | 03061 | |
Number of page(s) | 6 | |
Section | T3 - Distributed computing | |
DOI | https://doi.org/10.1051/epjconf/201921403061 | |
Published online | 17 September 2019 |
https://doi.org/10.1051/epjconf/201921403061
ATLAS Distributed Computing: Its Central Services core
1
University of Cape Town
2
European Laboratory for Particle Physics (CERN)
3
Brookhaven National Laboratory (BNL)
4
Budker Institute of Nuclear Physics
5
The University of Texas at Arlington
6
University of Wisconsin
* e-mail: chris.lee@cern.ch
Published online: 17 September 2019
The ATLAS Distributed Computing (ADC) Project is responsible for the off-line processing of data produced by the ATLAS experiment at the Large Hadron Collider (LHC) at CERN. It facilitates data and workload management for ATLAS computing on the Worldwide LHC Computing Grid (WLCG). ADC Central Services operations (CSOPS) is a vital part of ADC, responsible for the deployment and configuration of services needed by ATLAS computing and operation of those services on CERN IT infrastructure, providing knowledge of CERN IT services to ATLAS service managers and developers, and supporting them in case of issues. Currently this entails the management of 43 different OpenStack projects, with more than 5000 cores allocated for these virtual machines, as well as overseeing the distribution of 29 petabytes of storage space in EOS for ATLAS. As the LHC begins to get ready for the next long shut-down, which will bring in many new upgrades to allow for more data to be captured by the on-line systems, CSOPS must not only continue to support the existing services, but plan ahead for the expected increase in data, users, and services that will be required. This paper attempts to explain the current state of CSOPS as well as the strategies in place to maintain the service functionality in the long term.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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