| Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
|---|---|---|
| Article Number | 04010 | |
| Number of page(s) | 9 | |
| Section | Distributed Computing | |
| DOI | https://doi.org/10.1051/epjconf/202429504010 | |
| Published online | 06 May 2024 | |
https://doi.org/10.1051/epjconf/202429504010
BigPanDA monitoring system evolution in the ATLAS Experiment
1 University of Pittsburgh, Pittsburgh, PA, USA
2 University of Texas at Arlington, Arlington, TX, USA
3 Brookhaven National Laboratory, Upton, NY, USA
* e-mail: tatiana.korchuganova@cern.ch
Published online: 6 May 2024
Monitoring services play a crucial role in the day-to-day operation of distributed computing systems. The ATLAS Experiment at LHC uses the Production and Distributed Analysis workload management system (PanDA WMS), which allows a million computational jobs to run daily at over 170 computing centers of the WLCG and opportunistic resources, utilizing 600k cores simultaneously on average. The BigPanDA monitor is an essential part of the monitoring infrastructure for the ATLAS Experiment that provides a wide range of views, from top-level summaries to a single computational job and its logs. Over the past few years of the PanDA WMS advancement in the ATLAS Experiment, several new components were developed, such as Harvester, iDDS, Data Carousel, and Global Shares. Due to its modular architecture, the BigPanDA monitor naturally grew into a platform where the relevant data from all PanDA WMS components and accompanying services are accumulated and displayed in the form of interactive charts and tables. Moreover the system has been adopted by other experiments beyond HEP. In this paper we describe the evolution of the BigPanDA monitor system, the development of new modules, and the integration process into other experiments.
© The Authors, published by EDP Sciences, 2024
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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