Recent Experience with the CMS Data Management System

The CMS[1] experiment manages a large-scale data infrastructure, currently handling over 200 PB of disk and 500 PB of tape storage and transferring more than 1 PB of data per day on average between various WLCG[2] sites. Utilizing Rucio[3] for high-level data management, FTS[4] for data transfers, and a variety of storage and network technologies at the sites, CMS confronts inevitable challenges due to the system’s growing scale and evolving nature. Key challenges include managing transfer and storage failures, optimizing data distribution across different storages based on production and analysis needs, implementing necessary technology upgrades and migrations, and efficiently handling user requests. The data management team has established comprehensive monitoring to supervise this system and has successfully addressed many of these challenges. The team’s efforts aim to ensure data availability and protection, minimize failures and manual interventions, maximize transfer throughput and resource utilization, and provide reliable user support. This paper details the operational experience of CMS with its data management system in recent years, focusing on the encountered challenges, the effective strategies employed to overcome them and the ongoing challenges as we prepare for future demands.

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Publication Details

Journal
EPJ Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/epjconf/202533701151
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
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article

Recent Experience with the CMS Data Management System

Panos Paparrigopoulos, Eric Wayne Vaandering, Katy Ellis, Rahul Chauhan et al.
EPJ Web of Conferences
Distributed and Parallel Computing Systems
article

Recent Experience with the CMS Data Management System

Panos Paparrigopoulos, Eric Wayne Vaandering, Katy Ellis, Rahul Chauhan, Hasan Öztürk, Maggie Voetberg, Andrew Wightman, Dmytro Kovalskyi, Andres Manrique Ardila, Christos Emmanouil
article en

Abstract

The CMS[1] experiment manages a large-scale data infrastructure, currently handling over 200 PB of disk and 500 PB of tape storage and transferring more than 1 PB of data per day on average between various WLCG[2] sites. Utilizing Rucio[3] for high-level data management, FTS[4] for data transfers, and a variety of storage and network technologies at the sites, CMS confronts inevitable challenges due to the system’s growing scale and evolving nature. Key challenges include managing transfer and storage failures, optimizing data distribution across different storages based on production and analysis needs, implementing necessary technology upgrades and migrations, and efficiently handling user requests. The data management team has established comprehensive monitoring to supervise this system and has successfully addressed many of these challenges. The team’s efforts aim to ensure data availability and protection, minimize failures and manual interventions, maximize transfer throughput and resource utilization, and provide reliable user support. This paper details the operational experience of CMS with its data management system in recent years, focusing on the encountered challenges, the effective strategies employed to overcome them and the ongoing challenges as we prepare for future demands.

EPJ Web of ConferencesVol. 337
University of Nebraska–Lincoln (US), Rutherford Appleton Laboratory (GB), University of Wisconsin System (US), Fermi National Accelerator Laboratory (US), University of Wisconsin–Madison (US), Research Complex at Harwell (GB), Massachusetts Institute of Technology (US), European Organization for Nuclear Research (CH)
Openalex Percentile: Top 68%
Distributed and Parallel Computing Systems
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