| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01206 | |
| Number of page(s) | 7 | |
| DOI | https://doi.org/10.1051/epjconf/202533701206 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701206
Advanced Monitoring Capabilities of the CMS Experiment for LHC Run 3 and Beyond
1 Istituto Nazionale di Fisica Nucleare, Torino, Italy
2 CERN, Switzerland
3 Rutherford Appleton Laboratory, UK
* Corresponding author: brij.kishor.jashal@cern.ch
Published online: 7 October 2025
The Compact Muon Solenoid (CMS) experiment computing infrastructure, spread globally over 150 Worldwide LHC Computing Grid (WLCG) sites, forms an intricate ecosystem of computing resources, software, and services. In 2024, the production computing cores breached the half-million mark and storage capacity reached 250 petabytes on disk and 1.20 exabytes on tape. To monitor these resources in real time, CMS, working closely with CERN IT, has developed a multifaceted monitoring system providing real-time insights using more than 100 dashboards in production by CMS teams. In preparation for Run 3, the CMS monitoring infrastructure underwent significant evolution to broaden the scope of monitored applications and services while enhancing sustainability and ease of operation. Leveraging open-source solutions, provided either by the CERN IT department or managed internally, monitoring applications have transitioned from bespoke solutions to standardized data flow and visualization services. Notably, monitoring applications for distributed workload management and data handling have migrated to utilize technologies like OpenSearch, VictoriaMetrics, and HDFS, with access facilitated through programmatic APIs, Apache Spark, or Sqoop, and visualization primarily via Grafana. The majority of CMS monitoring applications are now deployed on Kubernetes clusters based on a micro-services architecture. This contribution unveils the comprehensive stack of CMS monitoring services, showcasing how the integration of common technologies enables versatile monitoring applications and addresses the computation demands of LHC Run 3. Additionally, it explores the incorporation of analytics into the monitoring framework, demonstrating how these insights contribute to the operational efficiency and scientific output of the CMS experiment.
© The Authors, published by EDP Sciences, 2025
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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