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.
Legger et al. (Wed,) studied this question.
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