Summary
This paper describes a generic monitoring solution for the CMS Data Acquisition system utilising the open-source Elasticsearch NoSQL database. The approach offers non-intrusive integration with existing infrastructure whilst providing horizontal scalability, automated failover, and data redundancy through cloud-hosted clustering. The solution was validated by parallel operation alongside an established in-house DAQ monitoring system to ensure robustness.
UK applicability
This paper addresses technical infrastructure for particle physics data acquisition at CERN and has limited direct applicability to UK agricultural or soil health research. The Elasticsearch monitoring methodology may be transferable to large-scale distributed agricultural sensor networks, but the findings are specific to high-energy physics instrumentation.
Key measures
System scalability, failover capability, data redundancy, horizontal scaling performance, integration compatibility with existing DAQ infrastructure
Outcomes reported
The study presents a generic, reusable monitoring solution for the CMS Data Acquisition system based on Elasticsearch, demonstrating non-intrusive integration with existing infrastructure. The solution was validated through parallel operation with an established in-house DAQ monitoring system to ensure robustness and scalability.
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