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URLhttps://doi.org/10.18429/JACoW-IBIC2024-WEP50
TitleResearch on visualization and indexing of data based on the ELK stack
Authors
  • Y. Li, J. Cao, Q. Ye, Y. Du
    Institute of High Energy Physics
AbstractThis paper presents a comprehensive solution for the real-time collection and analysis of BPM telemetry data using Kafka and the ELK stack. It includes the transmission of PV variables from BPM electronic devices to the Kafka message queue, thus realizing a powerful and scalable data streaming process. By retrieving JSON formatted data from Kafka using the ELK stack, efficient data indexing and visualization in Kibana are achieved. The paper details the architectural design, implementation details, and the advantages of using Kafka as a BPM data dissemination center. This integration not only enhances the performance and reliability of the data processing pipeline but also provides physicists and engineers with powerful tools for the real-time visualization and monitoring of BPM data. Our approach has shown significant improvements in data accessibility, searchability, and real-time analytics, offering profound implications for future research and development in the instrumentation and diagnostics of particle accelerators.
Paperdownload: WEP50.pdf
CiteBibTeX, LaTeX, Text/Word, RIS, EndNote
ConferenceProc. 13th International Beam Instrumentation Conference
Series
LocationBeijing
Date09-13 Sep 2024
PublisherJACoW Publishing, Geneva, Switzerland
Editorial BoardJianshe Cao (IHEP), Junhui Yue (IHEP), Lin Bian (IHEP), Ivan Andrian (Elettra-Sincrotrone Trieste S.C.p.A.), Volker RW Schaa (GSI), Zhichu Chen (SARI)
Online ISBN978-3-95450-249-3
Online ISSN2673-5350
Received05 September 2024
Revised06 September 2024
Accepted06 September 2024
Issued11 December 2024
DOI10.18429/JACoW-IBIC2024-WEP50
Pages386-389