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Research Paper | Information Technology | India | Volume 11 Issue 6, June 2022 | Popularity: 5 / 10
Unlocking the Potential of Logstash, Elasticsearch, and Kibana: A DevOps Approach to Big Data Logging
Nagaraju Islavath
Abstract: Organizations rely increasingly on the constant influx and data analysis to inform decision - making in the digital transformation era. Big data logging has become essential to operational excellence, particularly in DevOps settings where troubleshooting, real - time analysis, and performance monitoring call for extremely effective and scalable solutions. The possibilities of the ELK stack, which consists of Logstash, Elasticsearch, and Kibana as a complete, open - source option for big data logging and analysis in a DevOps setting, are examined in this paper. The study looks at the difficulties of logging large amounts of data, especially regarding scalability, performance, and real - time monitoring. It describes how the ELK stack overcomes these difficulties by offering strong, adaptable, and scalable tools for gathering, analyzing, and visualizing massive volumes of log data. To demonstrate the ELK stack's applicability in contemporary IT architecture, the paper also explores its practical applications, effects on DevOps operations, and general scope. The conclusion concludes by considering potential future developments and improvements that could fully realize the ELK stack's potential for managing massive data in DevOps environments.
Keywords: ELK stack, Logstash, Elasticsearch, Kibana, DevOps, Big Data Logging, Scalability, Real - time Monitoring, Data Visualization, Performance Analysis
Edition: Volume 11 Issue 6, June 2022
Pages: 2040 - 2044
DOI: https://www.doi.org/10.21275/SR20107085212
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