An Innovative Dynamic Method of Multiple Users Log Analysis using ELK Stack

An Innovative Dynamic Method of Multiple Users Log Analysis using ELK Stack

Hiral M. Patel1 [0000-0002-8232-8303] and Vatsala D. Patel2

1,2Department of Computer Engineering, SAL Institute of Diploma Studies, Ahmedabad 380060, India

hirvinpatel@gmail.com , vatsala5883@gmail.com

Abstract. Numerous different types of data, including raw data, metadata, logs, and metrics, were created by the systems, equipment, and devices in the most recent studies. The ELK i.e. Elasticsearch, Logstash and Kibana stack can be used to aggregate logs from applications and infrastructure. Summarizing and analyzing logs is of great value. Delivering innovative products and features faster is one of the main goals of the new world of cloud applications. To enable faster innovation in a data-driven digital economy, it is imperative to extract value from machine data by aggregating and analyzing logs, metrics, and events. Using ELK stack we can analyze logs and create visualizations for application and infrastructure monitoring, faster troubleshooting, security analytics, and much more purposes. Currently, we can manage to monitor any number of devices, apps, or infrastructures thanks to the ELK stack. To use ELK across numerous users, one must always visualize the data specific to each session (user) as well as set up ELK to operate in a highly dynamic environment for both current registered users and newly added monitoring entities. So, utilizing the ELK stack, we have developed a novel method of managing multiple users' logs on a dynamic basis.

Keywords: Elastic search, logstash, kibana, Data Visualization, Logs