Book Image

Kibana 7 Quick Start Guide

By : Anurag Srivastava
Book Image

Kibana 7 Quick Start Guide

By: Anurag Srivastava

Overview of this book

The Elastic Stack is growing rapidly and, day by day, additional tools are being added to make it more effective. This book endeavors to explain all the important aspects of Kibana, which is essential for utilizing its full potential. This book covers the core concepts of Kibana, with chapters set out in a coherent manner so that readers can advance their learning in a step-by-step manner. The focus is on a practical approach, thereby enabling the reader to apply those examples in real time for a better understanding of the concepts and to provide them with the correct skills in relation to the tool. With its succinct explanations, it is quite easy for a reader to use this book as a reference guide for learning basic to advanced implementations of Kibana. The practical examples, such as the creation of Kibana dashboards from CSV data, application RDBMS data, system metrics data, log file data, APM agents, and search results, can provide readers with a number of different drop-off points from where they can fetch any type of data into Kibana for the purpose of analysis or dashboarding.
Table of Contents (9 chapters)

Introducing Kibana

Kibana is a dashboard tool that's easy to use and works closely with Elasticsearch. We can use Kibana for different use cases, such as system monitoring and application monitoring. Kibana isn't just a visualization tool, it also creates a complete monitoring ecosystem when we leverage the power of Elastic Stack. Here's a small example: you're working on a project where you can't tolerate any outrage, be it due to the database, application, system-related issues, or anything related to the application's performance. In a traditional monitoring system, you can monitor system performance, application logs, and so on. But with Kibana and Elastic Stack, we can do following:

  • Configure Beats to monitor system metrics, database metrics, and log metrics
  • Configure APM to monitor your application metrics and issues if your application platform is supported
  • Configure the JDBC plugin of Logstash to pull RDBMS data into Elasticsearch to make it available to Kibana for creating visualizations on KPIs
  • There are different third-party plugins that help us to get data from those sources, for example, you can use the Twitter plugin to get Twitter feeds
  • You can create alerts for certain thresholds, so that whenever that situation occurs, you get alerts so you don't have to continuously monitor the application
  • You can apply machine learning on your data to get data anomalies or future trends by analyzing the current dataset