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)

Visualizing Data

In earlier chapters, we covered how to install different components of the Elastic Stack, and then configured Beats and Logstash to push data into Elasticsearch. After pushing the data into Elasticsearch, we covered Kibana Discover to explore data by applying query and filter on the data, and after that saved the search data for further use. So, basically, we have set the stage by creating the index pattern to create Elasticsearch index data availability in Kibana. Now, we are going to discuss the most important features of Kibana, using which we can create meaningful visualizations with the data.

There are different types of visualizations we can create using Kibana, such as basic charts under which we can create an area, heat map, horizontal bar, line, pie, vertical bar, and so on. Then under data category of visualization, we have data table, gauge, goal, and...