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Learning Kibana 5.0

You're reading from Learning Kibana 5.0 Exploit the visualization capabilities of Kibana and build powerful interactive dashboards

Product type Paperback

Published in Feb 2017

Publisher Packt

ISBN-13 9781786463005

Length 284 pages

Edition 1st Edition

Languages

Java

Tools

Elasticsearch

Concepts

Data Visualization

Author (1):

Bahaaldine Azarmi

View More author details

Table of Contents (10) Chapters

Preface

1. Introduction to Data-Driven Architecture

2. Installing and Setting Up Kibana 5.0 FREE CHAPTER

3. Business Analytics with Kibana 5.0

4. Logging Analytics with Kibana 5.0

5. Metric Analytics with Metricbeat and Kibana 5.0

6. Graph Exploration in Kibana

7. Customizing Kibana 5.0 Timelion

8. Anomaly Detection in Kibana 5.0

9. Creating a Custom Plugin for Kibana 5.0

Summary

In this chapter, we have seen the difference between industry Graph technologies and what Elastic Graph provides. Elastic Graph ties up aggregation and relevancy features to connect the document in Elasticsearch. Through this process, users get a way to build recommendations out of the indexed content. We then looked at some examples that illustrate how Elastic Graph can be used through simple exploration up to advanced exploration with multi-term graphs and advanced drill-downs.

In the next chapter, we'll start to delve fairly deeply into the world of Kibana customization by implementing an extension for Timelion.

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Authors (1)

Bahaaldine Azarmi

Bahaaldine Azarmi

Bahaaldine Azarmi, or Baha for short, is the head of solutions architecture in the EMEA South region at Elastic. Prior to this position, Baha co-founded ReachFive, a marketing data platform focused on user behavior and social analytics. He has also worked for a number of different software vendors, including Talend and Oracle, where he held positions as a solutions architect and architect. Prior to Machine Learning with the Elastic Stack, Baha authored books including Learning Kibana 5.0, Scalable Big Data Architecture, and Talend for Big Data. He is based in Paris and holds an MSc in computer science from Polytech'Paris.

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