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Learning ELK Stack

You're reading from Learning ELK Stack Build mesmerizing visualizations, analytics, and logs from your data using Elasticsearch, Logstash, and Kibana

Product type Paperback

Published in Nov 2015

Publisher

ISBN-13 9781785887154

Length 206 pages

Edition 1st Edition

Tools

Elasticsearch

Concepts

Enterprise Search

Author (1):

Saurabh Chhajed

View More author details

Table of Contents (12) Chapters

Preface

1. Introduction to ELK Stack FREE CHAPTER

2. Building Your First Data Pipeline with ELK

3. Collect, Parse and Transform Data with Logstash

4. Creating Custom Logstash Plugins

5. Why Do We Need Elasticsearch in ELK?

6. Finding Insights with Kibana

7. Kibana – Visualization and Dashboard

8. Putting It All Together

9. ELK Stack in Production

10. Expanding Horizons with ELK

Index

Kibana interface

A Kibana interface consists of four main tabs:

Discover: The Discover page enables free text searches, field-based searches, range-based searches, and so on.
Visualize: The Visualize page enables building many visualizations, such as pie charts, bar charts, line charts, and so on, which can be saved and used in dashboards later.
Dashboard: The Dashboard represents collections of multiple visualizations and searches, which can be used to easily apply filters based on click interaction, and draw conclusions based on multiple data aggregations.
Settings: Settings enables the configuration of index patterns, scripted fields, the data types of fields, and so on.

Let's take a look at the Discover page in more detail.

Discover page

The Discover page is used to perform interactive searches on your indexed data. It allows you to perform ad hoc searches based on fields, the filtering of data, and allows you to view indexed documents as well.

A typical Kibana home page, which defaults...

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Authors (1)

Chhajed

Chhajed

Saurabh Chhajed is a technologist with vast professional experience in building Enterprise applications that span across product and service industries. He has experience building some of the largest recommender engines using big data analytics and machine learning, and also enjoys acting as an evangelist for big data and NoSQL technologies. With his rich technical experience, Saurabh has helped some of the largest financial and industrial companies in USA build their large product suites and distributed applications from scratch. He shares his personal experiences with technology at http://saurzcode.in. Saurabh has also reviewed books by Packt Publishing, Apache Camel Essentials and Java EE 7 Development with NetBeans 8, in the past.

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