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Learning Elastic Stack 7.0

Learning Elastic Stack 7.0

By : Pranav Shukla, Sharath Kumar M N
3.8 (6)
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Learning Elastic Stack 7.0

Learning Elastic Stack 7.0

3.8 (6)
By: Pranav Shukla, Sharath Kumar M N

Overview of this book

The Elastic Stack is a powerful combination of tools that help in performing distributed search, analytics, logging, and visualization of data. Elastic Stack 7.0 encompasses new features and capabilities that will enable you to find unique insights into analytics using these techniques. This book will give you a fundamental understanding of what the stack is all about, and guide you in using it efficiently to build powerful real-time data processing applications. The first few sections of the book will help you understand how to set up the stack by installing tools and exploring their basic configurations. You’ll then get up to speed with using Elasticsearch for distributed search and analytics, Logstash for logging, and Kibana for data visualization. As you work through the book, you will discover the technique of creating custom plugins using Kibana and Beats. This is followed by coverage of the Elastic X-Pack, a useful extension for effective security and monitoring. You’ll also find helpful tips on how to use Elastic Cloud and deploy Elastic Stack in production environments. By the end of this book, you’ll be well-versed with fundamental Elastic Stack functionalities and the role of each component in the stack to solve different data processing problems.
Table of Contents (17 chapters)
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1
Section 1: Introduction to Elastic Stack and Elasticsearch
4
Section 2: Analytics and Visualizing Data
10
Section 3: Elastic Stack Extensions
12
Section 4: Production and Server Infrastructure

Parsing and enriching logs using Logstash

The analysis of structured data is easier and helps us find meaningful/deeper analysis, rather than trying to perform analysis on unstructured data. Most analysis tools depend on structured data. Kibana, which we will be making use of for analysis and visualization, can be used effectively if the data in Elasticsearch is right (the information in the log data is loaded into appropriate fields, and the datatypes of the fields are more appropriate than just having all the values of the log data in a single field).

Log data is typically made up of two parts, as follows:

logdata = timestamp + data

timestamp is the time when the event occurred and data is the information about the event. data may contain just a single piece of information or it may contain many pieces of information. For example, if we take apache-access logs, the data piece...

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