Book Image

Learning Elastic Stack 6.0

By : Pranav Shukla, Sharath Kumar M N
Book Image

Learning Elastic Stack 6.0

By: Pranav Shukla, Sharath Kumar M N

Overview of this book

The Elastic Stack is a powerful combination of tools for distributed search, analytics, logging, and visualization of data from medium to massive data sets. The newly released Elastic Stack 6.0 brings new features and capabilities that empower users to find unique, actionable insights through these techniques. This book will give you a fundamental understanding of what the stack is all about, and how to use it efficiently to build powerful real-time data processing applications. After a quick overview of the newly introduced features in Elastic Stack 6.0, you’ll learn how to set up the stack by installing the tools, and see their basic configurations. Then it shows you how to use Elasticsearch for distributed searching and analytics, along with Logstash for logging, and Kibana for data visualization. It also demonstrates the creation of custom plugins using Kibana and Beats. You’ll find out about Elastic X-Pack, a useful extension for effective security and monitoring. We also provide useful tips on how to use the Elastic Cloud and deploy the Elastic Stack in production environments. On completing this book, you’ll have a solid foundational knowledge of the basic Elastic Stack functionalities. You’ll also have a good understanding of the role of each component in the stack to solve different data processing problems.
Table of Contents (19 chapters)
Title Page
Credits
Disclaimer
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

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 data type 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:

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 will contain the response code, request URL, IP address, and so on. We would need to have a mechanism for extracting this information...