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
About the Authors
About the Reviewer
Customer Feedback

Chapter 1. Introducing Elastic Stack

We are living in an advanced stage of the information age. The emergence of the web, mobiles, social networks, blogs, and photo sharing has created a massive amount of data in recent years. These new data sources create information that cannot be handled using traditional data storage technology, typically relational databases. As an application developer or business intelligence developer, your job is to fulfill the search and analytics needs of the application.

A number of big data scale data stores have emerged in the last few years. This includes Hadoop ecosystem projects, several NoSQL databases, and search and analytics engines such as Elasticsearch. Hadoop and each NoSQL database have their own strengths and use cases. 

Elastic Stack is a rich ecosystem of components serving as a full search and analytics stack. The main components of Elastic Stack are Kibana, Logstash, Beats, X-Pack, and Elasticsearch. Elasticsearch is at the heart of Elastic Stack, providing storage, search, and analytics capabilities. Kibana, which is also called a window into Elastic Stack, is a great visualization and user interface for Elastic Stack. Logstash and Beats help in getting the data into Elastic Stack. X-Pack provides powerful features including monitoring, alerting, and security to make your system production ready. Since Elasticsearch is at the heart of Elastic Stack, we will cover the stack inside-out, starting from the heart and moving on to the surrounding components.

In this chapter, we will cover the following topics:

  • What is Elasticsearch, and why use it?
  • A brief history of Elasticsearch and Apache Lucene
  • Elastic Stack components 
  • Use cases of Elastic Stack

We will look at what Elasticsearch is and why you should consider it as your data store. Once you know the key strengths of Elasticsearch, we will look at the history of Elasticsearch and its underlying technology, Apache Lucene. We will then look at some use cases of Elastic Stack, and we will provide an overview of the Elastic Stack components.