Book Image

Learning Elastic Stack 7.0 - Second Edition

By : Pranav Shukla, Sharath Kumar M N
Book Image

Learning Elastic Stack 7.0 - Second Edition

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)
Free Chapter
Section 1: Introduction to Elastic Stack and Elasticsearch
Section 2: Analytics and Visualizing Data
Section 3: Elastic Stack Extensions
Section 4: Production and Server Infrastructure


In this chapter, we built a sensor data analytics application that has a wide variety of applications, as it is related to the emerging field of IoT. We understood the problem domain and the data model, including metadata related to sensors. We wanted to build an analytics application using only the components of the Elastic Stack, without using any other tools and programming languages, to obtain a powerful tool that can handle large volumes of data.

We started at the very core by designing the data model for Elasticsearch. Then, we designed a data pipeline that is secured and can accept data over the internet using HTTP. We enriched the incoming data using the metadata that we had in a relational database and stored in Elasticsearch. We sent some test data over HTTP just like those that real sensors send over the internet. We built some meaningful visualizations that...