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
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

Summary

In this chapter, we laid out the foundations of Logstash. We walked you through the steps to install and configure Logstash to set up basic data pipelines, and studied Logstash's architecture.

We also learned about the ingest node that was introduced in Elastic 5.x, which can be used instead of a dedicated Logstash setup. We saw how the ingest node can be used to preprocess documents before the actual indexing takes place, and also studied its different APIs.

In the next chapter, we will show you how a rich set of filters brings Logstash closer to the other real-time and near real-time stream processing frameworks with zero coding.