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

Ingest node

Prior to Elasticsearch 5.0, if we wanted to preprocess documents before indexing them to Elasticsearch, then the only way was to make use of Logstash or preprocess them programmatically/manually and then index them to Elasticsearch. Elasticsearch lacked the ability to preprocess/transform the documents, and it just indexed the documents as they were. However, the introduction of a feature called ingest node in Elasticsearch 5.x onward provided a lightweight solution for preprocessing and enriching documents within Elasticsearch itself before they are indexed.

If an Elasticsearch node is implemented with the default configuration, by default, it would be master, data, and ingest enabled (that is, it would act as a master node, data node, and ingest node). To disable ingest on a node, configure the following setting in the elasticsearch.yml file:

node.ingest: false