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

Using Logstash

Logstash is a popular open source data collection engine with real-time pipelining capabilities. Logstash allows us to easily build a pipeline that can help in collecting data from a wide variety of input sources, and parse, enrich, unify, and store it in a wide variety of destinations. Logstash provides a set of plugins known as input filters and output plugins, which are easy to use and are pluggable in nature, thus easing the process of unifying and normalizing huge volumes and varieties of data. Logstash does the work of the ETL engine:

Some of the salient features of logstash are as follows:

  • Pluggable data pipeline architecture: Logstash contains over 200 plugins that have been developed by Elastic and the open source community, which can be used to mix, match, and orchestrate different inputs, filters, and outputs, while building pipelines for data processing...