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

Introducing Beats

Beats are lightweight data shippers that are installed as agents on edge servers to ship operational data to Elasticsearch. Just like Elasticsearch, Logstash, Kibana, and Beats are open source products too. Depending on the use case, Beats can be configured to ship the data to Logstash to transform events prior to pushing the events to Elasticsearch.

The Beats framework is made up of a library called libbeat, which provides an infrastructure to simplify the process of shipping operation data to Elasticsearch. It offers the API that all Beats can use to ship data to an output (such as Elasticsearch, Logstash, Redis, Kafka, and so on), configure the input/output options, process events, implement logging, and more. The libbeat library is built using the Go programming language. Go was chosen to build Beats because it's easy to learn, very resource-friendly...