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

Monitoring Elasticsearch

Elasticsearch exposes a rich set of APIs, known as stats APIs, to monitor Elasticsearch at the cluster, node, and indices levels. Some of these APIs are _cluster/stats, _nodes/stats, and myindex/stats. These APIs provide state/monitoring information in real time, and the statistics that are presented in these APIs are point-in-time and in .json format. As an administrator/developer, when working with Elasticsearch, you will be interested in both real-time statistics as well as historical statistics, which would help you in understanding/analyzing the behavior (health or performance) of a cluster better.

Also, reading through a set of numbers for a period of time (say, for example, to find out the JVM utilization over time) would be very difficult. Rather, a UI that pictorially represents these numbers as graphs would be very useful for visualizing and...