Book Image

Mastering Elastic Stack

By : Ravi Kumar Gupta, Yuvraj Gupta
Book Image

Mastering Elastic Stack

By: Ravi Kumar Gupta, Yuvraj Gupta

Overview of this book

Even structured data is useless if it can’t help you to take strategic decisions and improve existing system. If you love to play with data, or your job requires you to process custom log formats, design a scalable analysis system, and manage logs to do real-time data analysis, this book is your one-stop solution. By combining the massively popular Elasticsearch, Logstash, Beats, and Kibana, elastic.co has advanced the end-to-end stack that delivers actionable insights in real time from almost any type of structured or unstructured data source. If your job requires you to process custom log formats, design a scalable analysis system, explore a variety of data, and manage logs, this book is your one-stop solution. You will learn how to create real-time dashboards and how to manage the life cycle of logs in detail through real-life scenarios. This book brushes up your basic knowledge on implementing the Elastic Stack and then dives deeper into complex and advanced implementations of the Elastic Stack. We’ll help you to solve data analytics challenges using the Elastic Stack and provide practical steps on centralized logging and real-time analytics with the Elastic Stack in production. You will get to grip with advanced techniques for log analysis and visualization. Newly announced features such as Beats and X-Pack are also covered in detail with examples. Toward the end, you will see how to use the Elastic stack for real-world case studies and we’ll show you some best practices and troubleshooting techniques for the Elastic Stack.
Table of Contents (19 chapters)
Mastering Elastic Stack
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Preparing Elastic Stack pipeline


We have a scenario for which we want to do data and log analysis covered in the preceding section. To do analysis, we want to use Elastic Stack components to help us. Those components will be installed on different nodes and will be submitting data to one central Elasticsearch node or to an Elasticsearch cluster. In order to set this up, we need to update our architecture to include elastic stack components, such as Logstash, Beats, Elasticsearch, and Kibana.

What to capture?

First thing, before we start updating our architecture, we need to understand what we want to capture and how that is going to help us. The following are few things we want to capture for our requirements:

  • Logs generated by the following:

    • Liferay, MySQL

    • Nginx

    • OpenDJ

    • Elasticsearch node, which is used by Liferay

  • System statistics for each node:

    • All nodes for Liferay, MySQL, Nginx, OpenDJ, and Elasticsearch

  • Network Traffic for each node:

    • Includes HTTP, MySQL protocols, and so on

Updated architecture...