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

How Beats fits into Elastic Stack


Having used the ELK Stack, which has been in existence for some time, we ask: is there space for another component in the Stack?

This is one of the biggest questions we think you'll have: where and how will Beats fit into the Elastic Stack? As we have already covered what Beats are, we have your answer covered, and this section that will provide you the answer to your question.

Beats has been added among the core components of the Stack due to the endless opportunities it creates when you use it. In the ELK Stack, you are bounded by the input plugins provided, via which only you can read the data. If you want to index operational data within Elasticsearch, such as transaction level information between multiple systems, Docker container statistics, Tomcat JMX metrics, or system-wide process level statistics, you would need to write a Logstash input plugin, which would then be used for such scenarios. For scenarios where you have multiple systems and you want...