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

Why do we need Logstash?


Logstash mainly started as a project for managing logs, but it has since been extended to analyze any type of data, be it event data, timestamped data, application logs, transactional data, CSV data, file input, and so on. Data can be structured, unstructured, or semi-structured, which makes it difficult to convert the data into a proper format. To manage logs of different types coming in from different systems, we require a tool which is powerful in handling the various different types of log data and analyzing it in near-real-time to generate insights from the log data. Logstash helps you to collect data from multiple systems into a central system wherein data can be parsed and processed as required. Also, Logstash helps you to gather the data from multiple systems and store the data in a common format, which is easily used by Elasticsearch and Kibana.

Logstash allows you to pipeline data, which can be extracted, cleansed, transformed, and loaded to gain valuable...