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Mastering Elastic Stack

Mastering Elastic Stack

By : Kumar Gupta, Gupta
1 (1)
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Mastering Elastic Stack

Mastering Elastic Stack

1 (1)
By: Kumar Gupta, 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 (13 chapters)
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Logstash Plugin Architecture


The Logstash pipeline consists of input, filter, and output plugins. Let's have a look at the following diagram to understand how Logstash uses the plugins:

In the preceding architecture, we can see that there can be multiple data sources from which data is collected, which constitutes as Logstash Input Plugin. After getting input, we can use the Filter Plugin to transform the data and we can store output or write data to a destination using the Output Plugin.

Logstash uses a configuration file to specify the plugins for getting input, filtering data, and storing output. The Input Plugin and Output Plugin are mandatory to specify in the configuration file whereas the Filter plugin is optional to use. If you have input data and without transforming or modifying the data, you can directly store the data in the destination, then in this case filter plugin is not required.

The architecture can be simplified as shown in the following diagram:

Now that we understand...

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