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Mastering Elastic Stack

You're reading from   Mastering Elastic Stack Dive into data analysis with a pursuit of mastering ELK Stack on real-world scenarios.

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781786460011
Length 526 pages
Edition 1st Edition
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Authors (2):
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Ravi Kumar Gupta Ravi Kumar Gupta
Author Profile Icon Ravi Kumar Gupta
Ravi Kumar Gupta
Yuvraj Gupta Yuvraj Gupta
Author Profile Icon Yuvraj Gupta
Yuvraj Gupta
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Toc

Table of Contents (13) Chapters Close

Preface 1. Elastic Stack Overview FREE CHAPTER 2. Stepping into Elasticsearch 3. Exploring Logstash and Its Plugins 4. Kibana Interface 5. Using Beats 6. Elastic Stack in Action 7. Customizing Elastic Stack 8. Elasticsearch APIs 9. X-Pack: Security and Monitoring 10. X-Pack: Alerting, Graph, and Reporting 11. Best Practices 12. Case Study-Meetup

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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