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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

Extending Elasticsearch

Elasticsearch is a rich-in-feature, stable, and mature project, yet it is growing everyday. Like a good open source project, Elasticsearch offers ways to extend and let users customize Elasticsearch in their own ways. There are many things you would want to achieve through customization, to name a few: you would want to support a new repository to which Elasticsearch can connect and keep data, you might be interested to write your own analyzer, which does some additional tasks as compared to the existing analyzers in Elasticsearch, and so on. For the previous versions of Elasticsearch (prior to v5), developers used to create their own rivers to support a new data source. In fact, using the HTTP and transport modules, there are numerous opportunities of extending Elasticsearch beyond Elasticsearch packaged code and providing something that helps to integrate Elasticsearch with some other tool or technology.

Although not too many attempts were made to customize Elasticsearch...

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