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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

Preparing Elastic Stack pipeline

We have a scenario for which we want to do data and log analysis covered in the preceding section. To do analysis, we want to use Elastic Stack components to help us. Those components will be installed on different nodes and will be submitting data to one central Elasticsearch node or to an Elasticsearch cluster. In order to set this up, we need to update our architecture to include elastic stack components, such as Logstash, Beats, Elasticsearch, and Kibana.

What to capture?

First thing, before we start updating our architecture, we need to understand what we want to capture and how that is going to help us. The following are few things we want to capture for our requirements:

  • Logs generated by the following:
    • Liferay, MySQL
    • Nginx
    • OpenDJ
    • Elasticsearch node, which is used by Liferay
  • System statistics for each node:
    • All nodes for Liferay, MySQL, Nginx, OpenDJ, and Elasticsearch
  • Network Traffic for each node:
    • Includes HTTP, MySQL protocols, and so on

Updated architecture...

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