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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

Configuring Elastic Stack components

In this section, we will configure all the tools for capturing the data. The components we will use are Elasticsearch, Logstash, Kibana, Filebeat, Metricbeat, and Packetbeat. Our pipeline would look like the following diagram:

Configuring Elastic Stack components

All of the components share the same version, that is, 5.1.1. We will read logs using Filebeat, push those logs to Logstash for processing, and then add them to Elasticsearch for indexing. For our setup, Logstash is used at 192.168.0.112, Kibana is installed at 192.168.0.111 and Elasticsearch instance is set up at 192.168.0.110. This Elasticsearch instance is different than what we installed for Liferay search engine capability. The one used for Liferay is a lower version, v1.4.0, because that is the one supported by Elasticray

On the other hand, we will use Metricbeat and Packetbeat to collect data and send it directly to Elasticsearch. Finally, we can visualize the data using Kibana.

Setting up Elasticsearch

Depending on the requirements...

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