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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

Using a message broker


The traffic on production servers is supposed to be high at times. When this happens, log entries and statistics data become very critical and the amount of such data in total is also high. All of the Beats will be doing their work and will be sending respective data to Elasticsearch, but it is possible that some of the packets/data are lost while processing. It may happen because of a network failure, very high peaks of data, or any other possible reason. The point is, the data being indexed must not be lost in any case.

To address this problem, using a message broker or buffer is a good choice. There are many tools that can be evaluated for your choice of the message broker. For Open Source, there are two good tools available:

Sometimes, it seems that message broker is a must for a production environment, but there might be cases when we don't need any message broker at all. When we use Filebeat, it acts as...

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