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Learning Elastic Stack 7.0

You're reading from   Learning Elastic Stack 7.0 Distributed search, analytics, and visualization using Elasticsearch, Logstash, Beats, and Kibana

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789954395
Length 474 pages
Edition 2nd Edition
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Authors (2):
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Sharath Kumar Sharath Kumar
Author Profile Icon Sharath Kumar
Sharath Kumar
Pranav Shukla Pranav Shukla
Author Profile Icon Pranav Shukla
Pranav Shukla
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Introduction to Elastic Stack and Elasticsearch FREE CHAPTER
2. Introducing Elastic Stack 3. Getting Started with Elasticsearch 4. Section 2: Analytics and Visualizing Data
5. Searching - What is Relevant 6. Analytics with Elasticsearch 7. Analyzing Log Data 8. Building Data Pipelines with Logstash 9. Visualizing Data with Kibana 10. Section 3: Elastic Stack Extensions
11. Elastic X-Pack 12. Section 4: Production and Server Infrastructure
13. Running Elastic Stack in Production 14. Building a Sensor Data Analytics Application 15. Monitoring Server Infrastructure 16. Other Books You May Enjoy

Introducing Beats

Beats are lightweight data shippers that are installed as agents on edge servers to ship operational data to Elasticsearch. Just like Elasticsearch, Logstash, Kibana, and Beats are open source products too. Depending on the use case, Beats can be configured to ship the data to Logstash to transform events prior to pushing the events to Elasticsearch.

The Beats framework is made up of a library called libbeat, which provides an infrastructure to simplify the process of shipping operation data to Elasticsearch. It offers the API that all Beats can use to ship data to an output (such as Elasticsearch, Logstash, Redis, Kafka, and so on), configure the input/output options, process events, implement logging, and more. The libbeat library is built using the Go programming language. Go was chosen to build Beats because it's easy to learn, very resource-friendly...

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