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Learning Elastic Stack 6.0

You're reading from   Learning Elastic Stack 6.0 A beginner's guide to distributed search, analytics, and visualization using Elasticsearch, Logstash and Kibana

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Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781787281868
Length 434 pages
Edition 1st 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 (12) Chapters Close

Preface 1. Introducing Elastic Stack 2. Getting Started with Elasticsearch FREE CHAPTER 3. Searching-What is Relevant 4. Analytics with Elasticsearch 5. Analyzing Log Data 6. Building Data Pipelines with Logstash 7. Visualizing data with Kibana 8. Elastic X-Pack 9. Running Elastic Stack in Production 10. Building a Sensor Data Analytics Application 11. Monitoring Server Infrastructure

 Deploymezs architecture


The following diagram depicts commonly used Elastic Stack deployment architecture:

The diagram depicts three possible architectures:

  • Ship the operation metrics directly to Elasticsearch: As seen in the preceding diagram, one will install various types of Beats such as Metricbeat, Filebeat, Packetbeat, and so on, on the edge servers from which they would like to ship the operation metrics/logs. If no further processing of events is required, then the generated events can be shipped directly to the Elasticsearch cluster. Once the data is present in Elasticsearch, it can then be visualized/analyzed using Kibana. In this architecture, the flow of events would be Beats → Elasticsearch → Kibana. 
  • Ship the operation metrics to Logstash: The operation metrics/logs captured by the Beats and installed on edge servers is sent to Logstash for further processing such as, for instance, parsing the logs or enriching log events. Then the parsed/enriched events are pushed to Elasticsearch...
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