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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 FREE CHAPTER 2. Getting Started with Elasticsearch 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

Building the Logstash data pipeline


Having set up the mechanism to automatically create the Elasticsearch index and also the metadata database, we can now focus on building the data pipeline using Logstash. What should our data pipeline do? It should perform the following steps:

  • Accept JSON requests over the web (over HTTP)
  • Enrich the JSON with the metadata we have in the MySQL database
  • Store the resulting documents in Elasticsearch

These three main functions that we want to perform correspond exactly to the Logstash data pipeline's input, filter, and output plugins respectively. The full Logstash configuration file for this data pipeline is in the code base at https://github.com/pranav-shukla/learningelasticstack/tree/master/chapter-10/files/logstash_sensor_data_http.conf.

Let us look at how to achieve the end goal of our data pipeline by following the aforementioned steps. We will start with accepting JSON requests over the web (over HTTP).

Accept JSON requests over the web

This function is achieved...

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