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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

Building the Logstash data pipeline

Having set up the mechanism to automatically create the Elasticsearch index and 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 with 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/v7.0/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...

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