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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

Summary

In this chapter, we built a sensor data analytics application that has a wide variety of applications, as it is related to the emerging field of IoT. We understood the problem domain and the data model, including metadata related to sensors. We wanted to build an analytics application using only the components of the Elastic Stack, without using any other tools and programming languages, to obtain a powerful tool that can handle large volumes of data.

We started at the very core by designing the data model for Elasticsearch. Then, we designed a data pipeline that is secured and can accept data over the internet using HTTP. We enriched the incoming data using the metadata that we had in a relational database and stored in Elasticsearch. We sent some test data over HTTP just like those that real sensors send over the internet. We built some meaningful visualizations that...

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