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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 Data Pipelines with Logstash

In the previous chapter, we understood the importance of Logstash in the log analysis process. We also covered its usage and its high-level architecture, and went through some commonly used plugins. One of the important processes of Logstash is converting unstructured log data into structured data, which helps us search for relevant information easily and also assists in analysis. Apart from parsing the log data to make it structured, it would also be helpful if we could enrich the log data during this process so that we can gain further insights into our logs. Logstash comes in handy for enriching our log data, too. In the previous chapter, we have also seen that Logstash can read from a wide range of inputs and that Logstash is a heavy process. Installing Logstash on the edge nodes of shipping logs might not always be feasible. Is there...

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