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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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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

Parsing and enriching logs using Logstash


The analysis of structured data is easier and helps us find meaningful/deeper analysis, rather than trying to perform analysis on unstructured data. Most analysis tools depend on structured data. Kibana, which we will be making use of for analysis and visualization, can be used effectively if the data in Elasticsearch is right (the information in the log data is loaded into appropriate fields, and the data type of the fields are more appropriate than just having all the values of the log data in a single field). 

Log data is typically made up of two parts:

logdata = timestamp + data

timestamp is the time when the event occurred and data is the information about the event. data may contain just a single piece of information or it may contain many pieces of information. For example, if we take apache-access logs, the data piece will contain the response code, request URL, IP address, and so on. We would need to have a mechanism for extracting this information...

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