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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
2. Introducing Elastic Stack FREE CHAPTER 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

Log analysis challenges

Logs are defined as records of incidents or observations. Logs are generated by a wide variety of resources, such as systems, applications, devices, humans, and so on. A log is typically made of two things; that is, a timestamp (the time the event was generated) and data (the information related to the event):

Log = Timestamp + Data

Logs are typically used for the following reasons:

  • Troubleshooting: When a bug or issue is reported, the first place to look for what might have caused the issue is the logs. For example, when looking at an exception stack trace in the logs, you may easily find the root cause of the issue.
  • To understand system/application behavior: When an application/system is running, it's like a black box, and, in order to investigate or understand what's happening within the system/application, you have to rely on logs. For example...
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