You're reading from Machine Learning with the Elastic Stack Gain valuable insights from your data with Elastic Stack's machine learning features

Product type Paperback

Published in May 2021

Publisher Packt

ISBN-13 9781801070034

Length 450 pages

Edition 2nd Edition

Languages

Python

Tools

Elasticsearch

Concepts

Machine Learning

Authors (3):

Camilla Montonen

Rich Collier

Bahaaldine Azarmi

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Table of Contents (19) Chapters

Preface

1. Section 1 – Getting Started with Machine Learning with Elastic Stack

2. Chapter 1: Machine Learning for IT FREE CHAPTER

3. Chapter 2: Enabling and Operationalization

4. Section 2 – Time Series Analysis – Anomaly Detection and Forecasting

5. Chapter 3: Anomaly Detection

6. Chapter 4: Forecasting

7. Chapter 5: Interpreting Results

8. Chapter 6: Alerting on ML Analysis

9. Chapter 7: AIOps and Root Cause Analysis

10. Chapter 8: Anomaly Detection in Other Elastic Stack Apps

11. Section 3 – Data Frame Analysis

12. Chapter 9: Introducing Data Frame Analytics

13. Chapter 10: Outlier Detection

14. Chapter 11: Classification Analysis

15. Chapter 12: Regression

16. Chapter 13: Inference

17. Other Books You May Enjoy

Appendix: Anomaly Detection Tips

Categorization analysis of unstructured messages

Imagine that you are troubleshooting a problem by looking at a particular log file. You see a line in the log that looks like the following:

   18/05/2020 15:16:00 DB Not Updated [Master] Table

Unless you have some intimate knowledge about the inner workings of the application that created this log, you may not know whether the message is important. Having the database be Not Updated possibly sounds like a negative situation. However, if you knew that the application routinely writes this message, day in and day out, several hundred times per hour, then you would naturally realize that this message is benign and should possibly be ignored, because clearly the application works fine every day despite this message being written to the log file.

The problem, obviously, is one of human interpretation. Inspection of the text of the message and the reading of a negative phrase (Not Updated) potentially biases a person...