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Machine Learning with the Elastic Stack

You're reading from   Machine Learning with the Elastic Stack Expert techniques to integrate machine learning with distributed search and analytics

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788477543
Length 304 pages
Edition 1st Edition
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Authors (2):
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Bahaaldine Azarmi Bahaaldine Azarmi
Author Profile Icon Bahaaldine Azarmi
Bahaaldine Azarmi
Rich Collier Rich Collier
Author Profile Icon Rich Collier
Rich Collier
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Toc

Table of Contents (12) Chapters Close

Preface Machine Learning for IT FREE CHAPTER Installing the Elastic Stack with Machine Learning Event Change Detection IT Operational Analytics and Root Cause Analysis Security Analytics with Elastic Machine Learning Alerting on ML Analysis Using Elastic ML Data in Kibana Dashboards Using Elastic ML with Kibana Canvas Forecasting ML Tips and Tricks Other Books You May Enjoy

Creating ML alerts manually

Now that we've seen the default bucket-level alert that you get automatically by using the ML UI in Kibana, let's look at a more complex watch that was created manually to solve a more interesting use case.

In this example, there is a desire to alert when a certain ML job has an elevated anomaly score at the bucket level, but it will only notify us (invoke the action clause) if there are also anomalies in two other supporting ML jobs within a 10 minute window (looking backwards in time). The main premise here is that the first job is an analysis of some important KPI that's worthy of Alerting upon, but only if there's supporting evidence of things that may have caused the KPI to deviate, some supporting, corroborating anomalies from other datasets analyzed in other ML jobs. If this is true, then give the user an alert that has...

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