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  • Book Overview & Buying Machine Learning with the Elastic Stack
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Machine Learning with the Elastic Stack

Machine Learning with the Elastic Stack

By : Rich Collier, Bahaaldine Azarmi
4.8 (5)
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Machine Learning with the Elastic Stack

Machine Learning with the Elastic Stack

4.8 (5)
By: Rich Collier, Bahaaldine Azarmi

Overview of this book

Machine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting. The book starts with installing and setting up Elastic Stack. You will perform time series analysis on varied kinds of data, such as log files, network flows, application metrics, and financial data. As you progress through the chapters, you will deploy machine learning within the Elastic Stack for logging, security, and metrics. In the concluding chapters, you will see how machine learning jobs can be automatically distributed and managed across the Elasticsearch cluster and made resilient to failure. By the end of this book, you will understand the performance aspects of incorporating machine learning within the Elastic ecosystem and create anomaly detection jobs and view results from Kibana directly.
Table of Contents (12 chapters)
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IT Operational Analytics and Root Cause Analysis

Up until this point, we have extensively explained the value of detecting anomalies across metrics and logs separately. This is extremely valuable, of course. In some cases, however, the knowledge that a particular metric or log file has gone awry may not tell the whole story of what is going on. It may, for example, be pointing at a symptom and not the cause of the problem. To have a better understanding of the full scope of an emerging problem, it is often helpful to look holistically at many aspects of a system or situation. This involves smartly analyzing multiple kinds of related datasets together.

In this chapter, we will cover the following topics:

  • Understanding the roles and importance of key performance indicators (KPIs) and other supporting metrics
  • Learning methods to organize, filter, and enrich the data to supply context...
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Machine Learning with the Elastic Stack
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