
Machine Learning with the Elastic Stack
Expert techniques to integrate machine learning with distributed search and analytics
Packt Publishing
Published on 31. January 2019
Book
Paperback/Softback
304 pages
978-1-78847-754-3 (ISBN)
Description
Leverage Elastic Stack's machine learning features to gain valuable insight from your data
Key Features
Combine machine learning with the analytic capabilities of Elastic Stack
Analyze large volumes of search data and gain actionable insight from them
Use external analytical tools with your Elastic Stack to improve its performance
Book DescriptionMachine 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.What you will learn
Install the Elastic Stack to use machine learning features
Understand how Elastic machine learning is used to detect a variety of anomaly types
Apply effective anomaly detection to IT operations and security analytics
Leverage the output of Elastic machine learning in custom views, dashboards, and proactive alerting
Combine your created jobs to correlate anomalies of different layers of infrastructure
Learn various tips and tricks to get the most out of Elastic machine learning
Who this book is forIf you are a data professional eager to gain insight on Elasticsearch data without having to rely on a machine learning specialist or custom development, Machine Learning with the Elastic Stack is for you. Those looking to integrate machine learning within their search and analytics applications will also find this book very useful. Prior experience with the Elastic Stack is needed to get the most out of this book.
Key Features
Combine machine learning with the analytic capabilities of Elastic Stack
Analyze large volumes of search data and gain actionable insight from them
Use external analytical tools with your Elastic Stack to improve its performance
Book DescriptionMachine 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.What you will learn
Install the Elastic Stack to use machine learning features
Understand how Elastic machine learning is used to detect a variety of anomaly types
Apply effective anomaly detection to IT operations and security analytics
Leverage the output of Elastic machine learning in custom views, dashboards, and proactive alerting
Combine your created jobs to correlate anomalies of different layers of infrastructure
Learn various tips and tricks to get the most out of Elastic machine learning
Who this book is forIf you are a data professional eager to gain insight on Elasticsearch data without having to rely on a machine learning specialist or custom development, Machine Learning with the Elastic Stack is for you. Those looking to integrate machine learning within their search and analytics applications will also find this book very useful. Prior experience with the Elastic Stack is needed to get the most out of this book.
More details
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 17 mm
Weight
572 gr
ISBN-13
978-1-78847-754-3 (9781788477543)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Rich Collier | Bahaaldine Azarmi
Machine Learning with the Elastic Stack
Expert techniques to integrate machine learning with distributed search and analytics
E-Book
09/2024
1st Edition
Packt Publishing Limited
€38.49
Available for download
Persons
Rich Collier is a solutions architect at Elastic. Joining the Elastic team from the Prelert acquisition, Rich has over 20 years' experience as a solutions architect and pre-sales systems engineer for software, hardware, and service-based solutions. Rich's technical specialties include big data analytics, machine learning, anomaly detection, threat detection, security operations, application performance management, web applications, and contact center technologies. Rich is based in Boston, Massachusetts. Bahaaldine Azarmi, Global VP Customer Engineering at Elastic, guides companies as they leverage data architecture, distributed systems, machine learning, and generative AI. He leads the customer engineering team, focusing on cloud consumption, and is passionate about sharing knowledge to build and inspire a community skilled in AI.
Content
Table of Contents
Machine Learning for IT
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
Machine Learning for IT
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