Rich Collier - Machine Learning with the Elastic Stack

Copyright 2019 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Commissioning Editor: Amey Varangaonkar
Acquisition Editor: Aditi Gour
Content Development Editor: Pratik Andrade
Technical Editor: Jovita Alva
Copy Editor: Safis Editing
Project Coordinator: Namrata Swetta
Proofreader: Safis Editing
Indexer: Priyanka Dhadke
Graphics: Jisha Chirayil
Production Coordinator: Arvindkumar Gupta

First published: January 2019

Production reference: 1300119

Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham
B3 2PB, UK.

ISBN 978-1-78847-754-3

www.packtpub.com

To the incredibly smart and talented development engineers of the Elastic Machine Learning team thanks for making an incredible product that artfully balances complexity with simplicity.

Mapt is an online digital library that gives you full access to over 5,000 books and videos, as well as industry leading tools to help you plan your personal development and advance your career. For more information, please visit our website.

• Spend less time learning and more time coding with practical eBooks and Videos from over 4,000 industry professionals

• Improve your learning with Skill Plans built especially for you

• Get a free eBook or video every month

• Mapt is fully searchable

• Copy and paste, print, and bookmark content

Did you know that Packt offers eBook versions of every book published, with PDF and ePub files available? You can upgrade to the eBook version at www.packt.com and as a print book customer, you are entitled to a discount on the eBook copy. Get in touch with us at customercare@packtpub.com for more details.

At www.packt.com , you can also read a collection of free technical articles, sign up for a range of free newsletters, and receive exclusive discounts and offers on Packt books and eBooks.

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, or Baha for short, is a solutions architect at Elastic. Prior to this position, Baha co-founded ReachFive, a marketing data platform focused on user behavior and social analytics. Baha also worked for different software vendors such as Talend and Oracle, where he held solutions architect and architect positions. Before Machine Learning with the Elastic Stack, Baha authored books including Learning Kibana 5.0, Scalable Big Data Architecture, and Talend for Big Data. Baha is based in Paris and has an MSc in computer science from Polytech'Paris.

Dan Noble is an accomplished full-stack web developer, data engineer, entrepreneur, and author with more than 12 years of industry experience and a passion for building novel software solutions that solve meaningful problems. Dan is the founder of Geofable, a software company that helps people tell stories with spatial data. He enjoys working with a variety of programming languages and tools, particularly Python, JavaScript, React, Elasticsearch, and Postgres.

Dan has been a user and advocate of Elasticsearch since 2011. He is the author of the book Monitoring Elasticsearch, and was a technical reviewer for several other books, including The Elasticsearch Cookbook, by Alberto Paro, and Learning Elasticsearch, by Abhishek Andhavarapu.

MatiasCascallares is a software engineer with more than 15 years of experience in software development in a variety of roles, with a deep focus on open source technologies and highly scalable environments. Having lived on three different continents, he has a wealth of experience in multicultural and distributed teams.

Nowadays, in the position of principal solutions architect at Elastic, he helps organizations to get value from their data and find success using the Elastic Stack. He has been involved in projects across multiple verticals, including finance and banking, transportation, e-commerce, and telecommunications.

If you're interested in becoming an author for Packt, please visit authors.packtpub.com and apply today. We have worked with thousands of developers and tech professionals, just like you, to help them share their insight with the global tech community. You can make a general application, apply for a specific hot topic that we are recruiting an author for, or submit your own idea.

Data analysis, manual charting, thresholding, and alerting have been an inherent part of IT and security operations for decades. Until the advent of sophisticated machine learning algorithms and techniques, much of the burden of proactive insight, problem detection, and root cause analysis fell onto the shoulders of the analysts. As the complexity and scale of modern applications and infrastructure has grown exponentially, it is apparent that humans need help. Elastic machine learning (ML) is an effective, easy-to-use solution for anomaly detection and forecasting use cases in relation to time-series machine data. This definitive elastic ML guide will get the reader proficient in the operation and techniques of advanced analytics without the need to be well-versed in data science.