Preface

Splunk is an increasingly popular platform for collecting, searching, monitoring, and analyzing ever-growing amounts of big data from applications, network devices, and Internet of Things sensors. Aggregating, centralizing, and analyzing log and event data with Splunk turns that data into answers regarding the health of machines and applications, counts and trends in customer transactions, security threats, and a multitude of other insights that may be valuable to a particular company or industry. 

Over the last five years, Splunk has more than doubled its number of customers, which now totals over 13,000 in 110 countries, including 89 of the Fortune 100. Given the increasing trend and opportunity to profit from the valuable insights derived by leveraging machine learning (ML) techniques on large data sets, Splunk has positioned itself well for further growth by building ML into its premium applications, such as IT Service Intelligence, Enterprise Security, User Behavior Analytics, and Industrial Asset Intelligence, in order to provide real-time and predictive analytics in those environments, as well as providing the Machine Learning Toolkit for developing custom solutions. So, as far as the IT professional who likes to work with data and data systems is concerned, learning how to architect, implement, administer, and/or use Splunk for analyzing data is a safe and valuable career investment for the foreseeable future. This book was written with a view to helping you embark on that journey and learn the landscape as quickly as possible.