Book Image

Implementing Splunk 7, Third Edition - Third Edition

Book Image

Implementing Splunk 7, Third Edition - Third Edition

Overview of this book

Splunk is the leading platform that fosters an efficient methodology and delivers ways to search, monitor, and analyze growing amounts of big data. This book will allow you to implement new services and utilize them to quickly and efficiently process machine-generated big data. We introduce you to all the new features, improvements, and offerings of Splunk 7. We cover the new modules of Splunk: Splunk Cloud and the Machine Learning Toolkit to ease data usage. Furthermore, you will learn to use search terms effectively with Boolean and grouping operators. You will learn not only how to modify your search to make your searches fast but also how to use wildcards efficiently. Later you will learn how to use stats to aggregate values, a chart to turn data, and a time chart to show values over time; you'll also work with fields and chart enhancements and learn how to create a data model with faster data model acceleration. Once this is done, you will learn about XML Dashboards, working with apps, building advanced dashboards, configuring and extending Splunk, advanced deployments, and more. Finally, we teach you how to use the Machine Learning Toolkit and best practices and tips to help you implement Splunk services effectively and efficiently. By the end of this book, you will have learned about the Splunk software as a whole and implemented Splunk services in your tasks at projects
Table of Contents (19 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Extended SPL (search processing language)


The Splunk Machine Learning Toolkit contains numerous custom search commands, referred to as ML-SPL commands, that implement standard machine learning tasks. You can use these commands on any Splunk platform instance on which the Splunk Machine Learning Toolkit is installed.

These commands are fit, apply, summary, listmodels, deletemodel, and sample:

  • fit: This command is used to apply a machine learning model to Splunk data search results
  • apply: This is used to calculate predictions for the current search results based on a model that was learned by the fit command
  • summary: This generates a summary of a machine learning model that was learned using the fit command
  • listmodels: This command is used to create a list of machine learning models that were learned using the fit command
  • deletemodel: Used to delete a machine learning model that was learned using the fit command
  • sample: This command can be used to randomly sample or partition events

ML-SPL performance...