Book Image

Advanced Splunk

By : Ashish Kumar Tulsiram Yadav
Book Image

Advanced Splunk

By: Ashish Kumar Tulsiram Yadav

Overview of this book

Master the power of Splunk and learn the advanced strategies to get the most out of your machine data with this practical advanced guide. Make sense of the hidden data of your organization – the insight of your servers, devices, logs, traffic and clouds. Advanced Splunk shows you how. Dive deep into Splunk to find the most efficient solution to your data problems. Create the robust Splunk solutions you need to make informed decisions in big data machine analytics. From visualizations to enterprise integration, this well-organized high level guide has everything you need for Splunk mastery. Start with a complete overview of all the new features and advantages of the latest version of Splunk and the Splunk Environment. Go hands on with uploading data, search commands for basic and advanced analytics, advanced visualization techniques, and dashboard customizing. Discover how to tweak Splunk to your needs, and get a complete on Enterprise Integration of Splunk with various analytics and visualization tools. Finally, discover how to set up and use all the new features of the latest version of Splunk.
Table of Contents (20 chapters)
Advanced Splunk
Credits
About the Author
Acknowledgements
About the Reviewer
www.PacktPub.com
Preface
Index

Correlation


The following set of commands that belongs to the set of the Correlation category of Splunk is used to generate insight from the given dataset by correlating various data points from one or more data sources. In simple terms, correlation means a connection or relationship between two or more things. The set of commands includes associate, contingency, correlate, and so on.

The correlate command

The correlate Splunk command is used to calculate the correlation between different fields of the events. In simpler terms, it means that this command returns an output that shows what is the co-occurrence between different fields of the given dataset. Let's say I have a dataset that has information about web server failures. Then, using the correlate command, a user can find out whenever there is a failure what other field values have also occurred most of the time. So, insight can be generated to show that whenever X set of events occurs, Y also occurs, and hence, failures can be detected...