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Implementing Splunk 7, Third Edition

Implementing Splunk 7, Third Edition

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Implementing Splunk 7, Third Edition

Implementing Splunk 7, Third Edition

5 (4)

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 (15 chapters)
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Calculating events per slice of time


There are a number of ways to calculate events per a specified period of time. All these techniques rely on rounding _time down to some period of time and then grouping the results by the rounded buckets of _time.

Using timechart

The simplest approach to counting events over time is simply to use timechart, like this:

sourcetype=impl_splunk_gen network=prod 
| timechart span=1m count 

In the table view, we see the following:

Charts in Splunk do not attempt to show more points than the pixels present on the screen. The user is, instead, expected to change the number of points to graph, using the bins or span attributes. Calculating average events per minute or per hour shows another way of dealing with this behavior.

If we only wanted to know about the minutes that actually had events instead of every minute of the day, we could use bucket and stats, like this:

sourcetype=impl_splunk_gen network=prod 
| bucket span=1m _time 
| stats count by _time 

The bucket...

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