Book Image

Splunk Operational Intelligence Cookbook. - Third Edition

By : Yogesh Raheja, Josh Diakun, Paul R. Johnson, Derek Mock
Book Image

Splunk Operational Intelligence Cookbook. - Third Edition

By: Yogesh Raheja, Josh Diakun, Paul R. Johnson, Derek Mock

Overview of this book

Splunk makes it easy for you to take control of your data, and with Splunk Operational Cookbook, you can be confident that you are taking advantage of the Big Data revolution and driving your business with the cutting edge of operational intelligence and business analytics. With more than 80 recipes that demonstrate all of Splunk’s features, not only will you find quick solutions to common problems, but you’ll also learn a wide range of strategies and uncover new ideas that will make you rethink what operational intelligence means to you and your organization. You’ll discover recipes on data processing, searching and reporting, dashboards, and visualizations to make data shareable, communicable, and most importantly meaningful. You’ll also find step-by-step demonstrations that walk you through building an operational intelligence application containing vital features essential to understanding data and to help you successfully integrate a data-driven way of thinking in your organization. Throughout the book, you’ll dive deeper into Splunk, explore data models and pivots to extend your intelligence capabilities, and perform advanced searching with machine learning to explore your data in even more sophisticated ways. Splunk is changing the business landscape, so make sure you’re taking advantage of it.
Table of Contents (12 chapters)

Generating alert events for high sensor readings

In this final recipe, you will create an alert type that triggers when temperature sensors in your metrics data exceed allowable levels. However, rather than fire off an email each time the alert fires, the alert will generate an event that is indexed by Splunk and searchable. This type of information could be useful in a situation where you wish to summarize verbose sensor data down to only specific notable events of interest. This notable event data could then be used for further visualization or analytics. For example, a single high temperature sensor event might be of less interest than a pattern of high temperature alerts over time, which could be an indicator of something more serious.

Getting ready

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