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Splunk Operational Intelligence Cookbook

Splunk Operational Intelligence Cookbook

By : Josh Diakun, Raheja, Paul R. Johnson, Derek Mock
4.7 (3)
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Splunk Operational Intelligence Cookbook

Splunk Operational Intelligence Cookbook

4.7 (3)
By: Josh Diakun, Raheja, 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)
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Play Time – Getting Data In

In this chapter, we will cover the basic ways to get data into Splunk, in addition to some other recipes that will help prepare you for later chapters. You will learn about the following recipes:

  • Indexing files and directories
  • Getting data through network ports
  • Using scripted inputs
  • Using modular inputs
  • Using the Universal Forwarder to gather data
  • Receiving data using the HTTP Event Collector
  • Getting data from databases using DB Connect
  • Loading the sample data for this book
  • Data onboarding: Defining field extractions
  • Data onboarding: Defining event types and tags
  • Installing the Machine Learning Toolkit
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