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Implementing Splunk 7, Third Edition

Implementing Splunk 7, Third Edition

5 (4)
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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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What this book covers

Chapter 1, The Splunk Interface, walks you through the most common elements in the Splunk interface.

Chapter 2, Understanding Search, dives into the nuts and bolts of how searching works so that you can make efficient searches to populate the cool reports.

 

Chapter 3, Tables, Charts, and Fields, starts using fields for more than searches; we'll build tables and graphs. Then we'll learn how to make our own fields.

Chapter 4, Data Models and Pivots, covers data models and pivots, the pivot editor, pivot elements and filters, and sparklines.

Chapter 5, Simple XML Dashboards, demonstrates simple XML dashboards; their purpose; using wizards to build, schedule the generation of, and edit XML directly; and building forms.

Chapter 6, Advanced Search Examples, dives into advanced search examples, which can be a lot of fun. We'll expose some really powerful features of the search language and go over a few tricks that I've learned over the years.

Chapter 7, Extending Search, uses more advanced features of Splunk to help extend the search language and enrich data at search time.

Chapter 8, Working with Apps, explores what makes up a Splunk app, as well as the latest self-service app management (originally introduced in version 6.6) updated in version 7.0.

Chapter 9, Building Advanced Dashboards, covers module nesting, layoutPanel, intentions, and an alternative to intentions with SideView Utils.

Chapter 10, Summary Indexes and CSV Files, explores the use of summary indexes and the commands surrounding them.

Chapter 11, Configuring Splunk, overviews how configurations work and gives a commentary on the most common aspects of Splunk configuration. 

Chapter 12, Advanced Deployments, digs into distributed deployments and looks at how they are efficiently configured.

Chapter 13, Extending Splunk, shows a number of ways in which Splunk can be extended to input, manipulate, and output events.

Chapter 14, Machine Learning Toolkit, overviews the fundamentals of Splunk's Machine Learning Toolkit and shows how it can be used to create a machine learning model.

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