You're reading from Data Analytics Using Splunk 9.x A practical guide to implementing Splunk's features for performing data analysis at scale

Product type Paperback

Published in Jan 2023

Publisher Packt

ISBN-13 9781803249414

Length 336 pages

Edition 1st Edition

Tools

Splunk

Concepts

Data Analysis

Author (1):

Dr. Nadine Shillingford

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Table of Contents (18) Chapters

Preface

1. Part 1: Getting Started with Splunk

2. Chapter 1: Introduction to Splunk and its Core Components FREE CHAPTER

3. Chapter 2: Setting Up the Splunk Environment

4. Chapter 3: Onboarding and Normalizing Data

5. Part 2: Visualizing Data with Splunk

6. Chapter 4: Introduction to SPL

7. Chapter 5: Reporting Commands, Lookups, and Macros

8. Chapter 6: Creating Tables and Charts Using SPL

9. Chapter 7: Creating Dynamic Dashboards

10. Part 3: Advanced Topics in Splunk

11. Chapter 8: Licensing, Indexing, and Buckets

12. Chapter 9: Clustering and Advanced Administration

13. Chapter 10: Data Models, Acceleration, and Other Ways to Improve Performance

14. Chapter 11: Multisite Splunk Deployments and Federated Search

15. Chapter 12: Container Management

16. Index

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17. Other Books You May Enjoy

To get the most out of this book

You will need access to deploy Amazon Web Services (AWS) instances in Chapter 2, Setting Up the Splunk Environment and Chapter 3, Onboarding and Normalizing Data. You will also need a tool such as puTTY to connect to the servers via the Secure Shell Protocol (SSH). The instructions outlined in Chapter 4 through to Chapter 7 were executed in macOS but can be run on any machine where Splunk Enterprise is installed, including Linux, macOS, or Windows environments.

Software/hardware covered in the book	Operating system requirements
Splunk Enterprise	Windows, macOS, or Linux
Splunk apps and add-ons
BOTS dataset
AWS instances
Amazon Web Services Account

You will need an Amazon Web Services account to deploy the instances in Chapter 2, Setting Up the Splunk Environment and Chapter 3, Onboarding and Normalizing Data.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to copying and pasting code.

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Table of Contents (18) Chapters

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Table of Contents (18) Chapters

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