Book Image

Data Analytics Using Splunk 9.x

By : Dr. Nadine Shillingford
5 (1)
Book Image

Data Analytics Using Splunk 9.x

5 (1)
By: Dr. Nadine Shillingford

Overview of this book

Splunk 9 improves on the existing Splunk tool to include important features such as federated search, observability, performance improvements, and dashboarding. This book helps you to make the best use of the impressive and new features to prepare a Splunk installation that can be employed in the data analysis process. Starting with an introduction to the different Splunk components, such as indexers, search heads, and forwarders, this Splunk book takes you through the step-by-step installation and configuration instructions for basic Splunk components using Amazon Web Services (AWS) instances. You’ll import the BOTS v1 dataset into a search head and begin exploring data using the Splunk Search Processing Language (SPL), covering various types of Splunk commands, lookups, and macros. After that, you’ll create tables, charts, and dashboards using Splunk’s new Dashboard Studio, and then advance to work with clustering, container management, data models, federated search, bucket merging, and more. By the end of the book, you’ll not only have learned everything about the latest features of Splunk 9 but also have a solid understanding of the performance tuning techniques in the latest version.
Table of Contents (18 chapters)
1
Part 1: Getting Started with Splunk
5
Part 2: Visualizing Data with Splunk
10
Part 3: Advanced Topics in Splunk

Summary

We focused on writing Splunk queries in this chapter. Before looking at the queries, we explored the Splunk search interface in the Search and Reporting app. We looked at seven different parts of the search interface, including the search bar, interesting fields, and time picker. We wrote simple filters using key/value conditions, including specifying the index and sourcetype in the index=botsv1 sourcetype=iis query. We also learned how we can increase the complexity of our queries using the pipe symbol. We then used this knowledge to get more out of our searches by using the pipe symbol and introducing commands such as eval, fields, regex, and rex. The eval command can be used with a variety of Splunk functions, including round() and lower(), which work on numerical and string values, respectively. Commands such as rex can be used to extract values from Splunk events using regular expressions.

We will explore more advanced reporting commands in Chapter 5, Reporting Commands...