Book Image

Splunk 9.x Enterprise Certified Admin Guide

By : Srikanth Yarlagadda
Book Image

Splunk 9.x Enterprise Certified Admin Guide

By: Srikanth Yarlagadda

Overview of this book

The IT sector's appetite for Splunk and skilled Splunk developers continues to surge, offering more opportunities for developers with each passing decade. If you want to enhance your career as a Splunk Enterprise administrator, then Splunk 9.x Enterprise Certified Admin Guide will not only aid you in excelling on your exam but also pave the way for a successful career. You’ll begin with an overview of Splunk Enterprise, including installation, license management, user management, and forwarder management. Additionally, you’ll delve into indexes management, including the creation and management of indexes used to store data in Splunk. You’ll also uncover config files, which are used to configure various settings and components in Splunk. As you advance, you’ll explore data administration, including data inputs, which are used to collect data from various sources, such as log files, network protocols (TCP/UDP), APIs, and agentless inputs (HEC). You’ll also discover search-time and index-time field extraction, used to create reports and visualizations, and help make the data in Splunk more searchable and accessible. The self-assessment questions and answers at the end of each chapter will help you gauge your understanding. By the end of this book, you’ll be well versed in all the topics required to pass the Splunk Enterprise Admin exam and use Splunk features effectively.
Table of Contents (17 chapters)
Part 1: Splunk System Administration
Part 2:Splunk Data Administration
Chapter 12: Self-Assessment Mock Exam

Data Parsing and Transformation

The first phases of the data journey is the input phase, which we discussed in detail in Chapter 9, Configuring Splunk Data Inputs. Data parsing is the second phase, followed by data being indexed on the disk. This chapter deals with the parsing phase, which comes right after the input phase and ends by handing over the data to the index phase for storage and preparation for data searching.

The question that might arise is what the need for the parsing phase is, as all the data has been collected, the metadata fields are set during the input phase, and finally, data is forwarded to indexers for indexing. The prominent features of the parsing phase are breaking the whole data stream into individual events, extracting and applying timestamps, setting the metadata fields to individual events, manipulating metadata before indexing, and transforming the data if needed. During the input phase, metadata fields such as the index, host, sourcetype, source...