Book Image

Splunk Best Practices

Book Image

Splunk Best Practices

Overview of this book

This book will give you an edge over others through insights that will help you in day-to-day instances. When you're working with data from various sources in Splunk and performing analysis on this data, it can be a bit tricky. With this book, you will learn the best practices of working with Splunk. You'll learn about tools and techniques that will ease your life with Splunk, and will ultimately save you time. In some cases, it will adjust your thinking of what Splunk is, and what it can and cannot do. To start with, you'll get to know the best practices to get data into Splunk, analyze data, and package apps for distribution. Next, you'll discover the best practices in logging, operations, knowledge management, searching, and reporting. To finish off, we will teach you how to troubleshoot Splunk searches, as well as deployment, testing, and development with Splunk.
Table of Contents (16 chapters)

Splunk architecture


At enterprise level it is rare to deal with a distributed deployment as opposed to a clustered deployment (and depending on the scale of your systems, the cluster and Disaster Recovery (DR) / High Availability (HA) components of Splunk will be pretty large). It's usually a good idea to use DNS addresses, hardware load balancing, and clustering (both search tier and indexing tier clusters) in order to meet all of the enterprise level DR/HA policies. In an enterprise level network, there are plenty of security restrictions that won't allow data to flow freely to Splunk from one source or another, and in this case, I am going to attempt to give some insight and an example of what has been used previously and does work in order to distribute data to different environments within an enterprise deployment. There are far too many aspects to Splunk architecture to cover in a single chapter, so I will use those that are relevant to the concept of a data router.

Clustering

Clustering...