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)

Deployment server


Now that we know what types of data inputs there are, let's say that you have 500 Forwarders and they are different parts of unique systems. How do you manage all of that?

I've got three words for you: Splunk deployment server.

If you're not familiar with Splunk deployment server, I highly recommend you become familiar. With a large deployment of Splunk it's surely the easiest way to manage all of your data inputs for your various systems:

  • Basics: As a general rule of thumb, in Splunk best practices, in Splunk architecture, there should be at least one deployment server. That deployment server would sit behind a load balancing device (let's use F5) and have its own DNS address.

  • Reason: Because if anything ever happens to your DS, and it has a catastrophic failure, what happens when you need to spin up a new one and you can't have the same IP address? Assuming that you don't have a system such as Puppet, Chef, or StackIQ to use to manage your infrastructure, that means you...