Knowledge Management

performance considerations macros vs. eventtypes vs. data-models

christian_l
Path Finder

Hi all,

are there any experiences out there regarding performance-comparison of macros, eventtypes and data-models?

We're currently planing a rebuild of a huge Splunk app which should get more flexible to be run within other landscapes. Therefore we'd like to build some kind of sublayer between the individual Splunk landscapes and the upper Splunk App-Part.
In Enterprise Security App this has been done using eventtypes.

I'm currently unsure if eventtypes are the best solution.
From my understanding eventtypes are some kind of "subsearches" - based on the behaviour of Splunk, this means a second search-thread is being initialized for each search eventtype-definition. Is this assumption correct?
How do macros behave in this situation? Only replacing parts of the search string, and no additional search-thread?
At least how do data-models fit in these thoughts?

How is the experience in performance and maintaining a huge set of macros, eventtypes or data-models?
Would love to hear some real-life experience.
Thank you all

Regards,
Christian

gfuente
Motivator

Hello

From a performace point of view:

  1. Macros: doesn't produce any performance improvements, they are just for code reusing and to keeps things simple an easy.
  2. Event-Types: they are not subsearaches, and have some kind of impact on performance but its not a big deal
  3. DataModels: If you use data model acceleration you will get a big performance improvement. So this will be your choice

Regards

Get Updates on the Splunk Community!

Introducing the 2024 SplunkTrust!

Hello, Splunk Community! We are beyond thrilled to announce our newest group of SplunkTrust members!  The ...

Introducing the 2024 Splunk MVPs!

We are excited to announce the 2024 cohort of the Splunk MVP program. Splunk MVPs are passionate members of ...

Splunk Custom Visualizations App End of Life

The Splunk Custom Visualizations apps End of Life for SimpleXML will reach end of support on Dec 21, 2024, ...