Decision Tree for Selecting the Right VM Types in Databricks – Looking for Feedback & Improvements!

saicharandeepb — Fri, 14 Nov 2025 11:03:27 GMT

Hi everyone,

I’ve been working on an updated VM selection decision tree for Azure Databricks, designed to help teams quickly identify the most suitable worker types based on workload behavior. I’m sharing the latest version (In this updated version I’ve also incorporated several recommendations from the community)below and would really appreciate feedback from the community!

For anyone interested in the background, my original thought process is shared here:
🔗 https://community.databricks.com/t5/data-engineering/looking-for-suggestions-designed-a-decision-tree-to-recommend/td-p/138101

I’m looking forward to any further suggestions or improvements you might have—thanks in advance!

Re: Decision Tree for Selecting the Right VM Types in Databricks – Looking for Feedback & Improv

Sahil_Kumar — Sun, 07 Dec 2025 12:42:21 GMT

Hi saicharandeepb,

You can enrich your chart by adding GPU-accelerated VMs.

For computationally challenging tasks that demand high performance, like those associated with deep learning, Azure Databricks supports compute resources that are accelerated with graphics processing units (GPUs). For more information, see GPU-enabled compute.

Thanks!

topic Decision Tree for Selecting the Right VM Types in Databricks – Looking for Feedback & Improvements! in Data Engineering

Decision Tree for Selecting the Right VM Types in Databricks – Looking for Feedback & Improvements!

Re: Decision Tree for Selecting the Right VM Types in Databricks – Looking for Feedback & Improv