Environmment for learning DeepStream - advise request

Lets start with the most important thing which is - I’m still learning ;)
I do work in media industry and we are looking into various AI use cases but for the purpose of this post lets assume I’m just trying to learn DeepStream in my private time on my private hardware which is Windows11 PC with RTX3090 GPU.
What would be best dev workflow in such case? Can I somehow use i.e. WSL or dockerized runtime to test my graphs built in windows graph composer? Both WSL and Docker for windows do seem to work fine with GPU - already using that with pytorch…
This may not be the most ‘professional’ setup but that is only what I can use right now. I will apreciate any advise.

WSL is not supported yet.
We propose to install on Ubuntu20.04 for native install Quickstart Guide — DeepStream 6.3 Release documentation (nvidia.com), or you may also use docker in Linux, refer the guide here Docker Containers — DeepStream 6.3 Release documentation (nvidia.com).

So what is the intended workflow for the Windows version of the Graph Composer?

You can run the application or deploy docker on remote machine such as Jetson or Ubuntu, please refer below docs:

The Window Graph Composer is only used as remote system Application Workflow — DeepStream 6.3 Release documentation

1 Like