Hi Strahil, 

color me surprised, too, especially considering where things are supposed to go 
in terms of roadmap.

Yet again, both oVIrt and Docker could be excused to think that they "own the 
hardware" they are running on, because it's a rather natural assumption, even 
if there are good reasons to run VMs and containers side-by-side as well as 

Yes, I believe, I have also done the reverse, put Docker on a system that was 
already running as oVirt compute host and it wasn't with better results, 
either. The biggest challenge is to repairing the node, without having to 
re-install the whole thing and I have gone through quite a few wobbles there, 
with colleagues who weren't too appreciative of having their ML jobs fail 
(those tend to be rather lenghty...)

I've managed to get CUDA work on KVM VMs twiddling the XML config files in 
these ways documented on the Web. But with oVirt those KVM XML config files get 
generated on the fly in Python and I'd have to fiddle with the code which does 

Actually I *did* try doing that at one point in time about a year or two ago, 
but I never found the right place, where that code actually was taken from. You 
see, there are copies of that code on every node, but also on the management 
engine. And you know how Ansible squirts code from machine to machine to do its 
magic, so that's were I stopped at one point, because running ML workloads 
containerized was more natural anyway and I was happy to have CPU-only VMs at 
their side.

Besides GPU access also disables live-migration and the abillity to move these 
long-running functional VMs around to manage resources for ML jobs is exactly 
what attracts me to oVirt.

Currently I am mostly probing around here, to see if what I try would be 
considered totally esoteric or irresponsible or if it's worth reporting as a 
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