From Remote Graphics Workstation to Machine Learning – GPU for every workload in Azure

Bonjour,J adore votre coopérative et je souhaite d etre particepant aavec vous MERCI ABDOKADER.
Very helpful and much easier to understand than the average git talk!
Interesting watch. We do something similar but it seems a little more intuitive than your solution;
We have a dev branch which everyone feature branches off then raises pull/merge requests once code is ready to merge back into dev.
However, when we are ready to publish/deploy we raise a pull/merge request into master. So master always tracks our production build(s)- no need to spin up MXXX branches and destroy them as you do.
One topic you didn't cover, which I would be interested in; How do you handle your merges? We try to rebase before merging to avoid any conflicts but haven't mastered the rebase process yet. I think we may be over complicating things and should maybe just merge and handle the conflicts.
I liked the video and it was nice to see this strategy being advocated again.
This seems a bit convoluted and not all that intuitive.
Personally, I prefer the way GitFlow works. It seems much more straight forward and intuitive.