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I moved from Windows to macOS for work — and I never want to go back
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this post was submitted on 02 Jul 2023
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I'm glad they mentioned rectangle, I found that app amazing. I have however upgraded to Amethyst for my app tiling though.
I'm a dev, so if I'm not doing .NET development. I found windows quite limiting. The new terminal stuff is nice but it's native on a mac. I'm not sure about Docker because that really spins the fans on my 16 Intel Pro.
Also, things like Spaces and virtual desktops have been pretty sweet for a long time now. Windows, I can't recall but it's been a horribly broken PowerToy for so long. I can't believe people were to recommending it. I think some people were telling me it's native now, but like, it's crazy how it wasn't done properly years ago.
Docker is not great on MacOS on Apple Silicon. Docker engine uses A TON of memory, around 8 gigs even with no containers running, and you can run into compatibility issues. My office, where we use Docker extensively, upgraded everyone's workstations to Apple silicon Macbook pros recently. We've been less than thrilled so far because turns out one of the images that we use as the base for many of our projects has trouble running on ARM chips. We fixed the problem, but still it was a whole thing. And there's no guarantee another similar problem won't pop up in the future either, unfortunately.
While it undeniably is a fantastic machine otherwise, I honestly think a higher end Dell or whatever that runs Linux would have been a better choice for the job. At least for the developer staff.
So your problem has nothing to do with ARM architecture or macOS itself, but on a lack of RAM.
Docker uses a lot of RAM on every platform, not only on macOS.
Looks like your company made a bad decision when choosing its hardware.
We use 16Gb M2 Pro to run docker instances running a copy of our infrastructure (ELK, CH, MariaDB, some maintenance batches, video encoding etc) with zero issue.
Docker for Mac has to run Linux in a virtual machine because macOS doesn’t natively support the containerisation APIs. That’s why it takes more memory and runs a bit slower than it does when running natively on a Linux machine.