I don’t need x86 compatibility - we run native aarch64 on M-series Macs, and x86 on older Intel macs; prod is x86, but we’re considering moving to aarch64
our app is more memory intensive than CPU intensive - basically a bunch of Python microservices
That said, after some research into colima, it looks like it wins on I/O. So if you workload is relatively heavy on I/O, then it’s probably worth trying out.
My issue is memory. I just need so many Python interpreters running Flask, FastAPI, and Django (we use all three). On macOS, I need to reserve the memory for the VM, which means I need to balance how much I can run vs what other stuff I want to run on my system. On Linux, there is no VM, so I benefit from all of the disk caching that the kernel does and can get a much better experience, even when running a lot of services (most of those services are idle most of the time).
So switching to colima probably wouldn’t solve my problem, but maybe it would solve yours.
I’d appreciate hearing your thoughts about this medium article describing the use of Lima VM for docker on MacOS.
https://medium.com/@guillem.riera/the-most-performant-docker-setup-on-macos-apple-silicon-m1-m2-m3-for-x64-amd64-compatibility-da5100e2557d
A couple things to start:
That said, after some research into colima, it looks like it wins on I/O. So if you workload is relatively heavy on I/O, then it’s probably worth trying out.
My issue is memory. I just need so many Python interpreters running Flask, FastAPI, and Django (we use all three). On macOS, I need to reserve the memory for the VM, which means I need to balance how much I can run vs what other stuff I want to run on my system. On Linux, there is no VM, so I benefit from all of the disk caching that the kernel does and can get a much better experience, even when running a lot of services (most of those services are idle most of the time).
So switching to colima probably wouldn’t solve my problem, but maybe it would solve yours.