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Current lineup has too little RAM for many dev-tasks. Like running multiple docker containers, or developing in a ram-hungry language (java+intellij), or runnin

Current lineup has too little RAM for many dev-tasks. Like running multiple docker containers, or developing in a ram-hungry language (java+intellij), or running emulators (mobile dev). If the next MBP16 lineup with M1 (M2?) supports 32+ GBs of RAM other vendors will have to step up their game, though.

eatbitseveryday 6y ago
> running emulators (mobile dev) 16GiB is insufficient for mobile? iPhone SE has 3GiB and 12 has 6GiB. That is less than half your M1 RAM. How much more does the emulator consume?
- matsemann 6y ago
  At least my coworker's former 16GB MBP (until he got a new one now) basically halted when the emulators were running, and he had to close lots of programs. Not strictly appdev, though, so he was then running and developing our backends locally, running some other needed services in docker, and then working on the android and ios app at the same time to match and test the changes in the backend. So basically all of my examples above, but at the same time. So not strictly necessary, but when you're used to it going back to having to work around the limitations is burdensome. People not having lots of ram seldom complain, but they don't know how much time they're wasting on an inefficient workflow.
- toomanybeersies 6y ago
  I'm not a mobile developer, but between docker, my IDE, Chrome, and whatever other crap I've got running on my 16 GB MBP, I'm using 14.8 GB of RAM and 20 GB of swap.
  - nottorp 6y ago
    I'm using 25 G of ram (out of 32) right now and I only have one IDE open. When I need to run VMs as well, sky's the limit.
grantcox 6y ago
I have a M1 Mini with 16GB memory. The machine's SSD is incredibly fast, so it swaps very well. Whereas my 2019 MBP will suffer incredibly when I start running out of memory (it literally becomes unusable and requires a hard reboot), the M1 will transparently start swapping, and I generally don't even notice. Just the other day I noticed a python process was running slower than expected, and it was a bug in my Pandas code so I had allocated 85GB of memory. The rest of the system was operating normally - Chrome, VSCode, Music were all fine. I regularly kick off a data pipeline process with 8x concurrency, even though each process uses between 4-6GB memory. It's probably inefficient in some way, but overall is still much faster than running at 2x concurrency (where everything would fit in memory and it wouldn't need to swap).

eatbitseveryday 6y ago

> running emulators (mobile dev) 16GiB is insufficient for mobile? iPhone SE has 3GiB and 12 has 6GiB. That is less than half your M1 RAM. How much more does the emulator consume?

matsemann 6y ago
At least my coworker's former 16GB MBP (until he got a new one now) basically halted when the emulators were running, and he had to close lots of programs. Not strictly appdev, though, so he was then running and developing our backends locally, running some other needed services in docker, and then working on the android and ios app at the same time to match and test the changes in the backend. So basically all of my examples above, but at the same time. So not strictly necessary, but when you're used to it going back to having to work around the limitations is burdensome. People not having lots of ram seldom complain, but they don't know how much time they're wasting on an inefficient workflow.
toomanybeersies 6y ago
I'm not a mobile developer, but between docker, my IDE, Chrome, and whatever other crap I've got running on my 16 GB MBP, I'm using 14.8 GB of RAM and 20 GB of swap.
- nottorp 6y ago
  I'm using 25 G of ram (out of 32) right now and I only have one IDE open. When I need to run VMs as well, sky's the limit.

grantcox 6y ago

I have a M1 Mini with 16GB memory. The machine's SSD is incredibly fast, so it swaps very well. Whereas my 2019 MBP will suffer incredibly when I start running out of memory (it literally becomes unusable and requires a hard reboot), the M1 will transparently start swapping, and I generally don't even notice. Just the other day I noticed a python process was running slower than expected, and it was a bug in my Pandas code so I had allocated 85GB of memory. The rest of the system was operating normally - Chrome, VSCode, Music were all fine. I regularly kick off a data pipeline process with 8x concurrency, even though each process uses between 4-6GB memory. It's probably inefficient in some way, but overall is still much faster than running at 2x concurrency (where everything would fit in memory and it wouldn't need to swap).