CS PhD Student. Running a laptop with 16GB of RAM. I dont train ML models on my machine but whenever I have to debug stuff locally, I realize precisely how starved for RAM my computer is. I start by closing down FF. Just plain killing the browser. RAM down from 12GB to 7. Then I close the other IDE (usually working on two parallel repos). 7GB to 5. Squeeze out the last few megabytes by killing Spotify, Signal, and other forgotten Terminal windows. Then I start to load my model to memory. 5 times out of 7, its over 12-13 GB at which point my OS stops responding and I have to force reboot my system cursing and arms flailing.

> lightweight docker containers

If you're on macOS, there's no such thing as a “lightweight Docker container”. The container itself might be small, but Docker itself is running a full Linux virtual machine. In no world is that “lightweight”.

I was going to say, I'm on a 16gb 2015 macbook pro (not sure what to upgrade to) and Docker for Mac is _brutal_ on my machine, I can't even run it and work on other things at the same time without frustration

I run like 50 chrome tabs, a half dozen Intellij panes, youtube, slack, and a bunch of heavy containers at the same time, and that's just my dev machine.

My desktop is an ML container train/test machine. I also have ssh into two similar machines, and a 5 machine, 20GPU k8s cluster. I pretty much continuously have dozens of things building /running at once.

Maybe I'm an outlier though?

Yeah. I suspect most people here are software engineers (or related) and IDEs, Docker, and VMs are all standard tools in the SE toolbox. If they aren't using Docker or VMs, then they are probably doing application development, which is also pretty damn RAM hungry.

I do most of my development in Chrome, bash, and sublime text and I'm still using 28GB of RAM.

Depending on the requirements of your job—-just a single VS instance with chrome, postman and slack open takes around 5GB. Teams adds another GB or so. The rest probably another 2GB (SSMS and the like).

On my particular team we also run a dockerfile that includes elastic search, sql server, rabbitmq and consul—-I had to upgrade my work laptop from 16GB to 24GB to make it livable.

Wouldn't you just have all the heavy stuff on a server? I don't understand the goal of running something like sql server and other server type apps on a desktop/laptop.

Having a local environment speeds up development significantly.

When I’m developing I don’t want any network dependency. I love coding with no WiFi on planes, or on a mountain, etc.

If you are on linux, try out zram.

I could believe that for students because students are usually working on projects that are tiny by industry standards.

10 klocs is huge for a student project but tiny for a real-world project.

I do use intellij and similarly hungry IDEs all the time, with many other resource hungry processes without trouble on 8 GB of RAM.

Though truth is that I use zram, which everyone should who is not fortunate enough to have plenty of RAM, but does have a decent CPU.