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Yep, if you're running big IDEs (e.g. Rider/IntelliJ, Visual Studio), containers and VMs, 32GB is really a must. There always seem to be people in these threads

Yep, if you're running big IDEs (e.g. Rider/IntelliJ, Visual Studio), containers and VMs, 32GB is really a must. There always seem to be people in these threads claiming that 16GB or even 8GB is enough - I just don't understand how that could possibly be for most of the HN demographic.

the_only_law 6y ago
Yeah 32gb is my baseline now. I could probably work on a 16gb machine now but last time I was using an 8gb machine the memory was nearly constantly maxed out.
hkstm 6y ago
Do you think most of the HN demographic is actually running big IDEs, containers and VMs at the same time? I'm personally a CS student and never had to run more than a few lightweight docker containers + maybe one running some kind of database + VS Code and that has been working fine on a laptop with 8GB and pop_os. Could imagine that a lot of other people on HN are also just generally interested in tech but not necessarily running things that require a lot of memory locally.
- kortex 6y ago
  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?
- twodave 6y ago
  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.
  - aNoob7000 6y ago
    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.
    - twodave 6y ago
      Having a local environment speeds up development significantly.
    - leesalminen 6y ago
      When I’m developing I don’t want any network dependency. I love coding with no WiFi on planes, or on a mountain, etc.
  - kaba0 6y ago
    If you are on linux, try out zram.
- kaba0 6y ago
  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.
- geraltofrivia 6y ago
  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.
- MrDOS 6y ago
  > 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”.
  - taternuts 6y ago
    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
- mywittyname 6y ago
  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.
- TheCoelacanth 6y ago
  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.
deleted 6y ago
[deleted]
vlovich123 6y ago
I don’t understand how a demographic as technically intelligent as HN could make the flawed assumption that GBs of RAM in isolation of the entire system is all that matters. Consider the fact that iOS devices ship with half the RAM of Android devices and feel as responsive, have better battery life, and have better performance. The Apple stack is better optimized to take advantage of the hardware they have. Indeed, one of the reasons is because they have so few SKUs to worry about it focuses the engineering team (for example, in the past, internally engineers would complain about architectural design missteps that couldn’t be fixed because 32bit support wasn’t dropped yet and was pushed out yet another year). Now, obviously in a laptop use-case this is trickier since the source code is the same as the x86 version. It’s possible that the ARM code generation was much more space efficient (using -Oz instead of previously likely set at -O3). It’s also possible that they have migrated over to iOS frameworks in an even greater part than they were able to in the past, leveraging RAM optimizations that hadn’t been ported to macos). There could also be RAM usage optimizations baked around knowing you will always have a blazing fast NVME drive. Now you may not even need to keep data cached around and can just load straight from disk. Sure, not all workloads might fit (and if running x86 emulation the RAM hit might be worse). For a lot of use cases though, even many dev ones, it’s clearly enough. I wouldn’t be surprised if Apple used telemetry to make an intelligent bet around the amount of RAM they’d need.
- GordonS 6y ago
  > I don’t understand how a demographic as technically intelligent as HN could make the flawed assumption that GBs of RAM in isolation of the entire system is all that matters I didn't claim it was all that matters, and I haven't seen anyone else do that either. I do take the point of the rest of your comment though, and it may well be the case that Apple does some clever stuff. But realistically there is only so far that optimisations can take it - DDR4 is DDR4, and it's the workload that makes the most difference. > I wouldn’t be surprised if Apple used telemetry to make an intelligent bet around the amount of RAM they’d need. Your average Apple user is likely not a developer though (as others are very often pointing out on HN, whenever they make non-dev-friendly hardware choices). Furthermore, I would think such telemetry would be a self-fulfilling prophecy; if you have a pitiful 8GB of RAM, you're not going to punish yourself by trying to run workloads you know it wouldn't support.
uncletaco 6y ago
Anecdotal. I write client software for bioinformatics workflows. Usually web apps or clis. Right now with my mock db, Emacs, browser, and tooling I’m using ~5G of ram. At most I’ll use ~8GB by the end of the day. I also shut down at the end of the day and make judicious use of browser history and bookmarks. If I were compiling binaries regularly I guess I could see the use in having more ram but as far as I’m concerned 8 is enough and so far people find what I put out perform at.

the_only_law 6y ago

Yeah 32gb is my baseline now. I could probably work on a 16gb machine now but last time I was using an 8gb machine the memory was nearly constantly maxed out.

hkstm 6y ago

Do you think most of the HN demographic is actually running big IDEs, containers and VMs at the same time? I'm personally a CS student and never had to run more than a few lightweight docker containers + maybe one running some kind of database + VS Code and that has been working fine on a laptop with 8GB and pop_os. Could imagine that a lot of other people on HN are also just generally interested in tech but not necessarily running things that require a lot of memory locally.

kortex 6y ago
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?
twodave 6y ago
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.
- aNoob7000 6y ago
  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.
  - twodave 6y ago
    Having a local environment speeds up development significantly.
  - leesalminen 6y ago
    When I’m developing I don’t want any network dependency. I love coding with no WiFi on planes, or on a mountain, etc.
- kaba0 6y ago
  If you are on linux, try out zram.
kaba0 6y ago
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.
geraltofrivia 6y ago
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.
MrDOS 6y ago
> 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”.
- taternuts 6y ago
  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
mywittyname 6y ago
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.
TheCoelacanth 6y ago
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.

deleted 6y ago

[deleted]

vlovich123 6y ago

I don’t understand how a demographic as technically intelligent as HN could make the flawed assumption that GBs of RAM in isolation of the entire system is all that matters. Consider the fact that iOS devices ship with half the RAM of Android devices and feel as responsive, have better battery life, and have better performance. The Apple stack is better optimized to take advantage of the hardware they have. Indeed, one of the reasons is because they have so few SKUs to worry about it focuses the engineering team (for example, in the past, internally engineers would complain about architectural design missteps that couldn’t be fixed because 32bit support wasn’t dropped yet and was pushed out yet another year). Now, obviously in a laptop use-case this is trickier since the source code is the same as the x86 version. It’s possible that the ARM code generation was much more space efficient (using -Oz instead of previously likely set at -O3). It’s also possible that they have migrated over to iOS frameworks in an even greater part than they were able to in the past, leveraging RAM optimizations that hadn’t been ported to macos). There could also be RAM usage optimizations baked around knowing you will always have a blazing fast NVME drive. Now you may not even need to keep data cached around and can just load straight from disk. Sure, not all workloads might fit (and if running x86 emulation the RAM hit might be worse). For a lot of use cases though, even many dev ones, it’s clearly enough. I wouldn’t be surprised if Apple used telemetry to make an intelligent bet around the amount of RAM they’d need.

GordonS 6y ago
> I don’t understand how a demographic as technically intelligent as HN could make the flawed assumption that GBs of RAM in isolation of the entire system is all that matters I didn't claim it was all that matters, and I haven't seen anyone else do that either. I do take the point of the rest of your comment though, and it may well be the case that Apple does some clever stuff. But realistically there is only so far that optimisations can take it - DDR4 is DDR4, and it's the workload that makes the most difference. > I wouldn’t be surprised if Apple used telemetry to make an intelligent bet around the amount of RAM they’d need. Your average Apple user is likely not a developer though (as others are very often pointing out on HN, whenever they make non-dev-friendly hardware choices). Furthermore, I would think such telemetry would be a self-fulfilling prophecy; if you have a pitiful 8GB of RAM, you're not going to punish yourself by trying to run workloads you know it wouldn't support.

uncletaco 6y ago

Anecdotal. I write client software for bioinformatics workflows. Usually web apps or clis. Right now with my mock db, Emacs, browser, and tooling I’m using ~5G of ram. At most I’ll use ~8GB by the end of the day. I also shut down at the end of the day and make judicious use of browser history and bookmarks. If I were compiling binaries regularly I guess I could see the use in having more ram but as far as I’m concerned 8 is enough and so far people find what I put out perform at.