5 ms·

Docker Was Too Slow, So We Replaced It: Nix in Production [video]

115 points by todsacerdoti 1y ago

forrestthewoods 1y ago
Alternative: just produce relocatable builds that don’t require all of this unnecessary extra infrastructure
- hamandcheese 1y ago
  Please elaborate. How does one "just" do that?
  - deleted 1y ago
    [deleted]
  - forrestthewoods 1y ago
    Deploying computer programs isn't that hard. What you actually need to run is pretty straight forward. Depend on glibc, copypaste all your other shared lib dependencies and plop them in RPATH. Pretend `/lib` is locked at initial install. Remove `/usr/lib` from the path and include everything. Docker was made because Linux sucks at running computer programs. Which is a very silly thing to be bad at. But here we are. What has happened in more recent years is that CMake sucks ass so people have been abusing Docker and now Nix as build system. Blech. The speaker does get it right at the end. A Bazel/Buck2 type solution is correct. An actual build system. They're abusing Nix and adding more layers to provide better caching. Sure, I guess. If you step back and look at the final output of what needs to be produced and deployed it's not all that complicated. Especially if you get rid of the super complicated package dependency graph resolution step and simply vendor the versions of the packages you want. Which everyone should do, and a company like Anthropic should definitely do.
    - hamandcheese 1y ago
      You contrast Nix with Bazel, and liken it to Docker, tells me you don't have a great grasp of what Nix is. It is far more similar to Bazel than it is to Docker. > Depend on glibc, copypaste all your other shared lib dependencies and plop them in RPATH. Pretend `/lib` is locked at initial install. Remove `/usr/lib` from the path and include everything. You are not describing relocatable builds at all. You are describing... well, it kinda sounds like how Nix handles RPATH.
      - forrestthewoods 1y ago
        Maybe. Ask 10 devs "what is Nix" and you'll get 15 to 25 responses. Maybe more. Nix is a million different things. There are certainly things within Nix that I like. But on the whole I think it's approximately two orders of magnitude more complicated than is necessary to efficiently build and deploy software.
        hamandcheese 1y ago
        Nix is 4 or 5 different things. I agree that the term is unfortunately quite overloaded. > But on the whole I think it's approximately two orders of magnitude more complicated than is necessary to efficiently build and deploy software. This might be true, if you dramatically constrain the problem space to something like "only build and deploy static Go binaries". If you have that luxury, by all means, simplify your life! But in the general case, it is an inherently complex problem space, and tools that attempt to rise to the challenge, like Bazel or Nix, will be lot more complex than a Dockerfile.
        forrestthewoods 1y ago
        My core hypothesis - which is maybe wrong - is that a good Bazel-like doesn't have to be that complex. I use Buck2 in my day job. For almost all projects its an order of magnitude simpler than CMake. It's got a ton of cruft to support a decades worth of targets that were made badly made. But the overall shape is actually pretty darn good. I think Starlark (and NixLang) are huge mistakes. Thou shalt not mix data and logic. Thou shalt not ever ever ever force users to use a language that doesn't have a great debugger. Build systems aren't actually that complicated. It's usually super duper trivial for me to write down the EXACT command I want to execute. It's "just" a matter of inducing a wobbly rube goldberg machine that can't be debugged to invoke the god damn command I know I want. Grumble grumble.
    - edoceo 1y ago
      > Docker was made because Linux sucks at running computer programs. I'm not sure that's why Docker was made. I'm pretty sure Linux is not-suck at running programs; it does run quite a lot of them. Might even be most of them? All those servers and phones and stuff.
      - forrestthewoods 1y ago
        Nah. Docker was created to solve the "works on my machine" problem. Because Linux made the wrong choice of having a global pool of shared libraries. So Docker hacked around this by containerizing a full copy of the desired environment. What Docker has done is kinda right. Programs should include all of their dependencies! But it sucks that you have to fight really hard and go out of your way to work around Linux's original choices. Now you may be thinking wait a second Linux was right! It's better to have a single copy of shared libraries so they can be securely updated just once instead of forcing every program to release a new update! Theoretically sure. But since everyone uses Docker you have to (slowly and painfully) rebuild the image and so that supposed benefit is moot. Womp womp. Additional reading if you are so inclined: https://jangafx.com/insights/linux-binary-compatibility https://jangafx.com/insights/linux-binary-compatibility
        edoceo 1y ago
        I'm firmly in the SO camp. One thing I see is that folk who are making software for Linux target Distribution rather than Linux generic. It's because of the SO "problem". It's a benefit of the tight coupling of Windows or Mac (which I don't use). Full agree that security updates in the Docker world is like the problem from static builds. Disclosure: I ship some stuff on Linux; for the problems we do static & docker. The demand side also seems to favour docker. I also prefer the docker method; for the compatibility reasons.
        forrestthewoods 1y ago
        Strong agree on the “target distro” or even “target specific env” versus Linux. I think I disagree on Windows being tightly coupled. Windows simply has a barren global library path. Programs merely included their extra DLLs adjacent to the exe. Very simple and reliable. Linux has added complexity in that glibc sucks and is horribly architected. GCC/Clang are bad and depend on the local environment waaaay too much. Linux ecosystem is very much not built to support sharing cross compiled binaries. It’s so painful. :(
    - literalAardvark 1y ago
      > simply vendor the versions of the packages you want That's really not how frontier research works. The packages they want are nightlies with lots of necessary fresh fixes that their team probably even contributed to, and waiting for Red Hat to include it in the next distro is completely out of the question.
      - forrestthewoods 1y ago
        Objectively false. There is a wealth of options between latest_master -> nightly -> ..... -> RedHat update. And there's only a very small number of specific libraries that you'd even want to consider for nightly. Majority of repo should absolutely be pinned and infrequently updated. There have been so many vendor supply chain exploits on HN in 2025 that I'd consider it borderline malpractice to use packages less than a month old in almost all cases. Certainly by default.
- musicale 1y ago
  Docker is overkill if all you really need is app packaging. Docker containers may not be portable anyway when the CUDA version used in the container has to match the kernel driver and GPU firmware, etc.
nickysielicki 1y ago
Doesn’t surprise me at all that people who know what they’re doing are building their own images with nix for ML. Tens of millions of dollars have been wasted in the past 2 years by teams who are too stupid to upgrade from buggy software bundled into their “golden” docker container, or too slow to upgrade their drivers/kernels/toolkits. It’s such a shame. It’s not that hard. Edit: see also the horrors that exist when you mix nvidia software versions: https://developer.nvidia.com/blog/cuda-c-compiler-updates-impacting-elf-visibility-and-linkage/ https://developer.nvidia.com/blog/cuda-c-compiler-updates-im...
- deleted 1y ago
  [deleted]
- dustbunny 1y ago
  Can you be explicit in how the dollars are being wasted? Maybe it's obvious to you but omjow does an old kernel waste money?
  - nickysielicki 1y ago
    The modern ML cards are much more raw than people realize. This isn’t a highly mature ecosystem with stable software, there are horrible bugs. It’s gotten better, but there are still big problems, and the biggest problem is that so many people are too stupid to use new releases with the fixes. They stick to the versions they already have because of nothing other than superstition. Go look at the llama 3 whitepaper and look at how frequently their training jobs died and needed to be restarted. Quoting: > During a 54-day snapshot period of pre-training, we experienced a total of 466 job interruptions. Of these, 47 were planned interruptions due to automated maintenance operations such as firmware upgrades or operator-initiated operations like configuration or dataset updates. The remaining 419 were unexpected interruptions, which are classified in Table 5. Approximately 78% of the unexpected interruptions are attributed to confirmed hardware issues, such as GPU or host component failures, or suspected hardware-related issues like silent data corruption and unplanned individual host maintenance events. [edit: to be clear, this is not meant to be a dig on the meta training team. They probably know what they’re doing. Rather, it’s meant to give an idea of how immature the nvidia ecosystem was when they trained llama 3 in early 2024. This is the kind of failure rates you can expect if you opt into using the same outdated software they were forced to use at the time.] The firmware and driver quality is not what people think it is. There’s also a lot of low-level software like NCCL and the toolkit that exacerbates issues in specific drivers and firmware versions. Grep for “workaround” in the NCCL source code and you’ll see some of them. It’s impossible to validate and test all permutations. It’s also worth mentioning that the drivers interact with a lot of other kernel subsystems. I’d point to HMM, the heterogeneous memory manager, which is hugely important for nvidia-uvm, which was only introduced in v6.1 and sees a lot of activity. Or go look at the amount of patches being applied to mlx5. Not all of those patches get back ported into stable trees. God help you if your network stack uses an out of tree driver.
pluto_modadic 1y ago
New corollary: sometimes new tech gets built because you don't know how to correctly use existing tech.
- dima55 1y ago
  Are you referring to this Nix effort or to Docker? Because that largely applies to most usages of Docker.
  - nine_k 1y ago
    Saying that Docker could be replaced by a simple script that does chroot + ufw + nsenter is like saying that Dropbox could be a simple script using rsync and cron. That is, technically not wrong, but it completely misses the UX / product perspective.
    - tymscar 1y ago
      Saying that nix is a simple script that does chroot + ufw + nsenter is missing the point even more
      - ranguna 1y ago
        Glancing over the UX/DX criticism is also missing the point. So I guess everyone in this thread is just looking at their own little world.
    - dima55 1y ago
      I'm saying that all usage of docker that I have ever seen is as a laughably over-engineered schroot. Literally. It can probably do more stuff, but I haven't seen it.
imiric 1y ago
Some people, when confronted with a problem, think "I know, I'll use Nix." Now they have two problems.
- HumanOstrich 1y ago
  Yup, and there's a high correlation between people rewriting everything in Rust and converting everything else to Nix. It's like a complexity fetish.
  - umvi 1y ago
    "your entire static website is running on GitHub pages? Sounds like legacy tech debt. I need to replace it with kubernetes pronto"
    - LaurensBER 1y ago
      The change with some engineers is a bit that if there's no user problem to solve, they'll happily solve some hypothetical problem. Having said that, my weekend project was "upgrading" my RSS reader to run HA on Kubernetes.
  - nine_k 1y ago
    It's removing complexity elsewhere, usually much more. Once you have invested in a relatively fixed bit of complexity, your other tasks become much easier to complete. Once you have invested in understanding the Clifford algebra, your whole classical electrodynamics turns from 30 equations into two. Once you have invested in writing a Fortran compiler, you can write numerical computations much easier and shorter than in assembly. Once you have invested in learning Nix, your whole elaborate build infra, plus chef / puppet / saltstack suddenly shrinks to a few declarations. Etc.
    - imiric 1y ago
      > Once you have invested in learning Nix, your whole elaborate build infra, plus chef / puppet / saltstack suddenly shrinks to a few declarations. Your analogy breaks down with Nix, since learning and using it is a hostile experience, unlike (I assume) your other examples. I have been using NixOS for about 5 years now on several machines, and I still don't know what I'm doing. Troubleshooting errors and implementing features is like climbing a mountain in the dark. The language syntax is alien. Most functionality is unintuitive. The errors are cryptic. The documentation ranges from poor to nonexistent. It tries to replace every package manager in existence. The community is unwelcoming. Guix addresses some of these issues, and at least it uses a sane language, but the momentum is, unfortunately, largely with Nix. Nix pioneered many important concepts that most operating systems and package managers should have. But the implementation and execution of those concepts leaves a lot to be desired. So, sure, if you and your team have patience to deal with all of its shortcomings, I can see how it can be useful. But personally, I would never propose using it in a professional setting, and would rather use established and more "complex" tooling most engineers are familiar with.
zenmac 1y ago
Great, can't wait for the systemd crew come out with: Docker was Too Slow, So We Replaced It: Systemd in Production [asciinema]
- mianos 1y ago
  No joke, it's already there, systemd-nspawn can run OCI containers.
  - miladyincontrol 1y ago
    Honestly I've been loving systemd-nspawn using mkosi to build containers, distroless ones too at that where sensible. Works a treat for building vms too. Scales wonderfully, fine grained permissions and configuration are exactly how you'd hope coming from systemd services. I appreciate it leverages various linux-isms like btrfs snapshots for faster read only or ephemeral containers. People still by large have this weird assumption that you can only do OS containers with nspawn, never too sure where that idea came from.
    - dusanh 1y ago
      Building VMs?
    - brainzap 1y ago
      I would like to learn this skill, if you could write a tutorial.
- hamandcheese 1y ago
  What does systemd have to do with the video?
- whateveracct 1y ago
  funnily enough, I stopped using Docker and use NixOS-configured systemd services half a decade ago and never looked back
  - 1y ago
amadio 1y ago
At CERN, software stacks are created centrally and software distribution for experiments is done with CVMFS (https://cernvm.cern.ch/fs/ https://cernvm.cern.ch/fs/), an HTTP-based read-only FUSE filesystem. EESSI (https://eessi.io https://eessi.io) has taken this model further by using CVMFS, Gentoo Prefix (https://prefix.gentoo.org https://prefix.gentoo.org), and EasyBuild to create full HPC environments for various architectures. CVMFS also has a docker driver to allow only used parts of a container image to be fetched on demand, which is very good for cases in which only a small part of a fat image is used in a job. EESSI has some documentation about it here: https://www.eessi.io/docs/tutorial/containers/ https://www.eessi.io/docs/tutorial/containers/
fouc 1y ago
Given that he calls their containers "pods", does anyone think he's using `podman --rootfs` to bypass overlayfs and the 128 layer limit? Or is it just a coincidence they're called "pods" ? Or he's using NixOS as the image OS and using nixos-containers (which use systemd-nspawn)
- 0x6c6f6c 1y ago
  Since no one responded, they're running on Kubernetes, where a unit of containers is called a "pod". A pod may be one or more containers, but it's the smallest deployable unit in the Kubernetes space. Their docker images were 11-35GB. Using the nix dockerTools approach would have resulted 100-300MB layers. These also may not even cache well between tags, though that's my intuition not knowledge. Especially if that's true, it wouldn't have improved the overall pull time issues they were having, which was 70-210s or image pull time on many new builds. In their case they added a sidecar container which was actually an init container, which runs before the primary container of the pod runs. They did utilize root privileges to perform things like bind mounting of nix store paths into the running container which made it possible for the container to run software provided in the /nix/store available from those bind mounts. This also meant both the Kubernetes hosts and containers did not require the nix daemon, the nix-sidecar running within the pod orchestrated pulling derivations , binding them, and running garbage collection at low priority in the background to ensure host SSDs don't run out of storage, while still allowing referenced derivations in the cluster to persist, improving sync time where the SSD may already contain all necessary derivations for a new pod startup.

115 points by todsacerdoti 1y ago

forrestthewoods 1y ago

Alternative: just produce relocatable builds that don’t require all of this unnecessary extra infrastructure

hamandcheese 1y ago
Please elaborate. How does one "just" do that?
- deleted 1y ago
  [deleted]
- forrestthewoods 1y ago
  Deploying computer programs isn't that hard. What you actually need to run is pretty straight forward. Depend on glibc, copypaste all your other shared lib dependencies and plop them in RPATH. Pretend `/lib` is locked at initial install. Remove `/usr/lib` from the path and include everything. Docker was made because Linux sucks at running computer programs. Which is a very silly thing to be bad at. But here we are. What has happened in more recent years is that CMake sucks ass so people have been abusing Docker and now Nix as build system. Blech. The speaker does get it right at the end. A Bazel/Buck2 type solution is correct. An actual build system. They're abusing Nix and adding more layers to provide better caching. Sure, I guess. If you step back and look at the final output of what needs to be produced and deployed it's not all that complicated. Especially if you get rid of the super complicated package dependency graph resolution step and simply vendor the versions of the packages you want. Which everyone should do, and a company like Anthropic should definitely do.
  - hamandcheese 1y ago
    You contrast Nix with Bazel, and liken it to Docker, tells me you don't have a great grasp of what Nix is. It is far more similar to Bazel than it is to Docker. > Depend on glibc, copypaste all your other shared lib dependencies and plop them in RPATH. Pretend `/lib` is locked at initial install. Remove `/usr/lib` from the path and include everything. You are not describing relocatable builds at all. You are describing... well, it kinda sounds like how Nix handles RPATH.
    - forrestthewoods 1y ago
      Maybe. Ask 10 devs "what is Nix" and you'll get 15 to 25 responses. Maybe more. Nix is a million different things. There are certainly things within Nix that I like. But on the whole I think it's approximately two orders of magnitude more complicated than is necessary to efficiently build and deploy software.
      - hamandcheese 1y ago
        Nix is 4 or 5 different things. I agree that the term is unfortunately quite overloaded. > But on the whole I think it's approximately two orders of magnitude more complicated than is necessary to efficiently build and deploy software. This might be true, if you dramatically constrain the problem space to something like "only build and deploy static Go binaries". If you have that luxury, by all means, simplify your life! But in the general case, it is an inherently complex problem space, and tools that attempt to rise to the challenge, like Bazel or Nix, will be lot more complex than a Dockerfile.
        forrestthewoods 1y ago
        My core hypothesis - which is maybe wrong - is that a good Bazel-like doesn't have to be that complex. I use Buck2 in my day job. For almost all projects its an order of magnitude simpler than CMake. It's got a ton of cruft to support a decades worth of targets that were made badly made. But the overall shape is actually pretty darn good. I think Starlark (and NixLang) are huge mistakes. Thou shalt not mix data and logic. Thou shalt not ever ever ever force users to use a language that doesn't have a great debugger. Build systems aren't actually that complicated. It's usually super duper trivial for me to write down the EXACT command I want to execute. It's "just" a matter of inducing a wobbly rube goldberg machine that can't be debugged to invoke the god damn command I know I want. Grumble grumble.
  - edoceo 1y ago
    > Docker was made because Linux sucks at running computer programs. I'm not sure that's why Docker was made. I'm pretty sure Linux is not-suck at running programs; it does run quite a lot of them. Might even be most of them? All those servers and phones and stuff.
    - forrestthewoods 1y ago
      Nah. Docker was created to solve the "works on my machine" problem. Because Linux made the wrong choice of having a global pool of shared libraries. So Docker hacked around this by containerizing a full copy of the desired environment. What Docker has done is kinda right. Programs should include all of their dependencies! But it sucks that you have to fight really hard and go out of your way to work around Linux's original choices. Now you may be thinking wait a second Linux was right! It's better to have a single copy of shared libraries so they can be securely updated just once instead of forcing every program to release a new update! Theoretically sure. But since everyone uses Docker you have to (slowly and painfully) rebuild the image and so that supposed benefit is moot. Womp womp. Additional reading if you are so inclined: https://jangafx.com/insights/linux-binary-compatibility https://jangafx.com/insights/linux-binary-compatibility
      - edoceo 1y ago
        I'm firmly in the SO camp. One thing I see is that folk who are making software for Linux target Distribution rather than Linux generic. It's because of the SO "problem". It's a benefit of the tight coupling of Windows or Mac (which I don't use). Full agree that security updates in the Docker world is like the problem from static builds. Disclosure: I ship some stuff on Linux; for the problems we do static & docker. The demand side also seems to favour docker. I also prefer the docker method; for the compatibility reasons.
        forrestthewoods 1y ago
        Strong agree on the “target distro” or even “target specific env” versus Linux. I think I disagree on Windows being tightly coupled. Windows simply has a barren global library path. Programs merely included their extra DLLs adjacent to the exe. Very simple and reliable. Linux has added complexity in that glibc sucks and is horribly architected. GCC/Clang are bad and depend on the local environment waaaay too much. Linux ecosystem is very much not built to support sharing cross compiled binaries. It’s so painful. :(
  - literalAardvark 1y ago
    > simply vendor the versions of the packages you want That's really not how frontier research works. The packages they want are nightlies with lots of necessary fresh fixes that their team probably even contributed to, and waiting for Red Hat to include it in the next distro is completely out of the question.
    - forrestthewoods 1y ago
      Objectively false. There is a wealth of options between latest_master -> nightly -> ..... -> RedHat update. And there's only a very small number of specific libraries that you'd even want to consider for nightly. Majority of repo should absolutely be pinned and infrequently updated. There have been so many vendor supply chain exploits on HN in 2025 that I'd consider it borderline malpractice to use packages less than a month old in almost all cases. Certainly by default.
musicale 1y ago
Docker is overkill if all you really need is app packaging. Docker containers may not be portable anyway when the CUDA version used in the container has to match the kernel driver and GPU firmware, etc.

nickysielicki 1y ago

Doesn’t surprise me at all that people who know what they’re doing are building their own images with nix for ML. Tens of millions of dollars have been wasted in the past 2 years by teams who are too stupid to upgrade from buggy software bundled into their “golden” docker container, or too slow to upgrade their drivers/kernels/toolkits. It’s such a shame. It’s not that hard. Edit: see also the horrors that exist when you mix nvidia software versions: https://developer.nvidia.com/blog/cuda-c-compiler-updates-impacting-elf-visibility-and-linkage/ https://developer.nvidia.com/blog/cuda-c-compiler-updates-im...

deleted 1y ago
[deleted]
dustbunny 1y ago
Can you be explicit in how the dollars are being wasted? Maybe it's obvious to you but omjow does an old kernel waste money?
- nickysielicki 1y ago
  The modern ML cards are much more raw than people realize. This isn’t a highly mature ecosystem with stable software, there are horrible bugs. It’s gotten better, but there are still big problems, and the biggest problem is that so many people are too stupid to use new releases with the fixes. They stick to the versions they already have because of nothing other than superstition. Go look at the llama 3 whitepaper and look at how frequently their training jobs died and needed to be restarted. Quoting: > During a 54-day snapshot period of pre-training, we experienced a total of 466 job interruptions. Of these, 47 were planned interruptions due to automated maintenance operations such as firmware upgrades or operator-initiated operations like configuration or dataset updates. The remaining 419 were unexpected interruptions, which are classified in Table 5. Approximately 78% of the unexpected interruptions are attributed to confirmed hardware issues, such as GPU or host component failures, or suspected hardware-related issues like silent data corruption and unplanned individual host maintenance events. [edit: to be clear, this is not meant to be a dig on the meta training team. They probably know what they’re doing. Rather, it’s meant to give an idea of how immature the nvidia ecosystem was when they trained llama 3 in early 2024. This is the kind of failure rates you can expect if you opt into using the same outdated software they were forced to use at the time.] The firmware and driver quality is not what people think it is. There’s also a lot of low-level software like NCCL and the toolkit that exacerbates issues in specific drivers and firmware versions. Grep for “workaround” in the NCCL source code and you’ll see some of them. It’s impossible to validate and test all permutations. It’s also worth mentioning that the drivers interact with a lot of other kernel subsystems. I’d point to HMM, the heterogeneous memory manager, which is hugely important for nvidia-uvm, which was only introduced in v6.1 and sees a lot of activity. Or go look at the amount of patches being applied to mlx5. Not all of those patches get back ported into stable trees. God help you if your network stack uses an out of tree driver.

pluto_modadic 1y ago

New corollary: sometimes new tech gets built because you don't know how to correctly use existing tech.

dima55 1y ago
Are you referring to this Nix effort or to Docker? Because that largely applies to most usages of Docker.
- nine_k 1y ago
  Saying that Docker could be replaced by a simple script that does chroot + ufw + nsenter is like saying that Dropbox could be a simple script using rsync and cron. That is, technically not wrong, but it completely misses the UX / product perspective.
  - tymscar 1y ago
    Saying that nix is a simple script that does chroot + ufw + nsenter is missing the point even more
    - ranguna 1y ago
      Glancing over the UX/DX criticism is also missing the point. So I guess everyone in this thread is just looking at their own little world.
  - dima55 1y ago
    I'm saying that all usage of docker that I have ever seen is as a laughably over-engineered schroot. Literally. It can probably do more stuff, but I haven't seen it.

imiric 1y ago

Some people, when confronted with a problem, think "I know, I'll use Nix." Now they have two problems.

HumanOstrich 1y ago
Yup, and there's a high correlation between people rewriting everything in Rust and converting everything else to Nix. It's like a complexity fetish.
- umvi 1y ago
  "your entire static website is running on GitHub pages? Sounds like legacy tech debt. I need to replace it with kubernetes pronto"
  - LaurensBER 1y ago
    The change with some engineers is a bit that if there's no user problem to solve, they'll happily solve some hypothetical problem. Having said that, my weekend project was "upgrading" my RSS reader to run HA on Kubernetes.
- nine_k 1y ago
  It's removing complexity elsewhere, usually much more. Once you have invested in a relatively fixed bit of complexity, your other tasks become much easier to complete. Once you have invested in understanding the Clifford algebra, your whole classical electrodynamics turns from 30 equations into two. Once you have invested in writing a Fortran compiler, you can write numerical computations much easier and shorter than in assembly. Once you have invested in learning Nix, your whole elaborate build infra, plus chef / puppet / saltstack suddenly shrinks to a few declarations. Etc.
  - imiric 1y ago
    > Once you have invested in learning Nix, your whole elaborate build infra, plus chef / puppet / saltstack suddenly shrinks to a few declarations. Your analogy breaks down with Nix, since learning and using it is a hostile experience, unlike (I assume) your other examples. I have been using NixOS for about 5 years now on several machines, and I still don't know what I'm doing. Troubleshooting errors and implementing features is like climbing a mountain in the dark. The language syntax is alien. Most functionality is unintuitive. The errors are cryptic. The documentation ranges from poor to nonexistent. It tries to replace every package manager in existence. The community is unwelcoming. Guix addresses some of these issues, and at least it uses a sane language, but the momentum is, unfortunately, largely with Nix. Nix pioneered many important concepts that most operating systems and package managers should have. But the implementation and execution of those concepts leaves a lot to be desired. So, sure, if you and your team have patience to deal with all of its shortcomings, I can see how it can be useful. But personally, I would never propose using it in a professional setting, and would rather use established and more "complex" tooling most engineers are familiar with.

zenmac 1y ago

Great, can't wait for the systemd crew come out with: Docker was Too Slow, So We Replaced It: Systemd in Production [asciinema]

mianos 1y ago
No joke, it's already there, systemd-nspawn can run OCI containers.
- miladyincontrol 1y ago
  Honestly I've been loving systemd-nspawn using mkosi to build containers, distroless ones too at that where sensible. Works a treat for building vms too. Scales wonderfully, fine grained permissions and configuration are exactly how you'd hope coming from systemd services. I appreciate it leverages various linux-isms like btrfs snapshots for faster read only or ephemeral containers. People still by large have this weird assumption that you can only do OS containers with nspawn, never too sure where that idea came from.
  - dusanh 1y ago
    Building VMs?
  - brainzap 1y ago
    I would like to learn this skill, if you could write a tutorial.
hamandcheese 1y ago
What does systemd have to do with the video?
whateveracct 1y ago
funnily enough, I stopped using Docker and use NixOS-configured systemd services half a decade ago and never looked back
- 1y ago

amadio 1y ago

At CERN, software stacks are created centrally and software distribution for experiments is done with CVMFS (https://cernvm.cern.ch/fs/ https://cernvm.cern.ch/fs/), an HTTP-based read-only FUSE filesystem. EESSI (https://eessi.io https://eessi.io) has taken this model further by using CVMFS, Gentoo Prefix (https://prefix.gentoo.org https://prefix.gentoo.org), and EasyBuild to create full HPC environments for various architectures. CVMFS also has a docker driver to allow only used parts of a container image to be fetched on demand, which is very good for cases in which only a small part of a fat image is used in a job. EESSI has some documentation about it here: https://www.eessi.io/docs/tutorial/containers/ https://www.eessi.io/docs/tutorial/containers/

fouc 1y ago

Given that he calls their containers "pods", does anyone think he's using `podman --rootfs` to bypass overlayfs and the 128 layer limit? Or is it just a coincidence they're called "pods" ? Or he's using NixOS as the image OS and using nixos-containers (which use systemd-nspawn)

0x6c6f6c 1y ago
Since no one responded, they're running on Kubernetes, where a unit of containers is called a "pod". A pod may be one or more containers, but it's the smallest deployable unit in the Kubernetes space. Their docker images were 11-35GB. Using the nix dockerTools approach would have resulted 100-300MB layers. These also may not even cache well between tags, though that's my intuition not knowledge. Especially if that's true, it wouldn't have improved the overall pull time issues they were having, which was 70-210s or image pull time on many new builds. In their case they added a sidecar container which was actually an init container, which runs before the primary container of the pod runs. They did utilize root privileges to perform things like bind mounting of nix store paths into the running container which made it possible for the container to run software provided in the /nix/store available from those bind mounts. This also meant both the Kubernetes hosts and containers did not require the nix daemon, the nix-sidecar running within the pod orchestrated pulling derivations , binding them, and running garbage collection at low priority in the background to ensure host SSDs don't run out of storage, while still allowing referenced derivations in the cluster to persist, improving sync time where the SSD may already contain all necessary derivations for a new pod startup.