bottlerocket VS setuptools

There's not one answer to your question, but here's mine: kubelet and AWS SSM (which, to the best of my knowledge will work on non-AWS infra it just needs to be provided creds). Bottlerocket <https://github.com/bottlerocket-os/bottlerocket#setup> comes batteries included with both of those things, and is cheaply provisioned with (ahem) TOML user-data <https://github.com/bottlerocket-os/bottlerocket#description-...>

In that specific case, one can also have "systemd for normal people" via its support for static Pod definitions, so one can run containerized toys on boot even without being a formal member of a kubernetes cluster

Don't overlook Bottlerocket, which despite coming out of AWS is not (AFAIK) AWS-centric: https://github.com/bottlerocket-os/bottlerocket#readme

It's also super handy for writing out static Pod manifests to have replace the brain-damaging Ignition as a less stupid alternative to cloud-init

According to this discussion - starting with Bottlerocket 1.13.0 (Mar 2023) new distributions will default to using Cgroups v2 interface for process organization and enforcing resource limits.

Well, the link I provided references the Bottlerocket docs which explains the control container and the admin container and also how you can configure Bottlerocket via the User Data field when launching it as an AMI. All the information appears to be in the docs

https://github.com/bottlerocket-os/bottlerocket/blob/develop...

On the server-side, there's Bottlerocket OS [1] (Amazon). They use A/B partitions for upgrades, and the idea is that you just run containers for anything non-base. Boot containers are used to do custom configuration at boot, and host-container (or DaemonSet, if you run K8S) is used for long-running services.

[1] https://github.com/bottlerocket-os/bottlerocket

Bottlerocket OS.

To add to the other excellent answers, I would recommend adding Bottlerocket to your reading list: https://github.com/bottlerocket-os/bottlerocket#readme

I'm also aware of (but haven't used) https://github.com/siderolabs/talos#readme

I just realized your question may have implied a desktop os, whereas Bottlerocket, Flatcar, and likely the others in this specific thread are server-side. I don't have much experience with trying to solve that problem on the desktop except for the horror-show that is snap

https://github.com/bottlerocket-os/bottlerocket/issues/2855 soon for bottlerocket, maybe you’ll see Amazon Linux 2023 for eks nodes soon too?

> I _think_ it's because there a bdist in PyPI for one, and not the other, so `pip` is using different "backends" that normalize the names into `METADATA` differently... ugh.

That isn't why: it's because `cast-from-env`'s sdist is from March 2023, while PEP 625 (which strongly stipulates package name normalization) was adopted in setuptools a month later[1].

But to take a step back: why does the difference in `pip freeze` affect you? It shouldn't matter to `pip`, since PyPI will happily serve from both the normalized and unnormalized names.

[1]: https://github.com/pypa/setuptools/issues/3593

To be fair, that seems to have been a 2 year warning:

https://github.com/pypa/setuptools/commit/3544de73b3662a27fa...

There was/is some discussion in setuptools about how to normalize the tarball (https://github.com/pypa/setuptools/issues/2133#issuecomment-...) coudl something similar be applied to Building Python itself ?

❯ yay -Sy python-setuptools python-jaraco.text ❯ pip show setuptools Name: setuptools Version: 67.7.0 Summary: Easily download, build, install, upgrade, and uninstall Python packages Home-page: https://github.com/pypa/setuptools Author: Python Packaging Authority Author-email: [email protected] License: Location: /usr/lib/python3.11/site-packages Requires: jaraco.text, more-itertools, ordered-set, packaging, platformdirs, tomli, validate-pyproject Required-by: Cerberus, fs, httpie, input-remapper, pecan, pycountry, python-lsp-server, reuse, setuptools-scm, zc.lockfile

Link: https://github.com/pypa/setuptools/issues/3772

For example, when it comes to Python, one option is to use the same packaging system that a huge number of open-source libraries and tools are published with. You can use setuptools or Hatch to build a "packaged" version of your code, and publish it to either the public PyPi repository or an internal one that you set up. Then your users can use pip to install your package, automatically fetch its dependencies, and keep it up to date, just like any other Python module.