source-to-image VS distribution-spec

You can try and use s2i (source to image) - https://github.com/openshift/source-to-image You deploy container to your cluster that produce another image

Surprised to see it supports source-to-image (S2I). If you're using S2I, you're likely using OpenShift where your development pipeline is figured out for you. You wouldn't be using Shipwright on that platform.

If that's not an option, I unfortunately don't know how to compile source code into an IMG file from github, but I have a feeling that there's quite a few people who are knowledgeable in these matters lurking around this subreddit. The only thing I found was this: https://github.com/openshift/source-to-image but I have no idea how or where exactly to execute the code outlined in the readme below. Looks promising though.

Source-To-Image (S2I) is a toolkit for building images directly from source code without Dockerfile. This tool works well for simple, expected scenarios and workflows but quickly becomes annoying and clumsy if you need little too much customization or if your project doesn't have the expected layout. You might consider using S2I if you are not very confident with Docker yet or if you build your images on OpenShift cluster, as builds with S2I are a built-in feature.

Back in 2013, a little company called Docker made it really easy to start using containers to package up applications. A big key to their success was the OCI (you can learn about that here), an industry wide initiative to have standards around how we package up our applications. Because of OCI standards, we have hundreds (maybe thousands?) of tools that can be combined to manage and deploy applications. So why aren’t we using this for packaging up Notebooks and AI models as well? It would make deploying, sharing, and managing our models easier for everyone involved.

Kubernetes on the backend used to utilize docker for much of its container runtime solutions. One of the modular features of Kubernetes is the ability to utilize a Container Runtime Interface or CRI. The problem was that Docker didn't really meet the spec properly and they had to maintain a shim to translate properly. Instead users could utilize the popular containerd or cri-o runtimes. These follow the Open Container Initiative or OCI's guidelines on container formats.

OCI stands for Open Container Initiative, and its goal as an organization is to define a specification for container formats and runtime.

https://opencontainers.org/

Here is Containerfile from the repo: https://github.com/ublue-os/bazzite/blob/main/Containerfile

apko allows us to build OCI container images from .apk packages.

Flagger's load testing service can be installed via a Kustomization resource based on manifests packaged as an artifact in an Open Container Initiative (OCI) registry

CRI-O is a lightweight container runtime for Kubernetes. It is an implementation of Kubernetes CRI to use Open Container Initiative (OCI) compatible runtimes for running pods. It supports runc and Kata Containers as the container runtimes, but any OCI-compatible runtime can be integrated.

So somebody else created runj (runj is an experimental, proof-of-concept OCI-compatible runtime for FreeBSD jails.) https://github.com/samuelkarp/runj