containerd VS distribution-spec

Containerd and nerdctl

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.

Container Engine: A runtime that executes and manages containers. Docker and containerd are popular container engines.

Multiple container runtimes are supported, like conatinerd, cri-o, or other CRI compliant runtimes.

This is a failed attempt to upstream part of containerd changes: https://github.com/containerd/containerd/pull/8789

Other part of containerd changes waits for gods-know-what: https://github.com/containerd/containerd/pull/9054

But I haven't gave up yet.

containerd is required by kubernetes to handle containers on its behalf. A big thanks to the HostAfrica blog for the information on setting containerd up for debain. So the containerd install will need to happen on both the WSL2 instance and the Raspberry Pis. For WSL2 you can just install containerd directly:

The context deadline exceeded: unknown is also in containerd, and is a known problem.

Get:1 https://download.docker.com/linux/ubuntu focal/stable amd64 containerd.io amd64 1.6.21-1 [28.3 MB]

Docker Desktop adds a bunch of stuff to simplify local development and that’s why it has a larger memory footprint. You don’t use that when deploying but something like https://containerd.io/.

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