runner-images VS containerd

Yeah this is a good option if you'd like something to deploy yourself! You can also build an AMI from GitHub's upstream image definition (https://github.com/actions/runner-images/tree/main/images/ub...) if you'd like it to match what's available in GitHub-hosted Actions.

With Depot, we're moving towards deeper performance optimizations and observability than vanilla GitHub runners - we've integrated the runners with a cache storage cluster for instance, and we're working on deeper integration with the compute platform that we built for distributed container image builds - as well as expanding the types of builds we can process beyond Actions and Docker, for instance.

But different options will be better for different folks, and the `philips-labs` project is good at what it does.

Whoa, there's a lot of stuff in there [1] that gets installed straight from vendors, without pinning content checksums to a value known-good to Github.

I get it, they want to have the latest versions instead of depending on how long Ubuntu (or, worse, Debian) package maintainers take to package stuff into their mainline repositories... but this attack surface is nuts.

[1] https://github.com/actions/runner-images/tree/main/images/ub...

I had a similar experience with ARC (actions-runner-controller).

One of the machines in the fleet failed to sync its clock via NTP. Once a job X got scheduled to it, the runner pod failed authentication due to incorrect clock time, and then the whole ARC system started to behave incorrectly: job X was stuck without runners, until another workflow job Y was created, and then X got run but Y became stuck. There were also other wierd behaviors like this so I eventually rebuilt everything based on VMs and stopped using ARC.

Using VMs also allowed me to support the use of the official runner images [0], which is good for compatibility.

I feel more people would benefit from managed "self-hosted" runners, so I started DimeRun [1] to provide cheaper GHA runners for people who don't have the time/willingness to troubleshoot low-level infra issues.

[0]: https://github.com/actions/runner-images

Reminds me: Still waiting for native ARM support on GitHub Actions https://github.com/actions/runner-images/issues/5631

Used https://github.com/actions/runner-images to get the packages needed for Ubuntu 22.04 As the packer requires a builder, I used "null" builder to set it as localhost ref: https://developer.hashicorp.com/packer/docs/builders/null (It was way difficult to figure it out the 1st time) I had to modify the .pkr.hcl file to pick my provisioners. I could not understand the use of /opt/hostedtoolcache folder (which I did later)

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/.