Development-Machine VS openvscode-server

There is a version of docker that exposes itself as a web service; I've even done poc for that: https://github.com/Venthe/Development-Machine/tree/main

> Yeah, sadly there are entry level laptops cheaper than a phone or said monitor plus a keyboard and mouse

Many people already have a monitor, mouse, and keyboard lying around. They'll also have a phone already. Plus, there are very cheap docks where you can just slide your phone into a laptop shell, priced similarly to the worst and most awful Chromebooks imaginable.

> So nothing works offline.

You can run a vscode server on your phone (https://github.com/gitpod-io/openvscode-server/releases). What's lacking is the VSCode GUI, so pointing a browser at http://[::1]:8080/ will work just fine.

This already exists!! https://www.gitpod.io/

The next part is the 'Public access' parameter which needs to be aligned with the DB Subnet Group configuration. When set to No, the provisioned ENI will only have Private IP. If you try to access it from the Internet, your PC or a cloud development environment such as Gitpod that would obviously not be accessible. However, if you set it to Yes, the ENI will also have a Public IP and a Public hostname (DNS endpoint). This settings can be changed without the need to re-provision the RDS which is quite handy.

https://www.gitpod.io/ does this

Not sure what .devcontainer means, but you can take a look to https://github.com/gitpod-io/openvscode-server or https://github.com/coder/code-server

I am using this project (https://github.com/gitpod-io/openvscode-server/) to run on my Linux box, then I can access it's server through my web browser.

We look forward to integrating more with Gitpod in the future! Check out the Gitpod homepage for more information and new development environment templates.

I suggest you check out https://www.gitpod.io, which does more general provisioning of GitOps clusters/Pods in their managed Kubernetes clusters. It's not specifically ML, but we've looked at it for POC ML projects that want basic hosting.

The last option - the Dev Environments - is the most exciting functionality - it gives you the possibility to host development environments (similar to Gitpod) on AWS using Cloud9 but also, and this is really cool, using Visual Studio or JetBrains IDEs. When using that option, the IDE on your local PC is only the "presentation layer", the source code is stored and run on an AWS instance and the IDE uses remote connectivity to talk to the Dev Environment in the background.