features VS templates

* "Features" (https://containers.dev/implementors/features/ ) which allow you to quickly add functionality to your dev containers. For example, when I want to add the terraform CLI, I add the corresponding feature to the devcontainer.json.

The way I see it - it's a really nice way to make modules out of your Docker files (e.g. we need to install a tool and we need to run apt-get + some config, etc). And a simpler, JSON syntax to apply those modules on top of a base image.

I love the experience so far, we've done a few features (modules) - e.g. this one to install `nvtop` to see GPU utilization https://github.com/iterative/features/blob/main/src/nvtop/in...

The whole CUDA + nvtop + (some other tools) for an example project to be run on a remote machine via VS Code becomes like this:

https://github.com/shcheklein/hackathon/blob/main/.devcontai...

And that's enough to run ML training on GH Codespaces with GPU support. Super cool experience.

// For format details, see https://aka.ms/devcontainer.json. For config options, see the // README at: https://github.com/devcontainers/templates/tree/main/src/python { "name": "Python 3", // Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile "image": "mcr.microsoft.com/devcontainers/python:1-3.11-bullseye", "customizations": { "codespaces": { "openFiles": [ "README.md", "streamlit_app.py" ] }, "vscode": { "settings": {}, "extensions": [ "ms-python.python", "ms-python.vscode-pylance" ] } }, "updateContentCommand": "[ -f packages.txt ] && sudo apt update && sudo apt upgrade && sudo xargs apt install -y

Ooo, they have one for rails + postgres!

https://github.com/devcontainers/templates/tree/main/src/rub...

// For format details, see https://aka.ms/devcontainer.json. For config options, see the // README at: https://github.com/devcontainers/templates/tree/main/src/python { "name": "Python 3", // Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile "image": "mcr.microsoft.com/devcontainers/python:0-3.11-bullseye", "features": { "ghcr.io/devcontainers-contrib/features/coverage-py:2": {} } // Features to add to the dev container. More info: https://containers.dev/features. // "features": {}, // Use 'forwardPorts' to make a list of ports inside the container available locally. "forwardPorts": [5003], // Use 'postCreateCommand' to run commands after the container is created. "postCreateCommand": "pip install -r requirements.txt", "postAttachCommand": ".devcontainer/addcodespacename.sh && python main.py", // Configure tool-specific properties. "customizations": { "codespaces": { "openFiles": [ ".well-known/ai-plugin.json", "openapi.yaml" ] } } } // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root. // "remoteUser": "root" }

$ cd tracing_publisher $ mkdir .devcontainer $ cat > .devcontainer/devcontainer.json // For format details, see https://aka.ms/devcontainer.json. For config options, see the // README at: https://github.com/devcontainers/templates/tree/main/src/rust { "name": "Rust", "service": "rust-log-processing", "dockerComposeFile": "../docker-compose.yml", "features": { "ghcr.io/devcontainers/features/rust:1": {} }, "workspaceFolder": "/workspaces/${localWorkspaceFolderBasename}", "shutdownAction": "stopCompose" }

Based on a previous blog post, this devcontainer is now publicly available as a template for anyone to use at Dev Container Templates and integrated with publicly available Codespace images.

When you start a Codespace for a project, it will try to use whatever Dev Container you have specified in your repo, else it will try to use a kitchen sink container. That default kitchen sink is can be way too much and so if you will be working with Conda environments with an Anaconda or Miniconda Dev Container template instead.

This example uses the Docker in Docker dev container. There are others that may suit you better, feel free to customize to your needs. This example doesn’t rely on the exact type of dev container used.

there are already built docker images for common development environment. You can either use one of them, or build one from Docker file. Using a pre-built dev container doesn't mean you are only limited to that image, because you can still add other tools, which they are called features to that image. For a list of the pre-built templates check here, and for the other features that you can add check this. You don't need a Docker file, unless you want to build your dev environment step by step.