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Development Containers: Use a container as a full-featured development environment. (by devcontainers)
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Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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features
A collection of development container 'features' for machine learning and data science (by iterative)
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gitpod
The developer platform for on-demand cloud development environments to create software faster and more securely.
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flask-surveys-container-app
An example Flask app for public surveys (no user auth) designed to be run inside Docker and deployed to Azure Container Apps with the Azure Developer CLI.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
My coworker uses this a lot at work. Being by Microsoft that dovetails really well with the visual studio code. I find the CLI to be okay I guess for something written in JavaScript. I prefer ASDF generally[1], there's always a lot of fiddling you have to do with containers, but this is more cross platform so there's that.
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.
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.
To be fair, GitPod claims they will support devcontainer.json: https://github.com/gitpod-io/gitpod/issues/7721
Have you tried this? https://github.com/asdf-vm/asdf-nodejs#nvmrc-and-node-versio...
Also lts, lts-hydrogen, etc are available to install I can see when running `asdf list all nodejs`