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A curated list of awesome tools and resources about dev containers for common programming languages and technology stacks to boost your developer productivity 🚀

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What's inside

Videos

Articles

Tools

  • AGRO

    A CLI that creates a durable Docker dev container workspace for AI coding agents on a laptop or remote VM, installs Claude Code, Codex, Pi, OpenCode, and other harnesses on demand, gives parallel agents separate git worktrees, and supports attaching from VS Code Dev Containers.

  • aicontainer

    A CLI that drops a sandboxed dev container into any project for running AI coding agents (Claude Code, Codex) in auto-approve mode, with filesystem isolation, a filtered Docker socket, and an opt-in outbound firewall.

  • crib

    A lean devcontainer runner that shells out to Docker/Podman. Single binary, no SSH, just

  • decolint

    A linter for Dev Container definitions, Features, and Templates, with checks for correctness, security, and reproducibility.

  • devcontainer-build-run

    A GitHub action and Azure DevOps task aimed at making it easier to re-use a Visual Studio Code devcontainer in a GitHub workflow or Azure DevOps pipeline.

  • devcontainer-devops

    A DevOps and Infrastructure-as-Code dev container (Terraform, Terragrunt, Azure CLI, Ansible, Kubernetes, PowerShell, .NET) with a

AI

  • AI Agents for BeginnersAI devcontainers

    Microsoft's agent-development course environment with Python, Node.js, .NET, and notebook support. Includes Microsoft Agent Framework and MCP SDK dependencies for agent and tool-calling examples.

  • Data Science with Python and RAI devcontainers

    Microsoft's Python, R, and Jupyter development environment for statistics and notebook-based experimentation. The published image is documented as x86-64.

  • Generative AI for BeginnersAI devcontainers

    Microsoft's devcontainer for learning LLM application development with Python, Jupyter notebooks, model APIs, and course dependencies.

  • Hugging Face Fine-Tuning (stack recipe)AI stack recipes

    Suggested stack: PyTorch, Transformers, Datasets, Accelerate, and PEFT, optionally with TRL, for reproducible fine-tuning and LoRA experiments. A compatible GPU is recommended for practical LLM workloads.

  • Jupyter Data Science NotebooksAI devcontainers

    Community devcontainer template based on Jupyter Docker Stacks, with selectable base images for dataset exploration, preprocessing, visualization, and machine learning.

  • LLM Evaluation Lab (stack recipe)AI stack recipes

    Suggested stack: Node.js, Python, promptfoo, and versioned evaluation datasets for comparing prompts and models, checking outputs, and catching quality regressions in CI. Hosted model evaluation does not require a local GPU.

Samples

  • C++ imageC/C++

    Develop C++ applications on Linux. Includes Debian C++ build tools (maintained by Microsoft).

  • Go Dev ContainerGo

    Ultimate Go development container for Visual Studio Code.

  • Go imageGo

    Develop Go based applications. Includes appropriate runtime args, Go, common tools, extensions, and dependencies (maintained by Microsoft).

  • Java imageJava

    Develop Java applications. Includes the JDK and Java extensions (maintained by Microsoft).

  • .NET image.NET

    Develop C# and .NET based applications. Includes all needed SDKs, extensions, and dependencies (maintained by Microsoft).

  • Node.js image w/ JavaScriptNode.js

    Develop Node.js based applications. Includes Node.js, eslint, nvm, and yarn (maintained by Microsoft).

Tutorials

Showing a sample of 66 resources. View the full list on GitHub →