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Holodeck

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A tool for creating and managing GPU-ready Cloud test environments.


📖 Documentation


✨ Features

  • Multi-OS Support: Ubuntu, Rocky Linux 9, Amazon Linux 2023 with automatic AMI resolution (guide)
  • Multi-Architecture: x86_64 and ARM64 with automatic architecture inference
  • Custom Templates: Run user-provided scripts at any provisioning phase (guide)
  • Multi-Node Clusters: HA Kubernetes clusters with kubeadm (guide)
  • Flexible Sources: Install components from packages, git, runfiles, or latest branches (guide)
  • Automatic IP Detection: No manual IP configuration needed for AWS (guide)

🚀 Quick Start

See docs/quick-start.md for a full walkthrough.

make build
sudo mv ./bin/holodeck /usr/local/bin/holodeck
holodeck --help

🛠️ Prerequisites

  • Go 1.20+
  • (For AWS) Valid AWS credentials in your environment
  • (For SSH) Reachable host and valid SSH key

See docs/prerequisites.md for details.


⚠️ Important: Kernel Compatibility

When installing NVIDIA drivers, Holodeck requires kernel headers matching your running kernel version. If exact headers are unavailable, Holodeck will attempt to find compatible ones, though this may cause driver compilation issues.

For kernel compatibility details and troubleshooting, see Kernel Compatibility in the prerequisites documentation.


📝 How to Contribute

See docs/contributing/ for full details.

Main Makefile Targets

  • make build – Build the holodeck binary
  • make test – Run all tests
  • make lint – Run linters
  • make clean – Remove build artifacts

🧑‍💻 Usage

See docs/commands/ for detailed command documentation and examples.

holodeck --help

Example: Create an environment

holodeck create -f ./examples/v1alpha1_environment.yaml

Example: List environments

holodeck list

Example: Delete an environment

holodeck delete <instance-id>

Example: Clean up AWS VPC resources

holodeck cleanup vpc-12345678

Example: Check status

holodeck status <instance-id>

Example: Dry Run

holodeck dryrun -f ./examples/v1alpha1_environment.yaml

Remote-access kubeconfig (opt-in)

By default, the kubeconfig holodeck produces is configured for in-VM use: file mode 0600 owned by the holodeck process user, and the server URL points at the cluster's internal IP. To run kubectl from outside the VPC (e.g., a GitHub Actions runner that provisioned the cluster), set kubernetes.remoteAccess: true:

spec:
  kubernetes:
    install: true
    installer: kubeadm
    remoteAccess: true

What changes when this is true:

  • The kubeconfig server URL is rewritten to https://<PublicDnsName>:6443.
  • The kubeconfig file is chowned to the bind-mounted workspace owner so the runner user (not just the action container's root) can read it. File mode stays 0600.

What does not change:

  • The security group still opens 6443 only to the auto-detected caller egress IP (utils.GetIPAddress()), not 0.0.0.0/0.
  • The embedded cluster admin cert is owner-only.

Platform: Linux/Darwin. On Windows, the chown step is a no-op.

For downstream CI repos (gpu-operator, k8s-device-plugin): set remoteAccess: true in your holodeck.yaml and replace any rsync + ssh + remote-run blocks in your workflow with a direct kubectl --kubeconfig=$GITHUB_WORKSPACE/kubeconfig … step.

Agentic skills

Holodeck ships an embedded catalog of agentic skills that teach an AI coding agent how to drive the CLI correctly. List the catalog:

holodeck skill list

Install a skill into your AI agent's native format:

# Claude Code (project-local: ./.claude/skills/<name>/SKILL.md)
holodeck skill add --claude using-holodeck

# Multiple agents at once
holodeck skill add --claude --cursor --codex --gemini using-holodeck

# Or install everything for every agent, user-wide
holodeck skill add --all --all-agents --global

Supported agents: Claude Code, Cursor, Codex CLI, Gemini CLI. Skills are short markdown guides authored against the actual CLI behavior; they version with the code so updates land alongside the features they describe.

📂 More


For more information, see the documentation directory.

About

Holodeck is a project to create test environments optimised for GPU projects.

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