Images

Arrakis images

A machine boots an Arrakis image unless you pick another. Each is an official base with SSH, a login banner and everyday tools added: git, git-lfs, tmux, htop, nvtop, rsync, curl, wget, jq and an editor. Python is on the path in every SSH session.

CUDA 13.0 is the build pip install torch gives, so wheels built for PyTorch fit. It runs on every machine on Arrakis, Blackwell included: each has an NVIDIA driver from the 580 series or newer. The images are public on Docker Hub, so you can pull the same one on your own computer; goodailabs/arrakis:latest is the default.

A login shows the machine's GPUs, the image and the free disk:

  6 × NVIDIA RTX A4000, 16 GB each
  PyTorch 2.14.1, CUDA 13.0, Python 3.12.3, Ubuntu 24.04.5 LTS
  32 CPU cores, 125 GB memory, 412 GB free in /workspace

Work in /workspace. Everything on a machine, /workspace included, is deleted when it stops.

Your own images

Any image works: vLLM, SGLang, NVIDIA NGC containers, or your team's own image, public or private.

• On Images, choose Add an image and paste it the way docker pull takes it, such as vllm/vllm-openai:v0.11.0. For a public image you can also pick Your own image when you rent.
• Arrakis asks the image's registry first: the image must exist, be pullable and have a linux/amd64 build. A typo or a wrong token is refused before anything is charged.
• Registries: Docker Hub, GitHub (ghcr.io), Amazon ECR and ECR Public, Google (Artifact Registry and gcr.io), Azure (azurecr.io), NVIDIA NGC (nvcr.io), Quay, GitLab and Microsoft (mcr.microsoft.com), or your own: Harbor, Artifactory, Nexus, a self-hosted GitLab or Quay, any registry at its public DNS name, such as registry.example.com:5000/team/app:v1.
• SSH is added to any image at start, so you log in as root the same way. The image needs a shell.
• The first start on a machine downloads the image. Large images take longer: a 12 GB image can take 10 to 20 minutes on a slow network.

Private images

Tick It's private: log in to pull it when you add the image, and give the login docker login would take. Arrakis checks the image with it before saving, keeps it encrypted, and uses it only to pull this image when you rent. The password is never shown again.

• Amazon ECR: use an AWS user that can only pull images (the AmazonEC2ContainerRegistryReadOnly policy). Each time you rent, Arrakis trades the key for a fresh 12-hour pull login, the one aws ecr get-login-password prints, so the machine never sees the key itself.
• Your own registry: machines pull straight from it, from wherever they are, so it must answer on the public internet over HTTPS with a certificate from a public authority (such as Let's Encrypt). A registry behind a VPN or an IP allowlist can't be reached; one with a self-signed certificate is refused.
• Use a token that can only read. The machine pulls with it, and the image can stay cached on that machine after your rental ends, so keep secrets out of the image and pass them in when it runs.
• To change a token, choose Change login next to the image, or save the same image again with the new one. Removing the image deletes its login everywhere Arrakis kept it.

When it starts

If the command exits, the machine can't be reached any more. When in doubt, choose Wait for me to log in.

Reach a server on the machine through SSH:

ssh -L 8000:localhost:8000 root@<host> -p <port>
curl localhost:8000/v1/models

Environment variables

Add KEY=value pairs to an image, one per line. They're stored with the image, so keep secrets out of them and set those over SSH instead, for example export HF_TOKEN=... in your session.

From the CLI, API and agents

arrakis images list
arrakis images add vllm/vllm-openai:v0.11.0 --start image
arrakis instances create --node-id <node> --image vllm/vllm-openai:v0.11.0 --start image --termination-hours 2

A private image takes its login, with the token on stdin the way docker login takes it:

echo "$GITHUB_TOKEN" | arrakis images add ghcr.io/acme/trainer:v3 --username acme-bot --password-stdin
arrakis instances create --node-id <node> --template-id <image id> --termination-hours 2

curl -X POST $ARRAKIS_URL/v1/instances -H "Authorization: Bearer $ARRAKIS_TOKEN" -H "Content-Type: application/json" \
  -d '{"node_id": "<node>", "name": "vllm", "termination_hours": 2, "ssh_public_key": "ssh-ed25519 AAAA...",
       "image": "vllm/vllm-openai:v0.11.0", "start": "image"}'

• GET /v1/templates lists the Arrakis images and yours; POST /v1/templates saves one (image, start, command, environment, and for a private image registry_username and registry_password). The password is write-only: answers show private and registry_username. PATCH /v1/templates/{id} with both replaces the login.
• POST /v1/instances boots template_id, or any public image with a start.
• Over MCP, list_images lists them, private ones marked, and rent_gpu takes template_id or image.