How to use a container registry with Quake AI
Coming from another cloud?
▸AWS·ECR
This Quake AI feature maps to AWS’s ECR.
▸Azure·ACR
This Quake AI feature maps to Azure’s ACR.
▸DigitalOcean·Container Registry
This Quake AI feature maps to DigitalOcean’s Container Registry.
▸Google Cloud·Artifact Registry
This Quake AI feature maps to Google Cloud’s Artifact Registry.
How to use a container registry with Quake AI
Pull private container images into Quake AI workloads from a third-party registry. Quake AI does not run a managed container registry. Push images to GitHub Container Registry (GHCR), GitLab Container Registry, Docker Hub, Quay, or a self-hosted registry on a Quake AI instance.
Pick a registry#
| Registry | Best for | Note |
|---|---|---|
| GHCR | GitHub-hosted repos | Free private images at modest scale |
| GitLab Container Registry | GitLab CI pipelines | Integrated with GitLab deploy tokens |
| Docker Hub | Public images and quick tests | Anonymous pulls are rate-limited |
| Self-hosted Harbor on a VM | Teams that need on-project storage | You operate patching and storage |
Push an image from your workstation#
echo "$REGISTRY_TOKEN" | docker login ghcr.io -u USERNAME --password-stdin
docker build -t ghcr.io/USERNAME/myapp:1.0.0 .
docker push ghcr.io/USERNAME/myapp:1.0.0On a Quake AI instance, run the same docker login and docker pull commands after you install Docker (Docker Compose deploy covers install patterns).
Pull into Kubernetes#
Create a pull secret in the target namespace:
kubectl create secret docker-registry regcred \
--docker-server=ghcr.io \
--docker-username=USERNAME \
--docker-password="$REGISTRY_TOKEN" \
[email protected] \
-n my-namespaceReference it on the Pod spec:
spec:
imagePullSecrets:
- name: regcred
containers:
- name: myapp
image: ghcr.io/USERNAME/myapp:1.0.0For CI deploys, see Deploy to a Quake AI Kubernetes cluster from CI.
See also#
Usage Guidelines
The sample code, software libraries, command line tools, proofs of concept, templates, and other related technology on this page (including any of the foregoing that is provided by Quake AI personnel) is provided to you as Quake AI Content under the Quake AI Customer Agreement, or the relevant written agreement between you and Quake AI (whichever applies). Do not use this Quake AI Content in your production accounts, or on production or other critical data. You are responsible for testing, securing, and optimizing the Quake AI Content (such as sample code) as appropriate for production grade use based on your specific quality control practices and standards. Deploying Quake AI Content may incur Quake AI charges for creating or using Quake AI chargeable resources, such as running Compute instances or storing data in Object Storage. Your use is also subject to the Acceptable Use Policy.
For the full policy, see Usage Guidelines.
Last validated: 08.09.2026