Using Connections
Connections let you store reusable access settings for external model sources and data services at the project level.
For direct YAML examples of model deployment from S3, PVC, or OCI sources, see Model Storage.
Note: For OCI-based model deployment, only connections whose
ACCESS_TYPEincludesPullare available in the model deployment form.
TOC
PrerequisitesCreating a ConnectionBuilt-in Field SetsVerificationUpdating a ConnectionDeleting a ConnectionManaging Connection TypesWhat a Connection Type ContainsBuilt-in TemplatesSupported Field TypesCreating a Connection TypeDuplicating, Editing, Enabling, and DeletingUsing Connections for Model DeploymentRuntime BehaviorResource ModelConnection Secret ExampleConnection Type ConfigMap ExamplePrerequisites
- You have access to the target project namespace.
- A suitable connection type already exists.
- You have the credentials and endpoint information for the external storage or registry that you want to use.
Creating a Connection
- In the business view, open the target project.
- Click Connections.
- Click Create connection.
- Select a connection type.
- Enter the Kubernetes resource name for the connection.
- Optional: Enter a display name.
- Complete the fields defined by the selected connection type.
- Click Create.
Built-in Field Sets
- URI: Provide the full URI in the
URIfield. - OCI-compliant registry: Provide
ACCESS_TYPE, upload or paste.dockerconfigjson, and enterOCI_HOST. - S3-compatible object storage: Provide
AWS_ACCESS_KEY_ID,AWS_SECRET_ACCESS_KEY,AWS_S3_ENDPOINT, and optionallyAWS_DEFAULT_REGIONandAWS_S3_BUCKET.
Verification
- The new item appears on the Connections page.
- The table shows the connection name, connection type, compatibility tags, and creator.
Note: The connection resource name and selected connection type cannot be changed after creation.
Updating a Connection
- On the Connections page, open the action menu for the target connection.
- Click Edit.
- Update the display name or connection fields.
- Click Save.
After you update credentials or endpoints, redeploy or restart dependent workloads so they pick up the latest values.
Deleting a Connection
- On the Connections page, open the action menu for the target connection.
- Click Delete.
- Confirm the operation.
Deleting a connection removes the project secret only. Any workload that still depends on that secret must be updated separately.
Managing Connection Types
Connection types are managed at cluster scope and stored in the kube-public namespace.
What a Connection Type Contains
- Basic metadata: name, display name, categories, and enabled state
- Ordered section headings and fields
- Optional default values and read-only settings
- Compatibility markers for URI, OCI, or S3 model serving
Built-in Templates
The connection type editor can append predefined field sets for:
- URI
- OCI compliant registry
- S3 compatible object storage
Supported Field Types
Note: File-type fields in the current UI accept pasted content or uploaded files up to 1 MiB.
Creating a Connection Type
- Open the target cluster and go to Settings > Connection types.
- Click Create connection type.
- Enter the connection type name. The platform stores it with the
ct-prefix. - Optional: Enter a display name.
- Select one or more categories.
- Set Enabled as needed.
- Add section headings and fields, or apply a built-in model-serving-compatible template.
- Click Create.
Duplicating, Editing, Enabling, and Deleting
- Use Duplicate when you want to base a new connection type on an existing type.
- Custom connection types can be edited or deleted.
- Preinstalled connection types can be duplicated, but the current UI does not allow editing or deleting them directly.
- The list page provides an Enabled switch to mark a connection type as active or inactive.
Note: Editing a connection type does not rewrite existing connection secrets that were created earlier.
Using Connections for Model Deployment
When you create or update an inference service, you can set Model location to Connection.
- Open the inference service creation or update form.
- Set Model location to Connection.
- Select the connection.
- Complete the model path field according to the connection kind:
- URI: No extra path is required; the platform reads the full URI from the connection.
- OCI: Enter the relative path under
oci://<OCI_HOST>/, for examplemy-model:latest. - S3: Enter the object path under
s3://<AWS_S3_BUCKET>/, for examplellm/qwen2.5.
Runtime Behavior
- For OCI connections, the connection secret is attached to the workload as an
imagePullSecret. - For S3 connections, the platform creates a dedicated
ServiceAccountthat references the connection secret. - The inference service metadata stores the selected connection name in the
aml-model-source-connectionannotation.
Resource Model
The current implementation uses project secrets for connections and cluster-level ConfigMaps for connection types.
Connection Secret Example
Connection Type ConfigMap Example
Note: Compared with recent OpenShift AI documentation, the current Alauda AI frontend still binds a connection to its template with
cpaas.io/connection-type-ref, and also writes model-serving compatibility tocpaas.io/connection-type-protocol.