Get Resource
azure_machinelearning.get_resource
ActionMicrosoft Azureconnection required
Calls Azure Resource Manager GET /subscriptions/{id}/resourceGroups/{rg}/providers/{namespace}/{type}/{name}.
Read one Microsoft.MachineLearning resource by name.
Connection
- Required
- Yes — the node will not save without one
- Auth type
- API key
- Providers
- Azure Machine Learning
- Secret shape
- {"tenant_id", "client_id", "client_secret"}
- Config it needs
- subscription_id, resource_group
- Resolved by
- config.connection_id, else node.connection_id
Configuration
4 fields, 1 required. A dotted path is a nested object and name[] an array of objects — the editor renders the same tree.
| Field | Type | Required | Default | Constraints | Example |
|---|---|---|---|---|---|
subscription_id Azure subscription id (overrides the connection). | string | No | — | — | — |
resource_type Which Microsoft.MachineLearning resource type to address. | string | No | workspaces | one of "webServices", "workspaces" | — |
resource_group Resource group holding the resource. Leave empty for a subscription-scoped resource (a role assignment, a Defender pricing, a cost budget — these live under no group). | string | No | — | — | — |
name Resource name. | string | Yes | — | — | — |
Example configuration
Every value below is the contract’s own example or default — nothing invented.
{
"resource_type": "workspaces"
}Output
One shape.
result
| Field | Type | Example |
|---|---|---|
id | string | — |
name | string | — |
type | string | — |
location | string | — |
properties | object | — |
{
"id": "",
"location": "",
"name": "",
"properties": {},
"type": ""
}Related Azure Machine Learning nodes
See Get Resource run in a workflow.
In a technical demo we add the Azure Machine Learning connection, drop the node on the canvas and let Workflow Health pre-flight it before the first real run.