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CLI (v2) Attached Azure Arc-enabled Kubernetes cluster (KubernetesCompute) YAML schema

APPLIES TO: Azure CLI ml extension v2 (current)

The source JSON schema can be found at https://azuremlschemas.azureedge.net/latest/kubernetesCompute.schema.json.

Note

The YAML syntax detailed in this document is based on the JSON schema for the latest version of the ML CLI v2 extension. This syntax is guaranteed only to work with the latest version of the ML CLI v2 extension. You can find the schemas for older extension versions at https://azuremlschemasprod.azureedge.net/.

YAML syntax

Key Type Description Allowed values Default value
$schema string The YAML schema. If you use the Azure Machine Learning VS Code extension to author the YAML file, including $schema at the top of your file enables you to invoke schema and resource completions.
type string Required. The type of compute. kubernetes
name string Required. Name of the compute.
description string Description of the compute.
resource_id string Fully qualified resource ID of the Azure Arc-enabled Kubernetes cluster to attach to the workspace as a compute target.
namespace string The Kubernetes namespace to use for the compute target. The namespace must be created in the Kubernetes cluster before the cluster can be attached to the workspace as a compute target. All Azure Machine Learning workloads running on this compute target will run under the namespace specified in this field.
identity object The managed identity configuration to assign to the compute. KubernetesCompute clusters support only one system-assigned identity or multiple user-assigned identities, not both concurrently.
identity.type string The type of managed identity to assign to the compute. If the type is user_assigned, the identity.user_assigned_identities property must also be specified. system_assigned, user_assigned
identity.user_assigned_identities array List of fully qualified resource IDs of the user-assigned identities.

Remarks

The az ml compute commands can be used for managing Azure Arc-enabled Kubernetes clusters (KubernetesCompute) attached to an Azure Machine Learning workspace.

Next steps