Microsoft Azure · OpenAPI Overlay 1.0.0

API Evangelist conversational phrasing for Microsoft Azure Outbound Network Dependencies Endpoints API

3 actions 3 updates phrasing extends openapi/microsoft-azure-outboundnetworkdependenciesendpoints-api-openapi.yml

Generated by API Evangelist Written by API Evangelist tooling for Microsoft Azure's API. It is a proposal applied on top of the contract, not a document Microsoft Azure publishes.

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What the actions change

x-apievangelist-phrasing

Targets 3

$.info

$.paths['/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/outboundNetworkDependenciesEndpoints'].get

$.paths['/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Databricks/workspaces/{workspaceName}/outboundNetworkDependenciesEndpoints'].get

OpenAPI Overlay

Raw ↑

# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
  title: API Evangelist conversational phrasing for Microsoft Azure Outbound Network Dependencies Endpoints API
  version: 1.0.0
extends: openapi/microsoft-azure-outboundnetworkdependenciesendpoints-api-openapi.yml
actions:
- target: $.info
  update:
    x-apievangelist-phrasing:
      method: generated
      generated: '2026-09-26'
      generator: build-phrasing.py
      label: Generated by API Evangelist
      operations: 2
- target: $.paths['/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/outboundNetworkDependenciesEndpoints'].get
  update:
    x-apievangelist-phrasing:
      intent: List outbound FQDN dependencies of an ML workspace
      effect: read
      questions:
      - Which external FQDNs does my Azure Machine Learning workspace need outbound access to?
      - What should I allow in my firewall for a Machine Learning workspace to work?
      instructions:
      - text: List outbound FQDN dependencies for Machine Learning workspace {workspaceName}.
        slots:
          workspaceName: path.workspaceName
      - text: Show the external hosts ML workspace {workspaceName} must reach.
        slots:
          workspaceName: path.workspaceName
      method: generated
      generated: '2026-09-26'
- target: $.paths['/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Databricks/workspaces/{workspaceName}/outboundNetworkDependenciesEndpoints'].get
  update:
    x-apievangelist-phrasing:
      intent: List egress endpoints for a Databricks workspace
      effect: read
      questions:
      - Which control plane endpoints does a VNet-injected Azure Databricks workspace call?
      - What egress rules do I need for a Databricks workspace with user-defined routes?
      instructions:
      - text: List egress endpoints for Databricks workspace {workspaceName} in resource group {resourceGroupName}, subscription {subscriptionId}.
        slots:
          workspaceName: path.workspaceName
          resourceGroupName: path.resourceGroupName
          subscriptionId: path.subscriptionId
      - text: Show the outbound endpoints Databricks workspace {workspaceName} needs for its control plane.
        slots:
          workspaceName: path.workspaceName
      method: generated
      generated: '2026-09-26'

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