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Hi, I'm testing the deployment of AI Foundry with network injection in the West Europe region. I'm using a VNet with the address space 10.0.0.0/23 and an existing Azure Machine Learning workspace located in the same region.
However, I encountered the following error during deployment:
[{"code":"OperationError","message":"Failed to Update the resource. Provisioning state: Failed","details":
[{"code":"ResourceProviderError","message":"Failed to create Aml RP virtual workspace due to System.Exception: Failed async operation\n
at Microsoft.CognitiveServices.ResourceProvider.AmlRp.AsyncOperationHelper.PollUntilCompleteAsync[T](TraceContext traceContext,
HttpResponseMessage response, HttpClient httpClient, Int32 timeoutInMin, CancellationToken cancellationToken) in
/__w/1/s/src/Common/ResourceProvider/AmlRp/AsyncOperationHelper.cs:line 85\n at
Microsoft.CognitiveServices.ResourceProvider.AmlRp.AmlRpClient.PutAmlRpVirtualHubAsync(TraceContext traceContext, Dictionary"2 headers,
ResourceIdentityInArm resourceIdentity, String primaryUserAssignedIdentity, String internalId, KeyVaultProperties keyVaultProperties, String
subscriptionId, String resourceGroupName, String workspaceName, List"1 networkInjections, PublicNetworkAccessType
publicNetworkAccessType, CancellationToken cancellationToken) in /__w/1/s/src/Common/ResourceProvider/AmlRp/AmlRpClient.cs:line
119\n at Microsoft.CognitiveServices.ResourceProvider.AmlRp.AmlRpService.PutAmlRpWorkspaceAsync(TraceContext traceContext,
ResourceRequestContext requestContext, WorkerMessageRequestContext workerMessageRequestContext,
IResourceEntity insertedResourceEntity, CancellationToken cancellationToken) in
/__w/1/s/src/Common/ResourceProvider/AmlRp/AmlRpService.cs:line 124\n at
Microsoft.CognitiveServices.ResourceProvider.Worker.MessageProcessor.ProcessInternalAsync(TraceContext traceContext,
RpWorkerQueueMessage message, CancellationToken cancellationToken) in
/__w/1/s/src/ResourceProvider/Rp.WorkerRole/AccountProvisioning/MessageProcessor.cs:line 297"}]
Properties that I'm using for deployment:
allowProjectManagement: true
customSubDomainName: accountName
amlWorkspace: {
identityClientId: <app ID of service principal>
resourceId: '/subscriptions/<SubscriptionID>/resourceGroups/<RG>/providers/Microsoft.MachineLearningServices/workspaces/<Workspace>'
}
networkAcls: {
defaultAction: 'Allow'
virtualNetworkRules: []
ipRules: []
}
publicNetworkAccess: 'Disabled'
networkInjections:([
{
scenario: 'agent'
subnetArmId: agentSubnetId
useMicrosoftManagedNetwork: false
}
])
disableLocalAuth: false
My concerns are:
-
Why does the deployment still attempt to create a new AML workspace, even though I’ve explicitly specified an existing one?
-
Is it supported to use an address range like 10.0.0.0/23? I understand the deployment scripts are designed to work with 192.168.0.0/16, but that space can not be used in our case.
Thanks in advance for your help.
mkemmerz
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