microsoft-foundry / microsoft-foundry/foundry-samples
Deployment Failure When Creating AI Services Account with Private Networking
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- Dominant language
- Bicep
- Stars
- 445
- Forks
- 494
- Avg merge
- 11h 35m
- Merged PRs (30d)
- 38
Description
- Description:
I'm encountering a deployment failure when deploying a Bicep template. I would greatly appreciate any guidance on how to resolve this issue.
the bicep template is below:
15-private-network-standard-agent-setup
- My Setup:
I manually created the following resources in advance:
VNet: 192.168.0.0/16
Agent Subnet: 192.168.1.0/24
Private Endpoint (PE) Subnet: 192.168.2.0/24
Azure AI Search: Created with PublicNetworkAccess = Disabled
Cosmos DB: Created with PublicNetworkAccess = Disabled
Storage Account: Created with PublicNetworkAccess = Disabled
Region: japaneast
I then provided these resource references in the azuredeploy.json parameters UI.
- Issue:
The deployment fails at the step of creating the AI Services Account (Microsoft.CognitiveServices/accounts). The error message is:
{
"code": "DeploymentFailed",
"target": "/subscriptions/733c0ac8-aaa8-4a85-b5d6-b788a74d82de/resourceGroups/rg-local-aif/providers/Microsoft.Resources/deployments/aiservicesy4z2-y4z2-deployment",
"message": "At least one resource deployment operation failed. Please list deployment operations for details. Please see https://aka.ms/arm-deployment-operations for usage details.",
"details": [
{
"code": "ResourceDeploymentFailure",
"target": "/subscriptions/733c0ac8-aaa8-4a85-b5d6-b788a74d82de/resourceGroups/rg-local-aif/providers/Microsoft.CognitiveServices/accounts/aiservicesy4z2",
"message": "The resource write operation failed to complete successfully, because it reached terminal provisioning state 'Failed'.",
"details": [
{
"code": "OperationError",
"message": "Failed to Create the resource. Provisioning state: Failed",
"details": [
{
"code": "ResourceProviderError",
"message": "Failed to create Aml RP virtual workspace due to System.Exception: Failed async operation {\n \"status\": \"Failed\",\n \"error\": {\n \"code\": \"InternalServerError\",\n \"message\": \"InternalServerError\"\n }\n}\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 117\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 223"
}
]
}
]
}
]
}
- What I’ve Tried:
Confirmed that all dependent resources (VNet, subnets, private resources) are successfully created.
- Request:
Could you please help identify:
Why this internal server error is occurring during the creation of the AI Services account?
Are there any known issues with private endpoint/Azure ML RP workspace creation in japaneast?
Any workarounds or required configurations I might have missed?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the linked 15-private-network-standard-agent-setup sample and reproduce the Bicep deployment in japaneast using the stated VNet, subnets, and private resources. Inspect the Microsoft.CognitiveServices/accounts deployment operations and Azure ML RP error; done means identifying a confirmed cause or documented workaround for the failed AI Services account creation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- azure
- Domain
- cloud, infrastructure
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100