[BUG][Resource Graph] Resource Graph API returns inconsistent casing for the resource group name in the 'id' field when query the resources with type Microsoft.CognitiveServices/accounts #31379
Labels
bug
This issue requires a change to an existing behavior in the product in order to be resolved.
customer-reported
Issues that are reported by GitHub users external to the Azure organization.
Mgmt
This issue is related to a management-plane library.
Resource Graph
Service Attention
Workflow: This issue is responsible by Azure service team.
API Spec link
https://github.com/Azure/azure-rest-api-specs/blob/main/specification/resourcegraph/resource-manager/Microsoft.ResourceGraph/stable/2024-04-01/resourcegraph.json#L37
API Spec version
2024-04-01
Describe the bug
The casing of the 'id' field is being inconsistently returned when query the resources with type Microsoft.CognitiveServices/accounts with Resource Graph API, when it contains upper case letters.
For example, using a resource group named 'BA-Test', firstly the 'id' field is returned with this in mixed case (/resourceGroups/BA-Test/) and after deploy a model in the AI Service, it would become lower case (/resourceGroups/ba-test/).
Expected behavior
Response to have consistent casing for the resource group in the 'id' field, every time, preferably the mixed casing to match the console.
Actual behavior
Resource group name in the 'id' field in the response would turn into lower case once deploy a model in the AI Service and turn back to mixed case once the deployed model removed.
Reproduction Steps
API: https://learn.microsoft.com/en-us/rest/api/azureresourcegraph/resourcegraph/resources/resources?view=rest-azureresourcegraph-resourcegraph-2024-04-01
Request body:
"query": "Resources | project id, name, type, resourceGroup | where type =~ 'Microsoft.CognitiveServices/accounts'"
Steps:
Create an Azure AI Services resource in the console using a mixed case resource group (for example BA-Test)
Call the api and the print out for the relevant resource will (most likely) be:
Navigate to AI Studio from this resource and deploy a model (i used gpt-4). Then call the api with same body and response is likely to be:
Environment
No response
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