Azure.ResourceManager.ArizeAIObservabilityEval
Manage Arize AI Resources on Azure with .NET
Deploy and manage Arize AI ML observability organizations on Azure through the Azure Resource Manager SDK. Simplifies Azure Marketplace subscription workflows for machine learning teams.
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Test it
Using "Azure.ResourceManager.ArizeAIObservabilityEval". Create Arize AI organization in East US
Expected outcome:
Successfully created Arize AI organization 'my-arize-org' in resource group 'ml-prod'. Provisioning state: Succeeded. Resource ID contains subscription, resource group, and organization name.
Using "Azure.ResourceManager.ArizeAIObservabilityEval". Check if organization exists
Expected outcome:
Organization 'my-arize-org' exists. Properties: Location=EastUS, ProvisioningState=Succeeded, MarketplaceStatus=Subscribed, Tags={environment: production}
Security Audit
SafeDocumentation-only skill providing usage examples for Azure Resource Manager SDK. Static analysis scanned 0 files with 0 suspicious patterns detected. No executable code present - only markdown documentation with standard Azure authentication patterns using DefaultAzureCredential.
Quality Score
What You Can Build
ML Platform Team Provisioning
Automate Arize AI organization creation for new machine learning teams joining your Azure environment
Resource Governance and Cleanup
Audit and manage Arize AI resources across subscriptions with programmatic control
Marketplace Subscription Management
Streamline Arize AI marketplace subscription workflows for enterprise deployments
Try These Prompts
Help me create a new Arize AI organization in Azure resource group 'ml-prod' located in East US with my marketplace subscription ID
Show me all Arize AI organizations in my Azure subscription and their current provisioning state
Update the tags on my Arize organization 'my-arize-org' to add environment=production and team=data-science
Guide me through safely deleting an Arize AI organization after verifying it is no longer in use
Best Practices
- Use DefaultAzureCredential for authentication to support multiple credential sources
- Always use async methods with proper await patterns in .NET
- Handle RequestFailedException with specific status codes for error scenarios
Avoid
- Avoid hardcoded credentials - always use environment variables or managed identity
- Do not ignore long-running operation results - wait for completion or poll status
- Never skip error handling for 404 Not Found when checking resource existence