Skip to content
cccskills
Official · MicrosoftFreePublished on GitHub

azure-mgmt-weightsandbiases-dotnet

Azure Weights & Biases SDK for .NET. ML experiment tracking and model management via Azure Marketplace. Use for creating W&B instances, managing SSO, marketplace integration, and ML observability. Triggers: "Weights and Biases", "W&B", "WeightsAndBiases", "ML experiment tracking", "model registry", "experiment management", "wandb".

The English summary is being prepared. Showing the original description.

Works withAzure
See how to install

Files included (1)

  • SKILL.md11.1 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Azure.ResourceManager.WeightsAndBiases (.NET)

Azure Resource Manager SDK for deploying and managing Weights & Biases ML experiment tracking instances via Azure Marketplace.

Installation

dotnet add package Azure.ResourceManager.WeightsAndBiases --prerelease
dotnet add package Azure.Identity

Current Version: v1.0.0-beta.1 (preview)
API Version: 2024-09-18-preview

Environment Variables

AZURE_SUBSCRIPTION_ID=<your-subscription-id> # Required: Azure subscription ID
AZURE_RESOURCE_GROUP=<your-resource-group> # Required: Azure resource group name
AZURE_WANDB_INSTANCE_NAME=<your-wandb-instance> # Required: Weights & Biases instance name
AZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production

Authentication

using Azure.Identity;
using Azure.ResourceManager;
using Azure.ResourceManager.WeightsAndBiases;

// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
var credential = new DefaultAzureCredential(
    DefaultAzureCredential.DefaultEnvironmentVariableName
);
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/dotnet/api/overview/azure/identity-readme?view=azure-dotnet#credential-classes
// var credential = new ManagedIdentityCredential();
ArmClient client = new ArmClient(credential);

Resource Hierarchy

Subscription
└── ResourceGroup
    └── WeightsAndBiasesInstance    # W&B deployment from Azure Marketplace
        ├── Properties
        │   ├── Marketplace          # Offer details, plan, publisher
        │   ├── User                 # Admin user info
        │   ├── PartnerProperties    # W&B-specific config (region, subdomain)
        │   └── SingleSignOnPropertiesV2  # Entra ID SSO configuration
        └── Identity                 # Managed identity (optional)

Core Workflows

1. Create Weights & Biases Instance

using Azure.ResourceManager.WeightsAndBiases;
using Azure.ResourceManager.WeightsAndBiases.Models;

ResourceGroupResource resourceGroup = await client
    .GetDefaultSubscriptionAsync()
    .Result
    .GetResourceGroupAsync("my-resource-group");

WeightsAndBiasesInstanceCollection instances = resourceGroup.GetWeightsAndBiasesInstances();

WeightsAndBiasesInstanceData data = new WeightsAndBiasesInstanceData(AzureLocation.EastUS)
{
    Properties = new WeightsAndBiasesInstanceProperties
    {
        // Marketplace configuration
        Marketplace = new WeightsAndBiasesMarketplaceDetails
        {
            SubscriptionId = "<marketplace-subscription-id>",
            OfferDetails = new WeightsAndBiasesOfferDetails
            {
                PublisherId = "wandb",
                OfferId = "wandb-pay-as-you-go",
                PlanId = "wandb-payg",
                PlanName = "Pay As You Go",
                TermId = "monthly",
                TermUnit = "P1M"
            }
        },
        // Admin user
        User = new WeightsAndBiasesUserDetails
        {
            FirstName = "Admin",
            LastName = "User",
            EmailAddress = "admin@example.com",
            Upn = "admin@example.com"
        },
        // W&B-specific configuration
        PartnerProperties = new WeightsAndBiasesPartnerProperties
        {
            Region = WeightsAndBiasesRegion.EastUS,
            Subdomain = "my-company-wandb"
        }
    },
    // Optional: Enable managed identity
    Identity = new ManagedServiceIdentity(ManagedServiceIdentityType.SystemAssigned)
};

ArmOperation<WeightsAndBiasesInstanceResource> operation = await instances
    .CreateOrUpdateAsync(WaitUntil.Completed, "my-wandb-instance", data);

WeightsAndBiasesInstanceResource instance = operation.Value;

Console.WriteLine($"W&B Instance created: {instance.Data.Name}");
Console.WriteLine($"Provisioning state: {instance.Data.Properties.ProvisioningState}");

2. Get Existing Instance

WeightsAndBiasesInstanceResource instance = await resourceGroup
    .GetWeightsAndBiasesInstanceAsync("my-wandb-instance");

Console.WriteLine($"Instance: {instance.Data.Name}");
Console.WriteLine($"Location: {instance.Data.Location}");
Console.WriteLine($"State: {instance.Data.Properties.ProvisioningState}");

if (instance.Data.Properties.PartnerProperties != null)
{
    Console.WriteLine($"Region: {instance.Data.Properties.PartnerProperties.Region}");
    Console.WriteLine($"Subdomain: {instance.Data.Properties.PartnerProperties.Subdomain}");
}

3. List All Instances

// List in resource group
await foreach (WeightsAndBiasesInstanceResource instance in 
    resourceGroup.GetWeightsAndBiasesInstances())
{
    Console.WriteLine($"Instance: {instance.Data.Name}");
    Console.WriteLine($"  Location: {instance.Data.Location}");
    Console.WriteLine($"  State: {instance.Data.Properties.ProvisioningState}");
}

// List in subscription
SubscriptionResource subscription = await client.GetDefaultSubscriptionAsync();
await foreach (WeightsAndBiasesInstanceResource instance in 
    subscription.GetWeightsAndBiasesInstancesAsync())
{
    Console.WriteLine($"{instance.Data.Name} in {instance.Id.ResourceGroupName}");
}

4. Configure Single Sign-On (SSO)

WeightsAndBiasesInstanceResource instance = await resourceGroup
    .GetWeightsAndBiasesInstanceAsync("my-wandb-instance");

// Update with SSO configuration
WeightsAndBiasesInstanceData updateData = instance.Data;

updateData.Properties.SingleSignOnPropertiesV2 = new WeightsAndBiasSingleSignOnPropertiesV2
{
    Type = WeightsAndBiasSingleSignOnType.Saml,
    State = WeightsAndBiasSingleSignOnState.Enable,
    EnterpriseAppId = "<entra-app-id>",
    AadDomains = { "example.com", "contoso.com" }
};

ArmOperation<WeightsAndBiasesInstanceResource> operation = await resourceGroup
    .GetWeightsAndBiasesInstances()
    .CreateOrUpdateAsync(WaitUntil.Completed, "my-wandb-instance", updateData);

5. Update Instance

WeightsAndBiasesInstanceResource instance = await resourceGroup
    .GetWeightsAndBiasesInstanceAsync("my-wandb-instance");

// Update tags
WeightsAndBiasesInstancePatch patch = new WeightsAndBiasesInstancePatch
{
    Tags =
    {
        { "environment", "production" },
        { "team", "ml-platform" },
        { "costCenter", "CC-ML-001" }
    }
};

instance = await instance.UpdateAsync(patch);
Console.WriteLine($"Updated instance: {instance.Data.Name}");

6. Delete Instance

WeightsAndBiasesInstanceResource instance = await resourceGroup
    .GetWeightsAndBiasesInstanceAsync("my-wandb-instance");

await instance.DeleteAsync(WaitUntil.Completed);
Console.WriteLine("Instance deleted");

7. Check Resource Name Availability

// Check if name is available before creating
// (Implement via direct ARM call if SDK doesn't expose this)
try
{
    await resourceGroup.GetWeightsAndBiasesInstanceAsync("desired-name");
    Console.WriteLine("Name is already taken");
}
catch (RequestFailedException ex) when (ex.Status == 404)
{
    Console.WriteLine("Name is available");
}

Key Types Reference

TypePurpose
WeightsAndBiasesInstanceResourceW&B instance resource
WeightsAndBiasesInstanceDataInstance configuration data
WeightsAndBiasesInstanceCollectionCollection of instances
WeightsAndBiasesInstancePropertiesInstance properties
WeightsAndBiasesMarketplaceDetailsMarketplace subscription info
WeightsAndBiasesOfferDetailsMarketplace offer details
WeightsAndBiasesUserDetailsAdmin user information
WeightsAndBiasesPartnerPropertiesW&B-specific configuration
WeightsAndBiasSingleSignOnPropertiesV2SSO configuration
WeightsAndBiasesInstancePatchPatch for updates
WeightsAndBiasesRegionSupported regions enum

Available Regions

Region EnumAzure Region
WeightsAndBiasesRegion.EastUSEast US
WeightsAndBiasesRegion.CentralUSCentral US
WeightsAndBiasesRegion.WestUSWest US
WeightsAndBiasesRegion.WestEuropeWest Europe
WeightsAndBiasesRegion.JapanEastJapan East
WeightsAndBiasesRegion.KoreaCentralKorea Central

Marketplace Offer Details

For Azure Marketplace integration:

PropertyValue
Publisher IDwandb
Offer IDwandb-pay-as-you-go
Plan IDwandb-payg (Pay As You Go)

Best Practices

  1. Use DefaultAzureCredential — Supports multiple auth methods automatically
  2. Enable managed identity — For secure access to other Azure resources
  3. Configure SSO — Enable Entra ID SSO for enterprise security
  4. Tag resources — Use tags for cost tracking and organization
  5. Check provisioning state — Wait for Succeeded before using instance
  6. Use appropriate region — Choose region closest to your compute
  7. Monitor with Azure — Use Azure Monitor for resource health

Error Handling

using Azure;

try
{
    ArmOperation<WeightsAndBiasesInstanceResource> operation = await instances
        .CreateOrUpdateAsync(WaitUntil.Completed, "my-wandb", data);
}
catch (RequestFailedException ex) when (ex.Status == 409)
{
    Console.WriteLine("Instance already exists or name conflict");
}
catch (RequestFailedException ex) when (ex.Status == 400)
{
    Console.WriteLine($"Invalid configuration: {ex.Message}");
}
catch (RequestFailedException ex)
{
    Console.WriteLine($"Azure error: {ex.Status} - {ex.Message}");
}

Integration with W&B SDK

After creating the Azure resource, use the W&B Python SDK for experiment tracking:

# Install: pip install wandb
import wandb

# Login with your W&B API key from the Azure-deployed instance
wandb.login(host="https://my-company-wandb.wandb.ai")

# Initialize a run
run = wandb.init(project="my-ml-project")

# Log metrics
wandb.log({"accuracy": 0.95, "loss": 0.05})

# Finish run
run.finish()

Related SDKs

SDKPurposeInstall
Azure.ResourceManager.WeightsAndBiasesW&B instance management (this SDK)dotnet add package Azure.ResourceManager.WeightsAndBiases --prerelease
Azure.ResourceManager.MachineLearningAzure ML workspacesdotnet add package Azure.ResourceManager.MachineLearning

Reference Links

ResourceURL
NuGet Packagehttps://www.nuget.org/packages/Azure.ResourceManager.WeightsAndBiases
W&B Documentationhttps://docs.wandb.ai/
Azure Marketplacehttps://azuremarketplace.microsoft.com/marketplace/apps/wandb.wandb-pay-as-you-go
GitHub Sourcehttps://github.com/Azure/azure-sdk-for-net/tree/main/sdk/weightsandbiases

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

agent-framework-azure-ai-py

Official · MicrosoftFree

Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.

The English summary is being prepared. Showing the original description.

microsoft/skills3.1KUpdated Oct 22, 2026

airunway-aks-setup

Official · MicrosoftFree

Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".

The English summary is being prepared. Showing the original description.

microsoft/skills3.1KUpdated Oct 22, 2026

aks-gpu-inference

Official · MicrosoftFree

Diagnose Day-2 AKS GPU and KAITO incidents using profile-aware, read-only evidence. WHEN: 'Insufficient nvidia.com/gpu', GPU pod Pending, model-load OOM, DCGM/VRAM, KAITO Workspace not ready, or GPU autoscaling. DO NOT USE FOR: setup (airunway-aks-setup), non-GPU incidents (aks-troubleshooting), standalone VM quota (azure-quotas), or generic cost (cost-analysis or cost-optimization from the optional azure-cost plugin).

The English summary is being prepared. Showing the original description.

microsoft/skills3.1KUpdated Oct 22, 2026

aks-known-issues

Official · MicrosoftFree

Lookup documented AKS fixes only when the prompt includes an exact catalog signature and all of its qualifiers: VMCannotFitEphemeralOSDisk; NodePoolMcVersionIncompatible; 'NodeImageVersion is not accepted'; AKS SkuNotAvailable with size, location, and zone; ZonalAllocationFailed with insufficient zone capacity; OverconstrainedAllocationRequest with listed constraints; nested AKS vmssCSE/CSE VMExtensionError_OutboundConnFail, VMExtensionError_K8SAPIServerConnFail, or VMExtensionError_K8SAPIServerDNSLookupFail; or AllocationFailed with the full cataloged internal-error or insufficient-regional-capacity message. Never use for quota errors, code-only or bare wrappers, generic symptoms, incomplete signatures, or failures outside AKS; use aks-troubleshooting or azure-diagnostics.

The English summary is being prepared. Showing the original description.

microsoft/skills3.1KUpdated Oct 22, 2026

aks-network-capture

Official · MicrosoftFree

Collects bounded packet captures from AKS nodes and Azure network configuration for wire-level evidence. WHEN: "capture packets on an AKS node", "take a pcap", "run tcpdump on AKS", "prove where packets drop". Use for explicit packet-capture intent after read-only diagnostics, not general AKS connectivity or ingress troubleshooting.

The English summary is being prepared. Showing the original description.

microsoft/skills3.1KUpdated Oct 22, 2026

aks-troubleshooting

Official · MicrosoftFree

Debug live Azure Kubernetes Service (AKS) incidents with a read-only, evidence-first investigation. WHEN: pod crashes or Pending, CrashLoopBackOff, OOMKilled, ImagePullBackOff, node NotReady, DNS or ingress failure, connectivity timeout, network policy, SNAT exhaustion, node-pool scaling blocked by QuotaExceeded or InsufficientVCPUQuota, upgrade stuck, spot or zone disruption, a bare VMExtensionProvisioningError or AllocationFailed wrapper, an uncataloged capacity symptom, or 'investigate my AKS cluster'. DO NOT USE FOR: packet capture (use aks-network-capture); GPU or model-serving issues (use aks-gpu-inference); cluster creation or provisioning (use azure-kubernetes); cost (use cost-analysis from the optional azure-cost plugin); pod rightsizing (use azure-kubernetes); a fully qualified documented AKS signature with every required nested qualifier (use aks-known-issues); standalone failures on non-AKS Azure resources (use azure-diagnostics). Unqualified errors and open-ended incidents stay here only for AKS.

The English summary is being prepared. Showing the original description.

microsoft/skills3.1KUpdated Oct 22, 2026

See all skills by microsoft

Report a problem with this skill