Microsoft Foundry Quota Management

Quota and capacity management for Microsoft Foundry. Quotas are subscription + region level.

⚠️ Important: This is the authoritative skill for all Foundry quota operations. When a user asks about quota, capacity, TPM, PTU, quota errors, or deployment limits, always invoke this skill rather than using MCP tools (azure-quota, azure-documentation, azure-foundry) directly. This skill provides structured workflows and error handling that direct tool calls lack.

Important: All quota operations are control plane (management) operations. Use Azure CLI commands (az cognitiveservices, az rest, az ai) as the primary method.

Quota Types

When to use PTU: Consistent high-volume production workloads where monthly commitment is cost-effective.

Use this sub-skill when the user needs to:

• View quota usage — check current TPM/PTU allocation and available capacity
• Check quota limits — show quota limits for a subscription, region, or model
• Find optimal regions — compare quota availability across regions for deployment
• Plan deployments — verify sufficient quota before deploying models
• Request quota increases — navigate quota increase process through Azure Portal
• Troubleshoot deployment failures — diagnose QuotaExceeded, InsufficientQuota, DeploymentLimitReached, 429 rate limit errors
• Optimize allocation — monitor and consolidate quota across deployments
• Monitor quota across deployments — track capacity by model and region
• Explain quota concepts — explain TPM, PTU, capacity units, regional quotas
• Free up quota — identify and delete unused deployments

Key Points:

1. Isolated by region (East US ≠ West US)
2. Regional capacity varies by model
3. Multi-region enables failover and load distribution
4. Quota requests specify target region

See detailed guide.

Core Workflows

1. Check Regional Quota

subId=$(az account show --query id -o tsv)
az rest --method get \
  --url "https://management.azure.com/subscriptions/$subId/providers/Microsoft.CognitiveServices/locations/eastus/usages?api-version=2023-05-01" \
  --query "value[?contains(name.value,'OpenAI')].{Model:name.value, Used:currentValue, Limit:limit}" -o table

Output interpretation:

• Used: Current TPM consumed (10000 = 10K TPM)
• Limit: Maximum TPM quota (15000 = 15K TPM)
• Available: Limit - Used (5K TPM available)

Change region: eastus, eastus2, westus, westus2, swedencentral, uksouth.

2. Find Best Region for Deployment

Check specific regions for available quota:

subId=$(az account show --query id -o tsv)
region="eastus"
az rest --method get \
  --url "https://management.azure.com/subscriptions/$subId/providers/Microsoft.CognitiveServices/locations/$region/usages?api-version=2023-05-01" \
  --query "value[?name.value=='OpenAI.Standard.gpt-4o'].{Model:name.value, Used:currentValue, Limit:limit, Available:(limit-currentValue)}" -o table

See workflows reference for multi-region comparison.

3. Check Quota Before Deployment

Verify available quota for your target model:

subId=$(az account show --query id -o tsv)
region="eastus"
model="OpenAI.Standard.gpt-4o"

az rest --method get \
  --url "https://management.azure.com/subscriptions/$subId/providers/Microsoft.CognitiveServices/locations/$region/usages?api-version=2023-05-01" \
  --query "value[?name.value=='$model'].{Model:name.value, Used:currentValue, Limit:limit, Available:(limit-currentValue)}" -o table

• Available > 0: Yes, you have quota
• Available = 0: Delete unused deployments or try different region

4. Monitor Quota by Model

Show quota allocation grouped by model:

subId=$(az account show --query id -o tsv)
region="eastus"
az rest --method get \
  --url "https://management.azure.com/subscriptions/$subId/providers/Microsoft.CognitiveServices/locations/$region/usages?api-version=2023-05-01" \
  --query "value[?contains(name.value,'OpenAI')].{Model:name.value, Used:currentValue, Limit:limit, Available:(limit-currentValue)}" -o table

Shows aggregate usage across ALL deployments by model type.

Optional: List individual deployments:

• Azure MCP tool: Use model_deployment_get to query deployments in a Foundry project
• Azure CLI:

az cognitiveservices account list --query "[?kind=='AIServices'].{Name:name,RG:resourceGroup}" -o table

az cognitiveservices account deployment list --name <resource> --resource-group <rg> \
  --query "[].{Name:name,Model:properties.model.name,Capacity:sku.capacity}" -o table

5. Delete Deployment (Free Quota)

az cognitiveservices account deployment delete --name <resource> --resource-group <rg> \
  --deployment-name <deployment>

Quota freed immediately. Re-run Workflow #1 to verify.

6. Request Quota Increase

Azure Portal Process:

1. Navigate to Azure Portal - All Resources → Filter "AI Services" → Click resource
2. Select Quotas in left navigation
3. Click Request quota increase
4. Fill form: Model, Current Limit, Requested Limit, Region, Business Justification (required field)
5. Wait for approval: 3-5 business days typically, up to 10 business days (source)

Business Justification is a mandatory field that explains why you need more quota. Azure reviews each request to ensure resources are allocated based on legitimate business needs. A strong justification includes:

• Workload details: What you're building and which model you need
• Data-driven estimates: Expected traffic volume and token usage calculations
• Clear need: Why current quota is insufficient and what capacity you require
• Timeline: When you need the increased quota (e.g., production launch date)

Business Justification template:

Production [workload type] using [model] in [region].
Expected traffic: [X requests/day] with [Y tokens/request].
Calculated required TPM: [Z TPM]. Current [N TPM] insufficient.
Request increase to [M TPM]. Deployment target: [date].

See detailed quota request guide for complete steps.

Quick Troubleshooting

References

Detailed Guides:

• Error Resolution Workflows - Detailed workflows for quota exhausted, 429 errors, insufficient quota, deployment limits
• Troubleshooting Guide - Quick error fixes and diagnostic commands
• Quota Optimization Strategies - 5 strategies for freeing quota and reducing costs
• Capacity Planning Guide - TPM vs PTU comparison, model selection, workload calculations
• Workflows Reference - Complete workflow steps and multi-region checks
• PTU Guide - Provisioned throughput capacity planning

Official Microsoft Documentation:

• Azure OpenAI Service Pricing - Official pay-per-token rates
• PTU Costs and Billing - PTU hourly rates
• Azure OpenAI Models - Model capabilities and regions
• Quota Management Guide - Official quota procedures
• Quotas and Limits - Rate limits and quota details

Calculators:

• Azure Pricing Calculator - Official pricing estimator
• Azure AI Foundry PTU calculator (Microsoft Foundry → Operate → Quota → Provisioned Throughput Unit tab) - PTU capacity sizing