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/microsoft-foundry

@04110d9
by microsoftmicrosoft/skills3.1k stars
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Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, create agent, update agent, add tool to agent, invoke agent, agent.yaml, agent insights, pull agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, prompt optimizer, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).

Use this Skill: https://skilld.dev/gh/microsoft/skills/microsoft-foundry

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quotareferencestroubleshooting.md

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Troubleshooting Quota Errors

Table of Contents: Common Quota Errors · Detailed Error Resolution · Request Quota Increase Process · Diagnostic Commands · External Resources

Common Quota Errors

Error Cause Quick Fix
QuotaExceeded Regional quota consumed (TPM or PTU) Delete unused deployments or request increase
InsufficientQuota Not enough available for requested capacity Reduce deployment capacity or free quota
DeploymentLimitReached Too many deployment slots used Delete unused deployments to free slots
429 Rate Limit TPM capacity too low for traffic (Standard only) Increase TPM capacity or migrate to PTU
PTU capacity unavailable No PTU quota in region Request PTU quota or try different region
SKU not supported PTU not available for model/region Check model availability or use Standard TPM

Detailed Error Resolution

QuotaExceeded Error

All available TPM or PTU quota consumed in the region.

Resolution:

  1. Check current quota usage:

    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}" -o table
  2. Choose resolution:

    • Option A: Delete unused deployments to free quota
    • Option B: Reduce requested deployment capacity
    • Option C: Deploy to different region with available quota
    • Option D: Request quota increase through Azure Portal

InsufficientQuota Error

Available quota less than requested capacity.

Resolution:

  1. Check available quota:

    # Calculate available: limit - currentValue
    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
  2. Options:

    • Reduce deployment capacity to fit available quota
    • Delete existing deployments to free capacity
    • Try different region with more available quota
    • Request quota increase

DeploymentLimitReached Error

Resource reached maximum deployment slot limit (10-20 slots).

Resolution:

  1. List existing deployments:

    az cognitiveservices account deployment list \
      --name <resource-name> \
      --resource-group <rg> \
      --query '[].{Name:name, Model:properties.model.name, Capacity:sku.capacity}' \
      --output table
  2. Delete unused deployments:

    az cognitiveservices account deployment delete \
      --name <resource-name> \
      --resource-group <rg> \
      --deployment-name <unused-deployment-name>
  3. Verify slot freed:

    az cognitiveservices account deployment list \
      --name <resource-name> \
      --resource-group <rg> \
      --query 'length([])'

429 Rate Limit Errors

TPM capacity insufficient for traffic volume (Standard TPM only).

Resolution:

  1. Check deployment capacity:

    az cognitiveservices account deployment show \
      --name <resource-name> \
      --resource-group <rg> \
      --deployment-name <deployment-name> \
      --query '{Name:name, Model:properties.model.name, Capacity:sku.capacity, SKU:sku.name}'
  2. Options:

    • Option A: Increase TPM capacity on existing deployment
      az cognitiveservices account deployment update \
        --name <resource-name> \
        --resource-group <rg> \
        --deployment-name <deployment-name> \
        --sku-capacity <higher-capacity>
    • Option B: Migrate to PTU for guaranteed throughput (no rate limits)
    • Option C: Implement retry logic with exponential backoff in application

PTU Capacity Unavailable Error

No PTU quota allocated in region, or PTU not available for model/region.

Resolution:

  1. Check PTU 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[?contains(name.value,'ProvisionedManaged')].{Model:name.value, Used:currentValue, Limit:limit}" -o table
  2. Options:

    • Request PTU quota increase through Azure Portal (include capacity calculator results)
    • Try different region where PTU is available
    • Use Standard TPM instead

SKU Not Supported Error

PTU not available for specific model or region combination.

Resolution:

  1. Check model availability:

  2. Options:

    • Deploy with Standard TPM SKU instead
    • Choose different region where PTU is supported
    • Use alternative model that supports PTU in your region

Request Quota Increase Process

For Standard TPM Quota

  1. Navigate to Azure Portal → Your Foundry resource → Quotas
  2. Identify model needing increase (e.g., "GPT-4o Standard")
  3. Click Request quota increase
  4. Fill form:
    • Model name
    • Requested quota (in TPM)
    • Business justification (required)
  5. Submit and monitor status

Processing Time: Typically 1-2 business days

For PTU Quota

  1. Navigate to Azure Portal → Your Foundry resource → Quotas
  2. Select Provisioned throughput unit tab
  3. Identify model needing PTU increase
  4. Click Request quota increase
  5. Fill form:
    • Model name
    • Requested PTU quota
    • Include capacity calculator results
    • Detailed business justification (workload characteristics)
  6. Submit and monitor status

Processing Time: Typically 3-5 business days (requires stronger justification)

Diagnostic Commands

# Check deployment status
az cognitiveservices account deployment show \
  --name <resource-name> \
  --resource-group <rg> \
  --deployment-name <deployment-name>

# Verify available 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, Available:(limit-currentValue)}" \
  --output table

# List all deployments
az cognitiveservices account deployment list \
  --name <resource-name> \
  --resource-group <rg> \
  --query '[].{Name:name, Model:properties.model.name, Capacity:sku.capacity, SKU:sku.name}' \
  --output table

External Resources

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub3d

    This skill provides a comprehensive environment for managing the end-to-end lifecycle of AI agents, models, and infrastructure on Microsoft Foundry. It includes sub-skills for deployment, evaluation, fine-tuning, and troubleshooting. The skill utilizes dynamic code execution and shell command wrappers, which are used within the context of local development and cloud orchestration. All external resources and dependencies originate from trusted organizations and well-known services.

  • Socket3d

    2 alerts: gptSecurity, gptAnomaly

  • Snyk3d

    Risk: LOW · No issues

  • Runlayer7mo

    36/36 files flagged

Signed by skilld at 04110d9. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

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metadata
{
  "author": "Microsoft",
  "version": "1.2.26"
}

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