bzellman/preset

Deploy Model to Optimal Region

Automates intelligent Azure OpenAI model deployment by checking capacity across regions and deploying to the best available option.

What This Skill Does

1. Verifies Azure authentication and project scope
2. Checks capacity in current project's region
3. If no capacity: analyzes all regions and shows available alternatives
4. Filters projects by selected region
5. Supports creating new projects if needed
6. Deploys model with GlobalStandard SKU
7. Monitors deployment progress

Prerequisites

• Azure CLI installed and configured
• Active Azure subscription with Cognitive Services read/create permissions
• Azure AI Foundry project resource ID (PROJECT_RESOURCE_ID env var or provided interactively)
  • Format: /subscriptions/{sub-id}/resourceGroups/{rg}/providers/Microsoft.CognitiveServices/accounts/{account}/projects/{project}
  • Found in: Azure AI Foundry portal → Project → Overview → Resource ID

Quick Workflow

Fast Path (Current Region Has Capacity)

1. Check authentication → 2. Get project → 3. Check current region capacity
→ 4. Deploy immediately

Alternative Region Path (No Capacity)

1. Check authentication → 2. Get project → 3. Check current region (no capacity)
→ 4. Query all regions → 5. Show alternatives → 6. Select region + project
→ 7. Deploy

---

Deployment Phases

| Phase | Action | Key Commands | |-------|--------|-------------| | 1. Verify Auth | Check Azure CLI login and subscription | az account show, az login | | 2. Get Project | Parse PROJECT_RESOURCE_ID ARM ID, verify exists | az cognitiveservices account show | | 3. Get Model | List available models, user selects model + version | az cognitiveservices account list-models | | 4. Check Current Region | Query capacity using GlobalStandard SKU | az rest --method GET .../modelCapacities | | 5. Multi-Region Query | If no local capacity, query all regions | Same capacity API without location filter | | 6. Select Region + Project | User picks region; find or create project | az cognitiveservices account list, az cognitiveservices account create | | 7. Deploy | Generate unique name, calculate capacity (50% available, min 50 TPM), create deployment | az cognitiveservices account deployment create |

For detailed step-by-step instructions, see workflow reference.

---

Error Handling

| Error | Symptom | Resolution | |-------|---------|------------| | Auth failure | az account show returns error | Run az login then az account set --subscription <id> | | No quota | All regions show 0 capacity | Defer to the quota skill for increase requests and troubleshooting; check existing deployments; try alternative models | | Model not found | Empty capacity list | Verify model name with az cognitiveservices account list-models; check case sensitivity | | Name conflict | "deployment already exists" | Append suffix to deployment name (handled automatically by generate_deployment_name script) | | Region unavailable | Region doesn't support model | Select a different region from the available list | | Permission denied | "Forbidden" or "Unauthorized" | Verify Cognitive Services Contributor role: az role assignment list --assignee <user> |

---

Advanced Usage

# Custom capacity
az cognitiveservices account deployment create ... --sku-capacity <value>

# Check deployment status
az cognitiveservices account deployment show --name <acct> --resource-group <rg> --deployment-name <name> --query "{Status:properties.provisioningState}"

# Delete deployment
az cognitiveservices account deployment delete --name <acct> --resource-group <rg> --deployment-name <name>

Notes

• SKU: GlobalStandard only — API Version: 2024-10-01 (GA stable)

---

Related Skills

• microsoft-foundry - Parent skill for Azure AI Foundry operations
• quota — For quota viewing, increase requests, and troubleshooting quota errors, defer to this skill
• azure-quick-review - Review Azure resources for compliance
• azure-cost-estimation - Estimate costs for Azure deployments
• azure-validate - Validate Azure infrastructure before deployment