skill
Preset
نبذة
# 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 - Microsoft 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: Microsoft 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](references/workflow.md).
---
## 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](../../../quota/quota.md) 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
```bash # 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 Microsoft Foundry operations - **[quota](../../../quota/quota.md)** — For quota viewing, increase requests, and troubleshooting quota errors, defer to this skill - **azure-quick-review** - Review Azure resources for compliance - **cost-estimation** - Estimate costs through the separately installed `azure-cost` plugin - **azure-validate** - Validate Azure infrastructure before deployment
التثبيت
شغل هذا الأمر
git clone https://github.com/microsoft/azure-skills && cp -r azure-skills/skills/microsoft-foundry/models/deploy-model/preset ~/.claude/skills/يعمل مع
خطوات التثبيت
Clone the repository and copy the `skills/microsoft-foundry/models/deploy-model/preset` folder into your Claude skills directory. Compatible with Claude Code, Cursor, Codex, and any Agent Skills-compatible agent.
أسئلة شائعة
كيف أثبت Preset؟
شغل هذا الأمر في الطرفية:
git clone https://github.com/microsoft/azure-skills && cp -r azure-skills/skills/microsoft-foundry/models/deploy-model/preset ~/.claude/skills/مع أي أدوات ذكاء اصطناعي تعمل Preset؟
تعمل مع claude_app، claude_code، claude_api، cursor، codex، windsurf، cline، zed.
من طور Preset؟
طورها Microsoft، وتصدر بترخيص MIT.
هل Preset مجانية؟
نعم، يمكنك استخدامها مجانا وفق ترخيص MIT.
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تدقيق الظهور في محركات الذكاء الاصطناعي
الظهور في الذكاء الاصطناعي
مولد ملف llms.txt
الظهور في الذكاء الاصطناعي
مقياس سهولة القراءة بالعربية
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