airunway-aks-setup
Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first…
Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast
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Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast
name: preset description: "Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize)." license: MIT metadata: author: Microsoft version: "1.0.1"
Automates intelligent Azure OpenAI model deployment by checking capacity across regions and deploying to the best available option.
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
1. Check authentication → 2. Get project → 3. Check current region capacity → 4. Deploy immediately
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
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| 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).
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| 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>` |
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# 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>---
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Repo: microsoft/azure-skills
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