preset

Name: preset
Availability: InStock
Author: Microsoft

Deploy Azure OpenAI models by checking regional capacity and selecting the best option.

2.9k|323|Updated Jan 16, 2026

Search Tags:#azure #openai #deploy #foundry #capacity #region

Ready to run

npx skills add https://github.com/microsoft/skills --skill preset-microsoft

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: preset
Source: https://github.com/microsoft/skills/tree/main/.github/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/preset
Command: npx skills add https://github.com/microsoft/skills --skill preset-microsoft

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

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

Core Features & Use Cases

Quick-path deployment: leverage current region capacity to deploy immediately when available.
Alternative-region handling: analyze all regions and present best-region options when local capacity is exhausted.
On-demand project management: create or locate projects as needed to support deployment.
End-to-end deployment monitoring: track provisioning progress and surface status updates.

Quick Start

Install and run the skill to automatically deploy your model to the optimal region with capacity checks.

Frequently Asked Questions about preset

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate Azure OpenAI deployment to regions with available capacity?▼

Azure OpenAI deployment is automated by checking capacity across regions and deploying to the best available option. This skill orchestrates authentication, region selection, and provisioning to ensure models deploy fast and smart.

What should I do if my current Azure region has no capacity for OpenAI models?▼

When local capacity is exhausted, the deployment process analyzes all alternative regions and presents the best-region options. It handles alternative-region capacity checks automatically to find an available deployment target.

Can I use Azure AI Foundry projects for multi-region OpenAI capacity checks?▼

Yes, multi-region capacity checks are supported using an Azure AI Foundry project resource ID. The skill creates or locates projects on demand to facilitate high-availability setups and intelligent region selection.

How does intelligent region selection work for Azure OpenAI model provisioning?▼

Intelligent region selection works by checking current region capacity for a quick-path deployment, or analyzing all regions for alternatives when capacity is exhausted, then monitoring the end-to-end provisioning progress.

Does Azure OpenAI deployment support high-availability setups across multiple regions?▼

Yes, high-availability setups are supported across multiple regions. The deployment automation checks capacity, selects the best available region, and tracks provisioning progress to ensure robust model availability.