customize
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
Target: Cloud, operations & security. Automatically collected · unverified.
Excerpt from the author’s documentation
Extracted from a fixed version of SKILL.md in its original language. This is the author’s documentation; installation, compatibility and runtime results have not been verified by this site.
Read the original English text
Topics in the source
- Customize Model Deployment
- Quick Reference
- When to Use This Skill
- Comparison: customize vs preset
- Prerequisites
- Workflow Overview
- Complete Flow (14 Phases)
- Fast Path (Defaults)
Interactive guided workflow for deploying Azure OpenAI models with full customization control over version, SKU, capacity, content filtering, and advanced options. | Property | Description | |----------|-------------| | Flow | Interactive step-by-step guided deployment | | Customization | Version, SKU, Capacity, RAI Policy, Advanced Options | | SKU Support | GlobalStandard, Standard, ProvisionedManaged, DataZoneStandard | | Best For | Precise control over deployment configuration | | Authentication | Azure CLI (az login) | | Tools | Azure CLI, MCP tools (optional) | Use this skill when you need precise control over deployment configuration: ✅ Choose specific model version (not just latest) ✅ Select deployment SKU (GlobalStandard vs Standard vs PTU) ✅ Set exact capacity within available range ✅ Configure content filtering (RAI policy selection) ✅ Enable advanced features (dynamic quota, priority processing, spillover) ✅ PTU deployments (Provisioned Throughput Units) Alternative: Use preset for quick deployment to the best available region with automatic configuration. | Feature | customize | preset | |---------|---------------------|----------------------------| | Focus | Full custo
This is an excerpt. Refer to the complete source and its current requirements.
- Source repository
- microsoft/skills
- Source file
- .github/plugins/azure-skills/skills/microsoft-foundry/models/deploy-model/customize/SKILL.md
- Fixed revision
- 9287b443662d2433c85621c7325ee72a0ce499b5
Requirements
- Only the author’s Skill metadata is included. Read the full instructions to check dependencies, licensing and conditions of use.
A small first task
先阅读原作者说明，再决定是否在自己的 AI 工具中使用。
Instructions for your AI tool
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- Codex: resource-specific guide not available yet
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This record was collected automatically. Its documentation, suitability and runtime behavior have not been manually verified.
Author: Microsoft Skills · original repository metadata. Documentation review: Not reviewed. Last source check: 2026-11-10T19:02:07.923Z.
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License and attribution
MIT. Third-party content and copyright remain with their authors. Refer to the original license and terms.
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