Discover Azure OpenAI capacity and quota across regions for a model version.
npx skills add https://github.com/Chieji/my-skills --skill capacity-chieji
Please help me install this Agent Skill. Skill: capacity Source: https://github.com/Chieji/my-skills/tree/main/microsoft-foundry/models/deploy-model/capacity Command: npx skills add https://github.com/Chieji/my-skills --skill capacity-chieji
Capacity planning for Azure OpenAI deployments is time-consuming and error-prone; this Skill automates cross-region capacity discovery and quota checks to guide deployment decisions.
Run the discovery script with a model name and version to generate a ranked region table of capacity and quota.
High-intent search queries and answers about installing and using this skill.
To check Azure OpenAI capacity, run the discovery script with a specific model name and version to query modelCapacities and subscription quota per region. It returns a ranked table comparing availability and existing AI Projects to guide your deployment planning.
The best way to find available regions is to automate cross-region capacity discovery. This script queries modelCapacities for a given model version and SKU, cross-references existing AI Projects, and ranks regions by quota availability to maximize deployment success.
Yes, you need Azure CLI, Python 3, and jq installed to automate OpenAI capacity discovery. These dependencies are required to execute the scripts that query subscription quota, list AIProjects, and process the ranked region results.
Cross-referencing AI Projects helps deployment planning by estimating existing deployment options within your subscription. The script lists current AIProjects alongside regional quota checks, providing a complete view of available capacity before handing off to presets or customization.
Yes, you can compare Azure OpenAI model capacities between regions before deployment. The script generates a ranked results table annotated with quota availability and project counts, allowing you to evaluate and select the optimal region for maximum availability.
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