Discover Azure OpenAI model capacity across regions and projects.
npx skills add https://github.com/jgezelscorp/Apex --skill capacity-jgezelscorp
Please help me install this Agent Skill. Skill: capacity Source: https://github.com/jgezelscorp/Apex/tree/main/.github/skills/microsoft-foundry/models/deploy-model/capacity Command: npx skills add https://github.com/jgezelscorp/Apex --skill capacity-jgezelscorp
This Skill helps you discover available Azure OpenAI model capacity across regions and projects, ensuring that you can find the best deployment location for your specific requirements.
Run the script 'discover_and_rank.ps1' with your model name, version, and minimum capacity target, e.g., './scripts/discover_and_rank.ps1 -ModelName gpt-4o -ModelVersion 2025-01-31 -MinCapacity 200'
High-intent search queries and answers about installing and using this skill.
Azure OpenAI capacity discovery analyzes accessible regions and projects to identify available model capacity, compares it against your subscription quota limits, and recommends optimal deployment locations based on your specified minimum capacity requirements.
Yes, checking Azure OpenAI quota limits requires Azure CLI for authentication and access to Cognitive Services resources. The discovery script analyzes regional model availability and compares it against your project quota limits to recommend deployment locations.
The best way to plan Azure OpenAI deployment locations is to execute a capacity discovery script with your target model name, specific model version, and minimum capacity target. This analyzes regional availability and ranks optimal deployment locations for your infrastructure planning.
Yes, Azure CLI is a required dependency for discovering Azure OpenAI model capacity. It handles authentication and provides access to Cognitive Services resources needed to perform region analysis, quota evaluation, and capacity discovery across projects.
Azure OpenAI deployments fail due to insufficient regional capacity when target regions lack available resources or exceed subscription quota limits. Running a capacity discovery script beforehand identifies regions with sufficient capacity, preventing deployment failures and ensuring successful model provisioning.
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