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DO NOT USE FOR: creating or provisioning an AKS cluster (use azure-kubernetes), assessing migration to AKS Automatic (use azure-kubernetes-automatic-readiness), or deploying to non-AKS targets like Web Apps, Container Apps, or Functions.\"\n---\n\n# Deploy to AKS\n\n**Use when:** deploying a web app\u002FAPI to AKS; containerizing for Kubernetes; generating manifests; AKS CI\u002FCD; DS001–DS013 failures.\n\n**Not for:** provisioning clusters (`azure-kubernetes`), AKS Automatic readiness (`azure-kubernetes-automatic-readiness`), non-AKS targets.\n\n## Workflow\n\nRequires: existing AKS cluster, `az login`, `kubectl` configured. Follow `phases\u002Fquick-deploy.md`. On failure: `references\u002Frollback.md`.\n\n## References\n\n- [detection.md](.\u002Freferences\u002Fdetection.md) — framework\u002Fport\u002Fhealth detection\n- [safeguards.md](.\u002Freferences\u002Fsafeguards.md) — DS001-DS013 checklist\n- [workload-identity.md](.\u002Freferences\u002Fworkload-identity.md) — Workload Identity setup\n- [rollback.md](.\u002Freferences\u002Frollback.md) — recovery procedures\n- [base-images.md](.\u002Freferences\u002Fbase-images.md) — base image policy and `\u003CLATEST_STABLE_*>` resolution\n\n## Knowledge Packs\n\nLoad `knowledge-packs\u002Fframeworks\u002F\u003Cframework>.md` per detected framework. 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Python (Flask\u002FDjango\u002FFastAPI) code to Azure App Service Linux. WHEN: \"Flask App Service\", \"Django App Service\", \"FastAPI App Service\", \"deploy Python to App Service\". DO NOT USE FOR: Container Apps, Functions, non-Python, Terraform\u002FBicep\u002FIaC, full infra — use azure-prepare.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fpython-appservice-deploy\u002FSKILL.md",[250],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[252,24,253,254,255,29,256,257,258,259,27,260,261,262,263,35,33,264,265,266],"python appservice deploy","python","linux","infra","do","django","for","azure app service","container","iac","fastapi","use","code","functions","fastapi app",{"skillNo":268,"name":269,"nameZh":6,"description":270,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":271,"categories":272,"keywords":277,"publishedAt":45},"01M699VDV3PT5P0YDXRT4GM2TJ","preset","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).","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fpreset\u002FSKILL.md",[273,274],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":275,"categoryName":276,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[269,24,278,9,279,280,256,281,282,258,283,284,285,27,286,287,288,263,289,290,291,292,293],"setup","capacity","customize","quick","availability","deployment","alternatives","selection","custom","deployments","high availability","version","across","check","multi","first",{"skillNo":295,"name":280,"nameZh":6,"description":296,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":297,"categories":298,"keywords":300,"publishedAt":45},"01M699VBT6YFAKBWCK890XDB6N","Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard\u002FStandard\u002FProvisionedManaged), 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).","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fcustomize\u002FSKILL.md",[299],{"categoryNo":275,"categoryName":276,"taxonomyType":21,"taxonomyTypeDesc":22},[280,269,9,279,301,31,281,302,303,304,305,306,285,307,308,309,310,311,312,313,314,256,258,283],"policy","processing","advanced","model","select","choose","configure","filter","azure openai","options","flow","openai","throughput","full",{"skillNo":316,"name":279,"nameZh":6,"description":317,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":318,"categories":319,"keywords":320,"publishedAt":45},"01M699V9FXHBSWG3Y48057VAYZ","Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fcapacity\u002FSKILL.md",[],[279,269,24,9,280,321,304,322,323,324,325,326,290,309,327,328,312,329,330,256,282,258,331,283],"projects","project","search","analysis","listing","hand","limits","azure portal","direct","TPM","discovery",{"skillNo":333,"name":334,"nameZh":6,"description":335,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":336,"categories":337,"keywords":340,"publishedAt":45},"01M699V7GW2RF4AB3RE3Z8Y048","deploy-model","Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version\u002FSKU\u002Fcapacity\u002FRAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent\u002Fcreate), project creation (use project\u002Fcreate).","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002FSKILL.md",[338,339],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":275,"categoryName":276,"taxonomyType":21,"taxonomyTypeDesc":22},[24,341,304,269,342,343,9,279,301,31,321,281,344,322,38,324,325,290,345,309,346,347,312,256,282],"deploy model","MCP","foundry","creation","create","intent","list",{"skillNo":349,"name":350,"nameZh":6,"description":351,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":352,"categories":353,"keywords":355,"publishedAt":45},"01M699V3NA4YQKCHJTVWHBQH10","finetuning","Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-tuned model, evaluate fine-tuned model. DO NOT USE FOR: general model deployment without fine-tuning (use deploy-model), agent creation (use agents), prompt optimization without training (use prompt-optimizer).","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fmicrosoft-foundry\u002Ffinetuning\u002FSKILL.md",[354],{"categoryNo":275,"categoryName":276,"taxonomyType":21,"taxonomyTypeDesc":22},[350,356,24,343,357,9,358,344,304,359,360,361,362,363,364,365,366,367,256,258,368,369,283,370],"placeholder","microsoft foundry","Prompt Optimization","training","dataset","optimizer","Evaluation","tuning","grader","data","supervised","distillation","Optimization","calibrate","submission"]