azure-kubernetes-app-deploy
Use when deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. 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.
- License 许可
- MIT
- 最近更新
- 2026-11-13
- Stars
- ★ 1.6k
- Forks
- 267
01 前言 Front Matter
- name
- azure-kubernetes-app-deploy
- license
- MIT
- metadata
- { "author": "Microsoft", "version": "1.0.0" }
- description
- Use when deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. 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.
02 资源文件 41
- 参考文档knowledge-packs/frameworks/aspnet-core.md7.3 KB
- 参考文档knowledge-packs/frameworks/django.md6.0 KB
- 参考文档knowledge-packs/frameworks/express.md6.7 KB
- 参考文档knowledge-packs/frameworks/fastapi.md5.8 KB
- 参考文档knowledge-packs/frameworks/flask.md6.2 KB
- 参考文档knowledge-packs/frameworks/go.md6.8 KB
- 参考文档knowledge-packs/frameworks/nestjs.md6.7 KB
- 参考文档knowledge-packs/frameworks/nextjs.md7.1 KB
- 参考文档knowledge-packs/frameworks/spring-boot.md6.0 KB
- 参考文档phases/quick-deploy.md7.8 KB
- 参考文档references/base-images.md3.6 KB
- 参考文档references/detection.md3.5 KB
- 参考文档references/rollback.md2.0 KB
- 参考文档references/safeguards.md2.9 KB
- 参考文档references/workload-identity.md7.4 KB
- 其他templates/dockerfiles/dotnet.Dockerfile2.6 KB
- 其他templates/dockerfiles/dotnet.dockerignore125 B
- 其他templates/dockerfiles/go.Dockerfile2.1 KB
- 其他templates/dockerfiles/go.dockerignore128 B
- 其他templates/dockerfiles/java.Dockerfile3.0 KB
- 其他templates/dockerfiles/java.dockerignore156 B
- 其他templates/dockerfiles/node.Dockerfile3.0 KB
- 其他templates/dockerfiles/node.dockerignore173 B
- 其他templates/dockerfiles/python.Dockerfile2.6 KB
- 其他templates/dockerfiles/python.dockerignore201 B
- 其他templates/dockerfiles/rust.Dockerfile3.2 KB
- 其他templates/dockerfiles/rust.dockerignore87 B
- 参考文档templates/github-actions/deploy.yml7.4 KB
- 参考文档templates/k8s/configmap.yaml1.0 KB
- 参考文档templates/k8s/deployment.yaml3.4 KB
- 参考文档templates/k8s/gateway.yaml1.5 KB
- 参考文档templates/k8s/hpa.yaml1.4 KB
- 参考文档templates/k8s/httproute.yaml1.3 KB
- 参考文档templates/k8s/ingress.yaml1.9 KB
- 参考文档templates/k8s/namespace.yaml734 B
- 参考文档templates/k8s/networkpolicy.yaml1.6 KB
- 参考文档templates/k8s/pdb.yaml758 B
- 参考文档templates/k8s/service.yaml864 B
- 参考文档templates/k8s/serviceaccount.yaml1.4 KB
- 参考文档templates/mermaid/architecture-diagram.md1.6 KB
- 参考文档templates/mermaid/summary-dashboard.md1.7 KB
03 SKILL.md 正文
Deploy to AKS
Use when: deploying a web app/API to AKS; containerizing for Kubernetes; generating manifests; AKS CI/CD; DS001–DS013 failures.
Not for: provisioning clusters (azure-kubernetes), AKS Automatic readiness (azure-kubernetes-automatic-readiness), non-AKS targets.
Workflow
Requires: existing AKS cluster, az login, kubectl configured. Follow phases/quick-deploy.md. On failure: references/rollback.md.
References
- detection.md — framework/port/health detection
- safeguards.md — DS001-DS013 checklist
- workload-identity.md — Workload Identity setup
- rollback.md — recovery procedures
- base-images.md — base image policy and
<LATEST_STABLE_*>resolution
Knowledge Packs
Load knowledge-packs/frameworks/<framework>.md per detected framework. Available: spring-boot, express, nextjs, fastapi, django, nestjs, aspnet-core, go, flask
Templates
templates/ (dockerfiles/, k8s/, github-actions/, mermaid/).
04 同仓库更多 Skills
python-appservice-deploy
Deploy Python (Flask/Django/FastAPI) 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/Bicep/IaC, full infra — use azure-prepare.
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).
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).
capacity
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.
deploy-model
Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI 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/create), project creation (use project/create).
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).