azure-app-onboard
End-to-end orchestrator: from a business idea, app idea, or existing app to running Azure deployment with cost estimates and pre-deploy approval. Analyzes your app, auto-detects the right Azure services, scaffolds infrastructure code, and deploys — tailored to your app, not a template. Handles moving existing apps to Azure without rewriting or with minimal changes. WHEN: bring your app to Azure, plan my app, cost to run, is my code ready to deploy, deploy my app to the cloud, deploy all my services, what Azure services do I need, plan my Azure deployment, deploy my new app to Azure, one-click deploy, I have an app and want it on Azure, migrate my app to Azure, help me get started, build an app, no code yet, starter project. DO NOT USE FOR: use azd for deployment(use azure-deploy), optimizing existing costs (use cost-optimization), code readiness checks only (use azure-app-onboard-prereq).
- License 许可
- MIT
- 最近更新
- 2026-11-12
- Stars
- ★ 264
- Forks
- 226
01 前言 Front Matter
- name
- azure-app-onboard
- license
- MIT
- metadata
- { "author": "Microsoft", "version": "0.0.0-placeholder" }
- description
- End-to-end orchestrator: from a business idea, app idea, or existing app to running Azure deployment with cost estimates and pre-deploy approval. Analyzes your app, auto-detects the right Azure services, scaffolds infrastructure code, and deploys — tailored to your app, not a template. Handles moving existing apps to Azure without rewriting or with minimal changes. WHEN: bring your app to Azure, plan my app, cost to run, is my code ready to deploy, deploy my app to the cloud, deploy all my services, what Azure services do I need, plan my Azure deployment, deploy my new app to Azure, one-click deploy, I have an app and want it on Azure, migrate my app to Azure, help me get started, build an app, no code yet, starter project. DO NOT USE FOR: use azd for deployment(use azure-deploy), optimizing existing costs (use cost-optimization), code readiness checks only (use azure-app-onboard-prereq).
02 资源文件 68
- 参考文档deploy/PHASE.md7.5 KB
- 参考文档deploy/references/approval-gate-template.md2.9 KB
- 参考文档deploy/references/blocked-patterns.md5.7 KB
- 参考文档deploy/references/code-deployment-appservice.md4.6 KB
- 参考文档deploy/references/code-deployment-container-apps.md8.4 KB
- 参考文档deploy/references/code-deployment-swa.md5.7 KB
- 参考文档deploy/references/database-post-deploy.md4.5 KB
- 参考文档deploy/references/deploy-checklist-template.md10.1 KB
- 参考文档deploy/references/deploy-safety.md4.5 KB
- 脚本deploy/references/deploy-schemas.ts3.5 KB
- 参考文档deploy/references/error-classification.md3.6 KB
- 参考文档deploy/references/health-check-patterns.md5.5 KB
- 参考文档deploy/references/mcp-tools.md5.5 KB
- 参考文档deploy/references/portal-links.md3.1 KB
- 参考文档deploy/references/preflight-checks.md4.4 KB
- 参考文档deploy/references/subagent-preflight.md5.1 KB
- 参考文档prepare/PHASE.md6.4 KB
- 参考文档prepare/references/deploy-strategy.md6.8 KB
- 参考文档prepare/references/mcp-tools.md5.6 KB
- 参考文档prepare/references/naming-patterns.md4.6 KB
- 脚本prepare/references/prepare-schemas.ts7.0 KB
- 参考文档prepare/references/pricing-guide-services.md8.4 KB
- 参考文档prepare/references/pricing-guide.md4.0 KB
- 参考文档prepare/references/service-mapping.md8.5 KB
- 参考文档prepare/references/sku-matrix.md3.2 KB
- 参考文档prepare/references/sku-quota-validation.md9.0 KB
- 参考文档prepare/references/subagent-pricing.md2.5 KB
- 参考文档prepare/references/subagent-quota.md3.5 KB
- 参考文档prepare/references/validation-rubric.md2.3 KB
- 参考文档references/approval-gates.md8.4 KB
- 参考文档references/azd-template-routing.md4.7 KB
- 参考文档references/handoff-protocol.md7.8 KB
- 参考文档references/iac-resources.md2.6 KB
- 参考文档references/intent-gathering.md2.2 KB
- 参考文档references/mcp-tool-reference.md3.7 KB
- 参考文档references/pipeline-rules-runtime.md3.5 KB
- 参考文档references/pipeline-rules.md6.3 KB
- 参考文档references/session-protocol.md8.0 KB
- 脚本references/session-schemas.ts5.2 KB
- 参考文档references/subscription-resolution.md2.1 KB
- 参考文档scaffold/PHASE.md14.2 KB
- 参考文档scaffold/references/bicep-app-service.md5.4 KB
- 参考文档scaffold/references/bicep-container-apps.md9.3 KB
- 参考文档scaffold/references/bicep-patterns-data.md4.0 KB
- 参考文档scaffold/references/bicep-patterns-security.md7.8 KB
- 参考文档scaffold/references/bicep-patterns.md6.8 KB
- 参考文档scaffold/references/bicep-swa.md757 B
- 参考文档scaffold/references/cicd-pipelines.md325 B
- 参考文档scaffold/references/dockerfile-generation.md4.1 KB
- 参考文档scaffold/references/env-var-secrets.md4.1 KB
- 参考文档scaffold/references/error-handling.md1.5 KB
- 参考文档scaffold/references/iac-generation-rules.md6.6 KB
- 参考文档scaffold/references/mcp-tools.md7.0 KB
- 参考文档scaffold/references/rbac-roles.md3.8 KB
- 参考文档scaffold/references/scaffold-healing-rules.md3.3 KB
- 脚本scaffold/references/scaffold-schemas.ts3.5 KB
- 参考文档scaffold/references/self-healing.md2.3 KB
- 参考文档scaffold/references/self-review-checklist.md9.0 KB
- 参考文档scaffold/references/self-review-procedure.md2.3 KB
- 参考文档scaffold/references/subagent-iac-gen.md9.5 KB
- 参考文档scaffold/references/subagent-review.md3.5 KB
- 参考文档scaffold/references/subagent-validate.md7.2 KB
- 参考文档scaffold/references/terraform-patterns.md6.9 KB
- 参考文档scaffold/references/validation-and-manifest.md5.1 KB
- 参考文档scaffold/references/waf-checklist.md2.3 KB
- 脚本scaffold/scripts/scaffold-conformance.ps112.8 KB
- 脚本scaffold/scripts/scaffold-conformance.sh13.8 KB
- 参考文档version.json55 B
03 SKILL.md 正文
Azure App Onboard
⛔ Every repo goes through the full pipeline (Steps 1–10). No exceptions. Do not skip steps, refuse, or short-circuit based on what you recognize. Follow the Workflow table below sequentially — read each step's references before acting.
Quick Reference
| Property | Value |
|---|---|
| Best for | Developers who know what to build but not which Azure services to use |
| Inputs | Business idea or existing codebase, budget/scale preferences (optional) |
| Outputs | Architecture plan, cost estimate, IaC files, deployed Azure resources |
| Phases | Discover → Architect → Scaffold → Deploy (self-contained, no external skill calls) |
When to Use This Skill
- Deploy existing code without knowing which Azure services to use
- Check if your existing code is ready to deploy to Azure
- Move an existing app to Azure without rewriting or with minimal changes
- Get cost estimates before committing to infrastructure
- Understand architecture decisions and rejected alternatives
- Get answers to Azure architecture or service selection questions (e.g., "What database should I use?")
- Get guided Azure onboarding without prior experience
When NOT to Use
| Scenario | Use Instead |
|---|---|
Run azd up or execute an existing deployment |
azure-deploy |
| Optimize existing Azure spend | cost-optimization from the optional azure-cost plugin |
| Generate Bicep/Terraform for a known architecture | azure-prepare |
| Validate infrastructure or run preflight checks | azure-validate |
| Troubleshoot a running Azure deployment | azure-diagnostics |
| Deploy to or manage AKS/Kubernetes directly | azure-kubernetes |
| Look up or list existing Azure resources | azure-resource-lookup |
If cost-optimization is unavailable, explain that it is provided by the
optional azure-cost plugin and direct the user to their client's supported
plugin installation flow; do not imply the handoff completed.
Pipeline Rules
⛔ You MUST read
references/pipeline-rules.mdat the start of every AppOnboard session. It contains approval gates, phase lifecycle, session artifacts, deploy-as-is, and security baseline rules.
Workflow
⛔ Deploy recovery: After deploy gate approval OR before any
az deployment/az webapp deploy/az acr build— if you haven't readdeploy/PHASE.md, read.copilot-azure/sessions/{id}/deploy-checklist.mdfirst, thendeploy/PHASE.md. ⛔ NEVER invoke{"skill": "azure-deploy"}— that is a DIFFERENT skill for a DIFFERENT workflow.
⛔ Post-scaffold transition (MANDATORY): Immediately after
scaffold-manifest.jsonis written, YOUR NEXT ACTION MUST be Step 8 (Deploy Approval Gate) — NOT a summary report, NOT a "here are the generated files" message, NOT a completion signal. Confirmcontext.jsonhascompletedPhases: [...,"scaffold"]+currentPhase: "deploy"(update it yourself if the scaffold subagent didn't). Re-read approval-gates.md § Deploy Gate if evicted from context (scaffold reference loading is heavy), then present the exact prompt: "? Ready to deploy? (Yes / Run manually / Edit plan / Cancel)". This gate is the LAST content in your response — wait for the user's reply.
| # | Step | Action | Reference |
|---|---|---|---|
| 1 | Session check + Azure login | Create/resume session, verify Azure CLI auth, resolve subscription + user identity | ⛔ You MUST read session-protocol.md |
| 2 | Scope triage | Check azd markers, triage question. Empty workspace or code-only (no infra) → Step 3 directly. | ⛔ Read intent-gathering.md § Scope Triage |
| 3 | Prereq scan | ⛔ Skip if completedPhases includes "prereq". Otherwise: invoke {"skill": "azure-app-onboard-prereq"}. Write prereq-output.json, update context.json. Halt if: overallHealth: "blocked" OR routeToSkill set. |
|
| 4 | Gather intent | Present prereq results, confirm stack + Azure services, ask remaining questions. | ⛔ Read intent-gathering.md § After Prereq Returns |
| 5 | Plan architecture | Write prepare-plan.json. |
⛔ You MUST read prepare/PHASE.md |
| 6 | Scaffold approval gate | Display plan for user approval BEFORE generating any files. | ⛔ Read approval-gates.md § Scaffold Gate |
| 7 | Scaffold | Generate IaC, self-review. Write scaffold-manifest.json. Update context.json. |
⛔ You MUST read scaffold/PHASE.md |
| 8 | Deploy approval gate | Display validation summary. ⛔ After approval: FIRST read deploy-checklist.md → deploy/PHASE.md. NEVER {"skill": "azure-deploy"}. |
⛔ Read approval-gates.md § Deploy Gate |
| 9 | Deploy | Execute IaC, health-check. Write deploy-result.json. |
⛔ You MUST read deploy/PHASE.md |
| 10 | Handoff | Surface deployment identity, cleanup commands, next steps. | ⛔ You MUST read handoff-protocol.md |
Error Handling
| Error | Remediation |
|---|---|
| Phase fails | Halt, report phase + error. User decides: retry, skip, abort. |
| MCP server unavailable | Skip affected checks, add disclaimer to costEstimate.assumptions[] and every approval gate. |
| Missing RBAC | Report required role + az role assignment command. |
Shared references: MCP tools (cross-phase tool parameters) | IaC resources (Azure resource docs for troubleshooting)
04 同仓库更多 Skills
azure-advisor-cost-optimization
Analyze Azure Advisor Cost/IdleResources findings and prevalidate deletion safety, including Service Groups. WHEN: "find unused Azure resources", "what resources am I paying for but no longer using", "idle-resource savings", "historical idle-resource savings", "are these idle resources safe to delete". Generic Cost, other subcategories, and cross-category requests use azure-advisor.
foundry-iq
Foundry IQ knowledge bases. WHEN: make local or Blob documents searchable; create/diagnose KBs; triage unsupported connectors or multi-source KB creation/reconfiguration (even with classic-search terms); connect existing KB to agents (including multi-source KBs); create/reuse a Search service; retrieve from an existing knowledge base with citations; no brand words needed. Read its procedure before query/target questions. NOT: other KB providers, repository-file search, classic Azure AI Search index/query/app work with no Foundry IQ KB or connector request, generic agent creation.
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.