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Azure App Onboard

MicrosoftOfficialCreated by Microsoft

  • Skill
  • Workflow
  • Cloud and DevOps
  • MIT
  • Low risk
  • Has scripts

From the author

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).
— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Azure App Onboard is a comprehensive workflow agent designed to take a business idea or an existing codebase and transition it to a running Azure deployment. It automates the entire lifecycle from initial discovery and architecture planning to infrastructure scaffolding and final deployment. The skill is built to be intelligent and tailored, analyzing the specific requirements of your application rather than relying on generic templates. It includes built-in approval gates for both the architecture plan and the final deployment, ensuring you maintain control over costs and resource configuration throughout the process.

What it does

  • Analyzes your application code or business idea to determine the optimal Azure service stack.
  • Generates custom infrastructure-as-code (IaC) files tailored to your specific application needs.
  • Provides detailed cost estimates for the proposed Azure infrastructure before deployment.
  • Executes the deployment of resources directly to your Azure subscription.
  • Handles the migration of existing applications to Azure with minimal code changes.
  • Provides a structured, step-by-step onboarding experience for developers of all experience levels.

When to use it

  • When you have an application and want to deploy it to Azure but are unsure which services to use.
  • When you need to migrate an existing application to the cloud without a complete rewrite.
  • When you require a cost estimate for your infrastructure before committing to a deployment.
  • When you need guided, end-to-end assistance for setting up a new Azure project.
  • When you want to verify if your current codebase is ready for a cloud deployment.

Advantages

  • Eliminates guesswork by auto-detecting the right Azure services for your specific stack.
  • Reduces manual effort by automating the scaffolding of infrastructure-as-code.
  • Ensures transparency with mandatory approval gates for architecture and deployment.
  • Provides cost visibility early in the planning phase.
  • Supports a wide range of scenarios from greenfield projects to existing app migrations.

Usage examples

“I have a Python web app and want to deploy it to Azure. Can you help me get started?”
The agent will initiate the discovery phase, scan your codebase, propose an architecture, and guide you through the deployment process.
“I need to move my existing application to Azure, but I'm not sure what services I need. Can you plan this for me?”
The agent will analyze your app's requirements, suggest the appropriate Azure services, and provide a cost estimate for your approval.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/microsoft/azure-app-onboard/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip azure-app-onboard.zip -d .agents/skills

Documentation by Microsoft

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

PropertyValue
Best forDevelopers who know what to build but not which Azure services to use
InputsBusiness idea or existing codebase, budget/scale preferences (optional)
OutputsArchitecture plan, cost estimate, IaC files, deployed Azure resources
PhasesDiscover → 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

ScenarioUse Instead
Run azd up or execute an existing deploymentazure-deploy
Optimize existing Azure spendcost-optimization from the optional azure-cost plugin
Generate Bicep/Terraform for a known architectureazure-prepare
Validate infrastructure or run preflight checksazure-validate
Troubleshoot a running Azure deploymentazure-diagnostics
Deploy to or manage AKS/Kubernetes directlyazure-kubernetes
Look up or list existing Azure resourcesazure-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.md at 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 read deploy/PHASE.md, read .copilot-azure/sessions/{id}/deploy-checklist.md first, then deploy/PHASE.md. ⛔ NEVER invoke {"skill": "azure-deploy"} — that is a DIFFERENT skill for a DIFFERENT workflow.

⛔ Post-scaffold transition (MANDATORY): Immediately after scaffold-manifest.json is 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. Confirm context.json has completedPhases: [...,"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.

#StepActionReference
1Session check + Azure loginCreate/resume session, verify Azure CLI auth, resolve subscription + user identity⛔ You MUST read session-protocol.md
2Scope triageCheck azd markers, triage question. Empty workspace or code-only (no infra) → Step 3 directly.⛔ Read intent-gathering.md § Scope Triage
3Prereq 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.
4Gather intentPresent prereq results, confirm stack + Azure services, ask remaining questions.⛔ Read intent-gathering.md § After Prereq Returns
5Plan architectureWrite prepare-plan.json.⛔ You MUST read prepare/PHASE.md
6Scaffold approval gateDisplay plan for user approval BEFORE generating any files.⛔ Read approval-gates.md § Scaffold Gate
7ScaffoldGenerate IaC, self-review. Write scaffold-manifest.json. Update context.json.⛔ You MUST read scaffold/PHASE.md
8Deploy approval gateDisplay validation summary. ⛔ After approval: FIRST read deploy-checklist.md → deploy/PHASE.md. NEVER {"skill": "azure-deploy"}.⛔ Read approval-gates.md § Deploy Gate
9DeployExecute IaC, health-check. Write deploy-result.json.⛔ You MUST read deploy/PHASE.md
10HandoffSurface deployment identity, cleanup commands, next steps.⛔ You MUST read handoff-protocol.md

Error Handling

ErrorRemediation
Phase failsHalt, report phase + error. User decides: retry, skip, abort.
MCP server unavailableSkip affected checks, add disclaimer to costEstimate.assumptions[] and every approval gate.
Missing RBACReport required role + az role assignment command.

Shared references: MCP tools (cross-phase tool parameters) | IaC resources (Azure resource docs for troubleshooting)

Files

scaffold/references/terraform-patterns.md

Terraform Patterns

Alternative-path patterns for AppOnboard scaffold. Used when .tf files detected or user overrides iacFormat. Per-resource config comes from mcp_azure_mcp_azureterraformbestpractices at runtime — this file covers layout, provider, naming, state, tagging, and wiring.

File Structure

Default (greenfield or user override)
infra/
├── main.tf              # Root module — provider, resource group, module calls
├── variables.tf         # Input variables (all configurable values)
├── outputs.tf           # Exported values (endpoints, resource IDs)
├── backend.tf           # State backend config (local default, Azure Storage for prod)
├── terraform.tfvars     # Default variable values (from prepare-plan.json)
└── modules/
    ├── app-service/
    │   ├── main.tf
    │   ├── variables.tf
    │   └── outputs.tf
    ├── container-app/
    ├── sql-database/
    ├── key-vault/
    ├── log-analytics/
    └── ...
Non-Azure IaC coexistence (GCP/AWS TF already in repo)

When detectedInfraProvider.terraform is "gcp", "aws", or "multi" (without azurerm), write Azure TF to a separate directory from existing non-Azure TF. Never overwrite or modify existing IaC files.

Output directory rule: If existing TF is NOT at infra/, write to infra/. If existing TF IS at infra/ (or any path containing infra), write to infra-azure/. Same module structure as default layout.

Each Azure service gets its own module. main.tf orchestrates resource group + module calls.

Provider Configuration

terraform {
  required_version = ">= 1.5"

  required_providers {
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "~> 4.0"
    }
    random = {
      source  = "hashicorp/random"
      version = "~> 3.0"
    }
  }
}

provider "azurerm" {
  features {}
  subscription_id                 = var.subscription_id
  resource_provider_registrations = "none"
}

⛔ Never pin to exact patch versions (e.g., = 4.1.0). Use ~> 4.0 to allow minor/patch updates. azurerm manages API versions internally — if a resource isn't available in azurerm, use azapi_resource with the latest stable ARM API version.

Conditional access (AADSTS530084): azurerm provider re-requests tokens that violate device-binding policies. Fix: (1) switch to Bicep, or (2) use service principal auth (ARM_CLIENT_ID + ARM_CLIENT_SECRET + ARM_TENANT_ID).

variables.tf

Required variables: environment_name (string, default "dev"), location (string, default "eastus"), subscription_id (string), session_id (string), deployed_by (string). All configurable values MUST be variables — no hardcoded regions, names, or SKUs.

terraform.tfvars

Populate from prepare-plan.json: environment_name, location, subscription_id, session_id. See naming-patterns.md for naming convention.

Backend

Local backend by default: backend "local" { path = "terraform.tfstate" }. Recommend Azure Storage backend in postDeployRecommendations[] for production.

Resource Group

Use rg-${var.project_name}-${var.environment_name}-${random_string.suffix.result} with tags = local.tags. Suffix prevents collisions across AppOnboard sessions.

Naming Convention

resource "random_string" "suffix" {
  length  = 4
  special = false
  upper   = false
}

locals {
  # Pattern: {type}-{appname}-{env}-{suffix}
  app_name    = "app-${var.environment_name}-${random_string.suffix.result}"
  kv_name     = "kv-${var.environment_name}-${random_string.suffix.result}"
  sql_name    = "sql-${var.environment_name}-${random_string.suffix.result}"
  # Storage/ACR: alphanumeric only, no hyphens
  storage_name = "st${replace(var.environment_name, "-", "")}${random_string.suffix.result}"
  acr_name     = "cr${replace(var.environment_name, "-", "")}${random_string.suffix.result}"
}

Cross-reference naming with prepare/references/naming-patterns.md — Terraform names must match prepare-plan.json.naming.resources[].

Resource Tags — Mandatory

Apply all 5 AppOnboard tags via local.tags — see iac-generation-rules.md § Session Tags for tag names and values.

locals {
  tags = {
    "app-onboard-skill"       = "true"
    "app-onboard-session-id"  = var.session_id
    "created-at"      = timestamp()
    "environment"     = var.environment_name
    "deployed-by"     = var.deployed_by
  }
}

⚠️ timestamp() changes on every plan. Add lifecycle { ignore_changes = [tags["created-at"]] } on every resource.

Secrets — random_password, Not random_string

resource "random_password" "db_password" {
  length  = 32
  special = true
  lifecycle { ignore_changes = [result] }
}

resource "azurerm_key_vault_secret" "db_password" {
  name         = "db-password"
  value        = random_password.db_password.result
  key_vault_id = azurerm_key_vault.kv.id
}

⛔ NEVER use random_string for secrets — it is not marked sensitive in state. Always use random_password.

Container Apps — Two-Phase Wiring

Same circular dependency as Bicep — see bicep-container-apps.md. Phase 1: placeholder image, no ACR/KV refs. Phase 2: build + push, assign AcrPull, update via az containerapp update --image outside Terraform.

# Phase 1: Placeholder image
resource "azurerm_container_app" "app" {
  template {
    container {
      name   = "app"
      image  = "mcr.microsoft.com/azuredocs/containerapps-helloworld:latest"
      cpu    = 0.25
      memory = "0.5Gi"
    }
  }
  identity {
    type = "SystemAssigned"
  }
}

outputs.tf

Export: resource_group_name, app_url (https://${hostname}), resource_ids (list of all deployed resource IDs for deploy-result.json).

Security Defaults

Apply same security rules as Bicep — see bicep-patterns-security.md. Terraform-specific syntax:

RuleTerraform HCL
Managed identityidentity { type = "SystemAssigned" }
⛔ No SQL admin passwordazuread_authentication_only = true. Never generate administrator_login_password
Key Vault RBACenable_rbac_authorization = true on azurerm_key_vault
KV secret referenceapp_settings = { KEY = "@Microsoft.KeyVault(VaultName=..;SecretName=..)" }
HTTPS onlyhttps_only = true, minimum_tls_version = "1.2"
Storagehttps_traffic_only_enabled = true, allow_nested_items_to_be_public = false, min_tls_version = "TLS1_2"
⛔ Cosmos DB RBACazurerm_cosmosdb_sql_role_assignment, NOT azurerm_role_assignment — see rbac-roles.md
RBAC assignmentsprincipal_type = "ServicePrincipal" REQUIRED — see rbac-roles.md
SCM/FTP authscm.allow: true (scaffold), ftp.allow: false (always) — use azapi_resource

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an MCP server, Needs Node.js

Security

What our scanner noticed· Low risk

  • Instructions that use the network
  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

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Attribution and licence

Created by
Microsoft
Publisher
Microsoft (Official)
Source
microsoft/skills · .github/plugins/azure-skills/skills/azure-app-onboard · commit 0696600
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from .github/plugins/azure-skills/LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced
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microsoft/azure-skills

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