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

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/microsoft/azure-app-onboard/download

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

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.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.

#	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)

Files

ATTRIBUTION.mdAdded by AutoGineer983 B
LICENSELicence file added by AutoGineer1.1 KiB
SKILL.md6.6 KiB
deploy/PHASE.md7.5 KiB
deploy/references/approval-gate-template.md2.9 KiB
deploy/references/blocked-patterns.md5.7 KiB
deploy/references/code-deployment-appservice.md4.6 KiB
deploy/references/code-deployment-container-apps.md8.4 KiB
deploy/references/code-deployment-swa.md5.7 KiB
deploy/references/database-post-deploy.md4.5 KiB
deploy/references/deploy-checklist-template.md10.1 KiB
deploy/references/deploy-safety.md4.5 KiB
deploy/references/deploy-schemas.tsScript3.5 KiB
deploy/references/error-classification.md3.6 KiB
deploy/references/health-check-patterns.md5.5 KiB
deploy/references/mcp-tools.md5.5 KiB
deploy/references/portal-links.md3.1 KiB
deploy/references/preflight-checks.md4.4 KiB
deploy/references/subagent-preflight.md5.1 KiB
prepare/PHASE.md6.4 KiB
prepare/references/deploy-strategy.md6.8 KiB
prepare/references/mcp-tools.md5.6 KiB
prepare/references/naming-patterns.md4.6 KiB
prepare/references/prepare-schemas.tsScript7.0 KiB
prepare/references/pricing-guide-services.md8.4 KiB
prepare/references/pricing-guide.md4.0 KiB
prepare/references/service-mapping.md8.5 KiB
prepare/references/sku-matrix.md3.2 KiB
prepare/references/sku-quota-validation.md9.0 KiB
prepare/references/subagent-pricing.md2.5 KiB
prepare/references/subagent-quota.md3.5 KiB
prepare/references/validation-rubric.md2.3 KiB
references/approval-gates.md8.4 KiB
references/azd-template-routing.md4.7 KiB
references/handoff-protocol.md7.8 KiB
references/iac-resources.md2.6 KiB
references/intent-gathering.md2.2 KiB
references/mcp-tool-reference.md3.7 KiB
references/pipeline-rules-runtime.md3.5 KiB
references/pipeline-rules.md6.3 KiB
references/session-protocol.md8.0 KiB
references/session-schemas.tsScript5.2 KiB
references/subscription-resolution.md2.1 KiB
scaffold/PHASE.md14.2 KiB
scaffold/references/bicep-app-service.md5.4 KiB
scaffold/references/bicep-container-apps.md9.3 KiB
scaffold/references/bicep-patterns-data.md4.0 KiB
scaffold/references/bicep-patterns-security.md7.8 KiB
scaffold/references/bicep-patterns.md6.8 KiB
scaffold/references/bicep-swa.md757 B
scaffold/references/cicd-pipelines.md325 B
scaffold/references/dockerfile-generation.md4.1 KiB
scaffold/references/env-var-secrets.md4.1 KiB
scaffold/references/error-handling.md1.5 KiB
scaffold/references/iac-generation-rules.md6.6 KiB
scaffold/references/mcp-tools.md7.0 KiB
scaffold/references/rbac-roles.md3.8 KiB
scaffold/references/scaffold-healing-rules.md3.3 KiB
scaffold/references/scaffold-schemas.tsScript3.5 KiB
scaffold/references/self-healing.md2.3 KiB
scaffold/references/self-review-checklist.md9.0 KiB
scaffold/references/self-review-procedure.md2.3 KiB
scaffold/references/subagent-iac-gen.md9.5 KiB
scaffold/references/subagent-review.md3.5 KiB
scaffold/references/subagent-validate.md7.2 KiB
scaffold/references/terraform-patterns.md6.9 KiB
scaffold/references/validation-and-manifest.md5.1 KiB
scaffold/references/waf-checklist.md2.3 KiB
scaffold/scripts/scaffold-conformance.ps1Script12.8 KiB
scaffold/scripts/scaffold-conformance.shScript13.8 KiB

prepare/references/pricing-guide-services.md

App Onboard Prepare — Per-Service Pricing Patterns

Filter strings, meter names, and formulas per Azure service. For methodology and troubleshooting, see pricing-guide.md.

Container Apps

No armSkuName. Filter: serviceName eq 'Azure Container Apps' and armRegionName eq '{region}' and priceType eq 'Consumption' and isPrimaryMeterRegion eq true

Key meters: Standard vCPU Active Usage (1 Second), Standard Memory Active Usage (1 GiB Second), Standard Requests (1M).

Monthly (Consumption, 1 vCPU, 2 GiB, 8h active/day): (vCPU_active_rate × 3600 × 8 × 30) + (memory_active_rate × 2 × 3600 × 8 × 30)

Free grant: 180K vCPU-sec + 360K GiB-sec + 2M requests/sub/month. Scale-to-zero = $0 idle. When min_replicas >= 1: add idle cost from idle meters.

Container Registry (ACR)

Empty armSkuName — ⛔ do NOT filter by sku (returns []). Filter: serviceName eq 'Container Registry' and armRegionName eq '{region}' and priceType eq 'Consumption', then match meterName.

Tier	`meterName`	`unitOfMeasure`	Monthly
Basic	`Basic Registry Unit`	`1/Day`	`retailPrice × 30` (~$5)
Standard	`Standard Registry Unit`	`1/Day`	`retailPrice × 30` (~$20)
Premium	`Premium Registry Unit`	`1/Day`	`retailPrice × 30` (~$50)

⛔ 1/Day → × 30, NOT × 730. The other ACR meters (Task vCPU Duration = 1 Second build compute, Data Stored = 1 GB/Month) are usage-based — exclude from the fixed monthly unless the app builds heavily. ACR Basic fixed cost ≈ $5/mo.

App Service

MCP call: pricing_get --service "Azure App Service" --region "{region}"

Meter-to-SKU mapping:

SKU	`meterName`	Notes
F1	`F1 App`	Free ($0 price)
B1	`B1`
B2	`B2`
S1	`S1 App`
P1v3	`P1 v3 App`	Linux/Windows have different `productName`

Gotcha: armSkuName empty for Basic/Standard. Match on meterName.

Monthly: retailPrice × 730

Azure SQL Database

DTU model — no armSkuName. Filter by productName + meterName.

SKU	`productName` contains	`meterName` (unit: 1/Day)
Basic (5 DTU)	`SQL Database Single Basic`	`B DTU`
S0 (10 DTU)	`SQL Database Single Standard`	`S0 DTUs`
S1 (20 DTU)	`SQL Database Single Standard`	`S1 DTUs`

Monthly (DTU): retailPrice × 30

vCore model: productName filters — Serverless: 'SQL Database General Purpose - Serverless - Compute Gen5'. Hyperscale: 'SQL Database Single/Elastic Pool Hyperscale'. Monthly: retailPrice × 730.

Cosmos DB

Filter: serviceName eq 'Azure Cosmos DB' and armRegionName eq '{region}' and priceType eq 'Consumption' and isPrimaryMeterRegion eq true

Model	Match on	Monthly formula
Provisioned	`meterName eq '100 RU/s'`, `productName eq 'Azure Cosmos DB'`	`(targetRU / 100) × retailPrice × 730`
Autoscale	`productName eq 'Azure Cosmos DB autoscale'`, `meterName` starts with `AP`	varies
Serverless	`productName eq 'Azure Cosmos DB serverless'`, `meterName eq '1M RUs'`	`retailPrice × estimatedMillionsOfRU`

⚠️ Provisioned 100 RU/s gotcha: The isPrimaryMeterRegion eq true entry has retailPrice: 0 (free-tier placeholder). The real price (~$0.008/hr in eastus) has isPrimaryMeterRegion: false. Drop isPrimaryMeterRegion from the filter or match on retailPrice > 0.

Storage: meterName eq 'Data Stored' with productName eq 'Azure Cosmos DB' (1 GB/Month). Note: this meter has isPrimaryMeterRegion: false — drop that filter or query without it.

Free tier: 1,000 RU/s + 25 GB per account (one per subscription).

Storage

No armSkuName. Filter by meterName + productName.

Filter (Hot LRS Blob):

serviceName eq 'Storage' and armRegionName eq '{region}' and meterName eq 'Hot LRS Data Stored' and productName eq 'Blob Storage'

Meter-to-SKU mapping:

SKU matrix tier	`meterName`	`productName`
Standard_LRS	`Hot LRS Data Stored`	`Blob Storage` or `General Block Blob v2`
Standard_GRS	`Hot GRS Data Stored`	`Blob Storage` or `General Block Blob v2`
Premium_LRS	`Premium LRS Data Stored`	`Premium Block Blob`

Monthly: retailPrice × estimatedGB

Key Vault

Filter:

serviceName eq 'Key Vault' and armRegionName eq '{region}' and priceType eq 'Consumption'

Key meters:

Tier	`meterName`	Unit
Standard	`Operations`	10K

Monthly (Standard): retailPrice × (estimatedOps / 10000). Negligible for typical AppOnboard apps.

Service Bus

Filter:

serviceName eq 'Service Bus' and armRegionName eq '{region}'

⚠️ Do NOT add isPrimaryMeterRegion eq true — all Service Bus meters have isPrimaryMeterRegion: false. Adding that filter returns zero useful results.

Key meters:

Tier	`meterName`	Unit	Notes
Basic	`Basic Messaging Operations`	1M	Usage-based only
Standard	`Standard Base Unit`	1/Hour	Base cost (always-on)
Standard	`Standard Messaging Operations`	1M	Tiered: first 13M free
Premium	`Premium Messaging Unit`	1/Hour	Per messaging unit

Monthly (Standard): baseUnitRate × 730 + operations beyond free tier. Standard tiered: first 13M free.

Gotcha: Standard Base Unit has two entries — hourly and monthly. Use hourly × 730.

Redis Cache

armSkuName IS populated — pricing_get --sku works.

MCP call: pricing_get --service "Redis Cache" --sku "{armSkuName}" --region "{region}"

armSkuName pattern: Azure_Redis_Cache_{Tier}_{Size}_Cache (e.g., Azure_Redis_Cache_Basic_C0_Cache, Azure_Redis_Cache_Standard_C1_Cache). Query the MCP tool for exact pricing.

Gotcha: Basic tier entries have isPrimaryMeterRegion: false. The standard filter strips them out. Query by armSkuName directly or omit isPrimaryMeterRegion and match on productName eq 'Azure Redis Cache Basic'.

Monthly: retailPrice × 730

Azure Database for PostgreSQL Flexible Server

armSkuName IS populated — pricing_get --sku works. ⛔ skuName is CASE-SENSITIVE: B1MS works, B1ms returns 0 results.

MCP call: pricing_get --service "Azure Database for PostgreSQL" --sku "{armSkuName}" --region "{region}"

armSkuName values: ⛔ Case-sensitive. Small Burstable uses short names (B1MS, B2S); larger Burstable + GP/MO use Standard_ prefix.

SKU	`armSkuName`
Burstable B1ms	`B1MS`
Burstable B2s	`B2S`
Burstable B2ms	`Standard_B2ms`
General Purpose D2ds_v5	`Standard_D2ds_v5`

Storage: Query separately — meterName eq 'Storage Data Stored' and productName containing Flexible Server Storage. Unit: 1 GiB/Month. Default 32 GiB included at ~$0.115/GiB/mo.

Monthly (compute): retailPrice × 730 Monthly (storage): storageRate × storageSizeGB Total: compute + storage (e.g., B1ms + 32 GiB ≈ $12.41 + $3.68 = ~$16.09)

Functions

Consumption plan: Not in API. Free: 1M executions + 400K GB-seconds/month.

Flex/Premium — filter: serviceName eq 'Functions' and armRegionName eq '{region}' and priceType eq 'Consumption' and isPrimaryMeterRegion eq true

Flex: On Demand Execution Time (1 GB Second), On Demand Total Executions (10), Always Ready Baseline
Premium: Premium vCPU Duration (1 Hour), Premium Memory Duration (1 GiB Hour). Monthly: vCPU_rate × 730 + memory_rate × GiB × 730

Static Web Apps

Not in the Retail Prices API. Fixed pricing — query azure.microsoft.com/pricing/details/app-service/static:

Free tier: 100 GB bandwidth, 2 custom domains
Standard tier: Flat monthly per app, unlimited bandwidth, 5 custom domains

Log Analytics / Application Insights

Filter:

serviceName eq 'Azure Monitor' and armRegionName eq '{region}' and priceType eq 'Consumption' and isPrimaryMeterRegion eq true

Key meters:

Platform Logs Data Processed (unit: 1 GB)
Log Analytics ingestion — match meterName containing Data Ingestion

Free grant: First 5 GB/month of Log Analytics data ingestion.

Monthly: retailPrice × estimatedGB (subtract 5 GB free grant).

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

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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

2026-11-08

Also distributed in

microsoft/azure-skills

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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-app-onboard.zip

From the author

AutoGineer summary

What it does

When to use it

Advantages

Usage examples

Install

Documentation by Microsoft

Azure App Onboard

Quick Reference

When to Use This Skill

When NOT to Use

Pipeline Rules

Workflow

Error Handling

Files

prepare/references/pricing-guide-services.md

App Onboard Prepare — Per-Service Pricing Patterns

Container Apps

Container Registry (ACR)

App Service

Azure SQL Database

Cosmos DB

Storage

Key Vault

Service Bus

Redis Cache

Azure Database for PostgreSQL Flexible Server

Functions

Static Web Apps

Log Analytics / Application Insights

Requirements and compatibility

Security

Attribution and licence

Related skills

Shipping And Launch

Quantized Export

Deployment Pipeline Design

Gitops Workflow

Spark Environment Setup

Cloud Infrastructure Deployment Engineer

Download ZIP