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/service-mapping.md

Service Mapping Tables

Component→Azure service selection. Apply context.json.intent as modifiers, context.json.overrides[] as hard constraints, and policy constraints as filters.

Hosting

⛔ Implicit dependencies: When selecting Container Apps and the component has a Dockerfile (or hasDockerfile: true in prereq), ALWAYS include Container Registry (Basic) in services[]. Container Apps requires ACR to host custom images — omitting it forces an imperative add during deploy, wasting a healing round. ACR Basic is $0.17/day (~$5/mo).

Component Type	Primary Service	Alternatives	Selection Signal
SPA Frontend	Static Web Apps	Blob + CDN	React/Vue/Angular, no SSR
SSR Web App	Container Apps	App Service, AKS	Next.js/Nuxt, server-rendered
REST/GraphQL API	Container Apps	App Service, Functions, AKS	Express/Fastify/Flask/FastAPI
Background Worker	Container Apps (scale-to-zero)	Functions, AKS	Celery/Bull/Agenda, no HTTP
Scheduled Task	Functions (Timer)	Container Apps Jobs	Cron patterns, periodic execution
Event Processor	Functions	Container Apps + KEDA	Event-driven, queue/topic consumer
Microservices (K8s)	AKS	Container Apps	kubectl/helm in repo, CRDs, service mesh
GPU inference (managed/serverless)	Container Apps	AKS, Azure ML	A100/T4 inference without Kubernetes API, operator, or custom-scheduling requirements
GPU/ML with Kubernetes control	AKS	Container Apps, Azure ML	Kubernetes APIs, operators/CRDs, custom scheduling, or advanced networking/control

Stack shortcuts: Containers (Docker, microservices) → Container Apps or AKS. Serverless (event-driven, variable traffic) → Functions. Traditional web (PaaS preference) → App Service.

AKS vs Container Apps: Use Container Apps when scale-to-zero is needed, no K8s expertise is required, KEDA-driven event processing fits, or serverless GPU inference does not require Kubernetes control. Use AKS when the workload requires Kubernetes APIs, operators/CRDs, custom scheduling, or advanced networking/control. Delegate AKS planning to the azure-kubernetes skill. See Azure Container Apps serverless GPUs.

App Service vs Container Apps: App Service preferred when user wants free tier (F1 $0 / B1 ~$13/mo) or single-process with no container orchestration. Container Apps preferred for REST/GraphQL APIs (scaffold generates Dockerfile if missing), scale-to-zero, multi-container/sidecar, or event-driven KEDA scaling. Budget affects SKU tier (Consumption vs Dedicated), not compute service type. Container Apps Consumption has no fixed free tier but scales to zero.

Static Dockerfile sites (nginx/httpd serving HTML):

Primary: Static Web Apps Free — $0, global CDN.
⛔ SWA region availability: Validate via az provider show --namespace Microsoft.Web --query "resourceTypes[?resourceType=='staticSites'].locations" -o tsv.
Alternative: App Service F1 (Free) — ⛔ F1 does NOT run Docker. Use Windows F1 (IIS serves index.html natively) or Linux F1 (linuxFxVersion: 'STATICSITE|1.0'). ⛔ Do NOT use NODE|*/PHP|*/PYTHON|* for static sites — causes 504/503 cold start.
If Docker required: Container Apps (scale-to-zero) or App Service B1+ (custom containers).

Plain HTML (no package manager, no Dockerfile): Windows App Service F1 preferred (IIS serves natively). Linux: linuxFxVersion: 'STATICSITE|1.0'. Or Static Web Apps Free.

Data

Need	Primary Service	Alternatives	Selection Signal
Relational	Azure SQL	PostgreSQL Flexible, MySQL Flexible	SQL schema, transactions, joins
Document/NoSQL	Cosmos DB	—	JSON docs, global distribution
Graph (Gremlin)	Cosmos DB (Gremlin API)	—	Graph traversal, relationships

Cosmos DB Serverless: Each Serverless account supports ONE API type (SQL, MongoDB, Gremlin, Table, Cassandra). Multi-API apps require separate Serverless accounts.

| Cache | Redis Cache | — | Session store, rate limiting | | Files/Blobs | Blob Storage | Files Storage | File uploads, static assets | | Search | AI Search | — | Full-text search requirements | | MariaDB/MySQL | MySQL Flexible Server | — | mariadb:* or mysql:* in compose / connection config | | Elasticsearch/OpenSearch | AI Search | Azure Monitor (for Kibana) | elasticsearch:* or opensearch:* in compose | | S3-compatible / MinIO | Blob Storage | — | minio/* in compose, S3 SDK usage |

Integration

Need	Primary Service	Selection Signal
Message Queue	Service Bus	Point-to-point, ordered, transactions
Pub/Sub	Event Grid	Event routing, fan-out
Streaming / Kafka	Event Hubs	High-throughput telemetry, logs. Kafka protocol compatible — apps using `kafka-clients`, Spring Kafka, `confluent-kafka-python` connect by changing bootstrap URL + SASL config only
Multi-step orchestration	Durable Functions + Durable Task Scheduler	DTS is the recommended managed backend
Low-code workflow	Logic Apps	Integration-heavy, visual designer

docker-compose → Azure mapping: Map each detectedServices[].type to its PaaS equivalent using these tables. Unmapped services (SSH daemons, custom sidecars — no managed equivalent): offer a Linux VM (B1s ~$7/mo) as companion at the scaffold gate. Present as option, not forced. Write to postDeployRecommendations[].

Supporting (always include)

Service	Purpose
Log Analytics	Centralized logging
Application Insights	Monitoring + APM
Key Vault	Secrets management
Managed Identity	Service-to-service auth (zero secrets)

Specialized Routing

Check before mapping — delegate to specialized skill if matched:

Signal	Delegate To
Copilot SDK, `@github/copilot-sdk`	`azure-hosted-copilot-sdk`
Foundry agent, AI agent deployment	`microsoft-foundry`

⛔ Non-Azure cloud SDK deps (AWS/GCP/Firebase) are handled by prereq — the pipeline does NOT reach prepare with cloud SDK findings present. If you see cloud SDK findings here, prereq failed to stop — HALT and do NOT continue architecture planning.

Non-Azure Terraform Resource Mapping

When context.json.detectedInfraProvider.terraform is "gcp" or "aws", read existing .tf files and map cloud resources to Azure equivalents. These mappings provide architecture signal for service selection — use alongside component detection.

GCP → Azure

GCP Terraform Resource	Azure Equivalent	Notes
`google_cloud_run_v2_service`	Container Apps	Map scaling, env vars, VPC config
`google_sql_database_instance` (POSTGRES)	PostgreSQL Flexible Server	Map tier, backup, maintenance config
`google_sql_database_instance` (MYSQL)	MySQL Flexible Server	Map tier, backup config
`google_artifact_registry_repository`	Container Registry (ACR)	Basic tier unless geo-replication needed
`google_pubsub_topic` / `google_pubsub_subscription`	Service Bus	Map topic/subscription model
`google_secret_manager_secret`	Key Vault	Map secret references
`google_firestore_database`	Cosmos DB (NoSQL API)	Map indexes, TTL config
`google_cloudfunctions2_function`	Azure Functions	Map triggers, runtime
`google_service_account` + `google_project_iam_member`	Managed Identity + RBAC	Map role bindings

Other GCP resources (storage, redis, compute network, VPC connector, cloud tasks) map 1:1 to their Azure equivalents (Blob Storage, Redis Cache, VNet, Queue Storage).

AWS → Azure

AWS Terraform Resource	Azure Equivalent	Notes
`aws_ecs_service` / `aws_ecs_task_definition`	Container Apps	Map task def → container config
`aws_rds_instance` (postgres/mysql)	PostgreSQL/MySQL Flexible Server	Map instance class → SKU
`aws_lambda_function`	Azure Functions	Map runtime, handler, triggers
`aws_dynamodb_table`	Cosmos DB (NoSQL API)	Map capacity, indexes
`aws_sns_topic`	Service Bus or Event Grid	Map subscriptions
`aws_secretsmanager_secret`	Key Vault	Map secret references

Other AWS resources (S3, ECR, SQS, ElastiCache) map 1:1 to their Azure equivalents (Blob Storage, ACR, Queue Storage/Service Bus, Redis Cache). SQS → Service Bus if FIFO ordering needed.

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
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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/service-mapping.md

Service Mapping Tables

Hosting

Data

Integration

Supporting (always include)

Specialized Routing

Non-Azure Terraform Resource Mapping

GCP → Azure

AWS → Azure

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

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