azure-enterprise-infra-planner
Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.
- Installs
- 440.9K
- Last 24h
- +1.4K
- Trending rank
- #198
- Security
- Warn
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/microsoft/azure-skills --skill azure-enterprise-infra-planner- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads azure-enterprise-infra-planner automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
Security audits
Independent scans of the skill's instructions and bundled files.
SKILL.md
The instructions your agent reads when the skill is triggered.
Azure Enterprise Infra Planner
When to Use This Skill
Activate this skill when user wants to:
- Plan enterprise Azure infrastructure from a workload or architecture description
- Architect a landing zone, hub-spoke network, or multi-region topology
- Design networking infrastructure: VNets, subnets, firewalls, private endpoints, VPN gateways
- Plan identity, RBAC, and compliance-driven infrastructure
- Generate Bicep or Terraform for subscription-scope or multi-resource-group deployments
- Plan disaster recovery, failover, or cross-region high-availability topologies
Quick Reference
| Property | Details |
|---|---|
| MCP tools | insights_get, get_azure_bestpractices_get, wellarchitectedframework_serviceguide_get, microsoft_docs_fetch, microsoft_docs_search, bicepschema_get |
| CLI commands | az deployment group create, az bicep build, az resource list, terraform init, terraform plan, terraform validate, terraform apply, checkov |
| Output schema | schema.md |
| Key references | workflow.md, waf-checklist.md, resources/, constraints/ |
Workflow (Start Here)
Follow the step-by-step instructions in workflow.md to execute the 7 phases of infrastructure planning and provisioning.
Architecture
The skill runs a 7-phase, gated pipeline. Input is triaged into one of two flows:
- Greenfield — only new requirements; run the phases straight through.
- Referenced (brownfield) — the user supplies something that already exists (a live resource / resource group / subscription, IaC or an infra plan, or a requirements doc). The same phases run, plus referenced-workload.md: existing resources are inventoried and referenced (never recreated), the new workload is wired into them, and Phase 7 deploys additively (incremental only — never modifying or destroying the referenced resources).
Every phase advances only after its gate passes. Phase 5 requires explicit user approval; Phase 6 is a
hardened, self-verifying gate — the generated IaC must be secure-by-default, pass local validation
(az bicep build / terraform validate) with zero errors, pass a checkov security scan with no
unresolved high/critical findings, and the skill must show the command output and emit a completion
self-check before advancing; Phase 7 requires an explicit, risk-acknowledged deploy confirmation.
flowchart TD
IN([Input]) --> TRIAGE{Existing infra<br/>referenced?}
TRIAGE -- "No (greenfield)" --> P1
TRIAGE -- "Yes (referenced)" --> RW[/referenced-workload.md:<br/>inventory + assign roles<br/>reference, never recreate/]
RW --> P1
subgraph PIPE [7-phase gated pipeline]
direction TB
P1[Phase 1 · Extract insights] --> P2[Phase 2 · Research best practices]
P2 --> P3[Phase 3 · Research resources]
P3 --> P4[Phase 4 · Generate plan]
P4 --> P5{Phase 5 · Verify<br/>user approves?}
P5 -- "no" --> P4
P5 -- "approved" --> P6[Phase 6 · Generate IaC]
P6 --> VAL{Validate<br/>az bicep build /<br/>terraform validate}
VAL -- "errors" --> P6
VAL -- "clean" --> P7{Phase 7 · Deploy<br/>risk-ack confirm?}
end
P7 -- "greenfield" --> DEP[az deployment / terraform apply]
P7 -- "referenced" --> DEPADD[Additive deploy · incremental only<br/>what-if preview · no destroy of<br/>referenced resources]
DEP --> OUT([Deployed])
DEPADD --> OUT
classDef gate fill:#fff3cd,stroke:#d39e00,color:#000;
classDef ref fill:#e2f0d9,stroke:#548235,color:#000;
class P5,VAL,P7,TRIAGE gate;
class RW,DEPADD ref;
Artifacts (written under <project-root>/): .azure/insights.json (Phase 1),
.azure/infrastructure-plan.json (Phase 4, status draft→approved→deployed), and
infra/main.bicep + infra/modules/* or infra/main.tf + infra/modules/** (Phase 6).
MCP Tools
| Tool | Purpose |
|---|---|
insights_get | Retrieve insights about the user's existing Azure environment to guide planning decisions |
get_azure_bestpractices_get | Azure best practices for code generation, operations, and deployment |
wellarchitectedframework_serviceguide_get | WAF service guide for a specific Azure service |
microsoft_docs_search | Search Microsoft Learn for relevant documentation chunks |
microsoft_docs_fetch | Fetch full content of a Microsoft Learn page by URL |
bicepschema_get | Bicep schema definition for any Azure resource type (latest API version) |
Error Handling
| Error | Cause | Fix |
|---|---|---|
| MCP tool error or not available | Tool call timeout, connection error, or tool doesn't exist | Retry once; fall back to reference files and notify user if unresolved |
| Plan approval missing | meta.status is not approved | Stop and prompt user for approval before IaC generation or deployment |
| IaC validation failure | az bicep build or terraform validate returns errors | Fix the generated code and re-validate; notify user if unresolved |
| Pairing constraint violation | Incompatible SKU or resource combination | Fix in plan before proceeding to IaC generation |
| Infra plan or IaC files not found | Files written to wrong location or not created | Verify files exist at <project-root>/.azure/ and <project-root>/infra/; if missing, re-create the files by following workflow.md exactly |
FAQ
What does the azure-enterprise-infra-planner skill do?
Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.
How do I install azure-enterprise-infra-planner?
Run npx skills add https://github.com/microsoft/azure-skills --skill azure-enterprise-infra-planner in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/azure-enterprise-infra-planner/ (personal) or .claude/skills/azure-enterprise-infra-planner/ (project).
Which AI agents can use azure-enterprise-infra-planner?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is azure-enterprise-infra-planner safe to install?
Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk flagged items to review; ZeroLeaks passed. As with any skill, read the SKILL.md and bundled scripts before installing.
Who maintains azure-enterprise-infra-planner?
It is published by microsoft in microsoft/azure-skills, and it is an official skill from the maker of the technology it covers. It has 440,854 recorded installs.
More from microsoft/azure-skills
microsoft-foundry
microsoft/azure-skills
Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, managed harness agent create, GitHub Copilot harness agent, create agent, update agent, add tool to agent, invoke agent, agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure
azure-diagnostics
microsoft/azure-skills
Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead letter.
azure-prepare
microsoft/azure-skills
Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.
azure-ai
microsoft/azure-skills
Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
azure-deploy
microsoft/azure-skills
Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.
azure-validate
microsoft/azure-skills
Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.
Popular devops & cloud skills
wizard
mattpocock/skills
Generate an interactive bash wizard that walks a human through steps only they can perform. Use when provisioning infrastructure, setting up credentials or CI secrets, walking an unfamiliar third-party dashboard, or running a one-off migration or cutover. Don't invoke this for steps the agent can perform itself.
google-agents-cli-deploy
google/agents-cli
This skill should be used when the user wants to "deploy an agent", "deploy my ADK agent", "set up CI/CD", "configure secrets", "troubleshoot a deployment", or needs guidance on Agent Runtime, Cloud Run, or GKE deployment targets, or binding an agent to an Agent Gateway. Covers deployment workflows, service accounts, rollback, and production infrastructure. Applies to any framework agents-cli deploys (ADK, LangChain, ...). Part of the agents-cli skills suite. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), evaluation (use google-agents-cli-eval), or project scaffolding (use google-agents-cli-scaffold).
google-agents-cli-scaffold
google/agents-cli
This skill should be used when the user wants to "create an agent project", "start a new ADK project", "build me a new agent", "add CI/CD to my project", "add deployment", "enhance my project", or "upgrade my project". Part of the agents-cli skills suite. Covers agents-cli scaffold create, scaffold enhance, and scaffold upgrade commands, template options, deployment targets, and the prototype-first workflow. Do NOT use for writing agent code (ADK projects: use google-agents-cli-adk-code) or deployment operations (use google-agents-cli-deploy).
google-agents-cli-observability
google/agents-cli
This skill should be used when the user wants to "set up tracing", "monitor my agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring deployed agents, including ADK (Agent Development Kit) agents. Covers Cloud Trace, prompt-response logging, BigQuery Agent Analytics, third-party integrations (AgentOps, Phoenix, MLflow, etc.), and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment setup (use google-agents-cli-deploy) or API code patterns (use google-agents-cli-adk-code).
vercel-composition-patterns
vercel-labs/agent-skills
React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.
sentry-cli
sentry/dev
Guide for using the Sentry CLI to interact with Sentry from the command line. Use when the user asks about viewing issues, events, projects, organizations, making API calls, or authenticating with Sentry via CLI.