azure-local-multi-rack

The big-hardware edition of Azure Local — Microsoft's cloud running on four or more pre-built racks in your own data centre — from planning the install to running workloads and watching its health. It is still in preview.

WHEN TO USE

SCOPE

USE FOR

Plan a rack-scale install: one aggregation rack plus at least three racks of compute machines.
Create virtual machines, disks and Kubernetes clusters on a multi-rack Azure Local system.
Configure the managed network fabric, isolated networks, load balancers and firewall rules.
Monitor a multi-rack system and reach a machine's serial console when something goes wrong.

NOT FOR

Standard Azure Local (1-16 machines hyperconverged, up to 64 disaggregated) or rack-aware clusters; use azure-local instead.

This is a saved copy of the skill's SKILL.md instructions. It may differ from the upstream file or the version you install.

In this document (6)

Azure Local Multi-Rack

Multi-rack is in preview — say so, and confirm availability from the docs before committing to a design.

Quick Reference

Property	Value
Best for	Rack-scale Azure Local: 100+ machines, preintegrated racks, SAN, managed fabric
Scale	Minimum four racks — one aggregation rack plus three or more compute racks
Providers	`Microsoft.NetworkCloud`, `Microsoft.ManagedNetworkFabric`, `Microsoft.AzureStackHCI`
CLI	`az networkcloud`, `az networkfabric`, `az stack-hci-vm`
Related skill	`azure-local` for standard 1-16 node and rack-aware deployments

When to Use This Skill

Use when the deployment is multi-rack / rack scale: preintegrated racks, an aggregation rack, a Network Fabric Controller, a Cluster Manager, SAN storage, or the networkcloud / managednetworkfabric CLI extensions.

Do not use for standard Azure Local (1-16 node hyperconverged, up to 64 disaggregated) or rack-aware clusters — hand off to the azure-local skill. If the scale is unclear, ask first: the two have separate, non-interchangeable procedures for the same-sounding tasks (logical networks, VM creation, NSGs).

MCP Tools

No dedicated MCP namespace. Use generic Azure MCP tools: mcp_azure_mcp_extension_cli_generate (confirm networkcloud/networkfabric extensions first), mcp_azure_mcp_monitor (needs Log Analytics), mcp_azure_mcp_resourcehealth (partial; not fabric or SAN health), mcp_azure_mcp_documentation (multi-rack articles only — standard Azure Local pages do not apply).

Details: cli-and-prereqs.

Workflow

Confirm this is multi-rack, not standard Azure Local — see When to Use.
Plan/deploy -> plan-and-deploy
VMs, AKS, images, disks -> workload-management
Fabric, isolation domains, load balancers, NSGs -> networking
Monitoring, metrics, serial console, failures -> operate-and-monitor

Read the matched workflow first and use docs-map. Start read-only. Ask before fabric changes, isolation domain edits, VM power/delete operations, or anything touching the aggregation rack or SAN.

Error Handling

Scenario	Remediation
Scale unknown	Ask whether the deployment is multi-rack or standard before recommending procedures.
Standard Azure Local detected	Hand off to the `azure-local` skill; multi-rack procedures do not apply.
Missing CLI extension	Install per cli-and-prereqs before running commands.
Risky fabric or SAN change	Stop and follow safety-rules.
Doc URL 404/redirect	Search Learn for the title, scoped to multi-rack deployments of Azure Local.

This skill ships inside the Azure Skills Plugin. Listed package contents include hooks and an MCP server. Installed components and skill versions may vary by AI tool.

Run this outside your AI tool, using Node.js 22.20.0 or newer. Skills CLI 1.7.2 skips skill selection; prompts cancel installation without an interactive terminal. If choosing Project when asked about installation scope, open your project's folder before running this.

Install checklist

Check selected tools if a picker appears; Claude Code may be unchecked under Additional agents. ↑/↓ moves, Space toggles selections, Enter confirms.
Without a tool picker, check Installing to: for your intended tool. Stop if it names a different tool.
If asked, choose Symlink (Recommended) for shared files or Copy to all agents for separate copies; review the summary before confirming installation.
Install the find-skills skill? defaults to Yes, adding another skill for all projects. Choose No if you don't want that extra installation.

Skills CLI 1.7.2 sends install data to skills.sh by default, including the source, skill names, target tools and file details; GitHub sources are reported only when GitHub confirms the repository is public, while other remote sources can also be reported. Confirmed-public GitHub sources also trigger a security-audit request. Before installing, set the environment variable DO_NOT_TRACK=1 or DISABLE_TELEMETRY=1 to disable both.

npx skills add microsoft/azure-skills --skill "azure-local-multi-rack" --full-depth

After installing for Claude Code, open it in the installation project if you chose Project; Global makes the skill available across projects on this computer. Once Claude Code loads the skill, its description helps Claude decide when to use it.

If installation created a top-level skills folder that did not exist when your Claude Code session started, run /reload-skills in that session. Run it again after later changes in that folder.

View on GitHub

Same repository

airunway-aks-setup
Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".Read full description
appinsights-instrumentation
Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best practices.Read full description
azure-ai
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.Read full description
azure-aigateway
Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.Read full description
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).Read full description
azure-app-onboard-prereq
Assess whether source code is ready to deploy to Azure — the check BEFORE infrastructure work. Evaluates build health, app completeness, dependencies and local services, stack compatibility, and deployment feasibility. Answers questions about what your app needs before it can be deployed — frameworks, dependencies, and configuration. Checks whether dependencies are compatible and identifies deployment blockers and unsupported frameworks. WHEN: \"evaluate my repo\", \"is my app ready to deploy\", \"what does my app need to deploy\", \"what do I need before deploying\", \"does my app need\", \"can I ship this to Azure\", \"scan my repo for issues\", \"is this app deployable\", \"check if my app is ready for Azure\", \"do I need a Dockerfile\", \"what's blocking my deployment\", \"are there any blockers\", \"are my dependencies compatible\", \"does Azure support my framework\", \"what needs to change before deploying\", \"check my app configuration\".Read full description

Azure Local Multi-Rack

Quick Reference

When to Use This Skill

MCP Tools

Workflow

Error Handling

Account or credentials required

More skills

MCP keyword matches