/azure-expert

name: azure-expert
description: Azure expert guardrails — Entra ID least-privilege, policy-first governance, data boundaries, cost, residency, and official-source validation. Trigger when designing or reviewing any Azure workload, especially agents, LLMs (Foundry/OpenAI), or landing-zone systems.

Azure Expert

> **Azure is policy-first: Entra ID and Azure Policy are the guardrails; the Foundry is the agent surface. If it is not enforced by policy, it is a wish.**

This skill enforces the discipline that makes Azure workloads production-safe: identity, policy, data boundaries, cost controls, and residency. It is not an Azure feature tour — it is a checklist of the things that cause incidents and compliance failures when skipped.

When to use

• Designing any Azure infrastructure (new or modified)
• Before deploying agents or LLM workloads to Azure (AI Foundry, Azure OpenAI, Azure AI Agent Service)
• When reviewing a Bicep/Terraform plan or a landing-zone design
• When a system spans subscriptions, touches regulated data, or crosses geographies

Procedure

1. **Identity and access** — verify least-privilege for every identity:

• Managed identities over service principals with secrets; no client secrets in code or config.
• Entra ID RBAC scoped to the specific function; PIM for standing privileged access.
• Conditional Access policies for human principals on production subscriptions.

2. **Policy and landing zones** — confirm governance is mechanical:

• Azure Policy assignments enforce allowed locations, required encryption, and denied public endpoints.
• Workload sits inside a Cloud Adoption Framework landing zone (or an explicit, owned deviation).

3. **Data boundaries** — for every data store:

• Classification recorded (Purview where in scope); CMK where required.
• Private Endpoints on PaaS data services; public network access disabled by default.
• Cross-tenant or cross-subscription sharing explicit and documented.

4. **Data residency** — for each resource:

• Allowed-locations policy constrains deployment geography (e.g. EU Data Boundary where required).
• For Azure OpenAI / Foundry calls: regional deployments, not global, where residency matters.

5. **Cost controls** — for every LLM, compute, or storage resource:

• Cost Management budgets with alerts at 50%, 75%, 90%, 100%.
• Foundry model quotas and rate limits set; autoscale maximums bounded.

6. **Network and egress** — confirm:

• Private Link over public endpoints; NSGs default-deny.
• Egress costed for cross-region and internet-bound traffic.

7. **Observability** — confirm:

• Azure Monitor / Log Analytics dashboards and alerts on error rate, latency, and cost.
• Activity logs routed centrally for retention and audit — evidence before go-live.

8. **Run the Adversarial Gate** — common Azure failure modes: service principals with secrets, public PaaS endpoints, missing allowed-locations policy, uncapped Foundry spend, standing owner access without PIM.

Official sources — validate before you assert

• Documentation: `learn.microsoft.com/azure` · Well-Architected: `learn.microsoft.com/azure/well-architected`
• Live docs via MCP (verify currency before pinning): the official **Azure MCP Server** (`github.com/microsoft/azure-mcp`) and the Microsoft Learn docs MCP endpoint — fetch current docs instead of relying on memory.
• GitHub, foundations: `github.com/Azure/Enterprise-Scale` (CAF landing zones) · `github.com/Azure/bicep` · `github.com/Azure-Samples`
• GitHub, agent examples: **Azure AI Agent Service** samples under `github.com/Azure-Samples` · AutoGen (`github.com/microsoft/autogen`) · Semantic Kernel (`github.com/microsoft/semantic-kernel`)
• Rule: every service/API claim cites an official doc. Quotas, prices, and model names are dated facts — stale until re-verified against the source.

Outputs

• Azure guardrail checklist (pass/fail per item)
• Identity matrix: principal | role | scope | justification
• Data classification and boundary map
• Budget alert confirmation
• Open findings for human review

Guardrails

• **No client secrets in code or config.** Managed identity or nothing.
• **Policy, not promises.** If a guardrail is not an Azure Policy assignment, it does not exist.
• **Residency is a constraint, not a preference.** Enforce with allowed-locations policy.
• **Budget alerts are not optional.** An unmonitored LLM workload will produce a surprise invoice.