azure-well-architected

Este extracto es una copia guardada durante la revisión. La fuente externa contiene la versión completa y actual.

---
name: azure-well-architected
description: Expert guidance for designing, assessing, and optimizing Azure workloads using Azure Well Architected. Covers design review checklists, recommendations, design principles, tradeoffs, service guides, workload patterns, and assessment questions. Use when designing AI, HPC, SaaS, AVD, AVS, or mission-critical workloads on Azure, and other Azure Well Architected related development tasks.
compatibility: Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
metadata:
  generated_at: "2026-08-09"
  generator: "docs2skills/1.0.0"
---
# Azure Well Architected Skill

This skill provides expert guidance for designing, assessing, and optimizing Azure workloads using Azure Well Architected. Covers design review checklists, recommendations, design principles, tradeoffs, service guides, workload patterns, and assessment questions. It combines local quick-reference content with remote documentation fetching capabilities.

## How to Use This Skill

> **IMPORTANT for Agent**: Use the **Category Index** below to locate relevant sections. For categories with line ranges (e.g., `L35-L120`), use `read_file` with the specified lines. For categories with file links (e.g., `[security.md](security.md)`), use `read_file` on the linked reference file

> **IMPORTANT for Agent**: If `metadata.generated_at` is more than 3 months old, suggest the user pull the latest version from the repository. If `mcp_microsoftdocs` tools are not available, suggest the user install it: [Installation Guide](https://github.com/MicrosoftDocs/mcp/blob/main/README.md)

This skill requires **network access** to fetch documentation content:
- **Preferred**: Use `mcp_microsoftdocs:microsoft_docs_fetch` with query string `from=learn-agent-skill`. Returns Markdown.
- **Fallback**: Use `fetch_webpage` with query string `from=learn-agent-skill&accept=text/markdown`. Returns Markdown.

## Category Index

| Category | Lines | Description |
|----------|-------|-------------|
| Design Review Checklists | L35-L43 | Checklists to review Azure workloads for cost, operations, performance, reliability, and security best practices and identify gaps against Well-Architected guidance. |
| Recommendations | L44-L117 | Guidance on cost optimization, reliability, performance, security, and operational excellence in Azure workloads, including CI/CD, monitoring, incident management, and sustainable cloud practices. |
| Design Principles | L118-L132 | Design patterns and best practices for cost, reliability, security, performance, operations, sustainability, and mission-critical design across AI, SaaS, AVD, HPC, and other Azure workloads. |
| Tradeoffs | L133-L142 | Guidance on weighing cost, reliability, performance, security, and operations tradeoffs in Azure architectures, including regions/AZ choices and cross-pillar design decisions. |
| Service Guides | L143-L178 | End-to-end Well-Architected (WAF) guidance for specific Azure services—covering design, networking, security/IAM, monitoring, BCDR, performance, and cost optimization patterns. |
| Workload Patterns | L179-L223 | Design patterns, reference architectures, and end-to-end guidance for AI, HPC, mission-critical, SaaS, and sustainable workloads on Azure, including platforms, data, ops, security, and governance. |
| Assessment Questions | L224-L235 | Guided assessments and maturity models to evaluate AI, SaaS, AVD, AVS, and other Azure workloads against WAF pillars: cost, reliability, security, performance, and operations. |

### Design Review Checklists
| Topic | URL |
|-------|-----|
| Use Cost Optimization design review checklist for Azure | https://learn.microsoft.com/en-us/azure/well-architected/cost-optimization/checklist |
| Use operational excellence design review checklist | https://learn.microsoft.com/en-us/azure/well-architected/operational-excellence/checklist |
| Use performance efficiency design review checklist | https://l