/azure-architecture

name: azure-architecture
description: Expert guidance for designing Azure solutions using Azure Architecture. Covers reference architectures, solution ideas, design patterns, technology choices, architecture styles, best practices, anti-patterns, example workloads, and migration guides. Use when designing AKS, data/AI, SAP, hybrid/Arc, IoT, DR, or mission-critical workloads on Azure, and other Azure Architecture related development tasks.
compatibility: Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
metadata:
  generated_at: "2026-09-13"
  generator: "docs2skills/1.0.0"

Azure Architecture Skill

This skill provides expert guidance for designing Azure solutions using Azure Architecture. Covers reference architectures, solution ideas, design patterns, technology choices, architecture styles, best practices, anti-patterns, example workloads, and migration guides. 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 | |----------|-------|-------------| | Reference Architectures | L37-L87 | End-to-end Azure solution blueprints: production-ready patterns for networking, AKS, data/ML, SAP, hybrid/Arc, security, DR, and mission-critical app architectures. | | Solution Ideas | L88-L127 | End-to-end solution patterns for AI, data, security, IoT, and migration on Azure—how to design, integrate, and operate real-world architectures using specific Azure services. | | Design Patterns | L128-L177 | Patterns for resilient, scalable, secure app design: messaging, transactions, caching, routing, identity, legacy migration, global distribution, and fault isolation in Azure architectures. | | Technology Choices | L178-L212 | Guides for choosing Azure/Fabric services (compute, storage, data, AI/ML, analytics, networking, containers, messaging, search) and matching them to specific workload and architecture needs. | | Architecture Styles | L213-L224 | Guidance on choosing and designing Azure app architectures (big compute, big data, event-driven, microservices, N-tier, web-queue-worker) with patterns, components, and best practices. | | Best Practices | L225-L281 | Best-practice patterns for Azure solutions: secure APIs/RAG/ML, AKS ops, networking/DNS, DR, multitenancy, caching/CDN, autoscaling, monitoring, CI/CD, and large-scale event/IoT workloads. | | Anti-patterns | L282-L296 | Diagnosing and fixing common Azure performance and scalability anti-patterns (busy DB/front end, chatty I/O, no caching, noisy neighbors, retry storms, sync I/O, monolithic persistence). | | Example Workloads | L297-L384 | End-to-end reference architectures and patterns for real-world Azure workloads: data/AI, AKS, networking, security, hybrid, mainframe, SAP, IoT/OPC UA, NetApp, Fabric, and app modernization. | | Migration Guides | L385-L414 | Guides for mapping AWS/GCP/Oracle/Kafka to Azure, comparing services (compute, storage, networking, identity, Kubernetes), and planning/migrating workloads and security to Azure. |

Reference Architectures

| Topic | URL | |-------|-----| | Automate video analysis with Azure ML and Vision | https://learn.microsoft.com/en-us/azure/architecture/ai-ml/architecture/analyze-video-computer-vision-machine-learning | | Deploy baseline enterprise chat with Microsoft Foundry | https://learn.microsoft.com/en-us/azure/architecture/ai-ml/architecture/baseline-microsoft-foundry-chat | | Implement baseline Foundry chat in an Azure landing zone | https://learn.microsoft.com/en-us/azure/architecture/ai-ml/architecture/baseline-microsoft-foundry-landing-zone | | Deploy MLOps v2 CI/CD and retraining architectures | https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/machine-learning-operations-v2 | | Implement DR-ready Azure enterprise data platform architecture | https://learn.microsoft.com/en-us/azure/architecture/data-guide/disaster-recovery/dr-for-azure-data-platform-architecture | | Enterprise-hardened Azure Data Factory lakehouse architecture | https://learn.microsoft.com/en-us/azure/architecture/databases/architecture/azure-data-factory-enterprise-hardened | | Mission-critical Azure Data Factory analytics architecture | https://learn.microsoft.com/en-us/azure/architecture/databases/architecture/azure-data-factory-mission-critical | | Implement Azure Data Factory medallion lakehouse baseline | https://learn.microsoft.com/en-us/azure/architecture/databases/architecture/azure-data-factory-on-azure-landing-zones-baseline | | Deploy MongoDB Atlas securely on Azure | https://learn.microsoft.com/en-us/azure/architecture/databases/architecture/mongodb-atlas-baseline | | Move archive data from mainframes to Azure storage | https://learn.microsoft.com/en-us/azure/architecture/example-scenario/mainframe/move-archive-data-mainframes | | Deploy a hub-spoke AKS cluster with Azure Firewall | https://learn.microsoft.com/en-us/azure/architecture/guide/aks/aks-firewall | | Architect mission-critical global content delive