name: azure-architecture-patterns
description: Well-Architected Framework principles and Azure best practices
tier: standard
applyTo: '/azure,/cloud,/waf,/architecture'
Azure Architecture Patterns
Well-Architected Framework principles, reference architectures, and Azure best practices.
The Five Pillars
| Pillar |
Focus |
Key Question |
| Reliability |
Resiliency, availability |
Will it stay up? |
| Security |
Protection, compliance |
Is it safe? |
| Cost Optimization |
Efficiency, value |
Is it worth it? |
| Operational Excellence |
Manageability, observability |
Can we run it? |
| Performance Efficiency |
Scalability, responsiveness |
Is it fast enough? |
Reliability Patterns
Key Patterns
- Circuit Breaker: Fail fast when downstream unhealthy (Polly)
- Retry with Backoff: Handle transient failures with exponential delays
- Availability Zones: Distribute across datacenters
Reliability Checklist
Security Patterns
Zero Trust
| Principle |
Implementation |
| Verify explicitly |
Always authenticate/authorize |
| Least privilege |
Minimal necessary permissions |
| Assume breach |
Segment, encrypt, detect |
Identity
- Managed Identity: Eliminate credential management
- RBAC: Built-in roles, scope to resource group, use groups
Network
- Private Endpoints: Keep traffic on Azure backbone
- NSG: Default deny, explicit allow (priority 100-4096)
Security Checklist
Cost Optimization
| Strategy |
Impact |
| Right-size |
Match SKU to workload |
| Reserved Instances |
40-72% savings |
| Spot VMs |
90% discount (interruptible) |
| Auto-shutdown |
Dev/test off at night |
| Serverless |
Pay per execution |
Compute Selection
| Workload |
Recommended |
| Steady-state web |
App Service Premium |
| Event-driven |
Azure Functions |
| Batch processing |
Container Apps + KEDA |
| Big compute |
Spot VMs + Batch |
| Dev/test |
B-series VMs |
Storage Tiers
| Tier |
Use Case |
Cost |
| Hot |
Frequent access |
~$0.02/GB |
| Cool |
Infrequent (30+ days) |
~$0.01/GB |
| Archive |
Rarely accessed |
~$0.002/GB |
Cost Checklist
Operational Excellence
IaC Tools
| Tool |
Best For |
| Bicep |
Azure-native, declarative |
| Terraform |
Multi-cloud, state management |
| ARM |
Legacy (avoid for new) |
Observability Stack
| Layer |
Service |
| Logs |
Log Analytics |
| Metrics |
Azure Monitor |
| Traces |
Application Insights |
| Alerts |
Azure Alerts |
| Dashboards |
Azure Workbooks |
Operational Checklist
Performance Efficiency
Scalability
| Service |
Mechanism |
| App Service |
Autoscale rules |
| Azure Functions |
Event-driven automatic |
| AKS |
HPA + Cluster Autoscaler |
| VMSS |
Autoscale rules |
Caching Strategy
| Type |
Use Case |
Service |
| CDN |
Static content |
Azure Front Door |
| Distributed |
Session, computed |
Redis Cache |
| Local |
Hot data |
In-memory |
Performance Checklist
Reference Architectures
Web Application
Internet → Front Door → App Service → Azure SQL + Redis
Microservices
Internet → API Management → AKS → Cosmos DB + Service Bus
Serverless
Events → Event Grid → Functions → Cosmos DB + Storage
SKU Selection
| Series |
Use Case |
| B-series |
Dev/test (burstable) |
| D-series |
Most production |
| E-series |
Memory-optimized |
| F-series |
Compute-optimized |
Anti-Patterns
| Anti-Pattern |
Fix |
| Monolithic deployment |
Microservices or modular |
| Hardcoded config |
App Configuration, Key Vault |
| Single region |
Multi-region + Traffic Manager |
| Over-provisioned |
Right-size + autoscale |
| No IaC |
Bicep/Terraform everything |
MCP Tools Available
| Tool |
Use Case |
mcp_azure_mcp_cloudarchitect |
Interactive architecture design |
mcp_azure_mcp_documentation |
Search Azure docs |
mcp_azure_mcp_get_bestpractices |
Code gen, deployment patterns |
| Service-specific tools |
AKS, App Service, Functions, Cosmos, SQL |
By