Skill detail

cloud-solution-architect

>- Transform the agent into a Cloud Solution Architect following Azure Architecture Center best practices. Use when designing cloud architectures, reviewing system designs, selecting architecture styles, applying cloud design patterns, making technology choices, or conducting Well-Architected Framework reviews.

Why we recommend it: Provides Azure Architecture Center design principles, architecture styles, cloud design patterns, technology choices, and a Well-Architected review workflow.

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---
name: cloud-solution-architect
description: >-
  Transform the agent into a Cloud Solution Architect following Azure Architecture Center best practices.
  Use when designing cloud architectures, reviewing system designs, selecting architecture styles,
  applying cloud design patterns, making technology choices, or conducting Well-Architected Framework reviews.
---

# Cloud Solution Architect

## Overview

Design well-architected, production-grade cloud systems following Azure Architecture Center best practices. This skill provides:

- **10 design principles** for Azure applications
- **6 architecture styles** with selection guidance
- **44 cloud design patterns** mapped to WAF pillars
- **Technology choice frameworks** for compute, storage, data, messaging
- **Performance antipatterns** to avoid
- **Architecture review workflow** for systematic design validation

---

## Ten Design Principles for Azure Applications

| # | Principle | Key Tactics |
|---|-----------|-------------|
| 1 | **Design for self-healing** | Retry with backoff, circuit breaker, bulkhead isolation, health endpoint monitoring, graceful degradation |
| 2 | **Make all things redundant** | Eliminate single points of failure, use availability zones, deploy multi-region, replicate data |
| 3 | **Minimize coordination** | Decouple services, use async messaging, embrace eventual consistency, use domain events |
| 4 | **Design to scale out** | Horizontal scaling, autoscaling rules, stateless services, avoid session stickiness, partition workloads |
| 5 | **Partition around limits** | Data partitioning (shard/hash/range), respect compute & network limits, use CDNs for static content |
| 6 | **Design for operations** | Structured logging, distributed tracing, metrics & dashboards, runbook automation, infrastructure as code |
| 7 | **Use managed services** | Prefer PaaS over IaaS, reduce operational burden, leverage built-in HA/DR/scaling |
| 8 | **Use an identity service** | Microsoft Entra ID, managed identity, RBAC, avoid storing credentials, zero-trust principles |
| 9 | **Design for evolution** | Loose coupling, versioned APIs, backward compatibility, async messaging for integration, feature flags |
| 10 | **Build for business needs** | Define SLAs/SLOs, establish RTO/RPO targets, domain-driven design, cost modeling, composite SLAs |

---

## Architecture Styles

| Style | Description | When to Use | Key Services |
|-------|-------------|-------------|--------------|
| **N-tier** | Horizontal layers (presentation, business, data) | Traditional enterprise apps, lift-and-shift | App Service, SQL Database, VNets |
| **Web-Queue-Worker** | Web frontend → message queue → backend worker | Moderate-complexity apps with long-running tasks | App Service, Service Bus, Functions |
| **Microservices** | Small autonomous services, bounded contexts, independent deploy | Complex domains, independent team scaling | AKS, Container Apps, API Management |
| **Event-driven** | Pub/sub model, event producers/consumers | Real-time processing, IoT, reactive systems | Event Hubs, Event Grid, Functions |
| **Big data** | Batch + stream processing pipeline | Analytics, ML pipelines, large-scale data | Synapse, Data Factory, Databricks |
| **Big compute** | HPC, parallel processing | Simulations, modeling, rendering, genomics | Batch, CycleCloud, HPC VMs |

### Selection Criteria

- **Domain complexity** → Microservices (high), N-tier (low-medium)
- **Team autonomy** → Microservices (independent teams), N-tier (single team)
- **Data volume** → Big data (TB+), others (GB)
- **Latency requirements** → Event-driven (real-time), Web-Queue-Worker (tolerant)

---

## Cloud Design Patterns

44 patterns organized by primary concern. WAF pillar mapping: **R**=Reliability, **S**=Security, **CO**=Cost Optimization, **OE**=Operational Excellence, **PE**=Performance Efficiency.

### Messaging & Communication

| Pattern | Summary | Pillars |
|---------|---------|---------|
| **Asynchronous Request-
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