system-architect

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🇺🇸

Original

English

🇨🇳

Translation

Chinese

System Architect Skill

系统架构师技能

Design scalable, maintainable software systems.

设计可扩展、可维护的软件系统。

When to Use

适用场景

Designing new system/feature
Evaluating architectural trade-offs
API/database/caching decisions
Commands:
```
/architect
```
,
```
/design
```
,
```
/system-design
```

设计新系统/功能
评估架构取舍
API/数据库/缓存决策
命令：
```
/architect
```
、
```
/design
```
、
```
/system-design
```

Capabilities

核心能力

1. System Design

1. 系统设计

Microservices vs monolith
API design (REST, GraphQL, gRPC)
DB selection & schema design
Caching & message queues
Event-driven systems

微服务 vs 单体架构
API设计（REST、GraphQL、gRPC）
数据库选型与Schema设计
缓存与消息队列
事件驱动系统

2. Scalability

2. 可扩展性

Horizontal/vertical scaling
Load balancing & sharding
CDN & auto-scaling

水平/垂直扩展
负载均衡与分片
CDN与自动扩缩容

3. Reliability

3. 可靠性

HA patterns & DR planning
Circuit breaker & retry
Graceful degradation

高可用模式与灾难恢复规划
断路器与重试机制
优雅降级

4. Security

4. 安全性

Auth systems (OAuth, JWT, SSO)
Authorization (RBAC, ABAC)
API security & encryption

认证系统（OAuth、JWT、SSO）
授权机制（RBAC、ABAC）
API安全与加密

Architecture Decision Process

架构决策流程

Step 1: Requirements

步骤1：需求

markdown

1. Functional: Core features, workflows, integrations
2. Non-Functional: Performance, scalability, availability, security, budget
3. Constraints: Tech stack, team expertise, timeline, existing systems

markdown

1. Functional: Core features, workflows, integrations
2. Non-Functional: Performance, scalability, availability, security, budget
3. Constraints: Tech stack, team expertise, timeline, existing systems

Step 2: Pattern Selection

步骤2：模式选型

Reference

patterns.json

for patterns, tech recommendations, trade-offs.

参考

patterns.json

获取模式、技术推荐及取舍分析。

Step 3: Design Doc Template

步骤3：设计文档模板

markdown

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markdown

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Architecture Design Document

1. Overview

[High-level description]

2. Goals & Non-Goals

3. Architecture

System Diagram

Components

Component	Responsibility	Technology

Component	Responsibility	Technology

Data Flow

4. Technical Decisions

Decision 1: [Title]

Context | Options | Decision | Rationale

Context | Options | Decision | Rationale

5. API Design

6. Data Model

7. Security

8. Scalability

9. Monitoring & Observability

10. Risks & Mitigations

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Pattern Reference

模式参考

Communication

通信模式

Pattern	Use When	Trade-offs
Sync REST	Simple CRUD	Tight coupling
Async Queue	Decoupling	Complexity
Event Sourcing	Audit trail	Storage
CQRS	Read/write opt	Eventual consistency
GraphQL	Flexible queries	Caching
gRPC	High perf	Browser support

Pattern	Use When	Trade-offs
Sync REST	Simple CRUD	Tight coupling
Async Queue	Decoupling	Complexity
Event Sourcing	Audit trail	Storage
CQRS	Read/write opt	Eventual consistency
GraphQL	Flexible queries	Caching
gRPC	High perf	Browser support

Data

数据模式

Pattern	Use When	Trade-offs
SQL	ACID, complex queries	Scaling
NoSQL	Flexibility, scale	Consistency
Cache-aside	Read-heavy	Invalidation

Pattern	Use When	Trade-offs
SQL	ACID, complex queries	Scaling
NoSQL	Flexibility, scale	Consistency
Cache-aside	Read-heavy	Invalidation

Resilience

韧性模式

Pattern	Purpose
Circuit Breaker	Prevent cascade failures
Retry w/ Backoff	Handle transient failures
Bulkhead	Isolate failures
Timeout	Prevent hanging
Fallback	Graceful degradation

Pattern	Purpose
Circuit Breaker	Prevent cascade failures
Retry w/ Backoff	Handle transient failures
Bulkhead	Isolate failures
Timeout	Prevent hanging
Fallback	Graceful degradation

Project Structures

项目结构

Reference

structures.json

for:

Python: FastAPI, Django
TypeScript: Next.js, React, Express
Java: Spring Boot
Go: Standard Layout

参考

structures.json

获取以下技术栈的结构规范：

Python: FastAPI, Django
TypeScript: Next.js, React, Express
Java: Spring Boot
Go: Standard Layout

Tech Stack Recommendations

技术栈推荐

Web Apps

Web应用

Frontend: React/Next.js, Vue/Nuxt, Angular
Backend: Node.js, Go, Python (FastAPI), Rust
DB: PostgreSQL, MongoDB
Cache: Redis | Queue: RabbitMQ, SQS, Kafka
Search: Elasticsearch, Meilisearch

Frontend: React/Next.js, Vue/Nuxt, Angular
Backend: Node.js, Go, Python (FastAPI), Rust
DB: PostgreSQL, MongoDB
Cache: Redis | Queue: RabbitMQ, SQS, Kafka
Search: Elasticsearch, Meilisearch

Real-time

实时应用

WebSocket: Socket.io, ws
Pub/Sub: Redis, Kafka

WebSocket: Socket.io, ws
Pub/Sub: Redis, Kafka

Data-Intensive

数据密集型应用

Processing: Spark, Flink
Storage: S3, GCS
Warehouse: Snowflake, BigQuery
Pipeline: Airflow, Dagster

Processing: Spark, Flink
Storage: S3, GCS
Warehouse: Snowflake, BigQuery
Pipeline: Airflow, Dagster

Diagramming

绘图指南

ASCII Component

ASCII组件图

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│   Client    │────▶│ API Gateway │────▶│  Services   │
└─────────────┘     └─────────────┘     └─────────────┘
                           │                   │
                           ▼                   ▼
                    ┌─────────────┐     ┌─────────────┐
                    │    Auth     │     │  Database   │
                    └─────────────┘     └─────────────┘

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│   Client    │────▶│ API Gateway │────▶│  Services   │
└─────────────┘     └─────────────┘     └─────────────┘
                           │                   │
                           ▼                   ▼
                    ┌─────────────┐     ┌─────────────┐
                    │    Auth     │     │  Database   │
                    └─────────────┘     └─────────────┘

Mermaid Sequence

Mermaid序列图

mermaid

sequenceDiagram
    Client->>API: Request
    API->>Auth: Validate Token
    Auth-->>API: Valid
    API->>Service: Process
    Service->>DB: Query
    DB-->>Service: Data
    Service-->>API: Response
    API-->>Client: Response

mermaid

sequenceDiagram
    Client->>API: Request
    API->>Auth: Validate Token
    Auth-->>API: Valid
    API->>Service: Process
    Service->>DB: Query
    DB-->>Service: Data
    Service-->>API: Response
    API-->>Client: Response

Evaluation Criteria

评估标准

Criterion	Weight	Description
Scalability	High	Can it handle growth?
Maintainability	High	Easy to modify/debug?
Performance	Med-High	Meets latency/throughput?
Cost	Medium	Infra + dev cost
Security	High	Meets requirements?
Complexity	Medium	Team can build/operate?

评估维度	权重	描述
可扩展性	高	是否能应对业务增长？
可维护性	高	是否易于修改/调试？
性能	中高	是否满足延迟/吞吐量要求？
成本	中	基础设施+开发成本
安全性	高	是否满足安全要求？
复杂度	中	团队是否能构建/运维？

Output Templates

输出模板

Quick Decision

快速决策模板

markdown

**Question**: [What needs deciding]
**Recommendation**: [Approach]
**Rationale**: [Why]
**Trade-offs**: [Accepting]
**Alternatives**: [Other options]

markdown

**问题**: [需要决策的内容]
**推荐方案**: [具体方法]
**理由**: [为什么选择该方案]
**取舍**: [需要接受的权衡]
**替代方案**: [其他可选方案]

Integration

集成能力

code-reviewer: Validate impl matches design
postgres-mcp: DB schema design
jira-bridge: Create impl tickets

code-reviewer: 验证实现是否符合设计要求
postgres-mcp: 数据库Schema设计
jira-bridge: 创建开发任务工单