
enterprise
by popup-studio-ai
bkit Vibecoding Kit - PDCA methodology + Claude Code mastery for AI-native development
SKILL.md
name: enterprise description: | Enterprise-grade system development with microservices, Kubernetes, and Terraform. Includes AI Native methodology and Monorepo architecture patterns. Handles high traffic, high availability, and complex architecture requirements.
Use proactively when user needs high traffic, microservices, custom infrastructure, or AI-native development patterns.
Triggers: microservices, kubernetes, terraform, k8s, AWS, monorepo, AI native, 10-day, 마이크로서비스, 모노레포, マイクロサービス, モノレポ, 微服务, 单仓库
Do NOT use for: simple websites, MVPs, or projects without infrastructure requirements. agent: infra-architect allowed-tools:
- Read
- Write
- Edit
- Glob
- Grep
- Bash
- Task user-invocable: false
Advanced (Enterprise) Skill
Target Audience
- Senior developers
- CTOs / Architects
- Large-scale system operators
Tech Stack
Frontend:
- Next.js 14+ (Turborepo monorepo)
- TypeScript
- Tailwind CSS
- TanStack Query
- Zustand
Backend:
- Python FastAPI (microservices)
- PostgreSQL (schema separation)
- Redis (cache, Pub/Sub)
- RabbitMQ / SQS (message queue)
Infrastructure:
- AWS (EKS, RDS, S3, CloudFront)
- Kubernetes (Kustomize)
- Terraform (IaC)
- ArgoCD (GitOps)
CI/CD:
- GitHub Actions
- Docker
Language Tier Guidance (v1.3.0)
Supported: All Tiers
Enterprise level handles complex requirements including legacy system integration.
| Tier | Usage | Guidance |
|---|---|---|
| Tier 1 | Primary services | New development, core features |
| Tier 2 | System/Cloud | Go (K8s), Rust (performance critical) |
| Tier 3 | Platform native | iOS (Swift), Android (Kotlin), legacy Java |
| Tier 4 | Legacy integration | Migration plan required |
Migration Path:
- PHP → TypeScript (Next.js API routes)
- Ruby → Python (FastAPI)
- Java → Kotlin or Go
Project Structure
project/
├── apps/ # Frontend apps (Turborepo)
│ ├── web/ # Main web app
│ ├── admin/ # Admin
│ └── docs/ # Documentation site
│
├── packages/ # Shared packages
│ ├── ui/ # UI components
│ ├── api-client/ # API client
│ └── config/ # Shared config
│
├── services/ # Backend microservices
│ ├── auth/ # Auth service
│ ├── user/ # User service
│ ├── {domain}/ # Domain-specific services
│ └── shared/ # Shared modules
│
├── infra/ # Infrastructure code
│ ├── terraform/
│ │ ├── modules/ # Reusable modules
│ │ └── environments/ # Environment-specific config
│ └── k8s/
│ ├── base/ # Common manifests
│ └── overlays/ # Environment-specific patches
│
├── docs/ # PDCA documents
│ ├── 00-requirement/
│ ├── 01-development/ # Design documents (multiple)
│ ├── 02-scenario/
│ ├── 03-refactoring/
│ └── 04-operation/
│
├── scripts/ # Utility scripts
├── .github/workflows/ # CI/CD
├── docker-compose.yml
├── turbo.json
└── pnpm-workspace.yaml
Clean Architecture (4-Layer)
┌─────────────────────────────────────────────────────────┐
│ API Layer │
│ - FastAPI routers │
│ - Request/Response DTOs │
│ - Auth/authz middleware │
├─────────────────────────────────────────────────────────┤
│ Application Layer │
│ - Service classes │
│ - Use Case implementation │
│ - Transaction management │
├─────────────────────────────────────────────────────────┤
│ Domain Layer │
│ - Entity classes (pure Python) │
│ - Repository interfaces (ABC) │
│ - Business rules │
├─────────────────────────────────────────────────────────┤
│ Infrastructure Layer │
│ - Repository implementations (SQLAlchemy) │
│ - External API clients │
│ - Cache, messaging │
└─────────────────────────────────────────────────────────┘
Dependency direction: Top → Bottom
Domain Layer depends on nothing
Core Patterns
Repository Pattern
# domain/repositories/user_repository.py (interface)
from abc import ABC, abstractmethod
class UserRepository(ABC):
@abstractmethod
async def find_by_id(self, id: str) -> User | None:
pass
@abstractmethod
async def save(self, user: User) -> User:
pass
# infrastructure/repositories/user_repository_impl.py (implementation)
class UserRepositoryImpl(UserRepository):
def __init__(self, db: AsyncSession):
self.db = db
async def find_by_id(self, id: str) -> User | None:
result = await self.db.execute(
select(UserModel).where(UserModel.id == id)
)
return result.scalar_one_or_none()
Inter-service Communication
# Synchronous (Internal API)
async def get_user_info(user_id: str) -> dict:
async with httpx.AsyncClient() as client:
response = await client.get(
f"{USER_SERVICE_URL}/internal/users/{user_id}",
headers={"X-Internal-Token": INTERNAL_TOKEN}
)
return response.json()
# Asynchronous (message queue)
await message_queue.publish(
topic="user.created",
message={"user_id": user.id, "email": user.email}
)
Terraform Module
# modules/eks/main.tf
resource "aws_eks_cluster" "this" {
name = "${var.environment}-${var.project_name}-eks"
role_arn = aws_iam_role.cluster.arn
version = var.kubernetes_version
vpc_config {
subnet_ids = var.subnet_ids
}
tags = merge(var.tags, {
Environment = var.environment
})
}
Kubernetes Deployment
# k8s/base/backend/deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: user-service
spec:
replicas: 2
template:
spec:
containers:
- name: user-service
image: ${ECR_REGISTRY}/user-service:${TAG}
resources:
requests:
cpu: "100m"
memory: "256Mi"
limits:
cpu: "500m"
memory: "512Mi"
livenessProbe:
httpGet:
path: /health
port: 8000
Environment Configuration
| Environment | Infrastructure | Deployment Method |
|---|---|---|
| Local | Docker Compose | Manual |
| Staging | EKS | ArgoCD Auto Sync |
| Production | EKS | ArgoCD Manual Sync |
Security Rules
✅ Allowed
- Retrieve secrets from Secrets Manager
- IAM role-based access
- VPC internal communication
- mTLS (inter-service)
❌ Prohibited
- Hardcoded secrets
- DB in public subnet
- Using root account
- Excessive IAM permissions
CI/CD Pipeline
Push to feature/*
↓
GitHub Actions (CI)
- Lint
- Test
- Build Docker image
- Push to ECR
↓
PR to staging
↓
ArgoCD Auto Sync (Staging)
↓
PR to main
↓
ArgoCD Manual Sync (Production)
SoR Priority
1st Priority: Codebase
- scripts/init-db.sql (source of truth for DB schema)
- services/{service}/app/ (each service implementation)
2nd Priority: CLAUDE.md / Convention docs
- services/CLAUDE.md
- frontend/CLAUDE.md
- infra/CLAUDE.md
3rd Priority: docs/ design documents
- For understanding design intent
- If different from code, code is correct
AI Native Development
3 Core Principles
- Document-First Design: Write design docs BEFORE code
- Monorepo Context Control: All code in one repo for AI context
- PR-Based Collaboration: Every change through PR
10-Day Development Pattern
| Day | Focus | Output |
|---|---|---|
| 1 | Architecture | Market analysis + System architecture |
| 2-3 | Core | Auth, User + Business services |
| 4-5 | UX | PO feedback → Documentation → Implementation |
| 6-7 | QA | Zero Script QA + bug fixes |
| 8 | Infra | Terraform + GitOps |
| 9-10 | Production | Security review + Deployment |
Monorepo Benefits for AI
Mono-repo:
└─ project/
├─ frontend/ ──────┐
├─ services/ ──────┤ AI reads completely
├─ infra/ ─────────┤ Context unified
└─ packages/ ──────┘
✅ AI understands full context
✅ Single source of truth for types
✅ Atomic commits across layers
✅ Consistent patterns enforced
CLAUDE.md Hierarchy
project/
├── CLAUDE.md # Project-wide context
├── frontend/CLAUDE.md # Frontend conventions
├── services/CLAUDE.md # Backend conventions
└── infra/CLAUDE.md # Infra conventions
Rule: Area-specific CLAUDE.md overrides project-level rules
Score
Total Score
Based on repository quality metrics
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Reviews
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