enterprise

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. Project initialization with "init enterprise" or "enterprise init". 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, init enterprise, enterprise init, 마이크로서비스, 모노레포, マイクロサービス, モノレポ, 微服务, 单仓库, microservicios, estrategia empresarial, arquitectura, CTO, nativo de IA, microservices, stratégie d'entreprise, architecture, CTO, natif IA, Microservices, Unternehmensstrategie, Architektur, CTO, KI-nativ, microservizi, strategia aziendale, architettura, CTO, AI nativo Do NOT use for: simple websites, MVPs, or projects without infrastructure requirements.

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Install skill "enterprise" with this command: npx skills add popup-studio-ai/bkit-claude-code/popup-studio-ai-bkit-claude-code-enterprise

Advanced (Enterprise) Skill

Actions

ActionDescriptionExample
initProject initialization (/init-enterprise feature)/enterprise init my-platform
guideDisplay development guide/enterprise guide
helpMSA/Infrastructure help/enterprise help

init (Project Initialization)

  1. Create Turborepo monorepo structure
  2. apps/, packages/, services/, infra/ folder structure
  3. Create CLAUDE.md (Level: Enterprise specified)
  4. docs/ 5-category structure
  5. infra/terraform/, infra/k8s/ base templates
  6. Initialize .bkit-memory.json

guide (Development Guide)

  • AI Native 10-Day development cycle
  • Microservices architecture patterns
  • Phase 1-9 full Pipeline (Enterprise version)

help (Infrastructure Help)

  • Kubernetes basic concepts
  • Terraform IaC patterns
  • AWS EKS, RDS configuration guide

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.

TierUsageGuidance
Tier 1Primary servicesNew development, core features
Tier 2System/CloudGo (K8s), Rust (performance critical)
Tier 3Platform nativeiOS (Swift), Android (Kotlin), legacy Java
Tier 4Legacy integrationMigration 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

EnvironmentInfrastructureDeployment Method
LocalDocker ComposeManual
StagingEKSArgoCD Auto Sync
ProductionEKSArgoCD 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

  1. Document-First Design: Write design docs BEFORE code
  2. Monorepo Context Control: All code in one repo for AI context
  3. PR-Based Collaboration: Every change through PR

10-Day Development Pattern

DayFocusOutput
1ArchitectureMarket analysis + System architecture
2-3CoreAuth, User + Business services
4-5UXPO feedback → Documentation → Implementation
6-7QAZero Script QA + bug fixes
8InfraTerraform + GitOps
9-10ProductionSecurity 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


bkit Features for Enterprise Level (v1.5.1)

Output Style: bkit-enterprise (Recommended)

For CTO-level architecture perspectives, activate the enterprise style:

/output-style bkit-enterprise

This provides:

  • Architecture tradeoff analysis tables (Option/Pros/Cons/Recommendation)
  • Performance, security, and scalability perspectives for every decision
  • Cost impact estimates for infrastructure changes
  • Deployment strategy recommendations (Blue/Green, Canary, Rolling)
  • SOLID principles and Clean Architecture compliance checks

Agent Teams (4 Teammates)

Enterprise projects support full Agent Teams for parallel PDCA execution:

RoleAgentsPDCA Phases
architectenterprise-expert, infra-architectDesign
developerbkend-expertDo, Act
qaqa-monitor, gap-detectorCheck
reviewercode-analyzer, design-validatorCheck, Act

To enable:

  1. Set environment: CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1
  2. Start team mode: /pdca team {feature}
  3. Monitor progress: /pdca team status

Agent Memory (Auto-Active)

All bkit agents automatically remember project context across sessions. Enterprise agents use project scope memory, ensuring architecture decisions and infrastructure patterns persist across development sessions.

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