| name | enterprise |
| classification | capability |
| classification-reason | Specialized domain knowledge with limited model overlap |
| deprecation-risk | low |
| effort | high |
| description | Enterprise-grade systems with microservices, Kubernetes, Terraform, and AI Native methodology. For multi-feature initiatives spanning a release timeline, combine with /sprint master-plan (v2.1.13) to group features into a single 8-phase sprint container with shared scope/budget and 4 auto-pause triggers (QUALITY_GATE_FAIL / ITERATION_EXHAUSTED / BUDGET_EXCEEDED / PHASE_TIMEOUT).
Triggers: microservices, k8s, terraform, monorepo, AI native, ๋ง์ดํฌ๋ก์๋น์ค, init enterprise.
|
| argument-hint | [init|guide|help] |
| agents | {"default":"bkit:enterprise-expert","infra":"bkit:infra-architect","architecture":"bkit:enterprise-expert","security":"bkit:security-architect","team":"bkit:cto-lead"} |
| allowed-tools | ["Read","Write","Edit","Glob","Grep","Bash","Task","WebSearch"] |
| user-invocable | true |
| imports | ["${PLUGIN_ROOT}/templates/design-enterprise.template.md"] |
| next-skill | phase-1-schema |
| pdca-phase | plan |
| task-template | [Init-Enterprise] {feature} |
Advanced (Enterprise) Skill
Actions
| Action | Description | Example |
|---|
init | Project initialization (/init-enterprise feature) | /enterprise init my-platform |
guide | Display development guide | /enterprise guide |
help | MSA/Infrastructure help | /enterprise help |
init (Project Initialization)
- Create Turborepo monorepo structure
- apps/, packages/, services/, infra/ folder structure
- Create CLAUDE.md (Level: Enterprise specified)
- docs/ 5-category structure
- infra/terraform/, infra/k8s/ base templates
- 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
- Sentry Browser SDK (@sentry/nextjs) โ Error tracking + Session Replay
Backend:
- Python FastAPI (microservices) โ default
- PostgreSQL (schema separation)
- Redis (cache, Pub/Sub)
- RabbitMQ / SQS (message queue)
- Sentry Server SDK (sentry-sdk[fastapi]) โ Error tracking + APM
Infrastructure:
- AWS (EKS, RDS, S3, CloudFront)
- Kubernetes (Kustomize)
- Terraform (IaC)
- ArgoCD (GitOps)
- ALB + NGINX Ingress Controller (L7 load balancing)
- CORS: Ingress annotation์ผ๋ก ์ฒ๋ฆฌ
nginx.ingress.kubernetes.io/enable-cors: "true"
- NLB(L4)๋ gRPC/WebSocket ์ ์ฉ ์๋น์ค์๋ง ์ฌ์ฉ
CI/CD:
- GitHub Actions
- Docker
- Semgrep (SAST) + Trivy (Container Scan)
Monitoring & Error Tracking:
- Sentry โ Error tracking, grouping, regression detection
- Prometheus + Grafana โ Metrics & dashboards
- Loki + Promtail โ Log aggregation
- Tempo + OpenTelemetry โ Distributed tracing
- Alertmanager โ PagerDuty (critical) / Slack (warning)
Self-Healing Pipeline:
- Sentry Webhook โ Self-Healing Agent trigger
- 4-Layer Living Context (Scenarios, Invariants, Impact, Incidents)
- Auto-fix (max 5 iterations) โ Auto PR โ Canary Deploy
- Auto-Rollback on error rate spike
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 โ TypeScript (Next.js API routes)
- Ruby โ Python (FastAPI)
- Java โ Kotlin or Go
Project Structure
project/
โโโ apps/ # Frontend apps (Turborepo)
โ โโโ web/ # Main web app
โ โโโ admin/ # Admin
โ โโโ docs/ # Documentation site
โ
โโโ packages/ # Shared packages
โ โโโ ui/ # UI components
โ โโโ api-client/ # API client
โ โโโ config/ # Shared config
โ
โโโ services/ # Backend microservices
โ โโโ auth/ # Auth service
โ โโโ user/ # User service
โ โโโ {domain}/ # Domain-specific services
โ โโโ shared/ # Shared modules
โ
โโโ infra/ # Infrastructure code
โ โโโ terraform/
โ โ โโโ modules/ # Reusable modules
โ โ โโโ environments/ # Environment-specific config
โ โโโ k8s/
โ โโโ base/ # Common manifests
โ โโโ overlays/ # Environment-specific patches
โ
โโโ docs/ # PDCA documents
โ โโโ 00-requirement/
โ โโโ 01-development/ # Design documents (multiple)
โ โโโ 02-scenario/
โ โโโ 03-refactoring/
โ โโโ 04-operation/
โ
โโโ scripts/ # Utility scripts
โโโ .github/workflows/ # CI/CD
โโโ docker-compose.yml
โโโ turbo.json
โโโ pnpm-workspace.yaml
Clean Architecture (4-Layer)
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ API Layer โ
โ - FastAPI routers โ
โ - Request/Response DTOs โ
โ - Auth/authz middleware โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ Application Layer โ
โ - Service classes โ
โ - Use Case implementation โ
โ - Transaction management โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ Domain Layer โ
โ - Entity classes (pure Python) โ
โ - Repository interfaces (ABC) โ
โ - Business rules โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ Infrastructure Layer โ
โ - Repository implementations (SQLAlchemy) โ
โ - External API clients โ
โ - Cache, messaging โ
โ - Sentry SDK integration (error capture) โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Dependency direction: Top โ Bottom
Domain Layer depends on nothing
Error Handling & Self-Healing Pipeline
Exception ๋ฐ์ (Frontend/Backend)
โ
Sentry SDK ์๋ ์บก์ฒ (stack trace + breadcrumbs + user context)
โ
Sentry Alert Rule (new issue / regression / spike)
โ
Webhook โ Self-Healing Agent trigger
โ
Living Context 4-Layer ๋ก๋ฉ
โโโ Scenario Matrix: ํ
์คํธ ์๋๋ฆฌ์ค
โโโ Invariants: ๋ถ๋ณ ์กฐ๊ฑด (critical = ์์ ์ฐจ๋จ)
โโโ Impact Map: blast radius ๊ณ์ฐ
โโโ Incident Memory: ๊ณผ๊ฑฐ ์ฅ์ ๊ตํ
โ
Claude Code Fix (max 5 iterations)
โ
4์ค ๊ฒ์ฆ (scenarios + invariants + impact + anti-patterns)
โ
Pass โ Auto PR โ Human Review โ Canary Deploy (10%โ25%โ50%โ100%)
Fail โ Escalation โ PagerDuty + Slack + Auto-Rollback
โ
Post-deploy: Sentry์์ issue resolved ํ์ธ + error_rate ๋ชจ๋ํฐ๋ง
Load Balancer Strategy
ALB + NGINX Ingress Controller (๊ธฐ๋ณธ, ๊ถ์ฅ)
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
- L7 ๋ก๋๋ฐธ๋ฐ์ฑ (HTTP/HTTPS/gRPC)
- CORS: Ingress annotation์ผ๋ก ์ฒ๋ฆฌ (์ฑ ์ฝ๋ ๋ถํ์)
- Path-based routing (/api/auth/*, /api/users/*)
- AWS Certificate Manager (ACM) TLS ์ฐ๋
- WAF ์ฐ๋ ๊ฐ๋ฅ
NLB (ํน์ ์ผ์ด์ค๋ง)
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
- L4 ๋ก๋๋ฐธ๋ฐ์ฑ (TCP/UDP)
- ๊ทน๋์ ์ ์ง์ฐ ํ์ ์ (< 1ms)
- WebSocket/gRPC ์ ์ฉ ์๋น์ค
- CORS ์ฒ๋ฆฌ ๋ถ๊ฐ โ ์ฑ๋จ์์ ์ง์ ์ฒ๋ฆฌ ํ์
Core Patterns
Repository Pattern
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
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
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()
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
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
โ
Allowed
- Retrieve secrets from Secrets Manager
- IAM role-based access
- VPC internal communication
- mTLS (inter-service)
โ Prohibited
- Hardcoded secrets
- DB in public subnet
- Using root account
- Excessive IAM permissions
CI/CD Pipeline
Push to feature/*
โ
GitHub Actions (CI)
- Lint
- Test
- Build Docker image
- Push to ECR
โ
PR to staging
โ
ArgoCD Auto Sync (Staging)
โ
PR to main
โ
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 โ Documentation โ 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:
โโ project/
โโ frontend/ โโโโโโโ
โโ services/ โโโโโโโค AI reads completely
โโ infra/ โโโโโโโโโโค Context unified
โโ packages/ โโโโโโโ
โ
AI understands full context
โ
Single source of truth for types
โ
Atomic commits across layers
โ
Consistent patterns enforced
CLAUDE.md Hierarchy
project/
โโโ CLAUDE.md # Project-wide context
โโโ frontend/CLAUDE.md # Frontend conventions
โโโ services/CLAUDE.md # Backend conventions
โโโ 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:
| Role | Agents | PDCA Phases |
|---|
| architect | enterprise-expert, infra-architect | Design |
| developer | bkend-expert | Do, Act |
| qa | qa-monitor, gap-detector | Check |
| reviewer | code-analyzer, design-validator | Check, Act |
To enable:
- Set environment:
CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1
- Start team mode:
/pdca team {feature}
- 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.