7.9 KiB
7.9 KiB
id, title, category, status, canonical_id, aliases, duplicate_of, source_trust_level, confidence_score, verification_status, tags, raw_sources, last_reinforced, github_commit, tech_stack
| id | title | category | status | canonical_id | aliases | duplicate_of | source_trust_level | confidence_score | verification_status | tags | raw_sources | last_reinforced | github_commit | tech_stack | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| wiki-2026-0508-복잡한-비즈니스-도메인-금융-헬스케어-이커머스-등 | 복잡한 비즈니스 도메인 (금융, 헬스케어, 이커머스 등) | 10_Wiki/Topics | verified | self |
|
none | A | 0.9 | applied |
|
2026-05-10 | pending |
|
복잡한 비즈니스 도메인 (금융, 헬스케어, 이커머스)
매 한 줄
"매 복잡한 도메인은 코드의 형태가 아니라 도메인 모델의 형태로 정복된다". 매 금융, 헬스케어, 이커머스는 각각 규제, 정확성, 동시성 압력이 다르며 매 DDD bounded context + invariant enforcement + event sourcing 이 2026 의 default approach.
매 핵심
매 도메인별 압력
- 금융: 매 정확성 (decimal arithmetic, no float), audit trail, regulatory (SOX, MiFID II, Basel III, K-AML), idempotency.
- 헬스케어: 매 PHI privacy (HIPAA, GDPR Art.9, K-MyData), HL7/FHIR interoperability, clinical decision support, audit immutability.
- 이커머스: 매 inventory consistency, payment idempotency, fraud detection, peak-load (Black Friday) elasticity, multi-currency/tax.
매 공통 architectural pillars
- Bounded Context: 매 Order, Payment, Inventory, Patient, Claim 의 명확한 ownership boundaries.
- Aggregate root + invariants: 매 transactional consistency unit, business rule enforcement.
- Event Sourcing + CQRS: 매 audit trail + read/write workload split.
- Sagas / Process Managers: 매 distributed transaction 대신 compensating actions.
- Anti-corruption layer: 매 legacy 시스템 (COBOL, HL7v2, EDI) 과의 격리.
매 응용
- 매 금융: 매 ledger as append-only event log, double-entry bookkeeping, eventual consistency 위 strong invariants.
- 매 헬스케어: 매 FHIR resource model + consent management + audit per-field-access.
- 매 이커머스: 매 inventory reservation saga + payment authorization/capture + outbox pattern.
💻 패턴
Decimal money (금융)
import Decimal from 'decimal.js';
class Money {
constructor(readonly amount: Decimal, readonly currency: string) {}
static of(amount: string, currency: string) {
return new Money(new Decimal(amount), currency);
}
add(other: Money): Money {
if (other.currency !== this.currency) throw new Error('currency mismatch');
return new Money(this.amount.plus(other.amount), this.currency);
}
// never use number — IEEE-754 binary float ruins cents
}
Aggregate with invariants (이커머스)
class Order {
private items: OrderItem[] = [];
private status: 'draft'|'placed'|'paid'|'fulfilled'|'cancelled' = 'draft';
addItem(productId: string, qty: number, unitPrice: Money) {
if (this.status !== 'draft') throw new Error('cannot modify placed order');
if (qty <= 0) throw new Error('qty>0');
this.items.push(new OrderItem(productId, qty, unitPrice));
}
place(): OrderPlaced {
if (this.items.length === 0) throw new Error('empty order');
this.status = 'placed';
return { type: 'OrderPlaced', orderId: this.id, total: this.total() };
}
}
Saga: payment + inventory (이커머스)
async function placeOrderSaga(orderId: string) {
const reservation = await inventory.reserve(orderId);
try {
const payment = await payments.authorize(orderId);
try {
await inventory.commit(reservation.id);
await payments.capture(payment.id);
} catch (e) {
await payments.void(payment.id);
await inventory.release(reservation.id);
throw e;
}
} catch (e) {
await inventory.release(reservation.id);
throw e;
}
}
Event sourcing (금융 ledger)
type LedgerEvent =
| { type: 'AccountOpened', accountId: string, currency: string }
| { type: 'Debited', accountId: string, amount: string, txId: string }
| { type: 'Credited', accountId: string, amount: string, txId: string };
function reduce(events: LedgerEvent[]): Account {
return events.reduce((acc, e) => {
if (e.type === 'AccountOpened') return { ...acc, currency: e.currency, balance: new Decimal(0) };
if (e.type === 'Debited') return { ...acc, balance: acc.balance.minus(e.amount) };
if (e.type === 'Credited') return { ...acc, balance: acc.balance.plus(e.amount) };
return acc;
}, {} as Account);
}
FHIR resource (헬스케어)
interface Patient {
resourceType: 'Patient';
id: string;
identifier: Array<{ system: string; value: string }>;
name: HumanName[];
birthDate: string; // ISO8601
consent?: Reference<Consent>; // K-MyData / HIPAA consent linkage
}
Outbox pattern (이커머스 reliability)
await db.transaction(async tx => {
await tx.insert('orders', order);
await tx.insert('outbox', {
id: ulid(),
aggregateId: order.id,
type: 'OrderPlaced',
payload: JSON.stringify(event),
createdAt: new Date(),
});
});
// async outbox poller publishes to Kafka — at-least-once delivery
Anti-corruption layer (legacy HL7v2 → FHIR)
class HL7v2ToFhirAdapter {
translate(adt: Hl7v2Message): Patient {
const pid = adt.segment('PID');
return {
resourceType: 'Patient',
id: pid.field(3).value(),
name: [{ family: pid.field(5).component(1), given: [pid.field(5).component(2)] }],
birthDate: this.parseHl7Date(pid.field(7).value()),
identifier: [{ system: 'urn:hospital:mrn', value: pid.field(3).value() }],
};
}
}
Idempotency key (payments)
async function charge(req: ChargeRequest, idempotencyKey: string) {
const existing = await db.idempotency.findOne({ key: idempotencyKey });
if (existing) return existing.response;
const result = await processor.charge(req);
await db.idempotency.insert({ key: idempotencyKey, response: result, ttl: '24h' });
return result;
}
매 결정 기준
| 상황 | Approach |
|---|---|
| 금융 ledger | Event sourcing + double-entry |
| 헬스케어 record | FHIR + consent + audit log |
| 이커머스 order flow | Saga + outbox + idempotency |
| Cross-domain integration | Anti-corruption layer |
| Strong invariant | Aggregate boundary, single-writer |
| High read throughput | CQRS read model |
기본값: 매 Bounded Context first, Aggregate + invariants second, Events as integration third.
🔗 Graph
- 부모: Domain-Driven Design · Bounded_Context
- 변형: Event Sourcing · CQRS · Saga Pattern
- 응용: 이커머스의 실시간 재고 관리 · 엔터프라이즈 소프트웨어 개발
- Adjacent: ACID Transactions · 비기능 요구사항 (Non-functional Requirements)
🤖 LLM 활용
언제: 매 도메인 모델링, invariant 추출, ubiquitous language 정리, regulatory mapping (HIPAA → field-level access policy). 언제 X: 매 specific compliance interpretation (변호사·CISO 검토 필수), 매 production money handling (independent audit 필요).
❌ 안티패턴
- Anonymic domain model: 매 getter/setter 만 있는 비즈니스 로직 없는 entity → service 비대화.
- Float for money: 매 0.1 + 0.2 ≠ 0.3 의 IEEE-754 catastrophe.
- Distributed transaction (2PC): 매 micro-services 간 2PC → coordinator deadlock + low availability.
- One DB for all bounded contexts: 매 schema coupling 으로 deploy lock-step.
- PHI in logs: 매 healthcare/finance 의 unmasked PII/PHI 가 log 에 → instant compliance breach.
🧪 검증 / 중복
- Verified (Evans "Domain-Driven Design", Vernon "Implementing DDD", FHIR R5 spec, ISO 20022).
- 신뢰도 A.
🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — finance/healthcare/ecommerce DDD patterns 정리 |