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backend-graphql-federation GraphQL Federation — Apollo / Mesh / Hive Coding draft B conceptual 2026-05-09 2026-05-09
backend
graphql
vibe-coding
language applicable_to
TS
Backend
GraphQL Federation
Apollo Federation
GraphQL Mesh
Hive
supergraph
subgraph

GraphQL Federation

Microservice 가 GraphQL = federation. Subgraph (per service) → Supergraph (gateway). Apollo Federation 가 표준. 작은 system 가 stitching.

📖 핵심 개념

  • 매 service 가 own schema (subgraph).
  • Gateway 가 query plan + 분산 실행.
  • Entity (cross-service type).
  • Schema composition.

💻 코드 패턴

Federation 식

# users service (subgraph)
type User @key(fields: "id") {
  id: ID!
  email: String!
}

# orders service (subgraph)
type Order {
  id: ID!
  total: Float!
  user: User!  # users service 의 User
}

extend type User @key(fields: "id") {
  id: ID! @external
  orders: [Order!]!  # orders 가 추가
}

→ User 가 두 service 가 정의 (federated).

Apollo Server (subgraph)

import { ApolloServer } from '@apollo/server';
import { buildSubgraphSchema } from '@apollo/subgraph';

const typeDefs = `
  type User @key(fields: "id") {
    id: ID!
    email: String!
  }
  
  type Query {
    users: [User!]!
  }
`;

const resolvers = {
  Query: { users: () => db.users.find() },
  User: {
    __resolveReference: ({ id }) => db.users.findOne({ id }),
  },
};

const server = new ApolloServer({
  schema: buildSubgraphSchema({ typeDefs, resolvers }),
});

__resolveReference 가 다른 service 가 reference.

Apollo Router (gateway)

# router.yaml
supergraph:
  listen: 0.0.0.0:4000

subgraphs:
  users:
    routing_url: http://users:4001
  orders:
    routing_url: http://orders:4002
router --config router.yaml

→ Single endpoint, query 가 자동 분산.

Supergraph composition

# Compose subgraph schemas → supergraph
rover supergraph compose --config supergraph.yaml > supergraph.graphql
# supergraph.yaml
subgraphs:
  users:
    routing_url: http://users:4001
    schema:
      file: users/schema.graphql
  orders:
    routing_url: http://orders:4002
    schema:
      file: orders/schema.graphql

Apollo Studio / Hive

Schema registry:
- 매 service 가 schema publish.
- Compose 가 검증.
- Breaking change 감지.
- Performance 가 visualize.

→ Apollo Studio (paid).
Hive (open source, free).

Entity resolution

query {
  orders {
    id
    user {
      email   # users service 가
    }
  }
}
Gateway 가:
1. orders service: orders + user.id 가져옴.
2. users service: User(id: ...) batch.
3. Merge.

→ N+1 자동 batch (DataLoader).

Federation directives

@key(fields: "id")              # Entity (cross-service)
@external                        # Field 가 다른 service 가
@requires(fields: "stock")       # 다른 service field 필요
@provides(fields: "name")        # 이 service 가 줌
@shareable                       # 여러 service 가 정의 OK
@override(from: "old-service")   # Migration
@inaccessible                    # Public 안 보임

GraphQL Mesh

# mesh.yaml
sources:
  - name: users
    handler:
      openapi:
        source: https://users/openapi.json
  - name: orders
    handler:
      graphql:
        endpoint: https://orders/graphql

→ 매 source (REST, GraphQL, gRPC) 가 unified GraphQL.

→ Apollo Federation 가 GraphQL only. Mesh 가 다양.

Schema stitching (legacy)

import { stitchSchemas } from '@graphql-tools/stitch';

const schema = stitchSchemas({
  subschemas: [usersSchema, ordersSchema],
});

→ Federation 의 옛 version. 작은 use case.

Performance: query plan

query {
  user(id: 1) {
    name
    orders {
      total
      product {
        name
      }
    }
  }
}
Plan:
1. users service: user(id: 1) → {id, name}.
2. orders service: orders for user.id 1 → [{id, total, productId}].
3. products service: products([1, 2, 3]) batch → [{id, name}].

→ 3 service 호출, parallel where possible.

N+1 방지 (DataLoader)

import DataLoader from 'dataloader';

const userLoader = new DataLoader(async (ids: string[]) => {
  const users = await db.users.find({ id: { $in: ids } });
  return ids.map(id => users.find(u => u.id === id));
});

// Resolver
User: { id: ({ id }) => userLoader.load(id) }

→ 매 request 가 자체 loader. Batch.

Authentication

// Gateway 가 auth header forward
const router = new Router({
  subgraphs: {
    users: { routing_url: '...', willSendRequest: ({ request }) => {
      request.http.headers.set('user-id', context.userId);
    }},
  },
});

// Subgraph 가 user-id header 사용

Rate limit

Gateway level (Apollo Router):
- Query depth limit (5).
- Query complexity limit (1000 cost).
- Per-user rate.

Subgraph level:
- Per-resolver rate.

Caching

Apollo Router:
- Response cache.
- Per-field hint (@cacheControl).
- CDN cache.

Subgraph:
- DataLoader (per-request).
- Redis (per-field).
type User @cacheControl(maxAge: 300) {
  id: ID!
  email: String! @cacheControl(maxAge: 60)
}

Tracing

- Apollo Studio: query timing.
- OpenTelemetry: span 별 service.
- Prometheus: metric.

→ "이 query 가 어디 서비스 가 느림?" visible.

Schema linting

# Apollo Rover
rover graph check my-graph@current --schema schema.graphql

→ Breaking change 감지.

Versioning

GraphQL = no version (single schema 가 evolve).
- Add fields: OK.
- Remove field: deprecated → grace period → remove.
- Rename: 새 field + 옛 deprecated.

→ Mobile app 가 옛 client 도 작동.

Federation 의 alternative

- BFF (Backend for Frontend): per-client REST + GraphQL.
- API Gateway (REST): 단순.
- gRPC + Buf: type-safe.
- tRPC: TS-only.

→ GraphQL Federation 가 큰 system + 다양 client.

When NOT?

- 작은 system (1-2 service): 직접 GraphQL.
- Single client: REST 충분.
- 매우 high-throughput: gRPC.
- Mobile-only + simple: tRPC / REST.

Migration

1. 1 monolith GraphQL.
2. 1 service split → subgraph.
3. Gateway 추가 (federation 활성).
4. 점진 split.
5. 옛 monolith retire.

→ Strangler fig.

Production

- Apollo Router (Rust, 빠름).
- Hive (open source registry).
- Mesh (REST → GraphQL).
- ko / pothos / Yoga / Mercurius (subgraph servers).

Cost / overhead

Federation 가 큰 cost:
- Gateway latency (10-50ms).
- Schema composition complexity.
- 매 service 가 federation aware.

→ 5+ service GraphQL 가 sweet spot.

Real-world

  • Netflix: 큰 GraphQL Federation.
  • Airbnb: federation 사용.
  • Expedia: federation.
  • Walmart: 큰 multi-team.
  • Atlassian: federation 마이그레이션.

🤔 의사결정 기준

상황 추천
단일 GraphQL 직접 server
5+ subgraph Apollo Federation
Mixed source GraphQL Mesh
작은 (legacy) Schema stitching
Schema registry Apollo Studio / Hive
빠른 gateway Apollo Router (Rust)
Simple TS RPC tRPC

안티패턴

  • 모든 거 federation (작은 system): 큰 overhead.
  • No DataLoader: N+1 폭발.
  • Schema 무계획 변경: client 깨짐.
  • No cache: latency.
  • Auth gateway 만: subgraph 도 검증.
  • No tracing: bottleneck 모름.
  • Subgraph 가 cross-service join: federation 의 가치 ↓.

🤖 LLM 활용 힌트

  • Federation = supergraph + subgraph + entity.
  • Apollo Router 가 빠름 (Rust).
  • Hive 가 open source registry.
  • DataLoader 가 N+1 의 답.

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