docs(10_Wiki): Topic_Business/General/Graphic/Programming을 Topics/ 하위로 이동
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id: wiki-2026-0508-publish-subscribe-model
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title: Publish-Subscribe Model
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category: 10_Wiki/Topics
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status: verified
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canonical_id: self
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aliases: [Pub-Sub, Pub/Sub, Topic-Based Messaging]
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duplicate_of: none
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source_trust_level: A
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confidence_score: 0.95
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verification_status: applied
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tags: [messaging, eda, distributed-systems, pattern]
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raw_sources: []
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last_reinforced: 2026-05-10
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github_commit: pending
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tech_stack:
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language: python
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framework: kafka-redis-nats
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---
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# Publish-Subscribe Model
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## 매 한 줄
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> **"매 publisher 매 subscribers 매 모름 — 매 topic / channel 매 통해 매 decoupled broadcast"**. 1987 ISIS Toolkit 매 origin, 매 today Kafka / Redis Pub/Sub / NATS / Google Pub/Sub / AWS SNS 매 ubiquitous backbone.
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## 매 핵심
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### 매 model variants
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- **Topic-based**: 매 logical channel name (e.g. `orders.created`).
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- **Content-based**: 매 message attributes 매 filter — 매 RabbitMQ headers exchange.
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- **Type-based**: 매 message class hierarchy.
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- **Hybrid**: 매 topic + filter (NATS subject wildcards `orders.*.created`).
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### 매 delivery semantics
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- **At-most-once**: fire-and-forget (Redis Pub/Sub).
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- **At-least-once**: ack required (Kafka, SQS).
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- **Exactly-once**: 매 idempotent + transactional (Kafka EOS, Pulsar).
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### 매 응용
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1. Event-driven microservices (orders → fulfillment, billing, notifications).
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2. Real-time dashboards (Grafana Live, websocket fanout).
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3. CDC (Debezium → Kafka → consumers).
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4. IoT telemetry (MQTT — pub-sub variant).
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## 💻 패턴
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### In-process pub-sub (Python)
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```python
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from collections import defaultdict
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from typing import Callable
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class Bus:
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def __init__(self):
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self.subs: dict[str, list[Callable]] = defaultdict(list)
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def subscribe(self, topic, fn): self.subs[topic].append(fn)
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def publish(self, topic, msg):
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for fn in self.subs[topic]:
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fn(msg)
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bus = Bus()
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bus.subscribe("user.created", lambda u: print(f"welcome {u}"))
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bus.publish("user.created", "alice")
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```
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### Redis Pub/Sub
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```python
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import redis, json
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r = redis.Redis()
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# Publisher
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r.publish("orders.created", json.dumps({"id": 42, "total": 99}))
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# Subscriber
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ps = r.pubsub()
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ps.subscribe("orders.*")
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for msg in ps.listen():
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if msg["type"] == "pmessage":
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handle(json.loads(msg["data"]))
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```
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### Kafka producer/consumer (Python)
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```python
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from confluent_kafka import Producer, Consumer
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p = Producer({"bootstrap.servers": "localhost:9092"})
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p.produce("orders", key="42", value=b'{"total":99}')
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p.flush()
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c = Consumer({
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"bootstrap.servers": "localhost:9092",
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"group.id": "fulfillment",
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"auto.offset.reset": "earliest",
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})
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c.subscribe(["orders"])
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while True:
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msg = c.poll(1.0)
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if msg and not msg.error():
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process(msg.value())
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c.commit(msg)
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```
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### NATS with subject wildcards
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```python
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import nats, asyncio
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async def main():
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nc = await nats.connect("nats://localhost:4222")
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async def cb(msg): print(msg.subject, msg.data)
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await nc.subscribe("orders.*.created", cb=cb)
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await nc.publish("orders.US.created", b'{"id":42}')
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await asyncio.sleep(1)
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asyncio.run(main())
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```
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### Google Cloud Pub/Sub
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```python
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from google.cloud import pubsub_v1
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publisher = pubsub_v1.PublisherClient()
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topic = publisher.topic_path("proj", "orders")
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publisher.publish(topic, b'{"id":42}', region="us-east1")
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sub = pubsub_v1.SubscriberClient()
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sub_path = sub.subscription_path("proj", "fulfillment-sub")
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def cb(msg): handle(msg.data); msg.ack()
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sub.subscribe(sub_path, callback=cb).result()
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```
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### AsyncAPI schema (governance, 2026)
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```yaml
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asyncapi: 3.0.0
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channels:
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ordersCreated:
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address: orders.created
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messages:
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OrderCreated:
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payload:
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type: object
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properties:
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id: {type: integer}
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total: {type: number}
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```
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## 매 결정 기준
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| 상황 | Approach |
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|---|---|
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| 매 in-process | Bus / EventEmitter |
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| 매 ephemeral, low-latency | Redis Pub/Sub / NATS |
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| 매 durable, replay 필요 | Kafka / Pulsar |
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| 매 cloud-native, managed | Google Pub/Sub / AWS SNS+SQS |
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| 매 IoT / mobile | MQTT |
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| 매 fan-in-out, transform | Kafka Streams / Pulsar Functions |
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**기본값**: 매 production EDA — Kafka. 매 simple/ephemeral — NATS.
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## 🔗 Graph
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- 부모: [[Event-Driven Architecture]]
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- 변형: [[Observer Pattern]] · [[Event Bus]]
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- 응용: [[Event Sourcing]] · [[CQRS]] · [[CDC]]
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- Adjacent: [[Kafka]] · [[NATS]] · [[Redis]] · [[MQTT]]
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## 🤖 LLM 활용
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**언제**: 매 schema design (AsyncAPI generation), 매 consumer code scaffolding, 매 dead-letter analysis.
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**언제 X**: 매 broker selection 매 trust 의 X — workload metrics 직접 측정.
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## ❌ 안티패턴
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- **Sync pub-sub**: 매 publisher block on slow subscriber — 매 async / queue 사용.
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- **No schema**: 매 consumer breakage — Avro/Protobuf + registry 필수.
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- **Topic explosion**: 매 user-per-topic — 매 millions of topics, broker 죽음. 매 partition / filter 사용.
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- **Duplicate semantics**: 매 at-least-once 인데 매 idempotency 없음 — duplicate processing.
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## 🧪 검증 / 중복
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- Verified (Eugster et al. — "The Many Faces of Publish/Subscribe" 2003; Kafka docs).
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- 신뢰도 A.
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## 🕓 Changelog
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| 날짜 | 변경 |
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|---|---|
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — full pub-sub pattern entry |
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