2nd/10_Wiki/Topics/Architecture/Publish-Subscribe Model.md

---
id: wiki-2026-0508-publish-subscribe-model
title: Publish-Subscribe Model
category: 10_Wiki/Topics
status: verified
canonical_id: self
aliases: [Pub-Sub, Pub/Sub, Topic-Based Messaging]
duplicate_of: none
source_trust_level: A
confidence_score: 0.95
verification_status: applied
tags: [messaging, eda, distributed-systems, pattern]
raw_sources: []
last_reinforced: 2026-05-10
github_commit: pending
tech_stack:
  language: python
  framework: kafka-redis-nats
---

# Publish-Subscribe Model

## 매 한 줄
> **"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.

## 매 핵심

### 매 model variants
- **Topic-based**: 매 logical channel name (e.g. `orders.created`).
- **Content-based**: 매 message attributes 매 filter — 매 RabbitMQ headers exchange.
- **Type-based**: 매 message class hierarchy.
- **Hybrid**: 매 topic + filter (NATS subject wildcards `orders.*.created`).

### 매 delivery semantics
- **At-most-once**: fire-and-forget (Redis Pub/Sub).
- **At-least-once**: ack required (Kafka, SQS).
- **Exactly-once**: 매 idempotent + transactional (Kafka EOS, Pulsar).

### 매 응용
1. Event-driven microservices (orders → fulfillment, billing, notifications).
2. Real-time dashboards (Grafana Live, websocket fanout).
3. CDC (Debezium → Kafka → consumers).
4. IoT telemetry (MQTT — pub-sub variant).

## 💻 패턴

### In-process pub-sub (Python)
```python
from collections import defaultdict
from typing import Callable

class Bus:
    def __init__(self):
        self.subs: dict[str, list[Callable]] = defaultdict(list)
    def subscribe(self, topic, fn): self.subs[topic].append(fn)
    def publish(self, topic, msg):
        for fn in self.subs[topic]:
            fn(msg)

bus = Bus()
bus.subscribe("user.created", lambda u: print(f"welcome {u}"))
bus.publish("user.created", "alice")
```

### Redis Pub/Sub
```python
import redis, json
r = redis.Redis()

# Publisher
r.publish("orders.created", json.dumps({"id": 42, "total": 99}))

# Subscriber
ps = r.pubsub()
ps.subscribe("orders.*")
for msg in ps.listen():
    if msg["type"] == "pmessage":
        handle(json.loads(msg["data"]))
```

### Kafka producer/consumer (Python)
```python
from confluent_kafka import Producer, Consumer

p = Producer({"bootstrap.servers": "localhost:9092"})
p.produce("orders", key="42", value=b'{"total":99}')
p.flush()

c = Consumer({
    "bootstrap.servers": "localhost:9092",
    "group.id": "fulfillment",
    "auto.offset.reset": "earliest",
})
c.subscribe(["orders"])
while True:
    msg = c.poll(1.0)
    if msg and not msg.error():
        process(msg.value())
        c.commit(msg)
```

### NATS with subject wildcards
```python
import nats, asyncio

async def main():
    nc = await nats.connect("nats://localhost:4222")
    async def cb(msg): print(msg.subject, msg.data)
    await nc.subscribe("orders.*.created", cb=cb)
    await nc.publish("orders.US.created", b'{"id":42}')
    await asyncio.sleep(1)

asyncio.run(main())
```

### Google Cloud Pub/Sub
```python
from google.cloud import pubsub_v1

publisher = pubsub_v1.PublisherClient()
topic = publisher.topic_path("proj", "orders")
publisher.publish(topic, b'{"id":42}', region="us-east1")

sub = pubsub_v1.SubscriberClient()
sub_path = sub.subscription_path("proj", "fulfillment-sub")
def cb(msg): handle(msg.data); msg.ack()
sub.subscribe(sub_path, callback=cb).result()
```

### AsyncAPI schema (governance, 2026)
```yaml
asyncapi: 3.0.0
channels:
  ordersCreated:
    address: orders.created
    messages:
      OrderCreated:
        payload:
          type: object
          properties:
            id: {type: integer}
            total: {type: number}
```

## 매 결정 기준
| 상황 | Approach |
|---|---|
| 매 in-process | Bus / EventEmitter |
| 매 ephemeral, low-latency | Redis Pub/Sub / NATS |
| 매 durable, replay 필요 | Kafka / Pulsar |
| 매 cloud-native, managed | Google Pub/Sub / AWS SNS+SQS |
| 매 IoT / mobile | MQTT |
| 매 fan-in-out, transform | Kafka Streams / Pulsar Functions |

**기본값**: 매 production EDA — Kafka. 매 simple/ephemeral — NATS.

## 🔗 Graph
- 부모: [[Event Driven Architecture]]
- 변형: [[Observer Pattern]] · [[Event Bus]]
- 응용: [[Event Sourcing]] · [[CQRS]] · [[CDC]]
- Adjacent: [[Kafka]] · [[NATS]] · [[Redis]] · [[MQTT]]

## 🤖 LLM 활용
**언제**: 매 schema design (AsyncAPI generation), 매 consumer code scaffolding, 매 dead-letter analysis.
**언제 X**: 매 broker selection 매 trust 의 X — workload metrics 직접 측정.

## ❌ 안티패턴
- **Sync pub-sub**: 매 publisher block on slow subscriber — 매 async / queue 사용.
- **No schema**: 매 consumer breakage — Avro/Protobuf + registry 필수.
- **Topic explosion**: 매 user-per-topic — 매 millions of topics, broker 죽음. 매 partition / filter 사용.
- **Duplicate semantics**: 매 at-least-once 인데 매 idempotency 없음 — duplicate processing.

## 🧪 검증 / 중복
- Verified (Eugster et al. — "The Many Faces of Publish/Subscribe" 2003; Kafka docs).
- 신뢰도 A.

## 🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — full pub-sub pattern entry |