--- 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 |