event-driven-architecture-expert

license	Apache-2.0
name	event-driven-architecture-expert
description	Message queues, pub/sub, event sourcing with Kafka, RabbitMQ, Redis Streams. Activate on: event-driven, message queue, pub/sub, Kafka, RabbitMQ, event bus, async messaging, dead letter queue. NOT for: CQRS projections (use cqrs-event-sourcing-architect), real-time WebSocket (use websocket-realtime-expert), observability (use observability-apm-expert).
allowed-tools	Read,Write,Edit,Bash(npm:*,npx:*,docker:*)
category	Backend & Infrastructure
tags	["event-driven","kafka","messaging","pub-sub","rabbitmq"]
pairs-with	[{"skill":"cqrs-event-sourcing-architect","reason":"Event sourcing builds on event-driven foundations"},{"skill":"streaming-pipeline-architect","reason":"Streaming pipelines consume event-driven sources"},{"skill":"observability-apm-expert","reason":"Distributed tracing across async event flows"}]

Event-Driven Architecture Expert

Design and implement resilient message-driven systems using Kafka, RabbitMQ, Redis Streams, and cloud-native event buses.

Activation Triggers

Activate on: "event-driven", "message queue", "pub/sub", "Kafka", "RabbitMQ", "event bus", "async messaging", "dead letter queue", "event broker", "fan-out", "Redis Streams"

NOT for: CQRS projections/event stores → cqrs-event-sourcing-architect | WebSocket real-time → websocket-realtime-expert | Distributed tracing → observability-apm-expert

Quick Start

1. Identify event boundaries — map domain events to bounded contexts
2. Choose broker — Kafka for ordered logs, RabbitMQ for routing flexibility, Redis Streams for lightweight queues
3. Define event schemas — use CloudEvents spec with JSON Schema or Avro
4. Implement idempotent consumers — design for at-least-once delivery
5. Configure DLQ and retry policies — never silently drop messages

Core Capabilities

Domain	Technologies
Message Brokers	Apache Kafka 3.8+, RabbitMQ 4.x, Redis Streams 7.4
Cloud-Native	AWS EventBridge, GCP Pub/Sub, Azure Service Bus
Schema Registry	Confluent Schema Registry, AWS Glue, Apicurio
Serialization	CloudEvents 1.0, Avro, Protobuf, JSON Schema
Frameworks	KafkaJS, amqplib, BullMQ 5.x, Temporal

Architecture Patterns

Fan-Out with Dead Letter Queue

Producer → Topic/Exchange
              ├─→ Consumer A (order-service)
              ├─→ Consumer B (notification-service)
              └─→ Consumer C (analytics-service)
                       ↓ (failure after 3 retries)
                   Dead Letter Queue → Alert + Manual Review

Transactional Outbox Pattern

Avoid dual-write problems by writing events to an outbox table within the same DB transaction, then polling/CDC to publish:

┌─────────────────────────────┐
│  BEGIN TRANSACTION          │
│  INSERT INTO orders (...)   │
│  INSERT INTO outbox (       │
│    event_type, payload,     │
│    published_at = NULL      │
│  )                          │
│  COMMIT                     │
└─────────────────────────────┘
         ↓ (CDC / Poller)
   Kafka / RabbitMQ Topic