using-message-queueslisted

# Message Queues Implement asynchronous communication patterns for event-driven architectures, background job processing, and service decoupling. ## When to Use This Skill Use message queues when: - **Long-running operations** block HTTP requests (report generation, video processing) - **Service decoupling** required (microservices, event-driven architecture) - **Guaranteed delivery** needed (payment processing, order fulfillment) - **Event streaming** for analytics (log aggregation, metrics pipelines) - **Workflow orchestration** for complex processes (multi-step sagas, human-in-the-loop) - **Background job processing** (email sending, image resizing) ## Broker Selection Decision Tree Choose message broker based on primary need: ### Event Streaming / Log Aggregation **→ Apache Kafka** - Throughput: 500K-1M msg/s - Replay events (event sourcing) - Exactly-once semantics - Long-term retention - Use: Analytics pipelines, CQRS, event sourcing ### Simple Background Jobs **→ Task Queues** - **Python** → Celery + Redis - **TypeScript** → BullMQ + Redis - **Go** → Asynq + Redis - Use: Email sending, report generation, webhooks ### Complex Workflows / Sagas **→ Temporal** - Durable execution (survives restarts) - Saga pattern support - Human-in-the-loop workflows - Use: Order processing, AI agent orchestration ### Request-Reply / RPC Patterns **→ NATS** - Built-in request-reply - Sub-millisecond latency - Cloud-native, simple operations - Use: Microservices RPC, IoT command/