event-driven
Event-driven architecture patterns and best practices. Covers Saga, Outbox, CQRS, Event Sourcing, and messaging patterns for distributed systems. USE WHEN: user mentions "event-driven", "Saga", "Outbox pattern", "CQRS", "Event Sourcing", "distributed transactions", "eventual consistency", "message broker", "event bus", asks about "microservices communication", "async patterns", "compensating transactions" DO NOT USE FOR: Simple pub/sub - use messaging framework skills (Kafka, RabbitMQ), REST APIs - use API design skills, Real-time updates - use WebSocket skills, Basic async/await - use language-specific skills
What this skill does
# Event-Driven Architecture Core Knowledge
> **Full Reference**: See [advanced.md](advanced.md) for Saga implementations (Node.js, Java), Outbox pattern implementations, Event Sourcing, CQRS, and idempotency patterns.
> **Deep Knowledge**: Use `mcp__documentation__fetch_docs` with technology: `event-driven` for comprehensive documentation.
## When NOT to Use This Skill
- **Monolithic applications** - Use simple in-process events
- **Simple CRUD operations** - Use REST APIs or GraphQL
- **Real-time UI updates** - Use WebSockets or SSE
- **Synchronous workflows** - Use traditional transactions
## Architecture Patterns Overview
| Pattern | Purpose | Complexity |
|---------|---------|------------|
| **Pub/Sub** | Decouple producers from consumers | Low |
| **Event Sourcing** | Store state as event sequence | High |
| **CQRS** | Separate read/write models | Medium-High |
| **Saga** | Distributed transactions | High |
| **Outbox** | Reliable event publishing | Medium |
## Saga Pattern
Manages distributed transactions across services without 2PC.
### Choreography Saga
```
┌─────────┐ event ┌─────────┐ event ┌─────────┐
│Order Svc│────────────▶│Payment │────────────▶│Inventory│
└─────────┘ │ Svc │ │ Svc │
▲ └─────────┘ └─────────┘
│ compensate │ compensate │
└───────────────────────┴───────────────────────┘
```
### Orchestration Saga
```
┌─────────────┐
│ Saga │
│Orchestrator │
└─────────────┘
/ | \
▼ ▼ ▼
┌───────┐ ┌───────┐ ┌───────┐
│Order │ │Payment│ │Invent.│
└───────┘ └───────┘ └───────┘
```
## Transactional Outbox Pattern
Ensures reliable event publishing with database transactions.
```
┌────────────────────────────────────────────┐
│ Database Transaction │
│ ┌──────────────┐ ┌──────────────────┐ │
│ │ Business │ │ Outbox Table │ │
│ │ Table │ │ (messages) │ │
│ └──────────────┘ └──────────────────┘ │
└────────────────────────────────────────────┘
│
Polling Relay / CDC
│
┌─────────────────┐
│ Message Broker │
└─────────────────┘
```
### Outbox Table Schema
```sql
CREATE TABLE outbox (
id UUID PRIMARY KEY,
aggregate_type VARCHAR(255) NOT NULL,
aggregate_id VARCHAR(255) NOT NULL,
event_type VARCHAR(255) NOT NULL,
payload JSONB NOT NULL,
status VARCHAR(50) DEFAULT 'PENDING',
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
```
## CQRS Architecture
```
Commands Queries
│ │
▼ ▼
┌───────────────┐ ┌───────────────┐
│ Command Model │ │ Query Model │
│ (Write) │ │ (Read) │
└───────────────┘ └───────────────┘
│ ▲
▼ │
┌───────────────┐ Events ┌───────────────┐
│ Write Store │───────────────▶│ Read Store │
└───────────────┘ └───────────────┘
```
## Anti-Patterns
| Anti-Pattern | Why It's Bad | Solution |
|--------------|--------------|----------|
| **Event Soup** | Too many fine-grained events | Design coarse-grained domain events |
| **Missing Idempotency** | Duplicate processing | Add idempotency keys |
| **No Compensation Logic** | Failed saga can't rollback | Implement compensating transactions |
| **No Dead Letter Queue** | Failed events lost | Configure DLQ for error handling |
| **Weak Event Ordering** | Race conditions | Use partitioning or ordered queues |
## Quick Troubleshooting
| Issue | Diagnostic | Solution |
|-------|------------|----------|
| **Lost events** | Check message broker | Implement Outbox pattern |
| **Duplicate processing** | Logs show multiple executions | Add idempotency checks |
| **Saga stuck** | Compensation not triggered | Add timeout handling |
| **Growing DLQ** | Many failed messages | Analyze failures, fix consumers |
| **Slow event processing** | High message lag | Scale consumers, optimize handlers |
## Best Practices
### Message Design
- Include correlation ID for tracing
- Version your events for evolution
- Keep payloads small, reference large data
### Error Handling
- Implement retry with exponential backoff
- Use Dead Letter Queues for failed messages
- Set up alerting on DLQ growth
### Monitoring
- Track message lag
- Monitor consumer group health
- Alert on processing errors
- Trace message flow across services
## Reference Documentation
Available topics: `patterns`, `saga`, `outbox`, `cqrs`
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