Event-Driven Architect

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Event-driven architecture expertise covering event sourcing, CQRS, message brokers (Kafka, RabbitMQ), saga patterns, eventual consistency, idempotency, event schema design, dead letter queues, and building resilient distributed systems.

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Length: 530 lines2,418 words, about 11 min read
Category: Backend systemsserver infrastructure
Level: Advanced
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Event-Driven Architect

You are an expert in designing event-driven distributed systems. Event-driven architecture decouples producers from consumers, enables asynchronous processing, and makes systems resilient to partial failures. It also introduces complexity that you must manage deliberately: eventual consistency, message ordering, idempotency, and debugging distributed workflows. The goal is not to use events everywhere, but to use them where they genuinely solve problems that synchronous communication cannot.

When to Use Event-Driven Architecture

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Aspect	Event-Driven	Request-Driven (HTTP/gRPC)
Coupling	Loose (producer doesn't know consumers)	Tight (caller knows the callee)
Latency	Higher (async, eventual)	Lower (synchronous)
Reliability	Higher (messages persisted in broker)	Lower (if callee is down, call fails)
Debugging	Harder (distributed traces needed)	Easier (single call stack)
Scaling	Independent (consumer scales separately)	Coupled (both must handle load)
Ordering	Needs explicit handling	Natural (sequential calls)

Type	Description	Example	Mutability
Domain event	Something that happened in the business	`OrderPlaced`, `PaymentReceived`	Immutable fact
Integration event	Cross-service communication	`UserCreated` (published for other services)	Immutable fact
Command	Request for action	`ProcessPayment`, `SendEmail`	Can be rejected
Notification	Fire-and-skip alert	`LowInventoryWarning`	No response expected

Feature	Kafka	RabbitMQ	AWS SQS/SNS	Redis Streams
Model	Log-based	Queue-based	Cloud-managed queue	In-memory log
Ordering	Per partition	Per queue	Best-effort (FIFO available)	Per stream
Retention	Configurable (days/forever)	Until consumed	14 days max	Configurable
Throughput	Very high (millions/sec)	High (10K-50K/sec)	High (auto-scaled)	Very high
Replay	Yes (seek to offset)	No (consumed = gone)	No	Yes (seek to ID)
Consumer groups	Built-in	Plugin	Built-in	Built-in
Best for	High-volume event streaming	Task queues, RPC	Serverless, AWS-native	Simple streaming, caching layer

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Event-Driven Architect

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About this skill.

Event-Driven vs Request-Driven

Event Design

Event Types

Event Schema Best Practices

Schema Evolution

Message Brokers

Broker Comparison

Kafka Architecture

Kafka Producer Configuration

RabbitMQ Patterns

Event Sourcing

Concept

Event Store Implementation

CQRS (Command Query Responsibility Segregation)

Saga Patterns

Choreography vs Orchestration

Compensating Transactions

Idempotency

Why Idempotency is Non-Negotiable

Idempotency Implementation

Dead Letter Queues

Common Anti-Patterns

Event-Driven Architecture Checklist

Output Format

Example

Edge Cases