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Event-Driven Architecture

ArchitectureDesign PatternsđŸŸĸ Free Lesson

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Architecture

Event-Driven Architecture

Event-driven systems communicate through events — immutable records of things that happened. This decouples producers from consumers and enables reactive, scalable architectures.

  • Events — Immutable facts about state changes
  • Event Sourcing — Store events instead of current state
  • CQRS — Separate read and write models

Event-driven architecture trades consistency for scalability and resilience.

What Is Event-Driven Architecture?

An architectural pattern where components communicate by producing and consuming events through a message broker.

Event-Driven ArchitectureProducersOrder ServicePayment SvcUser ServiceMessage BrokerKafka / RabbitMQTopic: ordersTopic: paymentsTopic: usersConsumersNotificationAnalyticsInventoryProducers and consumers are fully decoupled via the message broker

Event Sourcing

Event Store

CQRS

Separating read and write models for independent optimization.

CQRS PatternCommand Side (Write)CommandsAggregate / DomainEvent StoreEvent BusKafkaEventsQuery Side (Read)Event Handlers → Read ModelsUser ViewOrder ViewSearch ViewAnalytics ViewEach read model optimized for specific query patterns

Saga Pattern

Managing distributed transactions across services.

Choreography vs Orchestration

ApproachDescriptionProsCons
ChoreographyEach service listens for events and reactsLoose coupling, simpleHard to track flow, cyclic deps
OrchestrationCentral coordinator directs the flowClear flow, easy to modifySingle point of failure, tight coupling

Practice Exercises

  1. Design: Design an event-driven architecture for an e-commerce order flow: order placement, payment, inventory reservation, shipping. Include event schemas and saga steps.

  2. Event Sourcing: Implement event sourcing for a bank account. Events: AccountCreated, Deposited, Withdrawn, Transferred. Derive current balance by replaying events.

  3. CQRS: Design CQRS for a social media feed. The write side handles posts; the read side materializes personalized feeds. How do you handle fan-out?

  4. Trade-offs: Compare event-driven architecture with synchronous REST for a ride-sharing app. Which components benefit from events? Which should remain synchronous?


What to Learn Next

-> Service Mesh Envoy, Istio, and sidecar proxy patterns.

-> Data Replication Leader-follower, multi-leader, and conflict resolution.

-> Distributed Consensus Raft, Paxos, and leader election algorithms.

-> Containerization Docker, Kubernetes, and pod scheduling.

-> CI/CD Pipelines Continuous integration and deployment strategies.

-> Observability Logging, metrics, tracing, and monitoring.

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