// Live Demo
Click each layer to expand deeper content
◱ SURFACE LAYER
Microservices Architecture Overview
Our system uses event-driven microservices to scale independently. Services communicate via message queues, ensuring loose coupling and high fault tolerance. This architecture allows us to deploy updates without system-wide downtime.
Our system uses event-driven microservices to scale independently. Services communicate via message queues, ensuring loose coupling and high fault tolerance. This architecture allows us to deploy updates without system-wide downtime.
◧ INTERMEDIATE LAYER
Implementation Details
The architecture consists of 12 core services: API Gateway, Auth Service, User Management, Payment Processing, Notification Service, and more. We use RabbitMQ for asynchronous messaging with a fanout exchange pattern for broadcast events.
Each service maintains its own PostgreSQL database, and we implement eventual consistency through event sourcing. Circuit breakers (Hystrix patterns) prevent cascading failures.
The architecture consists of 12 core services: API Gateway, Auth Service, User Management, Payment Processing, Notification Service, and more. We use RabbitMQ for asynchronous messaging with a fanout exchange pattern for broadcast events.
Each service maintains its own PostgreSQL database, and we implement eventual consistency through event sourcing. Circuit breakers (Hystrix patterns) prevent cascading failures.
■ DEEP LAYER
Technical Specifications
Message Format: JSON schema v4 with Avro serialization
Queue Configuration: RabbitMQ 3.12, cluster mode with quorum queues
Retry Policy: Exponential backoff starting at 100ms, max 3 attempts
Dead Letter: Failed events route to dlq.{service}.retry queue
Message Format: JSON schema v4 with Avro serialization
Queue Configuration: RabbitMQ 3.12, cluster mode with quorum queues
Retry Policy: Exponential backoff starting at 100ms, max 3 attempts
Dead Letter: Failed events route to dlq.{service}.retry queue
// Event publishing pattern
await eventBus.publish('user.created', {
userId: user.id,
timestamp: Date.now(),
correlationId: uuid()
});
■ EXPERT NOTES
Edge Cases & Gotchas
• Message ordering: Use consistent hashing keys for user-scoped events
• Idempotency: All handlers must check event IDs to prevent duplicate processing
• Monitoring: Track queue depths, consumer lag, and processing latency
• Schema evolution: Use Avro's backward/forward compatibility rules
This layer contains tribal knowledge usually lost in Slack messages and hallway conversations.
• Message ordering: Use consistent hashing keys for user-scoped events
• Idempotency: All handlers must check event IDs to prevent duplicate processing
• Monitoring: Track queue depths, consumer lag, and processing latency
• Schema evolution: Use Avro's backward/forward compatibility rules
This layer contains tribal knowledge usually lost in Slack messages and hallway conversations.