event-driven-architecture_skill

Overview

This skill provides practical guidance for designing, implementing, and operating event-driven architectures using event sourcing, CQRS, sagas, and message-driven communication. It focuses on patterns and operational practices that enable scalable, loosely coupled, and eventually consistent distributed systems. Use it when you need auditability, high throughput, or resilient cross-service workflows.

How this skill works

The skill helps you identify domain events, design immutable event schemas with versioning and correlation IDs, and choose patterns (event sourcing, CQRS, choreography/orchestration, sagas) that match your requirements. It recommends infrastructure choices (Kafka, RabbitMQ, managed cloud services), outlines implementation details like append-only event stores, idempotent handlers, and read-model projections, and covers operation needs such as monitoring, replay, and schema management.

When to use it

• Designing asynchronous, decoupled microservices or distributed systems
• Implementing event sourcing for audit trails and temporal queries
• Applying CQRS to scale read models independently from writes
• Coordinating distributed transactions using sagas or compensations
• Building real-time event streams, data pipelines, or pub/sub systems

Best practices

• Model events as immutable, past-tense facts with correlation and causation IDs
• Design idempotent handlers and assume at-least-once delivery
• Version event schemas and support multiple versions during migration
• Partition by aggregate ID for scalability and keep event stores append-only
• Implement monitoring for event lag, processing errors, and throughput
• Provide replay capability and a schema registry for safe evolution

Example use cases

• E-commerce orders: OrderCreated events, payment sagas, and read-models for customer portals
• Financial ledgers: Event sourcing for auditability and temporal balance queries
• Inventory systems: CQRS read stores for fast queries and event streams for updates
• Cross-service workflows: Saga coordination for multi-step business processes
• Analytics pipelines: Kafka-based event streams feeding real-time dashboards