Can I use this for local application events without Kafka?

Absolutely. The skill covers both local ApplicationEvent patterns for internal decoupling and distributed Kafka patterns for cross-service communication.

Does it include testing strategies for event-driven systems?

Yes, the skill includes patterns for unit testing domain events and integration testing event handlers using Mockito and Testcontainers.

Does this skill support Spring Boot 3.x?

Yes, this skill is specifically designed for Spring Boot 3.x and leverages modern functional programming styles for event consumers.

How does this skill ensure message delivery reliability?

It provides implementation patterns for the Transactional Outbox pattern, ensuring that messages are only sent to Kafka after the local database transaction has successfully committed.

Spring Boot Event-Driven Patterns

Name: Spring Boot Event-Driven Patterns
Author: pur3v4d3r

bypur3v4d3r

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API Development

Implements Event-Driven Architecture (EDA) patterns in Spring Boot applications using Kafka, domain events, and transactional listeners.

About

This skill provides specialized guidance for building loosely-coupled, scalable microservices using Event-Driven Architecture (EDA) within the Spring Boot ecosystem. It enables developers to implement robust domain event publishing from aggregate roots, handle local events with transactional consistency using @TransactionalEventListener, and scale to distributed messaging via Kafka and Spring Cloud Stream. By incorporating advanced patterns like the Transactional Outbox, the skill ensures reliable event delivery and data consistency across complex distributed systems while following Domain-Driven Design (DDD) best practices.

Key Features

Transactional event listeners for consistent post-commit processing
1 GitHub stars
Distributed messaging integration with Kafka and Spring Cloud Stream
Reliable event delivery via the Transactional Outbox pattern
Implementation of DDD-based aggregate roots with event publishing
Standardized templates for domain events and DTO mapping

Use Cases

Building reactive, event-streamed systems with high availability
Ensuring consistency between database updates and external system notifications
Decoupling microservices through asynchronous event-based communication

About

Key Features

Transactional event listeners for consistent post-commit processing
1 GitHub stars
Distributed messaging integration with Kafka and Spring Cloud Stream
Reliable event delivery via the Transactional Outbox pattern
Implementation of DDD-based aggregate roots with event publishing
Standardized templates for domain events and DTO mapping

Use Cases

Building reactive, event-streamed systems with high availability
Ensuring consistency between database updates and external system notifications
Decoupling microservices through asynchronous event-based communication