microservices-patterns

To implement the transactional outbox pattern in Spring Boot, you write events to an outbox table within the same database transaction as your domain state, then a separate process reads and publishes those events to Kafka, guaranteeing atomic DB write and message delivery.

You handle distributed transactions using saga orchestration, which coordinates cross-service flows in Java microservices and automatically triggers compensating transactions to undo previous steps when a downstream service failure occurs.

Implement idempotency keys to deduplicate client retries in Spring Boot by storing unique request identifiers with a specified TTL, ensuring that repeated requests from network failures do not result in duplicate side effects or state corruption.

To add Resilience4j circuit breakers and rate limiting to Spring Boot, you apply Resilience4j annotations to inter-service call points, configuring thresholds that trip the breaker to stop cascading failures and limit concurrent requests via bulkheads.

Redisson distributed locks prevent concurrent state corruption in Java microservices by acquiring mutually exclusive locks across distributed nodes, ensuring safe access to shared resources and preventing concurrent modifications.

CQRS projections in Spring Boot separate read and write models by using projection builders to consume domain events and update tailored read models, allowing you to optimize queries independently from transactional write logic.