spring-kafka

To configure an idempotent Kafka producer in Spring Boot, you enable producer idempotence with acks=all alongside batching and compression. This ensures reliable event delivery by preventing duplicate messages during network retries.

You handle consumer failures and route messages to a Dead Letter Topic in Spring Boot using DefaultErrorHandler with DeadLetterPublishingRecoverer. This pattern routes failed events to topic.DLT after exhausting configurable retries with exponential backoff.

The transactional outbox pattern for Kafka event publishing atomically combines database writes with event delivery. It guarantees at-least-once delivery by storing events in an outbox table before publishing them to Kafka from your Spring Boot service.

You ensure idempotent Kafka consumer processing in Java by using a deduplication table to track processed event IDs. This prevents duplicate processing of redelivered messages when consuming events with manual offset acknowledgment.

Yes, this Kafka configuration works with Java 21 and Spring Boot 3.x, specifically targeting banking platforms. It handles topic configuration, partitioning, and consumer group processing for financial workloads like TransactionCreatedEvent.

Your Kafka consumer processes duplicate messages during retries because of at-least-once delivery guarantees. You can prevent this by implementing idempotent consumers via a deduplication table alongside manual offset acknowledgment.