Транзакционная публикация событий и исходящие сообщения
Гарантируйте доставку событий с помощью реестра публикаций событий и шаблона транзакционных исходящих сообщений.
«Транзакционная публикация событий и исходящие сообщения» — бесплатный урок Spring Boot 4 Complete Guide на CoddyKit. Это урок 3 из 4. Ты можешь прочитать весь урок бесплатно ниже — а потом практиковать его прямо в браузере с встроенным редактором кода и ИИ-репетитором 24/7. Это часть пути обучения Spring Boot 4 Complete Guide, и твой прогресс синхронизируется между веб-версией и приложением CoddyKit. Курс Spring Boot 4 Complete Guide содержит 4 уроков всего.
Части этого урока еще не переведены и отображаются на английском.
Why Events Get Lost
In an event-driven Spring Modulith application, modules talk to each other by publishing application events. A module raises an event inside a transaction, and listeners in other modules react to it.
The danger: by default, when you publish an event and a listener processes it asynchronously (or in a separate transaction), the listener's work can fail after the publisher already committed. The result is a lost event — the publisher's state changed, but the downstream side effect never happened.
- Publisher commits an
Orderas PAID. - The async listener that sends a confirmation email crashes.
- Nobody retries — the customer never gets the email.
This lesson shows how Spring Modulith's Event Publication Registry implements the transactional outbox pattern to guarantee delivery.
The Transactional Outbox Pattern
The transactional outbox pattern solves the dual-write problem: you must atomically (1) change your business state and (2) record that an event needs to be delivered.
Instead of trying to write to the database and a message broker in one transaction (impossible without distributed transactions), you write both into the same database in the same local transaction:
- The business change (e.g. the order row).
- A row in an outbox table describing the event.
A separate process then reads unprocessed outbox rows and delivers them, marking each as completed. Because the outbox write shares the business transaction, an event is recorded if and only if the business change committed.
Spring Modulith's Event Publication Registry
Spring Modulith ships a ready-made outbox: the Event Publication Registry. When an event has a transactional listener (annotated with @ApplicationModuleListener), Modulith automatically:
- Writes an event publication row before the listener runs.
- Marks it completed when the listener finishes successfully.
- Leaves it incomplete if the listener throws — so it can be retried.
You enable it by adding the starter and a persistence module. The registry persists publications in a table such as event_publication.
<dependency>
<groupId>org.springframework.modulith</groupId>
<artifactId>spring-modulith-starter-jpa</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.modulith</groupId>
<artifactId>spring-modulith-events-jpa</artifactId>
</dependency>@ApplicationModuleListener
The key annotation is @ApplicationModuleListener. It is a composed annotation that combines three behaviors:
@Async— the listener runs on a separate thread, decoupling modules.@Transactional(propagation = REQUIRES_NEW)— the listener runs in its own transaction.@TransactionalEventListener(phase = AFTER_COMMIT)— it fires only after the publisher's transaction commits.
Combined with the registry on the classpath, every event handled by such a listener gets an outbox entry. If the listener fails, the publication stays incomplete and survives restarts.
@Component
class OrderNotifications {
@ApplicationModuleListener
void on(OrderCompleted event) {
// runs async, in a NEW transaction, after the publisher committed
emailService.sendConfirmation(event.orderId());
}
}Publishing the Event
The publishing side stays simple. Inside a normal @Transactional service method you call ApplicationEventPublisher.publishEvent(...). Spring Modulith intercepts the publication and, because there is a transactional module listener, writes the outbox row in the same transaction as your business change.
Use immutable Java records for events — they are concise, serializable, and clearly value-typed.
public record OrderCompleted(String orderId) {}
@Service
class OrderService {
private final OrderRepository orders;
private final ApplicationEventPublisher events;
OrderService(OrderRepository orders, ApplicationEventPublisher events) {
this.orders = orders;
this.events = events;
}
@Transactional
public void complete(String orderId) {
Order order = orders.findById(orderId).orElseThrow();
order.markCompleted(); // business change
events.publishEvent(new OrderCompleted(orderId)); // outbox row, same tx
}
}How the Atomicity Works
Here is the crucial sequence that guarantees delivery:
- Your
complete()method opens a transaction and changes the order. publishEventcauses Modulith to INSERT an incomplete event_publication row in that same transaction.- The transaction commits — order change and outbox row land together, atomically.
- After commit, the
@ApplicationModuleListenerruns in a new transaction. - On success, the publication is marked completed.
If the JVM crashes between commit and listener success, the row is still incomplete in the database, ready to be republished. No event is ever silently dropped.
The event_publication Table
The JPA persistence module stores publications in a table. Each row identifies a serialized event and its target listener, plus timestamps. Knowing the schema helps you reason about retries and monitoring.
id— UUID primary key.listener_id— fully-qualified listener method that must handle it.event_type+serialized_event— the event payload (JSON by default via Jackson).publication_date— when it was created.completion_date— NULL while incomplete; set when the listener succeeds.
A row with completion_date IS NULL is an outstanding event awaiting (re)delivery.
CREATE TABLE event_publication (
id UUID NOT NULL,
listener_id TEXT NOT NULL,
event_type TEXT NOT NULL,
serialized_event TEXT NOT NULL,
publication_date TIMESTAMP WITH TIME ZONE NOT NULL,
completion_date TIMESTAMP WITH TIME ZONE,
PRIMARY KEY (id)
);Republishing on Startup
Incomplete publications are useless unless something retries them. Spring Modulith can republish outstanding events on application startup, which recovers from crashes that happened mid-delivery.
Enable it in application.properties:
spring.modulith.republish-outstanding-events-on-restart=true
On boot, Modulith reads all incomplete event_publication rows and re-invokes their listeners. Because listeners should be idempotent, replaying a partially-processed event is safe.
# application.properties
spring.modulith.republish-outstanding-events-on-restart=true
# optional: also serialize events as JSON columns you can query
spring.modulith.events.jdbc.schema-initialization.enabled=trueIdempotent Listeners
Because an event may be delivered more than once (retry after a crash, or scheduled resubmission), the at-least-once guarantee forces your listeners to be idempotent. Processing the same event twice must produce the same end state as processing it once.
Common techniques:
- Use a natural business key (the order id) and check whether the side effect already happened.
- Track processed event ids in a dedup table with a unique constraint.
- Make the operation naturally idempotent (UPSERT, or set-to-state instead of increment).
@Component
class InventoryAdjuster {
private final ProcessedEventRepository processed;
@ApplicationModuleListener
void on(OrderCompleted event) {
// skip if we've already handled this exact event
if (!processed.markIfNew(event.orderId())) {
return;
}
inventory.release(event.orderId());
}
}Scheduled Resubmission of Incomplete Events
Startup republishing only helps when you restart. For long-running services you also want periodic recovery of stuck publications (e.g. a listener that threw a transient error). Modulith offers a completion / resubmission scheduler.
spring.modulith.events.completion-mode— controls whether completed rows are deleted, archived, or updated.- Enable a recurring resubmission so incomplete events older than a threshold are retried automatically.
Combined with idempotency, this turns the outbox into a self-healing delivery channel without a separate message broker.
# application.properties
spring.modulith.events.republish-outstanding-events-on-restart=true
spring.modulith.events.completion-mode=update
# resubmit publications still incomplete after this interval
spring.modulith.events.republish-outstanding-events.interval=PT10MFrom Outbox to External Broker
The same registry bridges to external messaging. Spring Modulith provides externalization modules (Kafka, RabbitMQ, AMQP, SQS, etc.). You annotate an event with @Externalized, and a transactional listener publishes it to the broker — backed by the very same outbox.
This means the at-least-once guarantee extends across process boundaries: the broker send is itself an event publication that is only marked complete once the message is accepted by the broker.
import org.springframework.modulith.events.Externalized;
@Externalized("orders.completed::#{orderId()}")
public record OrderCompleted(String orderId) {}
// add: spring-modulith-events-kafka
// spring.modulith routes the event to topic "orders.completed"
// keyed by orderId, only after the publishing tx commitsQuick Check
Test your understanding of the transactional outbox guarantee.
Recap
You learned how to guarantee event delivery in Spring Modulith using the transactional outbox pattern:
- The Event Publication Registry persists an
event_publicationrow in the same transaction as your business change — solving the dual-write problem. @ApplicationModuleListener= async + REQUIRES_NEW transaction + AFTER_COMMIT, so listeners run after the publisher commits and get their own outbox entry.- A publication is incomplete until its listener succeeds (
completion_date IS NULL); failures leave it for retry. - Republish on restart and scheduled resubmission recover stuck events — making delivery at-least-once.
- Because delivery is at-least-once, listeners must be idempotent.
@Externalizedbridges the same outbox to Kafka/RabbitMQ/SQS for cross-process guarantees.
Часто задаваемые вопросы
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Чему я научусь в уроке «Транзакционная публикация событий и исходящие сообщения»?
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Все уроки этого курса
- Модули приложения и проверка границ
- Внутренние события приложения и слушатели
- Транзакционная публикация событий и исходящие сообщения
- Интеграционное тестирование модулей и сценарии