How to solve the consistency problem when using Kafka transactions between two services?

To ensure consistency when using Kafka transactions between two services, it is important to apply an approach that guarantees atomicity of operations and consistency of state. One common method is to use the "two-phase commit" pattern or implement idempotent operations with Kafka transactions.

Main recommendations:

• Use Kafka Producer with transactions enabled (initTransactions(), beginTransaction(), commitTransaction(), abortTransaction()). This guarantees that messages are either fully written or not written at all.
• In services that process messages, apply idempotency to prevent repeated processing from leading to inconsistent states.
• For coordination between two services, you can use a "consume-transform-produce" scheme with transactions: Service 1 sends a message to a transactional topic, Service 2 reads this message and publishes the result within its transaction. If one of the transactions does not complete, changes are not committed.
• Consider using Kafka Streams API, which supports transactional operations and provides Exactly-Once semantics.

Example of using transactions in Java Kafka Producer:

Properties props = new Properties();
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());
props.put(ProducerConfig.ENABLE_IDEMPOTENCE_CONFIG, "true");
props.put(ProducerConfig.TRANSACTIONAL_ID_CONFIG, "my-transactional-id");

KafkaProducer<String, String> producer = new KafkaProducer<>(props);
producer.initTransactions();

try {
    producer.beginTransaction();
    producer.send(new ProducerRecord<>("topic1", "key", "value1"));
    producer.send(new ProducerRecord<>("topic2", "key", "value2"));
    producer.commitTransaction();
} catch (Exception e) {
    producer.abortTransaction();
}

Thus, Kafka transactions allow ensuring consistency between services if the message processing and publishing logic are properly organized.