Resolving Kafka Stream Producer Fenced Exception During State Store Update in Migration from Kafka Streams 2.5.0 to 3.3.1

Problem:

During a migration from Kafka Streams 2.5.0 to 3.3.1, a client encounters a “Producer Fenced Exception” while processing aggregation tasks using a Processor in Kafka Streams. The issue occurs when attempting to update a State Store changelog topic, initiated by operations reading data from upstream and processing it with a punctuator.

Process:

Questions:

1. Should Kafka Streams control transaction time for State Store topics? Why does the client get this exception?
2. How can the client ensure that all operations executed in a punctuator will be executed inside the transaction timeout?
3. How can the client write safe Processors if Kafka Streams API does not give control about background operations?
4. Is there a way to solve this issue without code changes? Considering that all punctuator code is executed in less than 1/4 the transaction time.

Solution:

1. Ensure that clocks of Kafka cluster and brokers are synchronized.
2. Make sure each broker has a unique ID.
3. Update the client version of Kafka to match the brokers.
4. Investigate if brokers have duplicate IDs or if clocks are not synced.
5. Empty and discard topics created on an old version of Kafka; create and use new ones.

When brokers are misconfigured or miscoded, duplicates may occur. The most common cause is mismanagement of consumer and consumer group IDs. Consumers within the same group should not consume duplicate messages. It’s crucial to ensure that all client and server components are running the same version. Unfortunately, if misconfigurations occur on the broker side, duplicates may happen, and there’s limited control on the streamer’s end to prevent them. Best practices for configuring Kafka consumer group IDs can be found under the link https://www.confluent.io/blog/configuring-apache-kafka-consumer-group-ids/.

Conclusion:

In conclusion, addressing factors such as clock synchronization and broker configuration can help mitigate the “Producer Fenced Exception” during Kafka Streams migration. Ensuring synchronized Kafka cluster clocks, unique broker IDs, and matching client versions with brokers are essential steps, but persistent misconfigurations on the broker side may limit the client’s control, underscoring the importance of adhering to best practices for Kafka consumer group IDs to prevent similar issues in the future.