Solving the Kafka Listener Issue with Multiple Brokers in Spring Kafka

A detailed guide on configuring a Spring Kafka consumer to handle multiple brokers efficiently. This post addresses common issues and provides solutions for effective message consumption across different brokers.
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Understanding the Kafka Consumer Problem with Multiple Brokers

If you're venturing into the world of message streaming using Spring Kafka, you may encounter some challenges when working with multiple Kafka brokers. A common situation is when a Kafka listener fails to receive messages from one of the brokers, which can hinder your application's performance and reliability.

The Scenario:
You have two brokers, each associated with a topic featuring only one partition, essentially leading to the following setup:

Broker1Broker2Topic1Topic1One PartitionOne PartitionWith this setup, you might be wondering if simply passing the host of the two brokers to the listener and setting a concurrency level of 2 is sufficient to ensure that your consumer receives messages from both brokers.

Overview of the Current Configuration

In your configuration, you set up a Kafka listener using the @ KafkaListener annotation and adjusted several properties:

Listener Annotation:

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Concurrency Setting:

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Broker Array:

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Group ID:

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Partition Assignment Strategy:

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With these settings, your expectation is to receive messages from both brokers. However, you have faced issues where messages are not consistently received from one of the brokers.

Solution to Receive Messages from Multiple Brokers

Confirm Cluster Configuration

The first step to resolving your issue is to ensure that both brokers are part of the same Kafka cluster. If they are, your current configuration should generally work as intended, and you should be able to receive messages from both brokers seamlessly.

Handling Multiple Clusters

If the brokers are not in the same cluster, follow these adjustments:

Multiple @ KafkaListener Annotations:
Each listener should correspond to one broker within the distinct clusters. Here’s an example:

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Using Properties in Annotations:
Alternatively, you can override the BOOTSTRAP_SERVERS_CONFIG property directly in one of the listener annotations:

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Best Practices for Debugging

Check Cluster Connectivity: Ensure that your consumers can connect to all specified brokers.

Examine Broker Logs: Review logs from each broker to identify if messages are being sent or if there are any errors.

Monitor Consumer Group Status: Use Kafka's tools to monitor the health of your consumer groups.

Adjust Concurrency: Depending on your application demands, ensure that your concurrency settings are correctly tuned.

Conclusion

Configuring a Spring Kafka consumer to work correctly with multiple brokers can seem daunting, but understanding your cluster setup and making the necessary adjustments can streamline the process. By following the outlined solutions, you can ensure that your consumer effectively receives messages from all desired brokers.

You are now equipped with the knowledge to tackle the issue of message consumption across multiple Kafka brokers. Happy coding!