Apache Kafka Connect is a component of Apache Kafka that allows for simple and scalable data import and export to and from Kafka. It is commonly used to integrate Kafka with various databases, message queues, or file formats. However, connecting Kafka Connect with multiple Kafka clusters is not as straightforward and often requires a specific configuration setup.

Understanding Kafka Connect

Kafka Connect is an integration framework that is part of the broader Kafka ecosystem. It is designed to facilitate streaming data between Kafka and other data systems in a reliable manner. Its primary function is to abstract away the details of reading from and writing to different systems using a common framework.

Modes of Operation

Kafka Connect can operate in two modes:

1. Standalone Mode: Suitable for small, non-critical tasks where the configuration is stored in a local file. This is easy to set up but does not benefit from the fault tolerance and scalability of a distributed system.
2. Distributed Mode: Used for scalable, fault-tolerant deployments. Configuration is stored in Kafka itself, and the work is distributed across multiple workers.

Connecting with Multiple Kafka Clusters

To integrate Kafka Connect with multiple Kafka clusters, configurations must be specified to ensure each connector or task connects to the appropriate cluster. This might involve dealing with multiple source and sink clusters.

Configuration Details

Given the lack of native support in Kafka Connect for communicating with multiple clusters directly in a single Connect cluster, a typical approach includes setting up separate Connect clusters for each Kafka cluster or carefully managing producer and consumer configurations.

Example: Separate Kafka Connect Clusters

A common setup might involve deploying two separate Kafka Connect clusters; each is configured to connect to a different Kafka cluster. For instance:

Cluster A – Connect Cluster Configuration:

1bootstrap.servers=kafka-cluster-a:9092
2group.id=connect-cluster-a
3key.converter=org.apache.kafka.connect.storage.StringConverter
4value.converter=org.apache.kafka.connect.storage.StringConverter
5config.storage.topic=connect-cluster-a-configs
6offset.storage.topic=connect-cluster-a-offsets
7status.storage.topic=connect-cluster-a-status

Cluster B – Connect Cluster Configuration:

1bootstrap.servers=kafka-cluster-b:9092
2group.id=connect-cluster-b
3key.converter=org.apache.kafka.connect.storage.StringConverter
4value.converter=org.apache.kafka.connect.storage.StringConverter
5config.storage.topic=connect-cluster-b-configs
6offset.storage.topic=connect-cluster-b-offsets
7status.storage.topic=connect-cluster-b-status

Handling Multiple Clusters within a Single Connect Cluster:

To directly handle multiple Kafka clusters within the same Connect cluster (though less common and more complex), one would have to carefully manage the configuration files for each connector to point to different clusters.

Example Configuration for a Sink Connector Connecting to a New Cluster:

1{
2  "name": "sink-connector-to-cluster-c",
3  "config": {
4    "connector.class": "io.confluent.connect.jdbc.JdbcSinkConnector",
5    "tasks.max": "1",
6    "topics": "topic-to-sink",
7    "connection.url": "jdbc:mysql://database.example:3306/db",
8    "connection.user": "user",
9    "connection.password": "password",
10    "key.converter": "org.apache.kafka.connect.storage.StringConverter",
11    "value.converter": "org.apache.kafka.connect.storage.StringConverter",
12    "producer.override.bootstrap.servers": "kafka-cluster-c:9092"
13  }
14}

Summary Table

Conclusion

Integrating Kafka Connect with multiple Kafka clusters involves careful consideration of configurations, especially when dealing with multiple destination clusters in a single connect instance. The key is to ensure that each connector's configuration correctly points to its respective cluster, achieving data integrity and isolation across different systems and their respective clusters.