Is it possible to ensure horizontal scaling of Kafka to handle increasing data streams?

Yes, Apache Kafka supports horizontal scaling, which allows handling increasing data streams. This is achieved by partitioning topics, which can be distributed across different cluster brokers. Each broker handles its partitions, enabling parallel reading and writing of data.

To scale, you need to:

• Increase the number of partitions in the topic.
• Add new brokers to the Kafka cluster.
• Ensure partition balancing among brokers.

Thus, the load is distributed, and the system can handle larger volumes of data without performance loss.

Example of creating a topic with multiple partitions using Kafka command:

kafka-topics.sh --create --topic example-topic --partitions 10 --replication-factor 3 --bootstrap-server localhost:9092

In Go code, when using the sarama client, you can specify the partition when sending messages to control load distribution.