Why were different consumer groups used?

In Kafka, different consumer groups are used for scaling and isolating message consumption:

• Scaling: if multiple consumers are part of the same consumer group, they jointly process the topic partitions, distributing the load among themselves. This allows for parallel message processing.

• Isolation: different consumer groups read the same messages independently of each other. This is useful when different applications or services need to process the same data differently.

Thus, consumer groups enable flexible management of data consumption, providing load balancing and processing independence for different services.