Apache Kafka Complete Practice Exam 2025 – All-in-One Prep

A consumer group in Kafka plays a crucial role in the message consumption process by allowing a set of consumers to share the load of consuming messages from one or more topics. Each consumer within the group is responsible for reading messages from a specific subset of the topic's partitions, which enables parallel processing of the data. This distribution of workload enhances both efficiency and performance, as it allows the consumer group to scale horizontally by simply adding more consumers when higher throughput is needed.

The architecture of Kafka ensures that each message from a partition can only be processed by one consumer within a particular group at a time. This guarantees that messages are not duplicated in processing, as only one consumer can consume messages from a specific partition, thereby achieving effective load balancing and a seamless handling of the message stream.

This is fundamentally different from the other concepts presented in the choices. For instance, a group of producers pertains to the entities that send data to Kafka topics, while the collection of brokers refers to the servers that store and manage partitions of Kafka topics. The idea of processing messages in a single-threaded manner also does not align with the purpose of consumer groups, which aim to leverage multi-threading and parallel consumption to optimize throughput and resource utilization.