Topics

A stream of messages that are a part of a specific category or feed name is referred to as a Kafka topic. In Kafka, data is stored in the form of topics. Producers write their data to topics, and consumers read the data from these topics.

Brokers

A Kafka cluster comprises one or more servers that are known as brokers. In Kafka, a broker works as a container that can hold multiple topics with different partitions. A unique integer ID is used to identify brokers in the Kafka cluster. 

Consumers and Consumer Groups

Consumers read data from the Kafka cluster. The data to be read by the consumers has to be pulled from the broker when the consumer is ready to receive the message. A consumer group in Kafka refers to a number of consumers that pull data from the same topic or same set of topics.

Producers

Producers in Kafka publish messages to one or more topics. They send data to the Kafka cluster. Whenever a Kafka producer publishes a message to Kafka, the broker receives the message and appends it to a particular partition. Producers are given a choice to publish messages to a partition of their choice.

Partitions

Topics in Kafka are divided into a configurable number of parts, which are known as partitions. Partitions allow several consumers to read data from a particular topic in parallel. 

Partition Offset

Messages or records in Kafka are assigned to a partition. To specify the position of the records within the partition, each record is provided with an offset. 

Replicas

Replicas are like backups for partitions in Kafka. They are used to ensure that there is no data loss in the event of a failure or a planned shutdown.

Leader and Follower

Every partition in Kafka will have one server that plays the role of a leader for that particular partition. The leader is responsible for performing all the read and write tasks for the partition. 

https://www.projectpro.io/article/apache-kafka-architecture-/442