Apache Kafka Practice Exam 2025 – The Complete All-in-One Guide for Exam Success!

In Kafka's architecture, a topic plays a crucial role in organizing and storing streams of records, which represent a specific category of data. Each topic acts as an independent log where messages are written in a sequential manner. When producers send data to a topic, the records are appended, and consumers can then read these records based on their relevancy and discretion. This design allows for high-throughput data processing and provides fault tolerance, as the data in a topic can be replicated across multiple brokers for durability.

While topics do facilitate the sending of messages between applications, that is only part of their function. They primarily serve as a storage medium for this data, allowing consumers to pull the data they need at their own pace, thereby decoupling the production and consumption of messages. Topics do not manage consumer groups directly or serve as physical servers; rather, they are abstractions that allow for better organization and scalability in message processing workflows.