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Kafka Streams simplifies application development by building on the Kafka producer and consumer libraries and leveraging the native capabilities of Kafka to offer data parallelism, distributed coordination, fault tolerance, and operational simplicity. In this section, we describe how Kafka Streams works underneath the covers : https://kafka.apache.org/23/documentation/streams/architecture

  1. Kafka as a Messaging System

  2. Kafka Cluster

  3. Principles of distributed systems (multiple workers or nodes)

    In Kafka, worker nodes are the Kafka brokers. Within a distributed system, there are different roles and responsibilities and there is a hierarchy that starts with a controller or supervisor. A controller is just a worker node like any other.

  4. Reliable work distribution

  5. Distributed consensus with Apache Zookeeper

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