How System Work
The Kafka system is designed to efficiently handle large volumes of streaming data. It consists of a cluster of servers called brokers that work together to store, process, and deliver messages. Messages are organized into topics, which act as categories for different types of data. Each topic is divided into partitions, allowing for parallel processing. Within each partition, there is a leader broker responsible for handling read and write operations, while other brokers serve as replicas for fault tolerance. Producers publish messages to topics, specifying the target topic and partition, while consumers subscribe to topics and read messages at their own pace. Kafka uses ZooKeeper for cluster coordination and metadata management. It provides configurable replication and retention mechanisms for data durability and retention period. Kafka's distributed architecture allows for scalability, fault tolerance, and high throughput, making it suitable for various real-time data processing and messaging scenarios.