Design and Optimization of a High Availability, Low Latency Messaging Broker Using Zookeeper and Kafka for Asynchronous Processing

Abstract

This paper presents the design and optimization of a messaging broker leveraging Zookeeper and Kafka to achieve high availability and low latency for asynchronous processing. In modern distributed systems, ensuring reliable message delivery with minimal delay is critical for performance and user experience. Kafka, a distributed streaming platform, excels in high-throughput and fault-tolerant messaging, while Zookeeper provides centralized services for maintaining configuration information, naming, and synchronization. Key optimizations include configuring Kafka partitions and replicas for balanced load distribution, fine-tuning Zookeeper settings for faster consensus, and implementing advanced message batching and compression techniques to minimize network overhead. Through rigorous testing and benchmarking, we demonstrate significant improvements in message delivery times and system uptime. Our results show that the optimized broker can handle large-scale messaging workloads with improved efficiency and reliability, making it suitable for applications requiring real-time data processing and minimal downtime. This work contributes to the field by providing a comprehensive guide for deploying high-performance messaging systems using Kafka and Zookeeper.