Global Message Ordering using Distributed Kafka Clusters

TL;DR

This paper proposes new methods to achieve global message ordering across multiple Kafka partitions, enhancing log consistency and system reliability in distributed environments.

Contribution

It introduces innovative approaches to ensure global message order in Kafka, addressing a key limitation of in-order delivery only within individual partitions.

Findings

Developed techniques for global message ordering in Kafka

Improved log processing consistency across distributed systems

Enhanced system reliability through better message sequencing

Abstract

In contemporary distributed systems, logs are produced at an astounding rate, generating terabytes of data within mere seconds. These logs, containing pivotal details like system metrics, user actions, and diverse events, are foundational to the system's consistent and accurate operations. Precise log ordering becomes indispensable to avert potential ambiguities and discordances in system functionalities. Apache Kafka, a prevalent distributed message queue, offers significant solutions to various distributed log processing challenges. However, it presents an inherent limitation while Kafka ensures the in-order delivery of messages within a single partition to the consumer, it falls short in guaranteeing a global order for messages spanning multiple partitions. This research delves into innovative methodologies to achieve global ordering of messages within a Kafka topic, aiming to bolster the integrity and consistency of log processing in distributed systems. Our code is available on GitHub.