  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.
