Apache Kafka, an open-source messaging/streaming system, is a key enabler for many data-driven companies today. Companies like Uber, LinkedIn, and Tencent process trillions of messages daily using Kafka. Despite the emergence of alternative systems such as Flink, RabbitMQ, AWS Kinesis, Google Pub/Sub, and Azure Event Hub, Kafka remains dominant due to its reliability, scalability, compatibility with other data tools, and flexibility. However, managing and optimizing Kafka can be challenging for companies without the scale, budgets, and engineering manpower of Big Tech. This article explores how Walmart, Uber, Twitter, LinkedIn, and Tencent manage their cutting-edge Kafka deployments and provides insights on how other companies can efficiently manage and optimize their Kafka systems.