Confluent Cloud has significantly enhanced its performance, achieving speeds up to 10 times faster than Apache Kafka through the use of Kora, a cloud-native Kafka engine. Despite potential challenges in comparing performance due to Confluent Cloud's additional services like observability and auditing, Kora has been optimized to maintain low and consistent latency even under varying workload conditions and infrastructure disruptions. The blog post details how Confluent Cloud outperforms Apache Kafka across various workload profiles, achieving up to 16x improvements in p99 end-to-end latencies. The architecture has evolved with features like increased batching, parallelism, and a new replication protocol to ensure reliability and performance stability. Continuous optimizations have been implemented, such as improving the self-balancing algorithm and handling infrastructure degradation to minimize latency spikes. The post highlights real-world examples and customer feedback, illustrating the impact of these enhancements, and invites users to experience the improved performance of Confluent Cloud with the Kora engine.