Swiggy, India’s leading food delivery platform, processes millions of messages every second to power real-time recommendations, predictions, order tracking, and personalized user experiences. In this session, we’ll explore the challenges Swiggy faced while managing open-source Kafka and how we successfully migrated to Confluent’s managed Kafka cluster, streamlining operations and significantly improving performance. We’ll also dive into the critical role Confluent Kafka plays in our microservices architecture, with a special focus on the complexities of Kafka consumer canary testing. We’ll discuss why this process is complex and how we uniquely solved these challenges to ensure reliable, efficient service delivery. Finally, we’ll demonstrate how Confluent Kafka enables Swiggy to handle millions of messages per second, empowering real-time analytics, predictive models like SLA predictions, and personalized user experiences at scale. This session will provide valuable insights into Kafka’s central role in modern microservices architectures and how Confluent Kafka supports high-performance, scalable, and real-time data pipelines for large-scale applications.