One of the significant challenges faced by Kubernetes-based applications is that performance issues often only manifest in production environments, making them difficult to reproduce in development or staging settings. Imagine if we could "time travel" and recreate real-world production conditions within a controlled environment.

This session explores how a leading global bank (200M customers in 150+ countries) successfully recreated production workloads in controlled settings. By leveraging synthetic data generation, trace playback, and workload simulation, we tackled most performance issues without compromising sensitive data. This approach not only enhanced system reliability and reduced downtime but also improved the bank's ROI by decreasing operational costs by 30% and increasing transaction efficiency by 25%, resulting in significant annual savings.

Join us as we unravel the secrets of "time travel" to replicate production performance and resolve issues effectively.