Running workloads on Spot Instances is a cost-effective strategy for cloud computing, but it often faces challenges due to the unpredictability of interruptions. Traditional methods manage these interruptions reactively by reallocating resources, but Cast AI introduces a more proactive solution with their Reliable Spot Instances feature. This feature utilizes survival analysis to identify and prioritize Spot Instances with lower historical interruption rates, thereby reducing disruptions significantly across AWS, Google Cloud Platform, and Azure. By integrating these reliability scores into the autoscaling process, Cast AI ensures that capacity decisions consider both cost and reliability, enhancing workload stability while maintaining financial benefits. The use of statistical models allows for dynamic adaptation to changing cloud conditions, offering users a resilient and efficient approach to Spot Instance utilization.