Cloud cost anomalies can cause significant disruptions to work, with 41% of engineers reporting that cost issues last for at least a few hours per week. Running Kubernetes without real-time cloud cost monitoring and reporting makes it difficult to identify the source of these issues, leading to prolonged investigations that can take up an entire sprint or more. Implementing real-time cost visibility, allocating costs effectively, and analyzing historical cost data are key steps in minimizing disruption and optimizing cloud costs. By using a tool like CAST AI, which provides free cost monitoring for Kubernetes clusters with public pricing analysis, organizations can save 50-75% or more on their bills.