Kubernetes has the potential to help organizations use resources more efficiently, but in practice, they don't always lead to cost savings. This is due to how resources are allocated in Kubernetes environments and the fact that many organizations pay for resources they don’t end up using. To mitigate this issue, teams need to request the right amount of CPU and memory requests for their containers (i.e., size their pods correctly). Tools like the Kubernetes Vertical Pod Autoscaler and historical data can be used to rightsize workloads. Additionally, it is important to understand how CPU and memory limits affect scheduling and performance in Kubernetes environments.