Maximizing resource utilization in Google Kubernetes Engine (GKE) can lead to cost savings and better performance.This case study examines how an organization optimizes IP address management and budget allocation in GKE bycombining static and dynamic IP addresses, reserved instances, and autoscaling. The organization found that static IPaddresses were useful for critical services, while dynamic IP addresses were more appropriate for non-critical services.Using reserved instances and autoscaling allowed the organization to minimize costs while ensuring that resourceswere available when needed. The findings of this study have implications for organizations using GKE, highlighting theimportance of effective resource utilization for achieving optimal performance and cost savings.