Organizations using Kubernetes clusters in cloud-native environments should focus on operational efficiency and cost-effectiveness, but often neglect cost optimization until it becomes a pressing issue. Addressing this concern involves monitoring key signals to ensure resources are neither over- nor under-provisioned, as both extremes can lead to financial inefficiencies and environmental impacts. Indicators of under-provisioning include high CPU or memory utilization, high disk I/O, and frequent pod evictions, while over-provisioning is identified by low utilization of resources and high costs without proportional usage. To strike a balance, best practices like regular monitoring using tools like Prometheus and Grafana, implementing autoscaling, setting resource quotas, and continuously optimizing workloads are recommended. By closely monitoring these signals and making informed adjustments, organizations can achieve a Kubernetes environment that is both cost-effective and environmentally sustainable.