Amazon's Elastic Kubernetes Service (EKS) facilitates running Kubernetes on AWS, yet managing costs remains challenging as workloads grow. The 2025 State of Cloud Costs by Datadog reveals that over 80% of container spending is wasted, primarily due to over-provisioning of CPU and memory, leading to underutilized nodes and inefficient autoscaling. To optimize EKS costs, it's essential to understand pricing components like control plane, worker node, data transfer, and storage costs. Monitoring resource utilization is crucial for identifying inefficiencies, while cost optimization strategies include selecting appropriate instance types, using spot instances for non-critical tasks, and right-sizing workloads. Implementing best practices in autoscaling, resource requests, and scheduling non-critical workloads during off-peak hours can lead to significant savings. Automation tools, such as AWS-native solutions and third-party platforms like DevZero, offer dynamic optimization by continuously monitoring and adjusting resources, resulting in a potential 40-60% reduction in Kubernetes infrastructure costs.