Configuring accurate resource requests and limits in Kubernetes is essential for optimizing performance and reducing cloud costs by preventing overprovisioning. The process involves understanding the differences between container requests, which are guaranteed resources, and limits, which define the maximum resources a container can consume. Proper configuration ensures that performance is not compromised and that resources are not wasted. Harness Cloud Cost Workload Recommendation aids in this by analyzing historical utilization data to suggest optimal configurations, thereby enabling efficient resource use and cost savings. The recommendations are based on utilization metrics collected from Kubernetes clusters, with equal weightage given to historical data to account for potential seasonality in resource usage. This approach helps in determining suitable resources for each container and across replicas within a Pod, enhancing the overall efficiency of Kubernetes deployments. The article emphasizes that while recommendations are valuable, they are not mandatory to follow strictly, as they provide insight into resource utilization, allowing users to make informed decisions tailored to their specific needs.