Tony Chen developed a configurable resource tuning feature for the k8sgpt-ai/k8sgpt-operator repository, enabling dynamic CPU and memory allocation for K8sGPT deployments. Using Go and leveraging Kubernetes’ CRD-driven configuration, Tony designed the system to allow users to specify resource requests and limits through config.Spec.Resources, with sensible defaults to ensure stability and prevent misconfiguration. This approach supports scalable, cost-efficient deployments by giving operators precise control over resource usage. The work demonstrated a solid understanding of cloud native patterns and Kubernetes resource management, laying a foundation for improved performance predictability and operational flexibility in future K8sGPT operator releases.