Zheng Chen developed dynamic resource limit functionality for the AI-Hypercomputer/xpk repository, focusing on Kueue and Jobset controllers. He implemented auto-calculated memory limits that adjust based on the cluster’s node count, reducing the need for manual resource tuning as clusters scale. Using Python and YAML, Zheng updated both new and existing automation scripts to manage these resource updates, ensuring controllers consistently receive adequate resources. His work leveraged Kubernetes resource management and shell scripting to improve deployment reliability and throughput for job orchestration workloads. This feature enhanced the stability and scalability of the system, addressing operational challenges in cloud infrastructure environments.