Kevin Tan developed robust rate-limiting controls for the DataFrameService in the ni/install-systemlink-enterprise repository, focusing on improving system stability and throughput under load. He implemented configurable global, metadata query, and row data query rate limits using yaml for configuration management, allowing fine-grained control over tokens-per-second, token limits, and queue thresholds. This approach governed API request throughput, preventing bursty traffic from impacting service-level agreements and ensuring predictable latency. By centralizing rate-limit configuration, Kevin laid the foundation for enhanced operational visibility and capacity planning. His work demonstrated depth in system administration and configuration management, addressing both immediate reliability and future scalability needs.