Kevin Tan developed robust rate-limiting controls for the DataFrameService within the ni/install-systemlink-enterprise repository, focusing on improving system stability and throughput under load. He implemented configurable rate limits across global, metadata query, and row data query paths, using yaml for configuration management and applying system administration best practices. The solution introduced tokens-per-second, token limit, and queue limit thresholds to govern API request throughput, effectively preventing bursty traffic from impacting service-level agreements. By centralizing rate-limit configuration, Kevin’s work established a foundation for operational visibility and capacity planning, demonstrating a thoughtful approach to scalable and maintainable system governance.