Kai Su is a Software Engineer II based in Shanghai with five years' experience building cloud-native systems and developer tooling at AWS and Microsoft. He has shipped production services spanning front-end React apps and backend serverless APIs, and improved global DHCP infrastructure that supports AWS data centers. At Microsoft he contributes to the high-profile Azure CLI and extensions—fixing monitor command issues, adding dynamic metrics support, and adding test infrastructure for Azure Front Door features. Kai pairs practical DevOps and test automation skills with a strong systems background from robotics anomaly detection work and an MS in Software Engineering from Tufts. Colleagues rely on him for pragmatic refactors that reduce operational noise and for turning obscure edge cases into resilient, testable code.
5 years of coding experience
3 years of employment as a software developer
Bachelor of Engineering - BE, Energy and Power Engineering, Bachelor of Engineering - BE, Energy and Power Engineering at Northeast Electric Power University
Jilin No.1 High School
Master of Science - MS, Computer Software Engineering, Master of Science - MS, Computer Software Engineering at Tufts University
Contributions:1593 reviews, 121 commits, 688 PRs in 2 years 1 month
Contributions summary:Kai primarily focused on bug fixes and code improvements within the `azure-cli` repository, specifically targeting the monitor command module. Their contributions involved resolving non-actionable issues, simplifying exception handling, and supporting dynamic thresholds in metrics alerts. Additionally, they addressed test failures and added infrastructure code to support tests. The user also refactored existing code and updated help messages within the monitor command module.
Contributions:1674 reviews, 50 commits, 874 PRs in 2 years 2 months
Contributions summary:Kai focused on adding new features and testing capabilities for Azure Front Door load balancing within the Azure CLI extension repository. The commits include the addition of a new command and the creation of test scenarios to validate different aspects of the load-balancing settings. Code changes primarily involve modifications to Python scripts for the Azure CLI, demonstrating development and testing skills within the context of the Azure Front Door service.
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