Kangyi LI
Software Engineer II at Datadog
Greater Paris Metropolitan Region France
Summary
🤩
Rockstar🎓
Top SchoolKangyi LI is a Software Engineer II with seven years’ experience building backend and DevOps tooling, currently contributing to Datadog's core agent and orchestration features from the Greater Paris area. Trained at Shanghai University and pursuing engineering studies at UTC, he combines strong systems programming and Kubernetes orchestration expertise with hands-on performance and caching improvements. At Datadog he implemented pod-priority extraction, manifest collection, and performance-focused refactors in the widely used DataDog Agent, improving observability at scale. His background includes multi-role DevOps work at Polynom, giving him a practical, CI/CD-oriented perspective that complements his backend focus. Notably, he bridges research-level academic training and production engineering, often tackling data-scrubbing and process-chunking challenges that sit between tooling and platform reliability.
7 years of coding experience
3 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Shanghai UniversityEngineer's degree, Computer Science, Engineer's degree, Computer Science at Université de Technologie de Compiègne (UTC)
Chinese, French, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (12)
kubernetes10
orchestration10
observability10
orchestra10
go10
kubernetes-pods10
apm-agent9
metric9
distributed-tracing8
yaml8
dockers7
docker7
Programming languages (7)
Github contributions (5)
DataDog/datadog-agent
Sep 2021 - Jan 2023
Main repository for Datadog Agent
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:217 reviews, 41 commits, 104 PRs in 1 year 3 months
Contributions summary:Kangyi's contributions primarily involve the Datadog Agent, focusing on Kubernetes orchestration and internal systems. They implemented features related to extracting pod priority classes and updating cache stats for orchestrator components. Additionally, the user addressed issues around data scrubbing in the orchestrator and refactored code related to process chunking. Their work also includes adding manifest collection and related performance enhancements within the agent's core functionality.
golangdatadog-agentagentobservabilitypmm
NOLANKANGYI/NOLANKANGYI.github.io
Aug 2018 - Dec 2019
catch me if u can
Contributions:36 pushes in 1 year 4 months
javascript
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