Sunyanan Choochotkaew
CNCF Ambassador at Cloud Native Computing Foundation (CNCF)
Chiyoda, Japan
Summary
🤩
Rockstar🎓
Top SchoolSunyanan Choochotkaew is a CNCF Ambassador and Staff Research Scientist at IBM with 10 years of experience building cloud-native and energy-efficient systems. She holds a PhD from Osaka University and combines deep academic research with practical engineering across Kubernetes, eBPF, and ML-driven telemetry. Her open-source work includes contributions to Kepler, integrating TFLite-based power models and expanding test coverage to bring workload energy estimation into Prometheus ecosystems. At CNCF she helped lead KubeCon + CloudNativeCon Japan 2025, bridging community growth and technical outreach in the region. Based in Chiyoda, Japan, she blends cross-cultural research experience from institutions in Thailand, Germany, and the US with a track record of translating low-level system telemetry into actionable sustainability insights.
10 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at Osaka UniversityBachelor of Engineering (B.E.), Computer Engineering, 3.93, Bachelor of Engineering (B.E.), Computer Engineering, 3.93 at Chulalongkorn University
Github Skills (9)
unit-testing10
machine-learning10
go10
ginkgo10
ebpf9
kubernetes-pods9
tflite9
kubernetes9
cloud-native8
Programming languages (6)
Github contributions (5)
sustainable-computing-io/kepler
May 2022 - Jan 2023
Kepler (Kubernetes-based Efficient Power Level Exporter) uses eBPF to probe performance counters and other system stats, use ML models to estimate workload energy consumption based on these stats, and exports them as Prometheus metrics
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:197 reviews, 44 commits, 87 PRs in 8 months
Contributions summary:Sunyanan contributed to the integration of unit tests, specifically using the Ginkgo testing framework, for the power model code. They also initialized a framework for applying a TFLite model, including selector and handler components. In addition, the user made updates to build dependencies to accommodate TFLite and other necessary components. Overall, the work appears to be focused on expanding testing capabilities and the integration of machine learning models within the Kepler project.
energy-consumptionprobeexportsprometheus-metricsenergy-monitor
sunya-ch/kepler-operator
Sep 2022 - Apr 2024
Kepler Operator
Contributions:2 reviews, 2 PRs, 36 pushes in 1 year 7 months
kuberneteskepleroperator
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.