
Kaiyi Liu developed and enhanced CI/CD workflows and monitoring solutions for the sustainable-computing-io/kepler-metal-ci and kepler repositories. Over two months, Kaiyi delivered an end-to-end AWS EC2 runner management system, integrated Prometheus-based observability, and stabilized CI environments using Ansible and Shell scripting. In kepler, Kaiyi built an Energy Usage Dashboard to visualize node-level power metrics, leveraging Go and Python for backend development and data visualization. The work included standardizing training log management, improving artifact traceability, and fixing CI workflows for external contributions. These contributions demonstrate depth in cloud automation, system monitoring, and robust testing practices across complex DevOps pipelines.

In May 2025, delivered the Energy Usage Dashboard in sustainable-computing-io/kepler to visualize node-level power metrics across energy zones and instances, including historical, total, average, and current Watts. Fixed the CI workflow to correctly fetch the head commit from forked PRs, enabling accurate dependency analysis for external contributions. Added tests for the node power metrics dashboard to improve reliability and prevent regressions. These changes enhance data-driven energy optimization capabilities and strengthen external contribution workflows, with measurable improvements in monitoring, quality assurance, and security posture.
In May 2025, delivered the Energy Usage Dashboard in sustainable-computing-io/kepler to visualize node-level power metrics across energy zones and instances, including historical, total, average, and current Watts. Fixed the CI workflow to correctly fetch the head commit from forked PRs, enabling accurate dependency analysis for external contributions. Added tests for the node power metrics dashboard to improve reliability and prevent regressions. These changes enhance data-driven energy optimization capabilities and strengthen external contribution workflows, with measurable improvements in monitoring, quality assurance, and security posture.
November 2024 performance highlights for sustainable-computing-io/kepler-metal-ci. Delivered end-to-end CI/CD improvements across AWS runners, observability, training log management, and CI stability. Implementations included reusable AWS EC2 runner workflows with key-name authentication, Prometheus-based monitoring enhancements, standardized training log naming and dated archival, and CI environment stability fixes. Additionally, AWS-trained model artifacts were reorganized under a dedicated train-validate-e2e-aws path to improve artifact traceability and provider separation.
November 2024 performance highlights for sustainable-computing-io/kepler-metal-ci. Delivered end-to-end CI/CD improvements across AWS runners, observability, training log management, and CI stability. Implementations included reusable AWS EC2 runner workflows with key-name authentication, Prometheus-based monitoring enhancements, standardized training log naming and dated archival, and CI environment stability fixes. Additionally, AWS-trained model artifacts were reorganized under a dedicated train-validate-e2e-aws path to improve artifact traceability and provider separation.
Overview of all repositories you've contributed to across your timeline