
Worked on sustainable-computing-io/kepler and kepler-metal-ci, delivering features that enhanced observability, automation, and energy monitoring. Developed an Energy Usage Dashboard to visualize node-level power metrics, leveraging Go and Python for backend logic and data visualization. Improved CI/CD pipelines by implementing reusable AWS EC2 runner workflows, integrating Prometheus-based monitoring, and stabilizing CI environments using Ansible and Shell scripting. Added experimental support for hwmon-based power metrics collection, including configuration toggles and unit tests to ensure reliability. Addressed workflow issues for external contributors and maintained robust test coverage, resulting in improved traceability, system monitoring, and support for power-aware optimizations.
January 2026 (2026-01) monthly summary for sustainable-computing-io/kepler. Delivered the Experimental Hwmon Power Metrics feature, enabling power metrics collection via the hwmon subsystem and an experimental config toggle. Implemented a hwmon device reader for architectures with hwmon sensors to acquire watts, added docs and unit tests, and established configuration support to enable the feature. This work increases observability of power usage and provides a foundation for power-aware optimizations. Focus this month was on instrumentation, configuration, and test coverage to drive reliability and business value.
January 2026 (2026-01) monthly summary for sustainable-computing-io/kepler. Delivered the Experimental Hwmon Power Metrics feature, enabling power metrics collection via the hwmon subsystem and an experimental config toggle. Implemented a hwmon device reader for architectures with hwmon sensors to acquire watts, added docs and unit tests, and established configuration support to enable the feature. This work increases observability of power usage and provides a foundation for power-aware optimizations. Focus this month was on instrumentation, configuration, and test coverage to drive reliability and business value.
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.

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