Collection of tools and examples for managing Accelerated workloads in Kubernetes Engine
Role in this project:
Cloud Engineer & DevOps Engineer Contributions:26 commits, 24 PRs, 11 pushes in 2 years 1 month
Contributions summary:Jiaying primarily contributed to the development of a device plugin for NVIDIA GPUs, which involved setting up the environment, discovering GPU devices, and integrating with Kubernetes. They implemented the device plugin API, including ListAndWatch and Allocate functionalities. Key changes include supporting multiple API versions (v1beta1) and incorporating environment variables for CUDA-enabled containers.
kubernetes
Autotest - Fully automated tests on Linux
Role in this project:
QA Engineer / Test Automation Engineer Contributions:5 commits in 1 month
Contributions summary:Jiaying significantly contributed to the testing framework by extending the Linux Tracing Toolkit (lttng) profiler. Their work involved enabling specific trace points, adding features like output file size limits and compression, and ensuring proper data flushing before system reboot. The user also addressed setup and initialization to ensure the framework is well-integrated with the existing test environment. This indicates a focus on automated testing and improving the overall testing process within the repository.
automated-testsautotestlinuxpythontesting