5242f01e8c
Automatic merge from submit-queue (batch tested with PRs 56021, 55843, 55088, 56117, 55859). If you want to cherry-pick this change to another branch, please follow the instructions <a href="https://github.com/kubernetes/community/blob/master/contributors/devel/cherry-picks.md">here</a>. Extends deviceplugin to gracefully handle full device plugin lifecycle. **What this PR does / why we need it**: - Instead of using cm.capacity field to communicate device plugin resource capacity, this PR changes to use an explicit cm.GetDevicePluginResourceCapacity() function that returns device plugin resource capacity as well as any inactive device plugin resource. Kubelet syncNodeStatus call this function during its periodic run to update node status capacity and allocatable. After this call, device plugin can remove the inactive device plugin resource from its allDevices field as the update is already pushed to API server. - Extends device plugin checkpoint data to record registered resources so that we can finish resource removing even upon kubelet restarts. - Passes sourcesReady from kubelet to device plugin to avoid removing inactive pods during grace period of kubelet restart. - Extends gpu_device_plugin e2e_node test to verify that scheduled pods can continue to run even after device plugin deletion and kubelet restarts. **Which issue(s) this PR fixes** *(optional, in `fixes #<issue number>(, fixes #<issue_number>, ...)` format, will close the issue(s) when PR gets merged)*: Together with https://github.com/kubernetes/kubernetes/pull/54488, fixes https://github.com/kubernetes/kubernetes/issues/53395 **Special notes for your reviewer**: **Release note**: ```release-note Extends deviceplugin to gracefully handle full device plugin lifecycle. ``` |
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Kubernetes
Kubernetes is an open source system for managing containerized applications across multiple hosts, providing basic mechanisms for deployment, maintenance, and scaling of applications.
Kubernetes builds upon a decade and a half of experience at Google running production workloads at scale using a system called Borg, combined with best-of-breed ideas and practices from the community.
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