Public bug reported: On Ubuntu 22.04.3, when running a k3s workload that uses volumes (using default local-path storageClass), process gvfs-disks2-volume-monitor can take around 100% of one CPU core, and process gsd-housekeeping around 25% of one CPU core. Even if the actual k3s workload is idle.
Steps To Reproduce: - Use or install a desktop Ubuntu 22.04.3 (with default settings) - Install K3s on it (current version is "v1.28.4+k3s2"), with default settings: "curl -sfL https://get.k3s.io | sh -" - Deploy k8s manifests with many volumes, like https://gitlab.com/-/snippets/3634487: "wget https://gitlab.com/-/snippets/3634487/raw/main/deployment-wit-many-volumes.yaml && sudo k3s kubectl apply -f deployment-wit-many-volumes.yaml" - Check CPU consumption on the host, with top, gnome-system-monitor or anything else Expected behavior: Gnome desktop tools should not interfere with k3s. Actual behavior: Processes gvfs-disks2-volume-monitor and gsd-housekeeping consume a lot of CPU, at least at provisioning time. Same CPU consumption if you then remove the workload ("sudo k3s kubectl delete -f deployment-wit-many-volumes.yaml"), until the PVs are deleted by k3s. I have other workloads (with data in PVs) where this CPU consumption is always there, when the workload is running. Additional context: The symptoms are very similar to https://github.com/k3s-io/k3s/issues/522, but the workaround of comment https://github.com/k3s-io/k3s/issues/522#issuecomment-811737023 (adding a udev rule to ignore some loopback devices) does not help. Executing systemctl stop --user gvfs-udisks2-volume-monitor can be a temporary workaround NB: Was initially reported on https://github.com/k3s-io/k3s/issues/9093 ** Affects: gvfs (Ubuntu) Importance: Undecided Status: New -- You received this bug notification because you are a member of Desktop Packages, which is subscribed to gvfs in Ubuntu. https://bugs.launchpad.net/bugs/2047356 Title: gvfs-disks2-volume-monitor and gsd-housekeeping processes can eat a lot of CPU with k3s workload Status in gvfs package in Ubuntu: New Bug description: On Ubuntu 22.04.3, when running a k3s workload that uses volumes (using default local-path storageClass), process gvfs-disks2-volume-monitor can take around 100% of one CPU core, and process gsd-housekeeping around 25% of one CPU core. Even if the actual k3s workload is idle. Steps To Reproduce: - Use or install a desktop Ubuntu 22.04.3 (with default settings) - Install K3s on it (current version is "v1.28.4+k3s2"), with default settings: "curl -sfL https://get.k3s.io | sh -" - Deploy k8s manifests with many volumes, like https://gitlab.com/-/snippets/3634487: "wget https://gitlab.com/-/snippets/3634487/raw/main/deployment-wit-many-volumes.yaml && sudo k3s kubectl apply -f deployment-wit-many-volumes.yaml" - Check CPU consumption on the host, with top, gnome-system-monitor or anything else Expected behavior: Gnome desktop tools should not interfere with k3s. Actual behavior: Processes gvfs-disks2-volume-monitor and gsd-housekeeping consume a lot of CPU, at least at provisioning time. Same CPU consumption if you then remove the workload ("sudo k3s kubectl delete -f deployment-wit-many-volumes.yaml"), until the PVs are deleted by k3s. I have other workloads (with data in PVs) where this CPU consumption is always there, when the workload is running. Additional context: The symptoms are very similar to https://github.com/k3s-io/k3s/issues/522, but the workaround of comment https://github.com/k3s-io/k3s/issues/522#issuecomment-811737023 (adding a udev rule to ignore some loopback devices) does not help. Executing systemctl stop --user gvfs-udisks2-volume-monitor can be a temporary workaround NB: Was initially reported on https://github.com/k3s-io/k3s/issues/9093 To manage notifications about this bug go to: https://bugs.launchpad.net/ubuntu/+source/gvfs/+bug/2047356/+subscriptions -- Mailing list: https://launchpad.net/~desktop-packages Post to : desktop-packages@lists.launchpad.net Unsubscribe : https://launchpad.net/~desktop-packages More help : https://help.launchpad.net/ListHelp
