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Kubernetes v1.33: Prevent PersistentVolume Leaks When Deleting out of Order graduates to GA

https://kubernetes.io/blog/2025/05/05/kubernetes-v1-33-prevent-persistentvolume-leaks-when-deleting-out-of-order-graduate-to-ga/

I am thrilled to announce that the feature to prevent PersistentVolume (or PVs for short) leaks when deleting out of order has graduated to General Availability (GA) in Kubernetes v1.33! This improvement, initially introduced as a beta feature in Kubernetes v1.31, ensures that your storage resources are properly reclaimed, preventing unwanted leaks.

How did reclaim work in previous Kubernetes releases?

PersistentVolumeClaim (or PVC for short) is a user's request for storage. A PV and PVC are considered Bound if a newly created PV or a matching PV is found. The PVs themselves are backed by volumes allocated by the storage backend.

Normally, if the volume is to be deleted, then the expectation is to delete the PVC for a bound PV-PVC pair. However, there are no restrictions on deleting a PV before deleting a PVC.

For a Bound PV-PVC pair, the ordering of PV-PVC deletion determines whether the PV reclaim policy is honored. The reclaim policy is honored if the PVC is deleted first; however, if the PV is deleted prior to deleting the PVC, then the reclaim policy is not exercised. As a result of this behavior, the associated storage asset in the external infrastructure is not removed.

PV reclaim policy with Kubernetes v1.33

With the graduation to GA in Kubernetes v1.33, this issue is now resolved. Kubernetes now reliably honors the configured Delete reclaim policy, even when PVs are deleted before their bound PVCs. This is achieved through the use of finalizers, ensuring that the storage backend releases the allocated storage resource as intended.

How does it work?

For CSI volumes, the new behavior is achieved by adding a finalizer external-provisioner.volume.kubernetes.io/finalizer on new and existing PVs. The finalizer is only removed after the storage from the backend is deleted. Addition or removal of finalizer is handled by external-provisioner `

An example of a PV with the finalizer, notice the new finalizer in the finalizers list

kubectl get pv pvc-a7b7e3ba-f837-45ba-b243-dec7d8aaed53 -o yaml

apiVersion: v1 kind: PersistentVolume metadata: annotations: pv.kubernetes.io/provisioned-by: csi.example.driver.com creationTimestamp: "2021-11-17T19:28:56Z" finalizers:

• kubernetes.io/pv-protection
• external-provisioner.volume.kubernetes.io/finalizer name: pvc-a7b7e3ba-f837-45ba-b243-dec7d8aaed53 resourceVersion: "194711" uid: 087f14f2-4157-4e95-8a70-8294b039d30e spec: accessModes:
• ReadWriteOnce capacity: storage: 1Gi claimRef: apiVersion: v1 kind: PersistentVolumeClaim name: example-vanilla-block-pvc namespace: default resourceVersion: "194677" uid: a7b7e3ba-f837-45ba-b243-dec7d8aaed53 csi: driver: csi.example.driver.com fsType: ext4 volumeAttributes: storage.kubernetes.io/csiProvisionerIdentity: 1637110610497-8081-csi.example.driver.com type: CNS Block Volume volumeHandle: 2dacf297-803f-4ccc-afc7-3d3c3f02051e persistentVolumeReclaimPolicy: Delete storageClassName: example-vanilla-block-sc volumeMode: Filesystem status: phase: Bound

The finalizer prevents this PersistentVolume from being removed from the cluster. As stated previously, the finalizer is only removed from the PV object after it is successfully deleted from the storage backend. To learn more about finalizers, please refer to Using Finalizers to Control Deletion.

Similarly, the finalizer kubernetes.io/pv-controller is added to dynamically provisioned in-tree plugin volumes.

Important note

The fix does not apply to statically provisioned in-tree plugin volumes.

How to enable new behavior?

To take advantage of the new behavior, you must have upgraded your cluster to the v1.33 release of Kubernetes and run the CSI external-provisioner version 5.0.1 or later. The feature was released as beta in v1.31 release of Kubernetes, where it was enabled by default.

References

KEP-2644

Volume leak issue

Beta Release Blog

How do I get involved?

The Kubernetes Slack channel SIG Storage communication channels are great mediums to reach out to the SIG Storage and migration working group teams.

Special thanks to the following people for the insightful reviews, thorough consideration and valuable contribution:

Fan Baofa (carlory)

Jan Šafránek (jsafrane)

Xing Yang (xing-yang)

Matthew Wong (wongma7)

Join the Kubernetes Storage Special Interest Group (SIG) if you're interested in getting involved with the design and development of CSI or any part of the Kubernetes Storage system. We’re rapidly growing and always welcome new contributors.

via Kubernetes Blog https://kubernetes.io/

May 05, 2025 at 02:30PM

Kubernetes v1.33: Mutable CSI Node Allocatable Count

https://kubernetes.io/blog/2025/05/02/kubernetes-1-33-mutable-csi-node-allocatable-count/

Scheduling stateful applications reliably depends heavily on accurate information about resource availability on nodes. Kubernetes v1.33 introduces an alpha feature called mutable CSI node allocatable count, allowing Container Storage Interface (CSI) drivers to dynamically update the reported maximum number of volumes that a node can handle. This capability significantly enhances the accuracy of pod scheduling decisions and reduces scheduling failures caused by outdated volume capacity information.

Background

Traditionally, Kubernetes CSI drivers report a static maximum volume attachment limit when initializing. However, actual attachment capacities can change during a node's lifecycle for various reasons, such as:

Manual or external operations attaching/detaching volumes outside of Kubernetes control.

Dynamically attached network interfaces or specialized hardware (GPUs, NICs, etc.) consuming available slots.

Multi-driver scenarios, where one CSI driver’s operations affect available capacity reported by another.

Static reporting can cause Kubernetes to schedule pods onto nodes that appear to have capacity but don't, leading to pods stuck in a ContainerCreating state.

Dynamically adapting CSI volume limits

With the new feature gate MutableCSINodeAllocatableCount, Kubernetes enables CSI drivers to dynamically adjust and report node attachment capacities at runtime. This ensures that the scheduler has the most accurate, up-to-date view of node capacity.

How it works

When this feature is enabled, Kubernetes supports two mechanisms for updating the reported node volume limits:

Periodic Updates: CSI drivers specify an interval to periodically refresh the node's allocatable capacity.

Reactive Updates: An immediate update triggered when a volume attachment fails due to exhausted resources (ResourceExhausted error).

Enabling the feature

To use this alpha feature, you must enable the MutableCSINodeAllocatableCount feature gate in these components:

kube-apiserver

kubelet

Example CSI driver configuration

Below is an example of configuring a CSI driver to enable periodic updates every 60 seconds:

apiVersion: storage.k8s.io/v1 kind: CSIDriver metadata: name: example.csi.k8s.io spec: nodeAllocatableUpdatePeriodSeconds: 60

This configuration directs Kubelet to periodically call the CSI driver's NodeGetInfo method every 60 seconds, updating the node’s allocatable volume count. Kubernetes enforces a minimum update interval of 10 seconds to balance accuracy and resource usage.

Immediate updates on attachment failures

In addition to periodic updates, Kubernetes now reacts to attachment failures. Specifically, if a volume attachment fails with a ResourceExhausted error (gRPC code 8), an immediate update is triggered to correct the allocatable count promptly.

This proactive correction prevents repeated scheduling errors and helps maintain cluster health.

Getting started

To experiment with mutable CSI node allocatable count in your Kubernetes v1.33 cluster:

Enable the feature gate MutableCSINodeAllocatableCount on the kube-apiserver and kubelet components.

Update your CSI driver configuration by setting nodeAllocatableUpdatePeriodSeconds.

Monitor and observe improvements in scheduling accuracy and pod placement reliability.

Next steps

This feature is currently in alpha and the Kubernetes community welcomes your feedback. Test it, share your experiences, and help guide its evolution toward beta and GA stability.

Join discussions in the Kubernetes Storage Special Interest Group (SIG-Storage) to shape the future of Kubernetes storage capabilities.

via Kubernetes Blog https://kubernetes.io/

May 02, 2025 at 02:30PM

Kubernetes v1.33: New features in DRA

https://kubernetes.io/blog/2025/05/01/kubernetes-v1-33-dra-updates/

Kubernetes Dynamic Resource Allocation (DRA) was originally introduced as an alpha feature in the v1.26 release, and then went through a significant redesign for Kubernetes v1.31. The main DRA feature went to beta in v1.32, and the project hopes it will be generally available in Kubernetes v1.34.

The basic feature set of DRA provides a far more powerful and flexible API for requesting devices than Device Plugin. And while DRA remains a beta feature for v1.33, the DRA team has been hard at work implementing a number of new features and UX improvements. One feature has been promoted to beta, while a number of new features have been added in alpha. The team has also made progress towards getting DRA ready for GA.

Features promoted to beta

Driver-owned Resource Claim Status was promoted to beta. This allows the driver to report driver-specific device status data for each allocated device in a resource claim, which is particularly useful for supporting network devices.

New alpha features

Partitionable Devices lets a driver advertise several overlapping logical devices (“partitions”), and the driver can reconfigure the physical device dynamically based on the actual devices allocated. This makes it possible to partition devices on-demand to meet the needs of the workloads and therefore increase the utilization.

Device Taints and Tolerations allow devices to be tainted and for workloads to tolerate those taints. This makes it possible for drivers or cluster administrators to mark devices as unavailable. Depending on the effect of the taint, this can prevent devices from being allocated or cause eviction of pods that are using the device.

Prioritized List lets users specify a list of acceptable devices for their workloads, rather than just a single type of device. So while the workload might run best on a single high-performance GPU, it might also be able to run on 2 mid-level GPUs. The scheduler will attempt to satisfy the alternatives in the list in order, so the workload will be allocated the best set of devices available in the cluster.

Admin Access has been updated so that only users with access to a namespace with the resource.k8s.io/admin-access: "true" label are authorized to create ResourceClaim or ResourceClaimTemplates objects with the adminAccess field within the namespace. This grants administrators access to in-use devices and may enable additional permissions when making the device available in a container. This ensures that non-admin users cannot misuse the feature.

Preparing for general availability

A new v1beta2 API has been added to simplify the user experience and to prepare for additional features being added in the future. The RBAC rules for DRA have been improved and support has been added for seamless upgrades of DRA drivers.

What’s next?

The plan for v1.34 is even more ambitious than for v1.33. Most importantly, we (the Kubernetes device management working group) hope to bring DRA to general availability, which will make it available by default on all v1.34 Kubernetes clusters. This also means that many, perhaps all, of the DRA features that are still beta in v1.34 will become enabled by default, making it much easier to use them.

The alpha features that were added in v1.33 will be brought to beta in v1.34.

Getting involved

A good starting point is joining the WG Device Management Slack channel and meetings, which happen at US/EU and EU/APAC friendly time slots.

Not all enhancement ideas are tracked as issues yet, so come talk to us if you want to help or have some ideas yourself! We have work to do at all levels, from difficult core changes to usability enhancements in kubectl, which could be picked up by newcomers.

Acknowledgments

A huge thanks to everyone who has contributed:

Cici Huang (cici37)

Ed Bartosh (bart0sh

John Belamaric (johnbelamaric)

Jon Huhn (nojnhuh)

Kevin Klues (klueska)

Morten Torkildsen (mortent)

Patrick Ohly (pohly)

Rita Zhang (ritazh)

Shingo Omura (everpeace)

via Kubernetes Blog https://kubernetes.io/

May 01, 2025 at 02:30PM

Kubernetes v1.33: Storage Capacity Scoring of Nodes for Dynamic Provisioning (alpha)

https://kubernetes.io/blog/2025/04/30/kubernetes-v1-33-storage-capacity-scoring-feature/

Kubernetes v1.33 introduces a new alpha feature called StorageCapacityScoring. This feature adds a scoring method for pod scheduling with the topology-aware volume provisioning. This feature eases to schedule pods on nodes with either the most or least available storage capacity.

About this feature

This feature extends the kube-scheduler's VolumeBinding plugin to perform scoring using node storage capacity information obtained from Storage Capacity. Currently, you can only filter out nodes with insufficient storage capacity. So, you have to use a scheduler extender to achieve storage-capacity-based pod scheduling.

This feature is useful for provisioning node-local PVs, which have size limits based on the node's storage capacity. By using this feature, you can assign the PVs to the nodes with the most available storage space so that you can expand the PVs later as much as possible.

In another use case, you might want to reduce the number of nodes as much as possible for low operation costs in cloud environments by choosing the least storage capacity node. This feature helps maximize resource utilization by filling up nodes more sequentially, starting with the most utilized nodes first that still have enough storage capacity for the requested volume size.

How to use

Enabling the feature

In the alpha phase, StorageCapacityScoring is disabled by default. To use this feature, add StorageCapacityScoring=true to the kube-scheduler command line option --feature-gates.

Configuration changes

You can configure node priorities based on storage utilization using the shape parameter in the VolumeBinding plugin configuration. This allows you to prioritize nodes with higher available storage capacity (default) or, conversely, nodes with lower available storage capacity. For example, to prioritize lower available storage capacity, configure KubeSchedulerConfiguration as follows:

apiVersion: kubescheduler.config.k8s.io/v1 kind: KubeSchedulerConfiguration profiles: ... pluginConfig:

• name: VolumeBinding args: ... shape:
• utilization: 0 score: 0
• utilization: 100 score: 10

For more details, please refer to the documentation.

Further reading

KEP-4049: Storage Capacity Scoring of Nodes for Dynamic Provisioning

Additional note: Relationship with VolumeCapacityPriority

The alpha feature gate VolumeCapacityPriority, which performs node scoring based on available storage capacity during static provisioning, will be deprecated and replaced by StorageCapacityScoring.

Please note that while VolumeCapacityPriority prioritizes nodes with lower available storage capacity by default, StorageCapacityScoring prioritizes nodes with higher available storage capacity by default.

via Kubernetes Blog https://kubernetes.io/

April 30, 2025 at 02:30PM

Ep20 - Ask Me Anything About Anything with Scott Rosenberg

There are no restrictions in this AMA session. You can ask anything about DevOps, Cloud, Kubernetes, Platform Engineering, containers, or anything else. We'll have special guests Scott Rosenberg and Ramiro Berrelleza to help us out.

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▬▬▬▬▬▬ 🚀 Other Channels 🚀 ▬▬▬▬▬▬ 🎤 Podcast: https://www.devopsparadox.com/ 💬 Live streams: https://www.youtube.com/c/DevOpsParadox

via YouTube https://www.youtube.com/watch?v=nFWGZEI37SA

Week Ending April 27, 2025

https://lwkd.info/2025/20250430

Developer News

Benjamin Elder reminded contributors of the changes to the E2E Testing Framework that take effect now. Contributors must use framework.WithFeatureGate(features.YourFeature) for tests related to specific feature gates to ensure proper execution in CI jobs. Tests need to specify both feature gates and cluster configurations.

After 5 long years, SIG-Testing has finally acheived zero hard-coded test skips in pull-kubernetes-e2e-kind and related jobs. This is near parity with pull-kubernetes-e2e-gce (1056 tests vs 1080 test) in approximately half the runtime (~30m vs ~1h).

Applications for Project Lighting talks, Maintainer’s Track and ContribFest at KubeCon NA 2025 are open! Get your submissions in before 7th July.

Please read and comment on an ongoing discussion about AI-generated contributions to Kubernetes. Several repositories have been receiving AI-generated submissions which look acceptable until carefully reviewed. Younger developers may be more reliant on AI and may not realize that such contributions are unacceptable. Community members are discussing whether we need a more restrictive policy than the Linux Foundation’s.

Release Schedule

Next Deadline: 1.34 Release Cycle Begins – soon

We are in the between-release limbo period, so time to work on whatever you want. That irritating bug, the subproject you’ve been meaning to investigate, a birdhouse, whatever. The call for enhancements will come soon enough.

Featured PRs

131491: kubectl describe service: Add Traffic Distribution

This PR shows the Traffic Distribution field, added in Kubernetes 1.31, in kubectl describe service if the field is set. This makes the field much more accessible and useful to users.

130782: Kubeadm issue #3152 ControlPlane node setup failing with “etcdserver: can only promote a learner member”

This PR fixes a bug where in kubeadm ControlPlane node setup fails with the error “etcdserver: can only promote a learner member”; This PR adds a check to ensure that promotion does not retry if the member is already promoted and introduces a call to remove the learner member if the promotion fails entirely.

KEP of the Week

KEP 1769: Speed up recursive SELinux label change

This KEP speeds up volume mounts on SELinux-enforcing systems by using the -o context=XYZ mount option instead of slow recursive relabeling. It has rolled out in three phases: starting with ReadWriteOncePod volumes (v1.28), then adding metrics and an opt-out (v1.32), and finally applying to all volumes by default in 1.33.

Other Merges

Fix for OIDC discovery document publishing when external service account token signing is enabled

hack/update-codegen.sh now automatically ensures goimports and protoc

Deprecated scheduler cache metrics removed

Recovery feature’s status in kubelet now checks for newer resize fields

Fix for the invalid SucceededCriteriaMet condition type in the Job API

Watch handler tests moved to handlers package

Fix for error handling and CSI JSON file removal interaction

Pod resize e2e utilities moved out of e2e/framework

Fix for a possible deadlock in the watch client

Long directory names with e2e pod logs shortened

endpoint-controller and workload-leader-election FlowSchemas removed from the default APF configuration

Fix for the allocatedResourceStatuses Field name mismatch in PVC status validation

scheduler-perf adds option to enable api-server initialization

Kubelet to use the node informer to get the node addresses directly

Fix for a bug in Job controller which could result in creating unnecessary Pods for a finished Job

kube-controller-manager events to support contextual logging

Fix for a bug where NodeResizeError condition was in PVC status when the CSI driver does not support node volume expansion

kubeadm refactoring to reduce code repetition using slice package

Version Updates

google/cel-go to v0.25.0

cri-tools to v1.33.0

mockery to v2.53.3

coredns to v.1.12.1

Shoutouts

Ryota: Now that Kubernetes v1.33 is officially out, the Release Team Subteam Leads — , rayandas(Docs), Wendy Ha (Release Signal), Dipesh (Enhancements), and Ryota (Comms) — want to send a huge shoutout to our amazing Release Lead Nina Polshakova

via Last Week in Kubernetes Development https://lwkd.info/

April 30, 2025 at 05:00PM