Kubernetes 1.27: In-place Resource Resize for Kubernetes Pods (alpha)
Author: Vinay Kulkarni (Kubescaler Labs)
If you have deployed Kubernetes pods with CPU and/or memory resources specified, you may have noticed that changing the resource values involves restarting the pod. This has been a disruptive operation for running workloads... until now.
In Kubernetes v1.27, we have added a new alpha feature that allows users
to resize CPU/memory resources allocated to pods without restarting the
containers. To facilitate this, the
resources field in a pod's containers
now allow mutation for
memory resources. They can be changed
simply by patching the running pod spec.
This also means that
resources field in the pod spec can no longer be
relied upon as an indicator of the pod's actual resources. Monitoring tools
and other such applications must now look at new fields in the pod's status.
Kubernetes queries the actual CPU and memory requests and limits enforced on
the running containers via a CRI (Container Runtime Interface) API call to the
runtime, such as containerd, which is responsible for running the containers.
The response from container runtime is reflected in the pod's status.
In addition, a new
restartPolicy for resize has been added. It gives users
control over how their containers are handled when resources are resized.
What's new in v1.27?
Besides the addition of resize policy in the pod's spec, a new field named
allocatedResources has been added to
containerStatuses in the pod's status.
This field reflects the node resources allocated to the pod's containers.
In addition, a new field called
resources has been added to the container's
status. This field reflects the actual resource requests and limits configured
on the running containers as reported by the container runtime.
Lastly, a new field named
resize has been added to the pod's status to show the
status of the last requested resize. A value of
Proposed is an acknowledgement
of the requested resize and indicates that request was validated and recorded. A
InProgress indicates that the node has accepted the resize request
and is in the process of applying the resize request to the pod's containers.
A value of
Deferred means that the requested resize cannot be granted at this
time, and the node will keep retrying. The resize may be granted when other pods
leave and free up node resources. A value of
Infeasible is a signal that the
node cannot accommodate the requested resize. This can happen if the requested
resize exceeds the maximum resources the node can ever allocate for a pod.
When to use this feature
Here are a few examples where this feature may be useful:
- Pod is running on node but with either too much or too little resources.
- Pods are not being scheduled do to lack of sufficient CPU or memory in a cluster that is underutilized by running pods that were overprovisioned.
- Evicting certain stateful pods that need more resources to schedule them on bigger nodes is an expensive or disruptive operation when other lower priority pods in the node can be resized down or moved.
How to use this feature
In order to use this feature in v1.27, the
feature gate must be enabled. A local cluster with this feature enabled
can be started as shown below:
root@vbuild:~/go/src/k8s.io/kubernetes# FEATURE_GATES=InPlacePodVerticalScaling=true ./hack/local-up-cluster.sh go version go1.20.2 linux/arm64 +++ [0320 13:52:02] Building go targets for linux/arm64 k8s.io/kubernetes/cmd/kubectl (static) k8s.io/kubernetes/cmd/kube-apiserver (static) k8s.io/kubernetes/cmd/kube-controller-manager (static) k8s.io/kubernetes/cmd/cloud-controller-manager (non-static) k8s.io/kubernetes/cmd/kubelet (non-static) ... ... Logs: /tmp/etcd.log /tmp/kube-apiserver.log /tmp/kube-controller-manager.log /tmp/kube-proxy.log /tmp/kube-scheduler.log /tmp/kubelet.log To start using your cluster, you can open up another terminal/tab and run: export KUBECONFIG=/var/run/kubernetes/admin.kubeconfig cluster/kubectl.sh Alternatively, you can write to the default kubeconfig: export KUBERNETES_PROVIDER=local cluster/kubectl.sh config set-cluster local --server=https://localhost:6443 --certificate-authority=/var/run/kubernetes/server-ca.crt cluster/kubectl.sh config set-credentials myself --client-key=/var/run/kubernetes/client-admin.key --client-certificate=/var/run/kubernetes/client-admin.crt cluster/kubectl.sh config set-context local --cluster=local --user=myself cluster/kubectl.sh config use-context local cluster/kubectl.sh
Once the local cluster is up and running, Kubernetes users can schedule pods with resources, and resize the pods via kubectl. An example of how to use this feature is illustrated in the following demo video.
Example Use Cases
Cloud-based Development Environment
In this scenario, developers or development teams write their code locally but build and test their code in Kubernetes pods with consistent configs that reflect production use. Such pods need minimal resources when the developers are writing code, but need significantly more CPU and memory when they build their code or run a battery of tests. This use case can leverage in-place pod resize feature (with a little help from eBPF) to quickly resize the pod's resources and avoid kernel OOM (out of memory) killer from terminating their processes.
This KubeCon North America 2022 conference talk illustrates the use case.
Java processes initialization CPU requirements
Some Java applications may need significantly more CPU during initialization than what is needed during normal process operation time. If such applications specify CPU requests and limits suited for normal operation, they may suffer from very long startup times. Such pods can request higher CPU values at the time of pod creation, and can be resized down to normal running needs once the application has finished initializing.
This feature enters v1.27 at alpha stage. Below are a few known issues users may encounter:
- containerd versions below v1.6.9 do not have the CRI support needed for full
end-to-end operation of this feature. Attempts to resize pods will appear
to be stuck in the
resourcesfield in the pod's status are never updated even though the new resources may have been enacted on the running containers.
- Pod resize may encounter a race condition with other pod updates, causing delayed enactment of pod resize.
- Reflecting the resized container resources in pod's status may take a while.
- Static CPU management policy is not supported with this feature.
This feature is a result of the efforts of a very collaborative Kubernetes community. Here's a little shoutout to just a few of the many many people that contributed countless hours of their time and helped make this happen.
- @thockin for detail-oriented API design and air-tight code reviews.
- @derekwaynecarr for simplifying the design and thorough API and node reviews.
- @dchen1107 for bringing vast knowledge from Borg and helping us avoid pitfalls.
- @ruiwen-zhao for adding containerd support that enabled full E2E implementation.
- @wangchen615 for implementing comprehensive E2E tests and driving scheduler fixes.
- @bobbypage for invaluable help getting CI ready and quickly investigating issues, covering for me on my vacation.
- @Random-Liu for thorough kubelet reviews and identifying problematic race conditions.
- @Huang-Wei, @ahg-g, @alculquicondor for helping get scheduler changes done.
- @mikebrow @marosset for reviews on short notice that helped CRI changes make it into v1.25.
- @endocrimes, @ehashman for helping ensure that the oft-overlooked tests are in good shape.
- @mrunalp for reviewing cgroupv2 changes and ensuring clean handling of v1 vs v2.
- @liggitt, @gjkim42 for tracking down, root-causing important missed issues post-merge.
- @SergeyKanzhelev for supporting and shepherding various issues during the home stretch.
- @pdgetrf for making the first prototype a reality.
- @dashpole for bringing me up to speed on 'the Kubernetes way' of doing things.
- @bsalamat, @kgolab for very thoughtful insights and suggestions in the early stages.
- @sftim, @tengqm for ensuring docs are easy to follow.
- @dims for being omnipresent and helping make merges happen at critical hours.
- Release teams for ensuring that the project stayed healthy.
And a big thanks to my very supportive management Dr. Xiaoning Ding and Dr. Ying Xiong for their patience and encouragement.
For app developers
For cluster administrators
Configure Default Memory Requests and Limits for a Namespace