Provisioning Admission Check Controller
The Provisioning AdmissionCheck Controller is an AdmissionCheck Controller designed to integrate Kueue with Kubernetes cluster-autoscaler. Its primary function is to create ProvisioningRequests for the workloads holding Quota Reservation and keeping the AdmissionCheckState in sync.
The controller is part of Kueue. It is enabled by default. You can disable it by editing the ProvisioningACC
feature gate. Check the Installation guide for details on feature gate configuration.
The Provisioning Admission Check Controller is supported on Kubernetes cluster-autoscaler versions 1.29 and later. However, some cloud-providers may not have an implementation for it.
Check the list of supported Provisioning Classes and prerequisite for them in ClusterAutoscaler documentation.
Usage
To use the Provisioning AdmissionCheck, create an AdmissionCheck
with kueue.x-k8s.io/provisioning-request
as a .spec.controllerName
and create a ProvisioningRequest configuration using a ProvisioningRequestConfig
object.
Next, you need to reference the AdmissionCheck from the ClusterQueue, as detailed in Admission Check usage.
See below for a full setup.
ProvisioningRequest configuration
There are two ways to configure the ProvisioningRequests that Kueue creates for your Jobs.
- ProvisioningRequestConfig: This configuration in the AdmissionCheck applies to all the jobs that go through this check.
It enables you to set
provisioningClassName
,managedResources
, andparameters
- Job annotation: This configuration enables you to set
parameters
to a specific job. If both the annotation and the ProvisioningRequestConfig refer to the same parameter, the annotation value takes precedence.
ProvisioningRequestConfig
A ProvisioningRequestConfig
looks like the following:
apiVersion: kueue.x-k8s.io/v1beta1
kind: ProvisioningRequestConfig
metadata:
name: prov-test-config
spec:
provisioningClassName: check-capacity.autoscaling.x-k8s.io
managedResources:
- nvidia.com/gpu
Where:
- provisioningClassName - describes the different modes of provisioning the resources. Supported ProvisioningClasses are listed in ClusterAutoscaler documentation, also check your cloud provider’s documentation for other ProvisioningRequest classes they support.
- managedResources - contains the list of resources managed by the autoscaling.
Check the API definition for more details.
Job annotations
Another way to pass ProvisioningRequest’s parameters is by using Job annotations. Every annotation with the provreq.kueue.x-k8s.io/ prefix will be directly passed to created ProvisioningRequest. E.g. provreq.kueue.x-k8s.io/ValidUntilSeconds: "60"
will pass ValidUntilSeconds
parameter with the value of 60
. See more examples below.
Once Kueue creates a ProvisioningRequest for the job you submitted, modifying the value of annotations in the job will have no effect in the ProvisioningRequest.
Example
Setup
apiVersion: kueue.x-k8s.io/v1beta1
kind: ResourceFlavor
metadata:
name: "default-flavor"
---
apiVersion: kueue.x-k8s.io/v1beta1
kind: ClusterQueue
metadata:
name: "cluster-queue"
spec:
namespaceSelector: {} # match all.
resourceGroups:
- coveredResources: ["cpu", "memory", "nvidia.com/gpu"]
flavors:
- name: "default-flavor"
resources:
- name: "cpu"
nominalQuota: 9
- name: "memory"
nominalQuota: 36Gi
- name: "nvidia.com/gpu"
nominalQuota: 9
admissionChecksStrategy:
admissionChecks:
- name: "sample-prov"
onFlavors: [default-flavor] # optional if the admission check targets all flavors.
---
apiVersion: kueue.x-k8s.io/v1beta1
kind: LocalQueue
metadata:
namespace: "default"
name: "user-queue"
spec:
clusterQueue: "cluster-queue"
---
apiVersion: kueue.x-k8s.io/v1beta1
kind: AdmissionCheck
metadata:
name: sample-prov
spec:
controllerName: kueue.x-k8s.io/provisioning-request
parameters:
apiGroup: kueue.x-k8s.io
kind: ProvisioningRequestConfig
name: prov-test-config
---
apiVersion: kueue.x-k8s.io/v1beta1
kind: ProvisioningRequestConfig
metadata:
name: prov-test-config
spec:
provisioningClassName: check-capacity.autoscaling.x-k8s.io
managedResources:
- nvidia.com/gpu
retryStrategy:
backoffLimitCount: 2
backoffBaseSeconds: 0
backoffMaxSeconds: 1800
Job using a ProvisioningRequest
apiVersion: batch/v1
kind: Job
metadata:
generateName: sample-job-
namespace: default
labels:
kueue.x-k8s.io/queue-name: user-queue
annotations:
provreq.kueue.x-k8s.io/maxRunDurationSeconds: "600"
spec:
parallelism: 3
completions: 3
suspend: true
template:
spec:
tolerations:
- key: "nvidia.com/gpu"
operator: "Exists"
effect: "NoSchedule"
containers:
- name: dummy-job
image: gcr.io/k8s-staging-perf-tests/sleep:v0.1.0
args: ["120s"]
resources:
requests:
cpu: "100m"
memory: "100Mi"
nvidia.com/gpu: 1
limits:
nvidia.com/gpu: 1
restartPolicy: Never
Feedback
Was this page helpful?
Glad to hear it! Please tell us how we can improve.
Sorry to hear that. Please tell us how we can improve.