Overview
Kueue is a kubernetes-native system that manages quotas and how jobs consume them. Kueue decides when a job should wait, when a job should be admitted to start (as in pods can be created) and when a job should be preempted (as in active pods should be deleted).
Why use Kueue
You can install Kueue on top of a vanilla Kubernetes cluster. Kueue does not replace any existing Kubernetes components. Kueue is compatible with cloud environments where:
- Compute resources are elastic and can be scaled up and down.
- Compute resources are heterogeneous (in architecture, availability, price, etc.).
Kueue APIs allow you to express:
- Quotas and policies for fair sharing among tenants.
- Resource fungibility: if a resource flavor is fully utilized, Kueue can admit the job using a different flavor.
A core design principle for Kueue is to avoid duplicating mature functionality in Kubernetes components and well-established third-party controllers. Autoscaling, pod-to-node scheduling and job lifecycle management are the responsibility of cluster-autoscaler, kube-scheduler and kube-controller-manager, respectively. Advanced admission control can be delegated to controllers such as gatekeeper.
Features overview
- Job management: Support job queueing based on priorities with different strategies:
StrictFIFO
andBestEffortFIFO
. - Resource management: Support resource fair sharing and preemption with a variety of policies between different tenants.
- Dynamic resource reclaim: A mechanism to release quota as the pods of a Job complete.
- Resource flavor fungibility: Quota borrowing or preemption in ClusterQueue and Cohort.
- Integrations: Built-in support for popular jobs, e.g. BatchJob, Kubeflow training jobs, RayJob, RayCluster, JobSet, plain Pod.
- System insight: Built-in prometheus metrics to help monitor the state of the system, as well as Conditions.
- AdmissionChecks: A mechanism for internal or external components to influence whether a workload can be admitted.
- Advanced autoscaling support: Integration with cluster-autoscaler’s provisioningRequest via admissionChecks.
- All-or-nothing with ready Pods: A timeout-based implementation of All-or-nothing scheduling.
- Partial admission: Allows jobs to run with a smaller parallelism, based on available quota, if the application supports it.
Job-integrated features
Feature | Batch Job | JobSet | MXJob | PaddleJob | PytorchJob | TFJob | XGBoostJob | MPIJob | Pod | RayCluster | RayJob |
---|---|---|---|---|---|---|---|---|---|---|---|
Dynamic Reclaim | + | + | + | ||||||||
MultiKueue | + | + | + | + | + | + | + | ||||
MultiKueueBatchJobWithManagedBy | + | ||||||||||
PartialAdmission | + | ||||||||||
Workload Priority Class | + | + | + | + | + | + | + | + | + | + | + |
FlavorFungibility | + | + | + | + | + | + | + | + | + | + | + |
ProvisioningACC | + | + | + | + | + | + | + | + | + | + | + |
QueueVisibility | + | + | + | + | + | + | + | + | + | + | + |
VisibilityOnDemand | + | + | + | + | + | + | + | + | + | + | + |
PrioritySortingWithinCohort | + | + | + | + | + | + | + | + | + | + | + |
LendingLimit | + | + | + | + | + | + | + | + | + | + | + |
All-or-nothing with ready Pods | + | + | + | + | + | + | + | + | + | + | + |
Fair Sharing | + | + | + | + | + | + | + | + | + | + | + |
Topology Aware Scheduling | + | + | + | + | + | + | + | + | + | + | + |
High-level Kueue operation
To learn more about Kueue concepts, see the concepts section.
To learn about different Kueue personas and what you can do with Kueue, see the tasks section.
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