Kueue is a set of APIs and controller for job queueing. It is a job-level manager that decides when a job should be admitted to start (as in pods can be created) and when it should stop (as in active pods should be deleted).
Read the overview and watch the Kueue-related talks & presentations to learn more.
- Job management: Support job queueing based on priorities with different strategies:
StrictFIFO
andBestEffortFIFO
. - Advanced Resource management: Comprising: resource flavor fungibility, fair sharing, cohorts and preemption with a variety of policies between different tenants.
- Integrations: Built-in support for popular jobs, e.g. BatchJob, Kubeflow training jobs, RayJob, RayCluster, JobSet, plain Pod and Pod Groups.
- System insight: Build-in prometheus metrics to help monitor the state of the system, and on-demand visibility endpoint for monitoring of pending workloads.
- 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 and dynamic reclaim: mechanisms to run a job with reduced parallelism, based on available quota, and to release the quota the pods complete..
- Mixing training and inference: Simultaneous management of batch workloads along with serving workloads (such as Deployments or StatefulSets)
- Multi-cluster job dispatching: called MultiKueue, allows to search for capacity and off-load the main cluster.
- Topology-Aware Scheduling: Allows to optimize the Pod-to-Pod communication throughput by scheduling aware of the data-center topology.
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✔️ API version: v1beta1, respecting Kubernetes Deprecation Policy
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✔️ Up-to-date documentation.
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✔️ Test Coverage:
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✔️ Scalability verification via performance tests.
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✔️ Monitoring via metrics.
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✔️ Security: RBAC based accessibility.
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✔️ Stable release cycle(2-3 months) for new features, bugfixes, cleanups.
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✔️ Adopters running on production.
Based on community feedback, we continue to simplify and evolve the API to address new use cases.
Requires Kubernetes 1.25 or newer.
To install the latest release of Kueue in your cluster, run the following command:
kubectl apply --server-side -f https://github.com/kubernetes-sigs/kueue/releases/download/v0.10.0/manifests.yaml
The controller runs in the kueue-system
namespace.
Read the installation guide to learn more.
A minimal configuration can be set by running the examples:
kubectl apply -f examples/admin/single-clusterqueue-setup.yaml
Then you can run a job with:
kubectl create -f examples/jobs/sample-job.yaml
Learn more about:
Learn more about the architecture of Kueue with the following design docs:
- bit.ly/kueue-apis discusses the API proposal and a high level description of how Kueue operates. Join the mailing list to get document access.
- bit.ly/kueue-controller-design presents the detailed design of the controller.
High-level overview of the main priorities for 2025:
- Improve user experience for MultiKueue - multi-cluster Job dispatching, in particular:
- Improve user experience for Topology Aware Scheduling, in particular:
- Productization of the Kueue dashboard #940
- Support Hierarchical Cohorts with FairSharing #3759
- Improved support for AI inference, including:
- Progress towards the stable API (v1beta2) #768
Long-term aspirational goals:
- Integration with workflow frameworks #74
- Support dynamically-sized Jobs #77
- Budget support #28
- Flavor assignment strategies, e.g. minimizing cost vs minimizing borrowing #312
- Cooperative preemption support for workloads that implement checkpointing #477
- Delayed preemption for two-stage admission #3758
- Support Structured Parameters (DRA) in Kueue #2941
- Graduate the API to v1 #3476
Learn how to engage with the Kubernetes community on the community page and the contributor's guide.
You can reach the maintainers of this project at:
Participation in the Kubernetes community is governed by the Kubernetes Code of Conduct.