- Home
- GPU Cluster Management Software
- Apache YuniKorn
Apache YuniKorn
What it is
Apache YuniKorn schedules batch, data, and machine learning workloads on Kubernetes. It serves as an alternative to the default Kubernetes scheduler and is described as transparent to existing Kubernetes applications. Hierarchical resource queues let administrators set tenant-level controls and align queues with an organization’s structure. Scheduling capabilities include gang scheduling, FIFO and Fair job ordering, resource fairness, reservations, and preemption.
A web interface brings together views of cluster capacity, utilization, and application information. YuniKorn exposes scheduling metrics through Prometheus, and the project provides instructions for monitoring with Prometheus and Grafana. The project recommends installing it on an existing Kubernetes cluster with its Helm chart and Helm 3 or later. YuniKorn is free under the Apache License 2.0. Releases include source code tarballs, which must be built before use, and prebuilt Docker images. The project advises verifying downloaded artifacts with GPG or SHA-512. Users can seek help in the YuniKorn Slack #yunikorn-user channel or through the user mailing list.
For and against
For
- Supports gang scheduling, reservations, and preemption.
- Hierarchical queues provide tenant resource controls.
- Web UI shows capacity, utilization, and application information.
- Provides Prometheus metrics and Grafana monitoring instructions.
Against
- Source tarballs must be built before use.
- Deployment guidance calls for Helm 3 or later on Kubernetes.
The verdict
YuniKorn adds workload scheduling policies and hierarchical resource controls to Kubernetes. Teams considering the source release should account for its build requirement; prebuilt Docker images are also published.
Who it suits
YuniKorn suits teams scheduling batch, data, or machine learning workloads on Kubernetes. Its queues and scheduling policies are relevant to administrators managing tenant resources.
Plans and prices
Apache YuniKorn
Apache License 2.0 · source code release must be built before use
Read 7 Oct 2026 · yunikorn.apache.org
On the record
- Deployment
- The project recommends deploying YuniKorn to an existing Kubernetes cluster using its Helm chart and Helm 3 or later.yunikorn.apache.org · read 7 Oct 2026
- Integrations
- YuniKorn exposes scheduling metrics via Prometheus, and the project provides instructions for monitoring with Prometheus and Grafana.yunikorn.apache.org · read 7 Oct 2026
- Intended users
- The community page identifies users and developers interested in using or contributing to YuniKorn as audiences for its community meetings.yunikorn.apache.org · read 7 Oct 2026
- Kubernetes scheduling
- YuniKorn is a Kubernetes-compatible alternative to the default Kubernetes scheduler and is described as transparent to existing Kubernetes applications.yunikorn.apache.org · read 7 Oct 2026
- License
- The software is licensed under the Apache License 2.0.yunikorn.apache.org · read 7 Oct 2026
- Purpose
- Apache YuniKorn is a resource scheduler for running batch, data, and machine learning workloads on Kubernetes.yunikorn.apache.org · read 7 Oct 2026
- Queues
- Hierarchical resource queues provide fine-grained resource controls for tenants and can map to an organization’s structure.yunikorn.apache.org · read 7 Oct 2026
- Release format
- YuniKorn is released as source code tarballs, and the project also publishes prebuilt Docker images.yunikorn.apache.org · read 7 Oct 2026
- Release verification
- The download page says release artifacts should be checked for tampering using GPG or SHA-512.yunikorn.apache.org · read 7 Oct 2026
- Scheduling features
- The scheduler supports gang scheduling, job ordering policies including FIFO and Fair, resource fairness, reservations, and preemption.yunikorn.apache.org · read 7 Oct 2026
- Security reporting
- The project asks people to report security issues to [email protected] and not disclose them publicly before working with the security team.yunikorn.apache.org · read 7 Oct 2026
- Support
- Users can ask for help in the YuniKorn Slack #yunikorn-user channel or use the user mailing list.yunikorn.apache.org · read 7 Oct 2026
- Web UI
- The web UI provides a centralized view of cluster capacity, utilization, and application information.yunikorn.apache.org · read 7 Oct 2026
