Apache YuniKorn
Apache YuniKorn schedules batch, data, and machine learning workloads on Kubernetes.
What Apache YuniKorn is
Apache YuniKorn schedules batch, data, and machine learning workloads on Kubernetes. It offers an alternative to the default Kubernetes scheduler and is described as transparent to existing Kubernetes applications. Hierarchical resource queues let teams set fine-grained tenant controls and reflect organizational structure. Scheduling capabilities include gang scheduling, FIFO and Fair job ordering, resource fairness, reservations, and preemption. A web UI presents cluster capacity, utilization, and application information in one view, while Prometheus metrics and project instructions support monitoring with Prometheus and Grafana. The project recommends deploying YuniKorn to an existing Kubernetes cluster using its Helm chart and Helm 3 or later. It is free and open source under the Apache License 2.0. Releases include source tarballs, which must be built before use, and prebuilt Docker images. The project recommends verifying release artifacts against tampering with GPG or SHA-512. Users can request help in the YuniKorn Slack #yunikorn-user channel or through the user mailing list. Security issues should be reported privately to [email protected] rather than disclosed publicly before working with the security team.
Good
- Free under the Apache License 2.0
- Supports hierarchical tenant resource queues
- Offers gang scheduling, reservations, and preemption
- Web UI shows capacity, utilization, and applications
- Provides Prometheus metrics
Watch out
- Source releases must be built before use
- Deployment guidance assumes an existing Kubernetes cluster
- Recommended Helm version is 3 or later
Who it suits
YuniKorn suits teams running batch, data, or machine learning workloads on Kubernetes that need queue-based resource controls and scheduling policies. It is also relevant to users and developers interested in using or contributing to the project.
Verdict
YuniKorn offers Kubernetes workload scheduling with tenant queues, several scheduling policies, and a cluster overview interface. Teams should account for the existing-cluster deployment recommendation and the build step required for source releases.
Plans and prices
From Apache YuniKorn's own pricing page, checked 7 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Apache YuniKorn | Free | Apache License 2.0 · source code release must be built before use |
The facts
Each one read from Apache YuniKorn's own pages, with the date it was checked.
What it does
- Deployment
- The project recommends deploying YuniKorn to an existing Kubernetes cluster using its Helm chart and Helm 3 or later.checked 7 Oct 2026
- Integrations
- YuniKorn exposes scheduling metrics via Prometheus, and the project provides instructions for monitoring with Prometheus and Grafana.checked 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.checked 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.checked 7 Oct 2026
- License
- The software is licensed under the Apache License 2.0.checked 7 Oct 2026
- Purpose
- Apache YuniKorn is a resource scheduler for running batch, data, and machine learning workloads on Kubernetes.checked 7 Oct 2026
- Queues
- Hierarchical resource queues provide fine-grained resource controls for tenants and can map to an organization’s structure.checked 7 Oct 2026
- Release format
- YuniKorn is released as source code tarballs, and the project also publishes prebuilt Docker images.checked 7 Oct 2026
- Release verification
- The download page says release artifacts should be checked for tampering using GPG or SHA-512.checked 7 Oct 2026
- Scheduling features
- The scheduler supports gang scheduling, job ordering policies including FIFO and Fair, resource fairness, reservations, and preemption.checked 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.checked 7 Oct 2026
- Support
- Users can ask for help in the YuniKorn Slack #yunikorn-user channel or use the user mailing list.checked 7 Oct 2026
- Web UI
- The web UI provides a centralized view of cluster capacity, utilization, and application information.checked 7 Oct 2026
