Koordinator vs Volcano
Koordinator
koordinator.sh
Volcano
volcano.shSide by side
| Figure | Koordinator | Volcano |
|---|---|---|
| Price from | — | — |
| Free plan | — | — |
| Free trial | — | — |
| Open source | — | — |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 0 |
| Spec score · GPU Cluster Management Software | 7.5 (#10) | 6.5 (#19) |
| Community support | The project provides community support through a Slack #koordinator channel and a DingTalk group. | The project directs users to the CNCF #volcano Slack channel, a mailing list, and GitHub issues and repositories. |
| Purpose | Koordinator is a QoS-based scheduling system for efficient orchestration of microservices, AI and big-data workloads on Kubernetes. | Volcano is a cloud native system for high-performance workloads and a container batch scheduling project. |
| Scheduling policies | It provides customizable scheduling policies and profiles for workloads including Web Service, Spark, Presto, TensorFlow, and PyTorch. | Its scheduling policies include gang, binpack, heterogeneous-device, capacity, fair-share, task-topology, and NUMA-aware scheduling. |
In their own words
Koordinator
Koordinator is a free, self-hosted QoS scheduling system for Kubernetes microservices, AI, big-data, audio, and video workloads. It adds priority and quality-of-service controls so different pods and workload types can share nodes. Application profiling supports resource overcommitment while preserving QoS guarantees, and fine-grained isolation targets latency-sensitive work alongside batch jobs. Customizable policies cover Web Service, Spark, Presto, TensorFlow, and PyTorch. QoSManager tunes pod isolation using profiling, interference detection, and SLO settings. Koord-Queue supports TFJob, PyTorchJob, Spark, Argo Workflow, Ray, and native Kubernetes Jobs, with Kueue AdmissionCheck compatibility. YARN Copilot connects Hadoop YARN jobs with Kubernetes pods. Koordinator works alongside kube-scheduler, using control-plane and node components without invasive native changes. Helm 3.5 or newer and Kubernetes 1.18 or newer are required.