Volcano is a Kubernetes-native batch scheduling system, extending and enhancing the capabilities of the standard kube-scheduler. It provides a comprehensive set of features specifically designed to manage and optimize various batch and elastic workloads, including Artificial Intelligence (AI) / machine learning (ML) / deep learning (DL), bioinformatics / genomics, and other "Big Data" applications.
These workloads commonly leverage AI, Big Data, and HPC frameworks such as Spark, Flink, Ray, TensorFlow, PyTorch, Argo, MindSpore, PaddlePaddle, Kubeflow, MPI, Horovod, MXNet, KubeGene, and others, with which Volcano offers robust integration.
Volcano incorporates over fifteen years of collective experience in operating diverse high-performance workloads at scale across multiple systems and platforms. It combines proven best practices and innovative concepts from the open-source community to deliver a powerful and flexible scheduling solution.
As of 2025, Volcano has seen widespread adoption across numerous industries globally, including Internet/Cloud, Finance, Manufacturing, and Medical sectors. Many organizations and institutions are not only end-users but also active contributors to the project. Hundreds of contributors actively participate in code commits, pull request reviews, issue discussions, documentation updates, and design proposals. We encourage your participation in the ongoing development and growth of the Volcano project.
[!NOTE] the scheduler is built based on kube-batch; refer to #241 and #288 for more detail.
Volcano is an incubating project of the Cloud Native Computing Foundation (CNCF). Please consider joining the CNCF if you are an organization that wants to take an active role in supporting the growth and evolution of the cloud native ecosystem.
You can try Volcano by one of the following two ways.
[!NOTE]
- For Kubernetes v1.17 and above, use CRDs under config/crd/bases (recommended)
- For Kubernetes v1.16 and below, use CRDs under config/crd/v1beta1 (deprecated)
Install Volcano on an existing Kubernetes cluster. This way is both available for x86_64 and arm64 architecture.
kubectl apply -f https://raw.githubusercontent.com/volcano-sh/volcano/master/installer/volcano-development.yaml
Enjoy! Volcano will create the following resources in volcano-system namespace.
NAME READY STATUS RESTARTS AGE
pod/volcano-admission-5bd5756f79-dnr4l 1/1 Running 0 96s
pod/volcano-controllers-687948d9c8-nw4b4 1/1 Running 0 96s
pod/volcano-scheduler-94998fc64-4z8kh 1/1 Running 0 96s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/volcano-admission-service ClusterIP 10.98.152.108 <none> 443/TCP 96s
NAME READY UP-TO-DATE AVAILABLE AGE
deployment.apps/volcano-admission 1/1 1 1 96s
deployment.apps/volcano-controllers 1/1 1 1 96s
deployment.apps/volcano-scheduler 1/1 1 1 96s
NAME DESIRED CURRENT READY AGE
replicaset.apps/volcano-admission-5bd5756f79 1 1 1 96s
replicaset.apps/volcano-controllers-687948d9c8 1 1 1 96s
replicaset.apps/volcano-scheduler-94998fc64 1 1 1 96s
NAME COMPLETIONS DURATION AGE
job.batch/volcano-admission-init 1/1 48s 96s
To install official release, please visit helm-charts for details.
helm repo add volcano-sh https://volcano-sh.github.io/helm-charts
helm install volcano volcano-sh/volcano -n volcano-system --create-namespace
Install from source code for developers:
helm install volcano installer/helm/chart/volcano --namespace volcano-system --create-namespace
# list helm release
helm list -n volcano-system
If you don't have a kubernetes cluster, try one-click install from code base:
./hack/local-up-volcano.sh
This way is only available for x86_64 temporarily.
Please follow the guide Volcano Agent to install volcano agent.
If you want to get prometheus and grafana volcano dashboard after volcano installed, try following commands:
kubectl create -f installer/volcano-monitoring.yaml
Please follow the guide Volcano Dashboard to install volcano dashboard.
| Kubernetes 1.17 | Kubernetes 1.18 | Kubernetes 1.19 | Kubernetes 1.20 | Kubernetes 1.21 | Kubernetes 1.22 | Kubernetes 1.23 | Kubernetes 1.24 | Kubernetes 1.25 | Kubernetes 1.26 | Kubernetes 1.27 | Kubernetes 1.28 | Kubernetes 1.29 | Kubernetes 1.30 | Kubernetes 1.31 | Kubernetes 1.32 | Kubernetes 1.33 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Volcano v1.6 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | - | - | - | - | - | - | - | - | - | - |
| Volcano v1.7 | - | - | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | - | - | - | - | - |
| Volcano v1.8 | - | - | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | - | - | - | - | - |
| Volcano v1.9 | - | - | - | - | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | - | - | - | - |
| Volcano v1.10 | - | - | - | - | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | - | - | - |
| Volcano v1.11 | - | - | - | - | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | - | - |
| Volcano v1.12 | - | - | - | - | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | - |
| Volcano HEAD (master) | - | - | - | - | - | - | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
Key:
✓ Volcano and the Kubernetes version are exactly compatible.+ Volcano has features or API objects that may not be present in the Kubernetes version.- The Kubernetes version has features or API objects that Volcano can't use.If Volcano helps your research, we appreciate your citations. Here is the BibTeX entry:
@misc{volcano2025,
title={Volcano: A Cloud Native Batch System},
author={Klaus Ma and Kevin Wang and others},
year={2025},
howpublished={\url{https://github.com/volcano-sh/volcano}},
}
We hold community meetings for different timezones. See Volcano Community Meeting Info.
Resources:
If you have any question, feel free to reach out to us in the following ways:
WeChat: Please add WeChat account k8s2222 and request an invitation to the group chat.
FAQs
Unknown package
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Research
/Security News
Socket is tracking cloned Open VSX extensions tied to GlassWorm, with several updated from benign-looking sleepers into malware delivery vehicles.
Product
Reachability analysis for PHP is now available in experimental, helping teams identify which vulnerabilities are actually exploitable.
Product
Export Socket alert data to your own cloud storage in JSON, CSV, or Parquet, with flexible snapshot or incremental delivery.