Kubernetes batch scheduler for AI/ML/DL, big data, and HPC workloads
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Volcano is a Kubernetes-native batch scheduling system designed to enhance the default kube-scheduler for AI, ML, Big Data, and HPC workloads. It offers robust integration with popular frameworks like Spark, TensorFlow, PyTorch, and MPI, providing a mature and flexible solution for managing complex, high-performance computing tasks on cloud-native infrastructure.
How It Works
Volcano extends Kubernetes scheduling by introducing a custom scheduler and CRDs for defining batch jobs. It leverages concepts from kube-batch and incorporates over fifteen years of experience in operating high-performance workloads. This approach allows for advanced features like gang scheduling, resource preemption, and topology-aware scheduling, optimizing resource utilization and job execution for demanding applications.
Quick Start & Requirements
kubectl apply -f https://raw.githubusercontent.com/volcano-sh/volcano/master/installer/volcano-development.yaml
or via Helm: helm install volcano volcano-sh/volcano -n volcano-system --create-namespace
.volcano-admission
, volcano-controllers
, and volcano-scheduler
pods in the volcano-system
namespace.Highlighted Details
Maintenance & Community
Licensing & Compatibility
Limitations & Caveats
The README notes that the one-click install script ./hack/local-up-volcano.sh
is temporarily only available for x86_64 architecture. Compatibility with older Kubernetes versions (< v1.16) uses deprecated CRDs.
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