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On the recordRead 8 Oct 202618 facts
Voda Scheduler
On the record
- API
- The project documentation links to API endpoints as part of its getting-started steps.github.com · read 8 Oct 2026
- Changing nodes
- The scheduler is aware of node additions and deletions, works with an existing autoscaler, and is designed to tolerate failing nodes and spot instances that may come and go.github.com · read 8 Oct 2026
- Compatibility
- The project says it was tested with Kubernetes v1.20.github.com · read 8 Oct 2026
- Deployment
- The project says Voda Scheduler is designed to deploy in any Kubernetes cluster, on-cloud or on-premise, that can schedule GPUs.github.com · read 8 Oct 2026
- Elastic training
- It supports dynamically scaling distributed training jobs up or down at runtime without interrupting training.github.com · read 8 Oct 2026
- Fault tolerance
- The project lists fault tolerance as a feature.github.com · read 8 Oct 2026
- Intended users
- The stated use case is elastic or distributed deep learning workloads running in a Kubernetes cluster.github.com · read 8 Oct 2026
- License
- The GitHub repository identifies an Apache-2.0 license.github.com · read 8 Oct 2026
- License and maturity
- The repository lists an Apache-2.0 license and warns that everything is experimental and may change significantly at any time.github.com · read 8 Oct 2026
- Maturity
- The README warns that everything is experimental and may change significantly at any time.github.com · read 8 Oct 2026
- Monitoring
- The README links to documentation for Prometheus metrics exposed by the scheduler.github.com · read 8 Oct 2026
- Node changes
- It is aware of node additions and deletions, works with an existing autoscaler, and tolerates failing nodes.github.com · read 8 Oct 2026
- Prerequisite
- The README says the scheduler was tested with Kubernetes v1.20.github.com · read 8 Oct 2026
- Purpose
- Voda Scheduler is a GPU scheduler for elastic deep learning workloads built on Kubernetes, Kubeflow Training Operator, and Horovod.github.com · read 8 Oct 2026
- Related tools
- The README names Kubeflow Training Operator, Kubeflow MPI Operator, Horovod, and a Prometheus NVIDIA SMI exporter among related projects.github.com · read 8 Oct 2026
- Resource allocation
- The scheduler aims to use idle resources and allocate resources efficiently when a cluster is heavily loaded.github.com · read 8 Oct 2026
- Scheduling algorithms
- The listed algorithms include FIFO, Elastic-FIFO (the default), SRJF, Elastic-SRJF, Tiresias, Elastic-Tiresias, FfDL Optimizer, and AFS-L.github.com · read 8 Oct 2026
- Topology awareness
- Topology-aware scheduling and worker migration can consolidate resources to maximize cluster throughput.github.com · read 8 Oct 2026
