volcano-sh/volcano
A Cloud Native Batch System (Project under CNCF) observed · 2026-08-28
Health v2 · maintenance only
98/100
- Activity 99
- Release rhythm 95
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: 22.0
- age_days: 2729
- days_rel: 34
- days_push: 7
- n_releases_24m: 25
Adoption not part of the score
5899 stars · 1506 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Volcano is a CNCF-hosted, Kubernetes-native batch scheduling system that extends kube-scheduler for high-performance workloads like AI/ML training, big data, and HPC. It provides gang scheduling, queue management, heterogeneous GPU/NPU scheduling, and multi-cluster scheduling with integrations for frameworks such as TensorFlow, PyTorch, Spark, Flink, and Ray.
Use cases
- run distributed PyTorch or TensorFlow training jobs on Kubernetes with gang scheduling
- schedule Spark and Flink batch workloads on a Kubernetes cluster
- manage GPU sharing and heterogeneous device scheduling for AI workloads
- implement multi-level queue and resource quota management for batch jobs
- colocate online and offline workloads to improve cluster utilization
- schedule jobs across multiple Kubernetes clusters
- run HPC and genomics workloads on Kubernetes
When to choose
- you need gang scheduling so all pods of a distributed job start together
- you run AI/ML training, big data, or HPC batch workloads on Kubernetes
- you need fine-grained queue management, quotas, and preemption for batch jobs
- you need GPU/NPU scheduling with CUDA, MIG, or device sharing
- you want to colocate online services and offline batch jobs
When to avoid
- you only run simple microservices with default kube-scheduler needs
- you are not using Kubernetes as your orchestration platform
- you need a lightweight single-node scheduler without cluster infrastructure
Facets
service · maturity stable
container-orchestration scheduling cloud gpu-computing workflow-automation microservices cloud-computing machine-learning big-data go cloud batch-scheduling gang-scheduling hpc kubernetes-scheduler cncf gpu-scheduling queue-management distributed-training devops kubernetes linux docker
10 sources
- readme: https://github.com/volcano-sh/volcano · fetched 2026-08-28 · 668945e4d2c8
- homepage: https://volcano.sh · fetched 2026-08-29 · b22fd0d81fb8
- site_page: https://volcano.sh/docs/Home/Introduction · fetched 2026-08-29 · 6d73c522decb
- site_page: https://volcano.sh/docs/v1.15.0/Home/Introduction · fetched 2026-08-29 · 4ce8e8465a65
- site_page: https://volcano.sh/docs/v1.14.0/Home/Introduction · fetched 2026-08-29 · ea4574fd4b2f
- site_page: https://volcano.sh/docs/v1.13.0/Home/Introduction · fetched 2026-08-29 · 5b70741a426b
- site_page: https://volcano.sh/docs/v1.12.0/Home/Introduction · fetched 2026-08-29 · 241f168d64dd
- site_page: https://volcano.sh/docs/v1.11.0/Home/Introduction · fetched 2026-08-29 · 94b55c0d2511
- site_page: https://volcano.sh/docs/v1.10.0/Home/Introduction · fetched 2026-08-29 · 55b2f54b8639
- site_page: https://volcano.sh/docs/v1.9.0/Home/Introduction · fetched 2026-08-29 · b824f0b3fd6b
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| volcano-sh/volcano | main | 98 |
For agents
markdown · JSON · MCP: product_card(name="volcano-sh/volcano")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem