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Volcano

Volcano is a CNCF incubating batch processing and high-performance computing (HPC) scheduler for Kubernetes. It provides advanced scheduling capabilities including gang scheduling, fair-share scheduling, queue management, and job lifecycle management for batch workloads such as machine learning training, big data processing, and scientific computing. Volcano extends Kubernetes with three CRDs: Job (vcjob), Queue, and PodGroup.

3 APIs 1 Capabilities 0 Features
Batch ProcessingCloud NativeHPCIncubatingKubernetesSchedulingMachine Learning

APIs

Volcano Batch Scheduling API

Volcano extends Kubernetes with CRDs for batch workload management. The Job resource defines batch workloads with multiple task types and lifecycle policies. Queue resources man...

Volcano Queue API

Kubernetes CRD for defining and managing job queues in Volcano. Queues collect PodGroups and support weight-based fair-share scheduling and resource quotas, providing the primar...

Volcano PodGroup API

Kubernetes CRD that represents a group of pods with strong association, used as the unit of gang scheduling in Volcano. PodGroups define the minimum number of pods that must be ...

Capabilities

Volcano Batch Workload Management

Unified capability for managing Volcano batch workloads on Kubernetes. Combines Job, Queue, and PodGroup APIs to orchestrate distributed ML training, HPC simulation, big data pr...

Run with Naftiko

Semantic Vocabularies

Volcano Context

0 classes · 7 properties

JSON-LD

API Governance Rules

Volcano API Rules

7 rules · 1 errors 4 warnings 2 info

SPECTRAL

Resources

🔗
Website
Website
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JSON-LD
JSON-LD
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JSONSchema
JSONSchema
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JSONStructure
JSONStructure
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Vocabulary
Vocabulary
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SpectralRules
SpectralRules
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NaftikoCapability
NaftikoCapability
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Documentation
Documentation
🚀
Getting Started
Getting Started
📰
Blog
Blog
👥
GitHub Organization
GitHub Organization
👥
GitHubRepository
GitHubRepository
🔗
Community
Community

Sources

Raw ↑
aid: volcano
name: Volcano
description: >-
  Volcano is a CNCF incubating batch processing and high-performance
  computing (HPC) scheduler for Kubernetes. It provides advanced scheduling
  capabilities including gang scheduling, fair-share scheduling, queue
  management, and job lifecycle management for batch workloads such as
  machine learning training, big data processing, and scientific computing.
  Volcano extends Kubernetes with three CRDs: Job (vcjob), Queue, and PodGroup.
url: https://volcano.sh
image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg
tags:
  - Batch Processing
  - Cloud Native
  - HPC
  - Incubating
  - Kubernetes
  - Scheduling
  - Machine Learning
created: '2026-03-16'
modified: '2026-05-03'
specificationVersion: '0.19'
type: Index
apis:
  - aid: volcano:volcano-api
    name: Volcano Batch Scheduling API
    description: >-
      Volcano extends Kubernetes with CRDs for batch workload management.
      The Job resource defines batch workloads with multiple task types and
      lifecycle policies. Queue resources manage job scheduling with
      weight-based fair sharing and resource quotas. Volcano supports
      gang scheduling ensuring all pods in a group are scheduled together,
      and integrates with frameworks like TensorFlow, PyTorch, Spark, and MPI.
    humanURL: https://volcano.sh/en/docs/
    properties:
      - type: Documentation
        url: https://volcano.sh/en/docs/
      - type: Reference
        url: https://volcano.sh/en/docs/vcjob/
      - type: Getting Started
        url: https://volcano.sh/en/docs/installation/
      - type: OpenAPI
        url: openapi/volcano-job-openapi.yml
      - type: JSONSchema
        url: json-schema/volcano-job-schema.json
    tags:
      - Batch Scheduling
      - Gang Scheduling
      - Queues
  - aid: volcano:volcano-queue-api
    name: Volcano Queue API
    description: >-
      Kubernetes CRD for defining and managing job queues in Volcano. Queues
      collect PodGroups and support weight-based fair-share scheduling and resource
      quotas, providing the primary mechanism for multi-tenant resource partitioning
      and priority-based job admission.
    humanURL: https://volcano.sh/en/docs/v1-10-0/queue/
    properties:
      - type: Documentation
        url: https://volcano.sh/en/docs/v1-10-0/queue/
      - type: OpenAPI
        url: openapi/volcano-queue-openapi.yml
    tags:
      - Batch Scheduling
      - Kubernetes
      - Multi-Tenancy
      - Queues
      - Resource Management
  - aid: volcano:volcano-podgroup-api
    name: Volcano PodGroup API
    description: >-
      Kubernetes CRD that represents a group of pods with strong association,
      used as the unit of gang scheduling in Volcano. PodGroups define the minimum
      number of pods that must be scheduled together, enabling all-or-nothing
      scheduling semantics for distributed training and computing workloads.
    humanURL: https://volcano.sh/en/docs/podgroup/
    properties:
      - type: Documentation
        url: https://volcano.sh/en/docs/podgroup/
      - type: OpenAPI
        url: openapi/volcano-podgroup-openapi.yml
    tags:
      - Batch Scheduling
      - Distributed Computing
      - Gang Scheduling
      - Kubernetes
      - Pod Management
common:
  - type: Website
    url: https://volcano.sh/en/
  - type: JSON-LD
    url: json-ld/volcano-context.jsonld
  - type: JSONSchema
    url: json-schema/volcano-job-schema.json
  - type: JSONStructure
    url: json-structure/volcano-job-structure.json
  - type: Vocabulary
    url: vocabulary/volcano-vocabulary.yml
  - type: SpectralRules
    url: rules/volcano-rules.yml
  - type: NaftikoCapability
    url: capabilities/batch-workload-management.yaml
  - type: Documentation
    url: https://volcano.sh/en/docs/
  - type: Getting Started
    url: https://volcano.sh/en/docs/installation/
  - type: Blog
    url: https://volcano.sh/en/blog/
  - type: GitHub Organization
    url: https://github.com/volcano-sh
  - type: GitHubRepository
    url: https://github.com/volcano-sh/volcano
  - type: Community
    url: https://github.com/volcano-sh/community
maintainers:
  - FN: Kin Lane
    email: [email protected]