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Catalogue / ml-platform

Kubeflow

ML platformkubeflow

Open source AI platform toolkit for pipelines, notebooks and training on Kubernetes.

Provider
default
Kind
ML platform
Category
Compute
Official docs
https://github.com/kubeflow/kubeflow
Properties · 3 set by this component
propertytypevaluesrequiredkind defaultthis component
computeInstancesinteger—no—inherited
distribution · component propertyenumsubproject | community-distribution | packaged-distributionno—inherited
experimentTrackingboolean—notrue▸ true
gpuEnabledboolean—no—inherited
hyperparameterTuning · component propertyboolean—no—inherited
managedboolean—nofalse▸ false
modelRegistryboolean—notrue▸ true
notebooks · component propertyboolean—no—inherited
pipelines · component propertyboolean—no—inherited
publicAccessboolean—no—inherited
Rules that apply · 1

Every rule whose selector covers this component's kind or its category. Whether a rule fires depends on the design: its properties, its edges and its groups.

Stateful node without zone redundancyerror
stateful-node-without-zone-redundancy

A stateful compute node pinned to exactly one availability zone disappears with that zone, and its state goes with it. Nodes inside a cell are exempt, because there the cell is deliberately single-zone and redundancy comes from the other cells.

  • — all of these hold:
  • — the node's `stateless` is false
  • — the node sits inside exactly 1 availability-zone group
  • — this does not hold:
  • — the node sits inside at least one cell group
Use it in a design
nodes:
  - { id: "kubeflow", component: "kubeflow" }
Other ML platform products · 61
Platform for AIalibaba-paialibabacloudml-platformAWS Clean Rooms MLaws-clean-rooms-mlawsml-platformAmazon SageMaker AIaws-sagemakerawsml-platformAmazon SageMaker Canvasaws-sagemaker-canvasawsml-platformAmazon SageMaker Feature Storeaws-sagemaker-feature-storeawsml-platformManaged MLflow on Amazon SageMaker AIaws-sagemaker-mlflowawsml-platformAmazon SageMaker Unified Studioaws-sagemaker-unified-studioawsml-platformMicrosoft Foundryazure-ai-foundryazureml-platformAzure Machine Learningazure-machine-learningazureml-platformAbacus.AIabacus-aiml-platformAlteryxalteryxml-platformArgillaargillaml-platformC3 AI Platformc3-aiml-platformClearMLclearmlml-platformCometcomet-mlml-platformCVATcvatml-platformDataikudataikuml-platformDataRobotdatarobotml-platformDatasaurdatasaurml-platformDetermined AIdeterminedml-platformDomino Data Labdomino-data-labml-platformDVCdvcml-platformEncordencordml-platformFeastfeastml-platformFlyteflyteml-platformH2O.aih2oml-platformKilikiliml-platformKNIMEknimeml-platformLabel Studiolabel-studioml-platformLabelboxlabelboxml-platformMetaflowmetaflowml-platformGeneric ML platformml-platformml-platformMLflowmlflowml-platformneptune.aineptune-aiml-platformNVIDIA DGX Cloudnvidia-dgx-cloudml-platformPachydermpachydermml-platformPolyaxonpolyaxonml-platformProdigyprodigyml-platformRapidMiner AI Hubrapidminerml-platformRoboflowroboflowml-platform
and 21 more → ML platform page
Source
# yaml-language-server: $schema=../../schema/component.schema.json
# Kubeflow: open source AI platform toolkit installed on a Kubernetes cluster.
# Facts from the Kubeflow project README: composable subprojects plus a community and a packaged
# distribution, self-managed by the team that deploys it.
schemaVersion: "1"
type: "component"
id: "kubeflow"
kind: "ml-platform"
provider: "default"
docs: "https://github.com/kubeflow/kubeflow"
defaults:
  experimentTracking: true
  modelRegistry: true
  managed: false
properties:
  distribution:
    type: "enum"
    values: ["subproject", "community-distribution", "packaged-distribution"]
  pipelines:
    type: "boolean"
  notebooks:
    type: "boolean"
  hyperparameterTuning:
    type: "boolean"

The same page as markdown, for an agent: /catalogue/components/kubeflow.md