ClearML

AI development platform for experiment tracking, orchestration and model management.

Provider: default
Kind: ML platform
Category: Compute
Official docs: https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server/
Also known as: Trains

Properties · 3 set by this component

property	type	values	required	kind default	this component
computeInstances	integer	—	no	—	inherited
dataManagement · component property	boolean	—	no	true	inherited
deploymentFormat · component property	enum	docker-compose \| kubernetes \| cloud-image	no	—	inherited
experimentTracking	boolean	—	no	true	▸ true
gpuEnabled	boolean	—	no	—	inherited
hosting · component property	enum	self-hosted \| hosted-service	no	self-hosted	inherited
managed	boolean	—	no	false	▸ false
modelRegistry	boolean	—	no	true	▸ true
publicAccess	boolean	—	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: "clearml", component: "clearml" }

Other ML platform products · 61

Platform for AIalibaba-paialibabacloudml-platform AWS Clean Rooms MLaws-clean-rooms-mlawsml-platform Amazon SageMaker AIaws-sagemakerawsml-platform Amazon SageMaker Canvasaws-sagemaker-canvasawsml-platform Amazon SageMaker Feature Storeaws-sagemaker-feature-storeawsml-platform Managed MLflow on Amazon SageMaker AIaws-sagemaker-mlflowawsml-platform Amazon SageMaker Unified Studioaws-sagemaker-unified-studioawsml-platform Microsoft Foundryazure-ai-foundryazureml-platform Azure Machine Learningazure-machine-learningazureml-platform Abacus.AIabacus-aiml-platform Alteryxalteryxml-platform Argillaargillaml-platform C3 AI Platformc3-aiml-platform Cometcomet-mlml-platform CVATcvatml-platform Dataikudataikuml-platform DataRobotdatarobotml-platform Datasaurdatasaurml-platform Determined AIdeterminedml-platform Domino Data Labdomino-data-labml-platform DVCdvcml-platform Encordencordml-platform Feastfeastml-platform Flyteflyteml-platform H2O.aih2oml-platform Kilikiliml-platform KNIMEknimeml-platform Kubeflowkubeflowml-platform Label Studiolabel-studioml-platform Labelboxlabelboxml-platform Metaflowmetaflowml-platform Generic ML platformml-platformml-platform MLflowmlflowml-platform neptune.aineptune-aiml-platform NVIDIA DGX Cloudnvidia-dgx-cloudml-platform Pachydermpachydermml-platform Polyaxonpolyaxonml-platform Prodigyprodigyml-platform RapidMiner AI Hubrapidminerml-platform Roboflowroboflowml-platform

and 21 more → ML platform page

Source

1# yaml-language-server: $schema=../../schema/component.schema.json
2# ClearML: AI development platform with experiment tracking, orchestration, data and model management.
3# Facts from "ClearML Server": the same server runs either as the hosted service at app.clear.ml or
4# self-hosted from Docker images, Kubernetes Helm charts or cloud AMIs.
5schemaVersion: "1"
6type: "component"
7id: "clearml"
8kind: "ml-platform"
9provider: "default"
10docs: "https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server/"
11aliases: ["Trains"]
12defaults:
13  experimentTracking: true
14  modelRegistry: true
15  managed: false
16properties:
17  hosting:
18    type: "enum"
19    values: ["self-hosted", "hosted-service"]
20    default: "self-hosted"
21  deploymentFormat:
22    type: "enum"
23    values: ["docker-compose", "kubernetes", "cloud-image"]
24  dataManagement:
25    type: "boolean"
26    default: true

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