Manage computing resources, user permissions, and AI assets within workspaces to enable team collaboration across AI development stages.
Features
Workspaces offer:
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Computing resource management: Manage all AI development computing resources on a single platform.
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Permission management: Control member permissions at a fine-grained level.
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AI asset management: Save and manage AI models and algorithms for improvement and team collaboration.
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Event monitoring and alerting: Create alerting rules to monitor Deep Learning Containers (DLC) jobs, Machine Learning Designer pipeline jobs, or model version approval status.
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Resource scheduling: Allocate resource quotas, set maximum job runtime, and assign job priorities based on components and member roles to optimize resource distribution.
Roles
PAI provides these predefined roles for AI development and management:
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Resource administrator: Must be assigned to an Alibaba Cloud account or authorized RAM user. Add or delete workspaces and create Data Science Workshop (DSW) instances.
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Workspace administrator/owner: Manage members and public assets in the workspace.
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Algorithm developer: Manage training jobs and public assets.
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Algorithm O&M engineer: Manage all workspace training jobs, including viewing DLC jobs created by other members.
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Labeling administrator: Create and update labeling datasets.
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Visitor: View workspace information (members, resource groups, pipelines).
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MaxCompute developer: Use MaxCompute to execute jobs submitted in the workspace.
For role permissions, see Roles and permissions.
Workspace operations
To create and manage workspaces or configure notifications, see Workspace.
Asset management
To manage AI computing assets (datasets, models, images, jobs) in PAI, see AI Computing Asset Management.