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Platform For AI:Resource quota

Last Updated:Dec 04, 2024

You can allocate resources in the resource pool by creating resource quotas, adjusting the limits of existing resource quotas, or creating child-level resource quotas. After a resource quota is associated with a workspace, you can use the resource quota in the workspace for AI development and training. This way, you can use and manage the resources in a flexible and efficient manner.

Features

After you purchase resources in the resource pool, you can create resource quotas or adjust the limits of existing resource quotas to allocate and manage the purchased resources. You can associate resources in different resource groups with the same resource quota. You can also create a multi-level hierarchy of child-level resource quotas to refine the allocation of resources in a resource quota. The following types of resource quotas are supported based on the resource types:

  • Resource quotas for cloud-native resources, including Lingjun resources and general computing resources. You can create child-level resource quotas to generate a quota tree that enhances the performance in queueing and scheduling.

  • Resource quotas for big data resources, including MaxCompute resources and fully managed Flink resources.

Create a resource quota

Manage cloud-native resource quotas

You can manage the cloud-native resource quotas that you create. For more information, see Manage resource quotas.