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Instance resources provide the GPU/CPU computing power used by development environments, training tasks, and inference services. Before creating a workload, you need to understand the resource pool types, purchase or verify the instance quota, and determine which resource pool the quota will be assigned to. Quotas purchased without a specified target resource pool will be assigned to the shared resource pool and can be adjusted later as needed.

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Applicable Scenarios

  • Create JupyterLab or VS Code Server development environments.
  • Submit training jobs such as PyTorchJob and RayJob.
  • Publish LLM inference services or general services.
  • Reserve a fixed amount of computing capacity for your team.

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Learn About Resource Pool Types

When selecting a resource pool, first determine whether your task requires dedicated guarantees or node isolation.

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Buy Instance

If you do not have sufficient instance quota, you can first purchase instance resources. Go to Resources > Order, and under the Instance tab, click Buy. When purchasing an instance, select the Region and Cluster to which the resource belongs, and configure the following parameters: When purchasing instance resources, pay close attention to Target Pool. It determines which resource pool the instance quota purchased in this transaction will be allocated to:

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Estimate Task Resource Requirements

Before submitting a development environment, training task, or inference service, estimate the required resources based on the instance specification, number of specifications, and number of replicas, then verify the target resource pool and your remaining quota. Total task requirements = Resources per instance specification × Instance specifications per replica × Number of replicas. For example, an instance specification includes 2 GPUs, 16 vCPUs, and 128 GiB of memory. Each replica in the task uses 3 such specifications, and 4 replicas are running in total. The resource requirements are as follows: This task requires a total of 12 units of the specified configuration. Before submitting, verify this total against Remaining Quota and the available capacity in the target resource pool for the selected instance specification. The computation methods for different task types must also take role differences into account:
  • The total number of replicas for a PyTorch job includes the master node and Workers; the master node also consumes resources.
  • For a Ray job, calculate the resource requirements for the Head and each type of Worker separately. Aggregate and verify identical specifications; verify quotas separately for different specifications.
  • Different GPU models must be checked separately for model and capacity. The number of idle cards of one GPU model cannot offset the resource requirements of another model.

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Check Whether Resources Are Available

After completing the purchase, first verify that the order status is active in Orders, then return to Instance or the target resource pool to confirm that the quota has increased. Go to Resources > Instance, then select a region, cluster, and project group. The resource overview summarizes resources within the current scope, including: In the resource pool list, continue checking whether the target resource pool meets the task requirements. The list supports custom display columns. Commonly used columns include: If the utilization of a certain type of resource is high, or the target resource pool does not have sufficient available quota, subsequent task creation may be queued or submission may fail. If the resource pool is being updated, deleted, or is in a failed state, wait for the operation to complete or contact the resource administrator for confirmation before submitting the task.

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Request Resource Access Permissions and Quotas

If the target resource pool has not been authorized for the current account, or your remaining personal quota is insufficient, first apply for permission to use the resource pool or request additional quota. A resource request goes through two stages: approval and activation. After an administrator approves the request, the system must still apply the authorization and quota configuration. Only after the request status changes to Active can the newly granted permissions or quotas be used to create Develop environments, Training jobs, or Inference services.
  1. Go to Resources > Instance.
  2. Select the target region, cluster, and project group, then locate the target resource pool.
  3. Verify the resource pool’s instance specification, supported workload types, status, and personal quota.
  4. If Request Access is available, enter the required quota and purpose, then submit the request. If no request option is available, contact the resource pool administrator.
  5. View the approval and activation progress in the request records.
  6. After the status changes to Effective, refresh the resource pool page or the task creation form to confirm that your remaining personal quota has been updated.
Application status descriptions are as follows: Approval does not mean that resources are immediately available. After authorization and quota take effect, tasks must still wait for schedulable resources that meet the requirements. If a task remains queued for an extended period, see Troubleshoot insufficient resources or long task queue times.