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A CES instance is a computing resource in the GPU Cloud that you can log in to and use directly. Like a server, you can prepare the runtime environment, access data, and run training or inference tasks on an instance. Depending on the task status, you can start, stop, restart, renew, or delete the instance. If your tasks require direct control of the OS environment, temporary debugging, running standalone tasks, or managing a small number of fixed resources, prioritize CES instances. If you need to run containerized workloads over the long term, centrally schedule multiple nodes, or manage applications using Kubernetes-native capabilities, CKS clusters are recommended.

Select Instance Type

CES instances are classified as GPU Instances and CPU Instances. Before creating one, select an instance type based on whether the task requires GPU acceleration. GPU Instances are suitable for tasks that require direct access to GPU resources. CPU Instances are suitable for tasks that do not rely on GPU acceleration. If a CPU task has requirements for resource scale, hardware isolation, or RDMA networking, you can select a Bare Metal Instance when creating it.

What You Need to Decide Before Creating

Before creating an instance, we recommend confirming the following items to avoid rework caused by mismatched specifications, Logon Credential, or data access methods after creation. When creating instances in batches, if you need to distinguish the node order by HostName, you can select Custom HostName and enable HostName with a custom sequence as needed, making it easier for multi-node tasks to identify node roles and for subsequent operations and maintenance.

How to Use It After Creation

After the instance is created and ready, it is typically used as follows:
  1. Connect to the instance using the Logon Credential selected when creating the instance.
  2. Prepare the runtime environment, for example, by installing dependencies, configuring frameworks, or pulling images.
  3. Prepare the data required for the task. Select an appropriate storage location and complete the necessary preparations based on whether the data needs to be shared between instances, transferred to or from the local environment, or retained long term.
  4. Run common compute tasks such as training, inference, or data processing.
  5. Use Monitor to view resource utilization, use Logs to view task output and troubleshoot errors, and use Alerts to receive timely notifications of resource or task exceptions.
  6. After the task is complete, Stop, Renew, or Delete the instance depending on whether the resource is still needed.

Common Management Tasks

After an instance is created, go to the Instance page and manage it under the GPU Instance or CPU Instance tab. The available actions may vary depending on the status and billing method.

Security and Data Risks

  • Key pairs and account passwords are both login credentials. Keep them secure, and do not include them in public repositories, images, script templates, or logs.
  • Data stored locally on an instance or on system disks or data disks may be unrecoverable after deletion, reinstallation, or unexpected operations. Save important data to persistent storage.
  • Delete, Stop, restart, reinstallation, and batch operations may interrupt tasks. Before proceeding, confirm the task status and scope of impact.
  • To reduce the risk of accidental deletion, you can enable deletion protection for important instances.