gcloud-help/gcloud/ai/persistent-resources/create

NAME
    gcloud ai persistent-resources create - create a new persistent resource

SYNOPSIS
    gcloud ai persistent-resources create
        --persistent-resource-id=PERSISTENT_RESOURCE_ID
        (--config=CONFIG --resource-pool-spec=[RESOURCE_POOL_SPEC,...])
        [--display-name=DISPLAY_NAME] [--enable-custom-service-account]
        [--labels=[KEY=VALUE,...]] [--network=NETWORK] [--region=REGION]
        [--kms-key=KMS_KEY : --kms-keyring=KMS_KEYRING
          --kms-location=KMS_LOCATION --kms-project=KMS_PROJECT]
        [GCLOUD_WIDE_FLAG ...]

DESCRIPTION
    This command will create a persistent resource on the users project to use
    with Vertex AI custom training jobs. Persistent resources remain active
    until they are deleted by the user.

EXAMPLES
    To create a PersistentResource under project example in region us-central1,
    run:

        $ gcloud ai persistent-resources create --region=us-central1 \
            --project=example \
            --resource-pool-spec=replica-count=1,\
        machine-type='n1-standard-4' --display-name=example-resource

REQUIRED FLAGS
     --persistent-resource-id=PERSISTENT_RESOURCE_ID
        User-specified ID of the Persistent Resource.

     resource pool specification.

     At least one of these must be specified:

       --config=CONFIG
          Path to the Persistent Resource configuration file. This file should
          be a YAML document containing a list of ResourcePool If an option is
          specified both in the configuration file **and** via command-line
          arguments, the command-line arguments override the configuration
          file. Note that keys with underscore are invalid.

          Example(YAML):

              resourcePoolSpecs:
                machineSpec:
                  machineType: n1-standard-4
                replicaCount: 1

       --resource-pool-spec=[RESOURCE_POOL_SPEC,...]
          Defines a resource pool to be created in the Persistent Resource. You
          can include multiple resource pool specs in order to create a
          Persistent Resource with multiple resource pools.

          The spec can contain the following fields:

           machine-type
              (Required): The type of the machine. see
              https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types
              for supported types. This field corresponds to the
              machineSpec.machineType field in ResourcePool API message.
           replica-count
              (Required if autoscaling not enabled) The number of replicas to
              use when creating this resource pool. This field corresponds to
              the replicaCount field in 'ResourcePool' API message.
           min-replica-count
              (Optional) The minimum number of replicas that autoscaling will
              down-size to for this resource pool. Both min-replica-count and
              max-replica-count are required to enable autoscaling on this
              resource pool. The value for this parameter must be at least 1.
           max-replica-count
              (Optional) The maximum number of replicas that autoscaling will
              create for this resource pool. Both min-replica-count and
              max-replica-count are required to enable autoscaling on this
              resource pool. The maximum value for this parameter is 1000.
           accelerator-type
              (Optional) The type of GPU to attach to the machines. see
              https://cloud.google.com/vertex-ai/docs/training/configure-compute#specifying_gpus
              for more requirements. This field corresponds to the
              machineSpec.acceleratorType field in ResourcePool API message.
           accelerator-count
              (Required with accelerator-type) The number of GPUs for each VM
              in the resource pool to use. The default the value if 1. This
              field corresponds to the machineSpec.acceleratorCount field in
              ResourcePool API message.
           disk-type
              (Optional) The type of disk to use for each machine's boot disk
              in the resource pool. The default is pd-standard. This field
              corresponds to the diskSpec.bootDiskType field in ResourcePool
              API message.
           disk-size
              (Optional) The disk size in Gb for each machine's boot disk in
              the resource pool. The default is 100. This field corresponds to
              the diskSpec.bootDiskSizeGb field in ResourcePool API message.

          Example: --worker-pool-spec=replica-count=1,machine-type=n1-highmem-2

OPTIONAL FLAGS
     --display-name=DISPLAY_NAME
        Display name of the Persistent Resource.

     --enable-custom-service-account
        Whether or not to use a custom user-managed service account with this
        Persistent Resource.

     --labels=[KEY=VALUE,...]
        List of label KEY=VALUE pairs to add.

        Keys must start with a lowercase character and contain only hyphens
        (-), underscores (_), lowercase characters, and numbers. Values must
        contain only hyphens (-), underscores (_), lowercase characters, and
        numbers.

     --network=NETWORK
        Full name of the Google Compute Engine network to which the Job is
        peered with. Private services access must already have been configured.
        If unspecified, the Job is not peered with any network.

     Region resource - Cloud region to create a Persistent Resource. This
     represents a Cloud resource. (NOTE) Some attributes are not given
     arguments in this group but can be set in other ways.

     To set the project attribute:
      ◆ provide the argument --region on the command line with a fully
        specified name;
      ◆ set the property ai/region with a fully specified name;
      ◆ choose one from the prompted list of available regions with a fully
        specified name;
      ◆ provide the argument --project on the command line;
      ◆ set the property core/project.

       --region=REGION
          ID of the region or fully qualified identifier for the region.

          To set the region attribute:
          ▸ provide the argument --region on the command line;
          ▸ set the property ai/region;
          ▸ choose one from the prompted list of available regions.

     Key resource - The Cloud KMS (Key Management Service) cryptokey that will
     be used to protect the persistent resource. The 'Vertex AI Service Agent'
     service account must hold permission 'Cloud KMS CryptoKey
     Encrypter/Decrypter'. The arguments in this group can be used to specify
     the attributes of this resource.

       --kms-key=KMS_KEY
          ID of the key or fully qualified identifier for the key.

          To set the kms-key attribute:
          ▸ provide the argument --kms-key on the command line.

          This flag argument must be specified if any of the other arguments in
          this group are specified.

       --kms-keyring=KMS_KEYRING
          The KMS keyring of the key.

          To set the kms-keyring attribute:
          ▸ provide the argument --kms-key on the command line with a fully
            specified name;
          ▸ provide the argument --kms-keyring on the command line.

       --kms-location=KMS_LOCATION
          The Google Cloud location for the key.

          To set the kms-location attribute:
          ▸ provide the argument --kms-key on the command line with a fully
            specified name;
          ▸ provide the argument --kms-location on the command line.

       --kms-project=KMS_PROJECT
          The Google Cloud project for the key.

          To set the kms-project attribute:
          ▸ provide the argument --kms-key on the command line with a fully
            specified name;
          ▸ provide the argument --kms-project on the command line;
          ▸ set the property core/project.

GCLOUD WIDE FLAGS
    These flags are available to all commands: --access-token-file, --account,
    --billing-project, --configuration, --flags-file, --flatten, --format,
    --help, --impersonate-service-account, --log-http, --project, --quiet,
    --trace-token, --user-output-enabled, --verbosity.

    Run $ gcloud help for details.

NOTES
    These variants are also available:

        $ gcloud alpha ai persistent-resources create

        $ gcloud beta ai persistent-resources create