google-native.aiplatform/v1beta1.getPersistentResource

func LookupPersistentResource(ctx *Context, args *LookupPersistentResourceArgs, opts ...InvokeOption) (*LookupPersistentResourceResult, error)
func LookupPersistentResourceOutput(ctx *Context, args *LookupPersistentResourceOutputArgs, opts ...InvokeOption) LookupPersistentResourceResultOutput

> Note: This function is named LookupPersistentResource in the Go SDK.

Location string

PersistentResourceId string

Project string

Location string

PersistentResourceId string

Project string

location String

persistentResourceId String

project String

location string

persistentResourceId string

project string

location str

persistent_resource_id str

project str

location String

persistentResourceId String

project String

CreateTime string

Time when the PersistentResource was created.

DisplayName string

Optional. The display name of the PersistentResource. The name can be up to 128 characters long and can consist of any UTF-8 characters.

EncryptionSpec Pulumi.GoogleNative.Aiplatform.V1Beta1.Outputs.GoogleCloudAiplatformV1beta1EncryptionSpecResponse

Optional. Customer-managed encryption key spec for a PersistentResource. If set, this PersistentResource and all sub-resources of this PersistentResource will be secured by this key.

Error Pulumi.GoogleNative.Aiplatform.V1Beta1.Outputs.GoogleRpcStatusResponse

Only populated when persistent resource's state is STOPPING or ERROR.

Labels Dictionary<string, string>

Optional. The labels with user-defined metadata to organize PersistentResource. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

Name string

Immutable. Resource name of a PersistentResource.

Network string

Optional. The full name of the Compute Engine network to peered with Vertex AI to host the persistent resources. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the resources aren't peered with any network.

ReservedIpRanges List<string>

Optional. A list of names for the reserved IP ranges under the VPC network that can be used for this persistent resource. If set, we will deploy the persistent resource within the provided IP ranges. Otherwise, the persistent resource is deployed to any IP ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

ResourcePools List<Pulumi.GoogleNative.Aiplatform.V1Beta1.Outputs.GoogleCloudAiplatformV1beta1ResourcePoolResponse>

The spec of the pools of different resources.

ResourceRuntime Pulumi.GoogleNative.Aiplatform.V1Beta1.Outputs.GoogleCloudAiplatformV1beta1ResourceRuntimeResponse

Runtime information of the Persistent Resource.

ResourceRuntimeSpec Pulumi.GoogleNative.Aiplatform.V1Beta1.Outputs.GoogleCloudAiplatformV1beta1ResourceRuntimeSpecResponse

Optional. Persistent Resource runtime spec. For example, used for Ray cluster configuration.

StartTime string

Time when the PersistentResource for the first time entered the RUNNING state.

State string

The detailed state of a Study.

UpdateTime string

Time when the PersistentResource was most recently updated.

CreateTime string

Time when the PersistentResource was created.

DisplayName string

Optional. The display name of the PersistentResource. The name can be up to 128 characters long and can consist of any UTF-8 characters.

EncryptionSpec GoogleCloudAiplatformV1beta1EncryptionSpecResponse

Optional. Customer-managed encryption key spec for a PersistentResource. If set, this PersistentResource and all sub-resources of this PersistentResource will be secured by this key.

Error GoogleRpcStatusResponse

Only populated when persistent resource's state is STOPPING or ERROR.

Labels map[string]string

Optional. The labels with user-defined metadata to organize PersistentResource. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

Name string

Immutable. Resource name of a PersistentResource.

Network string

Optional. The full name of the Compute Engine network to peered with Vertex AI to host the persistent resources. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the resources aren't peered with any network.

ReservedIpRanges []string

Optional. A list of names for the reserved IP ranges under the VPC network that can be used for this persistent resource. If set, we will deploy the persistent resource within the provided IP ranges. Otherwise, the persistent resource is deployed to any IP ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

ResourcePools []GoogleCloudAiplatformV1beta1ResourcePoolResponse

The spec of the pools of different resources.

ResourceRuntime GoogleCloudAiplatformV1beta1ResourceRuntimeResponse

Runtime information of the Persistent Resource.

ResourceRuntimeSpec GoogleCloudAiplatformV1beta1ResourceRuntimeSpecResponse

Optional. Persistent Resource runtime spec. For example, used for Ray cluster configuration.

StartTime string

Time when the PersistentResource for the first time entered the RUNNING state.

State string

The detailed state of a Study.

UpdateTime string

Time when the PersistentResource was most recently updated.

createTime String

Time when the PersistentResource was created.

displayName String

Optional. The display name of the PersistentResource. The name can be up to 128 characters long and can consist of any UTF-8 characters.

encryptionSpec GoogleCloudAiplatformV1beta1EncryptionSpecResponse

Optional. Customer-managed encryption key spec for a PersistentResource. If set, this PersistentResource and all sub-resources of this PersistentResource will be secured by this key.

error GoogleRpcStatusResponse

Only populated when persistent resource's state is STOPPING or ERROR.

labels Map<String,String>

Optional. The labels with user-defined metadata to organize PersistentResource. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

name String

Immutable. Resource name of a PersistentResource.

network String

Optional. The full name of the Compute Engine network to peered with Vertex AI to host the persistent resources. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the resources aren't peered with any network.

reservedIpRanges List<String>

Optional. A list of names for the reserved IP ranges under the VPC network that can be used for this persistent resource. If set, we will deploy the persistent resource within the provided IP ranges. Otherwise, the persistent resource is deployed to any IP ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

resourcePools List<GoogleCloudAiplatformV1beta1ResourcePoolResponse>

The spec of the pools of different resources.

resourceRuntime GoogleCloudAiplatformV1beta1ResourceRuntimeResponse

Runtime information of the Persistent Resource.

resourceRuntimeSpec GoogleCloudAiplatformV1beta1ResourceRuntimeSpecResponse

Optional. Persistent Resource runtime spec. For example, used for Ray cluster configuration.

startTime String

Time when the PersistentResource for the first time entered the RUNNING state.

state String

The detailed state of a Study.

updateTime String

Time when the PersistentResource was most recently updated.

createTime string

Time when the PersistentResource was created.

displayName string

Optional. The display name of the PersistentResource. The name can be up to 128 characters long and can consist of any UTF-8 characters.

encryptionSpec GoogleCloudAiplatformV1beta1EncryptionSpecResponse

Optional. Customer-managed encryption key spec for a PersistentResource. If set, this PersistentResource and all sub-resources of this PersistentResource will be secured by this key.

error GoogleRpcStatusResponse

Only populated when persistent resource's state is STOPPING or ERROR.

labels {[key: string]: string}

Optional. The labels with user-defined metadata to organize PersistentResource. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

name string

Immutable. Resource name of a PersistentResource.

network string

Optional. The full name of the Compute Engine network to peered with Vertex AI to host the persistent resources. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the resources aren't peered with any network.

reservedIpRanges string[]

Optional. A list of names for the reserved IP ranges under the VPC network that can be used for this persistent resource. If set, we will deploy the persistent resource within the provided IP ranges. Otherwise, the persistent resource is deployed to any IP ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

resourcePools GoogleCloudAiplatformV1beta1ResourcePoolResponse[]

The spec of the pools of different resources.

resourceRuntime GoogleCloudAiplatformV1beta1ResourceRuntimeResponse

Runtime information of the Persistent Resource.

resourceRuntimeSpec GoogleCloudAiplatformV1beta1ResourceRuntimeSpecResponse

Optional. Persistent Resource runtime spec. For example, used for Ray cluster configuration.

startTime string

Time when the PersistentResource for the first time entered the RUNNING state.

state string

The detailed state of a Study.

updateTime string

Time when the PersistentResource was most recently updated.

create_time str

Time when the PersistentResource was created.

display_name str

Optional. The display name of the PersistentResource. The name can be up to 128 characters long and can consist of any UTF-8 characters.

encryption_spec GoogleCloudAiplatformV1beta1EncryptionSpecResponse

Optional. Customer-managed encryption key spec for a PersistentResource. If set, this PersistentResource and all sub-resources of this PersistentResource will be secured by this key.

error GoogleRpcStatusResponse

Only populated when persistent resource's state is STOPPING or ERROR.

labels Mapping[str, str]

Optional. The labels with user-defined metadata to organize PersistentResource. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

name str

Immutable. Resource name of a PersistentResource.

network str

Optional. The full name of the Compute Engine network to peered with Vertex AI to host the persistent resources. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the resources aren't peered with any network.

reserved_ip_ranges Sequence[str]

Optional. A list of names for the reserved IP ranges under the VPC network that can be used for this persistent resource. If set, we will deploy the persistent resource within the provided IP ranges. Otherwise, the persistent resource is deployed to any IP ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

resource_pools Sequence[GoogleCloudAiplatformV1beta1ResourcePoolResponse]

The spec of the pools of different resources.

resource_runtime GoogleCloudAiplatformV1beta1ResourceRuntimeResponse

Runtime information of the Persistent Resource.

resource_runtime_spec GoogleCloudAiplatformV1beta1ResourceRuntimeSpecResponse

Optional. Persistent Resource runtime spec. For example, used for Ray cluster configuration.

start_time str

Time when the PersistentResource for the first time entered the RUNNING state.

state str

The detailed state of a Study.

update_time str

Time when the PersistentResource was most recently updated.

createTime String

Time when the PersistentResource was created.

displayName String

Optional. The display name of the PersistentResource. The name can be up to 128 characters long and can consist of any UTF-8 characters.

encryptionSpec Property Map

Optional. Customer-managed encryption key spec for a PersistentResource. If set, this PersistentResource and all sub-resources of this PersistentResource will be secured by this key.

error Property Map

Only populated when persistent resource's state is STOPPING or ERROR.

labels Map<String>

Optional. The labels with user-defined metadata to organize PersistentResource. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

name String

Immutable. Resource name of a PersistentResource.

network String

Optional. The full name of the Compute Engine network to peered with Vertex AI to host the persistent resources. For example, projects/12345/global/networks/myVPC. Format is of the form projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is a network name. To specify this field, you must have already configured VPC Network Peering for Vertex AI. If this field is left unspecified, the resources aren't peered with any network.

reservedIpRanges List<String>

Optional. A list of names for the reserved IP ranges under the VPC network that can be used for this persistent resource. If set, we will deploy the persistent resource within the provided IP ranges. Otherwise, the persistent resource is deployed to any IP ranges under the provided VPC network. Example: ['vertex-ai-ip-range'].

resourcePools List<Property Map>

The spec of the pools of different resources.

resourceRuntime Property Map

Runtime information of the Persistent Resource.

resourceRuntimeSpec Property Map

Optional. Persistent Resource runtime spec. For example, used for Ray cluster configuration.

startTime String

Time when the PersistentResource for the first time entered the RUNNING state.

state String

The detailed state of a Study.

updateTime String

Time when the PersistentResource was most recently updated.

BootDiskSizeGb int

Size in GB of the boot disk (default is 100GB).

BootDiskType string

Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

BootDiskSizeGb int

Size in GB of the boot disk (default is 100GB).

BootDiskType string

Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

bootDiskSizeGb Integer

Size in GB of the boot disk (default is 100GB).

bootDiskType String

Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

bootDiskSizeGb number

Size in GB of the boot disk (default is 100GB).

bootDiskType string

Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

boot_disk_size_gb int

Size in GB of the boot disk (default is 100GB).

boot_disk_type str

Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

bootDiskSizeGb Number

Size in GB of the boot disk (default is 100GB).

bootDiskType String

Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

KmsKeyName string

The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

KmsKeyName string

The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

kmsKeyName String

The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

kmsKeyName string

The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

kms_key_name str

The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

kmsKeyName String

The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

AcceleratorCount int

The number of accelerators to attach to the machine.

AcceleratorType string

Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.

MachineType string

Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.

TpuTopology string

Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").

AcceleratorCount int

The number of accelerators to attach to the machine.

AcceleratorType string

Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.

MachineType string

Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.

TpuTopology string

Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").

acceleratorCount Integer

The number of accelerators to attach to the machine.

acceleratorType String

Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.

machineType String

Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.

tpuTopology String

Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").

acceleratorCount number

The number of accelerators to attach to the machine.

acceleratorType string

Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.

machineType string

Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.

tpuTopology string

Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").

accelerator_count int

The number of accelerators to attach to the machine.

accelerator_type str

Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.

machine_type str

Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.

tpu_topology str

Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").

acceleratorCount Number

The number of accelerators to attach to the machine.

acceleratorType String

Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count.

machineType String

Immutable. The type of the machine. See the list of machine types supported for prediction See the list of machine types supported for custom training. For DeployedModel this field is optional, and the default value is n1-standard-2. For BatchPredictionJob or as part of WorkerPoolSpec this field is required.

tpuTopology String

Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1").

HeadNodeResourcePoolId string

Optional. This will be used to indicate which resource pool will serve as the Ray head node(the first node within that pool). Will use the machine from the first workerpool as the head node by default if this field isn't set.

ImageUri string

Optional. Default image for user to choose a preferred ML framework (for example, TensorFlow or Pytorch) by choosing from Vertex prebuilt images. Either this or the resource_pool_images is required. Use this field if you need all the resource pools to have the same Ray image. Otherwise, use the {@code resource_pool_images} field.

ResourcePoolImages Dictionary<string, string>

Optional. Required if image_uri isn't set. A map of resource_pool_id to prebuild Ray image if user need to use different images for different head/worker pools. This map needs to cover all the resource pool ids. Example: { "ray_head_node_pool": "head image" "ray_worker_node_pool1": "worker image" "ray_worker_node_pool2": "another worker image" }

HeadNodeResourcePoolId string

Optional. This will be used to indicate which resource pool will serve as the Ray head node(the first node within that pool). Will use the machine from the first workerpool as the head node by default if this field isn't set.

ImageUri string

Optional. Default image for user to choose a preferred ML framework (for example, TensorFlow or Pytorch) by choosing from Vertex prebuilt images. Either this or the resource_pool_images is required. Use this field if you need all the resource pools to have the same Ray image. Otherwise, use the {@code resource_pool_images} field.

ResourcePoolImages map[string]string

Optional. Required if image_uri isn't set. A map of resource_pool_id to prebuild Ray image if user need to use different images for different head/worker pools. This map needs to cover all the resource pool ids. Example: { "ray_head_node_pool": "head image" "ray_worker_node_pool1": "worker image" "ray_worker_node_pool2": "another worker image" }

headNodeResourcePoolId String

Optional. This will be used to indicate which resource pool will serve as the Ray head node(the first node within that pool). Will use the machine from the first workerpool as the head node by default if this field isn't set.

imageUri String

Optional. Default image for user to choose a preferred ML framework (for example, TensorFlow or Pytorch) by choosing from Vertex prebuilt images. Either this or the resource_pool_images is required. Use this field if you need all the resource pools to have the same Ray image. Otherwise, use the {@code resource_pool_images} field.

resourcePoolImages Map<String,String>

Optional. Required if image_uri isn't set. A map of resource_pool_id to prebuild Ray image if user need to use different images for different head/worker pools. This map needs to cover all the resource pool ids. Example: { "ray_head_node_pool": "head image" "ray_worker_node_pool1": "worker image" "ray_worker_node_pool2": "another worker image" }

headNodeResourcePoolId string

Optional. This will be used to indicate which resource pool will serve as the Ray head node(the first node within that pool). Will use the machine from the first workerpool as the head node by default if this field isn't set.

imageUri string

Optional. Default image for user to choose a preferred ML framework (for example, TensorFlow or Pytorch) by choosing from Vertex prebuilt images. Either this or the resource_pool_images is required. Use this field if you need all the resource pools to have the same Ray image. Otherwise, use the {@code resource_pool_images} field.

resourcePoolImages {[key: string]: string}

Optional. Required if image_uri isn't set. A map of resource_pool_id to prebuild Ray image if user need to use different images for different head/worker pools. This map needs to cover all the resource pool ids. Example: { "ray_head_node_pool": "head image" "ray_worker_node_pool1": "worker image" "ray_worker_node_pool2": "another worker image" }

head_node_resource_pool_id str

Optional. This will be used to indicate which resource pool will serve as the Ray head node(the first node within that pool). Will use the machine from the first workerpool as the head node by default if this field isn't set.

image_uri str

Optional. Default image for user to choose a preferred ML framework (for example, TensorFlow or Pytorch) by choosing from Vertex prebuilt images. Either this or the resource_pool_images is required. Use this field if you need all the resource pools to have the same Ray image. Otherwise, use the {@code resource_pool_images} field.

resource_pool_images Mapping[str, str]

Optional. Required if image_uri isn't set. A map of resource_pool_id to prebuild Ray image if user need to use different images for different head/worker pools. This map needs to cover all the resource pool ids. Example: { "ray_head_node_pool": "head image" "ray_worker_node_pool1": "worker image" "ray_worker_node_pool2": "another worker image" }

headNodeResourcePoolId String

Optional. This will be used to indicate which resource pool will serve as the Ray head node(the first node within that pool). Will use the machine from the first workerpool as the head node by default if this field isn't set.

imageUri String

Optional. Default image for user to choose a preferred ML framework (for example, TensorFlow or Pytorch) by choosing from Vertex prebuilt images. Either this or the resource_pool_images is required. Use this field if you need all the resource pools to have the same Ray image. Otherwise, use the {@code resource_pool_images} field.

resourcePoolImages Map<String>

Optional. Required if image_uri isn't set. A map of resource_pool_id to prebuild Ray image if user need to use different images for different head/worker pools. This map needs to cover all the resource pool ids. Example: { "ray_head_node_pool": "head image" "ray_worker_node_pool1": "worker image" "ray_worker_node_pool2": "another worker image" }

MaxReplicaCount string

Optional. max replicas in the node pool, must be ≥ replica_count and > min_replica_count or will throw error

MinReplicaCount string

Optional. min replicas in the node pool, must be ≤ replica_count and < max_replica_count or will throw error

MaxReplicaCount string

Optional. max replicas in the node pool, must be ≥ replica_count and > min_replica_count or will throw error

MinReplicaCount string

Optional. min replicas in the node pool, must be ≤ replica_count and < max_replica_count or will throw error

maxReplicaCount String

Optional. max replicas in the node pool, must be ≥ replica_count and > min_replica_count or will throw error

minReplicaCount String

Optional. min replicas in the node pool, must be ≤ replica_count and < max_replica_count or will throw error

maxReplicaCount string

Optional. max replicas in the node pool, must be ≥ replica_count and > min_replica_count or will throw error

minReplicaCount string

Optional. min replicas in the node pool, must be ≤ replica_count and < max_replica_count or will throw error

max_replica_count str

Optional. max replicas in the node pool, must be ≥ replica_count and > min_replica_count or will throw error

min_replica_count str

Optional. min replicas in the node pool, must be ≤ replica_count and < max_replica_count or will throw error

maxReplicaCount String

Optional. max replicas in the node pool, must be ≥ replica_count and > min_replica_count or will throw error

minReplicaCount String

Optional. min replicas in the node pool, must be ≤ replica_count and < max_replica_count or will throw error

AutoscalingSpec Pulumi.GoogleNative.Aiplatform.V1Beta1.Inputs.GoogleCloudAiplatformV1beta1ResourcePoolAutoscalingSpecResponse

Optional. Optional spec to configure GKE autoscaling

DiskSpec Pulumi.GoogleNative.Aiplatform.V1Beta1.Inputs.GoogleCloudAiplatformV1beta1DiskSpecResponse

Optional. Disk spec for the machine in this node pool.

MachineSpec Pulumi.GoogleNative.Aiplatform.V1Beta1.Inputs.GoogleCloudAiplatformV1beta1MachineSpecResponse

Immutable. The specification of a single machine.

ReplicaCount string

Optional. The total number of machines to use for this resource pool.

UsedReplicaCount string

The number of machines currently in use by training jobs for this resource pool. Will replace idle_replica_count.

AutoscalingSpec GoogleCloudAiplatformV1beta1ResourcePoolAutoscalingSpecResponse

Optional. Optional spec to configure GKE autoscaling

DiskSpec GoogleCloudAiplatformV1beta1DiskSpecResponse

Optional. Disk spec for the machine in this node pool.

MachineSpec GoogleCloudAiplatformV1beta1MachineSpecResponse

Immutable. The specification of a single machine.

ReplicaCount string

Optional. The total number of machines to use for this resource pool.

UsedReplicaCount string

The number of machines currently in use by training jobs for this resource pool. Will replace idle_replica_count.

autoscalingSpec GoogleCloudAiplatformV1beta1ResourcePoolAutoscalingSpecResponse

Optional. Optional spec to configure GKE autoscaling

diskSpec GoogleCloudAiplatformV1beta1DiskSpecResponse

Optional. Disk spec for the machine in this node pool.

machineSpec GoogleCloudAiplatformV1beta1MachineSpecResponse

Immutable. The specification of a single machine.

replicaCount String

Optional. The total number of machines to use for this resource pool.

usedReplicaCount String

The number of machines currently in use by training jobs for this resource pool. Will replace idle_replica_count.

autoscalingSpec GoogleCloudAiplatformV1beta1ResourcePoolAutoscalingSpecResponse

Optional. Optional spec to configure GKE autoscaling

diskSpec GoogleCloudAiplatformV1beta1DiskSpecResponse

Optional. Disk spec for the machine in this node pool.

machineSpec GoogleCloudAiplatformV1beta1MachineSpecResponse

Immutable. The specification of a single machine.

replicaCount string

Optional. The total number of machines to use for this resource pool.

usedReplicaCount string

The number of machines currently in use by training jobs for this resource pool. Will replace idle_replica_count.

autoscaling_spec GoogleCloudAiplatformV1beta1ResourcePoolAutoscalingSpecResponse

Optional. Optional spec to configure GKE autoscaling

disk_spec GoogleCloudAiplatformV1beta1DiskSpecResponse

Optional. Disk spec for the machine in this node pool.

machine_spec GoogleCloudAiplatformV1beta1MachineSpecResponse

Immutable. The specification of a single machine.

replica_count str

Optional. The total number of machines to use for this resource pool.

used_replica_count str

The number of machines currently in use by training jobs for this resource pool. Will replace idle_replica_count.

autoscalingSpec Property Map

Optional. Optional spec to configure GKE autoscaling

diskSpec Property Map

Optional. Disk spec for the machine in this node pool.

machineSpec Property Map

Immutable. The specification of a single machine.

replicaCount String

Optional. The total number of machines to use for this resource pool.

usedReplicaCount String

The number of machines currently in use by training jobs for this resource pool. Will replace idle_replica_count.

AccessUris Dictionary<string, string>

URIs for user to connect to the Cluster. Example: { "RAY_HEAD_NODE_INTERNAL_IP": "head-node-IP:10001" "RAY_DASHBOARD_URI": "ray-dashboard-address:8888" }

NotebookRuntimeTemplate string

The resource name of NotebookRuntimeTemplate for the RoV Persistent Cluster The NotebokRuntimeTemplate is created in the same VPC (if set), and with the same Ray and Python version as the Persistent Cluster. Example: "projects/1000/locations/us-central1/notebookRuntimeTemplates/abc123"

AccessUris map[string]string

URIs for user to connect to the Cluster. Example: { "RAY_HEAD_NODE_INTERNAL_IP": "head-node-IP:10001" "RAY_DASHBOARD_URI": "ray-dashboard-address:8888" }

NotebookRuntimeTemplate string

The resource name of NotebookRuntimeTemplate for the RoV Persistent Cluster The NotebokRuntimeTemplate is created in the same VPC (if set), and with the same Ray and Python version as the Persistent Cluster. Example: "projects/1000/locations/us-central1/notebookRuntimeTemplates/abc123"

accessUris Map<String,String>

URIs for user to connect to the Cluster. Example: { "RAY_HEAD_NODE_INTERNAL_IP": "head-node-IP:10001" "RAY_DASHBOARD_URI": "ray-dashboard-address:8888" }

notebookRuntimeTemplate String

The resource name of NotebookRuntimeTemplate for the RoV Persistent Cluster The NotebokRuntimeTemplate is created in the same VPC (if set), and with the same Ray and Python version as the Persistent Cluster. Example: "projects/1000/locations/us-central1/notebookRuntimeTemplates/abc123"

accessUris {[key: string]: string}

URIs for user to connect to the Cluster. Example: { "RAY_HEAD_NODE_INTERNAL_IP": "head-node-IP:10001" "RAY_DASHBOARD_URI": "ray-dashboard-address:8888" }

notebookRuntimeTemplate string

The resource name of NotebookRuntimeTemplate for the RoV Persistent Cluster The NotebokRuntimeTemplate is created in the same VPC (if set), and with the same Ray and Python version as the Persistent Cluster. Example: "projects/1000/locations/us-central1/notebookRuntimeTemplates/abc123"

access_uris Mapping[str, str]

URIs for user to connect to the Cluster. Example: { "RAY_HEAD_NODE_INTERNAL_IP": "head-node-IP:10001" "RAY_DASHBOARD_URI": "ray-dashboard-address:8888" }

notebook_runtime_template str

The resource name of NotebookRuntimeTemplate for the RoV Persistent Cluster The NotebokRuntimeTemplate is created in the same VPC (if set), and with the same Ray and Python version as the Persistent Cluster. Example: "projects/1000/locations/us-central1/notebookRuntimeTemplates/abc123"

accessUris Map<String>

URIs for user to connect to the Cluster. Example: { "RAY_HEAD_NODE_INTERNAL_IP": "head-node-IP:10001" "RAY_DASHBOARD_URI": "ray-dashboard-address:8888" }

notebookRuntimeTemplate String

The resource name of NotebookRuntimeTemplate for the RoV Persistent Cluster The NotebokRuntimeTemplate is created in the same VPC (if set), and with the same Ray and Python version as the Persistent Cluster. Example: "projects/1000/locations/us-central1/notebookRuntimeTemplates/abc123"

RaySpec Pulumi.GoogleNative.Aiplatform.V1Beta1.Inputs.GoogleCloudAiplatformV1beta1RaySpecResponse

Optional. Ray cluster configuration. Required when creating a dedicated RayCluster on the PersistentResource.

ServiceAccountSpec Pulumi.GoogleNative.Aiplatform.V1Beta1.Inputs.GoogleCloudAiplatformV1beta1ServiceAccountSpecResponse

Optional. Configure the use of workload identity on the PersistentResource

RaySpec GoogleCloudAiplatformV1beta1RaySpecResponse

Optional. Ray cluster configuration. Required when creating a dedicated RayCluster on the PersistentResource.

ServiceAccountSpec GoogleCloudAiplatformV1beta1ServiceAccountSpecResponse

Optional. Configure the use of workload identity on the PersistentResource

raySpec GoogleCloudAiplatformV1beta1RaySpecResponse

Optional. Ray cluster configuration. Required when creating a dedicated RayCluster on the PersistentResource.

serviceAccountSpec GoogleCloudAiplatformV1beta1ServiceAccountSpecResponse

Optional. Configure the use of workload identity on the PersistentResource

raySpec GoogleCloudAiplatformV1beta1RaySpecResponse

Optional. Ray cluster configuration. Required when creating a dedicated RayCluster on the PersistentResource.

serviceAccountSpec GoogleCloudAiplatformV1beta1ServiceAccountSpecResponse

Optional. Configure the use of workload identity on the PersistentResource

ray_spec GoogleCloudAiplatformV1beta1RaySpecResponse

Optional. Ray cluster configuration. Required when creating a dedicated RayCluster on the PersistentResource.

service_account_spec GoogleCloudAiplatformV1beta1ServiceAccountSpecResponse

Optional. Configure the use of workload identity on the PersistentResource

raySpec Property Map

Optional. Ray cluster configuration. Required when creating a dedicated RayCluster on the PersistentResource.

serviceAccountSpec Property Map

Optional. Configure the use of workload identity on the PersistentResource

EnableCustomServiceAccount bool

If true, custom user-managed service account is enforced to run any workloads (for example, Vertex Jobs) on the resource. Otherwise, uses the Vertex AI Custom Code Service Agent.

ServiceAccount string

Optional. Default service account that this PersistentResource's workloads run as. The workloads include: * Any runtime specified via ResourceRuntimeSpec on creation time, for example, Ray. * Jobs submitted to PersistentResource, if no other service account specified in the job specs. Only works when custom service account is enabled and users have the iam.serviceAccounts.actAs permission on this service account. Required if any containers are specified in ResourceRuntimeSpec.

EnableCustomServiceAccount bool

If true, custom user-managed service account is enforced to run any workloads (for example, Vertex Jobs) on the resource. Otherwise, uses the Vertex AI Custom Code Service Agent.

ServiceAccount string

Optional. Default service account that this PersistentResource's workloads run as. The workloads include: * Any runtime specified via ResourceRuntimeSpec on creation time, for example, Ray. * Jobs submitted to PersistentResource, if no other service account specified in the job specs. Only works when custom service account is enabled and users have the iam.serviceAccounts.actAs permission on this service account. Required if any containers are specified in ResourceRuntimeSpec.

enableCustomServiceAccount Boolean

If true, custom user-managed service account is enforced to run any workloads (for example, Vertex Jobs) on the resource. Otherwise, uses the Vertex AI Custom Code Service Agent.

serviceAccount String

Optional. Default service account that this PersistentResource's workloads run as. The workloads include: * Any runtime specified via ResourceRuntimeSpec on creation time, for example, Ray. * Jobs submitted to PersistentResource, if no other service account specified in the job specs. Only works when custom service account is enabled and users have the iam.serviceAccounts.actAs permission on this service account. Required if any containers are specified in ResourceRuntimeSpec.

enableCustomServiceAccount boolean

If true, custom user-managed service account is enforced to run any workloads (for example, Vertex Jobs) on the resource. Otherwise, uses the Vertex AI Custom Code Service Agent.

serviceAccount string

Optional. Default service account that this PersistentResource's workloads run as. The workloads include: * Any runtime specified via ResourceRuntimeSpec on creation time, for example, Ray. * Jobs submitted to PersistentResource, if no other service account specified in the job specs. Only works when custom service account is enabled and users have the iam.serviceAccounts.actAs permission on this service account. Required if any containers are specified in ResourceRuntimeSpec.

enable_custom_service_account bool

If true, custom user-managed service account is enforced to run any workloads (for example, Vertex Jobs) on the resource. Otherwise, uses the Vertex AI Custom Code Service Agent.

service_account str

Optional. Default service account that this PersistentResource's workloads run as. The workloads include: * Any runtime specified via ResourceRuntimeSpec on creation time, for example, Ray. * Jobs submitted to PersistentResource, if no other service account specified in the job specs. Only works when custom service account is enabled and users have the iam.serviceAccounts.actAs permission on this service account. Required if any containers are specified in ResourceRuntimeSpec.

enableCustomServiceAccount Boolean

If true, custom user-managed service account is enforced to run any workloads (for example, Vertex Jobs) on the resource. Otherwise, uses the Vertex AI Custom Code Service Agent.

serviceAccount String

Optional. Default service account that this PersistentResource's workloads run as. The workloads include: * Any runtime specified via ResourceRuntimeSpec on creation time, for example, Ray. * Jobs submitted to PersistentResource, if no other service account specified in the job specs. Only works when custom service account is enabled and users have the iam.serviceAccounts.actAs permission on this service account. Required if any containers are specified in ResourceRuntimeSpec.

Code int

The status code, which should be an enum value of google.rpc.Code.

Details List<ImmutableDictionary<string, string>>

A list of messages that carry the error details. There is a common set of message types for APIs to use.

Message string

A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.

Code int

The status code, which should be an enum value of google.rpc.Code.

Details []map[string]string

A list of messages that carry the error details. There is a common set of message types for APIs to use.

Message string

A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.

code Integer

The status code, which should be an enum value of google.rpc.Code.

details List<Map<String,String>>

A list of messages that carry the error details. There is a common set of message types for APIs to use.

message String

A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.

code number

The status code, which should be an enum value of google.rpc.Code.

details {[key: string]: string}[]

A list of messages that carry the error details. There is a common set of message types for APIs to use.

message string

A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.

code int

The status code, which should be an enum value of google.rpc.Code.

details Sequence[Mapping[str, str]]

A list of messages that carry the error details. There is a common set of message types for APIs to use.

message str

A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.

code Number

The status code, which should be an enum value of google.rpc.Code.

details List<Map<String>>

A list of messages that carry the error details. There is a common set of message types for APIs to use.

message String

A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.