pulumi-gcp-kotlin/com.pulumi.gcp.vertex.kotlin.outputs/AiEndpointDeployedModel

AiEndpointDeployedModel

data class AiEndpointDeployedModel(val automaticResources: List<AiEndpointDeployedModelAutomaticResource>? = null, val createTime: String? = null, val dedicatedResources: List<AiEndpointDeployedModelDedicatedResource>? = null, val displayName: String? = null, val enableAccessLogging: Boolean? = null, val enableContainerLogging: Boolean? = null, val id: String? = null, val model: String? = null, val modelVersionId: String? = null, val privateEndpoints: List<AiEndpointDeployedModelPrivateEndpoint>? = null, val serviceAccount: String? = null, val sharedResources: String? = null)

Constructors

fun AiEndpointDeployedModel(automaticResources: List<AiEndpointDeployedModelAutomaticResource>? = null, createTime: String? = null, dedicatedResources: List<AiEndpointDeployedModelDedicatedResource>? = null, displayName: String? = null, enableAccessLogging: Boolean? = null, enableContainerLogging: Boolean? = null, id: String? = null, model: String? = null, modelVersionId: String? = null, privateEndpoints: List<AiEndpointDeployedModelPrivateEndpoint>? = null, serviceAccount: String? = null, sharedResources: String? = null)

Types

Companion

object Companion

Properties

automaticResources

val automaticResources: List<AiEndpointDeployedModelAutomaticResource>? = null

(Output) A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. Structure is documented below.

createTime

val createTime: String? = null

(Output) Output only. Timestamp when the DeployedModel was created.

dedicatedResources

val dedicatedResources: List<AiEndpointDeployedModelDedicatedResource>? = null

(Output) A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration. Structure is documented below.

displayName

val displayName: String? = null

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

enableAccessLogging

val enableAccessLogging: Boolean? = null

(Output) These logs are like standard server access logs, containing information like timestamp and latency for each prediction request. Note that Stackdriver logs may incur a cost, especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option.

enableContainerLogging

val enableContainerLogging: Boolean? = null

(Output) If true, the container of the DeployedModel instances will send stderr and stdout streams to Stackdriver Logging. Only supported for custom-trained Models and AutoML Tabular Models.

val id: String? = null

(Output) The ID of the DeployedModel. If not provided upon deployment, Vertex AI will generate a value for this ID. This value should be 1-10 characters, and valid characters are /0-9/.

model

val model: String? = null

(Output) The name of the Model that this is the deployment of. Note that the Model may be in a different location than the DeployedModel's Endpoint.

modelVersionId

val modelVersionId: String? = null

(Output) Output only. The version ID of the model that is deployed.

privateEndpoints

val privateEndpoints: List<AiEndpointDeployedModelPrivateEndpoint>? = null

(Output) Output only. Provide paths for users to send predict/explain/health requests directly to the deployed model services running on Cloud via private services access. This field is populated if network is configured. Structure is documented below.

serviceAccount

val serviceAccount: String? = null

(Output) The service account that the DeployedModel's container runs as. Specify the email address of the service account. If this service account is not specified, the container runs as a service account that doesn't have access to the resource project. Users deploying the Model must have the iam.serviceAccounts.actAs permission on this service account.

sharedResources

val sharedResources: String? = null

(Output) The resource name of the shared DeploymentResourcePool to deploy on. Format: projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}