Vertex AI Endpoint

Vertex AI Endpoint in Google Cloud is a managed resource that provides a secure and scalable way to deploy and serve machine learning models. It allows you to host models trained in Vertex AI or imported from other frameworks, enabling real-time predictions through REST or gRPC APIs. Endpoints handle traffic management, versioning, and autoscaling, making it easier to integrate ML models into applications without managing infrastructure.

gcp.aiplatform_endpoint

Fields

TitleIDTypeData TypeDescription
_keycorestring
ancestorscorearray<string>
client_connection_configcorejsonConfigurations that are applied to the endpoint for online prediction.
create_timecoretimestampOutput only. Timestamp when this Endpoint was created.
datadog_display_namecorestring
dedicated_endpoint_dnscorestringOutput only. DNS of the dedicated endpoint. Will only be populated if dedicated_endpoint_enabled is true. Depending on the features enabled, uid might be a random number or a string. For example, if fast_tryout is enabled, uid will be fasttryout. Format: `https://{endpoint_id}.{region}-{uid}.prediction.vertexai.goog`.
dedicated_endpoint_enabledcoreboolIf true, the endpoint will be exposed through a dedicated DNS [Endpoint.dedicated_endpoint_dns]. Your request to the dedicated DNS will be isolated from other users' traffic and will have better performance and reliability. Note: Once you enabled dedicated endpoint, you won't be able to send request to the shared DNS {region}-aiplatform.googleapis.com. The limitation will be removed soon.
deployed_modelscorejsonOutput only. The models deployed in this Endpoint. To add or remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel respectively.
descriptioncorestringThe description of the Endpoint.
enable_private_service_connectcoreboolDeprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set.
encryption_speccorejsonCustomer-managed encryption key spec for an Endpoint. If set, this Endpoint and all sub-resources of this Endpoint will be secured by this key.
etagcorestringUsed to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
gcp_display_namecorestringRequired. The display name of the Endpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.
gen_ai_advanced_features_configcorejsonOptional. Configuration for GenAiAdvancedFeatures. If the endpoint is serving GenAI models, advanced features like native RAG integration can be configured. Currently, only Model Garden models are supported.
labelscorearray<string>The labels with user-defined metadata to organize your Endpoints. 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.
model_deployment_monitoring_jobcorestringOutput only. Resource name of the Model Monitoring job associated with this Endpoint if monitoring is enabled by JobService.CreateModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_monitoring_job}`
namecorestringOutput only. The resource name of the Endpoint.
networkcorestringOptional. The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and-firewalls#networks) to which the Endpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. Only one of the fields, network or enable_private_service_connect, can be set. [Format](https://cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where `{project}` is a project number, as in `12345`, and `{network}` is network name.
organization_idcorestring
parentcorestring
predict_request_response_logging_configcorejsonConfigures the request-response logging for online prediction.
private_service_connect_configcorejsonOptional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive.
project_idcorestring
project_numbercorestring
resource_namecorestring
satisfies_pzicoreboolOutput only. Reserved for future use.
satisfies_pzscoreboolOutput only. Reserved for future use.
tagscorehstore
update_timecoretimestampOutput only. Timestamp when this Endpoint was last updated.