Update Endpoint
vertex_ai.update_endpoint
ActionGoogle Cloudconnection required
Calls aiplatform v1 PATCH /v1/projects/{projectsId}/locations/{locationsId}/endpoints/{endpointsId}.
Updates an Endpoint.
Connection
- Required
- Yes — the node will not save without one
- Auth type
- OAuth 2.0
- Providers
- Google Vertex AI
- Secret shape
- {"client_id", "client_secret", "refresh_token"}
- Config it needs
- project_id, region
- Resolved by
- config.connection_id, else node.connection_id
Configuration
4 fields, 2 required. A dotted path is a nested object and name[] an array of objects — the editor renders the same tree.
| Field | Type | Required | Default | Constraints | Example |
|---|---|---|---|---|---|
location Location or region; taken from the connection when unset. | string | No | — | — | — |
endpoint Endpoint name or id. | string | Yes | — | — | — |
body The GoogleCloudAiplatformV1Endpoint resource, as the API defines it. | object | Yes | — | — | — |
update_mask The update mask applies to the resource. Optional. | string | No | — | — | — |
Output
One shape.
result
Extra keys beyond the ones listed can appear.
| Field | Type | Example |
|---|---|---|
clientConnectionConfig | object | — |
createTime | string | — |
dedicatedEndpointDns | string | — |
dedicatedEndpointEnabled | boolean | — |
deployedModels | array | — |
description | string | — |
displayName | string | — |
enablePrivateServiceConnect | boolean | — |
encryptionSpec | object | — |
etag | string | — |
gdcConfig | object | — |
genAiAdvancedFeaturesConfig | object | — |
labels | object | — |
modelDeploymentMonitoringJob | string | — |
name | string | — |
network | string | — |
predictRequestResponseLoggingConfig | object | — |
privateServiceConnectConfig | object | — |
satisfiesPzi | boolean | — |
satisfiesPzs | boolean | — |
trafficSplit | object | — |
updateTime | string | — |
{
"clientConnectionConfig": {},
"createTime": "",
"dedicatedEndpointDns": "",
"dedicatedEndpointEnabled": false,
"deployedModels": [],
"description": "",
"displayName": "",
"enablePrivateServiceConnect": false,
"encryptionSpec": {},
"etag": "",
"gdcConfig": {},
"genAiAdvancedFeaturesConfig": {},
"labels": {},
"modelDeploymentMonitoringJob": "",
"name": "",
"network": "",
"predictRequestResponseLoggingConfig": {},
"privateServiceConnectConfig": {},
"satisfiesPzi": false,
"satisfiesPzs": false,
"trafficSplit": {},
"updateTime": ""
}Related Google Vertex AI nodes
See Update Endpoint run in a workflow.
In a technical demo we add the Google Vertex AI connection, drop the node on the canvas and let Workflow Health pre-flight it before the first real run.