Try Gemini 1.5 models, our newest multimodal models in Vertex AI, and see what you can build with a 1M token context window. Try Gemini 1.5 models, our newest multimodal models in Vertex AI, and see what you can build with a 1M token context window.

Method: projects.locations.modelMonitors.create

Creates a ModelMonitor.

HTTP request

POST http://{service-endpoint}/v1beta1/{parent}/modelMonitors

Where {service-endpoint} is one of the supported service endpoints.

Path parameters

Parameters

Parameters
`parent`	`string` Required. The resource name of the Location to create the ModelMonitor in. Format: `projects/{project}/locations/{location}`

parent

string

Required. The resource name of the Location to create the ModelMonitor in. Format: projects/{project}/locations/{location}

Query parameters

Parameters

Parameters
`modelMonitorId`	`string` Optional. The ID to use for the Model Monitor, which will become the final component of the model monitor resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`.

modelMonitorId

string

Optional. The ID to use for the Model Monitor, which will become the final component of the model monitor resource name.

The maximum length is 63 characters, and valid characters are /^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/.

Request body

The request body contains an instance of ModelMonitor.

Response body

If successful, the response body contains a newly created instance of Operation.

Authorization scopes

Requires the following OAuth scope:

http://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.