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.modelMonitoringJobs.create

Creates a ModelMonitoringJob.

HTTP request

POST https://{service-endpoint}/v1beta1/{parent}/modelMonitoringJobs

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

Path parameters

Parameters

Parameters
`parent`	`string` Required. The parent of the ModelMonitoringJob. Format: `projects/{project}/locations/{location}/modelMoniitors/{modelMonitor}`

parent

string

Required. The parent of the ModelMonitoringJob. Format: projects/{project}/locations/{location}/modelMoniitors/{modelMonitor}

Query parameters

Parameters

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

modelMonitoringJobId

string

Optional. The ID to use for the Model Monitoring Job, which will become the final component of the model monitoring job 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 ModelMonitoringJob.

Response body

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

Authorization scopes

Requires the following OAuth scope:

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

For more information, see the Authentication Overview.