Try Gemini 1.5 models, the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window. Try Gemini 1.5 models, the latest multimodal models in Vertex AI, and see what you can build with up to a 2M token context window.

Method: projects.locations.deploymentResourcePools.patch

Update a DeploymentResourcePool.

HTTP request

PATCH https://{service-endpoint}/v1/{deploymentResourcePool.name}

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

Path parameters

Parameters

Parameters
`deploymentResourcePool.name`	`string` Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deploymentResourcePool}`

deploymentResourcePool.name

string

Immutable. The resource name of the DeploymentResourcePool. Format: projects/{project}/locations/{location}/deploymentResourcePools/{deploymentResourcePool}

Query parameters

Parameters

Parameters
`updateMask`	`string (FieldMask format)` Required. The list of fields to update. This is a comma-separated list of fully qualified names of fields. Example: `"user.displayName,photo"`.

updateMask

string (FieldMask format)

Required. The list of fields to update.

This is a comma-separated list of fully qualified names of fields. Example: "user.displayName,photo".

Request body

The request body contains an instance of DeploymentResourcePool.

Response body

If successful, the response body contains an instance of Operation.

Authorization scopes

Requires the following OAuth scope:

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

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

aiplatform.deploymentResourcePools.update

For more information, see the IAM documentation.