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Showing content from https://cloud.google.com/sql/docs/postgres/integrate-cloud-sql-with-vertex-ai below:

Integrate Cloud SQL with Vertex AI | Cloud SQL for PostgreSQL

Create or update a Cloud SQL instance so that the instance can integrate with Vertex AI. gcloud Create the instance

To create the Cloud SQL instance, use the gcloud sql instances create command.

gcloud sql instances create INSTANCE_NAME \
--database-version=DATABASE_VERSION \
--tier=MACHINE_TYPE \
--region=REGION_NAME \
--enable-google-ml-integration \
--database-flags cloudsql.enable_google_ml_integration=on

Make the following replacements:

INSTANCE_NAME: the name of the instance
DATABASE_VERSION: the database version for the instance (for example, POSTGRES_13)
MACHINE_TYPE: the machine type for the instance
REGION_NAME: the region name for the instance

Note: For more information about these parameters, see Create instances. Update the instance

To update the instance, use the gcloud sql instances patch command.

gcloud sql instances patch INSTANCE_NAME \
--enable-google-ml-integration \
--database-flags cloudsql.enable_google_ml_integration=on

If this update modifies a value that requires a restart, then you see a prompt to proceed with the change or cancel.

Note: For more information about updating an instance, see Edit instances. REST v1 Create the instance

Use this example to create the instance. For a complete list of parameters for this call, see the instances:insert page. For information about instance settings, including valid values for a region, see Instance settings.

Before using any of the request data, make the following replacements:

PROJECT_ID: the ID or project number of the Google Cloud project that contains the instance
INSTANCE_NAME: the name of the instance
REGION_NAME: the region name for the instance
DATABASE_VERSION: enum string of the database version (for example: POSTGRES_13)
PASSWORD: the password for the root user
MACHINE_TYPE: enum string of the machine (tier) type, as: db-custom-[CPUS]-[MEMORY_MBS]
EDITION_TYPE: your Cloud SQL edition

Note: For more information about these parameters, see Create instances.

You must also include the enableGoogleMlIntegration object in the request. Set the following parameters, as required:

enableGoogleMlIntegration: when this parameter is set to true, Cloud SQL instances can connect to Vertex AI to pass requests for real-time predictions and insights to the AI
cloudsql.enable_google_ml_integration: when this parameter is set to on, Cloud SQL can integrate with Vertex AI

HTTP method and URL:

POST https://sqladmin.googleapis.com/v1/projects/PROJECT_ID/instances

Request JSON body:

{
  "name": "INSTANCE_NAME",
  "region": "REGION_NAME",
  "databaseVersion": "DATABASE_VERSION",
  "rootPassword": "PASSWORD",
  "settings": {
    "tier": "MACHINE_TYPE",
    "edition": "EDITION_TYPE",
    "enableGoogleMlIntegration": "true" | "false"
    "databaseFlags":
      {
        "name": "cloudsql.enable_google_ml_integration",
        "value": "on" | "off"
      }
  }
}

To send your request, expand one of these options:

curl (Linux, macOS, or Cloud Shell) Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://sqladmin.googleapis.com/v1/projects/PROJECT_ID/instances"

PowerShell (Windows) Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `

-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://sqladmin.googleapis.com/v1/projects/PROJECT_ID/instances" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "kind": "sql#operation",
  "targetLink": "https://sqladmin.googleapis.com/v1/projects/PROJECT_ID/instances/INSTANCE_ID",
  "status": "PENDING",
  "user": "user@example.com",
  "insertTime": "2019-09-25T22:19:33.735Z",
  "operationType": "CREATE",
  "name": "OPERATION_ID",
  "targetId": "INSTANCE_ID",
  "selfLink": "https://sqladmin.googleapis.com/v1/projects/PROJECT_ID/operations/OPERATION_ID",
  "targetProject": "PROJECT_ID"
}

Update the instance

Use this example to update the instance. For a complete list of parameters for this call, see the instances.patch page.

If this update modifies a value that requires a restart, then you see a prompt to proceed with the change or cancel.

Before using any of the request data, make the following replacements:

PROJECT_ID: the ID or project number of the Google Cloud project that contains the instance
INSTANCE_NAME: the name of the instance

HTTP method and URL:

PATCH https://sqladmin.googleapis.com/v1/projects/PROJECT_ID/instances/INSTANCE_NAME

Request JSON body:

{
  "settings": {
    "enableGoogleMlIntegration": true,
    "databaseFlags":
      {
        "name": "cloudsql.enable_google_ml_integration",
        "value": "on"
      }
   }
}

To send your request, expand one of these options:

Save the request body in a file named request.json, and execute the following command:

curl -X PATCH \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://sqladmin.googleapis.com/v1/projects/PROJECT_ID/instances/INSTANCE_NAME"

Save the request body in a file named request.json, and execute the following command:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `

-Method PATCH `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://sqladmin.googleapis.com/v1/projects/PROJECT_ID/instances/INSTANCE_NAME" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "kind": "sql#operation",
  "targetLink": "https://sqladmin.googleapis.com/v1/projects/PROJECT_ID/instances/INSTANCE_NAME",
  "status": "PENDING",
  "user": "user@example.com",
  "insertTime": "2020-01-16T02:32:12.281Z",
  "operationType": "UPDATE",
  "name": "OPERATION_ID",
  "targetId": "INSTANCE_NAME",
  "selfLink": "https://sqladmin.googleapis.com/v1/projects/PROJECT_ID/operations/OPERATION_ID",
  "targetProject": "PROJECT_ID"
}

Note: For more information about updating an instance, see Edit instances. REST v1beta4 Create the instance

Before using any of the request data, make the following replacements:

PROJECT_ID: the ID or project number of the Google Cloud project that contains the instance
INSTANCE_NAME: the name of the instance
REGION_NAME: the region name for the instance
DATABASE_VERSION: enum string of the database version (for example: POSTGRES_13)
PASSWORD: the password for the root user
MACHINE_TYPE: enum string of the machine (tier) type, as: db-custom-[CPUS]-[MEMORY_MBS]
EDITION_TYPE: your Cloud SQL edition

Note: For more information about these parameters, see Create instances.

You must also include the enableGoogleMlIntegration object in the request. Set the following parameters, as required:

enableGoogleMlIntegration: when this parameter is set to true, Cloud SQL instances can connect to Vertex AI to pass requests for real-time predictions and insights to the AI
cloudsql.enable_google_ml_integration: when this parameter is set to on, Cloud SQL can integrate with Vertex AI

HTTP method and URL:

POST https://sqladmin.googleapis.com/v1beta4/projects/PROJECT_ID/instances

Request JSON body:

{
  "name": "INSTANCE_NAME",
  "region": "REGION_NAME",
  "databaseVersion": "DATABASE_VERSION",
  "rootPassword": "PASSWORD",
  "settings": {
    "tier": "MACHINE_TYPE",
    "edition": "EDITION_TYPE",
    "enableGoogleMlIntegration": "true" | "false"
    "databaseFlags":
      {
        "name": "cloudsql.enable_google_ml_integration",
        "value": "on" | "off"
      }
  }
}

To send your request, expand one of these options:

Save the request body in a file named request.json, and execute the following command:

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://sqladmin.googleapis.com/v1beta4/projects/PROJECT_ID/instances"

Save the request body in a file named request.json, and execute the following command:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `

-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://sqladmin.googleapis.com/v1beta4/projects/PROJECT_ID/instances" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "kind": "sql#operation",
  "targetLink": "https://sqladmin.googleapis.com/v1beta4/projects/PROJECT_ID/instances/INSTANCE_ID",
  "status": "PENDING",
  "user": "user@example.com",
  "insertTime": "2019-09-25T22:19:33.735Z",
  "operationType": "CREATE",
  "name": "OPERATION_ID",
  "targetId": "INSTANCE_ID",
  "selfLink": "https://sqladmin.googleapis.com/v1beta4/projects/PROJECT_ID/operations/OPERATION_ID",
  "targetProject": "PROJECT_ID"
}

Update the instance

Use this example to update the instance. For a complete list of parameters for this call, see the instances.patch page.

If this update modifies a value that requires a restart, then you see a prompt to proceed with the change or cancel.

Before using any of the request data, make the following replacements:

PROJECT_ID: the ID or project number of the Google Cloud project that contains the instance
INSTANCE_NAME: the name of the instance

HTTP method and URL:

PATCH https://sqladmin.googleapis.com/v1beta4/projects/PROJECT_ID/instances/INSTANCE_NAME

Request JSON body:

{
  "settings": {
    "enableGoogleMlIntegration": true,
    "databaseFlags":
      {
        "name": "cloudsql.enable_google_ml_integration",
        "value": "on"
      }
   }
}

To send your request, expand one of these options:

Save the request body in a file named request.json, and execute the following command:

curl -X PATCH \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://sqladmin.googleapis.com/v1beta4/projects/PROJECT_ID/instances/INSTANCE_NAME"

Save the request body in a file named request.json, and execute the following command:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `

-Method PATCH `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://sqladmin.googleapis.com/v1beta4/projects/PROJECT_ID/instances/INSTANCE_NAME" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "kind": "sql#operation",
  "targetLink": "https://sqladmin.googleapis.com/v1beta4/projects/PROJECT_ID/instances/INSTANCE_NAME",
  "status": "PENDING",
  "user": "user@example.com",
  "insertTime": "2020-01-16T02:32:12.281Z",
  "operationType": "UPDATE",
  "name": "OPERATION_ID",
  "targetId": "INSTANCE_NAME",
  "selfLink": "https://sqladmin.googleapis.com/v1beta4/projects/PROJECT_ID/operations/OPERATION_ID",
  "targetProject": "PROJECT_ID"
}

Note: For more information about updating an instance, see Edit instances.

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