Manage applications

After you build and deploy apps, you can manage these apps using the Google Cloud console or command line.

Manage an application

Update an app

Undeployed apps

Make any modifications to the app (such as adding or removing component nodes) ; Vertex AI Vision will automatically store the changes.

Deployed apps

Changes to deployed apps are automatically stored to the Vertex AI Vision server and the deployed application is not affected. To discard modifications, click the Discard changes button. To save changes, select Update the application. To apply these local changes to the application, undeploy the current application, then redeploy it.

List apps

REST

To list all apps in a project, send a GET request by using the projects.locations.applications.list method.

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

• PROJECT: Your Google Cloud project ID or project number.
• LOCATION_ID: The region where you are using Vertex AI Vision. For example: us-central1, europe-west4. See available regions.

HTTP method and URL:

GET https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/applications

To send your request, choose one of these options:

curl

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.

Execute the following command:

curl -X GET \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     "https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/applications"

PowerShell

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.

Execute the following command:

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

Invoke-WebRequest `
    -Method GET `
    -Headers $headers `
    -Uri "https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/applications" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

{
  "applications": [
    {
      "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/applications/test-application-1",
      "createTime": "2022-03-01T20:04:12.558371402Z",
      "updateTime": "2022-03-01T20:07:21.589713094Z",
      "displayName": "Test Application 1",
      "runtimeInfo": {
        "deployTime": "2022-03-01T20:07:21.460654Z"
      }
      "state": "DEPLOYED"
    },
    {
      "name": "projects/PROJECT_NUMBER/locations/LOCATION_ID/applications/test-application-2",
      "createTime": "2022-03-01T20:04:12.558371402Z",
      "updateTime": "2022-03-01T20:07:21.589713094Z",
      "displayName": "Test Application 2",
      "runtimeInfo": {
        "deployTime": "2022-03-01T20:07:21.460654Z"
      }
      "state": "DEPLOYED"
    },
  ]
}

What's next

• Learn how to read app input data from an ingestion stream or analyzed model output data in Read stream data.