Deploy and undeploy an application

After you create an app you must deploy the app to be able to stream and analyze data.

Deploy an application

After you have built an end-to-end application with all the necessary components, you must deploy the app to start using it.

Console

Open the Applicationstab of the Vertex AI Vision dashboard.

Go to the Applications tab
Select View appnext to the name of your application from the list.
From the application graph builder page click the Deploybutton.
In the Deploy applicationmenu that opens, select any options and click Deploy.

Note: For more information about the Enable output streamingoption, see Enable live stream output . For more information about the Enable monitoring for this applicationoption, see Enable and use app monitoring .

After deployment completes there will be green check marks next to the nodes.

REST & CMD LINE

To deploy your application for use, send a POST request using the projects.locations.applications.deploy 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 .
APPLICATION_ID : The ID of your target application.

HTTP method and URL:

POST https://visionai.googleapis.com/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/applications/ APPLICATION_ID 
:deploy

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 POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json; charset=utf-8" \
-d "" \
"https://visionai.googleapis.com/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/applications/ APPLICATION_ID 
:deploy"

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 POST `
-Headers $headers `
-Uri "https://visionai.googleapis.com/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/applications/ APPLICATION_ID 
:deploy" | Select-Object -Expand Content

If successful, the request starts a long-running operation and returns a JSON object with the operation ID.

{
  "name": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/operations/ OPERATION_ID 
",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.OperationMetadata",
    "createTime": " YYYY-MM-DDTHH:MM:SS.454506987Z 
",
    "target": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/applications/ APPLICATION_ID 
",
    "verb": "update",
    "requestedCancellation": false,
    "apiVersion": "v1"
  }, "done": false}

Get operation status

Use the operation ID in the response to get the status of the deploy request.

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

REGIONALIZED_ENDPOINT : Endpoint might include a prefix matching the LOCATION_ID such as europe-west4- . See more about regionalized endpoints .
PROJECT_NUMBER : Your Google Cloud project number .
LOCATION_ID : The region where you are using Vertex AI Vision. For example: us-central1 , europe-west4 . See available regions .
OPERATION_ID : The operation ID that is returned when you start a long-running operation. For example:
- projects/123456/locations/us-central1/ [...] /operations/ OPERATION_ID

HTTP method and URL:

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

To send your request, choose one of these options:

curl

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 
/operations/ OPERATION_ID 
"

PowerShell

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 
/operations/ OPERATION_ID 
" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

Response

{
  "name": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/operations/ OPERATION_ID 
",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.OperationMetadata",
    "createTime": " 2023-01-12T17:53:14.454506987Z 
",
    "endTime": " 2023-01-12T17:53:22.979720545Z 
",
    "target": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/applications/ APPLICATION_NAME 
",
    "verb": "update",
    "statusMessage": "Instance Deployment Pending....",
    "requestedCancellation": false,
    "apiVersion": "v1"
  }, "done": true,"response": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.Application",
    "name": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/applications/ APPLICATION_NAME 
",
    "createTime": " 2023-01-06T21:16:26.465867295Z 
",
    "updateTime": " 2023-01-12T17:53:14.458441937Z 
",
    "displayName": " APPLICATION_NAME 
",
    "applicationConfigs": {
      "nodes": [
        {
          "name": "builtin-input-stream",
          "displayName": "Streams",
          "nodeConfig": {
            "videoStreamInputConfig": {}
          },
          "processor": "builtin:stream-input",
          "outputAllOutputChannelsToStream": false
        },
        {
          "name": "builtin-general-object-detector",
          "displayName": "Object detector",
          "nodeConfig": {
            "generalObjectDetectionConfig": {}
          },
          "processor": "builtin:general-object-detector",
          "parents": [
            {
              "parentNode": "builtin-input-stream"
            }
          ],
          "outputAllOutputChannelsToStream": false
        },
        {
          "name": "builtin-media-warehouse",
          "displayName": "Vision AI Warehouse",
          "nodeConfig": {
            "mediaWarehouseConfig": {
              "corpus": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
"
            }
          },
          "processor": "builtin:media-warehouse",
          "parents": [
            {
              "parentNode": "builtin-input-stream"
            },
            {
              "parentNode": "builtin-general-object-detector"
            }
          ],
          "outputAllOutputChannelsToStream": false
        }
      ]
    },
    "runtimeInfo": {
      "deployTime": " 2023-01-12T17:53:22.887918Z 
",
      "globalOutputResources": [
        {
          "outputResource": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/dataSchemas/stream-resource-name",
          "key": "stream-resource-name"
        },
        {
          "outputResource": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/dataSchemas/stream-display-name",
          "key": "stream-display-name"
        },
        {
          "outputResource": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/dataSchemas/stream-resource-id",
          "key": "stream-resource-id"
        },
        {
          "outputResource": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
/dataSchemas/general-object-detection",
          "producerNode": "builtin-general-object-detector",
          "key": "general_object_detection_data_schema_id"
        }
      ]
    }, "state": "DEPLOYED","deploymentEnvironment": "DEPLOYMENT_ENVIRONMENT_CLOUD"
  }
}

Undeploy an application

To stop using an app, you must undeploy the application.

Console

Open the Applicationstab of the Vertex AI Vision dashboard.

Go to the Applications tab
Select View appnext to the name of your application from the list.
From the application graph builder page click the Deactivatebutton.

REST & CMD LINE

To undeploy your application, send a POST request using the projects.locations.applications.undeploy 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 .
APPLICATION_ID : The ID of your target application.

HTTP method and URL:

POST https://visionai.googleapis.com/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/applications/ APPLICATION_ID 
:undeploy

To send your request, choose one of these options:

curl

Execute the following command:

curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json; charset=utf-8" \
-d "" \
"https://visionai.googleapis.com/v1/projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/applications/ APPLICATION_ID 
:undeploy"

PowerShell

Execute the following command:

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

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

If successful, the request starts a long-running operation and returns a JSON object with the operation ID.

{
  "name": "projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/operations/ OPERATION_ID 
",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.OperationMetadata",
    "createTime": "2023-01-12T18:14:48.260296926Z",
    "target": "projects/ PROJECT_NUMBER 
/locations/ LOCATION_ID 
/applications/ APPLICATION_NAME 
",
    "verb": "update",
    "requestedCancellation": false,
    "apiVersion": "v1"
  }, "done": false}

Get operation status

Use the operation ID in the response to get the status of the undeploy request.

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

REGIONALIZED_ENDPOINT : Endpoint might include a prefix matching the LOCATION_ID such as europe-west4- . See more about regionalized endpoints .
PROJECT_NUMBER : Your Google Cloud project number .
LOCATION_ID : The region where you are using Vertex AI Vision. For example: us-central1 , europe-west4 . See available regions .
OPERATION_ID : The operation ID that is returned when you start a long-running operation. For example:
- projects/123456/locations/us-central1/ [...] /operations/ OPERATION_ID

HTTP method and URL:

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

To send your request, choose one of these options:

curl

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 
/operations/ OPERATION_ID 
"

PowerShell

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 
/operations/ OPERATION_ID 
" | Select-Object -Expand Content

You should receive a JSON response similar to the following:

Response

{
  "name": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/operations/ OPERATION_ID 
",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.OperationMetadata",
    "createTime": " 2023-01-12T18:14:48.260296926Z 
",
    "endTime": " 2023-01-12T18:14:58.059563424Z 
",
    "target": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/applications/ APPLICATION_NAME 
",
    "verb": "update",
    "statusMessage": "Instance Undeployment Pending....",
    "requestedCancellation": false,
    "apiVersion": "v1"
  }, "done": true,"response": {
    "@type": "type.googleapis.com/google.cloud.visionai.v1.Application",
    "name": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/applications/ APPLICATION_NAME 
",
    "createTime": " 2023-01-06T21:16:26.465867295Z 
",
    "updateTime": " 2023-01-12T18:14:48.264089325Z 
",
    "displayName": " APPLICATION_NAME 
",
    "applicationConfigs": {
      "nodes": [
        {
          "name": "builtin-input-stream",
          "displayName": "Streams",
          "nodeConfig": {
            "videoStreamInputConfig": {}
          },
          "processor": "builtin:stream-input",
          "outputAllOutputChannelsToStream": false
        },
        {
          "name": "builtin-general-object-detector",
          "displayName": "Object detector",
          "nodeConfig": {
            "generalObjectDetectionConfig": {}
          },
          "processor": "builtin:general-object-detector",
          "parents": [
            {
              "parentNode": "builtin-input-stream"
            }
          ],
          "outputAllOutputChannelsToStream": false
        },
        {
          "name": "builtin-media-warehouse",
          "displayName": "Vision AI Warehouse",
          "nodeConfig": {
            "mediaWarehouseConfig": {
              "corpus": "projects/ PROJECT_ID 
/locations/ LOCATION_ID 
/corpora/ CORPUS_ID 
"
            }
          },
          "processor": "builtin:media-warehouse",
          "parents": [
            {
              "parentNode": "builtin-input-stream"
            },
            {
              "parentNode": "builtin-general-object-detector"
            }
          ],
          "outputAllOutputChannelsToStream": false
        }
      ]
    },
    "state": "CREATED",
    "deploymentEnvironment": "DEPLOYMENT_ENVIRONMENT_CLOUD"
  }
}

What's next

Read instructions about how to begin data ingestion from an app's input stream in Create and manage streams .
Learn how to list apps and view a deployed app's instances in Managing applications .
Learn how to read app input data from an ingestion stream or analyzed model output data in Read stream data .

Deploy and undeploy an application Stay organized with collections Save and categorize content based on your preferences.

Deploy an application

Console

REST & CMD LINE

curl

PowerShell

curl

PowerShell

Response

Undeploy an application

Console

REST & CMD LINE

curl

PowerShell

curl

PowerShell

Response

What's next

Deploy and undeploy an application