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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.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-28 UTC."],[],[],null,["# Manage applications\n\nAfter you [build](/vision-ai/docs/build-app) and [deploy](/vision-ai/docs/deploy-app) apps, you can\nmanage these apps using the Google Cloud console or command line.\n\nManage an application\n---------------------\n\nUpdate an app\n-------------\n\n#### Undeployed apps\n\nMake any modifications to the app (such as adding or removing component nodes)\n; Vertex AI Vision will automatically store the changes.\n\n#### Deployed apps\n\nChanges to deployed apps are automatically stored to the Vertex AI Vision server\nand the deployed application is not affected. To discard modifications, click\nthe **Discard changes** button. To save changes, select\n**Update the application**. To apply these local changes to the application,\nundeploy the current application, then redeploy it.\n\nList apps\n---------\n\n### REST\n\nTo list all apps in a project, send a GET request by using the\n[projects.locations.applications.list](/vision-ai/docs/reference/rest/v1/projects.locations.applications/list)\nmethod.\n\n\nBefore using any of the request data,\nmake the following replacements:\n\n- \u003cvar translate=\"no\"\u003ePROJECT\u003c/var\u003e: Your Google Cloud [project ID or\n project number](/resource-manager/docs/creating-managing-projects#identifying_projects).\n- \u003cvar translate=\"no\"\u003eLOCATION_ID\u003c/var\u003e: The [region](/about/locations) where you are using Vertex AI Vision. For example: `us-central1`, `europe-west4`. See [available regions](/vision-ai/docs/warehouse-supported-regions).\n\n\nHTTP method and URL:\n\n```\nGET https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/applications\n```\n\nTo send your request, choose one of these options: \n\n#### curl\n\n| **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](/sdk/gcloud/reference/init) or [`gcloud auth login`](/sdk/gcloud/reference/auth/login) , or by using [Cloud Shell](/shell/docs), which automatically logs you into the `gcloud` CLI . You can check the currently active account by running [`gcloud auth list`](/sdk/gcloud/reference/auth/list).\n\n\nExecute the following command:\n\n```\ncurl -X GET \\\n -H \"Authorization: Bearer $(gcloud auth print-access-token)\" \\\n \"https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/applications\"\n```\n\n#### PowerShell\n\n| **Note:** The following command assumes that you have logged in to the `gcloud` CLI with your user account by running [`gcloud init`](/sdk/gcloud/reference/init) or [`gcloud auth login`](/sdk/gcloud/reference/auth/login) . You can check the currently active account by running [`gcloud auth list`](/sdk/gcloud/reference/auth/list).\n\n\nExecute the following command:\n\n```\n$cred = gcloud auth print-access-token\n$headers = @{ \"Authorization\" = \"Bearer $cred\" }\n\nInvoke-WebRequest `\n -Method GET `\n -Headers $headers `\n -Uri \"https://visionai.googleapis.com/v1/projects/PROJECT_NUMBER/locations/LOCATION_ID/applications\" | Select-Object -Expand Content\n```\n\nYou should receive a JSON response similar to the following:\n\n```\n{\n \"applications\": [\n {\n \"name\": \"projects/PROJECT_NUMBER/locations/LOCATION_ID/applications/test-application-1\",\n \"createTime\": \"2022-03-01T20:04:12.558371402Z\",\n \"updateTime\": \"2022-03-01T20:07:21.589713094Z\",\n \"displayName\": \"Test Application 1\",\n \"runtimeInfo\": {\n \"deployTime\": \"2022-03-01T20:07:21.460654Z\"\n }\n \"state\": \"DEPLOYED\"\n },\n {\n \"name\": \"projects/PROJECT_NUMBER/locations/LOCATION_ID/applications/test-application-2\",\n \"createTime\": \"2022-03-01T20:04:12.558371402Z\",\n \"updateTime\": \"2022-03-01T20:07:21.589713094Z\",\n \"displayName\": \"Test Application 2\",\n \"runtimeInfo\": {\n \"deployTime\": \"2022-03-01T20:07:21.460654Z\"\n }\n \"state\": \"DEPLOYED\"\n },\n ]\n}\n```\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\nWhat's next\n-----------\n\n- Learn how to read app input data from an ingestion stream or analyzed model output data in [Read stream data](/vision-ai/docs/read-stream)."]]
