Mantieni tutto organizzato con le raccolte
Salva e classifica i contenuti in base alle tue preferenze.
Dopo aver creato ed eseguito il deployment delle app, puoi
gestirle utilizzando la console Google Cloud o la riga di comando.
Gestire un'applicazione
Aggiornare un'app
App di cui è stato annullato il deployment
Apporta le modifiche all'app (ad esempio aggiungendo o rimuovendo nodi dei componenti).
Vertex AI Vision memorizzerà automaticamente le modifiche.
App di cui è stato eseguito il deployment
Le modifiche alle app di cui è stato eseguito il deployment vengono archiviate automaticamente sul server Vertex AI Vision
e l'applicazione di cui è stato eseguito il deployment non viene interessata. Per ignorare le modifiche, fai clic sul pulsante Annulla modifiche. Per salvare le modifiche, seleziona
Aggiorna l'applicazione. Per applicare queste modifiche locali all'applicazione,
annulla il deployment dell'applicazione corrente, quindi esegui di nuovo il deployment.
[[["Facile da capire","easyToUnderstand","thumb-up"],["Il problema è stato risolto","solvedMyProblem","thumb-up"],["Altra","otherUp","thumb-up"]],[["Difficile da capire","hardToUnderstand","thumb-down"],["Informazioni o codice di esempio errati","incorrectInformationOrSampleCode","thumb-down"],["Mancano le informazioni o gli esempi di cui ho bisogno","missingTheInformationSamplesINeed","thumb-down"],["Problema di traduzione","translationIssue","thumb-down"],["Altra","otherDown","thumb-down"]],["Ultimo aggiornamento 2025-09-09 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)."]]
