Microsoft Azure AI Engineer Associate AI-102 Practice Question
You manage a Language Understanding (LUIS) app that is currently at version 3.0. Before experimenting with major schema changes, you need a point-in-time backup that you can later restore, even if version 3.0 is accidentally deleted from the authoring resource. Which action should you take to meet this requirement?
Clone version 3.0 in the LUIS portal and rename the clone to Backup_3_0.
Publish version 3.0 to the staging slot and switch traffic back if you need to roll back.
Enable version pinning on the prediction resource so version 3.0 remains available even if deleted.
Export version 3.0 to a JSON file and store it externally; import the file later to restore the model.
Exporting the current LUIS version to a JSON file creates an offline copy that is completely independent of the LUIS authoring resource. The file can be stored in source control or secure storage and later re-imported as a new version to fully recover intents, entities, and utterances. Cloning a version only makes an in-portal copy that is lost if the resource is removed. Publishing to the staging slot provides an endpoint for testing but does not act as a backup. Version pinning lets prediction requests target a specific version but does not preserve that version if it is deleted.
Ask Bash
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What does exporting a LUIS app version to a JSON file achieve?
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Why is cloning a version insufficient as a backup in LUIS?
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What is the purpose of version pinning in LUIS and how is it different from exporting?
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Microsoft Azure AI Engineer Associate AI-102
Implement natural language processing solutions
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