Question

You maintain an Azure AI Search index that grounds a RAG-based support agent. Documents are stored in an Azure Blob Storage container that receives roughly 50 updated or new files per day out of 2 million total blobs. The current indexer runs on a nightly schedule but reprocesses the entire container each run, consuming large amounts of enrichment (skillset) cost and taking hours. You need the indexer to process only blobs that have changed since the last successful run, with the least operational effort. What should you configure?

Accepted Answer

Rely on the indexer's default change detection for Azure Blob Storage, which uses the blob's LastModified timestamp as the high-water mark.

Answer

Enable soft delete on the storage account and add a deletion detection policy so the indexer skips unchanged blobs.

Answer

Add a custom Web API skill that compares document hashes and short-circuits enrichment for unchanged files.

Answer

Switch the indexer to a full reset and re-run on demand only when the source data owner notifies you of changes.