Question

A media company uses an Amazon Bedrock Knowledge Base backed by an Amazon S3 data source containing 50,000 documents. During a scheduled ingestion job, the sync completes but the team notices that roughly 300 documents were not indexed. They need a reliable way to identify exactly which documents failed and why, without re-processing the entire corpus. What is the most effective approach?

Accepted Answer

Review the ingestion job's data source sync status and inspect the per-document failure details and reasons emitted to the configured Amazon CloudWatch/S3 logs, then correct and re-sync only the affected documents.

Answer

Delete the entire Knowledge Base and recreate it from scratch, since partial ingestion failures cannot be diagnosed at the document level.

Answer

Increase the provisioned throughput of the embedding model so all 50,000 documents are processed together in a single batch.

Answer

Enable hybrid search on the vector store so that documents that failed dense embedding are still retrievable through keyword matching.