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“Monitor unapproved workflows and approval latency” concerns Automated embedding updates currently ignore content classification; the reported problem instead is Embedding jobs miss deleted records. Monitor capture lag and duplicate events.

“Monitor model versions and dimension mismatch errors” concerns A replacement embedding model produces vectors of a different length; the reported problem instead is Embedding jobs miss deleted records. Monitor capture lag and duplicate events.

“Monitor language-level recall drift” concerns The original embedding model performs poorly on non-English text; the reported problem instead is Embedding jobs miss deleted records. Monitor capture lag and duplicate events.

“Inspect modality of source content and model input capabilities” concerns Text-only embeddings do not reflect visual diagrams; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Inspect trigger workload, model latency and safe asynchronous handoff.

“Inspect SQL trigger binding and available identity to model service” concerns Heavy embedding calls cannot safely run in every SQL write transaction; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Inspect trigger workload, model latency and safe asynchronous handoff.

“Inspect model token limits, concurrency and rate limits” concerns Endpoint overhead dominates ingestion time; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Inspect trigger workload, model latency and safe asynchronous handoff.

“Use Azure Function triggered by SQL changes to compute and write embeddings” concerns Heavy embedding calls cannot safely run in every SQL write transaction; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Use a lightweight trigger to enqueue work instead of blocking on model inference.

“Choose a multilingual embedding model with compatible output size and governance” concerns The original embedding model performs poorly on non-English text; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Use a lightweight trigger to enqueue work instead of blocking on model inference.

“Select model/settings enforcing schema-bound JSON and validation” concerns Free-form model prose breaks downstream parsing; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Use a lightweight trigger to enqueue work instead of blocking on model inference.

“Call an isolated test model with synthetic data” concerns A third-party model region is outside allowed residency; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Change a synthetic row and observe queued update.

“Modify sample catalog row and observe isolated Function execution” concerns Heavy embedding calls cannot safely run in every SQL write transaction; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Change a synthetic row and observe queued update.

“Insert/update/delete test items through the CDC path” concerns Embedding jobs miss deleted records; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Change a synthetic row and observe queued update.

“Relevant support paragraphs rank higher without embedding protected details” concerns Embedding customer IDs and secrets would add noise and risk; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Transaction completes quickly and embedding job eventually updates.

“Stored vector version corresponds to newest source text” concerns Heavy embedding calls cannot safely run in every SQL write transaction; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Transaction completes quickly and embedding job eventually updates.

“Data stays within authorized processing boundary” concerns A third-party model region is outside allowed residency; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Transaction completes quickly and embedding job eventually updates.

“Monitor invocation retries and stale vector age” concerns Heavy embedding calls cannot safely run in every SQL write transaction; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Monitor trigger retries and work queue growth.

“Monitor model versions and dimension mismatch errors” concerns A replacement embedding model produces vectors of a different length; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Monitor trigger retries and work queue growth.

“Monitor endpoint region changes and transfer logs” concerns A third-party model region is outside allowed residency; the reported problem instead is Synchronous model calls in a DML trigger would slow transactions. Monitor trigger retries and work queue growth.

“Examine modality of source content and model input capabilities” addresses the multimodal model suitability situation—text-only embeddings do not reflect visual diagrams. The observed failure is: Heavy embedding calls cannot safely run in every SQL write transaction. Inspect SQL trigger binding and available identity to model service.

“Inspect model token limits, concurrency and rate limits” concerns Endpoint overhead dominates ingestion time; the reported problem instead is Heavy embedding calls cannot safely run in every SQL write transaction. Inspect SQL trigger binding and available identity to model service.

“Inspect trigger workload, model latency and safe asynchronous handoff” concerns Synchronous model calls in a DML trigger would slow transactions; the reported problem instead is Heavy embedding calls cannot safely run in every SQL write transaction. Inspect SQL trigger binding and available identity to model service.

“Use supported CDC stream to update or delete corresponding vectors” concerns Embedding jobs miss deleted records; the reported problem instead is Heavy embedding calls cannot safely run in every SQL write transaction. Use Azure Function triggered by SQL changes to compute and write embeddings.

“Use a lightweight trigger to enqueue work instead of blocking on model inference” concerns Synchronous model calls in a DML trigger would slow transactions; the reported problem instead is Heavy embedding calls cannot safely run in every SQL write transaction. Use Azure Function triggered by SQL changes to compute and write embeddings.

“Keep dimensions consistent or migrate vector schema and regenerate embeddings” concerns A replacement embedding model produces vectors of a different length; the reported problem instead is Heavy embedding calls cannot safely run in every SQL write transaction. Use Azure Function triggered by SQL changes to compute and write embeddings.

“Change a synthetic row and observe queued update” concerns Synchronous model calls in a DML trigger would slow transactions; the reported problem instead is Heavy embedding calls cannot safely run in every SQL write transaction. Modify sample catalog row and observe isolated Function execution.

“Update a sample description and run incremental embedding worker” concerns Vector similarity returns obsolete product details; the reported problem instead is Heavy embedding calls cannot safely run in every SQL write transaction. Modify sample catalog row and observe isolated Function execution.

“Call an isolated test model with synthetic data” concerns A third-party model region is outside allowed residency; the reported problem instead is Heavy embedding calls cannot safely run in every SQL write transaction. Modify sample catalog row and observe isolated Function execution.

“The vector store reflects each committed source operation” addresses the embedding refresh via cdc situation—embedding jobs miss deleted records. The observed failure is: Heavy embedding calls cannot safely run in every SQL write transaction. Stored vector version corresponds to newest source text.

“New vector represents changed content and stale vector is replaced” concerns Vector similarity returns obsolete product details; the reported problem instead is Heavy embedding calls cannot safely run in every SQL write transaction. Stored vector version corresponds to newest source text.

“Result can be traced to current source content and model version” concerns Expired policy versions may be presented as current; the reported problem instead is Heavy embedding calls cannot safely run in every SQL write transaction. Stored vector version corresponds to newest source text.

“Monitor trigger retries and work queue growth” concerns Synchronous model calls in a DML trigger would slow transactions; the reported problem instead is Heavy embedding calls cannot safely run in every SQL write transaction. Monitor invocation retries and stale vector age.

“Monitor outdated vector/source mismatches” concerns Expired policy versions may be presented as current; the reported problem instead is Heavy embedding calls cannot safely run in every SQL write transaction. Monitor invocation retries and stale vector age.

“Monitor capture lag and duplicate events” concerns Embedding jobs miss deleted records; the reported problem instead is Heavy embedding calls cannot safely run in every SQL write transaction. Monitor invocation retries and stale vector age.