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“Monitor drift in search quality and zero-result rates” concerns Latency metric alone says nothing about retrieval quality; the reported problem instead is Approximate index recall is unnecessary for this dataset. Monitor exact-search latency as table grows.

“Monitor RLS test failures and filtered-search recall” concerns Top-k results may contain another tenant's content; the reported problem instead is Approximate index recall is unnecessary for this dataset. Monitor exact-search latency as table grows.

“Monitor optimizer fallback to exact scan” concerns Compatible ANN index may not be selected; the reported problem instead is Approximate index recall is unnecessary for this dataset. Monitor exact-search latency as table grows.

“Inspect index metric and query plan warnings” concerns Compatible ANN index may not be selected; the reported problem instead is Exact full scans miss API latency target. Inspect engine/version and ANN index availability and chosen distance metric.

“Inspect model recommended similarity metric and normalization” concerns Euclidean distance changes ranking for varying-length vectors; the reported problem instead is Exact full scans miss API latency target. Inspect engine/version and ANN index availability and chosen distance metric.

“Inspect engine VECTOR support and embedding dimension” concerns Numeric similarity queries are slow and error-prone; the reported problem instead is Exact full scans miss API latency target. Inspect engine/version and ANN index availability and chosen distance metric.

“Use supported VECTOR type with correct dimensions for numeric embeddings” concerns Numeric similarity queries are slow and error-prone; the reported problem instead is Exact full scans miss API latency target. Use supported vector index with VECTOR_SEARCH latest syntax when applicable.

“Use supported VECTOR_DISTANCE ordering to compute exact pairwise distances” concerns Approximate index recall is unnecessary for this dataset; the reported problem instead is Exact full scans miss API latency target. Use supported vector index with VECTOR_SEARCH latest syntax when applicable.

“Align vector index metric to the query scoring requirement” concerns Compatible ANN index may not be selected; the reported problem instead is Exact full scans miss API latency target. Use supported vector index with VECTOR_SEARCH latest syntax when applicable.

“Run exact phrase and inflection tests on sample texts” concerns LIKE contains pattern scans large text columns; the reported problem instead is Exact full scans miss API latency target. Compare approximate top-k results with exact baseline on test vectors.

“Query synthetic vectors from tenant A and B under An identity” addresses the tenant-scoped vector retrieval situation—top-k results may contain another tenant's content. The observed failure is: Exact full scans miss API latency target. Compare approximate top-k results with exact baseline on test vectors.

“Insert sample vectors with intended dimension into test schema” concerns Queries fail during similarity calculation; the reported problem instead is Exact full scans miss API latency target. Compare approximate top-k results with exact baseline on test vectors.

Relevance checks alone can miss unacceptable query latency. The requirement explicitly includes latency and recall measured against an agreed exact-result benchmark. Only D tests both named acceptance dimensions.

Relevance against a benchmark is necessary but does not demonstrate the production response time. D explicitly requires both top-k recall and latency compared to fixed thresholds.

Low latency can hide a fast but low-quality index that misses relevant documents. D additionally requires recall against an exact-result benchmark, which the latency-only criterion cannot establish.

“Monitor metric mismatches between index and requests” concerns Euclidean distance changes ranking for varying-length vectors; the reported problem instead is Exact full scans miss API latency target. Monitor ANN recall, index health and plan selection.

“Monitor RLS test failures and filtered-search recall” concerns Top-k results may contain another tenant's content; the reported problem instead is Exact full scans miss API latency target. Monitor ANN recall, index health and plan selection.

“Monitor recall loss after index changes” concerns ANN tuning could miss a few true nearest matches; the reported problem instead is Exact full scans miss API latency target. Monitor ANN recall, index health and plan selection.

“Inspect engine/version and ANN index availability and chosen distance metric” concerns Exact full scans miss API latency target; the reported problem instead is Vector feature support and preview status differ by platform. Identify engine edition, update policy and feature configuration.

“Inspect engine VECTOR support and embedding dimension” concerns Numeric similarity queries are slow and error-prone; the reported problem instead is Vector feature support and preview status differ by platform. Identify engine edition, update policy and feature configuration.

“Inspect model version recorded for each chunk and target similarity” concerns New query embeddings and historical vectors are incompatible semantically; the reported problem instead is Vector feature support and preview status differ by platform. Identify engine edition, update policy and feature configuration.

“Regenerate index vectors and rebuild/revalidate compatible index” concerns New query embeddings and historical vectors are incompatible semantically; the reported problem instead is Vector feature support and preview status differ by platform. Gate index usage on documented target-platform capability.

“Align vector index metric to the query scoring requirement” concerns Compatible ANN index may not be selected; the reported problem instead is Vector feature support and preview status differ by platform. Gate index usage on documented target-platform capability.

“Use reciprocal rank fusion with documented rank offset” concerns Raw score addition unfairly favors one system; the reported problem instead is Vector feature support and preview status differ by platform. Gate index usage on documented target-platform capability.

“Insert sample vectors with intended dimension into test schema” concerns Queries fail during similarity calculation; the reported problem instead is Vector feature support and preview status differ by platform. Apply planned DDL in test SQL Server and Azure SQL environments.

“Insert a valid numeric vector and malformed text in test table” concerns Numeric similarity queries are slow and error-prone; the reported problem instead is Vector feature support and preview status differ by platform. Apply planned DDL in test SQL Server and Azure SQL environments.

“Measure recall before and after controlled reembedding of test corpus” concerns New query embeddings and historical vectors are incompatible semantically; the reported problem instead is Vector feature support and preview status differ by platform. Apply planned DDL in test SQL Server and Azure SQL environments.

“Vectors round-trip and invalid dimensions or formats are rejected” concerns Numeric similarity queries are slow and error-prone; the reported problem instead is Vector feature support and preview status differ by platform. Deployment succeeds only where feature is supported and reviewed.

“Chosen retrieval meets pre-agreed relevance and latency thresholds” concerns Latency metric alone says nothing about retrieval quality; the reported problem instead is Vector feature support and preview status differ by platform. Deployment succeeds only where feature is supported and reviewed.

“Search relevance meets benchmark using a consistent model version” concerns New query embeddings and historical vectors are incompatible semantically; the reported problem instead is Vector feature support and preview status differ by platform. Deployment succeeds only where feature is supported and reviewed.

“Track recall loss after index changes” addresses the ann versus exact tradeoff situation—aNN tuning could miss a few true nearest matches. The observed failure is: Vector feature support and preview status differ by platform. Monitor feature changes and migration incompatibilities.

“Monitor full-text population lag and stoplist changes” concerns LIKE contains pattern scans large text columns; the reported problem instead is Vector feature support and preview status differ by platform. Monitor feature changes and migration incompatibilities.

“Monitor failed conversions and vector schema changes” concerns Numeric similarity queries are slow and error-prone; the reported problem instead is Vector feature support and preview status differ by platform. Monitor feature changes and migration incompatibilities.