Retrieval-Augmented Generation (RAG) solutions built using Azure AI Search and Azure OpenAI often perform well during initial testing and early production rollout. However, many teams notice that retrieval quality degrades gradually over time—even when there are no code changes, no infrastructure issues, and no service outages. A common underlying cause is vector drift. This article explains what vector drift is, why it appears in production RAG systems, and how to design drift-resilient architectures using Azure-native patterns.
What Is Vector Drift?
Vector drift occurs when embeddings stored in a vector index no longer accurately represent the semantic intent of incoming queries.
Because vector similarity search dep...
Updated Feb 06, 2026
Version 1.0
akankshaGahalout
Microsoft
Microsoft