Observing .NET RAG Systems: OpenTelemetry, Latency, and Cost
Learn OpenTelemetry RAG .NET tracing to connect retrieval, generation, latency, and cost boundaries with privacy-minimizing telemetry and evaluation signals.
Explore AI development for software engineers, including GitHub Copilot CLI workflows, Model Context Protocol servers, and Microsoft Agent Framework patterns.
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Learn OpenTelemetry RAG .NET tracing to connect retrieval, generation, latency, and cost boundaries with privacy-minimizing telemetry and evaluation signals.
Build a trustworthy RAG golden dataset in .NET with versioned evidence, synthetic-case review, human sentinel calibration, and drift-driven refreshes.
Learn RAG evaluation metrics in .NET with Precision@K, Recall@K, MRR, nDCG, groundedness, and answer relevance for clearer, repeatable offline RAG diagnostics.
Learn RAG query transformation in .NET through baseline retrieval, HyDE, step-back abstraction, decomposition, candidate merging, and retrieval evaluation.
See how semantic reranking for RAG in .NET applies Azure AI Search semantic ranking after retrieval, with configuration, scores, captions, and limits.
Learn how hybrid search RAG .NET combines lexical BM25 and dense vector candidates in one Azure AI Search request with reciprocal rank fusion.