Complete RAG Pipeline Observability

Real-time latency tracking across retrieval, augmentation, and generation stages. Monitor throughput (queries/sec), error rates by component, and p95/p99 latency percentiles.

Automated quality assessment using retrieval relevance scoring (NDCG, MRR), hallucination detection via source attribution verification, and answer completeness grading with LLM-as-judge.

Monitor query latency and indexing throughput for Pinecone, Weaviate, Qdrant, Chroma, Milvus, and pgvector. Track index size, memory usage, and shard distribution.

Track embedding model performance across OpenAI, Cohere, HuggingFace, and custom models. Monitor embedding latency, token throughput, and dimension consistency.

Granular cost breakdown per pipeline, per query, per token. Track embedding costs, LLM generation costs, vector store operations, and identify cost optimization opportunities.

Configure multi-channel alerts via PagerDuty, Slack, Email, and webhooks. Set thresholds for latency, error rates, quality scores, and cost spikes. Auto-scaling triggers for infrastructure.

Run controlled experiments on chunking strategies, embedding models, reranking algorithms, and prompt templates. Statistical significance testing with automatic winner selection.

Forecast infrastructure needs based on query volume trends, user growth patterns, and seasonal spikes. Recommend scaling actions before capacity limits are hit.

Compare fixed-size, semantic, recursive, and document-based chunking strategies. Measure impact on retrieval quality, latency, and token efficiency across different document types.

Version-controlled pipeline configurations with rollback capabilities. Track parameter changes, A/B test configurations, and maintain audit trails for compliance.

Track document ingestion paths, embedding generation flows, and retrieval patterns. Maintain compliance with data retention policies and access controls.

Build custom dashboards with drag-and-drop widgets. Monitor multiple pipelines in a single view. Export data to Grafana, Datadog, or custom analytics platforms.