Skill UI

A comprehensive guide to diagnosing and fixing performance bottlenecks when using Qdrant. Covers optimizing slow uploads, resolving stuck optimizers, and tuning HNSW parameters, including best practices for sharding, bulk loading, and multi-tenant indexing to ensure efficient vector search performance.

This skill integrates LangChain 1.0 and LangGraph 1.0 into standard OpenTelemetry (OTEL) backends (e.g., Jaeger, Honeycomb, Tempo). It solves critical observability gaps by ensuring correct prompt content capture, propagating spans across complex subgraphs, and providing five LLM-specific Service Level Objectives (SLOs) like latency and cost. Ideal for multi-tenant, compliance-sensitive, or existing OTEL stack environments where LangSmith is unsuitable.