# Implementing LLM Observability at Honeycomb ## Company Background and Initial Implementation Honeycomb, an observability company, implemented a natural language querying interface for their product in May 2023. The initial release was successful, solving approximately 80% of their use cases and creating a strong marketing moment. However, the real challenges emerged during the iteration phase, particularly in addressing the remaining 20% of use cases that were crucial for their paying customers. ## Challenges in Production - Initial deployment was relatively straightforward - Post-deployment challenges ## Observability Implementation ### Comprehensive Data Capture - Captured extensive data points including: ### Technical Architecture - Implemented distributed tracing - Used OpenTelemetry for instrumentation ### Monitoring and Analysis - End-to-end user experience monitoring - Detailed error tracking and grouping - Dimension-based analysis capabilities - Real-time monitoring of success/failure rates - Ability to isolate specific problem instances ## Implementation Results and Benefits ### Business Impacts - Improved product retention rates - Higher conversion rates to paid tiers - Enhanced sales team efficiency ### Operational Improvements - Established continuous improvement flywheel - Better problem isolation and resolution - Improved ability to prevent regressions ## Best Practices and Future Developments ### Current Best Practices - Implement comprehensive observability from the start - Capture all possible data points - Use distributed tracing for system understanding - Monitor end-user experience, not just technical metrics - Establish clear feedback loops for improvements ### Future Developments - OpenTelemetry project developments - Community-driven best practices ## Technical Implementation Details - Distributed tracing architecture - RAG pipeline monitoring ## Lessons Learned - Traditional software engineering tools are insufficient for LLM systems - Comprehensive observability is crucial for long-term reliability - Real-world behavior tracking is essential for improvement - Continuous monitoring and iteration are key to success - Understanding the full context of each request is vital - Integration of multiple system components requires detailed tracking