OpenTelemetry4 articles

OpenTelemetry

Articles

LLM Observability and Tracing in Production: Comparing Langfuse, Arize Phoenix, LangSmith, and OpenLLMetry
LLM Observability and Tracing in Production: Comparing Langfuse, Arize Phoenix, LangSmith, and OpenLLMetry Moving language models from single-turn prompt wrappers into multi-agent architectures, recursive Retrieval-Augmented Generation (RAG) graphs, and autonomous tool-calling loops fundamentally changes system dynamics. LLM applications behave as distributed state machines where failure modes are rarely deterministic. Latency spikes can stem from vector store indexing bottlenecks, context wind
August 27, 20261 min
LLM Observability and Tracing in Production: Comparing Langfuse, Arize Phoenix, OpenInference, and Helicone Architecture, OpenTelemetry GenAI Semantic Conventions, Sampling Strategies, and Ingestion Economics
Monitoring distributed software architectures has traditionally relied on metrics, logs, and distributed traces centered around deterministic HTTP requests and database queries. As production architectures shift toward autonomous agents, multi-step retrieval-augmented generation (RAG) pipelines, and chain-of-thought inference loops, standard application performance monitoring (APM) tools struggle with the non-deterministic execution paths, large token payloads, and variable latencies inherent to
August 26, 20261 min
LLM Observability in Production: OpenTelemetry GenAI Semantic Conventions vs. OpenInference, Distributed Trace Propagation Across Multi-Agent Graphs, and High-Throughput Sampling Economics
Production large language model (LLM) architectures have transitioned from isolated completion endpoints to complex, distributed directed acyclic graphs (DAGs). Modern AI systems incorporate multi-agent orchestration, iterative tool execution, vector retrieval pipelines, and speculative decoding loops. Operating these workloads at enterprise scale exposes critical observability gaps that traditional application performance monitoring (APM) tools cannot address. Standard request-response APM metr
August 25, 20261 min
LLM Observability in Production: OpenTelemetry Semantic Conventions, Distributed Tracing, and Latency Profiling
LLM Observability in Production: OpenTelemetry Semantic Conventions, Distributed Tracing, and Latency Profiling Deploying large language models into production introduces failure modes that traditional application performance monitoring (APM) tools were never designed to diagnose. Standard web services fail with discrete HTTP error codes, predictable database timeouts, or memory leaks. In contrast, LLM applications fail through silent semantic drift, hallucinated tool parameters, unbounded prom
August 18, 20261 min

OpenTelemetry

LLM Observability and Tracing in Production: Comparing Langfuse, Arize Phoenix, LangSmith, and OpenLLMetry

LLM Observability and Tracing in Production: Comparing Langfuse, Arize Phoenix, OpenInference, and Helicone Architecture, OpenTelemetry GenAI Semantic Conventions, Sampling Strategies, and Ingestion Economics

LLM Observability in Production: OpenTelemetry GenAI Semantic Conventions vs. OpenInference, Distributed Trace Propagation Across Multi-Agent Graphs, and High-Throughput Sampling Economics

LLM Observability in Production: OpenTelemetry Semantic Conventions, Distributed Tracing, and Latency Profiling