Tag: #langfuse

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• Self-Hosting Langfuse — Deployment Paths, Secrets, and What Catches You on First Boot

  Running Langfuse yourself means standing up two containers and four datastores at once. Working from the official documentation, this post lays out the docker compose path and the Helm chart path, which secrets you have

  2026-08-14 · 9 min read #observability#langfuse#self-hosting#docker-compose#kubernetes

• When Traces Become Cost — Retention, Sampling, and Masking in Langfuse

  Tracing feels free at low traffic and then comes back as storage cost and a privacy problem. This post splits the points where volume turns into cost into four, confirms from the official documentation that sampling deci

  2026-08-14 · 9 min read #observability#langfuse#cost#sampling#data-retention

• Langfuse SDK Instrumentation — What Is Captured Automatically and What You Add by Hand

  Creating traces is not about installing an SDK, it is about drawing boundaries. Working from the Langfuse Python SDK v4, this post lays out what the decorator, the context manager, and manual observation creation each do

  2026-08-14 · 8 min read #observability#langfuse#llm-tracing#instrumentation#opentelemetry

• Why Langfuse Puts Traces in ClickHouse — How the Storage Layer Splits the Work

  The first surprise when you self-host Langfuse is that there is not one datastore but four. ClickHouse, Postgres, Redis, and object storage each take a different share. Working from the official documentation, this post

  2026-08-14 · 10 min read #observability#langfuse#clickhouse#architecture#postgres

• The Langfuse Tracing Data Model — How Trace, Observation, and Score Hold One Execution

  Looking at the Langfuse UI first tells you nothing about what you are looking at. This post starts from the shape of the data Langfuse collects. What a trace groups, what separates a span from a generation from an event,

  2026-08-14 · 8 min read #observability#langfuse#llm-tracing#data-modeling#opentelemetry

• After You Have Collected It — Langfuse Dashboards, the Metrics API, and Scores on Traces

  Collecting traces and getting answers out of them are different jobs. This post lays out which metric axes Langfuse offers and which dimensions you have to slice them by, then walks the Metrics API v2 query structure as

  2026-08-14 · 9 min read #observability#langfuse#llm-evaluation#metrics-api#dashboard

• LLM Observability & Prompt Tools 2026 — Helicone / LangSmith / Langfuse / Braintrust / Athina / Comet Opik / Portkey Deep Dive ♪ Listenable

  The 2026 LLM ops map. Helicone (YC) · LangSmith (LangChain) · Langfuse (open source, Series A) · W&B Weave · Arize Phoenix · Braintrust · Athina · Comet Opik (released March 2025) · Vellum · PromptHub · Portkey AI Gatewa

  2026-05-16 · 22 min read #llm-observability#prompt-engineering#helicone#langsmith#langchain

• LLM Evaluation & Observability: Eval Harness, LLM-as-Judge, Tracing, Regression Prevention (2025)

  Claiming a new model "seems better" is not science. The 1 failure mode of 2025 LLM products is "not measuring". Eval harness design, LLM-as-judge pitfalls and calibration, 3-layer observability (Trace/Span/Metric), produ

  2026-04-15 · 11 min read #llm-eval#observability#llm-judge#distributed-tracing#langsmith

• Comparing LLM Production Monitoring Platforms: A Practical Operations Guide for LangSmith, LangFuse, and Arize Phoenix ♪ Listenable

  A comprehensive comparison guide of three LLM production monitoring platforms (LangSmith, LangFuse, Arize Phoenix). Covers trace collection, prompt version management, evaluation pipelines, cost monitoring, quality dashb

  2026-03-09 · 23 min read #ai-platform#llm-monitoring#langsmith#langfuse#arize