Engineering Resources
In-depth, engineering-focused articles on LLM observability, evaluation, and tooling. These guides compare Langfuse with other platforms and walk through migrations so you can choose the right setup for your stack.
Comparisons
- Arize AX Alternative? Langfuse vs. Arize AI and Arize Phoenix for LLM Observability
This article compares Langfuse and Arize AI and Arize Phoenix for LLM observability, analytics, evaluations, testing, and annotation.
Last updated Jul 7, 2026
- Braintrust Data Alternatives? The best LLMOps platform?
his article compares Langfuse and Braintrust for LLM observability, analytics, evaluations, and engineering workflows.
Last updated Jul 7, 2026
- Galileo AI Alternatives? The best LLMOps platform?
This article compares Langfuse and Galileo AI for LLM observability, analytics, evaluations, testing, and annotation.
Last updated Jun 23, 2026
- Langfuse vs. Datadog for LLM Observability & Agent Tracing
Compare Langfuse and Datadog LLM Observability: tracing, evals, prompt management, pricing, self-hosting, and how teams run both together via OpenTelemetry.
Last updated Jul 15, 2026
- LangSmith Alternative? Langfuse vs. LangSmith for LLM Observability
Langfuse is the open-source LangSmith alternative. Updated July 2026 comparison of open source, self-hosting, storage architecture, evals, alerting, and pricing.
Last updated Jul 15, 2026
Migrations
- How to Migrate from Helicone to Langfuse
Step-by-step guide to migrate your prompt management and observability from Helicone to Langfuse, covering prompt templates, variables, versioning, and tracing.
Last updated Jun 23, 2026
- Migrate from Arize Phoenix to Langfuse
Step-by-step guide to migrating from Arize Phoenix to Langfuse: keep your OpenInference instrumentation, repoint one OTLP endpoint, and map datasets, experiments, and prompts.
Last updated Jul 3, 2026
- Migrate from Braintrust to Langfuse
Step-by-step guide to migrate from Braintrust to Langfuse: swap SDK instrumentation, export datasets via API, keep autoevals scorers, and re-run experiments.
Last updated Jul 15, 2026
Articles
- 10 code evaluator examples for AI application evaluation
Ten copy-paste code evaluators for LLM applications: output validation, PII screening, RAG citation checks, numeric tolerance, refusal detection, and more.
Last updated Jul 6, 2026
- AI agent evaluation: trajectory, tool calls, and task completion
AI agent evaluation explained: how to measure trajectory, tool use, task completion, and multi-turn quality, with offline and online evaluation patterns.
Last updated Jul 15, 2026
- Chatbot analytics: analyzing what users ask your AI chatbot
Four working patterns for chatbot analytics on LLM traces: offline intent classification, LLM-as-a-judge detection, score dashboards, and agent-driven analysis.
Last updated Jul 15, 2026
- How to build an LLM evaluation strategy
How to build an LLM evaluation strategy: quality dimensions from failure modes, evaluator selection, CI release gates, production monitoring, and human review.
Last updated Jul 15, 2026
- PII masking patterns for LLM applications
Where to mask PII in an LLM application: client-side SDK masking, server-side ingestion masking, gateway-level filtering, and detection with evaluators. Patterns and trade-offs.
Last updated Jul 6, 2026
- Tracing coding agents: Claude Code, Codex, Copilot & more
How to trace AI coding agents with Langfuse: Claude Code, OpenAI Codex, GitHub Copilot, Cursor, and five more. Setup patterns, cost tracking, and team governance.
Last updated Jul 3, 2026
- Use Langfuse from Go, Java, C#, and Ruby via OpenTelemetry
Langfuse works from any language with an OpenTelemetry SDK: point the OTLP exporter at the Langfuse endpoint. Setup for Go, Java, C#/.NET, and Ruby.
Last updated Jul 3, 2026
- What is an LLM gateway? When you need one (and when you don't)
An LLM gateway is a proxy layer between your application and model providers: one API, failover, caching, cost controls. How gateways work and how to pick one.
Last updated Jul 3, 2026
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