Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with re…
---
name: phoenix-observability
description: Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [Observability, Phoenix, Arize, Tracing, Evaluation, Monitoring, LLM Ops, OpenTelemetry]
dependencies: [arize-phoenix>=12.0.0]
---
# Phoenix - AI Observability Platform
Open-source AI observability and evaluation platform for LLM applications with tracing, evaluation, datasets, experiments, and real-time monitoring.
## When to use Phoenix
**Use Phoenix when:**
- Debugging LLM application issues with detailed traces
- Running systematic evaluations on datasets
- Monitoring production LLM systems in real-time
- Building experiment pipelines for prompt/model comparison
- Self-hosted observability without vendor lock-in
**Key features:**
- **Tracing**: OpenTelemetry-based trace collection for any LLM framework… load the full skill through Skill Me