Phoenix
AI observability & evaluation: LLM tracing, evaluation, and RAG troubleshooting
Overview
Requirements
Recommended VPS
Hostinger · KVM 4
4 vCPU · 16384 MB · 200 GB
Hostinger · KVM 4
4 vCPU · 16384 MB · 200 GB
Hostinger · KVM 8
8 vCPU · 32256 MB · 400 GB
Affiliate disclosure
Docker Compose
# Generated by Run This Ai — docker-compose.yml
services:
phoenix:
image: arizephoenix/phoenix:latest
restart: unless-stopped
ports:
- 8080:8080
volumes:
- ./data/phoenix:/data
How to Install Phoenix using Docker Compose
Phoenix
Phoenix is an open-source AI observability platform designed for LLM tracing, evaluation, and RAG troubleshooting. It provides standard OpenTelemetry traces to monitor execution steps, calculate response metrics, and evaluate LLM output quality dynamically.
Prerequisites
- Docker installed (version 24.0+)
- Docker Compose (version 2.20+)
- At least 1GB RAM (2GB recommended)
Quick start with Docker
# Pull the image
docker pull arizephoenix/phoenix:latest
# Run the container
docker run -d --name phoenix -p 8080:8080 arizephoenix/phoenix:latestKey features
- Self-hosted and open source
- Docker-based deployment
- License: Apache-2.0
- Repository: https://github.com/Arize-AI/phoenix
- Docker image:
arizephoenix/phoenix:latest
Phoenix: Self-Hosted AI Observability & Evaluation Platform
Phoenix
Phoenix is an open-source AI observability platform designed for LLM tracing, evaluation, and RAG troubleshooting. It provides standard OpenTelemetry traces to monitor execution steps, calculate response metrics, and evaluate LLM output quality dynamically.
Key features
- Self-hosted and open source
- Docker-based deployment
- License: Apache-2.0
- Repository: https://github.com/Arize-AI/phoenix
- Docker image:
arizephoenix/phoenix:latest
What it's good for
Phoenix runs entirely on your own infrastructure — your data never leaves your server.
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