Discover / LLM Ops & Observability

Phoenix

by Arize-aiPython

Open-source LLM tracing, evaluation, and observability platform.

Toolstable

Maturity: stable because 4y old, arize-phoenix-v19.11.0 released 4d ago. Derived from release and commit history, not a rating.

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Last commit
2026-08-03
License
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Market and trust evidence

Edition not yet matched

No exact skills.sh identity match is available for this repository. Repository adoption and freshness remain visible above; install momentum is not inferred.

Trust analysis is a screening signal, not a security warranty. Read the ranking and trust methodology.

In practice

Written by AI from this repository’s README · medium confidence

Debugging an LLM application means guessing what happened inside a chain with no trace or eval baseline.

Use it when

Use it when you want OpenTelemetry based traces plus datasets and experiments in one self hostable tool.

Not the right pick when

The README is thin on setup detail and points to external docs, so expect to leave the repo to configure it.

Capabilities

  • trace LLM application runtime with OpenTelemetry based instrumentation
  • evaluate response and retrieval quality with LLM based evals
  • create versioned datasets of examples
  • track and evaluate experiments
  • deployable via Docker, Helm or Kustomize

Cost: Free and open source

Install

Derived from the published package name in the repository, not from a model.

Video walkthroughs

Third-party YouTube uploads matched to this tool by title, channel and repository name on 2026-08-03. Not made, reviewed or endorsed by SkillPilot. View counts and publish months are as of the match date and the month is approximate. Nothing loads from YouTube until you press play.

What the repository ships

Ships CLAUDE.mdCursor rulesHas testsHas docsHas examplesDocker imageSecurity policyCI configured

Detected from the actual files in the repository root.

Latest release arize-phoenix-v19.11.0

Published 2026-07-30

19.11.0 (2026-07-30)

Features

  • add project evaluation metrics charts (#14481) (7ef4832)
  • evals: count subagent tool calls online (#14843) (819c09b)
  • project: defer metric chart loading and lift the chart selection cap (#14901) (b455a3f)
  • sandboxes: use Pydantic logo for Monty provider icon (#14900) (73abdaf)
  • show tool and tool call counts in LLM span card headers (#14841) (0be0c11), closes #14712
  • trace: pinned note-taking bar for span details (#14845) (de52ce8)
  • ui: move root-span scoping into the filter condition (#14599) (a4a2a78)

Bug Fixes

  • accept null provider in createModel and report the real conflict (#14847) (6cea2cf)
  • keep trace tree duration labels on a single line (#14849) (0a2587d)
  • Mobile responsive login page text (#14826) (12a20bb)
  • server: make the monty binary discoverable in Docker images (#14935) (e2feff5)
  • trace: put a copy button in the top right of every span card (#14814) (2074035)
  • ui: resolve span details project id from the span, not the route (#14917) (d070d62)

Documentation

  • add REST how-to for linking dataset examples to spans (#14810) (2b039ae)
  • move toxicity evaluator out of the legacy nav section (#14905) (0483806)
  • skills: weekly audit — 2026-07-29 (#14873) (f56e31b)

Tags

README

<p align="center">

<a target="_blank" href="https://phoenix.arize.com" style="background:none">

<img alt="phoenix banner" src="https://github.com/Arize-ai/phoenix-assets/blob/main/images/socal/github-large-banner-phoenix-v2.jpg?raw=true" width="auto" height="auto"></img>

</a>

<br/>

<br/>

<a href="https://arize.com/docs/phoenix/">

<img src="https://img.shields.io/static/v1?message=Docs&logo=data:image/png;base64,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&labelColor=grey&color=blue&logoColor=white&label=%20"/>

</a>

<a target="_blank" href="https://join.slack.com/t/arize-ai/shared_invite/zt-3r07iavnk-ammtATWSlF0pSrd1DsMW7g">

<img src="https://img.shields.io/static/v1?message=Community&logo=slack&labelColor=grey&color=blue&logoColor=white&label=%20"/>

</a>

<a target="_blank" href="https://bsky.app/profile/arize-phoenix.bsky.social">

<img src="https://img.shields.io/badge/-phoenix-blue.svg?color=blue&labelColor=gray&logo=bluesky">

</a>

<a target="_blank" href="https://x.com/ArizePhoenix">

<img src="https://img.shields.io/badge/-ArizePhoenix-blue.svg?color=blue&labelColor=gray&logo=x">

</a>

<a target="_blank" href="https://www.linkedin.com/showcase/113218220">

<img src="https://img.shields.io/badge/-ArizePhoenix-blue.svg?color=blue&labelColor=gray&logo=linkedin">

</a>

<a target="_blank" href="https://pypi.org/project/arize-phoenix/">

<img src="https://img.shields.io/pypi/v/arize-phoenix?color=blue">

</a>

<a target="_blank" href="https://anaconda.org/conda-forge/arize-phoenix">

<img src="https://img.shields.io/conda/vn/conda-forge/arize-phoenix.svg?color=blue">

</a>

<a target="_blank" href="https://pypi.org/project/arize-phoenix/">

<img src="https://img.shields.io/pypi/pyversions/arize-phoenix">

</a>

<a target="_blank" href="https://hub.docker.com/r/arizephoenix/phoenix/tags">

<img src="https://img.shields.io/docker/v/arizephoenix/phoenix?sort=semver&logo=docker&label=image&color=blue">

</a>

<a target="_blank" href="https://hub.docker.com/r/arizephoenix/phoenix-helm">

<img src="https://img.shields.io/badge/Helm-blue?style=flat&logo=helm&labelColor=grey"/>

</a>

<a target="_blank" href="https://arize.com/docs/phoenix/integrations/remote-mcp">

<img src="https://badge.mcpx.dev?status=on" title="MCP Enabled"/>

</a>

<a href="cursor://anysphere.cursor-deeplink/mcp/install?name=phoenix&config=eyJ1cmwiOiJodHRwOi8vbG9jYWxob3N0OjYwMDYvbWNwIn0%3D"><img src="https://cursor.com/deeplink/mcp-install-dark.svg" alt="Add Arize Phoenix MCP server to Cursor" height=20 /></a>

<img referrerpolicy="no-referrer-when-downgrade" src="https://static.scarf.sh/a.png?x-pxid=8e8e8b34-7900-43fa-a38f-1f070bd48c64&page=README.md" />

</p>

Phoenix is an open-source AI observability platform designed for experimentation, evaluation, and troubleshooting. It provides:

  • _Tracing_ - Trace your LLM application's runtime using OpenTelemetry-based instrumentation.
  • _Evaluation_ - Leverage LLMs to benchmark your application's performance using response and retrieval evals.
  • _Datasets_ - Create versioned datasets of examples for experimentation, evaluation, and fine-tuning.
  • _Experiments_ - Track and evaluate changes to prompts, LLMs, and retrieval.
  • _Playground_- Optimize prompts, compare models, adjust parameters, and replay traced LLM calls.
  • _Prompt Management_- Manage and test prompt changes systematically using version control, tagging, and experimentation.
  • _PXI (Phoenix Intelligence)_ - An AI engineering agent built into Phoenix for debugging traces, iterating on prompts, and navigating the product.
  • _Remote MCP Server_ - Connect Claude Code, Cursor, and other MCP clients directly to your Phoenix instance's /mcp endpoint to query traces, datasets, experiments, and more.

<p align="center">

<video src="https://storage.googleapis.com/arize-phoenix-assets/assets/videos/tracing_realtime.mp4" controls muted loop playsinline width="800"></video>

</p>

Phoenix is vendor and language agnostic with out-of-the-box support for popular frameworks (OpenAI Agents SDK, Claude Agent SDK, LangGraph, Vercel AI SDK, Mastra, CrewAI, LlamaIndex, DSPy) and LLM providers (OpenAI, Anthropic, Google GenAI, Google ADK, AWS Bedrock, OpenRouter, LiteLLM, and more). For details on auto-instrumentation, check out the OpenInference project.

Phoenix runs practically anywhere, including your local machine, a containerized deployment, or in the cloud. See Environments for a walkthrough of each option, or jump straight into the Tracing Quickstart.

Table of Contents

  • Run Locally
  • Trace Your Application
  • Deploy
  • Packages
  • Tracing Integrations
  • Sandboxes
  • For Humans and Coding Agents
  • Security & Privacy
  • Community

Run Locally

Install Phoenix via pip or conda and have a fully functional Phoenix. For all installation and hosting options, see the install guide.


pip install arize-phoenix
phoenix serve

Or run it with no install using uvx:


uvx arize-phoenix serve

Trace Your Application

The fastest way to send traces is to let your coding agent (Claude Code, Codex, Cursor, and others) instrument your app. From your project directory, run:


npx @arizeai/phoenix-cli setup
# or, with Phoenix installed: px setup

Setup detects your framework and LLM provider, installs the right OpenInference instrumentation, and wires up trace export. Prefer to wire it up in code? See the tracing documentation.

Deploy

Phoenix container images are available via Docker Hub and can be deployed using Docker or Kubernetes via the Helm chart.

For Docker Compose, Kubernetes/Helm, and other deployment options, see the self-hosting documentation.

<p align="center">

<a href="https://railway.app/template/PTHRoq?referralCode=Xe2txW"><img src="https://railway.com/button.svg" alt="Deploy on Railway" height="30"></a>

&nbsp;

<a href="https://render.com/deploy?repo=https://github.com/Arize-ai/phoenix"><img src="https://render.com/images/deploy-to-render-button.svg" alt="Deploy to Render" height="30"></a>

&nbsp;

<a href="https://deploy.cloud.run/?git_repo=https://github.com/Arize-ai/phoenix"><img src="https://deploy.cloud.run/button.svg" alt="Run on Google Cloud" height="30"></a>

&nbsp;

<a href="https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FArize-ai%2Fphoenix%2Fmain%2Fazuredeploy.json"><img src="https://aka.ms/deploytoazurebutton" alt="Deploy to Azure" height="30"></a>

&nbsp;

<a href="https://arize.com/docs/phoenix/self-hosting/deployment-options/aws-with-cloudformation"><img src="https://img.shields.io/badge/Deploy%20to-AWS-FF9900?logo=amazonwebservices&logoColor=white&labelColor=232F3E" alt="Deploy to AWS" height="30"></a>

</p>

[!NOTE]

The Google Cloud button builds Phoenix from source in Cloud Shell rather than deploying the prebuilt Docker Hub image. The Azure template serves plain HTTP (Azure Container Instances does not terminate TLS) — front it with a TLS proxy such as an Application Gateway before production use.

Packages

The arize-phoenix package includes the entire Phoenix platform. However, if you have deployed the Phoenix platform, there are lightweight Python sub-packages and TypeScript packages that can be used in conjunction with the platform.

Python Subpackages

| Package | Version & Docs | Description |

| --------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------ |

| arize-phoenix-otel | PyPI Version Docs | Provides a lightweight wrapper around OpenTelemetry primitives with Phoenix-aware defaults |

| arize-phoenix-client | PyPI Version [Docs](https://arize-phoenix.readthedocs.io/projects/client/

Truncated. Read the full README on GitHub ↗

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