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ease
features
design
support

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Description

Phoenix serves as a comprehensive open-source observability toolkit tailored for experimentation, evaluation, and troubleshooting purposes. It empowers AI engineers and data scientists to swiftly visualize their datasets, assess performance metrics, identify problems, and export relevant data for enhancements. Developed by Arize AI, the creators of a leading AI observability platform, alongside a dedicated group of core contributors, Phoenix is compatible with OpenTelemetry and OpenInference instrumentation standards. The primary package is known as arize-phoenix, and several auxiliary packages cater to specialized applications. Furthermore, our semantic layer enhances LLM telemetry within OpenTelemetry, facilitating the automatic instrumentation of widely-used packages. This versatile library supports tracing for AI applications, allowing for both manual instrumentation and seamless integrations with tools like LlamaIndex, Langchain, and OpenAI. By employing LLM tracing, Phoenix meticulously logs the routes taken by requests as they navigate through various stages or components of an LLM application, thus providing a clearer understanding of system performance and potential bottlenecks. Ultimately, Phoenix aims to streamline the development process, enabling users to maximize the efficiency and reliability of their AI solutions.

Description

It aids in collecting timing information essential for diagnosing latency issues within service architectures. Its functionalities encompass both the gathering and retrieval of this data. When you have a trace ID from a log, you can easily navigate directly to it. If you don't have a trace ID, queries can be made using various parameters such as service names, operation titles, tags, and duration. Additionally, notable data is summarized, including the proportion of time spent on each service and the success or failure of operations. The Zipkin user interface also features a dependency diagram that illustrates the volume of traced requests processed by each application. This visualization can be instrumental in recognizing overall patterns, including error trajectories and interactions with outdated services. Overall, this tool not only simplifies the troubleshooting process but also enhances the understanding of service interactions within complex architectures.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

GitHub
Amazon Bedrock
Apache Cassandra
Apache Kafka
Arize AI
Codestral
Codestral Mamba
Databricks
Haystack
JupyterLab
LangChain
Le Chat
Mathstral
Ministral 3B
Mistral Large
Mixtral 8x22B
NetScaler
OpenAI
Pixtral Large
Slack

Integrations

GitHub
Amazon Bedrock
Apache Cassandra
Apache Kafka
Arize AI
Codestral
Codestral Mamba
Databricks
Haystack
JupyterLab
LangChain
Le Chat
Mathstral
Ministral 3B
Mistral Large
Mixtral 8x22B
NetScaler
OpenAI
Pixtral Large
Slack

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Arize AI

Country

United States

Website

docs.arize.com/phoenix

Vendor Details

Company Name

Zipkin

Website

zipkin.io

Product Features

Application Performance Monitoring (APM)

Baseline Manager
Diagnostic Tools
Full Transaction Diagnostics
Performance Control
Resource Management
Root-Cause Diagnosis
Server Performance
Trace Individual Transactions

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