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features
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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

Gain comprehensive insight into your cloud-native and distributed applications, encompassing everything from microservices to serverless setups, allowing for swift identification and resolution of underlying issues. Effortlessly integrate Application Performance Management (APM) to automatically detect anomalies, visualize service dependencies, and streamline the investigation of outliers and unusual behaviors. Enhance your application code with robust support for widely-used programming languages, OpenTelemetry, and distributed tracing methodologies. Recognize performance bottlenecks through automated, curated visual representations of all dependencies, which include cloud services, messaging systems, data storage, and third-party services along with their performance metrics. Investigate anomalies in detail, diving into transaction specifics and various metrics for a more profound analysis of your application’s performance. By employing these strategies, you can ensure that your services run optimally and deliver a superior user experience.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

OpenTelemetry
Python
AWS Lambda
Ansible
Arize AI
C
C++
CoLab
Codestral
Codestral Mamba
Conda
Java
JavaScript
Jenkins
Le Chat
Mistral 7B
Mistral NeMo
Node.js
Pixtral Large
Vercel

Integrations

OpenTelemetry
Python
AWS Lambda
Ansible
Arize AI
C
C++
CoLab
Codestral
Codestral Mamba
Conda
Java
JavaScript
Jenkins
Le Chat
Mistral 7B
Mistral NeMo
Node.js
Pixtral Large
Vercel

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$95 per month
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

Elastic

Country

United States

Website

www.elastic.co/observability/application-performance-monitoring

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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