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Arize Exporter

Arize provides observability platforms for AI applications through Phoenix (open-source) and Arize AX (enterprise). The Arize exporter sends AI traces using OpenTelemetry and OpenInference semantic conventions, compatible with any OpenTelemetry platform that supports OpenInference.

When to Use Arize​

Arize is ideal when you need:

  • OpenInference standards - Industry-standard semantic conventions for AI traces
  • Flexible deployment - Self-hosted Phoenix or managed Arize AX
  • OpenTelemetry compatibility - Works with any OTLP-compatible platform
  • Comprehensive AI observability - LLM traces, embeddings, and retrieval analytics
  • Open-source option - Full-featured local deployment with Phoenix

Installation​

npm install @mastra/arize

Configuration​

Phoenix Setup​

Phoenix is an open-source observability platform that can be self-hosted or used via Phoenix Cloud.

Prerequisites​

  1. Phoenix Instance: Deploy using Docker or sign up at Phoenix Cloud
  2. Endpoint: Your Phoenix endpoint URL (ends in /v1/traces)
  3. API Key: Optional for unauthenticated instances, required for Phoenix Cloud
  4. Environment Variables: Set your configuration
.env
PHOENIX_ENDPOINT=http://localhost:6006/v1/traces  # Or your Phoenix Cloud URL
PHOENIX_API_KEY=your-api-key  # Optional for local instances
PHOENIX_PROJECT_NAME=mastra-service  # Optional, defaults to 'mastra-service'

Basic Setup​

src/mastra/index.ts
import { Mastra } from "@mastra/core";
import { ArizeExporter } from "@mastra/arize";

export const mastra = new Mastra({
  observability: {
    configs: {
      arize: {
        serviceName: process.env.PHOENIX_PROJECT_NAME || "mastra-service",
        exporters: [
          new ArizeExporter({
            endpoint: process.env.PHOENIX_ENDPOINT!,
            apiKey: process.env.PHOENIX_API_KEY,
            projectName: process.env.PHOENIX_PROJECT_NAME,
          }),
        ],
      },
    },
  },
});
info

Quick Start with Docker

Test locally with an in-memory Phoenix instance:

docker run --pull=always -d --name arize-phoenix -p 6006:6006 \
  -e PHOENIX_SQL_DATABASE_URL="sqlite:///:memory:" \
  arizephoenix/phoenix:latest

Set PHOENIX_ENDPOINT=http://localhost:6006/v1/traces and run your Mastra agent to see traces at localhost:6006.

Arize AX Setup​

Arize AX is an enterprise observability platform with advanced features for production AI systems.

Prerequisites​

  1. Arize AX Account: Sign up at app.arize.com
  2. Space ID: Your organization's space identifier
  3. API Key: Generate in Arize AX settings
  4. Environment Variables: Set your credentials
.env
ARIZE_SPACE_ID=your-space-id
ARIZE_API_KEY=your-api-key
ARIZE_PROJECT_NAME=mastra-service  # Optional

Basic Setup​

src/mastra/index.ts
import { Mastra } from "@mastra/core";
import { ArizeExporter } from "@mastra/arize";

export const mastra = new Mastra({
  observability: {
    configs: {
      arize: {
        serviceName: process.env.ARIZE_PROJECT_NAME || "mastra-service",
        exporters: [
          new ArizeExporter({
            apiKey: process.env.ARIZE_API_KEY!,
            spaceId: process.env.ARIZE_SPACE_ID!,
            projectName: process.env.ARIZE_PROJECT_NAME,
          }),
        ],
      },
    },
  },
});

Configuration Options​

The Arize exporter supports advanced configuration for fine-tuning OpenTelemetry behavior:

Complete Configuration​

new ArizeExporter({
  // Phoenix Configuration
  endpoint: "https://your-collector.example.com/v1/traces", // Required for Phoenix

  // Arize AX Configuration
  spaceId: "your-space-id", // Required for Arize AX

  // Shared Configuration
  apiKey: "your-api-key", // Required for authenticated endpoints
  projectName: "mastra-service", // Optional project name

  // Optional OTLP settings
  headers: {
    "x-custom-header": "value", // Additional headers for OTLP requests
  },

  // Debug and performance tuning
  logLevel: "debug", // Logging: debug | info | warn | error
  batchSize: 512, // Batch size before exporting spans
  timeout: 30000, // Timeout in ms before exporting spans

  // Custom resource attributes
  resourceAttributes: {
    "deployment.environment": process.env.NODE_ENV,
    "service.version": process.env.APP_VERSION,
  },
});

Batch Processing Options​

Control how traces are batched and exported:

new ArizeExporter({
  endpoint: process.env.PHOENIX_ENDPOINT!,
  apiKey: process.env.PHOENIX_API_KEY,

  // Batch processing configuration
  batchSize: 512, // Number of spans to batch (default: 512)
  timeout: 30000, // Max time in ms to wait before export (default: 30000)
});

Resource Attributes​

Add custom attributes to all exported spans:

new ArizeExporter({
  endpoint: process.env.PHOENIX_ENDPOINT!,
  resourceAttributes: {
    "deployment.environment": process.env.NODE_ENV,
    "service.namespace": "production",
    "service.instance.id": process.env.HOSTNAME,
    "custom.attribute": "value",
  },
});

OpenInference Semantic Conventions​

This exporter implements the OpenInference Semantic Conventions for generative AI applications, providing standardized trace structure across different observability platforms.