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Overview

SentryMetrics extends FrameProcessorMetrics to provide performance monitoring integration with Sentry. It tracks Time to First Byte (TTFB) and processing duration metrics for frame processors, enabling real-time performance monitoring and error tracking for your Pipecat applications.

Sentry Metrics API Reference

Pipecat’s API methods for Sentry metrics integration

Example Implementation

Browse examples using Sentry metrics

Sentry Documentation

Official Sentry Python SDK documentation

Sentry Platform

Access performance monitoring and error tracking

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Installation

To use Sentry analytics services, install the required dependencies: 
pip install "pipecat-ai[sentry]"

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Prerequisites

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Sentry Account Setup

Before using Sentry metrics services, you need:
  1. Sentry Account: Sign up at Sentry Platform
  2. Project Setup: Create a project and obtain your DSN
  3. SDK Initialization: Configure Sentry SDK in your application
  4. Metrics Configuration: Set up performance monitoring and error tracking

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Required Configuration

  • Sentry DSN: Your project’s Data Source Name for authentication
  • Traces Sample Rate: Configure performance monitoring sampling
  • SDK Initialization: Initialize Sentry before using metrics

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Key Features

  • Performance Monitoring: Track TTFB and processing duration metrics
  • Error Tracking: Automatic error capture and reporting
  • Frame Processor Metrics: Monitor individual processor performance
  • Real-time Analytics: Live performance data and alerting
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