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Traceloop’s OpenLLMetry is an open source project that allows you to easily start monitoring and debugging the execution of your LLM app.
Traceloop’s non-intrusive instrumentation combined with Portkey’s intelligent gateway provides comprehensive observability without modifying your application code, while adding routing intelligence, caching, and failover capabilities.

Why Traceloop + Portkey?

Non-Intrusive Monitoring

Automatic instrumentation without changing your application code

OpenTelemetry Native

Built on industry-standard OpenTelemetry for maximum compatibility

Flexible Export Options

Send traces to Portkey or any OpenTelemetry-compatible backend

Enhanced Intelligence

Portkey adds gateway features like caching, fallbacks, and load balancing

Quick Start

Prerequisites

  • Python
  • Portkey account with API key
  • OpenAI API key (or add it to Model Catalog)

Step 1: Install Dependencies

Install the required packages for Traceloop and Portkey integration:

Step 2: Initialize Traceloop

Configure Traceloop to send traces to Portkey’s OpenTelemetry endpoint:

Step 3: Configure Portkey Gateway

Set up the OpenAI client to use Portkey’s intelligent gateway:

Step 4: Make Instrumented LLM Calls

Your LLM calls are now automatically traced by Traceloop and enhanced by Portkey:

Complete Example

Here’s a full example bringing everything together:

Next Steps

Configure Gateway

Set up intelligent routing, fallbacks, and caching

Model Catalog

Manage AI providers, credentials, and model access centrally

View Analytics

Analyze costs, performance, and usage patterns

Set Up Alerts

Configure alerts for anomalies and performance issues

See Your Traces in Action

Once configured, navigate to the Portkey dashboard to see your Traceloop instrumentation combined with gateway intelligence:
OpenTelemetry traces in Portkey
Last modified on February 27, 2026