Integrating Langtrace with Honeycomb: A Quick Guide

By: Jay Thakrar (Head of Product)

Understanding how an LLM behaves within an application is paramount, particularly given the nondeterministic outcomes of LLMs. As a result, observability into an LLM stack is mandatory. Today, we’re excited to announce that Langtrace can easily be integrated into Honeycomb, a leading observability platform for understanding and troubleshooting complex systems. In this blog post, we’ll walk you through the steps to integrate Langtrace with Honeycomb.

Prerequisites

• You will need a Honeycomb account with a valid API key
• Note: the Honeycomb API key should have the necessary permissions to create datasets and ingest traces

Steps

• Install the Honeycomb OpenTelemetry Python distribution package
• Install the Langtrace Python SDK and initialize the SDK in your terminal
• Note: don’t forget to input your Honeycomb API key into your app configuration — this will direct the traces from Langtrace to your Honeycomb dashboard.
• Start visualizing high cardinality traces on Honeycomb; it’s that simple!

Additional resources:

1. For a detailed walk-through on how to integrate Langtrace into Honeycomb, be sure to check out Langtrace’s documentation
2. Honeycomb website: https://www.honeycomb.io/
3. Langtrace website: https://langtrace.ai/
4. Langtrace SDK: https://pypi.org/project/langtrace-python-sdk/

We’d love to hear from you.

We’d love to hear your feedback, Langtrace! We invite you to join our community on Discord or reach out at support@langtrace.ai and share your experiences, insights, and suggestions. Together, we can continue to set new standards of observability in LLM development.

Happy tracing!