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1 change: 1 addition & 0 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -73,6 +73,7 @@ Now, you need to decide where to export the traces to.
## ⏫ Supported (and tested) destinations

- [x] Traceloop
- [x] Dynatrace
- [x] Datadog
- [x] New Relic
- [x] Honeycomb
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15 changes: 14 additions & 1 deletion docs/python-sdk/exporting.mdx
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@@ -1,6 +1,6 @@
---
title: "Exporting your Traces"
description: "Connect to any observability platform - Traceloop, Datadog, Honeycomb, and others"
description: "Connect to any observability platform - Traceloop, Dynatrace, Datadog, Honeycomb, and others"
---

Since Traceloop SDK is using OpenTelemetry under the hood, you can see everything
Expand All @@ -20,6 +20,19 @@ If you're calling a vector DB, or any other external service or database, you'll

</Accordion>

<Accordion title="Dynatrace">
Analyze all collected LLM traces within Dynatrace by using the native OpenTelemetry ingest endpoint of your Dynatrace environment.

Go to your Dynatrace environment and create a new access token under **Manage Access Tokens**.
The access token needs the following permission scopes that allow the ingest of OpenTelemetry spans, metrics and logs (openTelemetryTrace.ingest, metrics.ingest, logs.ingest).

Set `TRACELOOP_BASE_URL` environment variable to the URL of your Dynatrace OpenTelemetry ingest endpoint (e.g.: TRACELOOP_BASE_URL=https:\<YOUR_ENV>.live.dynatrace.com\api\v2\otlp).
Set the `TRACELOOP_HEADERS` environment variable to include your previously created access token (e.g.: TRACELOOP_HEADERS=Authorization=Api-Token%20<YOUR_ACCESS_TOKEN>).

Done! All the exported spans along with their span attributes will show up within the Dynatrace trace view.

</Accordion>

<Accordion title="Datadog">
With datadog, there are 2 options - you can either export directly to a Datadog Agent in your cluster, or through an OpenTelemetry Collector (which requires that you deploy one in your cluster).

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