---
type: concept
x-llmwiki:
  schemaVersion: "0.1"
  contentHash: 80e680dcb05c25666f2a073aeaa44ce28865bb2ec06148f5ce7d1f6e67d80d6c
  pageDirectory: concepts
  sources:
    - export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md
  confidence: 0.95
  provenanceState: extracted
  freshnessStatus: unverified
  aliases:
    - databricks-otlp-trace-endpoint
    - DOTE
  citations:
    - file: export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md
    - file: export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md
      start: 68
      end: 70
    - file: export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md
      start: 71
      end: 71
    - file: export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md
      start: 72
      end: 73
    - file: export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md
      start: 46
      end: 80
    - file: export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md
      start: 10
      end: 14
title: Databricks OTLP Trace Endpoint
description: The /api/2.0/otel/v1/traces endpoint that accepts OpenTelemetry traces via a BatchSpanProcessor and OTLPSpanExporter, routing them to a Unity Catalog table via the X-Databricks-UC-Table-Name header.
tags:
  - tracing
  - opentelemetry
  - databricks
  - api
timestamp: "2026-06-19T18:46:10.018Z"
---

# Databricks OTLP Trace Endpoint

The **Databricks OTLP Trace Endpoint** is an HTTP endpoint that accepts OpenTelemetry Protocol (OTLP) traces and stores them in [Unity Catalog](/concepts/unity-catalog.md), making them available alongside other [[MLflow Trace|MLflow Traces]]. It enables third-party observability tools, such as Langfuse, to send trace data directly to Databricks for centralized storage, querying, and governance. ^[export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md]

## Endpoint Details

The endpoint is located at:

```
{DATABRICKS_HOST}/api/2.0/otel/v1/traces
```

Traces are sent over HTTP using the OTLP protobuf format (`application/x-protobuf`). The endpoint is part of the Databricks [MLflow Tracing](/concepts/mlflow-tracing.md) infrastructure and requires the "OpenTelemetry on Databricks" preview to be enabled in the workspace. ^[export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md:68-70]

## Authentication

Each request must include an `Authorization` header with a Bearer token obtained from the Databricks workspace (for example, an API token). The token must have appropriate permissions to send traces to the target table. ^[export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md:71]

## Table Routing

A custom HTTP header `X-Databricks-UC-Table-Name` is used to route incoming spans to a specific Unity Catalog table. The value of this header is the full OTel spans table name returned by the `set_experiment_trace_location` API, which links an [MLflow Experiment](/concepts/mlflow-experiment.md) to a Unity Catalog [Catalog and Schema](/concepts/catalog-and-schema.md). ^[export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md:72-73]

## Usage

To send traces to the Databricks OTLP endpoint, an application must:

1. Install the OpenTelemetry SDK packages and the OTLP HTTP protobuf exporter.
2. Obtain the Databricks workspace host URL and a valid API token.
3. Link an MLflow experiment to a Unity Catalog [Catalog and Schema](/concepts/catalog-and-schema.md) using `mlflow.tracing.enablement.set_experiment_trace_location`, which returns the full OTel spans table name.
4. Configure an `OTLPSpanExporter` with the endpoint URL, authentication header, and the `X-Databricks-UC-Table-Name` header.
5. Attach the exporter to the application's TracerProvider (for example, via a BatchSpanProcessor).

Once set up, any OpenTelemetry spans generated by the application are forwarded to Databricks and stored in the designated Unity Catalog table. ^[export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md:46-80]

## Benefits

- Query and compare traces from different frameworks in a single place.
- Use Databricks SQL to analyze trace data at scale.
- Apply [Unity Catalog](/concepts/unity-catalog.md) governance, such as access controls and lineage, to all traces. ^[export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md:10-14]

## Related Concepts

- OpenTelemetry – The observability framework whose protocol the endpoint implements.
- OTLP – The OpenTelemetry Protocol used to send traces.
- [MLflow](/concepts/mlflow.md) – The platform that ingests and manages traces on Databricks.
- [[MLflow Trace|MLflow Traces]] – The trace data model used in MLflow experiments.
- [Unity Catalog](/concepts/unity-catalog.md) – The governance layer where traces are stored.
- Langfuse – A third-party tool that can export traces to the endpoint.
- Span – The fundamental unit of a trace.

## Sources

- export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md

# Citations

1. [export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md](/references/export-langfuse-traces-to-databricks-mlflow-databricks-on-aws-edce6b99.md)
2. [export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md:68-70](/references/export-langfuse-traces-to-databricks-mlflow-databricks-on-aws-edce6b99.md)
3. [export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md:71-71](/references/export-langfuse-traces-to-databricks-mlflow-databricks-on-aws-edce6b99.md)
4. [export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md:72-73](/references/export-langfuse-traces-to-databricks-mlflow-databricks-on-aws-edce6b99.md)
5. [export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md:46-80](/references/export-langfuse-traces-to-databricks-mlflow-databricks-on-aws-edce6b99.md)
6. [export-langfuse-traces-to-databricks-mlflow-databricks-on-aws.md:10-14](/references/export-langfuse-traces-to-databricks-mlflow-databricks-on-aws-edce6b99.md)
