docs: Add MLflow to tracing backends (#10697)

* docs: Add MLflow to tracing backends

Add MLflow section to the tracing documentation page alongside
Langfuse and Weights & Biases Weave. MLflow provides native tracing
support for Haystack via mlflow.haystack.autolog().

Co-Authored-By: Claude <noreply@anthropic.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

* comments

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>

---------

Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Bilge Yücel <bilgeyucel96@gmail.com>

Author: 3 people

docs-website/docs/development/tracing.mdx

@@ -126,6 +126,28 @@ Check out the component's [documentation page](../pipeline-components/connectors
 :::
 <ClickableImage src="/img/11cec4f-langfuse-generation-span.png" alt="Langfuse trace detail view showing generation span with input prompt, output, metadata, latency, and cost information for a language model call" />
 
+### MLflow
+
+[MLflow](https://mlflow.org/) is an open-source platform for managing the end-to-end machine learning and AI lifecycle. MLflow provides native tracing support for Haystack. Simply install MLflow and enable automatic tracing with a single line of code.
+
+```shell
+pip install mlflow
+```
+
+```python
+import mlflow
+
+mlflow.haystack.autolog()
+# Optionally set an experiment name
+mlflow.set_experiment("Haystack")
+```
+
+This automatically captures traces from all Haystack pipelines and components, including latencies, token usage, cost, and any exceptions.
+
+:::info
+Check out the [MLflow Haystack integration guide](https://haystack.deepset.ai/integrations/mlflow) for a full walkthrough with examples.
+:::
+
 ### Weights & Biases Weave
 
 The `WeaveConnector` component allows you to trace and visualize your pipeline execution in [Weights & Biases](https://wandb.ai/site/) framework.

docs-website/versioned_docs/version-2.25/development/tracing.mdx

@@ -126,6 +126,28 @@ Check out the component's [documentation page](../pipeline-components/connectors
 :::
 <ClickableImage src="/img/11cec4f-langfuse-generation-span.png" alt="Langfuse trace detail view showing generation span with input prompt, output, metadata, latency, and cost information for a language model call" />
 
+### MLflow
+
+[MLflow](https://mlflow.org/) is an open-source platform for managing the end-to-end machine learning and AI lifecycle. MLflow provides native tracing support for Haystack. Simply install MLflow and enable automatic tracing with a single line of code.
+
+```shell
+pip install mlflow
+```
+
+```python
+import mlflow
+
+mlflow.haystack.autolog()
+# Optionally set an experiment name
+mlflow.set_experiment("Haystack")
+```
+
+This automatically captures traces from all Haystack pipelines and components, including latencies, token usage, cost, and any exceptions.
+
+:::info
+Check out the [MLflow Haystack integration guide](https://haystack.deepset.ai/integrations/mlflow) for a full walkthrough with examples.
+:::
+
 ### Weights & Biases Weave
 
 The `WeaveConnector` component allows you to trace and visualize your pipeline execution in [Weights & Biases](https://wandb.ai/site/) framework.