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AWS sagemaker documentation change

Service: sagemaker · 2025-07-25 · Documentation low

File: sagemaker/latest/dg/mlflow-track-experiments.md

Summary

Added installation command for AWS MLflow plugin and updated documentation links

Security assessment

Updates installation instructions and references without modifying security-related content or addressing vulnerabilities

Diff

diff --git a/sagemaker/latest/dg/mlflow-track-experiments.md b/sagemaker/latest/dg/mlflow-track-experiments.md
index 4f611b728..9925634e0 100644
--- a//sagemaker/latest/dg/mlflow-track-experiments.md
+++ b//sagemaker/latest/dg/mlflow-track-experiments.md
@@ -11 +11 @@ The following page describes how to get started with the MLflow SDK and the AWS
-Amazon SageMaker AI uses an MLflow plugin to customize the behavior of the MLflow Python client and integrate AWS tooling. The AWS MLflow plugin authenticates API calls made with MLflow using [AWS Signature Version 4](https://docs.aws.amazon.com/AmazonS3/latest/API/sig-v4-authenticating-requests.html). The AWS MLflow plugin allows you to connect to your MLflow tracking server using the tracking server ARN. For more information about plugins, see [MLflow Plugins](https://mlflow.org/docs/latest/plugins.html) in the MLflow documentation.
+Amazon SageMaker AI uses an MLflow plugin to customize the behavior of the MLflow Python client and integrate AWS tooling. The AWS MLflow plugin authenticates API calls made with MLflow using [AWS Signature Version 4](https://docs.aws.amazon.com/AmazonS3/latest/API/sig-v4-authenticating-requests.html). The AWS MLflow plugin allows you to connect to your MLflow tracking server using the tracking server ARN. For more information about plugins, see [AWS MLflow plugin](https://pypi.org/project/sagemaker-mlflow/) and [MLflow plugins](https://mlflow.org/docs/latest/plugins.html).
@@ -22,0 +23,3 @@ Within your development environment, install both MLflow and the AWS MLflow plug
+    
+    pip install sagemaker-mlflow
+