AWS nova documentation change
Summary
Added AWS CLI implementation guide for MLflow integration and changed 'Supervised fine-tuning (SFT)' to 'Direct Preference Optimization (DPO)'.
Security assessment
New content provides operational guidance for MLflow setup without modifying security controls. The CLI example shows standard resource creation without security configurations. Algorithm name change doesn't impact security posture.
Diff
diff --git a/nova/latest/userguide/nova-model-monitor.md b/nova/latest/userguide/nova-model-monitor.md index 97c04be55..c987afead 100644 --- a//nova/latest/userguide/nova-model-monitor.md +++ b//nova/latest/userguide/nova-model-monitor.md @@ -102,0 +103,16 @@ MLFlow integration is already built into the SageMaker Studio UI experience. Whe +### Submitting a job via the AWSAWS CLI + +If you use the AWS AWS CLI, you must create an MLflow app and pass it as an input to the training job API request. + + + mlflow_app_name="<enter your MLflow app name>" + role_arn="<enter your role ARN>" + bucket_name="<enter your bucket name>" + region="<enter your region>" + + mlflow_app_arn=$(aws sagemaker create-mlflow-app \ + --name $mlflow_app_name \ + --artifact-store-uri "s3://$bucket_name" \ + --role-arn $role_arn \ + --region $region) + @@ -199 +215 @@ To use the Amazon Web Services Documentation, Javascript must be enabled. Please -Supervised fine-tuning (SFT) +Direct Preference Optimization (DPO)