AWS sagemaker documentation change

Service: sagemaker · 2026-07-01 · Documentation low

File: sagemaker/latest/dg/processing-job-frameworks-xgboost.md

Summary

Removed legacy SageMaker Python SDK v2 code example and v3 section header

Security assessment

Changes involve removing deprecated SDK implementation examples. No security-related content modifications, vulnerability disclosures, or security enhancements are present in the diff.

Diff

diff --git a/sagemaker/latest/dg/processing-job-frameworks-xgboost.md b/sagemaker/latest/dg/processing-job-frameworks-xgboost.md
index 9ce6ddf0c..b3883d660 100644
--- a//sagemaker/latest/dg/processing-job-frameworks-xgboost.md
+++ b//sagemaker/latest/dg/processing-job-frameworks-xgboost.md
@@ -13,3 +12,0 @@ The following code example shows how you can run your Processing job using a Doc
-SageMaker Python SDK v3
-    
-    
@@ -42,37 +38,0 @@ SageMaker Python SDK v3
-SageMaker Python SDK v2 (Legacy)
-    
-    
-    
-    from sagemaker.xgboost import XGBoostProcessor
-    from sagemaker.processing import ProcessingInput, ProcessingOutput
-    from sagemaker import get_execution_role
-    
-    #Initialize the XGBoostProcessor
-    xgb = XGBoostProcessor(
-        framework_version='1.2-2',
-        role=get_execution_role(),
-        instance_type='ml.m5.xlarge',
-        instance_count=1,
-        base_job_name='frameworkprocessor-XGB',
-    )
-    
-    #Run the processing job
-    xgb.run(
-        code='processing-script.py',
-        source_dir='scripts',
-        inputs=[
-            ProcessingInput(
-                input_name='data',
-                source=f's3://{BUCKET}/{S3_INPUT_PATH}',
-                destination='/opt/ml/processing/input/data'
-            )
-        ],
-        outputs=[
-            ProcessingOutput(
-                output_name='processed_data',
-                source='/opt/ml/processing/output/',
-                destination=f's3://{BUCKET}/{S3_OUTPUT_PATH}'
-            )
-        ]
-    )
-