AWS sagemaker documentation change

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

File: sagemaker/latest/dg/debugger-bring-your-own-container.md

Summary

Added deprecation notice and removed legacy SDK examples

Security assessment

Change adds Debugger deprecation notice and removes outdated code samples. No security-related content or vulnerabilities are referenced in the modifications.

Diff

diff --git a/sagemaker/latest/dg/debugger-bring-your-own-container.md b/sagemaker/latest/dg/debugger-bring-your-own-container.md
index 4f77c9bbd..bb4f819ca 100644
--- a//sagemaker/latest/dg/debugger-bring-your-own-container.md
+++ b//sagemaker/latest/dg/debugger-bring-your-own-container.md
@@ -10,0 +11,4 @@ Prepare to build a custom training containerRegister Debugger Hook to Your Train
+###### Note
+
+After careful consideration, we have made the decision to close new customer access to Amazon Sagemaker Debugger, effective 6/30/26. Existing customers can continue to use the service as normal. AWS continues to invest in security and availability improvements for Debugger, but we do not plan to introduce new features. For more information, see [Debugger availability change](./debugger-availability-change.html). 
+
@@ -181,3 +184,0 @@ After you build and push your docker container to Amazon ECR, configure a SageMa
-SageMaker Python SDK v3
-    
-    
@@ -215,32 +215,0 @@ SageMaker Python SDK v3
-SageMaker Python SDK v2 (Legacy)
-    
-    
-    
-    import sagemaker
-    from sagemaker.estimator import Estimator
-    from sagemaker.debugger import Rule, DebuggerHookConfig, CollectionConfig, rule_configs
-    
-    profiler_config=ProfilerConfig(...)
-    debugger_hook_config=DebuggerHookConfig(...)
-    rules=[
-        Rule.sagemaker(rule_configs.built_in_rule()),
-        ProfilerRule.sagemaker(rule_configs.BuiltInRule())
-    ]
-    
-    estimator=Estimator(
-        image_uri=byoc_image_uri,
-        entry_point="./debugger_custom_container_test_folder/your-training-script.py"
-        role=sagemaker.get_execution_role(),
-        base_job_name='debugger-custom-container-test',
-        instance_count=1,
-        instance_type='ml.p3.2xlarge',
-        
-        # Debugger-specific parameters
-        profiler_config=profiler_config,
-        debugger_hook_config=debugger_hook_config,
-        rules=rules
-    )
-    
-    # start training
-    estimator.fit()
-