AWS sagemaker documentation change
Summary
Added deprecation notice for Amazon SageMaker Debugger (closing to new customers after 6/30/26) and removed SageMaker Python SDK v2 examples
Security assessment
The change announces service deprecation without mentioning security vulnerabilities. Removal of legacy SDK examples doesn't indicate security fixes. No evidence of security incidents or vulnerabilities addressed.
Diff
diff --git a/sagemaker/latest/dg/debugger-built-in-actions.md b/sagemaker/latest/dg/debugger-built-in-actions.md index ec82e033c..2c98d35f4 100644 --- a//sagemaker/latest/dg/debugger-built-in-actions.md +++ b//sagemaker/latest/dg/debugger-built-in-actions.md @@ -10,0 +11,4 @@ Set up Amazon SNS, create an SMDebugRules topic, and subscribe to the topicSet u +###### 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). + @@ -165,3 +168,0 @@ If you want to assign all of the three built-in actions to a single rule, config -SageMaker Python SDK v3 - - @@ -194,29 +194,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - - from sagemaker.debugger import Rule, rule_configs - - # Configure an action list object for Debugger rules - actions = rule_configs.ActionList( - rule_configs.StopTraining(), - rule_configs.Email("[email protected]"), - rule_configs.SMS("+1234567890") - ) - - # Configure rules for debugging with the actions parameter - rules = [ - Rule.sagemaker( - base_config=rule_configs.built_in_rule(), # Required - rule_parameters={"paramter_key": value }, # Optional - actions=actions - ) - ] - - estimator = Estimator( - ... - rules = rules - ) - - estimator.fit(wait=False) - @@ -227,3 +198,0 @@ If you want to assign the built-in actions to be triggered at different threshol -SageMaker Python SDK v3 - - @@ -275,48 +243,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - - from sagemaker.debugger import Rule, rule_configs - import time - - base_job_name_prefix= 'smdebug-stalled-demo-' + str(int(time.time())) - - # Configure an action object for StopTraining - action_stop_training = rule_configs.ActionList( - rule_configs.StopTraining() - ) - - # Configure an action object for Email - action_email = rule_configs.ActionList( - rule_configs.Email("[email protected]") - ) - - # Configure a rule with the Email built-in action to trigger if a training job stalls for 60 seconds - stalled_training_job_rule_email = Rule.sagemaker( - base_config=rule_configs.stalled_training_rule(), - rule_parameters={ - "threshold": "60", - "training_job_name_prefix": base_job_name_prefix - }, - actions=action_email - ) - stalled_training_job_rule_text.name="StalledTrainingJobRuleEmail" - - # Configure a rule with the StopTraining built-in action to trigger if a training job stalls for 120 seconds - stalled_training_job_rule = Rule.sagemaker( - base_config=rule_configs.stalled_training_rule(), - rule_parameters={ - "threshold": "120", - "training_job_name_prefix": base_job_name_prefix - }, - actions=action_stop_training - ) - stalled_training_job_rule.name="StalledTrainingJobRuleStopTraining" - - estimator = Estimator( - ... - rules = [stalled_training_job_rule_email, stalled_training_job_rule] - ) - - estimator.fit(wait=False) -