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Turn off Debugger - Amazon SageMaker AI

Turn off Debugger

Note

After careful consideration, we have made the decision to close new customer access to Amazon Sagemaker Debugger, effective 7/30/26. 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.

If you want to completely turn off Debugger, do one of the following:

  • Before starting a training job, do the following:

    To stop both monitoring and profiling, include the disable_profiler parameter to your estimator and set it to True.

    Warning

    If you disable it, you won't be able to view the comprehensive Studio Debugger insights dashboard and the autogenerated profiling report.

    To stop debugging, set the debugger_hook_config parameter to False.

    Warning

    If you disable it, you won't be able to collect output tensors and cannot debug your model parameters.

    estimator=Estimator(
    ...
    disable_profiler=True
    debugger_hook_config=False
)

    For more information about the Debugger-specific parameters, see SageMaker AI Estimator in the Amazon SageMaker Python SDK.

  • While a training job is running, do the following:

    To disable both monitoring and profiling while your training job is running, use the following estimator classmethod:

    estimator.disable_profiling()

    To disable framework profiling only and keep system monitoring, use the update_profiler method:

    estimator.update_profiler(disable_framework_metrics=true)

    For more information about the estimator extension methods, see the estimator.disable_profiling and estimator.update_profiler classmethods in the Amazon SageMaker Python SDK documentation.