Open the Amazon SageMaker Debugger Insights dashboard

In the SageMaker Debugger Insights dashboard in Studio Classic, you can see the compute resource utilization, resource utilization, and system bottleneck information of your training job that runs on Amazon EC2 instances in real time and after trainings

Note

The SageMaker Debugger Insights dashboard runs a Studio Classic application on an ml.m5.4xlarge instance to process and render the visualizations. Each SageMaker Debugger Insights tab runs one Studio Classic kernel session. Multiple kernel sessions for multiple SageMaker Debugger Insights tabs run on the single instance. When you close a SageMaker Debugger Insights tab, the corresponding kernel session is also closed. The Studio Classic application remains active and accrues charges for the ml.m5.4xlarge instance usage. For information about pricing, see the Amazon SageMaker AI Pricing page.

Important

When you are done using the SageMaker Debugger Insights dashboard, you must shut down the ml.m5.4xlarge instance to avoid accruing charges. For instructions on how to shut down the instance, see Shut down the Amazon SageMaker Debugger Insights instance.

To open the SageMaker Debugger Insights dashboard

1. On the Studio Classic Home page, choose Experiments in the left navigation pane.

2. Search your training job in the Experiments page. If your training job is set up with an Experiments run, the job should appear in the Experiments tab; if you didn't set up an Experiments run, the job should appear in the Unassigned runs tab.

3. Choose (click) the link of the training job name to see the job details.

4. Under the OVERVIEW menu, choose Debuggger. This should show the following two sections.

   • In the Debugger rules section, you can browse the status of the Debugger built-in rules associated with the training job.

   • In the Debugger insights section, you can find links to open SageMaker Debugger Insights on the dashboard.

5. In the SageMaker Debugger Insights section, choose the link of the training job name to open the SageMaker Debugger Insights dashboard. This opens a Debug [your-training-job-name] window. In this window, Debugger provides an overview of the computational performance of your training job on Amazon EC2 instances and helps you identify issues in compute resource utilization.

You can also download an aggregated profiling report by adding the built-in ProfilerReport rule of SageMaker Debugger. For more information, see Configure Built-in Profiler Rules and Profiling Report Generated Using SageMaker Debugger.