Fix debug article for designer

Author: PeterCLu

articles/machine-learning/how-to-debug-pipelines.md

@@ -17,7 +17,7 @@ ms.date: 03/18/2020
 In this article, you learn how to debug and troubleshoot [machine learning pipelines](concept-ml-pipelines.md) in the [Azure Machine Learning SDK](https://docs.microsoft.com/python/api/overview/azure/ml/intro?view=azure-ml-py) and [Azure Machine Learning designer (preview)](https://docs.microsoft.com/azure/machine-learning/concept-designer). Information is provided on how to:
 
 * Debug using the Azure Machine Learning SDK
-* Debug using the Azure Machine Learning Designer
+* Debug using the Azure Machine Learning designer
 * Debug using Application Insights
 * Debug interactively using Visual Studio Code (VS Code) and the Python Tools for Visual Studio (PTVSD)
 
@@ -88,7 +88,7 @@ The table below provides information for different debug options for pipelines.
 | Library                    | Type   | Example                                                          | Destination                                  | Resources                                                                                                                                                                                                                                                                                                                    |
 |----------------------------|--------|------------------------------------------------------------------|----------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
 | Azure Machine Learning SDK | Metric | `run.log(name, val)`                                             | Azure Machine Learning Portal UI             | [How to track experiments](how-to-track-experiments.md#available-metrics-to-track)<br>[azureml.core.Run class](https://docs.microsoft.com/python/api/azureml-core/azureml.core.run(class)?view=experimental)                                                                                                                                                 |
-| Python printing/logging    | Log    | `print(val)`<br>`logging.info(message)`                          | Driver logs, Azure Machine Learning Designer | [How to track experiments](how-to-track-experiments.md#available-metrics-to-track)<br><br>[Python logging](https://docs.python.org/2/library/logging.html)                                                                                                                                                                       |
+| Python printing/logging    | Log    | `print(val)`<br>`logging.info(message)`                          | Driver logs, Azure Machine Learning designer | [How to track experiments](how-to-track-experiments.md#available-metrics-to-track)<br><br>[Python logging](https://docs.python.org/2/library/logging.html)                                                                                                                                                                       |
 | OpenCensus Python          | Log    | `logger.addHandler(AzureLogHandler())`<br>`logging.log(message)` | Application Insights - traces                | [Debug pipelines in Application Insights](how-to-debug-pipelines-application-insights.md)<br><br>[OpenCensus Azure Monitor Exporters](https://github.com/census-instrumentation/opencensus-python/tree/master/contrib/opencensus-ext-azure)<br>[Python logging cookbook](https://docs.python.org/3/howto/logging-cookbook.html) |
 
 #### Logging options example
@@ -133,7 +133,7 @@ For pipelines created in the designer, you can find the **log files** on either
 When you submit a pipeline run and stay in the authoring page, you can find the log files generated for each module.
 
 1. Select any module in the authoring canvas.
-1. In the right pane of the module, go to the  **Outputs+ogs** tab.
+1. In the right pane of the module, go to the  **Outputs+logs** tab.
 1. Select the log file `70_driver_log.txt`
 
     ![Authoring page module logs](./media/how-to-debug-pipelines/pipelinerun-05.png)
@@ -145,7 +145,7 @@ You can also find the log files of specific runs in the pipeline run detail page
 1. Select a pipeline run created in the designer.
     ![Pipeline run page](./media/how-to-debug-pipelines/pipelinerun-04.png)
 1. Select any module in the preview pane.
-1. In the right pane of the module, go to the  **Outputs+ogs** tab.
+1. In the right pane of the module, go to the  **Outputs+logs** tab.
 1. Select the log file `70_driver_log.txt`
 
 ## Debug and troubleshoot in Application Insights

articles/machine-learning/toc.yml

@@ -355,6 +355,7 @@
     - name: Trigger a pipeline
       href: how-to-trigger-published-pipeline.md
     - name: Debug & troubleshoot pipelines
+      displayName: designer
       href: how-to-debug-pipelines.md
     - name: Debug pipelines in Application Insights
       displayname: pipelines, log, monitor