The details view for runs was updated to better align with the data returned and viewing patterns. Summary tables of run metrics and options used are separated into their own view called Summary which is the default landing view when you click on a run. If you are documenting the objective function in your output, then a table summarizing the objective function for the run will be displayed as well.

The input and output tabs have been updated with more intuitive controls for managing table and raw data views and visualizations if they exist as well.

Additional views include a new Metadata view which displays a variety of information related to the run like duration, type, queuing, which version and instance were used, and so forth. The run status has been pulled out of the metadata view and displayed in the header so you can easily view the status of a run no matter which tab view is active.

Then there is a tab for viewing run logs, ensemble analysis details (if it’s an ensemble run), and series data charts if they exist (in the Analysis tab). You can navigate the different views by clicking the tabs in the header or you can use the left and right arrows in the page footer to navigate between the views.

And you can continue to edit the run, download the full input and output files, share views, or create a new run or clone the run you’re viewing using the action buttons in the header.

When defining managed options for your model with the app manifest, you now have the ability to set a display name for the option. Before the actual option’s name would be the value that was displayed, but sometimes internal model options do not always translate to the most user-friendly names in a UI.

To define a display name for an option, you just add a display_name property in the ui definition block, like so:

- name: model.constraints.disable.maximumstops
  option_type: bool
  default: false
  required: false
  ui:
    display_name: Disable maximum stops

Then, when the option is loaded in Console, the name for the option field will be the display_name value rather than the name value.

You can read more about the display_name option in the UI section of the managed options docs.

You can now delete shadown and switchback tests directly from Console using the UI. On any experiment details view, click the Edit button in the header, then delete in the lower right, and then finally confirm the delete action.

When you delete a shadow test, all of the associated shadow runs are deleted as well. However, baseline runs are left in place as those runs are not tied to the experiment. Deleting a switchback test will not affect any of the runs associated with a switchback test, however, the switchback test information will be removed from those runs.

Note that once the experiment and its associated runs or run data has been deleted they cannot be recovered.

You now have the ability to delete runs in Console. On the run details view, click the “Edit” button in the header, and then click the “Delete” button in the lower right. A confirmation message will appear; click “Delete run” to delete the run. Note that once the run is deleted it cannot be recovered.

The ability to clone ensemble definitions has been added to Console. If you go to any existing ensemble definition and click the create button, there will be an option to clone that definition.

Clicking the clone button will take you to the create ensemble definition view with the fields pre-filled with the values from the ensemble definition that is being cloned. Once the cloned create ensemble definition view has loaded, you can further edit the new definition as needed.

The flow for creating a new app in Nextmv Console has been updated with a user-friendly walk-through that helps you get your app connected to your model. It closely follows the flow of the new user on-boarding screens for repeated use. Also, at anytime you can close the walk-through screens and go directly to your app.

The ID of the input input_id used for a scenario test run has been added to the scenario test result view’s pivot table. You can now use inputs as a basis for comparison and analysis in a scenario test result.