Summary

The logs analysis page should offer the possibility for the user to delete the deployed ML jobs associated with the current space and source.

Rationale

It is important that the user can delete the ML jobs for several reasons:

• Since the ML jobs used for log analysis can use up valuable cluster resources, it might become necessary or economical for the user to delete the jobs.
• An updated version of Kibana might offer new or improved ML job configurations. Since most job parameters can not be changed, there should be a way to delete and recreate the jobs.
• The job and datafeed configurations might have become inconsistent due to various reasons such as data loss, manipulation or deletion of the jobs via the ML UI or source configuration changes. In all of these cases there should be a way to delete the potentially dysfunctional jobs and replace them with consistently configured jobs.

Acceptance Criteria

• The log analysis results page contains a UI element that indicates the overall status of the log analysis jobs.
• If the status is nominal, it has a neutral to positive appearance and offers at least the following pieces of information about the deployed jobs:
  • The index pattern used in the job config.
  • The timestamp field used in the job config.
• If the status is inconsistent, it has an appearance that indicates a warning and, in addition to the nominal information above, displays the reason for the warning:
  • The index pattern or timestamp field differ from the current source configuration.
  • The job revision is older than the revision shipped with the current Kibana version.
  • The job or datafeed are not open and started respectively.
  • The job or datafeed do not exist.
  • Or any other reason...
• To avoid cluttering the UI the information beyond the overall status can be put into a popover that is only displayed after a user action (e.g. click on the status indicator).
• If the status is inconsistent, the popover contains a call to action that navigates to a reset page, which in turn...
  • warns about the loss of result data when the jobs are deleted.
  • offers an unambiguous way for the user to confirm the deletion of the jobs (e.g. by typing a phrase).
  • perform the deletion after user confirmation.
  • display the progress and outcome of the deletion.
  • offers a way to navigate to the setup screen after performing the deletion.
  • offers a way to return to the results page without performing the deletion.

Mockups

Next step would be to include a warning when chaning the settings

...and a toast message indicating that a new ML job has been created