Our software engineers have developed an easy-to-use script that will allow us to assess the accuracy of the estimated runtime for your most time-critical workflows. Collecting runtime estimation data will also allow our data scientists and engineers to improve Automic’s runtime estimation accuracy, allowing you to schedule and complete your time-critical jobs on-time.

Follow the instructions below to export data from your five most business and time critical workflows in an easy to review CSV format. Once you approve the extracted data, send it over. The data will be analyzed internally, however it will not contain sensitive information, and will not be shared with outside parties or customers.

Installation instructions:
  1. Access client 0 of the AE and modify in UC_SYSTEM_SETTINGS
  2. Set SQLVAR_INTERNAL value to "YES"
  3. Set SQLVAR_MAX_ROWS value to "6000"
  4. Save the changes and disconnect from client 0
  5. Connect to a client, which contains desired workflow history
  6. Import the UC4-objects from the provided xml-file
  8. Enter data in the prompt:
    • workflow names
    • OS agent
    • login of the OS agent
    • filepath to a csv-file
  9. Submit the task
  10. Collect the two CSV files from the selected OS agent
    (default names are jobp_overview.csv and jobp_details.csv)
  11. Login and upload the two CSV files.
Large prediction error values indicate poor runtime predictions. Here you can see runtime estimation for Workflow objects is poor, compared with File Transfer objects.