Scheduling and running AI Workbench notebooks

In AI Workbench, you create and run AI models using Jupyter notebooks. To run a model, or set a schedule for running it, you use the scheduling tab in AI Workbench. This page also shows the run history, with details of the run and output files you can download. In the metadata section at the top of the notebook page, you can set up email notifications when the notebook runs.

scheduling and running AI Workbench machine learning notebooks in BlueConic CDP

Setting a schedule for AI Workbench notebooks

To access the schedule settings for AI Workbench, open the Schedule and run history panel for a notebook. In the Setup section, activate the Enable scheduled execution checkbox to set a schedule to run the notebook.

To do a single run of a notebook, click the [Run now] button under Run history.

To set up a schedule for running it, click the configuration icon (cog wheel) and set the time and frequency for running the notebook. Save your settings.

how do I schedule and run an AI Workbench Jupyter notebook in BlueConic?

First, choose the type of schedule you want. There are four options:

  • Every X minutes
  • Number of times per day
  • Days of the week
  • Day of the month
  • Weekday of the month

Depending on the choice you make, you will have to fill in some extra data to complete the schedule.

Get notified when AI Workbench notebooks run 

At the top of the configuration page for AI notebooks, in the metadata section, you can request that BlueConic notify one or more email addresses when the notebook is run. 


You can choose to receive emails either each time it runs or only if it fails to run successfully. 


Running an AI Workbench notebook

Green arrows appear at the top of the Schedule and run history panel when a notebook Python kernel is scheduled to run, or enabled for scheduled execution. These arrows are grey if notebooks are not running or scheduled. We have collected tips and best practices for optimizing the performance of AI Workbench notebooks.

scheduling AI Workbench notebooks with green arrows in BlueConic

AI Workbench notebook status icons

In AI Workbench, each Jupyter notebook's icon shows that notebook's current status:

Scheduling status:  
If a note book is scheduled, the icon contains arrows.
Learn more about scheduling and running AI Workbench notebooks.
AI Workbench status icon image for BlueConic machine learning notebooksor AI Workbench status icon image for BlueConic machine learning notebooks
If a note book is not scheduled, it shows the Python logo. AI Workbench status icon image for BlueConic Python machine learning notebooks or AI Workbench status icon image for BlueConic Python machine learning notebooks
Editing status:  
If a notebook is being edited, it shows a green icon:  
A notebook's icon shows green arrows if the notebook is being edited and also being scheduled. scheduled AI Workbench notebooks in Jupyter in BlueConic
A notebook's icon shows the green Python logo if it is being edited but is not scheduled. green Python icon in Jupyter noteook in BlueConic
Notebooks that are not being edited have grey icons. grey inactive icon for Jupyter notebooks in BlueConicor notebook with grey icon in BlueConic AI Workbench
Execution status:
A notebook icon is green when the notebook kernel is running -- which is when the notebook is being edited (or was edited in the past minute), or if the notebook is executed via the Run now command or on a schedule.
Notebooks executed on a schedule show animated green arrows. circular green arrows in Jupyter notebook AI Workbench

Notebooks executed via the "Run now" command or via one or more cells being executed show the green Python logo.

running Jupyter notebooks in BlueConic AI Workbench

If a notebook's kernel is not running, its icon is grey.

grey kernel icon in BlueConic AI Workbench orJupyter notebook AI Workbench grey icons

Resource usage

Your instance of AI Workbench uses a shared resource pool with other BlueConic customers. Note that BlueConic does not share data across customers; you only share resources such as memory and computing power. If your AI Workbench use cases require additional resources, let us know via We'll discuss your requirements and upgrade your subscription as necessary.