On Demand Schedules

On Demand Schedules are used to trigger the rendering of publications, alerts, and subscriptions. This improves system performance by triggering the scheduled event, rather than running a schedule to check whether or not the trigger condition has been met.

When the on demand schedules are triggered for a given data model, all on demand publication, alert, and subscription schedules associated with that model will run. On Demand Schedules can be triggered either when the underlying data model is reprocessed, or via an API call.

There are 3 methods for triggering on demand schedules:

  1. Use the API call to trigger on demand schedules.
  2. When a cube source is updated, all on demand schedules associated with the cube will be triggered.
  3. When performing data prep in Pyramid via Model, connect the On Demand node to the Master Flow.

Pyramid On Demand Node

Connect the On Demand node to the Master Flow to trigger on demand schedules associated with the data model. Whenever the model is reprocessed, the On Demand node will trigger all corresponding on demand schedules.

Configure the On Demand Node

  1. Connect the 'Pyramid On Demand' node to the Master Flow anywhere after the Data Model node.
  2. Configure the node's properties (see below).

You'll next need to set the relevant publication, alert, and subscription schedules to "on demand".

On Demand Properties

Click on the Pyramid On Demand node to show its properties in the Properties panel.

Display Name

By default, the node's display name is 'Pyramid On Demand 1'. Any subsequent data flow nodes are named according to this naming convention, with the appropriate numeric suffix, e.g. 'Pyramid On Demand 2', 'Pyramid On Demand 3', etc.

You can change the data flow node name from directly from this field.


You have the option to add a description to the Pyramid On Demand node; this can be a useful way of documenting the node for yourself and other users.

Select Model

From the Select Model drop-down, navigate the content tree to find and select the relevant data model. Each On Demand node can be assigned to a single data model; to enable on demand scheduling for content from multiple data sources contained in the current Master Flow, add a separate On Demand node for each relevant data model.