Astra Schedule Help (7.5)

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Astra Schedule interface jobs can be configured to run in one of three modes: Batch (import and export), Realtime (import and export), or On-Demand (import only).

 

Batch

 

Batch mode is applicable to both import and export processes, and can be run manually at any time, or scheduled to run regularly, as often as needed. A batch job attempts to update or export all fields for all records for the appropriate term(s) and campus(es). For this reason, batch jobs are typically used for initial imports and when a more thorough update is desired that could potentially bog down a realtime process.

 

Realtime

 

Realtime mode varies slightly between import and export processes. The Astra Schedule application knows when a change is made in its database that should trigger an export. Identifying changes in the SIS database is slightly more challenging.

 

For realtime imports, Astra Schedule employs a separate realtime service that constantly watches the SIS database for changes to certain fields.

 

For realtime exports from Astra Schedule to the SIS, the system is immediately aware of changes that occur. Therefore, if a realtime job is created using an export configuration file, the Astra Schedule export service will export these changes (room assignments) every 30 seconds for those sections defined in the job.

 

On-Demand

 

On-Demand mode is applicable only for updates to existing sections in Astra Schedule. When On-Demand mode is selected for a job using an import configuration file, section record information is updated every time a section record detail is viewed, or when the optimizer is run. In other words, sections are updated at the time that details are required by a user.

NoteNOTE: On-Demand mode will only update section information if the record was edited in the SIS, and only for existing sections at the time that details are required. Therefore, sections edited in Astra Schedule but not in the SIS will not be changed, and new sections added to the SIS must be imported using a batch job before on-demand can take place.