A mid-sized company heavily relies on ServiceNow for incident management. They have a business rule that runs before insert on the Incident table. The rule dynamically sets the assignment group based on the category of the incident and the location of the caller. To determine the correct group, the script performs a GlideRecord query against a custom table called "u_group_mapping", which contains approximately 5000 records mapping category-location pairs to groups. During peak business hours, when many incidents are created simultaneously, the business rule causes significant delays and occasional timeouts, impacting user experience. The development team has been tasked with optimizing this business rule without changing its functionality. The current script structure is roughly:
(function executeRule(current, previous) {
var gr = new GlideRecord('u_group_mapping');
gr.addQuery('category', current.category);
gr.addQuery('location', current.caller_id.location);
gr.query();
if (gr.next()) {
current.assignment_group = gr.assignment_group;
}
})(current, previous);
The team wants to reduce the database access overhead. Which optimization technique should the developer implement?

Question

A mid-sized company heavily relies on ServiceNow for incident management. They have a business rule that runs before insert on the Incident table. The rule dynamically sets the assignment group based on the category of the incident and the location of the caller. To determine the correct group, the script performs a GlideRecord query against a custom table called "u_group_mapping", which contains approximately 5000 records mapping category-location pairs to groups. During peak business hours, when many incidents are created simultaneously, the business rule causes significant delays and occasional timeouts, impacting user experience. The development team has been tasked with optimizing this business rule without changing its functionality. The current script structure is roughly:
(function executeRule(current, previous) {
    var gr = new GlideRecord('u_group_mapping');
    gr.addQuery('category', current.category);
    gr.addQuery('location', current.caller_id.location);
    gr.query();
    if (gr.next()) {
        current.assignment_group = gr.assignment_group;
    }
})(current, previous);
The team wants to reduce the database access overhead. Which optimization technique should the developer implement?

Accepted Answer

Create a script include with a static variable to cache the mapping for the duration of the current transaction. Caching the mapping data in a static variable within a script include ensures that the GlideRecord query against the 5000-record custom table is executed only once per transaction, rather than on every incident creation. This drastically reduces database access overhead during peak hours, as subsequent invocations of the business rule within the same transaction reuse the cached results, eliminating redundant queries and preventing timeouts.

Answer

Use GlideAggregate to retrieve the count of matching groups

Answer

Store the mapping in a global script include variable that persists across sessions

Answer

Move the business rule to run after insert so it does not block the insert

SNOW-CAD Practice Question: Automating application logic with business rules and scripts

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