[Performance Optimization] A company is implementing field-level auditing in their application. What two scenarios can affect the field-level…

Field-level auditing can introduce performance overhead. The two primary factors affecting its performance are the scope and frequency of the audit triggers. Auditing a large number of fields (scope) increases the processing required for every case save operation, as the system must check each audited field for changes. Auditing fields that are modified frequently (frequency) results in a high volume of write operations to the history tables in the database, increasing I/O load and database storage consumption. Both scenarios can significantly degrade application performance if not managed carefully.

B. The application is hosted on a high-performance server.

This is a mitigating factor. A high-performance server helps handle the load generated by auditing but is not a scenario that negatively affects the feature itself.

C. The application has a lot of users accessing it.

This is too general. The direct performance impact comes from the specific action of modifying audited data, not just the number of users.

1. Pega Community

"Best practices for field-level auditing": This official Pega article explicitly advises on performance. It states

"Limit the number of fields that you audit" and "Avoid auditing fields that change frequently

such as counters." This directly supports options A and D as scenarios that affect the feature's performance.

Reference: Pega Community > Pega Platform > Data management and integration > Best practices for field-level auditing.

2. Pega Platform Documentation

"Data audit policy": The official documentation on creating audit policies includes performance considerations. It states

"Auditing data can impact system performance. To minimize the impact

audit only the data that you need." This principle underlies the reasoning for selecting options A and D

as both represent scenarios where auditing is not minimal.

Reference: Pega Platform 8.8 Documentation > Case management > Auditing case changes > Data audit policy.