The most effective corrective actions an LSA can recommend to address performance degradation from high data volume are application-centric. Archiving and purging resolved cases (B) directly reduces the size of the active dataset in transactional tables, which significantly improves query performance and processing times. This is a standard Pega best practice. Concurrently, ensuring critical tables are properly indexed (D) is essential. As data volume grows, unindexed or poorly indexed queries become a primary bottleneck. An LSA uses tools like the Performance Analyzer (PAL) to identify slow queries and creates database indexes on properties to optimize data retrieval for reports, UI displays, and background processing.

A. Implement horizontal and vertical database partitioning strategies and replication to distribute the load effectively. This is a database infrastructure-level activity, typically managed by a Database Administrator (DBA), not a direct application-level change implemented by an LSA.

C. Schedule regular database defragmentation sessions in collaboration with the Database Administrator. While beneficial for database health, defragmentation is a routine maintenance task for a DBA and is less impactful for this specific problem than directly reducing and optimizing access to the data.

1. Archiving and Purging (Supports Option B): Pega Academy

Lead System Architect (Pega Infinity '23) course

"Data Management" module. This module details the process of using the case archival and purge wizard to move resolved case data from primary transactional tables to an archive

directly addressing performance issues caused by large data volumes.

2. Database Indexing (Supports Option D): Pega Community

"Creating a custom index." This document explains how LSAs can create single or composite indexes on properties directly from the property rule form in Dev Studio to improve the performance of database queries

especially for reports.

3. Performance Best Practices (Supports B & D): Pega Community

"Performance guidance for Pega Platform." This guide emphasizes that managing data growth through purging and archiving

and ensuring proper database indexing

are two fundamental strategies for maintaining application performance. It distinguishes these application-level tasks from underlying database administration.

4. LSA Responsibilities (General Support): Pega Academy

Lead System Architect (Pega Infinity '23) course

"Pega's Class Structure" module

"Property Optimization" lesson. This lesson describes the LSA's responsibility to optimize properties by creating indexes to improve report and query performance

reinforcing that this is a core LSA task.