Infor LN Performance Tuning Guide
Performance tuning Infor LN requires understanding the full technology stack: the database layer (Oracle or SQL Server), the BShell application server, the web UI delivery layer, and the batch processing infrastructure. Each layer can become a bottleneck, and symptoms in one layer often have root causes in another. This guide provides a systematic approach to diagnosing and resolving LN performance issues across all layers.
Database Performance Optimization
The database is the most common performance bottleneck in LN environments. LN generates complex queries through its session framework, and without proper indexing, these queries result in full table scans on million-row transaction tables. Database optimization for LN requires understanding LN's query patterns, maintaining statistics and indexes, and configuring the database engine specifically for LN's mixed workload of interactive queries and batch processing.
- Analyze top SQL statements by execution time and resource consumption using database monitoring tools
- Create indexes on columns used in LN session filters, sorts, and join conditions for frequently accessed tables
- Maintain database statistics with weekly updates to ensure the query optimizer makes correct decisions
- Configure database memory allocation to balance between LN's interactive queries and batch processing needs
Application Server and Session Tuning
The BShell application server hosts user sessions and executes business logic. Performance issues at this layer manifest as slow session opens, delayed calculations, and timeout errors. Key tuning parameters include the number of BShell server processes, memory allocation per process, and session timeout settings. Monitor server process utilization to determine whether adding capacity or optimizing session logic provides better return.
- Size the number of BShell server processes based on peak concurrent users plus a 20% buffer
- Configure memory limits per BShell process to prevent individual sessions from consuming excessive resources
- Set session timeout values that balance user convenience with resource reclamation for inactive sessions
- Monitor BShell process CPU and memory utilization to detect sessions with runaway resource consumption
Performance Monitoring and Baseline Management
Effective performance management requires continuous monitoring and baseline comparison. Establish baselines for key metrics: session open time, common query execution time, batch job duration, and web response time. Track these metrics weekly and investigate deviations exceeding 15%. Common causes of gradual degradation include data growth without corresponding index updates, statistics staleness, and log file accumulation consuming disk I/O.
- Establish performance baselines for the top 20 sessions and 10 batch jobs by execution time
- Monitor weekly performance trends and investigate deviations exceeding 15% from baseline values
- Review database growth rates monthly and plan storage expansion and index maintenance accordingly
- Schedule quarterly performance tuning reviews that compare current metrics to baselines and industry benchmarks
Improve LN performance—our performance engineers diagnose and resolve bottlenecks across the entire stack.
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