Performance Optimization and Scalability Assessment of Learning Management Systems Through Strategic Resource Augmentation

Mustika Kurnia Mayangsari, Teguh Junian Kuswanto, Sholahuddin Muhammad Irsyad, Wibowo Arninputranto, Dwi Sasmita Aji Pambudi, Adianto Adianto

Abstract


This research investigates the performance optimization and scalability of the Learning Management System (LMS) at Politeknik Perkapalan Negeri Surabaya (PPNS) through strategic resource augmentation. Initial diagnostic assessments identified a critical state of resource exhaustion. Where RAM utilization consistently reached 99%, Network File System (NFS) storage hit 95.38% capacity. These constraints induced a “memory thrashing” phenomenon and severe I/O wait bottlenecks, establishing a performance ceiling that impeded scalability during high-stakes academic events. To mitigate these issues, the infrastructure was upgraded by increasing RAM capacity to 223 GB and expanding storage to 12.9 TB. The efficacy of this intervention was validated using Apache JMeter to simulate a stress test with 1,000 concurrent virtual users. Empirical findings demonstrate a significant shift in the system’s operational baseline: average response times were reduced by 87.2% (from 4,850 ms to 620 ms), and throughput increased approximately seven-fold (from 12.5 to 85.2 requests per second). Additionally, the error rate dropped from 18.4% to a negligible 0.05%, while disk utilization stabilized at 44%. The results indicate that vertical scaling successfully recovered the system’s operational elasticity. However, for long-term sustainability, the institution is advised to transition toward horizontal scaling architectures and advanced caching mechanisms.

Keywords


Load Testing; Learning Management System; Performance Optimization; Resource Augmentation; Scalability Assessment

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DOI: https://doi.org/10.29100/jipi.v11i3.10074

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