Regex Pre-Compiling for Multitenancy CPU Optimization, Reducing Memory and Costs

Authors: Pradeep Kumar

DOI: https://doi.org/10.5281/zenodo.14615442

Short DOI: https://doi.org/g8x3ph

Country: USA

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Abstract: SAP SuccessFactors Learning (SF Learning) is a cornerstone of corporate learning environments, offering scalable, customizable solutions to meet the diverse needs of organizations. However, the increasing complexity of maintaining multi-tenant systems, especially with extensive customizations, has raised concerns regarding performance, scalability, and maintenance overhead. This paper explores the potential for optimizing SF Learning's architecture by focusing on the pre-compilation of regular expressions (regex), which plays a significant role in performance enhancement within multi-tenant environments. By leveraging pre-compiled regex, organizations can optimize CPU usage, reduce memory consumption, and decrease operational costs while improving scalability. This approach ensures more efficient management of large-scale implementations, reduces the reliance on custom code, and enhances system reliability. The paper investigates how integrating native SAP resources and leveraging regex in a cloud-based architecture can streamline development and maintenance processes. Additionally, case studies from organizations that have reaped the benefits of such optimizations are presented, providing insights into real-world applications. Finally, the paper discusses future trends in SAP SF Learning architecture, with an emphasis on AI, machine learning, and deeper integrations with SAP’s other solutions, ensuring a holistic and sustainable approach to enterprise learning management.

Keywords: JVM, Apache Tomcat, Performance, Regex, Multitenancy

Paper Id: 231997

Published On: 2019-03-06

Published In: Volume 7, Issue 2, March-April 2019

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