AUTOMATION AND OPTIMIZATION OF THE SAP SOFTWARE INSTALLATION PROCESS IN CORPORATE WORKSTATIONS: IMPACTS ON SCALABILITY AND SECURITY

The automation and optimization of SAP software installation in corporate workstations are critical for enhancing scalability, security, and efficiency. Manual deployment processes are time-consuming, error-prone, and challenging to standardize in large-scale environments. This study explores automation tools such as Ansible, Terraform, and SCCM to streamline SAP deployment, reducing manual intervention and ensuring consistent configurations across multiple devices. The research also highlights the significance of security measures, including system hardening, least privilege policies, and multi-factor authentication, to mitigate potential vulnerabilities. A comprehensive literature review examines recent advancements in SAP deployment automation, emphasizing scalability and security. Studies demonstrate that integrating automation with cloud-based infrastructures improves deployment consistency, while compliance automation frameworks facilitate regulatory adherence. Additionally, AI-driven monitoring solutions enhance system reliability by predicting failures and optimizing resource allocation. The discussion highlights how automation tools significantly reduce deployment time while improving traceability and security. Standardized installation protocols prevent misconfigurations, and centralized deployment management minimizes human errors. Moreover, implementing security best practices safeguards SAP environments against cyber threats, ensuring compliance with regulatory requirements. This study concludes that automating SAP installation is a strategic necessity for organizations seeking operational efficiency, security, and scalability. Future research should explore AI-based automation to further refine installation processes and enhance proactive threat detection. By adopting automation and security best practices, organizations can achieve a more resilient and efficient SAP deployment framework.