Network automation for zero-based provisioning, simulation, testing, and policy-compliant optimization

Aims: To evaluate the effectiveness of an Automated Provisioning System in financial data centers, focusing on time efficiency, error reduction, and user satisfaction compared to manual provisioning. The study also aims to align automation benefits with UN Sustainable Development Goals (SDGs), particularly in promoting resilient infrastructure and sustainable IT practices. Methodology: Using a mixed-methods approach, the research combines quantitative metrics (time/error rates) with qualitative feedback from IT engineers via Likert-scale surveys. A Django-Python-based automation system was tested in a financial data center in a third-world country, featuring Zero-Touch Provisioning (ZTP), configuration templating, simulation, testing, and policy-compliance checks. Results: Results demonstrate a 91.67% reduction in provisioning time (5 vs. 60 minutes per device manually) and complete elimination of configuration errors. User surveys revealed high satisfaction (mean scores: 4.2–4.8/5), particularly for simplified device configuration (4.8 ± 0.45) and productivity gains (4.6 ± 0.55). The system’s scalability allowed simultaneous configuration of 12 devices unachievable manually. While the findings underscore automation’s potential to align with UN Sustainable Development Goals (e.g., resilient infrastructure), minor reliability concerns (SD: 1.3 for stability metrics) indicate areas for refinement. Conclusion: The study concludes that automated provisioning significantly enhances operational efficiency in financial institutions but recommends further improvements in system robustness, training, and security frameworks for broader adoption.