The increasing complexity, scale, and diversity of today’s enterprise network infrastructures demand more efficient, agile, and error-free management approaches. As organizations strive to meet these demands, network automation has emerged as an increasingly critical strategy. However, not all automation approaches are created equal. While many organizations still rely on traditional scripting for network automation, more advanced methodologies like intent-based data model driven automation have emerged, offering significant advantages in managing modern networks.
The limitations of traditional scripting
For years, network engineers have leveraged scripts to automate repetitive tasks and configurations. While scripting has undoubtedly improved efficiency compared to manual processes, it comes with inherent limitations. As networks grow, maintaining and updating scripts becomes increasingly complex and time-consuming, creating scalability issues. Scripts often work at a low level, requiring detailed knowledge of device-specific commands and syntax. This low-level approach is also error-prone, as even small mistakes in scripts can lead to significant network disruptions. Furthermore, scripts typically don’t account for the dynamic nature of modern networks or easily adapt to changes in network topology or vendor equipment, limiting their adaptability to evolving network environments.
