Forward Networks enables customers to perform queries against the model. And it overlays other types of data, such network performance monitoring, in order to facilitate troubleshooting. The snapshot process (collecting and processing the data) can take several hours in a large enterprise network and might be conducted, for example, a couple of times a day. So, the model is current, but not real-time.
Asperitas uses an open-source framework called EVE-NG (emulated virtual environment – next generation) to reverse engineer the network. Wheeler explains if enterprise network engineers wanted to create a digital twin using EVE-NG, they would have to take on the coding work required to build the virtual network and would also need to constantly update it to reflect changes to the network.
Wheeler adds that deploying digital twin requires a significant effort, both in terms of complexity and cost. And it is typically limited to modeling the impact of a change involving a single component from a single vendor. Or to a specific part of the network, such as a campus, says Zimmerman.
Even within a campus environment, Zimmerman has identified three levels of digital twins: The first level is network configuration and parameter/policy validation; the second level is single vendor equipment replacement or upgrade; and the third level is multiple vendor migration or vendor replacement.
The future of digital twins in networking
Gartner points out that “enterprise IT leaders continue to face a combination of challenges: increasing network complexity, heightened cybersecurity risk, and a shortage of skilled personnel. In this context, enterprise network digital twins are emerging as a tool to support network resilience and operations planning.”
But that won’t happen overnight. Gartner expects that in the next 3-5 years, digital twins will be used to model parts of campus networks, and within the next 10 years they will expand to the entire network.
