Network professionals are increasingly familiar with digital twin technology and the benefits it can bring to network environments. Some of those benefits include end-to-end network visibility and improved training.
A digital twin network is a virtual replica of the physical network. Network professionals can use digital twins to aid in network design, lifecycle management and security, among other use cases.
According to an Internet Research Task Force (IRTF) draft, "Digital Twin Network: Concepts and Reference Architecture," released in October 2022 as a work in progress, digital twins could become an indispensable element of networking, creating a path toward more interactive and proactive networks. For example, network teams can use digital twins to pre-test a network change or troubleshoot a fix without negatively affecting the actual network. They can also use digital twin data to analyze the environment and improve network operations and workflows.
"Such virtual representation of the network is meant to be used to analyze, diagnose, emulate and then control the physical network based on data, models and interfaces," the IRTF draft said.
Components of digital twin networks
Digital twin networks rely on the interworking of different components to function. According to the IRTF working draft, digital twin networks include four main components:
- Data. Digital twins rely on both historical and real-time data to simulate a network environment. This data is stored in a data repository that acts as a single source of truth.
- Models. A model is the representation of a physical network. It collects data from sources and studies the environment to create a virtual simulation.
- Interfaces. Digital twins use interfaces to communicate among the digital twin, physical infrastructure and applications. These interfaces collect data and deliver requests.
- Mapping. The mapping process identifies the digital twin and its corresponding network elements. Mapping provides the necessary visibility and analysis into both environments.
Together, these elements create a virtual representation that provides network teams with valuable insights into the entire network. Ideally, digital twins move beyond more static simulations, using real-time data to enable automation and create a more intelligent, self-healing network.
Because a digital twin network gleans data from the physical network via mapping and interfaces, it sees the environment end to end. This insight is especially important for network teams that want -- and need -- improved network visibility and management, according to "End-to-end Networking Visibility and Management," an April 2023 report from TechTarget's Enterprise Strategy Group (ESG).
Digital twins and network visibility
In an August 2022 survey, ESG asked 339 North American IT and networking professionals about the importance of visibility into their network environments. Of the respondents, 68% said end-to-end visibility was very important, with another 13% saying it was critical. When asked why they need that visibility, respondents cited the following reasons:
- A complete view of all network assets.
- Risk mitigation when making changes.
- Visibility over remote workers.
While network visibility software offers one approach, it's often difficult for network teams to find a single tool that offers the end-to-end visibility they want, ESG said. Digital twin networks could act as another option to achieve comprehensive visibility and management. Because digital twins constantly use mapping, they stay updated about the status of the network and its various elements, according to the IRTF draft.
"Such mappings provide a good visibility of actual status, making the digital twin suitable to analyze and understand what is going on in the physical network," the IRTF draft said. "It also allows the digital twin to optimize the performance and maintenance of the physical network."
Benefits of digital twin networks
The benefit of increased network visibility with digital twin networks flows into other advantages, such as device discovery and inventory, network visualization and network maintenance. Below are some other benefits of digital twin networks.
Understand network behavior
Increased network visibility also means improved decision-making using the data analysis inherent to digital twins. According to the IRTF draft, digital twin networks are better able to predict and reproduce network behaviors, due to data processing and AI integration.
Improved network training
Both ESG and the IRTF draft said digital twin networks can aid teams in training. The ability to run changes or processes in a simulated environment enables network and security staff to gain experience with network operations tasks, threat detection and troubleshooting -- without the fear of causing a network outage or vulnerability. Teams might also feel more comfortable trying out new technologies, such as AI and machine learning, because they can test in a more controlled environment.
Security and compliance
Digital twin networks use high amounts of simulated data compared to real network data that falls under stricter compliance and privacy requirements. This factor can help minimize the risk of compromised data or security vulnerabilities.
Awareness of digital twin networks grows
Familiarity with digital twin technology is growing among network professionals, according to ESG. As teams investigate digital twin networks for their businesses, they should evaluate the benefits and use cases that apply to their network environments.