How Network Digital Twins are Transforming IT Infrastructure

Network automation promises efficiency, but deploying changes without thorough testing can be risky. What if there was a better way?

Network automation has rapidly evolved, and professionals driving it are often top-tier network engineers mastering the art of coding. The professionals driving network automation are often the top network engineers within their organizations. However, most network engineers didn’t grow up learning how to code; it’s a new skill they’re working hard to master.

To innovate and refine their skills effectively, they require a safe testing environment - a "sandbox" - where they can experiment without fear of disrupting production networks.

Much like software engineers utilize DevOps platforms, today's network engineers need a robust NetDevOps platform.

This article explores how digital twins for networks are essential for enabling effective and safe network automation through robust network automation labs within a modern NetDevOps framework. We'll explore what a network digital twin is, how it enables safer automation, and how CloudMyLab’s solutions can help you embrace this transformation.

What are Network Digital Twins?

While the term has been somewhat overused in the industry, a network digital twin refers to a replica of network devices in a non-production (lab) environment. It's a virtual representation, mirroring how your physical infrastructure behaves.

If the physical network changes (for instance, new device configurations or varying traffic loads), the digital twin network can reflect those changes through telemetry data, ensuring an up-to-date representation. This live linkage is a key differentiator: unlike a static network simulation or emulation, which runs on fixed input parameters, a digital twin network is meant to be an evolving mirror of the network’s behavior and state.

Creating a digital twin, however, is far from a simple task. Networks are uniquely complex, and building a non-production replica requires meticulous planning and execution. The complexity and scale of a digital twin depend on several factors such as the goals of the project, the extent to which the network can be emulated, available resources, and the need for physical devices to fill in gaps where emulation is not possible.

Digital Twins vs. Traditional Network Emulation / Simulation

It's important to distinguish network digital twins from traditional lab simulators or emulators (like GNS3, EVE-NG, or vendor-specific tools). While both involve virtual network environments, a digital twin has a broader scope and a more dynamic connection to the real network.

Instead of running on predefined configurations like classic simulations, a digital twin incorporates real-time or near-real-time data from the live network. If link latencies change in production, the twin might ingest those updates to stay synchronized. Traditional simulators typically operate in isolation once set up.

Network emulation tools often focus on specific scenarios or network subsets, like labbing a routing protocol on a few virtual devices. A digital twin aims to model the network more holistically, potentially covering entire segments or the full infrastructure. It serves as an ongoing virtual proxy for network operations, not just a one-time test environment. While complexity means many twins are built incrementally today, the goal is an integrated model supporting planning, testing, and operational decisions.

Perhaps the most significant difference lies in the potential for a twin to integrate into closed-loop systems. Because it stays synced, automation tools could test changes on the twin before pushing them to production, conditional on the twin showing no issues.

Digital twins often achieve higher fidelity by using virtualized versions of actual device software or high-quality models, updated with real conditions. Emulators excel at control-plane accuracy but may abstract data-plane performance. Simulations might simplify protocol details. A digital twin aims to combine the flexibility of simulation with the realism derived from live network data and accurate device modeling.

The Importance of Digital Twins for Network Automation in Modern Network Engineering

A digital twin allows you to test and validate network changes and automation scripts before production implementation. This increases deployment confidence and minimizes the risk of misconfigurations leading to downtime. With a digital twin, you can innovate faster, explore new technologies confidently, and accelerate team learning without disrupting the live network.

The most immediate value is risk-free testing. Engineers can load proposed configuration changes or simulate new topologies on the twin to observe outcomes safely. For NetDevOps teams developing automation scripts or playbooks (like an Ansible playbook for firmware updates), the twin provides a controlled validation environment. It can be integrated into CI/CD pipelines, automatically testing every proposed network change (defined as code) before approval, mirroring software development practices.

Network digital twins also foster innovation. Experimenting with new technologies (like a different routing protocol or SD-WAN feature) is often too risky or costly in production. In a twin, engineers can freely trial new software versions or configurations, even stress-testing the network to understand its behavior, encouraging continuous improvement.

Beyond testing, a live-synced twin aids in daily optimization and troubleshooting. By mirroring real network data, it allows diagnosing issues non-intrusively. If an outage occurs, engineers could replicate conditions in the twin (or use its current state) to trace the root cause without further production impact.

The Challenges in Building Network Digital Twins

While the benefits of a network digital twin for automation sound great, building one isn't trivial. Building an effective digital twin is a complex undertaking that often requires careful planning and significant resources.

First, networks are often highly unique. There's no one-size-fits-all solution, and what works for one organization might not work for another. This complexity increases in large, diverse infrastructures with multiple vendors, protocols, and legacy systems. Replicating these nuances is intricate.

Most networks are multi-vendor, with different device operating systems and features. A key challenge is accurately modeling the behavior of devices from various vendors (e.g., subtle differences in protocol implementation between Cisco and Juniper).

The cost and resource requirements of building and maintaining a digital twin can be substantial and depends on several factors:

• What are your goals?
• Can the entire network be emulated? (Most likely, no.)
• Do you have the team and resources to create this on your own, or do you need assistance?
• For devices that cannot be emulated, where can you procure or stand up physical devices to bridge the gap?

Emulation has limits. While many network devices and functions can be emulated, some systems require the use of physical equipment to accurately represent real-world behavior. This creates a need for a hybrid twin approach, combining emulated and physical components, which adds another layer of complexity. The management and configuration of hybrid environments are more complex than a fully virtualized environment.

Finally, there aren’t many off-the-shelf solutions or digital twin network software to automatically generate a twin of a multi-vendor network. One has to manually or semi-manually set up the lab, device by device, using configs pulled from production.

Mini Digital Twins: Scaled-Down, Cost-Effective Models

A common misconception is that a digital twin must be an exact 1:1 replica of the production environment. For many large organizations with complex networks, replicating everything is not only unnecessary but also often prohibitively expensive and time-consuming.

Instead, there is a growing trend towards mini digital twins.

What is a Mini Digital Twin?

A mini digital twin is a scaled-down yet realistic representation of the most critical parts of your network, designed for testing and validation. It acts as a minimum viable product required for effective testing.

Why go for a mini twin? Large networks (especially in enterprises or service providers) are extremely complex. Replicating everything – every branch office, every last device – would be prohibitively expensive and complicated. Moreover, not every part of the network is relevant to every test. For example, if you’re validating a new data center routing policy, you don’t need to model remote office switches. If you’re testing an MPLS core configuration, you might not need the Wi-Fi access network in the twin.

A well-planned, representative mini digital twin can be more valuable than a poorly designed full twin. It might include key core routers, a simulated branch, and critical interacting services (DNS, authentication). This represents the essential building blocks for testing enterprise-wide changes.

It’s important to note that a mini digital twin still aims to be realistic within its scope. The devices included are configured just like their production counterparts, and if possible, fed with production-like data. It’s simply a matter of scope optimization. This concept is analogous to using a targeted test environment in software testing that covers critical functionality, rather than simulating every possible user and scenario at once.

CloudMyLab's Collaborative Approach to Custom Network Digital Twins

At CloudMyLab, we understand that every network is unique, and that a successful digital twin requires more than just technology, it requires a deep understanding of your specific needs and objectives.

CloudMyLab was purpose-built to address these challenges by offering custom solutions tailored to each organization’s lab requirements. While there may not be an easy button for building a digital twin, our team is ready to roll up our sleeves and help customers create labs that are accessible, effective, and aligned with their goals.

Our process is rooted in customer collaboration:

• We listen carefully to your objectives.
• We collaborate to define the appropriate scale of the lab for your use case.
• We assess how much of your network can be emulated.
• We provide physical infrastructure for rent (housed in our own data centers, on our own hardware).
• We deliver professional services to configure the lab environment to mirror your production setup.

Our emphasis on hybrid solutions

We recognize that not all network components can be emulated effectively, and some require the use of physical equipment to provide a realistic testing environment. Therefore, we provide physical infrastructure for rent in our secure data centers, giving you access to real hardware when needed.

What sets this approach apart is that the emulated and physical environments can be merged, creating a cohesive, functional setup that’s as close to a digital twin as possible. A helpful analogy here is the difference between theoretical and actual yield: while a perfect digital twin is unattainable, we can help you achieve a highly effective and realistic approximation with this method.

To simplify the process even further, we provide comprehensive professional services. Our team of experts can work with you to configure the lab environment to mirror your production setup as closely as possible, and to integrate this with other components and infrastructure. For example, we offer seamless integration with popular network emulation platforms like EVE-NG, where applicable, enabling users to utilize existing configurations and tools.

Where can we build and run these digital twins easily?

Choosing CloudMyLab for your network digital twin development delivers tangible advantages that directly impact your organization's efficiency, innovation, and bottom line. Our approach, combining collaboration, hybrid solutions, and expert professional services, provides our clients with:

Reduced Risk: With our digital twins, you can test network changes and automation scripts in a safe, non-production environment.

Faster Time to Market: By enabling safe, rapid experimentation, our solutions accelerate the deployment of new network services and technologies.

Significant Cost Savings: Our focus on practical and efficient “mini digital twins” ensures you’re not investing in unnecessary complexity.

Improved Team Skills: Digital twins offer a powerful training ground for your network engineers.

Increased Efficiency and Agility: You can build and maintain your labs quickly, adapt to changing requirements easily and achieve a higher return on your testing efforts.

If you're facing challenges with network automation, or you are looking to optimize your current processes, we encourage you to take the next step. Contact us today for a free consultation to discuss your specific network needs, and explore how our digital twin solutions can help you achieve your goals. Our team of experts are ready to help you build a practical, efficient lab that aligns with your business objectives.

FAQ

What is a network digital twin example?

A network digital twin is a virtual replica of a physical network, mirroring its devices, configurations, and behavior for testing and analysis. A great example is its use in network automation script development as a sandbox for confident deployments. A NetDevOps team is tasked with automating VLAN provisioning across a multi-vendor network featuring Cisco, Juniper, and Arista devices. They create a digital twin that replicates their production environment, complete with virtual switches and routers configured to match the real setup. Using this twin, they run their Ansible or Python scripts, testing each step to ensure the automation correctly configures VLANs across all device types. If the script fails, say, due to a Juniper-specific quirk, they analyze the twin’s logs, fix the code, and retest, all without touching the live network.

How Digital Twins Can Boost Network Operations?

Network digital twins enhance network operations by offering a risk-free, data-driven platform for testing and optimization. They prevent outages by validating changes, streamline automation with safe script testing, and optimize designs using simulated data. Digital twins for networks also de-risk upgrades through virtual proofs-of-concept and provide realistic training labs.