![]() “The cost difference between simulating a relatively simple residential network model and an AT&T internet backbone is astronomical,” Grammer said. Not only that, but, modeling tools are costly to scale up. Therefore, simulating network performance is subject to the users’ needs, which can change at any time, making it more difficult to actively predict. #Cisco ios image for gns3 full#The network traffic produced by a coffee shop full of casual internet users is a far cry from the needs of petroleum engineers working with real-time drilling operations. They also need to simulate the ideal flow of traffic, along with all the ways it could break or that paths could be isolated from the rest of the network.Ĭhristopher Grammer, vice president of solution technology at IT solutions provider Calian, told VentureBeat that one of the biggest challenges is that real network traffic is random. Still, they often struggle with new protocols, domains or scaling to more extensive networks. Overcoming the struggle with new protocolsĮarly modeling and simulation tools, such as the GNS3 virtual labs, help network engineers understand what is going on in the network in terms of traffic path, connectivity and isolation of network elements. These areas are critical for proactive and predictive analysis to prevent network or service downtime or impact user experience adversely. These tools are also starting to plug into continuous integration and continuous deployment (CI/CD) tools to support incremental updates and rollback using existing devops processes.Ĭisco has developed tools for what-if analysis, change impact analysis, network dimensioning and capacity planning. Vendors like Gluware, Forward Networks and others are creating real-time digital twins to simulate network, security and automation environments to forecast where problems may arise before these are rolled out. This will be critical for widespread rollouts in healthcare, factories, warehouses and new IoT businesses. Tiwari said digital twins will make it easier to model different network designs up front and then fine-tune them to ensure they work as intended. Minas Tiwari, client partner for cross-industry comms solutions at Capgemini Engineering, believes that digital twins will help roll out disaggregated networks composed of different equipment, topologies and service providers in the same way enterprises now provision services across multiple cloud services. If the digital twin operates on older data, it will return out-of-date answers. Keeping the data lake current with the state of the network. ![]()
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