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Network Infrastructure Magazine | Wednesday, February 24, 2021
As SD-WAN continues to be adopted, it should widen the use of machine learning to all applications in the future, transforming the focus from branch connectivity to automated operations.
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FREMONT, CA: Given the pace with which technology evolves to securely connect users to applications, combined with the quick changes in traffic patterns, SD-WAN is needed to thrive. New tools must be developed and implemented to automatically identify and analyze network behavior before it impacts end users. To reduce and prevent network problems before they affect users, networking professionals must be quick to realize and adopt these tools. One of the most valuable technologies in networking, machine learning (ML), can save time for implementing changes, effectively manage networking issues, and constantly and automatically adjust to new situations.
Artificial intelligence (AI) and machine learning are presently used in production for wider use cases, including security. They are rapidly being infused into IT operations and changing how humans connect with technology, offering a more proactive and automated approach. The time required to find the source of network issues and remediate them contributes to a network’s total ownership cost. Legacy software-defined WAN solutions may provide centralized network management, assisting administrators in locating issues quickly. Still, ML-based potentials found in next-generation SD-WAN can anticipate problems before they even happen.
When AI and machine learning are combined in an SD-WAN solution, the network gets vast data processing and a richer understanding of network and application performance. The network becomes intelligent. The combination of automation, machine learning, and AI makes a self-healing network that can monitor, analyze, and adjust with minimal human intervention.
Next-generation SD-WAN platform with ML-based potentials enables firms to simplify network operations and enhance performance by offering accurate visibility into the network and a deeper understanding of network and application performance, which is key to resolve issues as they develop. It also provides smart analytics, including intelligent alerts and recommendations for network changes after analyzing how various events affect the network, application performance, and security. This will usher in a new age of expected exceptional performance, highly available and flexible bandwidth, and data and analytics, all while mitigating operational costs.
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