Reducing Network Downtime using AI-Enhanced SD-WAN

SD-WAN has replaced MPLS for better network performance, and it is no wonder the latest technologies like Artificial intelligence, Machine Language, and the Internet of Things are all being associated with SD-WAN to improve enterprise network traffic management. The association of artificial intelligence with SD-WAN is changing the perspective of networking and its applications. Today’s blog will discuss how to reduce network downtime using AI-enhanced SD-WAN.

Transforming network operations with AI-enhanced SD-WAN

1. Quick troubleshooting: The AI algorithm detects potential threats even before the problem escalates. The ability to predict problems in advanced and automated troubleshooting is a noteworthy achievement of AI-enhanced SD-WAN. The VPN tunnels are restarted once the anomalies are identified and interruptions are prevented.
2. Intelligent traffic optimisation: AI-powered SD-WAN selects the best data paths in real time to improve application performance. Critical applications are allotted the necessary bandwidth to improve overall network performance and reliability.
3. Automated network management: One of the most beneficial tasks of AI-powered SD-WAN is automated routine network management. Removing manual processes can reduce human error and protect against network downtime. Automated systems can identify and resolve issues for quick recovery.
4. Improved security: Since threats are detected in advance, downtime is controlled. Machine learning models detect unusual patterns and notify security breaches. They also automate corrective actions to reduce downtime caused by security breaches.
5. Network management made simple: The complex networks can be monitored and configured automatically without any need for manual intervention. Large organisations with huge network infrastructure can now focus on their core activities while their network management is automated.
6. Understanding application behaviour: With deeper insights into network performance, it is easier to analyse application behaviour using AI-powered analytics. Real-time monitoring helps organisations make decisions on resource allocation and capacity planning easily, reducing downtime.

AI-powered SD-WAN Vs traditional SD-WAN

• AI-driven SD-WAN uses predictive analytics to reduce network downtime by identifying the problem before it escalates into something big.  Rerouting traffic and adjusting bandwidth allocation are some of the techniques adopted. Traditional SD-WANs do not have the advantage of advanced predictive techniques as they rely on reactive measures to address issues that lead to longer downtimes.
• AI-driven SD-WAN follows intelligent traffic management to optimise data paths in real-time to provide the necessary bandwidth for critical applications, reducing downtime. In traditional SD-WAN, routing policies are static and not adaptable to changes, resulting in traffic congestion and downtime, especially during peak times.
• Automation and troubleshooting are breezes in AI-powered SD-WAN, where issues are detected and resolved quickly. There is reduced human intervention, and operational complexities can be overcome quickly due to automation. Traditional SD-WAN lacks these features, and the longer response time leads to longer downtime.
• With AI-driven SD-WAN, you can enjoy seamless connectivity. It comes with failover capabilities that redirect traffic automatically during link failure for uninterrupted ongoing sessions. It also ensures continuous connectivity for critical applications. Traditional SD-WAN requires manual reconfiguration and does not have a robust failure mechanism, causing frequent interruptions and outages.
• Improves visibility: With advanced analytics, AI-driven SD-WAN offers insight into network performance for proactive adjustments and quick decisions to avoid downtime. In traditional SD-WAN, visibility is limited, leading to performance chokepoints.

AI-driven SD-WAN improves network performance by continuously adapting routing policies depending on changing conditions. The network’s self-optimising capabilities make it agile and responsive to user demands for improved performance. The security integration is top-notch, with automated detection of malicious activities and isolation of threats that impact the network performance.

Integrating AI with SD-WAN is marred with challenges, and to enjoy the benefits, the challenges must be addressed. Compatibility issues are a major challenge, and organisations need to integrate them with the existing system for the best results, which may require upgrades and modifications. AI relies on data for training and operations. High-quality data for AI algorithms is crucial, and organisations have faced the challenges of processing large volumes of data for AI implementation. As the organisation grows, the network requirement also evolves, and AI-driven SD-WAN is the right choice to meet the increasing demands of the organisation without compromising on cost or security.

SMOAD SD-Branch solutions offer AI-driven analytics for smoother network performance without worry of downtime. They help handle branch-critical issues across industries. With features like diverse WAN links, quantum secure communication, and intelligent routing, SMOAD is the go-to destination for automated network solutions to avoid seamless connectivity.

For more information, contact us for a demo.