How can artificial intelligence (AI) empower SD-WAN Solutions?
Learn more about SD-WAN
SD-WAN (Software-Denied Wide Area Network) is the cornerstone of the widely applied SASE (Secure Access Service Edge) architecture. It brings all traffic, regardless of connection type, to a single network platform where IT administrators can centrally manage it.
SD-WAN allows enterprises and SASE vendors to collect innumerable amounts of networking and cybersecurity data. How can you unleash the power of this unprecedentedly large data tank? That is where Artificial Intelligence (AI) and Machine Learning (ML) come into play.
When enterprises and SASE vendors deploy AI over SD-WAN, they can gain an in-depth understanding of the network by learning and processing massive data sets they’ve collected. Their capacities make the network more intelligent, self-driving, and automated.
The most significant benefits of integrating artificial intelligence into SD-WAN solutions are sharpening analytics, enhancing security, and boosting performance.
When AI frees the network from human intervention, which could sometimes lead to human error, it also saves SD-WAN engineers from tedious and time-consuming troubleshooting. It helps them focus on more complicated tasks, dramatically increasing efficiency.
Below we will introduce four use cases where unifying artificial intelligence and SD-WAN solutions can bring SASE to the next level.
Predictive maintenance has already been one of the manufacturing industry’s most prevalent AI use cases. The same predictive analytics can apply to threat detection in the cybersecurity world.
The legacy intrusion detection system is excellent at looking for a signature of known attacks but is clumsy when responding to new threats. AI can recognize novel attacks – typically variations of previously known threats.
Also, you can train AI models to automatically detect and address all the known vulnerabilities and attacks even before they impact users. AI engines can leverage real-time network monitoring and stop previously known attacks.
The capacities of AI enable IT to adopt a proactive approach to detect and analyze anomalous network behavior before it can affect the user experience. The ML-based anomaly algorithm can constantly analyze network activities and find patterns.
ML algorithms are extensively valuable when processing vast datasets and looking for patterns. They can use those patterns to detect irregular and suspicious network activities that may threaten the network.
Anomaly algorithms can alert IT teams of anomalous behaviors so that security engineers can predict problems before they impact end users. That is one of the most significant use cases for AI in cybersecurity.
However, not all anomalous activities are inherently malicious – some are benign. As the network behaviors are closely related to the network configuration, the patterns in one network may not apply to another.
Therefore, the mounting volume of false positive alerts can overwhelm security engineers if the traditional screening tools fail to distinguish anomalous from malicious behaviors – alert fatigue is real. AI can address this challenge by further analyzing and classifying alerts.
Root Cause Analysis
When AI detects networking or security issues, it can help IT teams identify their source.
According to ZK Research, IT professionals spend 90% of their problem-solving time identifying the source of the issue.
Automating AI algorithms’ diagnosis of networking faults and security issues saves engineers from sifting through countless log files and alerts and allows them to focus on more complicated tasks.
Nowadays, AI-powered next-generation SD-WAN solutions usually address this challenge by providing one-click root analysis.
For example, a dysfunctional cable disconnects from the network suddenly and causes problems for end users. IT administrators may need to spend a tremendous amount of time going through a checklist of software and hardware to pinpoint the issue and physically check cables.
If they embed artificial intelligence into SD-WAN, the system completes the checklist automatically using the decision tree ML algorithm. IT professionals can quickly identify disconnected and faulty cables and focus on addressing the issue.
Network Routing Optimization
Network routing optimization is another area where AI plays a significant role. SD-WAN solutions can utilize AI to anticipate the conditions on a specific link, track traffic peaks, and avoid traffic congestion.
For example, an AI-driven network can make more intelligent routing decisions, such as shifting traffic from an overloaded to a less congested link. AI-powered network path selection can save enterprises from ordering more bandwidth.
AI can also ensure the connection is reliable for devices to play their function without wasting bandwidth by analyzing the devices’ features and automating traffic steering policies. AI helps SD-WAN solutions manage and steer traffic to different clouds and application resources wisely and safely.
Artificial intelligence and SD-WAN solutions are a perfect combination that amplifies network security, simplifies network troubleshooting, and optimizes network routing. Massive data from SD-WAN and AI algorithms drive insights that empower IT engineers to deliver a better user experience. In the future, artificial intelligence will be a must-have feature to combine with SD-WAN solutions.
If you have interest in knowing more about how Cloudi-Fi completes access security in the SD-WAN journey you can visit this page.
What is SD-WAN?
SD-WAN is an abbreviated term that stands for “software-defined wide-area networking.” SD-WAN products allow corporations to manage and optimize their WAN traffic using software instead of traditional hardware appliances.
This technology can aggregate multiple links (wired and wireless) into a single logical network, improving performance and reliability while reducing costs. SD-WAN solutions also provide advanced security capabilities, such as encryption, intrusion detection & prevention, as well as firewall protection.
SD-WAN is a key component in the software-defined networking (SDN) approach, which enables organizations to manage wide-area networks with more flexibility and efficiency. These solutions enable enterprises to quickly connect branch offices to applications in the cloud or on-premise with granular visibility into network traffic via analytics and control.
As SD-WAN technology continues to evolve at an increasing rate, it will become an even more critical piece of any organization’s networking strategy. These solutions make networks more resilient, secure, and cost-effective while providing greater control over wide-area networks. It is an ideal solution for businesses that require a fast, reliable, and secure network connection across multiple locations.
SD-WAN technology is here to stay, and businesses need to understand how SD-WAN solutions can benefit them.
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