This digitally driven world requires robust, agile, and high-performance networks. Deploying only network automation tools doesn’t work in a fully-fledged manner. Therefore, to get ahead of your competitors you need to integrate modern networking technologies like AI & ML with your network automation tools. For example, we want real-time network monitoring systems and cybersecurity features in our network infrastructures. So, how is that possible with network automation alone? Thus, we will discuss the challenges in today’s scenario and learn how to combat them.
First of all, we will learn about AI and ML tools & their features. Then, we will learn how enterprises can integrate AI and ML technologies with network automation tools.
Knowing Network automation
Using software programs and tools to automate various network management tasks, without any human intervention, is termed Network Automation. Network automation tools have provided a big relief to network administrators. It can handle complex and large networking infrastructures with the same ease as it can manage small and simple architectures.
Network automation solutions simplify network device configuration, provisioning, monitoring, and other related operations. Further, network automation tools reduce human errors that are most likely to appear in the management of complex networking architectures. Also, the deployment speed of new networking devices can boost with network automation architecture.
Knowing Machine Learning
Machine learning is the ability of machines to learn from data, recognize patterns, and make decisions without complex programming. Machine learning is actually a subset of AI. It is a powerful tool that enables a system to catch the bug by analyzing the patterns made during data transmission over networks. It can help a network infrastructure to adapt to the changing environment, like the addition or deletion of a networking device/peripheral. Further, you can easily achieve network optimization features with the help of machine learning tools.
Knowing Artificial Intelligence
Artificial Intelligence(AI) is a miraculous innovation that has the capability of replacing human efforts to an extent. You can call it a human imitation. But, it can supersede human efforts in terms of real-time monitoring. Human intelligence processes like learning, reasoning, problem-solving, and decision-making are imitated by AI tools. You can get real-time recommendations and automate complex operations if you adopt AI technology with your network automation solution.
Benefits of AI and ML Integrated Network Automation Architecture
Let us discuss the benefits of the integration of AI and ML tools with network automation architecture to get some more clear view:
Enable Predictive Maintenance and Proactive Issue Resolution
Traditional approaches with network automation solutions are inefficient in matching the current digital requirements. Network downtime can turn costly in terms of money, time, and reputation too. Thus, the integration of AI and ML with network automation infrastructure can make the networks more proactive. Tools powered by AI and ML technology help analyze network traffic patterns, performance data, and device logs to predict potential failures before they damage the whole system.
Such technologies can prevent hardware and software failures by alarming the system even in case of small discrepancies. Even, a drop in network throughput gets noticed by AI & ML tools. Thus, cases like network downtime can be prevented with ease using these innovative tools. In addition, you can assume rerouting traffic and provisioning additional bandwidth whenever application requires.
Ease in network performance optimization
If network optimization is achieved automatically, then a big overhead from the network teams can be subsidised. In addition, using AI and ML tools can optimize network performance in real time without requiring human intervention. ML tools read and recognize the patterns made earlier while running a particular enterprise application under different conditions.
Adopting ML can lead to analyze different application traffic patterns and prioritize critical traffic before anything else. These tools can easily adjust Quality of Service (QoS) rules to allocate bandwidth for seamless application operations. Therefore, you can get improved user-experience and productivity by reducing congestion-free network paths.
Enable Automated Security Threat Detection and Response
Network security is a big concern for automated networking infrastructures. However, AI and ML tools provide you with improved and advanced network security systems that work in real time. These tools can detect and respond to cybersecurity threats accordingly. Irregular patterns like Distributed Denial of Service (DDoS) attack, malware infection, or unauthorized access attempts are noticed and notified by ML & AI in proactive mode. In addition, they can improve various security policies with advancements in cybersecurity threats and issues.
Improved scalability and visibility
AI and ML tools can improve the ability to add new networking devices in new locations to setup new offices. Further, you can enhance the ease in managing network infrastructures by monitoring network’s performance, health, and security. Traditional network monitoring tools are not able to perform with such agility and accuracy as ML & AI tools do. ML tools can identify even the hidden and minute patterns in network behaviour. AI and ML tools provide the opportunity to track networks in real time. So, if anything unusual happens, it is reported instantly and a suitable action can be taken further on.
Summary
Well, it will be wise if you adopt the integration of ML and AI tools with network automation solutions for your enterprise. Reading this article must have made you understand the significance of integrating AI & ML tools with your existing networking infrastructure. Therefore, you must adopt these innovations to enhance the security, performance, scalability, and visibility in your enterprise network infrastructure to enhance productivity and improve end-user experience.
FAQs:
- What can AI do for improving your enterprise network infrastructure?
AI can prevent bottlenecks in the network path. In addition, AI can help in enhancing the proactive network monitoring by analyzing network security threats in real time.
- What does ML tools help in enhancing the network security features?
ML tools can recognize specific patterns made while operating different enterprise applications. Thus, if any difference is found in network pattern usage, then ML tools notice it and alarm the network administrators.