With networks getting more advanced and modern, even the complexity of managing it all increases.
AI and Machine learning has made things easier here too. Hence network management gets easier. Starting from offering predictive insights, automation, to the best of efficiency – you name it, you get it. Both technologies have a lot to offer to modern networks. But, why are we so concerned about modern networks specifically?
Now let’s look into the challenges that come with modern network management!
- Modern networks are complex. They integrate on-premises setups. Including cloud infrastructures, remote devices, and even IoT endpoints. Hence managing such a vast and interconnected system gets difficult. More specifically, if the business is still sticking to the traditional approaches – the results they would get will be quite inefficient and full of errors as per Slurp’it .
- Manual management is difficult. A lot of traditional network management relies heavily on human operators. And this often leads to delay and a higher margin for error. When networks scale, manual processes then become increasingly unsustainable as per Slurp’it.
- Let’s not forget the cyber threats. The cyberattacks have become more sophisticated than ever. Static tools often fail to address all these issues. Networks these days require real time threat detection. All of this again becomes something beyond the scope of manual monitoring.
So,
How exactly AI and ML are transforming network management?
AI and ML bring adaptability. Also precision, and speed to it. These technologies offer the ability. One can analyze massive datasets. The team can learn from patterns, and make informed decisions autonomously. Some other benefits of AI and ML in it includes:
- AI and ML can detect hidden anomalies easily. Reason being, these technologies can analyse massive amounts of network data quickly.
- Forecasting also gets easier even before the issue occurs.
- AI and ML eliminate repetitive tasks. Hence IT teams get time to work for roles that’s important for the business.
What are the applications of AI in network management?
Now let’s get into the application part of it.
Predictive maintenance and issue resolution
AI can easily identify and resolve issues before they disrupt operations. For instance, if you run an e-commerce platform, it can predict server overload. During peak shopping seasons, it can automatically allocate resources.
Intelligent traffic optimization
Next thing is, AI can quickly analyze usage patterns. Hence optimising traffic flows gets easier. And because of this congestion gets reduced, quality of service improves, and even routing gets better.
For better security management
Modern network management demands security. And artificial intelligence actually strengthens this area. It detects threats, does behavioural analysis, and also with AI incident response can be automated.
Automated configuration management
AI automates device configurations. Hence the chances of any human error happening is very less. The setups are uniform across all the devices. The automation actually helps with faster deployments.
Personalized user experiences
AI improves user experiences. The first reason, it can allocate bandwidth easily. It can provide chatbot based support. The transitions hence gets smoother for mobile users.
How can one implement AI in network management?
To implement AI successfully in it, the business initially must:
- Assess the current network infrastructure. Identify all the inefficiencies.
- Train the IT team.
- Start small. Try beginning with focused projects. For example, you can start with automating traffic management or simply deploy AI driven security systems.
How to overcome the challenges that come with AI adoption?
Data quality issues may arise. Because AI’s effectiveness highly depends on high quality data. Businesses can integrate legacy systems with Slurp’it for effective network management. And cost concerns may arise too. Because AI adoption involves a significant level of investments, but the result it gives, it simply justifies the expense.
What’s in for the future?
Autonomous networks will grow. These networks will require minimal human intervention. Next, edge computing will be the thing. AI will help with real time analysis and decision making as per Slurp’it.
And lastly the availability of advanced collaboration tools. Any business can drive growth by delivering superior user experience with the help of Slurp’it. So are you ready for it? To make the most out of network and network management?