A major part of the IT teams time is spent on fixing network issues. Challenging them is new world technologies like Artificial Intelligence, Big Data, Augmented and Virtual Reality, Cloud and an increasingly connected world. All these are changing the network landscape. The traditional networks are ill-equipped to handle this dynamic scenario.
Problems faced by network managers
- Analyze the tons of data streaming from network logs, Wi-Fi devices, network transactions between wired packets
- Identify patterns and network insights from them to provide quality recommendations for the decision makers
- Alert fatigue from the innumerable alerts and events generated from the network operating points
So, what’s the need for an online network management and optimization system.
- Adapt to changing network conditions
- Agility to adapt as per need and in a timely manner with low network overhead
- Efficiency so that the network operates at the optimal point for the current network conditions and traffic scenarios
What’s changed in the Network Landscape?
Cloud, IoT, AR/VR and Big Data is what’s changed the network. Scalable, highly available, cloud security and ability to cater to multiple organizational environment is its advantages. At the same time, flexible workloads, virtual networks and bring your own devices have increased traffic volumes.
Now, imagine a world where the network will self-identify network issues, analyze the data and recommend remedial solutions for the network managers. All this is possible with Artificial intelligence.
The current network infrastructure is monitored by algorithms that scrutinize the activities and traffic to detect any anomalies and attempted hacks. By powering these algorithms with Artificial Intelligence, organizations will manage, maintain and protect their networks faster and with more fool proof methods of anticipating threats and cleaning the network.
AI will be able to collect and analyze real-time data as it collects network information to make accurate predictions for network managers. AI and machine learning provide the network capabilities to learn and improve by looking for trends, patterns and anomalies within the data to make increasingly better correlations, inferences and predictions.
The machine learning algorithm progresses through the data, learning enough to discover what input generates a particular output. This produces a framework that makes predictions and recommendations for the network personnel to improve the overall system.
- Reduces manual effort and cost involved in analysis and correlation of network data sources by IT teams
- Pinpoints specific and systemic user network performance issues across the entire network
- Delivers predictions and recommendations for fixing them
- 360 degree of the network with a single source of network dashboard for various sections of the network team
- Reduce blame game when IT issues arise
- Identify and predict potential network problems and capacity requirements before they happen.
Moving forward, as organizational network complexities increase, AI based networking will only increase. This will include the need for collaboration between the network management and the enterprises. AI is and will be the future of IT.
– Shantha Kumari,
Sr. Technical Writer,