How has network management evolved? In the past, corporate networks were focused on maintaining a LAN (local area network) and keeping everyone connected within the organization. Stronger connections to the outside world were required as the internet age emerged. Then Wi-Fi began to spread. Companies now must provide robust wireless LANs and support remote workers in establishing reliable network connectivity.
In the past, local area networks (LANs) and keeping everyone linked within the organization were the focus of corporate networks. Stronger links to the outside world were required as the internet age emerged. Wi-Fi then began to spread. Companies now need to provide robust wireless LANs and support remote workers in establishing reliable network connectivity. Edge networking has arrived at this point.
Some of the leading trends in network management are as follows:
#1. The Need For Partners
As networks become more complicated, as the edge technology develops and IoT gains momentum, it becomes clear that no one company can handle everything. As a result, network management vendors are now partnering with IoT and edge specialists. IT vendors are establishing closer relationships with networking vendors as they attempt to position themselves for the needs of changing network architectures. And companies are seeking all the support they need to integrate edge, IoT, and other data into their business operations.
Informa’s 2021 study found that 20% of business leaders actively search for the best delivery partners for edge or IoT services. That number has risen significantly over the past year.
#2. Edge Networking Surge
One of the hottest topics in networking right now is the networking edge. A report on the edge internet economy by Chetan Sharma Consulting predicts that by 2030, the edge economy will be worth $4.1 trillion. This has significant effects on network management. IT will not only have to manage the Wi-Fi, LAN, remote connections over VPNs, and other typical tasks; but it will also need to be able to maintain, monitor, and manage the numerous edge devices and mini-data centers that are anticipated to emerge.
Self-driving cars will also require a significant quantity of edge services in order to be able to keep track of all the factors that affect safe and efficient transportation. The Internet of Things (IoT) should also be taken into account. IoT is enabling billions more connections to global networks. This results in a massive need for edge processing. For example, telecom companies have begun to investigate the possibility of integrated edge data centers with their cell towers so they may send data to the central and local points, summarize it, and store it for specific amounts of time.
#3. Moving Away From Device-Focused Management
The traditional network management systems were designed primarily to manage the device management function and how these devices were supplied over the network. The device offered the service, which was accessible as long as it was operational. However, that long-term approach is now being challenged by new trends such as software-defined networking, virtualization, edge computing, and cloud computing.
In light of the disaggregation of the relationship between services and devices, Mulica stated that “It is now necessary to replace the current network management frameworks with new ones that have been developed and put into use that span across various stack layers and offer coordination between various domains in multi-cloud environments.”
“Understanding connectivity and hosting operations and how they are used to build new services is necessary for this problem’s solution. This allows us to rethink our approach to network management as service orchestration.”
As a result, manufacturers of network orchestration are noticing increased interest in their products. Furthermore, most of these vendors and traditional networking providers are working hard to bring new types of networking management to market.
#4. Containerized Networks
Alef CEO Mike Mulica observes increased businesses developing custom services leveraging third-party infrastructure. These hosted functions can be used as a service to create a particular business logic. For instance, a company might access a Docker registry with several SW functions. These SW functions are packaged as containers, which will be orchestrated into a working app using Kubernetes.
“Because there is no specific device connected to the service, the network management system (NMS) are flying blind regarding service availability, “according to Mulica.
Therefore, network management systems must be up to the task of managing these containerized networks.
#5. Analytics And Artificial Intelligence Driving Network Management
Artificial Intelligence (AI) is increasingly being integrated into more workloads and applications. However, a significant networking issue is standing in its way. The time it takes to connect AI systems to edge data is excessive. If the architecture is overly centralized, it can take one hour for data to be processed locally, moved to a central artificial intelligence system, analyzed, and then transmitted instructions or the findings to the point where it is required.
Moreover, that may work when dealing with sales estimates for the upcoming quarter, but it fails terribly when dealing with real-time workloads like financial fraud systems, self-driving cars, and other things. The necessary networking modification will allow data to be processed and analyzed as it is being created rather than sending it to a centralized data center. This means that there are many edge data centers with high processing power.
Conclusion
Network management is evolving rapidly and will continue to do so in the coming years. In addition, network management recent trends involve several things, such as the continued rise of wireless networking and the Internet of Things (IoT), increased use of artificial intelligence (AI), and machine learning for network management. Also, the rise of SD-WANs and other software-defined networking technologies growing focus on cybersecurity and data privacy.
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Over 4 years’ experience in the research industry. Experience with research and consulting projects, catering to domains such as ICT, Health & Pharma, and packaging. Managed projects on both B2B as well as B2C perspectives, which includes consumer preference analysis, interviews with key executives, etc
