There has always been a need to analyze network performance data to understand how to utilize resources most efficiently. This need has only increased with growing numbers of users and devices connecting to the network. However, traditional network monitoring tools have inherent limitations.
The Simple Network Management Protocol (SNMP), for example, was developed in the 1980s to collect metrics about network-connected devices but is not well-suited for retrieving and evaluating large data volumes. Network administrators need the power of big data analytics to gain greater insight into how the network is performing.
Network analytics tools enable administrators to identify potential problems, fine-tune performance, predict traffic volumes and enhance security. Traditionally, these tools have only been used by large enterprises with complex networks. Now they are becoming cheaper and easier to use, and embedded in cloud-based network management platforms. Small to midsize businesses (SMBs) can also capture the value of network analytics through managed services offerings.
The global market for network analytics solutions is expected to see a compound annual growth rate of 20.9 percent through 2030, according to Emergen Research. Market growth is being driven by skyrocketing network traffic volumes and growing adoption of Internet of Things (IoT) devices.
Harnessing Artificial Intelligence
In order to take advantage of network analytics, organizations need to capture high- and low-level data on network usage and performance and aggregate it in a centralized system. The network analytics platform must be integrated with other management systems, and give users the ability to perform ad hoc queries. Dashboards and visualization tools also allow administrators to investigate anomalies and trends.
The latest network analytics tools use artificial intelligence and machine learning to predict the future state of the network and track the functioning of network devices to detect potential failures. These techniques also enable network analytics platforms to understand the normal behavior of users and devices so that they can spot anomalies that could indicate a malfunction or cyberattack. As a result, network analytics can form the foundation for a zero-trust security architecture.
Many of our customers are using the Ruckus Analytics solution from CommScope to enhance their ability to analyze and use growing numbers of network assets. Built on a patented machine learning and artificial intelligence foundation, the cloud-based service improves network visibility, enhances troubleshooting capabilities and automatically identifies performance issues.
The Ruckus Solution
A web-based dashboard makes it easy to explore network data, allowing users to see high-level views of network operations or click through to the most granular level of detail. Users can create custom dashboards with a Data Explorer tool, or they can use a variety of pre-packaged templates to produce reports about network performance, traffic patterns, application usage and more.
An AI-enabled virtual network assistant known as Melissa is one of the solution’s most user-friendly features. Users don’t need any specialized IT skills to conduct data analysis – they can simply ask Melissa. Using natural language processing, Melissa discerns the user’s request and can quickly present graphical renderings of the data requested.
Network devices and management tools are capable of capturing large volumes of data on traffic flows but provide little insight into how the network is actually functioning. Organizations need solutions such as Ruckus Analytics that evaluate this data and provide dashboards, visualizations and reports. Contact us to learn how you can utilize Ruckus Analytics to improve the performance of your network.
