From 2020 to 2025, IDC forecasts new data creation to grow at a compound annual growth rate (CAGR) of 23%, resulting in approximately 175 ZB of data creation by 2025. So, how will you make sense of the influx of data? Analytics is the answer. When you have the intelligence of the network on your side, you’re equipped with powerful insights for your business as well as the capacity and stability for the data downpour.
In a fast-expanding digital economy, enterprises must create the right IT infrastructure to fulfill increased customer expectations and deliver great experiences. To keep up with the pace of change, many organizations are increasingly adopting cloud-first models. As the number of cloud environments grows, there is a need for a sound hybrid cloud strategy that is well supported by an intelligent and secure network. That said, one of the biggest considerations in the design of hybrid environments is making data and applications available to a distributed workforce so they can make informed, real-time decisions. Connecting multiple users in different locations to voice, video, and collaboration tools requires network infrastructure services that do not compromise the performance of these tools, thereby impacting the immersive experiences they intend to create.
As the network is vital to the performance of every organization and is a critical element of cloud and technology transformation, networks must be extremely resilient. If network issues occur, the IT function must be able to resolve them fast, so that business operations can continue uninterrupted, and people can carry out productive work.
The importance of network analytics
As the network is one of the core elements for creating an effective digital transformation strategy, IT teams must have the ability to anticipate, detect, and resolve potential problems before they occur through the analysis and correlation of pre-emptive parameters and indicators. This is possible using network analytics.
Network analytics makes it possible for IT teams to view, flag, hone in on, and automatically respond to network issues in real time, as (or even before) they happen. What’s more, it’s also possible to replay and retrospectively observe historical network events and underperformance and implement predictive and self-healing interventions to ensure that those problems don’t recur in the future.
Perhaps the most obvious use case for network analytics is in using network data to optimize the performance of the network itself. This is something that’s become increasingly important as more users and devices connect to the network from the edge and into the cloud, using sophisticated applications and services and generating growing volumes of data. Networks must not only be up and running and high-performing and resilient but also able to swiftly flex and adapt to change.
Analyze and resolve network issues as they occur
A long-term thorn in the side of network managers has been the need to analyze individual application usage, patterns, and flows of network traffic – as they’re occurring. The good news is that today, network analytics has evolved to the point where IT teams have at their disposal real-time, interactive dashboards that allow them to continually check the health of their network and applications and continuously monitor traffic flows. This puts them in a good position to identify and respond to business-impacting events as they happen. The high level of granularity of these advanced network insights is made possible by multidimensional visualization of application performance, utilization, and the end-user experience. The result? Businesses get a clear line of sight into issues at the site level, application layer, or even individual-user level – in real-time.
Finding out the root cause of non-performance
In addition to having immediate, real-time visibility into network performance, advanced network analytics capabilities enable organizations to do detailed retrospective analytics such as replay functions as well as forward-looking predictive analytics. Retrospective network analytics allows organizations to get a view of how applications are performing across network connectivity at a given time. By analyzing and measuring huge amounts of performance data, you can playback the timeline from that point, just like a recording. This allows the IT team to determine the exact point in time a degradation occurred, the impacted applications, and potential causes that may be affecting it.
Predictive analytics on the other hand allows you to learn from past data of performance issues (potentially over many years and involving multiple devices) and the causes that led to them. You can prevent issues in the future when similar past event data patterns occurred and quickly identify remediation solutions that will prevent them from happening again in the future. Predictive network analytics leverages big data, AI, and machine learning to detect conditions where the abnormal behavior of a network device is likely based on historical events. In some cases, network adjustments or repairs can then be carried out automatically through a self-healing functionality such as an automated equipment reset or traffic rebalancing.
Anticipate and improve security
While traditional security analytics uses specific tools to monitor features such as firewall logs, network analytics goes a step further by identifying malicious patterns and potential attacks. If organizations can proactively anticipate security threats, then they are in a stronger position to protect themselves. Network analytics is particularly useful in identifying behavioral-based threats. A baseline model of the network can be created over time, and alerts raised when abnormal behavior is detected. Alerts can trigger an incident for the cybersecurity team to respond to, or for a security control to automatically mitigate the threat and significantly decrease the time to respond.
Analytics is also crucial to building a zero-trust environment. Zero-trust architectures require a way to close the loop between both policy and observed network behavior. Analytics that looks for bad network behavior and anomalies close that loop.
In summary, a high-performing network is extremely crucial for ensuring that enterprises have the right digital infrastructure to fulfill the demands of users. In a dynamically changing world, network analytics can be an extremely powerful tool for IT leaders to keep a finger on the pulse of their network’s performance and use intelligent insights to prevent and mitigate any potential issues, bottlenecks, or application overloads before they impact employee or business productivity.
Disclaimer: The views expressed are the author’s own and APAC News Network is not responsible for any of them.
