As carrier service providers (CSPs) continue to roll out 5G, Multi Edge Computing (MEC/MEAC) and network slicing are making it possible to achieve low latency, high bandwidth, and super-fast connectivity services required to meet customer demands. Multiparty video, virtual reality (VR), gaming, augmented reality (AR), industrial automation, connected agriculture, connected health, and connected public transportation are just a few of the many use cases that will be putting CSPs to the test.
The delivery of MEC and network slicing are made possible by public, private, and hybrid cloud resources, which come with their own inherent complexities. The sheer density of devices expected as 5G and MEC becomes more commonplace presents significant hurdles when it comes to monitoring, managing, maintaining, reporting, and analyzing issues that could negatively impact customer experience.
To meet customer experience expectations, CSPs must continuously monitor for performance anomalies, and identify changes through the orchestration layer to automate, thus staying aligned with SLA-defined service conditions. This requires real-time network operations, along with service-level delivery and assurance functions that perform at the network edge. Accomplishing this will necessitate a new level of assurance and security.
According to a recent IDC report, “Traditional visibility, trending, and reactive assurance management functions must transform into proactive, predictive and, eventually, self-optimizing capabilities.”
Automation is Key to Customer Experience Management
To ensure the best customer experience, CSPs need a new approach for understanding the traffic traversing networks and new tools for assuring service quality. Due to the vast amounts and complexity of data that must be analyzed, and the sheer speed required by 5G and MEC, traditional human-centric methods of analysis are simply insufficient. Utilizing machine learning and artificial intelligence algorithms provides a more viable approach, but still comes up short. What is needed is “Smart Data.”
The NETSCOUT® Advanced Analytics solution harnesses NETSCOUT’s packet-level “Smart Data” framework, AI/ML technologies with domain expertise, and data knowledge. This comprehensive analytics solution is perfectly suited to identifying issues impacting customer experience, as well as gathering critical insights into what services are working effectively and how customers are interacting with them.
This solution delivers workflow automation, revealing business impact across multiple domains. This is accomplished by adding specific domain knowledge to AI and ML algorithms – providing rapid, actionable intelligence – a manual process that in the past would have taken days or even weeks. This AI-powered Smart Data may also be used to inform the orchestration layer with actionable intelligence for automation.
As the IDC report concludes, “Without a means for analyzing data in near real-time, businesses everywhere are stuck using approaches from the past that are now misaligned with the realities of today’s markets. Automation is the key for addressing business tasks that are close to impossible for humans to perform.”
Workflow automation that relies on ML and AI to analyze millions of data points can facilitate actionable intelligence and insights that enable a better customer experience while lowering OPEX, mitigating customer churn, and reducing mean-time-to-resolution (MTTR). In this era of 5G and MEC deployment, Smart Data is the ultimate key to CSP success.
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