The Future of Network Service Assurance: Real-time Visibility, AI, and Cloud-native Architecture
Contributed by Matthew Twomey, Head of Product Marketing & Marketing, Anritsu Service Assurance
This originally appeared on Futurenet World as a blog for their MENA Event in March 2023 — https://futurenetworld.net/service-assurance-ai/the-future-of-network-service-assurance-real-time-visibility-ai-and-cloud-native-architecture/2023/03/
The rapid evolution of network technologies and the increasing complexity of services have transformed the landscape of network service assurance. In the era of 5G and beyond, operators are faced with escalating demand for new business-focused applications, improved service quality, and real-time issue resolution. The future of network service assurance lies in real-time visibility of subscriber/device issues, the application of AI, and adapting to cloud-native architecture amidst changing 3GPP standards. This article will discuss these crucial aspects and differentiate between service assurance from a fulfilment perspective and service assurance from the network.
Real-time Visibility of Subscriber Issues vs. Real-time Visibility of Network Functions
Traditionally, network service assurance focused on monitoring network functions and infrastructure to ensure seamless connectivity. However, as networks become more complex and user expectations rise, the focus has to shift toward real-time visibility of subscriber issues. This entails understanding the customer experience, detecting and resolving service issues in real-time, and proactively addressing potential problems before they affect the end user. This shift in focus is essential for maintaining customer satisfaction, reducing time spent troubleshooting, and ultimately, ensuring business success.
The Application of AI in Real-time
Artificial Intelligence (AI) is poised to play a pivotal role in the future of network service assurance. With the increasing complexity of networks, manual monitoring, and intervention have
become less efficient and less effective. Assurance-AI can analyse vast amounts of data generated by the network infrastructure and user devices to identify patterns, predict potential issues, and prescribe actions to optimize network performance. This real-time AI-driven analysis, looking at subscriber-level detail, allows service providers to detect and resolve issues faster, improve network efficiency, and enhance the overall customer experience.
Fulfilment Perspective vs. Network Perspective
Service assurance can be viewed from the fulfilment perspective and the network perspective. From a fulfilment perspective, service assurance focuses on the end-to-end process of delivering services to customers, including order management, provisioning, and activation. This viewpoint emphasizes the seamless delivery and activation of services to meet customer expectations. In this realm, real-time AI, though as important, has fewer challenges for visibility.
On the other hand, service assurance from a network perspective needs to acquire its data and is concerned with monitoring and maintaining the health and performance of the network infrastructure. This includes identifying and resolving network issues, ensuring availability, and optimizing network performance. Of course, the subscriber experience is the foundational part of this view.
Both perspectives are crucial for a comprehensive approach to service assurance. Understanding and addressing service assurance from these two angles ensures that service providers can effectively manage network resources, deliver high-quality services, and maintain customer satisfaction.
Challenges in Moving to a Cloud-native Architecture
The transition to cloud-native architecture is essential for operators to keep pace with the increasing demands of businesses and subscribers while supporting technologies like private networks. However, this move comes with its own set of challenges. One significant ongoing challenge will be the adoption of evolving 3GPP standards, which continue to redefine network specifications. These escalating standards introduce escalating complexity for operational teams, requiring them to adapt to new tools, protocols, and processes. This necessitates a continuous learning process, ensuring that teams have the skills and knowledge to manage and assure cloud-native networks effectively. This further cements the need to look at AI-assisted Assurance systems today.
Another challenge for future networks is capturing the data needed to understand subscribers’ experiences as they always have. 5G SA and future versions have security built-in to the heart of the network. This makes data acquisition more difficult. If you don’t understand the subscribers’ experience, you cannot make a network corrective action either manually or automatically, as you won’t know the impact on subscribers.
In conclusion, the future of network service assurance calls for a paradigm shift from mere real-time visibility of network functions to real-time visibility of subscriber issues. This approach will facilitate a more customer-centric model, enhancing user experience and driving automation. AI’s real-time application will play a crucial role in addressing the increasing complexity of network management and enabling proactive troubleshooting. As the industry transitions to a cloud-native architecture and adapts to the ever-evolving standards, operational teams must navigate the escalating complexity accompanying these changes with a shift to becoming an automation-driven operational team.
