• As operators modernize networks towards the goal of cloud native architectures, the multi-domain, cloud-oriented nature breeds complexity, which is the leading challenge today.
• To tackle this complexity, operators, vendors and a new breed of network platform vendor are turning to AI tools for orchestration management and assurance as well as APIs and open standards.
FutureNet Asia, a leading conference bringing the telecoms industry together to discuss strategic and commercial priorities was held this October in Singapore. The event saw leading players from the operator side including Bharti Airtel, Indosat Hutchinson Ooredoo, and Telenor Asia, the infrastructure side such as Juniper, Dell, and Intel, heavy representation from network enablement vendors such as Amdocs, BluePlanet, and Rakuten Symphony, and newer players with a focus on cloud-native and AI enabled networks like B-YOND and Robin.IO, come together to discuss the future of operator networks and how AI will play a role in delivering services in the 5G era. Operators like IOH shared their journey towards automated cloud native networks, including the challenges still ahead, while vendors like VMware and B-YOND discussed how they are assisting their operator partners in dealing with the complexity of these new architectures with automation, including the use of AI tools. Below is a discussion of some of the key challenges raised and how the industry is addressing them.
Some of the biggest challenges facing operators as they try to modernize networks for the 5G era are related to the increasing complexity of managing network elements across both traditional network domains. With the rise of bundled multiplay services, operators need to not only ensure that there is visibility across the RAN, transport, and core, but also orchestrate fixed services as well. Further, the rise of microservices and containers in telco infrastructure means that telcos must now manage cloud-native resources in the service environment. For operators this means that it is not the typical faults and service failures that may arise that are the most concerning, but new service types and network elements causing problems that are the biggest worries. This means observability at every layer, from service assurance down to the network domains Is key to help maintain service levels.
Further to address this rising complexity, network vendors, operators, and standards bodies are looking to develop standards around the automation of network operations, administration, and management, to achieve zero touch networks or networks that can maintain service levels even in the event of adverse conditions without human manual intervention. ETSI (ZTM) and TM Forum (ZOOM) for example are pursuing their own standards to this end. The use of open-source technologies, APIs for interface between domains, service, and resource orchestration as well as common standards will be increasingly important. Further, in some cases the management of new 5G services alongside legacy will need to be achieved, with the main case today being 5G to 4G handover.
To achieve this, operators are turning to AIOps to streamline network planning, service, testing, root cause analysis (RCA), holistic management, network orchestration, etc. However, AI is not a magic bullet and every operator environment is different, meaning different approaches to training AI models will be needed.
The rise of 5G is adding new challenges to network management, not only from the incorporation of new cloud-based architectures and use of edge compute, but also the rise of new business cases it is expected to support. While LTE was largely focused on B2C, consumer best effort networks, 5G is expected to support more B2B use cases including those that will leverage network slicing and edge compute resources to deliver services. This shift from B2C to B2B will require operators to deliver on enterprise level SLAs in the mobile network, increasing the importance of achieving Zero-touch networks. Another challenge is that enterprise 5G service may be delivered with more than one partner ultimately responsible for service delivery this opens up challenges in how to manage SLAs as both partner environments need to be able to communicate. APIs may be one way to tackle this but it is still an evolving question.