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Assure next-generation networks by exploiting data intelligence

Network complexity on the rise

Next-generation, programable networks are becoming smarter and capable of delivering differentiated services over shared infrastructure. The upside is the of wealth of opportunities. The corollary is the unprecedented growth in complexity.

And even as traditional networks continue to operate in the background, the adoption of virtualization, cloudification and disaggregation are making networks more diverse and dynamic, opening the door to new players and promoting a new wave of innovation in a market traditionally dominated by a small number of network equipment providers (NEPs). As an additional benefit, it’s also providing more options to avoid vendor lock-in.

For an example, let’s see how 5G networks are propelling a radical evolution across multiple network domains:
• The Radio Access Network (RAN) is evolving towards disaggregation and openness with Open RAN promoting interoperability and standardization of RAN elements.
• The mobile core is evolving from monolithic appliance-based architecture to a service-based architecture where the 5G core is delivered by a modular set of interconnected cloud-based network functions (NFs).
• The introduction of edge and telco clouds is supporting network cloudification with a next-generation of NFs that run on commodity hardware on private and public clouds.

Another important outcome of this evolution is the massive impact it’s causing on operations. Specifically, with the growth in complexity, it opens a gap between current operational capacity and actual demand. Closing this gap requires bringing operational support systems and processes up to speed, by adopting integrated solutions that can support automated operations with dynamic orchestration and intelligent assurance.

Operating the programmable network

Monetizing the investment in next-generation networks also demands new business models that can support the delivery of diverse and advanced services with optimal performance and high reliability – all prerequisites for supporting new use cases with demanding needs such as remote healthcare or autonomous cars.

To get there, we need to take a completely new approach to operations – moving away from siloed, domain-specific, and human-driven operational systems and processes that are simply not scalable. And as complexity increases, it also requires automation to ensure we can continue delivering an outstanding customer experience. This can only be achieved by removing the boundaries between service and network orchestration, as well as inventory and assurance, and converging these processes to support closed-loop operations.

So how do you create a modern, integrated, intent-driven solution where the business intent drives the entire lifecycle of the services? The answer lies in combining dynamic orchestration with the power of intelligent assurance and its ability to continuously observe the network and services. This in turn, allows you to proactively identify service degradation and outages, and leverage policy, artificial intelligence and machine learning to drive the required remedial actions.

Yet such a change needs to be gradual, evolving from open loops that require human input to closed loops and “hyperautomation”, a business-driven, disciplined approach to rapidly identifying, vetting and automating as many operational processes as possible. Crucially, choosing the right partner from the initial stage will be key to a successful outcome.

Inventory data powers automation

A key challenge in the journey to hyperautomation is securing access to comprehensive, accurate data to ensure the right decisions are taken during the entire service lifecycle. This is where the inventory plays a key role, providing a 360-degree view of interdependencies between network and service topologies, enabling automated root cause analysis and restoration of service quality.

Nevertheless, given the dynamicity of next-generation networks, the inventory too must evolve to become dynamic, so it can receive live updates from the network to enrich the data it stores. Here, due to the need to integrate with multiple data sources, alignment with standard bodies such as 3GPP, ETSI and IETF will be key.

Data analytics become a must

To support the tremendous growth in scale and diversity of data derived from next-generation networks, artificial intelligence and machine learning, supported by analytics, will also be required to harness data storms, as well as to efficiently deliver and maintain high-quality services.

And since new analytics sources will be available in different network domains, when it comes to services spanning across multiple domains, analytics and AI/ML will also fulfil the role of understanding what’s happening in the network from end to end, so it can anticipate and resolve any impact on services before the user is affected. An example of a new analytics source is the network data analytics function (NWDAF), which collects data from other 5G core NFs to help automate network optimization and service performance.

Enabling a digital society with hyperautomation

If next-generation networks are to serve as true enablers for consolidating the service provider’s role in enabling digital society and increase revenues, we need to look beyond just rolling out new networks. The true benefits will only be realized by working with a partner whose knowledge and experience can provide integrated, end-to-end solutions that close the operations capacity gap and facilitate the journey to hyperautomation.

Find out more here: Research: Achieving success with intent-driven next-generation networks | AMDOCS

This content is sponsored by Amdocs.

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