Building cost-efficient cloud-native 5G SA networks: a TCO comparison

The 5G network has been conceived as a cloud-based network in which all functions are expected to run on a horizontal network cloud rather than on siloed virtualized platforms. Leading telecoms operators are beginning to deploy the 5G standalone (SA) core; this is a set of cloud-native network functions (CNFs) that will require operators to accelerate their adoption of cloud-native infrastructure. The cloud-native 5G SA core also requires operators to commit to a cloud-first, horizontal approach to running the network with very high levels of automation.

Cloud-native clouds enable operators to adopt open and disaggregated architecture; cloud-native infrastructure is sourced independently from vendors’ CNFs. However, operators must choose between two main approaches to disaggregated cloud deployment. The first option is to build a private network cloud by integrating multiple technology components including compute and storage hardware, cloud technology platforms, software-defined networking (SDN) and, in advanced cases, orchestration capabilities. We call this the do-it-yourself (DIY) private cloud deployment model. The alternative is to use the hyperscale-based infrastructure and advanced automation frameworks offered by public cloud providers (PCPs). Operators that are planning their 5G SA core deployments and are looking to deploy virtualized/Open RANs in the future must decide on their approach to cloud-native infrastructure; a holistic total cost of ownership (TCO) analysis is critical.

Analysys Mason, in collaboration with Microsoft, has analyzed the TCO of deploying a cloud-native 5G SA network using a PCP cloud solution based on Azure Operator Nexus compared with that using the DIY private cloud model. The TCO model considers three greenfield deployment scenarios for the cloud-native 5G SA core in consumer macro networks, modeled for two hypothetical Tier-1 operator profiles (in Western Europe and in Latin America). In this report, we discuss the key findings of this analysis.