Introduction
Designing 5G network architecture for public cloud platforms requires an architectural approach that leverages the unique strengths of hyperscalers while addressing the complexities of telecommunications systems. This section delves into Key Architectural Considerations for Cloud-Native 5G, emphasizing integration, scalability, and operational strategies.
While this section focuses on the architectural considerations for deploying 5G networks on public cloud platforms, it is essential to highlight that private and hybrid cloud models offer alternative approaches to building cloud-native 5G design networks. These models can address specific challenges, such as tighter control over latency, data sovereignty, and regulatory compliance. However, they may lack the scalability and cost efficiency of public clouds. By carefully weighing these trade-offs, telecom operators can choose the deployment model that best suits their operational and strategic goals.
Core and Access Network Integration Considerations
1. Core Network Components
What: Operators need to decide how to distribute 5G core network functions like AMF, SMF, and UPF between central public cloud regions and edge zones to balance performance and cost.
Why: Proper placement ensures low-latency communication, scalability, and cost efficiency while meeting QoS requirements for diverse applications.
2. Access Network Components
What: Evaluate the deployment of CU functions on public cloud platforms while ensuring DU functions are hosted on private cloud or on-premises environments with specialized hardware for performance reasons.
Why: DUs require low-latency and high-performance computing that public clouds cannot reliably provide, while CUs can benefit from the scalability and flexibility of public cloud 5G deployments.
3. Geographical Considerations
What: Decide the geographic placement of data centers, edge zones, and critical components like UPF to optimize latency, cost, data sovereignty, and regulatory compliance requirements.
Why: Proper placement mitigates latency concerns, ensures regional coverage, reduces backhaul traffic, and ensures compliance with data governance laws and local regulatory mandates.
Cloud and Computing Strategy Considerations
1. Role of Edge Computing in Low-Latency 5G Networks
What: Decide the placement of latency-sensitive workloads, such as IoT, AR/VR, and AI-driven applications, across edge zones and central regions.
Why: Ensures ultra-low latency and reduces backhaul costs while improving user experience for edge-heavy applications.
2. Hybrid Cloud Integration
What: Design seamless workflows between private and public cloud environments to support consistent operations.
Why: Hybrid models offer greater flexibility, enabling operators to keep sensitive workloads on private clouds while scaling on public clouds. If carefully architected, deploying AI models at the edge can optimize backhaul traffic costs by processing data locally.
3. Multi-Cloud Strategies for 5G
What: Assess the feasibility of leveraging multiple hyperscalers versus a single cloud provider for critical workloads.
Why: Minimizes vendor lock-in risks, increases resilience, and ensures regulatory compliance across different regions.
Operational and Automation Insight Considerations
1. Lifecycle Management for Cloud-Native NFs
What: Establish CI/CD pipelines and Kubernetes-based orchestration for deploying, scaling, and updating Network Functions (NFs).
Why: Ensures efficient fault recovery and scalability, reducing downtime and improving network reliability.
2. AI/ML Based Network Automation
What: Leverage hyperscalers AI/ML in Telecom Operations for predictive maintenance, anomaly detection, and auto-scaling.
Why: Optimizes resource utilization and ensures the network adapts dynamically to changing demands.
3. Service Assurance in a Cloud Environment
What: Build service-level assurance mechanisms into the architecture to monitor latency, jitter, and packet loss.
Why: Maintains quality of service (QoS) and ensures reliable performance in multi-tenant cloud environments.
Transport and Network Slicing for 5G Considerations
1. Segment Routing for Cloud-Native 5G Transport
What: Evaluate whether SR-MPLS or SRv6 fits better into the existing network and public cloud integration strategies.
Why: Enhances traffic engineering, scalability, and security in multi-tenant and hybrid cloud environments.
2. Network Slicing Strategies
What: Design and manage virtualized network slices with specific QoS, bandwidth, and latency tailored to customer requirements. Evaluate tools like AWS Network Manager, Google Cloud Network Connectivity Center, and Azure Virtual WAN to manage slicing at the transport layer.
Why: Ensures that Telcos can deliver differentiated services to enterprise customers while maintaining performance, isolation, and security across multi-tenant environments.
Security and Interoperability Considerations
1. Best Practices for 5G Security and Compliance
What: Integrate public cloud security features (e.g., encryption, identity management, threat detection) with telco-specific measures like signaling firewalls.
Why: Protects sensitive data and ensures compliance with regulatory standards in multi-tenant environments.
Advanced security strategies, such as zero-trust architectures, ensure that no user or device is automatically trusted, reducing attack surfaces. AI-driven threat detection further strengthens security by identifying anomalies and potential risks in real-time, ensuring proactive protection.
Advance Security Needs: Security frameworks must evolve to incorporate advanced measures like zero-trust architectures and AI-driven threat detection, ensuring robust protection for multi-tenant cloud-native environments.
2. Interoperability with Legacy Systems
What: Implement middleware or protocol converters to bridge compatibility gaps between 4G and proprietary systems.
Why: Ensures seamless coexistence and gradual transitions to cloud-native 5G architectures.
Observability and Monitoring Considerations
1. Observability and Monitoring
What: Build a tailored end-to-end observability in multi-cloud 5G networks that integrate hyperscaler tools (e.g., AWS CloudWatch, Google Cloud Monitoring, and Azure Monitor) with legacy systems.
Why: Ensures seamless monitoring and troubleshooting across multi-cloud environments, providing real-time insights into network performance.
Examples From Global Operators:
Telefónica Germany
Telefónica Germany successfully deployed its 5G core network on AWS, leveraging AWS CloudWatch and Kubernetes for lifecycle management and observability, along with edge zones for low-latency services. The multi-cloud strategy helped mitigate vendor lock-in, ensuring resilience and scalability.
Dish Wireless
Dish Wireless built a greenfield 5G network entirely on AWS, deploying core network functions in AWS regions and edge zones. Automation and advanced network slicing enabled tailored enterprise services like IoT and private 5G, demonstrating the potential of a fully cloud-native approach.
Conclusion
In designing 5G networks on public cloud platforms, telecom operators face both immense opportunities and significant challenges. By carefully considering aspects such as core and access network integration, leveraging edge computing, ensuring slice-aware orchestration, and embracing multi-cloud and hybrid strategies, Telcos can unlock the full potential of hyperscale platforms. With robust observability, lifecycle management, and AI-powered automation for telecom networks, the architectural foundation for 5G can deliver unparalleled agility, efficiency, and innovation. As network slicing emerges as a transformative capability, its integration with transport and NF layers will shape the next generation of tailored enterprise solutions.
Authors:
Vivek Tiwary, Vice President and Head of Network Services Business, Tata Elxsi
RajaGopalan Rajappa, CTO, Communication Technologies and Platforms, Tata Elxsi
