Challenges and Mitigation Strategies for Running 5G on Public Cloud

Leverage Edge Computing for 5G: Deploy hyperscaler edge zones to bring compute resources closer to end-users, reducing round-trip times for latency-sensitive applications.

Hybrid Architectures: Combine public cloud with on-premises edge deployments to balance latency requirements and resource availability.

Multi-Region Redundancy: Use multi-region deployments to ensure service continuity during outages.

Cloud-Native 5G Network Resilience: Implement redundancy, failover mechanisms, and self-healing capabilities within cloud-native architectures.

Customized Monitoring Solutions: Develop tools that provide telco-specific KPIs, such as latency, jitter, and packet loss.

AI/ML for 5G Performance Optimization: Use predictive analytics to identify and resolve performance bottlenecks in 5G cloud networks.

Dedicated Instances: Opt for dedicated cloud instances to avoid resource contention with other tenants.

Resource Reservation: Use reservation and prioritization features offered by hyperscalers to allocate consistent resources for critical workloads.

Modular Architectures: Use containerized and modular architectures to decouple upgrades from core operations.

Agile Testing Pipelines: Establish pipelines for CI/CD for 5G core network upgrades to validate and implement updates rapidly.

Protocol Translation Tools: Use standardized protocol conversion tools to bridge legacy systems with cloud-native environments.

Data Optimization: Optimize and migrate legacy data for hyperscaler storage formats.

Network Orchestration for 5G Cloud Integration: Develop orchestration platforms to manage network slicing efficiently.

Standardized Deployments: Collaborate with hyperscalers to adopt standardized edge computing solutions.

Adopt Multi-Cloud 5G Strategy: Deploy workloads across multiple hyperscalers to diversify dependencies and maintain flexibility.

Leverage Open Standards: Use open-source tools and frameworks that ensure portability and minimize proprietary dependencies.

Build Abstraction Layers: Create abstraction layers that decouple applications from specific hyperscaler APIs, simplifying transitions.

Sandbox Environments: Use test beds to validate multi-vendor integrations before full-scale deployment.

For Handover Latency:

Edge Caching: Cache critical data (e.g., user sessions, active slice data) closer to the end-user for faster access.

Predictive Pre-Fetching: Use AI/ML algorithms to anticipate transitions and pre-load necessary resources.

For Data Consistency:

Global Transaction Frameworks: Deploy transaction frameworks to ensure atomicity and consistency of updates across distributed systems.

Eventual Consistency Mechanisms: Adopt eventual consistency models for non-critical data, ensuring service continuity while synchronizing updates.

For Metadata Access Latency:

API Gateway Optimization: Streamline access to metadata APIs by reducing hops and optimizing caching layers.

Localized Data Storage: Store sensitive user data within the region to comply with data sovereignty laws.

Zero-Trust Security in 5G Networks: Implement strong authentication mechanisms and continuous security monitoring.

Geo-Fencing Capabilities: Implement geo-fencing to manage cross-border data flows.

Cost Management Tools: Use hyperscaler tools to monitor and optimize cloud resource usage. In addition to cost benefits, hyperscaler platforms reduce energy consumption through optimized infrastructure management, contributing to telcos' environmental sustainability goals.

Predictable Pricing Models: Negotiate long-term contracts with fixed pricing structures to ensure cost stability and avoid unexpected price hikes.

Training Programs: Invest in reskilling programs to equip teams with cloud-native expertise.