{"id":293489,"date":"2025-06-14T21:04:57","date_gmt":"2025-06-14T21:04:57","guid":{"rendered":"https:\/\/peraltafinancing.com\/5g-technology\/cloud-native-telco-transformation-insights-from-t-systems\/"},"modified":"2025-06-14T21:04:57","modified_gmt":"2025-06-14T21:04:57","slug":"cloud-native-telco-transformation-insights-from-t-systems","status":"publish","type":"post","link":"https:\/\/fivemor.com\/?p=293489","title":{"rendered":"Cloud Native Telco Transformation Insights from T-Systems"},"content":{"rendered":"


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The journey to becoming a cloud-native telco is not just a buzzword exercise. It requires a full-scale transformation of networks, business models, and operating cultures. At Mobile Europe\u2019s Becoming a Cloud-Native Telco virtual event, Richard Simon, CTO at T-Systems International, outlined how telcos are grappling with this change, sharing insights from both successes and ongoing challenges.<\/p>\n

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Cloud-native is not just about adopting containers or orchestrating with Kubernetes. Richard Simon described it as a maturity model that demands strategic vision, architectural readiness, and cultural shift. The telco industry, long rooted in proprietary systems, is gradually moving towards software-defined infrastructure. Network Function Virtualisation (NFV) remains foundational, enabling operators to decouple traditional monolithic services and deliver them in a modular, digital-native manner\u2014whether in private data centres or public clouds.<\/p>\n

The industry is also seeing the rise of platform engineering. This evolution builds on DevOps and site reliability engineering (SRE) to create standardised internal developer platforms. These platforms reduce cognitive load for developers, increase consistency in toolchains and workflows, and enable a shift-left approach for operations and security. It is a critical step towards making innovation scalable and repeatable within telcos.<\/p>\n

The cloud-native ecosystem has exploded in scope, with the CNCF landscape illustrating the diversity and maturity of open source components now in use. Telcos, once cautious about community-led projects, are now not only consuming but also contributing to open source. This openness is pivotal for achieving agility and interoperability in a multivendor environment.<\/p>\n

With the increasing complexity of hybrid and multicloud strategies, avoiding vendor lock-in has become essential. Richard highlighted how telcos are optimising costs, improving resilience, and aligning workloads with the most suitable cloud environments. Multicloud is no longer a theoretical construct. It is operational reality. But with it comes the need for new thinking around cloud economics.<\/p>\n

Cloud financial operations are no longer limited to cost tracking. They now include strategic frameworks (FinOps), real-time cost management, and a growing focus on application profiling. Profiling looks at how software consumes cloud resources, guiding developers to write more efficient code and enabling cost-effective deployments.<\/p>\n

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While generative AI dominates headlines, the pace of adoption in telco is deliberate. Richard pointed out that while investment in GenAI is widespread, only a small fraction of deployments have reached production. Most telcos are still in proof-of-concept or pilot phases, reflecting the technical and regulatory complexity involved.<\/p>\n

Unlike some sectors, telcos face strict compliance requirements. GenAI inference stages\u2014when customer data is processed\u2014raise concerns around data sovereignty and privacy. As a result, telcos are exploring how to balance innovation with responsibility. Some are experimenting with fine-tuning foundational models internally, while others prefer to consume GenAI as a service, depending on use cases ranging from network automation to document processing.<\/p>\n

GenAI is a high-performance computing (HPC) workload. Training large models requires significant infrastructure, making decisions around build versus buy critical. Richard outlined three tiers of AI adoption: infrastructure-as-a-service for DIY approaches, foundation-model-as-a-service for fine-tuning, and software-as-a-service for fully hosted solutions. Each tier comes with trade-offs in control, cost, and complexity.<\/p>\n

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Looking ahead, three themes stood out in Richard\u2019s conclusions.<\/p>\n

First, the era of AI agents is beginning. These autonomous systems, capable of reasoning and acting across complex tasks, will be the next experimentation frontier. Pilots in 2025 and 2026 will pave the way for a broader agentic AI economy.<\/p>\n

Second, cloud economics continues to evolve. Operators must invest in cost visibility and governance rather than reactively scaling back cloud usage. The emergence of profiling and observability tooling is helping align cost with performance and business value.<\/p>\n

Third, sovereignty is rising in importance. Telcos must ensure control over data and infrastructure, not only to comply with regional regulations but also to maintain intellectual property and operational resilience. Sovereign cloud models, abstracted control planes, and localised inference infrastructure are becoming strategic imperatives.<\/p>\n

His complete talk is embedded below:<\/p>\n