Telco Cloud

Telco cloud refers to the cloud-native infrastructure operators use to run network functions as software, rather than on dedicated hardware — spanning private clouds, public-cloud partnerships, and hybrid models. It is the foundation for virtualized cores, cloud-native RAN, automation, and the agility 5G standalone demands. A defining trend is the deepening relationship between operators and hyperscalers, who increasingly host or support network workloads, raising strategic questions about control, cost, and dependency. For operators, telco cloud strategy shapes how flexible, scalable, and cost-efficient their networks can be; for vendors and hyperscalers, it’s a major battleground. This channel covers telco cloud across private, public, and hybrid models — cloud-native network functions, operator-hyperscaler partnerships, and the platforms involved — with analysis of how cloud is reshaping operator architecture, economics, and competitive dynamics.

Deutsche Telekom Switches to Mavenir for 5G Standalone Core

Deutsche Telekom made cloud jump from Ericsson to Mavenir in 5G
Deutsche Telekom's transition from Ericsson to Mavenir as its primary 5G standalone core provider represents a fundamental rethinking of how Tier 1 operators architect and operate networks in the cloud-native era. Mavenir now carries all standalone 5G traffic in Germany, while Ericsson handles legacy 4G and non-standalone 5G. Driven by the Horizontal TelCo Cloud initiative, the shift has already produced measurable results including 65% energy savings in live testing and three commercial network slicing deployments, with Apple FaceTime set to leverage these capabilities at consumer scale via iOS 26.

ETSI OpenOP Release 1: 6G-Ready Operator Platform

ETSI OpenOP Release 1: 6G-Ready Operator Platform
ETSI has introduced OpenOP Release 1 as an open-source operator platform for telco cloud, designed to standardize capability exposure and federation at the edge while creating a practical bridge from 5G-Advanced to early 6G experimentation. Networks are becoming software-first and distributed, but operators still face fragmented exposure of network capabilities and inconsistent approaches to multi-operator edge. OpenOP targets this gap with a standards-aligned, open implementation that lets developers consume telecom capabilities via CAMARA APIs and deploy applications across federated edge zones. Release 1 provides a working, end-to-end baseline with integrated components for exposure, orchestration, federation, and AI-assisted intent, suitable for hands-on testing and integration.

MWC 2026 Keynote 2: Transforming Tomorrow’s Connected World

MWC 2026 Keynotes
Live Streamed on Mon, 2 Mar at 11:15 - 12:45 CET

Visionary voices from around the globe take the stage to reflect on the expanding scope of connectivity, from core networks to cloud platforms to the emerging capabilities that stretch beyond our planet. Join us to explore how the interplay of innovation, leadership and global collaboration can drive meaningful transformation. Discover how bold thinking and shared ambition can build on this momentum and redefine what is possible in an increasingly connected world.

TELUS Digital AI in Telecom: Scaled 20+ GenAI use cases on Fuel iX

TELUS Digital AI in Telecom: Scaled 20+ GenAI use cases on Fuel iX
TELUS Digital is using Mobile World Congress 2026 to move the AI-in-telecom conversation from pilots to proven production at scale. TELUS Digital reports processing more than two trillion tokens in 2025 through its Fuel iX generative AI platform for TELUS operations and customers. The portfolio spans AI for customer experience, application safety, and network modernization—built and battle-tested within TELUS before client rollout. The Network Design Services practice applies AI to planning and optimization while charting a path from legacy network stacks to cloud-native, automated environments.

Deutsche Telekom telco cloud cuts 5G core energy by up to 65%

Deutsche Telekom telco cloud cuts 5G core energy by up to 65%
Deutsche Telekom’s early live results showing up to 65% energy savings in its 5G core spotlight a pragmatic path to cut opex and carbon as traffic surges and standalone 5G scales. Operators have wrung out much of the easy efficiency from hardware refreshes; the next gains come from software-driven, demand-aware control. DT is applying that logic to the core, shifting components to run only when needed rather than idling at full power. The results are enabled by DT’s “Horizontal Telco Cloud,” a unified, standards-based platform that replaces fragmented stacks with one common layer for core services. Initial live-network tests have been completed, with broader rollout planned and further detail expected at MWC Barcelona 2026.

India’s AI stack needs AI-native networks: Ericsson CTO

India’s AI stack needs AI-native networks: Ericsson CTO
India’s AI agenda increasingly spans silicon, data platforms, models, and applications, with an intent to catalyze domestic innovation and contribute to global ecosystems. For telecom leaders, the message is clear: AI is not a bolt-on capability but a system-level transformation that touches RAN, core, transport, cloud, and the enterprise edge. The AI economy runs on connectivity—low-latency access to data, assured bandwidth, location-aware processing, and programmable control. The operators that can fuse connectivity, compute, and data into a cohesive platform will set the pace for India’s next wave of digital growth.

Singapore Thwarts UNC3886 Telco Attack, Boosting Telecom Security

Singapore Thwarts UNC3886 Telco Attack, Boosting Telecom Security
Singapore has confirmed an attempted cyber‑espionage campaign against its national telecom backbone, highlighting a rising class of APT activity aimed at network devices and virtualized cores rather than traditional IT endpoints. Singapore’s Cyber Security Agency (CSA) and Infocomm Media Development Authority (IMDA) disclosed that all four major operators—Singtel, StarHub, M1 and Simba Telecom—were targeted by UNC3886 in incidents last year. The threat actor gained limited access to segments of telco systems and exfiltrated a small volume of network‑related technical data. There was no service disruption, no personal data exposure and, critically, sensitive and segregated systems (including 5G networks) were not compromised.

FutureNet World 2026

Start: April 21, 2026
End: April 22, 2026
Venue: Intercontinental O2 London
Location: London, UK

ElevenLabs raises $500M for telco AI

ElevenLabs raises $500M for telco AI
ElevenLabs raised $500 million in Series D funding at an $11 billion valuation, led by Sequoia Capital with continued participation from Andreessen Horowitz and ICONIQ, and new backing from Lightspeed, Evantic Capital and BOND alongside existing investors. The company says it has surpassed key ARR milestones and reported strong enterprise adoption across sectors through 2025, with telecom emerging as a priority vertical as operators seek to modernize legacy IVR and contact center stacks. Conversational agents can replace keypad IVRs with natural dialogue that recognizes intent, confirms identity, retrieves context and executes actions across channels.

The Future of Telecom B2B: From Connectivity Providers to Intelligent Digital Ecosystem Enablers

The global telecom B2B landscape is undergoing a fundamental shift driven by AI, automation, private 5G networks, and cloud-native architectures. Telco's can no longer survive by selling connectivity alone—they must evolve into strategic technology partners delivering scalable, intelligent, and composable services. This article explores: The rising market opportunity for B2B in telecom 1.Why private 5G, AI, cloud, and edge computing are reshaping enterprise demand 2.How Global Business Services (GBS), composable commerce, and API-first strategies enable scalability 3.Six strategic AI pillars transforming the telecom value chain 4.New monetization pathways including AI-as-a-Service and Open Gateway APIs

Palo Alto Networks to Acquire Chronosphere for AI Observability

Palo Alto Networks to Acquire Chronosphere for AI Observability
Palo Alto Networks is buying Chronosphere to fuse cost-efficient, large-scale observability with AI-driven automation for modern cloud and AI data centers. Palo Alto Networks agreed to acquire Chronosphere for approximately $3.35 billion in a mix of cash and replacement equity, with closing expected in the second half of PANW’s fiscal 2026 (ending July 31). Chronosphere brings a next-generation observability architecture and telemetry pipeline built for scale and cost control. Together, they aim to turn observability from passive dashboards into autonomous, governed remediation that blends performance and security insights.

AI Data Centers: How Much Renewable Energy?

IEA: $580B will go to data centers, surpassing oil. Can solar, storage, and new microgrids deliver 24/7 carbon-free power for the AI boom?
Renewables are emerging as the default option for new AI campuses, but the share that is truly carbon-free around the clock will hinge on siting, storage, and market design. Annual REC matching is no longer sufficient for leading buyers; the bar is shifting toward hourly, 24/7 carbon-free energy matching initiatives. Yet diurnal and seasonal variability limits how much of a site’s load can be met by solar and batteries alone, especially in non-sunny regions or during prolonged weather events. Expect mixed portfolios: on-site renewables and batteries, off-site PPAs (solar and wind), emerging long-duration storage, and grid purchases backed by hourly certificates where available.

Frequently Asked Questions

What is ‘Telco Cloud,’ and how is it different from regular cloud computing?
Telco Cloud refers to cloud computing infrastructure specifically built or adapted to run telecom network functions, distinguishing it from general-purpose public cloud platforms that businesses across many industries use for ordinary computing needs like web hosting or data storage. The key difference is that telecom network functions often have far stricter requirements around latency, reliability, and real-time performance than typical enterprise cloud workloads, since a delay or failure in a network function can directly disrupt live calls, data sessions, or critical infrastructure services for potentially millions of subscribers simultaneously. Telco Cloud platforms are engineered specifically to meet these more demanding requirements, whether built by traditional telecom vendors, run on a major public cloud provider’s infrastructure, or some hybrid combination of both approaches.
Why are major hyperscalers like AWS, Microsoft, and Google increasingly involved in Telco Cloud?
Major hyperscalers have increasingly built telecom-specific offerings, like Microsoft’s Azure for Operators and Google Cloud’s telecom-focused infrastructure, recognizing that operators represent a substantial, largely untapped customer base for cloud computing services beyond the hyperscalers’ traditional enterprise customer base. For operators, partnering with an established hyperscaler can reduce the cost and complexity of building and maintaining their own data center infrastructure from scratch, while gaining access to the hyperscaler’s broader expertise in cloud computing and AI infrastructure. This represents a notable shift in industry dynamics, since these partnerships position hyperscalers as increasingly important infrastructure partners, a role traditionally filled almost entirely by telecom-specific equipment vendors like Ericsson, Nokia, and Huawei.
What does the shift from ‘cloud-native’ to ‘AI-native’ infrastructure actually mean?
The shift from cloud-native to AI-native describes infrastructure designed from the ground up to run AI workloads efficiently alongside traditional network functions, rather than treating AI as a separate, bolted-on capability running on infrastructure originally designed purely for conventional network functions. This involves incorporating specialized AI-optimized hardware, like GPUs, directly into the telco cloud platform’s design, and building software architectures specifically capable of supporting increasingly autonomous AI agents that can monitor and manage network operations directly. Industry vendors, including Huawei with its TICC and AgenticCore platforms, have specifically marketed offerings around this AI-native framing, positioning it as the next meaningful evolution of telco cloud architecture beyond the original cloud-native virtualization shift.
What challenges do operators face when migrating network functions to Telco Cloud?
Migrating network functions to telco cloud infrastructure presents several recurring challenges. Ensuring virtualized functions actually meet the strict performance and reliability requirements telecom services demand requires careful testing and validation, since a function that performs adequately in a general-purpose cloud environment might not automatically meet the more demanding latency standards telecom-grade services require. Integration across multiple cloud environments and vendors, particularly for operators using a mix of their own infrastructure and one or more hyperscaler partnerships, adds meaningful operational complexity. There’s also a workforce dimension, since network engineering teams historically focused on managing dedicated hardware need different skills to effectively manage cloud-based, software-defined infrastructure.
How does Telco Cloud relate to Open RAN and network slicing?
Telco Cloud provides the underlying computing infrastructure that both Open RAN and network slicing depend on to actually function in practice. Open RAN’s disaggregated, multi-vendor radio network components frequently run as software on telco cloud infrastructure rather than dedicated hardware, meaning a robust telco cloud platform is often a practical prerequisite for a successful Open RAN deployment. Network slicing similarly depends on telco cloud’s flexible, virtualized infrastructure to actually create and manage multiple distinct virtual networks running on shared physical resources, since the dynamic resource allocation slicing requires is fundamentally a cloud computing capability rather than something a fixed, dedicated hardware architecture could practically support at the same level of flexibility.
What’s a concrete example of an AI-native telco cloud platform in deployment today?
Huawei’s TICC, short for Telecom Intelligent Cloud Core, and its accompanying AgenticCore platform represent a concrete example of vendors building infrastructure specifically designed to support autonomous AI agents managing network operations directly, alongside more traditional virtualized network functions, on shared underlying infrastructure. These platforms are designed to support increasingly sophisticated AI capabilities, including agents that can independently monitor network performance, predict and respond to emerging issues, and make operational adjustments with less direct human oversight than earlier generations of network management software required. While still relatively early in broader commercial deployment, these AI-native offerings reflect the direction major telecom equipment vendors are actively pushing their telco cloud product lines toward.
Do operators build their own Telco Cloud infrastructure, or rely entirely on vendors?
It varies considerably by operator and specific use case. Some larger, well-resourced operators build and maintain significant portions of their own telco cloud infrastructure internally, often using open-source software frameworks and components from multiple vendors rather than relying entirely on a single external provider. Others rely more heavily on partnerships with hyperscalers like Microsoft or Google, or with telecom equipment vendors offering pre-packaged telco cloud platforms, particularly for capabilities like AI infrastructure where building genuinely competitive internal capability from scratch would require substantial investment. Many operators ultimately pursue a hybrid approach, maintaining direct control over certain core, mission-critical infrastructure while relying on external partners for less differentiating capabilities.
What role does Red Hat and open-source software play in Telco Cloud?
Red Hat, primarily through its OpenShift platform and broader open-source software portfolio, has become a significant player in telco cloud infrastructure, providing operators and telecom equipment vendors with an open-source foundation for building and running virtualized network functions rather than relying entirely on proprietary, vendor-specific software stacks. This open-source approach appeals to operators partly because it reduces dependency on any single proprietary vendor’s specific technology stack, and partly because it benefits from a broader community of contributors across the technology industry beyond telecom specifically. Several major telecom equipment vendors and operators have built their own telco cloud offerings on top of Red Hat’s open-source foundation, reflecting how significant open-source software has become as an underlying building block for telco cloud infrastructure broadly.

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