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Fujitsu Unveils Virtuora

Fujitsu Network Communications introduced the Virtuora Service Management and Orchestration (SMO) offering to enable intelligent, automated and adaptive service delivery over multi-layer, multi-vendor mobile networks, subnets, network slices and the cloud.

This unified, O-Cloud-enabled software solution provides lifecycle service orchestration, control and management across open RAN networks, and helps integrate and harmonize cloud infrastructure.

Early adoption of 5G services in sectors like healthcare, retail, agriculture, manufacturing, logistics, and gaming creates the need for new services, products, and digital experiences. Fujitsu helps operators transform their networks to meet these needs by evolving networks from closed and proprietary architectures to open radio access networks that offer interoperability, flexibility and innovation. To enable more adaptive, resilient service delivery across these open networks, the Fujitsu Virtuora SMO offering uses an inherently scalable, cloud-native microservices framework that supports 3GPP, O-RAN and TM Forum industry standards and interfaces.

The Virtuora SMO solution incorporates advanced analytics, artificial intelligence (AI) and machine learning (ML) capabilities to spark intelligent network automation, scalability, prediction and self-healing capabilities. By delivering policy-based inputs with user equipment (UE) centric strategies, this offering enables uniform quality of experience in dense multivendor mobile networks, improved agility, and optimized virtual functions in any environment.

The Virtuora SMO Network Slice Management Functions (NSMF) and Network Slice Subnet Management Functions (NSSMF) allow network planners, technicians and DevOps engineers to design, instantiate and operate cloud services in smart RAN, edge, transport and core networks, as well as network functions (xNFs) over virtual and cloud infrastructure-enabled environments. A non real-time RAN Intelligent Controller (Non-RT RIC) and rApps support responsive and rapid control, optimization and sustainability of physical and virtual network elements, and are fully integrated and harmonized with O-Cloud resources, including servers, databases and storage elements.

“Powered by 40 years of Fujitsu network experience and open architecture expertise, Virtuora Cloud Service Management and Orchestration applies intelligence, policy-based inputs, automation, powerful AI/ML and O-Cloud integration to extend the network from the data center to the cloud and beyond,” said Rod Naphan, CTO, Fujitsu Network Communications, Inc. “This offering delivers total lifecycle management to provide network operators and cloud providers with the keys to unlock the transformative business potential of 5G technologies.”

The Virtuora SMO offering uses common language and design principles, standard system information resources, as well as common data models including standards-based descriptors for services, resources and applications.

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Fujitsu Unveils Virtuora

Fujitsu Network Communications introduced the Virtuora Service Management and Orchestration (SMO) offering to enable intelligent, automated and adaptive service delivery over multi-layer, multi-vendor mobile networks, subnets, network slices and the cloud.

This unified, O-Cloud-enabled software solution provides lifecycle service orchestration, control and management across open RAN networks, and helps integrate and harmonize cloud infrastructure.

Early adoption of 5G services in sectors like healthcare, retail, agriculture, manufacturing, logistics, and gaming creates the need for new services, products, and digital experiences. Fujitsu helps operators transform their networks to meet these needs by evolving networks from closed and proprietary architectures to open radio access networks that offer interoperability, flexibility and innovation. To enable more adaptive, resilient service delivery across these open networks, the Fujitsu Virtuora SMO offering uses an inherently scalable, cloud-native microservices framework that supports 3GPP, O-RAN and TM Forum industry standards and interfaces.

The Virtuora SMO solution incorporates advanced analytics, artificial intelligence (AI) and machine learning (ML) capabilities to spark intelligent network automation, scalability, prediction and self-healing capabilities. By delivering policy-based inputs with user equipment (UE) centric strategies, this offering enables uniform quality of experience in dense multivendor mobile networks, improved agility, and optimized virtual functions in any environment.

The Virtuora SMO Network Slice Management Functions (NSMF) and Network Slice Subnet Management Functions (NSSMF) allow network planners, technicians and DevOps engineers to design, instantiate and operate cloud services in smart RAN, edge, transport and core networks, as well as network functions (xNFs) over virtual and cloud infrastructure-enabled environments. A non real-time RAN Intelligent Controller (Non-RT RIC) and rApps support responsive and rapid control, optimization and sustainability of physical and virtual network elements, and are fully integrated and harmonized with O-Cloud resources, including servers, databases and storage elements.

“Powered by 40 years of Fujitsu network experience and open architecture expertise, Virtuora Cloud Service Management and Orchestration applies intelligence, policy-based inputs, automation, powerful AI/ML and O-Cloud integration to extend the network from the data center to the cloud and beyond,” said Rod Naphan, CTO, Fujitsu Network Communications, Inc. “This offering delivers total lifecycle management to provide network operators and cloud providers with the keys to unlock the transformative business potential of 5G technologies.”

The Virtuora SMO offering uses common language and design principles, standard system information resources, as well as common data models including standards-based descriptors for services, resources and applications.

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In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...