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Cisco and NVIDIA Partners on AI Infrastructure for Data Centers

Cisco and NVIDIA announced plans to deliver AI infrastructure solutions for the data center that are easy to deploy and manage, enabling the massive computing power that enterprises need to succeed in the AI era.

"AI is fundamentally changing how we work and live, and history has shown that a shift of this magnitude is going to require enterprises to rethink and re-architect their infrastructures," said Chuck Robbins, Chair and CEO, Cisco. "Strengthening our great partnership with NVIDIA is going to arm enterprises with the technology and the expertise they need to build, deploy, manage, and secure AI solutions at scale."

"Companies everywhere are racing to transform their businesses with generative AI," said Jensen Huang, founder and CEO of NVIDIA. "Working closely with Cisco, we're making it easier than ever for enterprises to obtain the infrastructure they need to benefit from AI, the most powerful technology force of our lifetime."

Cisco, with its industry-leading expertise in Ethernet networking and extensive partner ecosystem, together with NVIDIA, the inventor of the GPU that fueled the AI boom, share a vision and commitment to help customers navigate the transitions for AI with highly secure Ethernet-based infrastructure.

Cisco and NVIDIA have offered a broad range of integrated product solutions over the past several years across Webex collaboration devices and data center compute environments to enable hybrid workforces with flexible workspaces, AI-powered meetings and virtual desktop infrastructure. The companies are now deepening their partnership in the data center to enable enterprise customers with scalable and automated AI cluster management, automated troubleshooting, best-in-class customer experiences, and more. Highlights include:

Cisco and NVIDIA Integrated Data Center Solutions available now:

- NVIDIA's newest Tensor Core GPUs are available in Cisco's M7 generation of UCS rack and blade servers, including Cisco UCS X-Series and UCS X-Series Direct, to enable optimal performance across a broad array of AI and data-intensive workloads in the data center and at the edge

- NVIDIA AI Enterprise, which includes software frameworks, pretrained models and development tools for more secure, stable and supported production AI is now available on Cisco's global price list.

- Jointly validated reference architectures through Cisco Validated Designs (CVDs) make it simple to deploy and manage AI clusters at any scale in a wide array of use cases spanning virtualized and containerized environments, with both converged and hyperconverged options. CVDs for FlexPod and FlashStack for Generative AI Inferencing with NVIDIA AI Enterprise will be available this month, with more to follow.

- Supporting Cisco Networking Cloud: Cisco simplified AI infrastructure management and operations through both on-premises and cloud-based management with Cisco Nexus Dashboard and Cisco Intersight.

- Digital Experience Monitoring: With AI workloads and data in the public cloud, on premises and across multiple data centers, ThousandEyes provides Digital Experience Monitoring to provide AI-driven insights and automated remediation of problems that occur anywhere across the cloud to on-premises networks.

- The Cisco Observability Platform uses AI capabilities to contextualize and correlate real-time telemetry across domains, so organizations can better attain the visibility, insights and actions to improve digital experiences.

- Partners Reducing Risks: As organizations plan to successfully adopt AI and automation, they will look to Cisco's global ecosystem of partners to advise, support and guide them.

"As enterprises look to transform their businesses with AI, they must understand the unique demands that AI workloads place on data center infrastructure," said Vijay Bhagavath, Vice President, Cloud & Data Center Networks at IDC Research. "The Cisco and NVIDIA partnership brings together two trusted brands with complementary technologies to enable customers to realize the full potential of AI with a wide range of performance-optimized Ethernet-based infrastructure. "

Availability: 2Q Calendar Year; Solutions sold through Cisco Channel partners.

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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 ...

Cisco and NVIDIA Partners on AI Infrastructure for Data Centers

Cisco and NVIDIA announced plans to deliver AI infrastructure solutions for the data center that are easy to deploy and manage, enabling the massive computing power that enterprises need to succeed in the AI era.

"AI is fundamentally changing how we work and live, and history has shown that a shift of this magnitude is going to require enterprises to rethink and re-architect their infrastructures," said Chuck Robbins, Chair and CEO, Cisco. "Strengthening our great partnership with NVIDIA is going to arm enterprises with the technology and the expertise they need to build, deploy, manage, and secure AI solutions at scale."

"Companies everywhere are racing to transform their businesses with generative AI," said Jensen Huang, founder and CEO of NVIDIA. "Working closely with Cisco, we're making it easier than ever for enterprises to obtain the infrastructure they need to benefit from AI, the most powerful technology force of our lifetime."

Cisco, with its industry-leading expertise in Ethernet networking and extensive partner ecosystem, together with NVIDIA, the inventor of the GPU that fueled the AI boom, share a vision and commitment to help customers navigate the transitions for AI with highly secure Ethernet-based infrastructure.

Cisco and NVIDIA have offered a broad range of integrated product solutions over the past several years across Webex collaboration devices and data center compute environments to enable hybrid workforces with flexible workspaces, AI-powered meetings and virtual desktop infrastructure. The companies are now deepening their partnership in the data center to enable enterprise customers with scalable and automated AI cluster management, automated troubleshooting, best-in-class customer experiences, and more. Highlights include:

Cisco and NVIDIA Integrated Data Center Solutions available now:

- NVIDIA's newest Tensor Core GPUs are available in Cisco's M7 generation of UCS rack and blade servers, including Cisco UCS X-Series and UCS X-Series Direct, to enable optimal performance across a broad array of AI and data-intensive workloads in the data center and at the edge

- NVIDIA AI Enterprise, which includes software frameworks, pretrained models and development tools for more secure, stable and supported production AI is now available on Cisco's global price list.

- Jointly validated reference architectures through Cisco Validated Designs (CVDs) make it simple to deploy and manage AI clusters at any scale in a wide array of use cases spanning virtualized and containerized environments, with both converged and hyperconverged options. CVDs for FlexPod and FlashStack for Generative AI Inferencing with NVIDIA AI Enterprise will be available this month, with more to follow.

- Supporting Cisco Networking Cloud: Cisco simplified AI infrastructure management and operations through both on-premises and cloud-based management with Cisco Nexus Dashboard and Cisco Intersight.

- Digital Experience Monitoring: With AI workloads and data in the public cloud, on premises and across multiple data centers, ThousandEyes provides Digital Experience Monitoring to provide AI-driven insights and automated remediation of problems that occur anywhere across the cloud to on-premises networks.

- The Cisco Observability Platform uses AI capabilities to contextualize and correlate real-time telemetry across domains, so organizations can better attain the visibility, insights and actions to improve digital experiences.

- Partners Reducing Risks: As organizations plan to successfully adopt AI and automation, they will look to Cisco's global ecosystem of partners to advise, support and guide them.

"As enterprises look to transform their businesses with AI, they must understand the unique demands that AI workloads place on data center infrastructure," said Vijay Bhagavath, Vice President, Cloud & Data Center Networks at IDC Research. "The Cisco and NVIDIA partnership brings together two trusted brands with complementary technologies to enable customers to realize the full potential of AI with a wide range of performance-optimized Ethernet-based infrastructure. "

Availability: 2Q Calendar Year; Solutions sold through Cisco Channel partners.

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Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

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 ...