The News: Cisco and NVIDIA announced plans to deliver AI infrastructure solutions for the data center that are targeted at easing deployment and management with the goal of enabling the massive computing powers that enterprises need in the AI era. Read the full press release on the Cisco website.
Cisco and NVIDIA Ease Enterprise Adoption of AI Infrastructure
Analyst Take: Cisco and NVIDIA are collaborating to offer enterprises cloud-based and on-premises AI infrastructure, networking, and software solutions, including infrastructure management, secure AI infrastructure, observable AI solutions, and access to NVIDIA AI Everywhere software that supports the building and deployment of advanced AI and generative AI workloads.
Cisco and NVIDIA are adroitly addressing growing enterprise demand for integrated AI networking and AI hosting solutions. The key driver is that enterprises are fundamentally committed to avoiding putting their intellectual property (IP) and mission-critical data onto cloud-based public AI models. To protect their data without compromise, enterprises are prioritizing the hosting of AI workloads, integral to their AI infrastructure builds.
AI Infrastructure Focus Represent Deeper Partnership
With their alliance now focusing on accelerating enterprise adoption of AI infrastructure, I see the Cisco-NVIDIA alliance as a deeper relationship now. For starters, Cisco and NVIDIA have already been partners for several years. What is different is that now NVIDIA’s Tensor Core GPUs are embedded in Cisco’s M7 generation of UCS rack and blade servers.
Moreover, the joint validated reference architecture via Cisco Validated Designs (CVDs) and the availability of NVIDIA AI Enterprise on Cisco’s global price list as well as the enlistment of Cisco Networking Cloud, Cisco Observability Platform, and digital experience monitoring capabilities all demonstrate the strategic nature of the announcement indicating an enduring alliance. Specifically, the price listing incentives sales teams to also push NVIDIA AI Enterprise solutions.
Already NVIDIA targets AI enterprise use cases by combining its DGX BasePOD reference architecture with software and tools from the NVIDIA AI Enterprise software suite aimed at enabling enterprises to build their own AI Center of Excellence, as I see many enterprises are expanding their recruitment of AI specialists to address ongoing AI and data science skill shortages.
Cisco emphasizes how its AI enterprise portfolio provides the visibility essential to fueling AI-driven insights that span applications, security, devices, networks, and the Internet. This includes its recent introduction of model observability to monitor models and APIs so that customers can obtain insights such as more accurate cost management. Plus, as AI’s role in software creation expands, the demand for observability increases, since AI-generated software may be prone to errors. Moreover, Cisco is strategically committed to making AI pervasive in Cisco Security Cloud, augmenting workforce inputs to help close the gap between cybersecurity intent and outcomes, especially as cyberattacks continue to evolve in sophistication.
The InfiniBand and Ethernet Dimensions
From my view, the Cisco alliance refresh does not signify that NVIDIA is backing away from InfiniBand in the near term. For starters, InfiniBand is integral to NVIDIA’s networking business $10B annual run rate. When it comes to AI/ML workloads at the data center, InfiniBand technology is delivering and fulfilling the latency and bandwidth requirements of key customers such as Microsoft.
Beyond the near term, I see NVIDIA as hedging somewhat more against its InfiniBand cash cow as the hyperscalers including Amazon Web Services (AWS), Azure, Google Cloud, and Meta are actively investing in and focusing portfolio development resources to build their own AI chips as well as investing more in Ethernet-centric solutions. Plus, industry-wide initiatives such as the Ultra Ethernet Consortium point are focused on addressing AI workloads indicating alignment with the industry trend toward broader adoption of Ethernet for meeting future AI workload requirements. Naturally Cisco is a robust Ethernet solutions channel partner in this vein.
The main competition is extensive including Cisco’s data center server and switching rivals such as Arista, Juniper, HPE/Aruba, Broadcom/VMware, Dell, and Extreme. For NVIDIA, the move counters AMD Instinct MI300 and Intel GPU Max series moves as well as the emerging hyperscaler GPU products. Among hyprerscaler AI chip development missions, Meta’s new Artemis AI chip comes to mind. The alliance helps Cisco secure more mindshare in the tightly contested data center switching segment, especially as the competition focuses in on AI-focused portfolio development and marketing prioritization. It also helps pre-empts the new portfolio pending merger between HPE and Juniper which heavily emphasized Juniper’s AI portfolio assets, especially Mist AI, as a prime motivator for the $14 billion deal, reinforced by Juniper’s recent AI-Native Networking Platform launch.
Key Takeaway: Cisco NVIDIA Ready to Spur Enterprise AI Infrastructure Builds and Expansion
The Cisco NVIDIA alliance announcement specifically targets the enterprise space, as reinforced by the availability of NVIDIA AI Enterprise on Cisco’s global price list. As such, the greatest near-term impact will be felt in the enterprise realm. This can help accelerate business and operational outcomes from ongoing investments in AI and GenAI by streamlining the channel relation across Cisco and NVIDIA as well as taking advantage of solutions purpose developed for heavy lifting AI workloads.
For cloud providers, Europe’s ClusterPower is on onboard, indicating that cloud providers who are targeting the enterprise space can benefit by offering a proposition that can improve AI workload performance and latency across data center and edge environments. As such, I believe the strengthened Cisco NVIDIA alliance can play an integral role in accelerating enterprise transition and re-architecting to AI networking vital to deploying, managing, and securing AI solutions at scale.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
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Author Information
Ron is an experienced, customer-focused research expert and analyst, with over 20 years of experience in the digital and IT transformation markets, working with businesses to drive consistent revenue and sales growth.
Ron holds a Master of Arts in Public Policy from University of Nevada — Las Vegas and a Bachelor of Arts in political science/government from William and Mary.
