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Cisco unveils integrated edge platform for AI

Cisco is offering an integrated package of networking, compute and storage aimed at helping enterprise customers more efficiently handle data from AI and other workloads at the edge, where the data is typically created. The new platform…

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Cisco is offering an integrated package of networking, compute and storage aimed at helping enterprise customers more efficiently handle data from AI and other workloads at the edge, where the data is typically created.





The new platform – Cisco Unified Edge – includes a 25G network uplink and is powered by an Intel Xeon System On a Chip (SOC) central processing unit. The 3U, 19-inch chassis features five front-facing slots for compute nodes, GPUs and future modules that may include a networking node for routing, switching, and secure access service edge (SASE) capabilities. It can support up to 120 terabytes of storage and features redundant power and cooling, according to Cisco. 





On the security side, Cisco Unified Edge supports zero-trust technology for access, segmentation, and to protect applications and AI models, Jeremy Foster, Cisco senior vice president and general manager, told Network World.





In addition, there are multiple packages from Cisco’s security portfolio that can be added, Foster said. “We can include things like Isovalent so that they have a secure container environment if they’re, for example, using a Red Hat-type deployment.”





The platform can be centrally managed by Cisco’s cloud-based Intersight platform, which lets IT teams scale deployments to thousands of locations, shift focus from administrative tasks to business outcomes, and employ edge-optimized infrastructure management capabilities such as fleet management, full-stack solution blueprints, and zero-touch provisioning, according to Foster.





“Across industries, AI is moving closer to where data is born,” Foster wrote in a blog post about the news. “By 2027, 75% of enterprise data will be created and processed at the edge, as AI workloads shift from centralized model training to real-time inference. In retail, drive-through operations rely on inferencing to optimize order throughput and customer experience. In manufacturing, machine vision systems depend on low-latency analytics to monitor assets and prevent downtime,” Foster stated.





Announced at Cisco’s Partner Summit, Unified Edge will likely be part of many third-party packages that can be configured in a variety of ways, Cisco stated.





“The platform is customer definable. For example, if a customer has a workload and they’ve decided they want to use Nutanix, they can go ahead and work with their channel partner to configure the server with the amount of memory and storage that they would want. Then we are going to ship that customized, well-unified edge system,” Foster said. “It’s critical for edge locations and the customers that we’re working with, that they have flexibility and can easily work with someone in the independent software vendor ecosystem around edge and that customers can grow as their needs increase over the next 10 years with the options available in this chassis.”





Flexibility is key as enterprises grow not only AI applications but also other edge applications, experts say.





“A highly distributed IT ecosystem introduces new challenges in building, deploying, and maintaining remote infrastructure. The scale and reach of edge deployments creates a significant burden on IT organizations,” IDC wrote in a white paper on edge computing. “Without rigorous management, data security is at risk. And edge environments often come with unavoidable physical security risks. For these reasons, infrastructure that is designed to streamline and simplify deployment is preferred. Modernized edge platforms automate management, ensuring that configurations remain intact and that systems can remain updated even when no IT staff is physically present.”





“There are a variety of factors driving edge transformation. Most notable are AI workloads, and particularly those that are latency sensitive, such as real-time data processing for fraud detection, machine sensors and video analytics in manufacturing for quality control and predictive maintenance, and in-store retail analytics to create new customer experiences,” IDC wrote. “New AI workloads at the edge require high performance and better resilience, with critical operations and business processes relying on edge infrastructure. Greater efficiency and cost optimization are key benefits and will drive continued deployment of new edge use cases.”





Cisco Unified Edge can be ordered now and will ship in December, Foster said.


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