Catch Cisco\u2019s thought leaders on the main stage and beyond<\/h2>\n The shift toward AI-ready infrastructure requires new frameworks and operational models. Our experts will be sharing actionable insights across several key sessions:<\/p>\n
When Agents Run the Network: Security, Access, and the AI Data Center Ahead<\/strong>Main Stage Keynote | May 13<\/em>From AI Ambition to AI Infrastructure: Your Blueprint to Success for Enterprise Networks<\/strong>Cisco Triple-T Session | May 13<\/em>Hybrid AI Infrastructure and AgenticOps Security in Practice<\/strong>Panel Session | May 14<\/em>Defending Against Adversarial AI Agents \u2013 From Digital Darwinism to Guardrails<\/strong>Panel Session | May 13<\/em>Innovations powering the AI enterprise<\/h2>\n At ONUG, we will highlight the latest Cisco innovations designed to scale out and scale across for the agentic era, ensuring your transition to production AI is seamless and secure.<\/p>\n
Unprecedented scale and simplicity<\/h2>\n AI workloads generate traffic intensity that pushes conventional networks to the breaking point. We are answering this challenge with Cisco Nexus One, powered by the Silicon, Systems, Optics, Software, Operational Models, Security and Observability.<\/p>\nFigure 1: Cisco Nexus One<\/figcaption><\/figure>\nFurthermore, we are leveraging AgenticOps<\/strong> via AI Canvas<\/strong>, bringing AI-driven troubleshooting and optimization to your enterprise infrastructure using the Cisco Deep Network Model.<\/p>\nTo ensure every AI job runs at peak efficiency, Cisco\u2019s architecture brings together advanced AI job monitoring, intelligent mixed mode load balancing, and built-in GPU optimization across the fabric. Real-time monitoring provides visibility into job status and resource allocation, so infrastructure teams can identify and resolve congestion or bottlenecks before they impact performance. Mixed mode load balancing dynamically shifts workloads across network paths and clusters for optimal flow, minimizing latency and maximizing throughput\u2014even during periods of unpredictable demand. Combined with deep integration into GPU orchestration, this enables organizations to boost compute utilization, speed up AI model convergence, and ultimately drive greater business value from every GPU investment.<\/p>\n
The result: your AI workloads are executed more efficiently, reliably, and with agility, empowering you to move faster from proof-of-concept to impactful production deployments.<\/p>\n
Deep, pervasive security for AI workloads<\/h2>\n You cannot scale AI without securing it. Traditional security models often create bottlenecks or tax the very CPUs needed for AI processing. We are changing the game with a unified security approach embedded directly into the network.<\/p>\n
Our Cisco N9300 Series Smart Switches<\/strong> fuse networking and security, supporting L4 segmentation to ensure policies follow the workload. Combined with Cisco Hypershield, organizations gain air-gapped, distributed segmentation across the fabric. To protect against vulnerabilities in real time, Cisco Live Protect<\/strong> instantly deploys eBPF-based shields without requiring reboots or downtime.<\/p>\nFor the ultimate in server-level security, we are showcasing our integration of Cisco Hybrid Mesh Firewall with NVIDIA BlueField DPUs<\/strong>. By running stateful segmentation and firewall policies directly on the DPU, we deliver line-rate protection without compromising GPU or CPU performance. This ensures your AI front-end fabrics remain secure, isolated, and highly efficient.<\/p>\nLet\u2019s build the future of AI together<\/h2>\n The AI revolution is here, and the network is its foundation. Whether you need to scale massive GPU clusters, secure multi-tenant AI environments, or simplify operations with agentic automation, Cisco has the blueprint to get you there.<\/p>\n
We look forward to being a part of the ONUG community and seeing you in Dallas. Be sure to attend our sessions and connect with our experts to discuss your AI networking and security strategies.<\/p>\n
\n<\/blockquote><\/div>\n
Enterprise AI is moving rapidly from piloting to production. As organizations deploy larger models and agentic AI systems, they quickly realize that AI is only […]<\/p>\n","protected":false},"author":1,"featured_media":17032,"comment_status":"","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[],"class_list":["post-17031","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology"],"_links":{"self":[{"href":"https:\/\/dmsretail.com\/RetailNews\/wp-json\/wp\/v2\/posts\/17031","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dmsretail.com\/RetailNews\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dmsretail.com\/RetailNews\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dmsretail.com\/RetailNews\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/dmsretail.com\/RetailNews\/wp-json\/wp\/v2\/comments?post=17031"}],"version-history":[{"count":0,"href":"https:\/\/dmsretail.com\/RetailNews\/wp-json\/wp\/v2\/posts\/17031\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/dmsretail.com\/RetailNews\/wp-json\/wp\/v2\/media\/17032"}],"wp:attachment":[{"href":"https:\/\/dmsretail.com\/RetailNews\/wp-json\/wp\/v2\/media?parent=17031"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dmsretail.com\/RetailNews\/wp-json\/wp\/v2\/categories?post=17031"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dmsretail.com\/RetailNews\/wp-json\/wp\/v2\/tags?post=17031"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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