Advertise on podcast: CloudNets

At the AI Infra Summit, DriveNets’ Dudy Cohen (VP Product Marketing) explores how networking plays a key role in AI infrastructure, from optimizing GPU utilization, supporting scale-across for data centers to enabling heterogeneous AI. What will you learn: How networking helps optimize GPU utilization and improve tokens per dollar and per watt.Why full-stack optimization spans switches, NICs, communication libraries, and workloads.How networking enables heterogeneous AI clusters with different GPU and ASIC types.Why disaggregated inference requires networks that handle bursty traffic and KV cache transfers.How scale-across connects GPUs across geographically separated data centers to tap into available power resources.𝗟𝗲𝗮𝗿𝗻 𝗺𝗼𝗿𝗲 𝗮𝗯𝗼𝘂𝘁 𝗗𝗿𝗶𝘃𝗲𝗡𝗲𝘁𝘀  👉 https://drivenets.com/ai-fabric 𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗗𝗿𝗶𝘃𝗲𝗡𝗲𝘁𝘀 🔗 LinkedIn:    https://www.linkedin.com/company/drivenets 🔗 X:   https://x.com/drivenets 𝗣𝗼𝗱𝗰𝗮𝘀𝘁𝘀 🔈 Apple: https://podcasts.apple.com/il/podcast/cloudnets/id1589786423  🔈 Spotify:  https://open.spotify.com/show/1q8e4hNOyaz5ySTeRjTP25

Nasdaq Marketsite reporter Kristina Ayanian interviews DriveNets CEO & co-founder, Ido Susan, and Hillel Kobrinsky, Chief Strategy Officer and co-founder. DriveNets Co-Founder and CEO Ido Susan and Co-Founder and Chief Strategy Officer Hillel Kobrinsky joined Kristina Ayanian at Nasdaq MarketSite to discuss DriveNets’ $410 million Series D funding round, the company’s growth, and the future of AI infrastructure. In the interview, they explained why the round is not a traditional fundraising milestone, but a “delivery round” designed to support DriveNets' scaling inventory, supply chain, and customer delivery. They also covered AMD’s role as a strategic investor, the market shift toward open, multi-vendor AI infrastructure, and why network performance has become critical to maximizing GPU utilization. DriveNets is helping to solve AI networking bottlenecks by optimizing the software stack connecting tens of thousands of GPUs into a single high-performance infrastructure. Discussing the rise of heterogeneous AI, they expand on how different AI workloads should be matched to the most suitable chips, resources, and architectures. 𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗗𝗿𝗶𝘃𝗲𝗡𝗲𝘁𝘀 🔗 LinkedIn: https://www.linkedin.com/company/drivenets         🔗 X:   https://x.com/drivenets 𝗣𝗼𝗱𝗰𝗮𝘀𝘁𝘀 🔈 Apple:  https://podcasts.apple.com/il/podcast/cloudnets/id1589786423 🔈 Spotify:  https://open.spotify.com/show/1q8e4hNOyaz5ySTeRjTP25 👇SUBSCRIBE TO OUR NEWSLETTER NOW👇 Subscribe on LinkedIn https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=6953575364468056064

Dudy Cohen, VP of Product Marketing at DriveNets, examines the rapid evolution of Ethernet technology and its critical role in AI infrastructure. Cohen discusses how Ethernet is advancing through multiple dimensions—from 800G to 1.6T line rates, co-packaged optics integration, and the introduction of scheduling layers that address Ethernet's traditional limitations. He explores the dramatic scaling of GPU clusters, from thousands to potentially millions of units, and explains why different scheduling approaches—fabric scheduling versus endpoint scheduling—suit different deployment scenarios. Cohen traces DriveNets' journey from building scalable service provider routers to applying the same scheduled fabric technology to AI backend networks. The discussion reveals how technical architecture choices directly impact business metrics, from time to first token to cost per million tokens, and why open, Ethernet-based solutions are gaining traction across hyperscalers, neoclouds, and enterprise deployments. What You Will Learn: How Ethernet technology is evolving across speed, optics, and scheduling capabilitiesThe difference between fabric scheduling and endpoint scheduling for AI networksWhy ESUN technology enables Ethernet to compete with purpose-built scale-up protocolsHow GPU cluster sizes are scaling from thousands to potentially millions of unitsThe business case for Ethernet-based AI infrastructure in terms of deployment speed and operational costs

From the SuperCompute25 event in St. Louis, this episode takes a look behind the scenes of the world’s largest temporary network. Hear about the real challenges of orchestrating massive, multi-vendor networks—and how a new platform aims to simplify network operations end to end, with big news coming in 2026. 𝗟𝗲𝗮𝗿𝗻 𝗺𝗼𝗿𝗲 𝗮𝗯𝗼𝘂𝘁 𝗗𝗿𝗶𝘃𝗲𝗡𝗲𝘁𝘀 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗖𝗹𝗼𝘂𝗱 👉 https://drivenets.com/solutions/ai-networking/ 𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗗𝗿𝗶𝘃𝗲𝗡𝗲𝘁𝘀 🔗 LinkedIn:    https://www.linkedin.com/company/drivenets 🔗 X:   https://x.com/drivenets 𝗣𝗼𝗱𝗰𝗮𝘀𝘁𝘀 🔈 Apple: https://podcasts.apple.com/il/podcast/cloudnets/id1589786423  🔈 Spotify:  https://open.spotify.com/show/1q8e4hNOyaz5ySTeRjTP25

In this episode of CloudNets, we dive into the last-mile redundancy dilemma for service providers. We explore the trade-offs between single and dual connections, the complexity of traditional chassis-based designs, and how Distributed Disaggregated Chassis (DDC) delivers the best of both worlds—true redundancy, resilience, and scalability without added operational complexity. DriveNets Service Provider Networking solution: https://drivenets.com/products/ Follow us on social LinkedIn: https://www.linkedin.com/company/drivenetsX: https://twitter.com/drivenets𝗣𝗼𝗱𝗰𝗮𝘀𝘁𝘀 🔈 Apple:  https://podcasts.apple.com/il/podcast/cloudnets/id1589786423 🔈 Spotify:   https://open.spotify.com/show/1q8e4hNOyaz5ySTeRjTP25

In this episode of CloudNets, we dive into blast radius and how to design networks that prevent failures from cascading and impacting customers. We explore how network segmentation and distributed chassis architectures dramatically reduce blast radius and improve resiliency. 𝗟𝗲𝗮𝗿𝗻 𝗺𝗼𝗿𝗲 𝗮𝗯𝗼𝘂𝘁 𝗗𝗿𝗶𝘃𝗲𝗡𝗲𝘁𝘀 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗖𝗹𝗼𝘂𝗱 https://drivenets.com/products/ 𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗗𝗿𝗶𝘃𝗲𝗡𝗲𝘁𝘀 LinkedIn: https://www.linkedin.com/company/drivenets X: https://x.com/drivenets 𝗣𝗼𝗱𝗰𝗮𝘀𝘁𝘀 Apple:  https://podcasts.apple.com/il/podcast/cloudnets/id1589786423 Spotify:  https://open.spotify.com/show/1q8e4hNOyaz5ySTeRjTP25 𝗪𝗮𝘁𝗰𝗵 𝗠𝗼𝗿𝗲 𝗩𝗶𝗱𝗲𝗼𝘀       • CloudNets S4 Ep7 Network Modernization        • CloudNets 4 Ep 1 New Automation Capabilities        • CloudNets 4 Ep 3 Autonomous Network

This episode of CloudNets explains how network operators should prioritize upgrades by balancing new feature value against security, reliability, and SLA risks. It highlights the importance of addressing security vulnerabilities quickly using targeted hot patches, which reduce testing scope and operational risk while allowing upgrades to be scheduled and deployed with minimal network disruption. 𝗟𝗲𝗮𝗿𝗻 𝗺𝗼𝗿𝗲 𝗮𝗯𝗼𝘂𝘁 𝗗𝗿𝗶𝘃𝗲𝗡𝗲𝘁𝘀 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗖𝗹𝗼𝘂𝗱 https://drivenets.com/products/ 𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗗𝗿𝗶𝘃𝗲𝗡𝗲𝘁𝘀 LinkedIn: https://linkedin.com/drivenets   X: https://x.com/drivenets 𝗣𝗼𝗱𝗰𝗮𝘀𝘁𝘀 Apple:  https://podcasts.apple.com/il/podcast/cloudnets/id1589786423 Spotify:  https://open.spotify.com/show/1q8e4hNOyaz5ySTeRjTP25 𝗪𝗮𝘁𝗰𝗵 𝗠𝗼𝗿𝗲 𝗩𝗶𝗱𝗲𝗼𝘀    • https://youtu.be/-8EbkT524yo?si=qs70VVUFBqrTQtki    • https://youtu.be/F7MwHpnbGP0?si=L5R-s3Kq4PgcyVOh    • https://youtu.be/SI5MPwFy_XM?si=MJAgiWkQl91vIH6Y

In this episode, we explain the challenge network operators face when introducing new features—balancing speed, risk, and maintenance windows—and why traditional “big bang” upgrades are risky and slow. Here, we introduce automated scheduled maintenance that allows gradual, controlled software rollouts, reducing risk while accelerating innovation without late-night manual work. 𝗟𝗲𝗮𝗿𝗻 𝗺𝗼𝗿𝗲 𝗮𝗯𝗼𝘂𝘁 𝗗𝗿𝗶𝘃𝗲𝗡𝗲𝘁𝘀 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗖𝗹𝗼𝘂𝗱 https://drivenets.com/products/ 𝗪𝗵𝗲𝗿𝗲 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗗𝗿𝗶𝘃𝗲𝗡𝗲𝘁𝘀 LinkedIn: https://linkedin.com/drivenets  X: https://x.com/drivenets 𝗣𝗼𝗱𝗰𝗮𝘀𝘁𝘀 Apple:  https://podcasts.apple.com/il/podcast/cloudnets/id1589786423 Spotify:  https://open.spotify.com/show/1q8e4hNOyaz5ySTeRjTP25

At the SC25 event, DriveNets’ Dudy Cohen (VP Product Marketing) and Andy Holland (Sales Director for AI Infrastructure) explore how Ethernet is expanding its reach beyond traditional scale-out and scale-across applications to challenge InfiniBand in the demanding scale-up domain. Key highlights DriveNets powers the world’s largest AI and Telco networksDriveNets brings an AI Networking solution with peak performance out-of-the-boxDriveNets fabric scheduled Ethernet is solving industry-wide pain points in AI NetworkingWatch the interview  Want to learn how DriveNets is reshaping AI networking infrastructure? Explore DriveNets AI Networking Solution 𝗪𝗵𝗲𝗿𝗲 can you 𝗳𝗶𝗻𝗱 𝗗𝗿𝗶𝘃𝗲𝗡𝗲𝘁𝘀 LinkedIn X

What is the new service provider network? This is the network modernization process all service providers need to go through. Service Providers cannot continue to build networks the same way they have for over 20 years, and still maintain a valid business.

DCI is going through something and this something is called AI. The three changes that AI made to DCI are capacity, performance, and one environment and layer three capabilities.

What’s the importance of latency in AI networks. AI networks introduce new challenges that need different treatments of latency.

DES, DSF, DDC – Comparing Scheduled Fabric Arista recently launched their DES solution, the Distributed Etherlink Switch, which is essentially an end to end VOQ system – a large scale chassis. The approach is basically saying we should put as much logic as we can on the switch side. The switch will handle all the congestion control, all the reordering of packets, the load balancing of packets, which are all necessary for AI networking. So why choose DriveNets DDC over those solutions?

Are autonomous networks coming soon? We’re taking baby steps, starting with islands of automation and we’re going to automate small, mundane tasks by helping operators develop CI/CD pipelines that allow them to take innovation from their lab to a network digital twin and eventually into production in a much faster way.

We have an issue with resolving the AI fabric, or an AI networking problem with large clusters of GPUs usually used for training. This episode looks at the issue with resolving the AI fabric and explores how an Ethernet based solution can resolve this – by building a chassis which is distributed (a disaggregated, distributed chassis). This approach has no packet loss, is lossless and is a fully scheduled fabric, but without the scale limitation of a chassis.