CloudNets

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 s...

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/...

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 Pro...

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.linke...

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. 𝗟...

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 𝗗𝗿𝗶...

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 networks DriveNets brings an AI Networking solution w...

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 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.

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

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.

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, whi...

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 sc...

What are the new automation sets coming to DriveNets Network Orchestrator? Autoboot profiles helps you bootstrap new white boxes from the factory. Smart Rollout is a brand new feature and it allows you to push software into the entire network after configuring just a few parameters. The Single Source of Truth integration seamlessly integrates the inventory that we have in DNOR into NetBox, or or o...

Failure recovery is a very big issue when it comes to AI clusters because there are always failures and when the failure come, it’s a big thing because you need to stop the calculation, go back to the last checkpoint. You lose a lot of time and money and resources that are spent idle and and wasted time. And the networking part is crucial in order to create a fail.

Congestion demands attention, otherwise it can result in higher latency and packet loss. The main dilemma around congestion is around avoidance or mitigation. We’ll look at how scheduled fabrics make sure that AI infrastructure is lossless and predictable rather than bringing additional technologies to mitigate the congestion, but do not avoid it

Why is cell-based fabric is so much better than the alternative when it comes to Ethernet for AI fabric or AI infrastructure.

Chassis and Clos, which is better? From the perspective of scale, absolutely Clos topology outranks a chassis. From an operational standpoint, a Clos topology would mean that you will need to manage a lot of boxes and that's a bigger headache than managing a single device, a chassis, one stop shop. But from a Capex standpoint, a Clos topology prevails over chassis. Looking at the alternative,...

We're going to talk about KDDI, one of Japan's major Tier 1 operators. They recently announced that they implemented DriveNets Network Cloud solution in its network and they are very satisfied. They are talking about huge TCO advantages, about 46% saving in power and 40% savings in rackspace, etc.  Let's hear about KDDI and why is this deployment, a major deployment, of Network Clou...

How can a disaggregated network solution provide benefits in terms of Total Cost of Ownership to service providers in a long term perspective

What are three things we can learn about Network Cloud in real world network operations.

Today we're going to talk about recovering from major faults, those things that keep you up at night.

DriveNets hosted a panel for analysts and media at MWC23 in order to explain its work and hear from industry leaders on progress for disaggregated networking. Members of the panel included Igal Elbaz, SVP and network CTO at AT&T;  Jean Louis Le Roux, executive vice president for International Networks with Orange; Cayetano Carbajo, VP for core, transport and service platforms with Telefonica.

Today we're going to talk again about AI networking, and we will provide the solutions for the challenges we mentioned last time. With the fast growth of AI workloads, network solutions need to be ready to resolve issues including  having a flexible and online architecture, being able to  scale and maintain performance at scale, and  having a field proven rock-solid solution.

What are the challenges of AI Networking?  We’re going to talk about AI, and specifically about AI networking. we want to talk about the challenges behind the AI infrastructure, because AI ML training, it’s very compute, intense task.  What are the main challenges in AI networking that companies like the Hyperscalers that are going into this market now needs to resolve?