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.

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 other inventory systems.

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, Distributed Disaggregated Chassis (DDC), it takes the same scalability factor of a Clos, the operational aspects of a chassis and even when you look at the cost side of things, from an operational standpoint, DDC operates as a single device. Then from a Capex standpoint, DDC operates or works as white boxes.

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 Cloud so important?

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.