It has taken many years for the AI boom to reach the general ledgers and balance sheets of the world’s largest original equipment manufacturers, and one might say that it has taken particularly long for Cisco Systems, the dominant supplier of switching and routing in the enterprise and traditional telco/service provider spaces as well as a respectable systems supplier with over 90,000 customers using its UCS converged server-switch platforms. …
The Memory Crunch Pinches Cisco’s Profits was written by Timothy Prickett Morgan at The Next Platform.

Million Dollar Home Page by Alex Tew – http://milliondollarhomepage.com/, Fair use, https://en.wikipedia.org/w/index.php?curid=20132455
I need you to try to do something very hard for me. I need you to read this entire blog post. I don’t think it’s going to be hard because I’m going to use big words or highly technical terms. I don’t think it’s going to be hard because of the subject matter. It’s going to be hard because you’re going to get interrupted. In fact, I’m willing to be you got some notification before you ever finished this paragraph.
I didn’t realize just how scattered my attention was until a close friend pointed it out to me. She mentioned that I was always checking my watch for notifications. I didn’t realize it until someone that wasn’t around me all the time saw it. I stepped back and honestly asked myself why I was getting so many notifications. In the back of my mind I knew I was getting too many because when I go on a run my watch won’t stop buzzing with all the things that I don’t even bother to check. That’s when I realized my attention was beyond Continue reading
The way content and businesses are discovered online is changing rapidly. In the past, traffic originated from traditional search engines, and SEO determined who got found first. Now the traffic is increasingly coming from AI crawlers and agents that demand structured data within the often-unstructured Web that was built for humans.
As a business, to continue to stay ahead, now is the time to consider not just human visitors, or traditional wisdom for SEO-optimization, but start to treat agents as first-class citizens.
Feeding raw HTML to an AI is like paying by the word to read packaging instead of the letter inside. A simple ## About Us on a page in markdown costs roughly 3 tokens; its HTML equivalent – <h2 class="section-title" id="about">About Us</h2> – burns 12-15, and that's before you account for the <div> wrappers, nav bars, and script tags that pad every real web page and have zero semantic value.
This blog post you’re reading takes 16,180 tokens in HTML and 3,150 tokens when converted to markdown. That’s a 80% reduction in token usage.
Markdown has quickly become the lingua franca for agents and AI systems as a whole. The format’s explicit structure Continue reading
It does not happen very often in the history of business that an orthogonal product is invented that almost immediately doubles the revenue pool of a market and has the prospect of tripling it over the next handful of years. …
Only A Few AI Platforms Can Survive was written by Timothy Prickett Morgan at The Next Platform.
Calico, Cilium, Retina, and Netobserv: Which Observability Tool is Right for Your Kubernetes Cluster? Network observability is a tale as old as the OSI model itself and anyone who has managed a network or even a Kubernetes cluster knows the feeling: a service suddenly can’t reach its dependency, a pod is mysteriously offline, and the Slack alerts start rolling in. Investigating network connectivity issues in these complex, distributed environments can be incredibly time consuming. Without the right tools, the debugging process often involves manually connecting to each node, running tcpdump on multiple machines, and piecing together logs to find the root cause. A path that often leads to frustration and extended downtime.
This is the problem that Kubernetes Network Observability was built to solve. By deploying distributed observers, these cloud-native solutions take the traditional flow entries and enrich them with Kubernetes flags and labels to allow Kubernetes users to get insight into the inner workings of their clusters.
This blog post aims to give you a rundown of the leading solutions in the CNCF ecosystem, and compare how they track a packet’s journey across your cluster.
Before diving into the specifics, let’s look at how these four Continue reading
AI projects don’t fail because models don’t work or GPUs lack performance. …
Attending GTC? Join Us For An Exclusive Roundtable Dinner On AI Data Platforms was written by Atul Chaudhary at The Next Platform.
netlab release 26.02 is out, including the usual potpourri of goodies:
The fun part, however, are the new container configuration methods:
In the modern AI datacenter – really, a data galaxy at this point because AI processing needs have broken well beyond the bounds of a single datacenter or even multiple datacenters in a region in a few extreme cases – has two pinch points in the network. …
Cisco Doubles Up The Switch Bandwidth To Take On AI Scale Up And Scale Out was written by Timothy Prickett Morgan at The Next Platform.
The NVIDIA GTC conference has a reputation for delivering announcements that reshape industry roadmaps. …
The Greatest AI Show On Earth was written by David Gordon at The Next Platform.

In the previous posts in this series, we covered the basics of multicast, IGMP, PIM Dense Mode, and PIM Sparse Mode. In the Sparse Mode post, we manually configured the RP address on every router in the network. This works fine in a small lab, but in a larger network with many routers, it becomes difficult to manage. If the RP changes, you have to update the configuration on every single router.

AutoRP solves this problem by allowing routers to dynamically learn the RP address. Instead of manually configuring the RP on each router, you configure one or more routers to announce themselves as Candidate RPs. A separate router (or the same as the Candidate RP router) called the Mapping Agent collects these announcements and distributes the RP information to all other routers in the network. This makes RP management much easier and also provides a way to implement RP redundancy.
There are two methods to dynamically learn the RP address, which are Auto-RP and Bootstrap Router (BSR). In this Continue reading
Brian Linkletter published an updated overview of open-source network simulators and emulators.
containerlab and GNS3 are clear leaders (no surprise there) with the original vrnetlab becoming abandonware (fortunately, we have Roman Dodin’s fork), which makes me think we should focus on using netlab primarily with containerlab and slowly sunset the Vagrant support, particularly considering some people actively hate the license change.
Also, if anyone feels like writing an interface (provider module) between netlab and GNS3, the pull request would be most welcome 😎
Any thoughts? Please leave a comment!
This is turning into a “dog bites man” story, but the forecasts for spending in the datacenter for this year keep going up and up, and a few days ago Gartner’s economists and prognosticators finished up their tea and looked at the leaves at the common of a cup through a polished crystal ball and predicted that datacenter spending this year would go up. …
Datacenter Spending Forecast Revised Upwards – Yet Again was written by Timothy Prickett Morgan at The Next Platform.
After the enormous speedup I achieved with the FRR containers, I tried to do something similar with the Arista cEOS ones. After all, Arista’s pretty open about running its software on standard Linux, so it should be possible to map host-side configuration files into container-side scripts and execute them, right?
There was just one tiny gotcha: all netlab-generated EOS configuration files are device configuration snippets that are intended to be submitted via EOS CLI, and I didn’t feel like cracking open the netmiko documentation (that’s another backburner project).
However, Arista cEOS includes this magic command called FastCli ;)