Techstrong TV – November 26, 2024

Hey folks, I'm Mike Azar. Today we're talking about Mobile Madness. Then we're gonna shift gears and discuss, maybe have we come to the end of Ragtime.

And then finally, well just how green can the Emerald Aisle be in the age of AI and data centers? You're watching Textron Gang, and we'll be back in a minute. All right, folks, it's Tuesday, which means that we're gonna be discussing yet another awesome tech field day.

This one's on mobility. And Steven, I gotta say, you've been doing these things at a pretty hot clip these days. So, um, walk us through the latest and greatest, who showed up and what were they talking about?

Sure, yeah. So, uh, each tech field day event, we've got different bra topics. Uh, as you mentioned, this one's on mobility, which is the, our name for the event that focuses on things like wifi, uh, 5G mobile device management, mobile clients network as a service, that sort of thing.

And, um, you know, so each event, although it seems like there's quite a few of them, uh, each one has a different set of companies, a different set of, uh, attendees, a different audience, and so on. Um, this one was, uh, is one of my favorites because mobility and mobile device management, wifi and everything is, it's like a parallel universe. Um, it's like landing on another planet and, uh, you know, in, in your favorite science fiction book, and you, and you're looking around and you're like, you know, wow, that's, so, that's how they do this, and that's how they do that.

And isn't it interesting that they've got, you know, they've invented the same thing in, in a different way. And mobile mobility is like that. Essentially, uh, everything that we get in the data center, everything we get in the cloud is done in mobile, but it's done with a different flavor because it has to be.

So, uh, for example, um, you know, zero trust provisioning and, um, software defined networking originated in mobility spaces first. Uh, when it became clear that companies would have hundreds, if not thousands of wireless access points, each of which needs to be configured, uh, you know, provisioned, configured, and managed in, you know, by a central device. And that's, uh, you know, that whole concept has really spread into the cloud.

So, uh, this one was no different. Uh, we heard from Cisco, for example. Um, they're coming in with, uh, a topic that I think is really, uh, kind of an interesting one.

They're talking about wireless backhaul. So for a while in the enterprise wireless space, uh, there, there was a lot of talk about using wifi protocols. Um, and, uh, that was challenging 'cause wifi wasn't designed for, uh, long distance communication.

And so even though there are such devices, they're, they're not, uh, maybe as great as they could be, um, especially when you've got MO devices that are moving around and, and so on. Um, Cisco came in talking about using, um, uh, new wireless protocols to replace, uh, private 5G, which has been another big topic in this space. Essentially, companies are using exactly the same technology that your phone uses to connect at, uh, high speed to a tower or base station, uh, using that exact same technology to deliver a much, much greater range for wireless devices.

Uh, so if you look, think about something like a, um, a farm or a mine or a, uh, big manufacturing facility, they may use private 5G instead of wifi because they need better range. Um, that's also been used for backhaul purposes, and now Cisco's got an alternative solution for that. Um, uh, a bigger topic, uh, in terms of, uh, what was discussed by the delegates though, was network as a service.

So essentially, um, this whole concept, as I said, of, uh, centrally central management and, uh, zero trust provisioning and, and, and modify, you know, monitoring and managing and maintaining networks not as, um, individual devices, but as a enterprise service has really been gaining traction. Um, we talked about, uh, with a company called Nile that's getting a lot of attention in this space. Um, uh, a pretty high profile company all may have of heard of, and if you haven't, you should probably look it up because I, I think that they're gonna go pretty far.

Uh, but the practitioners in the audience were concerned and questioning how exactly this, this is deployed, how it fits in with modern enterprise IT and enterprise networking, and whether network as a service is another one of those things, sort of like, um, infrastructure as a service where it seems like a really great idea until the practitioners actually have to go out there and implement it and manage it. And I think that that's actually gonna come up in some of our later stories here about rag. Um, you know, maybe we need, uh, to, to, to think about things organizationally, not just technologically.

And, uh, so that was another topic. Now another thing the delegates were kind of buzzing about was non wifi wireless protocols. Uh, many of you have heard about the, the home, uh, standard matter, um, that uses, uh, thread networks, which is, uh, related to ZigBee.

There's also Z-Wave and other non-wireless or non wifi protocols. So this is kind of the other end of that, um, wireless backhaul story. Um, you know, how do you, how do you connect low powered devices always on devices?

I mean, here in the office, I use a lot of Z-Wave devices with home assistant, um, as I said, matter and threat are getting a lot of attention. So anyway, if, if, if all of this stuff per piques your interest, uh, do check out some of the mobility field day presentations, but also the round table discussions, podcasts, that sort of thing, because, uh, there's a lot going on in this space. You know, I've been trying to figure out as of late where that line is between what I, as a member of an IT team or a network admin manage versus that which is managed by the carrier or somebody else.

And, um, do you have a vibe for how that's evolving? 'cause you know, back in the day, you know, there were network admins and they were gods and they managed everything. And then these days it kind of feels like, you know, more and more of this stuff is just a service that kind of is paid for on a monthly basis.

Yeah, I think that that's really the, the core of the question here. And like, you know, it really is a, a, a, a question of a trade off between having in-house staff who can manage things versus having things be sort of externally managed as a service for your business. Uh, some companies, I'm sure would be thrilled to have their networks managed as a service.

Um, others, you know, maybe not so much. And I think that just like, uh, when it, when we have discussions about cloud, uh, when we have discussions about platform as a service and software as a service, there's a lot of things that we need to think about that are trade-offs between who's running what and what their SLAs are, and what their responsibilities are in terms of, you know, uh, availability, but also in terms of how to deal with problems when they arise. And, and I think that some people too, just like in the, the cloud space, are a little nervous about letting, uh, something as essential as their network, uh, be managed by outsiders.

Mitch, what's your take on their capability? I'm asking this question because, um, in Boca Raton where Textron is roughly about every 30 days or so, it seems like there's a wireless network issue. And then, you know, Alan, who's not here, or somebody else is up on a ladder pulling cables and switching things around.

And, um, you know, and I scratch my head because, you know, at home here, I don't seem to have a problem with my wifi network. So is there a difference between what happens in the office at home and what's going on here? The, uh, Boca office is more of a issue of density, which you run into in different, different, uh, zones within, you know, highly dense, uh, areas in cities and things like that.

You don't run into it as much, uh, in, in the communities, in the rural communities. It, I think what's interesting about this, Mike, is that when we say wireless now, now it spans multiple things. It spans what we traditionally thought of cellular wireless, right?

When we talk about 5G now, we talk about, uh, cellular, but it's also 5G data. But 5G also includes another, uh, several other types of 5G uh, data networks, uh, that Steam was talking about. Um, it's been a little while since I've been in the space, but I used to do, had a, had a lab, that lab that did early testing of 5G and software based radios and rans, things like that.

And also, um, some of the early 5G and then also c certificates for protecting those devices. And, and what's happening is we've kind of blurred the lines now that, that the network, what used to be the edge of the cellular network or the edge of the carrier network, if you want to think of it that way, it's now sitting inside our homes or our offices. Um, we may get all of our, our service over a cellular 5G type service.

We may also use a different type of five, 5G uh, for data networking between buildings or doing long distance, you know, so the, the days of what, what you were talking about, uh, uh, Stephen of trying to go long distance with wifi, 'cause that's kind of all we had, you know, as, uh, something less than what a carrier would offer. Uh, enterprises have a lot more options to, uh, pursue. So your, your, uh, mobile field day is very timely for this.

'cause a lot of organizations are trying to figure out as they move, move around office locations are changing or closing, and what do they do to collapse or expand the network to the edge? Yeah, and I don't wanna cast aspersions on any particular network administrators, but I will say that the, uh, mobility field, a delegates are some of the experts in this field. And, um, you know, a, a few of them, for example, are the people responsible for wifi at, uh, major stadiums, uh, factories, that sort of thing.

Uh, they know how to make wifi incredibly robust and reliable. Um, back in the day, I remember sitting down with one of those guys and we were having a conversation, and the analogy was, remember when, um, when Windows servers first came out and everybody who had ever used a Windows laptop or desktop thought that they could administer a Windows server because it's Windows, right? I mean, it's Windows.

Of course I can do this. And, um, that was the same that the wifi people felt about non, um, well, non robust enterprise trained people, uh, building and deploying wifi networks. Um, I've experienced this myself repeatedly, where you go into a place and the wifi network is just horribly misconfigured.

Either they've got way too many routers or, uh, or, you know, wireless, uh, access points, way too few. Uh, they're, they're jamming up the spectrum. They're using too high power, uh, essentially they're, you know, working across purposes.

Whereas a, a properly managed and deployed enterprise wifi environment is a, is a thing of beauty. That's, that's all to say though, that, um, all these people have jobs because most wifi networks are not properly managed, properly designed or properly deployed, and basically they suck. And there are a lot of good people you can hire to do that for you.

I know some, Yes, I heard of that. Steven, did anybody talk about AI and the democratization of networking? Because like I mentioned early on, there was always this notion of the networking gods, but, you know, can mere mortals now master networking and I can just have, you know, your standard IT people manage the network.

Well, certainly that's a big topic with a lot of the enterprise, uh, network management companies, uh, both in terms of data center networks, but also campus and mobility networks. Um, lot of talk about using AI to optimize, uh, network designs and so on. And, and I'm just gonna go out a limb and suggest that probably a lot of that stuff is gonna be moderately successful.

Essentially, wifi is, as I said, so poorly managed, so poorly designed that, uh, an artificial intelligence or even, even just a basic template could probably do a much better job than what most people have, uh, at their disposal. So I'm gonna guess that that's gonna be a big wave. But, um, I guess happily, uh, since it's 2024 and everybody's talking about ai, that wasn't a huge topic at a, at, uh, mobility Field day, simply because, um, it, it's not, it, it's AI is more of a tool for them than it is a, uh, central concern.

Mitch, did you ever hear the one about the one thing that the IT admin and the application developer can agree on? It's the network's fault. It's, It's the Networking guy's Fault.

It's either the network's fault or, or hit the any button, you know, any key, any key on your keyboard, where's the, It's always DNS, It's always dns. You, you know, so, so here's where we get into both, you know, land as well as, you know, wireless type of, uh, networking because of the, the, uh, cable networks. You've, you've heard, seen advertised 10 G by com, by Infinity, uh, Comcast.

That's not a thing. It's not a thing, it's not a thing. It's a marketing label, right?

And, and consciously done that way, I believe. But what's behind that is how they're getting, they're getting much higher bandwidths. It hasn't reached 10 gig, but it, but that's kind of in the game scheme of where they're headed.

They do something where they used, um, coherent optics to be able to send multiple, basically optical streams down one piece of fiber. So much like we do kind of spread spectrum or things like that in, in wireless world, they've done that with, with, uh, fiber. And part of that is to be able to be the backhaul for software based radios.

It can be anywhere on the edge. Uh, matter of fact, a lot of the equipment that sits at the edge has been turned into software and could potentially actually live not on the edge, doesn't have to be there. Uh, so it, it's a combination of, you know, they're going that direction.

So what's behind 10 G is not just to your home and to your business, but also as a backbone or backhaul for, for, uh, cellular and, and other wireless networks. But I think, you know, I, I learned something long ago. I'm gonna do an Alan, I've been doing this for a long time, and one of the things I've learned is that this is another thing you can always tell who drew the diagram by what's in the center.

If it's the cloud, it was the network guys. Actually, let me, let me follow on that with one last pitch. Uh, if you're a nerd, and you probably are, if you're listening to this, if you're a nerd like me, uh, check out R-T-L-S-D-R.

It's a whole hobbyist community of software defined radio enthusiasts. They're doing just incredible fun things with software defined radios and, um, you know, basic stuff like listening in on the, um, A DSB transmissions from airlines that are flying over to all sorts of just amazing, incredible stuff. It's a whole hobbyist area, and it's a lot of fun.

It's like the ham radio, the 21st century almost. I will say the one thing I keep hearing over and over again is we're building these highly distributed latency sensitive applications, and nobody has any visibility into the networks that they're running over. And so we don't have any understanding of exactly what happens to them when something goes bad.

So, Mitch, do we need to kind of meld maybe observability and networking together a little bit better than we have? I think we do. I think we also need to, you know, what's the saying?

The fu the future is uneven? Well, wireless networks are extremely uneven, uneven, and 5G suffers from all the marketing hype it did about, it's gonna replace everything and gonna be everywhere. And we all know it's not.

And how many times, even if we get a signal, it doesn't, we don't have the data capacity or data connection to Do it. It's not that stable. I have 5G at home and I I, every time I call when there's an outage, it's an external error.

Like, oh, you must live near an airport, or, you know, no one, there's no responsibility being taken. I, I'm glad I have it. It's reasonably priced, but, um, the reliability hopefully will improve.

It's no silver bullet, right? No, but, but it is also, you know, it's coverage and, you know, you're talking about markets outside on the edge of cities and also even dead zones in cities and things like that. So I think that's part of our, our challenge is you in the, in the cable network days, and I did some work in the early, kinda late nineties, mid nineties, you know, we, we relied on the customers to call us to tell us when the network was down.

That's how we knew there was an issue, and customers knew that, right? So they knew to call right away. Maybe there's still some of that going on.

I think we have much better, better visibility, but I don't think we have the observability that we need that you're talking about, Mike, to really understand not just where congestion issues are, but where our coverage issues and where are there, where are there interference issues, right? Well, that's one of the things that people get from buying, uh, you know, and deploying high grade enterprise stuff. So, I mean, if you go to a company like Cisco or HPEs Aruba or Ruckus or, uh, you know, any of these companies, you'll find that their stuff is incredibly robust.

Mm-Hmm. And well instrumented and reliable. Uh, the problem, like I said, it's that a lot of things.

I mean, God, I was at a hotel and they literally had a wifi access point sitting on every desk in every room. And I'm like, well, no wonder your wifi doesn't work. And if you're wondering why your wifi doesn't work, well maybe check out Wireless Field Day Mobility Field day, some of the presentations.

There you go. That's a bad, I more, More is not better When it comes to wifi. More, not Better wifi.

All right, folks, we're gonna move on the next block, but I'm holding out for six GI think that'll answer everything. Seven G, keep waiting on that, Mike. We'll get to 10 G eventually.

There you go. All right, folks, we'll be back in a minute. Cloud native now is the web's leading resource for the growing cloud native ecosystem.

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All right, folks, we're back on the B block here. And we're talking about rag, otherwise known as retrieval, augmented generation for a catchy term for extending large language models into data that they weren't initially trained on. And it requires a significant amount of effort to do that.

You're getting a Vector database or some sort of mastery of, uh, search capability. You gotta set all that up. Typically, you might need a data engineer, and it gets complicated in a hurry.

There's a company out there called Min io that is showing a way to extend the object file system used in the cloud via API to the LLM, so that you don't have to do all that stuff. Steven, I know that you have talked to them at length about this. What's, is this kind of just a one-off kind of solution, or is this the future?

Um, this, well, first off, let me just say yes, I've talked to MIN IO a lot over the years. They've presented at, at Tech Field Day, many times since the very fi beginning of the company. And I know the whole team since before min IO was a thing.

So, um, I, I don't wanna sound biased though, because of course we've got a lot of companies that we've talked to. But what that means is that I've talked to them, I've gotten in deep with the product. I've actually used the product in the field.

Um, it is a heck of an object store, essentially Min io. Uh, just to kind of catch people up here, uh, MIN io is probably the world's most popular object store that's not called Amazon S3, and it basically is compatible with Amazon S3. Um, that being said, what we're talking about here is their enterprise product, not their open source product and the enterprise product.

Um, you know, there's, you know, many different ways of, of building a business around an open source product. The way that Min IO has done it is that they've built a very, very robust, full featured, uh, enterprise version of their, uh, S3 compatible object store. And the enterprise version HA is now, um, I believe this is version three.

Um, and it's, yeah, it's AI store. It's basically a, uh, a, a complete revision of the direction of the enterprise products to be an AI based platform and an AI supporting platform. So imagine, I mean, what you know about an object store, what you know about Amazon S3.

Essentially it's a database in the sky, a scalable database. You can put a as much as you want. And we're talking a lot, we're talking many customers with hundreds of petabytes or even exabyte scale data in min io.

And, um, what they've added here in addition to some, uh, you know, decent upgrades that you would see in any next generation enterprise product, so, you know, user interface enhancements and things like that, what they've added is a lot of very cool AI features. Um, and essentially the, my, my, uh, focus, uh, kind of zooms in on two of 'em. Uh, number one, as you described, uh, they have built in a, uh, AI based, uh, query system that allows this, the, this, uh, min io platform to be itself an AI application that can interact with, uh, with data at that kind of scale.

The other thing that they've built in is, uh, a new protocol that allows these nodes to communicate with each other and with storage or with, uh, client devices incredibly quickly using RDMA protocols. So, I don't know which of those you want to get into. Um, I'm happy to talk about either or both of them.

'cause as you can see, storage nerd, Mitch, you know, I think it was a year ago now, or at least it seems like a year ago, but we hosted a hackathon and we had all these DevOps folks coming in, and you were there for, I think it was like three days. And one of the things that struck me at the time was like how much these developers were discovering the fundamentals of 1 0 1 data management. Like it was a brand new thing.

And, and I kind of like look back at it now, and I'm still scratching my head about it, but, um, are we asking people to know too much about data management and to build these AI applications? And do we just need to simplify this whole thing? Well, since developers are gonna take care of operations and security for us too, we might as well ask 'em to do data management, right?

Yeah. That, well, a lot of, a lot of what we were wrestling with then, then, I guess it's been year and a half ago now, close to is just how do you set up a vector database and how do you structure things so that you can front end, you know, whatever it is, you're, whichever model we were experimenting with at the time. So it was kind of a, a science project learning, learning process for us to see how you build these things is really what that, that, uh, that offsite that camp was about.

Absolutely. So, so here's my, here's my view on AI is everybody is, is racing to add AI to their products, which is great. That's fine.

And we're, we're, we've evolving from the chat bot and natural language interface two now AI agents, and there will be more, there'll be orchestrated agents and more kinds of things to come after that. The, the issue isn't adding AI to our, to our product. The issue is, what Min IO is doing is the organizations who effectively leverage their DNA, their data about their company, about their customers, about the market, whatever it is that they, they collect information on the use it, whether it's oil and gas pipelines or it's, you know, at the mall, you know, selling, selling products to people, walking through the stores, the people who effectively find the really interesting and valuable applications for AI to that data and to a business problem.

Those are the winners in ai, not the people just adding AI to their product. Steven, geek out for a minute. How many folks out there have an object file system?

Because last time I checked all these folks were running this unstructured data on something that looked like a file server or a NAS platform or something of that ilk. So how do I get all that stuff into the object file system? Well, uh, you may be surprised 'cause it may already be there.

Um, that being said, you're right that most, I think most companies, if you talk about their unstructured data, well first maybe we start, let's go into reverse here. Um, unstructured versus structured. So structured data is databases, you know, conventional databases, data warehouses, data lakes, et cetera.

And so you've got companies that are doing, you know, some very, very cool stuff there. You know, um, I was just talking to Star Tree about their, uh, incredible, uh, scalable data warehouse. Um, you know, we had Elastic Talk about using, uh, you know, rag integrating, um, vector database access to their, you know, massively scalable databases and so on.

Um, that's all great companies have that, but companies also have what's called unstructured, which is basically a mess, a complete mess. It's all the files and in some cases all the objects that make up everything. And yes, most companies, if you said, what is, where is your data?

That's not your database data, the answer would be, uh, file server. But for the most part, um, I think people also are kind of overlooking the fact that basically every Webscale app uses S3 as their, um, uh, storage engine for blobs of all sorts of different kinds of data S3 protocol and, and, and in some cases actual S3. But of course, there's other companies with compatible, you know, work alike, uh, object stores that work just like S3.

Um, you know, I, I am familiar with, uh, digital Ocean and CloudFlare and companies like that. Um, so we've got those, those things out there quite a lot. And many companies now have, uh, they're surprised to find that they have more data in an S3 compatible object store than they do on their regular enterprise file store.

Because just naturally what happened was, as you mentioned, the developers, you know, when they're out there developing things, are you gonna, you know, I'm Joe Developer, I'm building a web scale app. Am I going to use NFS or SMB to access a file server to store my data or just dump it in a file system? Or am I gonna call S3?

S3 is much more, um, developer, like, it's much more friendly, it's much more scalable, it's much less administration. So what happens is, in most modern web scale apps, they just, uh, have bucket after bucket of S3 compatible data that's out there. And as I said, many, many of those applications, if they're not using as a service like Amazon's own S3, they're using something that dumps that data into an io um, open source or corporate data store.

So yeah, I think there is a lot more data in, uh, cloud com, you know, S3 object stores than, than you might think. That being said, the other aspect is that in many cases, um, file servers are actually better understood and better managed. And and the same with, for example, Microsoft SharePoint servers.

They're better, better understood than by it because essentially it already has their arms around it. Whereas a lot of that stuff that's getting dumped into these buckets, and it is exabytes of data now that's getting dumped into these buckets, they have no idea what it's, and so for example, Google, um, recently, uh, introduced the ability to basically query your object store and say, what the heck is this stuff? Um, you know, Amazon has some capability like that.

There's a lot of third parties that are doing that. And that's kind of what Min IO is doing here. Essentially, they're, they're giving you the ability not just to say, what the heck is this stuff?

But okay, we've got this stuff now, let me query it, let me ask questions based on this incredible volume of data that's sitting in these giant object stores. I think, I'm Sorry, go ahead. No, I was just gonna say, um, I think overall, um, just bringing this back to the sustainability, um, points, I think that optimizing the storage and having it more centralized is, is, is, is going inherently going to improve sustainability.

I don't know if that was, you know, the objective in this, but I think that it's gonna be something we're gonna see going forward, and we're already seeing it in, in the larger tech companies. So this is another extension of that. It is a big advantage of object stores, you know, stored in buckets as you talked about.

Th those can be anywhere, right? You can place those all over the network. The other thing about this, uh, that I thought was interesting too, Steven, maybe you've talked to them about their AI hub.

I think it's part of the AI sub ai, uh, store story, if you will. But it lets you bring your own models that you might get from hugging face or whatever source, um, that you store in your environment. 'cause oftentimes we don't wanna be going to a public service, right?

We may host those models ourselves. And in effect, it's, it's acting as a rag in front of the object store that has your data in it, as well as interfacing with, with the AI models, gen AI models. So it's kind of its own little ecosystem with a, with a rag and also, uh, Storage of your own models that you're using.

So I think that's a pretty fascinating model for enterprises. Yeah, that's actually something that I zoomed into. We talked about this a couple weeks ago on the gestalt, it rundown, and that's one of the things that I zoomed into when they talked about AI Hub to me.

I was like, why are you doing this? Why do, why do, why is a storage an object storage company developing a hugging face compatible, um, model storage? I, oh, there's the word and it, and it's the flip side, right?

So on the one hand of the coin, we have, let me query this, like exabytes of data that I've got in my object store. The other side of the coin is, wait a second, how can I use an object store to better serve ai? And that's actually something, by the way, that Min io presented at our recent AI data infrastructure Field day event too.

There's a, a min IO presentation, you can zoom in there. Um, as I said, they've got S3 protocol over RDMA, which makes it super fast and scalable, but they've also got this AI hub. And, and there again, it all comes down to the fact that a lot of enterprises are using hugging face the same way that they would use GitHub for code.

The problem is that hugging face is a public, you know, software as a service provider. I mean, it's essentially, you know, once you put things in hugging face, um, it's, it's a little bit outside your hands. And a lot of people are a little nervous about putting enterprise AI models on something like that.

And so, you know, MIN io did what they did to S3. They basically looked at the, uh, the hugging face, API and they said, what if we built a our own, your own hugging face? So you could store your models, uh, securely locally, um, you know, you can use them internally and uh, to your developers, it looks just like using hugging face, which they like.

And so what it first didn't make any sense to me now makes a lot of sense for another reason too, which is that those models take up a lot of, a lot of storage space. It's hard to manage a lot of storage, but actually it's not a lot of storage for MIN io. And it's actually super easy to manage it on that because it just sort of, there you go.

It, that's, I mean, to MIN io, that's like nothing. You know, they can, they can handle that kind of storage capacity and snapshots and versions, all that kind of stuff, no big deal. Um, so it made some sense to in, to do this, uh, AI hub as well as, uh, some of the other things, All right folks, I'm gonna call it on this subject.

But I would point out that all those folks that grew up in the old school, it ways were taught one thing, nothing good happens when you move data. And I think it's still true. Alright, Hey guys, we'll be back in a minute.

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Hi everyone, welcome back to the Techron Gang. Well, now we're gonna take you on a journey across the Atlantic to talk about a beautiful place. Ireland and Ireland is known for many, many things.

We'll get into that in a little bit. But for one of the things that Ireland has really been, uh, benefiting from and economically is the investment from big tech in terms of data centers and, and lots of planning and, um, things like for expansion of t there. Now, while that has been an economic boom, it's also presented some drawbacks because particularly in the city of Dublin and some others, it is just draining the, the power.

And this is why there is a moratorium actually on new data centers in some of the city limits. So I wanted to take a closer look at Ireland's place I've always wanted to visit, so maybe that's why I was drawn to it. But, um, in the video I'm about to present, I take a look at the data center expansion and the energy demands, and perhaps some potential solutions as we move into 2025 of what Ireland can do to benefit both economically, but also, uh, meet their carbon goals that they have going forward.

Hi everyone. I'm Bonnie Schneider with your Ecotech analyst Insights. Ireland's tech Boom has hit a major roadblock, its power grid.

According to a recent report in the Irish Times, there's a growing backlash against data centers due to their energy use. This comes at a time when Ireland is struggling to meet its targets to cut carbon emissions. In Dublin.

Data centers now consume about 14% of the city's total electricity, more than the combined usage of Cork, Galway, and Waterford. Demand shows no sign of slowing down. It's projected by 2030, that number could rise to 30%.

Last year, Ireland's grid operator imposed a moratorium on new data centers in Dublin, effective until 2028. But before assuming Ireland will completely restrict data center growth, it's critical to consider the economic stakes. Data centers have been central to Ireland's tech-driven success, attracting billions in investments from companies like Amazon, Google, and Microsoft.

Looking ahead, Ireland faces the challenge of balancing digital expansion with energy security. This will likely require a multifaceted approach. First, accelerate renewable energy initiatives, particularly offshore wind, which could not only power homes, but also the expanding tech infrastructure.

Second, explore innovations like waste heat recovery. Amazon is already piloting this approach, which repurposes excess heat from data centers to warm nearby buildings. It's a move that could mitigate some environmental impacts.

Finally, instead of clustering facilities in Dublin and risking grid overload, a more distributed model across the country could ease pressure on the power supply and spread economic benefits. The choices Ireland makes in the coming years will have broad implications with global demand for data rising. Other countries are closely watching as they weigh similar trade-offs between economic growth and environmental sustainability.

So digging into renewable energy as a power source is one solution, as I mentioned, as well as looking at other areas to potentially develop these data centers. But it is kind of a tug of war going on right now in Ireland. So that's why I wanted to take a closer look at it.

And of course, we have our Irish expert here, Mike Ard, to comment. All right, well, both my parents come from Ireland and I still hold citizenship in here and there, but it is a hot debate because the issue is, I think they're on a projection that said, if they actually built everything they approved for data centers, it would consume about 70% of all the power that Ireland is able to generate today. And that would increase pricing.

And there's a huge debate right now in Ireland over housing and the cost of electricity. And there's an election that's coming up on this whole issue, and it's not the kind of topic that's very popular. And some people would point out that there's already more than 80 of these data centers, and they've only added maybe 16,000 jobs.

So people are kind of scratching their head going, you know, what exactly is the benefit? I mean, I think the number is, they said that injected 7 billion into the local Irish economy, but outside Ireland, this is the same debate that's happening everywhere, right? Yeah.

We're seeing communities all around the world having the same conversation. These data centers are also a little bit on the noisy side. They don't exactly insert themselves well into the landscape, and we're not quite clear how energy efficient AI will eventually be.

But Steven, I know we've talked about this topic in the past, it's becoming, uh, not just a technical issue, it's a political issue. Yeah. And, and I think that, uh, Bonnie's spot on in, in her analysis here in that, um, yes, data centers take a lot of power, but uh, also the fact that they're so concentrated in the Dublin area is, is a real problem.

And I think that that's what we're seeing globally where, uh, data centers were initially built. I mean, Northern Virginia, for example, the San Francisco Bay Area, um, they are extremely, extremely concentrated in a, in a few spots, but over time they've been, uh, distributed. And of course, Ireland has a lot going for it in terms of data centers.

'cause number, it, it, number one, it, um, it still part of the European Union. Um, it is located, uh, as close as pretty much any other part of the European Union is to the United States. So a lot of transatlantic cables land in Ireland.

Uh, there's a lot of cables as well that go from Ireland to the uk, Ireland to France and so on. Um, but if you look at the map, which I actually did in preparation for this story, those cables don't all land in Dublin. Yes, a lot of them do, but a lot of them are in other places.

So for example, there's a cable landing in Kalala Ireland from New Jersey. Uh, there's a, a cable in, uh, Galway. There's, uh, cables that go to the UK that are on the southern coast in the southeast coast.

All of those could be data center spots as well to Bonnie's point. And, uh, one thing I'll say, number one, Bonnie, you definitely gotta go. It's a fantastic, fantastic country.

Beautiful country. Um, we went there for, for a honeymoon. Um, oh, nice.

Just a great place. Um, Irish people too. Yeah.

Um, but, uh, the west coast of Ireland has no shortage of land, no shortage of wind, um, no shortage of, and maybe can you power data centers on rain and sheep? I don't know. But, uh, maybe make it more sustainable by moving some of this stuff to the west coast on the south coast.

The Wind is a great point because Scotland right now, um, has huge, um, initiatives and wind right, uh, wind energy. So I, I agree. I think that that's a great opportunity for them as well.

I just wanna go on the record that Steven said, once again, it's the networking guy's fault. That's all I heard. Definitely.

Yeah. The wind comment was not a slight against Irish people talking, Mike, that was, don't take that the wrong way, that he didn't mean it that Way. If, if if talking generated energy we'd be self-sufficient, then there you go.

Well, there is the transatlantic cable that lands in Kark, and that's the, you know, you you got the Yeah, I'm trying to make some kind of lar stone reference. I think, I Think the issue with the networking stuff though is they want the software to run closer to Europe so that they can take advantage of the axis and the latency. So, you know, Galway may be on the wrong side of the island from their perspective.

Yeah, and it's, I'm sorry, I was just gonna say it's, you know, it's interesting that debate between that's becoming more political as, as Mike mentioned, a lot of it has to do with the pressure that they're feeling, um, to reduce carbon emissions and to meet those goals. So it's, it's really like coming from all sides of how they're going to settle this. The moratorium that I mentioned affected a deal that was supposed to happen in August with Google.

So, um, it is already a, a situation where, where not everyone is satisfied. So I think we'll see, uh, some changes ahead next year. Not everybody in Ireland is in love with that, um, climate change regulation because so many of the people out in the west depend upon something known as peat or turf to heat their homes, and that's now essentially illegal to do because it adds too much to the climate.

So guess what's been the latest and greatest thing going on for smugglers? People are throwing Pete in the back of their cars and smuggling it around to each other. Wow.

Black Market. Interesting. Yeah, it's interesting.

I, it, I mean, data is the new oil, right? It, it's, it's, whether it's in transit or we were talking about storage before, and it, it's interesting how much, not just the economy, but politics now as part of this, it, it almost reminds me of, you know, the, uh, regulatory bodies that control the spectrum that we use for wireless, right? This is allocated to that.

This is allocated to government, this is allocated to that. And we have so much, so many pipes going across the Atlantic and different oceans and, and now points of land are points of presence for these large data interconnection points. You know, we used to have inter naps, but we do have inter naps in the us right?

And now we have the mega versions of that just, I I'm thinking of multiple, you know, blade Runner or the kind of few futuristic movies that, you know, you gotta have data to power all those neon signs in, in the rainy climate that you're running in. Mm-Hmm. Yeah.

And, and the issue will come down and this, the cost of housing in Dublin is through the roof. And those people will say, wait, we're allocating land to data centers. Mm-hmm.

When we need housing, and then the data centers aren't generating jobs, they're gonna be like, you know, ultimately they're gonna say, this is crazy. And they're gonna be like, we need more downstream benefits to the local population before you go and kind of go build the next data center. And I think, you know, we saw that in this country where, uh, a lot of the politics didn't pay attention to the basic local economics and things changed.

And so don't be surprised when that election comes around in Ireland that something different happens. Well, besides a few jobs, and I don't mean to, to, you know, undermine what, what the jobs that it may add, but what's the benefit of having that data center there? You know, wherever the location is in the middle of Iowa or the middle of Ireland or whatever location it is, I think if they brought more value than, than just jobs and kind of indirect benefits to the economy, now there's a real reason why you want it there beyond just employing a few additional people, a few thousand extra people, and if they brought value that way to the, to the, you know, to the, uh, economy and to the community, I think there may be a much more of a positive view of having those things located nearby.

Mm-Hmm. I agree. All right, cool.

Well folks, we'll be watching this closely because it's gonna play out everywhere in the world. Yeah. And it'll be as election cycles come forward, this is gonna be a bigger, bigger issue all the time.

Hey folks, I wanna thank you all for being on the show today, sharing your knowledge and insights. Great to be here, great to be here. I'm so glad that we could make the green pun too, Daniel.

It's all about puns at the end of the day. I mean, what's the point of having the show if you can't have puns? We Need a, we need a good limerick to end the show.

Are you ready? Ready, Mike? Uh, I'm not quite ready for that, but your Relatives could do that on demand, Mike.

There's, there's just, there's a whole county in Ireland if you lack, so you just go visit Limerick and you'll have a great time. All right guys, thank you all for watching the latest episodes of the Textron Gang. We have tons of great content coming up right behind this, and till then we'll see them.

This is Textron tv. Hey everybody, welcome back to CubeCon plus Cloud Native Con in Salt Lake City. We're here with Azi Faan and Daniel Cook from Stack Gen.

And we're talking about, well, a different way of thinking about infrastructure's code. Hey guys, welcome to the show. Thanks For Having us.

Thanks for having us. Everywhere I turn around, there's somebody talking about infrastructure's code, and there's a lot of debate in these community now, and some people are unhappy with other folks, but, um, I guess I'm gonna ask the question to you. Is there a whole other way of thinking about this thing that we're kind of missing?

Absolutely. And that is what we have come up with and that we refer to it Stack Gen as infrastructure from code because, uh, the past 10 years or so, right, seven to 10 years, uh, Terraform has reached its maturity. It has become overly complex.

So all the arguments and the discussion that you hear about, uh, about how to make infrastructure as code, they're primarily talking about Terraform and how to streamline it, how to just deal with that complexity. And we strongly believe that every enterprise and every organization that is dealing with and using and managing infrastructure as code, primarily the Terraform files and so on, and the templates, they should be thinking about infrastructure from code. We're here at CubeCon.

Um, how does that thought process apply to cloud native applications and Kubernetes? And, you know, 'cause we're all in love with those ammo files, right? Well, yes.

Um, so, you know, we asked this community what they thought about infrastructure as code, and they all said it was hard. And you know, in this community specifically, they're looking at Helm charts going, wait, what? So, you know, we wanted to remove all of that problem.

And we actually asked the community what they thought, like, is infrastructures code easy? Is it hard? And only 13% of them said it was actually reached a mature level in their organization.

People are struggling with it. And 97% of the people we asked are like, it's hard. It's hard to write it, it's hard to manage it.

Like we don't know what to do. So when we looked at it, and you know, the reason we're here is because, you know, we wanna make it easy. We wanna make, you know, your helm chart creation, your infrastructure code easy.

And we don't want you to have to be working through your YAML files to figure out how to deploy an application. One of the dirty little secrets of it is that a lot of the security issues we deal with are directly related to Misconfigurations that resulted from somebody who didn't really know how to use the tool in the first place. So if I'm gonna do, um, infrastructure from the application rather than me the developer can, will it be better outcome?

Will I have a better implementation and a more secure configuration? Absolutely. So there are two problems, uh, associated with people handcrafting infrastructure as code and managing them over a period of time manually or through using some clergy tools, if I can call it that, right?

The way infrastructure from code addresses that problem is that rather than taking a reactive approach to scanning the infrastructure as code after it has been written and it has been rewritten or corrected, infrastructure from code basically takes into account the policies that need to be applied and builds in those policies in the form of specific configuration. So as a developer, just to be very specific, I don't even need to care about what kind of security or in compliance policies my application deployment needs to adhere to and in first place as a developer, most developers do not, not just care about it, they do not also know about them. You know, so that is how infrastructure from code solves a problem, making it built in rather than be reactive and do this post scanning and then remediating and fixing all of those issues, Right?

I think we skipped one step here. How exactly does the thing work? 'cause a lot of people are gonna be like, well, that sounds great, but you know, is that magic or what?

Uh, there is a bit of magic and there is a bit of a lot of hard work as you can imagine. So when we talk about infrastructure from code, let me start by defining it, right? So code is when, when we say from code, code is not just the application code, code could be from our perspective, there are four different things that we support as infrastructure from Code.

One is the application code itself doing the static code analysis, which is what Stack Gen platform does, infers the, uh, the infrastructure related dependency that an application has, generates the topology, presents it to the user. And then once the user has confirmed that the deployment topology looks, looks right, stack Gen goes at and auto generates the deployment files or the IAC files with builtin policies like I just mentioned. The second flow is that the user could be a DevOps engineer, may just say that, Hey, I do not have access to the application code because I'm not an application developer, but I would still like to create the infrastructure.

Those DevOps engineers or such DevOps engineers or users could actually go and use our canvas, which we call as the visual builder, and drag and drop all the resources that they need with all the iams and the rules and the policies built in and generate the corresponding infrastructure as code for them. The third approach that we support is, uh, you could already have applications that are deployed and resources provisioned in the cloud, and those resources could be provisioned from, uh, the cloud console, like AWS cloud console and so on. We can reverse engineer, or the Stack Gen platform can reverse engineer the, uh, those deployed resources and configured resources and generate the infrastructure as code for you.

The fourth, uh, flow that we support, uh, sorry, please bear with me as I lay out all the details. Um, the fourth floor that we support is, uh, you may have used Terraform for provisioning the resources in the cloud, but those Terraform templates on your files would've gone out of date, right? I mean, they are outdated because they were created and never managed, and the users were going directly to the cloud and making the changes and so on.

So if you give us the state file, right, we can reverse engineer your Terraform State file, getting into specific details here, and also generate the latest and greatest compliant security and governance policy compliant Terraform code or IIC code for you. I'm curious, based on what he just said, there's a lot of people talking about platform engineering here at this conference. Where does that fit in your construct a little bit?

'cause as I understood what he just said, well, if I do that, then maybe I don't need this massive cultural change to make the entire environment work. Or, you know, am I, is that overkill or is it a response to a problem that we can solve another way? You're, you still need your platform teams, right?

The platform teams are creating that paved road, you know, they're helping developers with their experience, their velocity and whatnot. But this is one slice of that puzzle, right? Developers are slowed down because they're having to write their infrastructure as code and the platform teams or the DevOps teams, they're having to audit those things and, and, and support their developers when they're going, I can't get this out and I'm delayed and the business wants me to be deploying this new feature, this new application, but I can't do it.

They, it's taking away from the platform teams actually making the platform better. So we're just eliminating that burden to all of the teams by going, Hey, we got you. We're gonna make you more secure.

We're gonna standardize this and you're not gonna have to serve as this help desk for the devs and they're gonna be happier. The other thing everybody's talking about is, you know, ai, so where does AI fit in your mindset in terms of this construct? Does it have a role?

Am I gonna use agents at some point or Absolutely. Uh, it, it does have a, the short answer to your question is that it does have a role. We are already using Gen AI capabilities for some features within our platform.

Uh, what I just talked about, the canvas to code feature, the users can just use our gene AI prompt and basically just describe in natural language. Currently only English is what is supported for prompts. Um, they can describe their entire topology in, uh, in, in natural language and get that entire topology diagram be presented to them on canvas and auto generate, or get the IEC files that are autogenerated in terms of, uh, using gen AI based agents for analyzing the source code.

We constantly experiment with various different LLM models that are out there, and both open source alama and the closed source ones, right? Like the ones from OpenAI and such. What we have realized is that they hallucinate big time, you know, and so what we are talking about is the problem that we are trying to address is, hey, developer, you do not, one of the flows that we were talking about earlier from an infrastructure, from code perspective, you do not have to wait for the DevOps, uh, uh, engineers or the DevOps team to be creating the Terraform files for you.

What that means is whatever is the replacement for that existing process has to be reliable. Okay? If we were to use Gen AI tools the way they exist and create something which are let's say 99% accurate, which means for the one per percent, the remaining 1% of the confirmation, the developer would still have to go back to the DevOp DevOps engineer, and then we are back to square, uh, uh, square one, where the deployments are getting delayed and fingers are pointed or blame being passed around as to what caused the delays.

This Is the difference between probabilistic and deterministic, right? Absolutely. Absolutely.

That is, I'm so glad that you brought it up because our approach is completely deterministic. You run it and it is item Putin, which mean you run it 100 times, you're going to get exact 100 the same result 100 times, or the Terraform files with the same set of configurations. You've had a number of customers do this at this point.

What have you seen them do? Well, what are they, you know, what's your advice based on what you've seen and these people kinda learn and, you know, what's the thing you wish people who might do this would learn earlier and avoid? Well, I think it's a crawl, walk, run approach.

You know, we are disrupting the infrastructure as code industry. So when we have customers, they might not be ready for the full generative infrastructure from code, but they do need help and they need, you know, help with their state files and they need help with, you know, what, what exists in the cloud and what doesn't. And we're able to support them on that journey to go, let's start here.

Let's clean up what you already have as infrastructure, as code, and then let's create views that your teams can easily use. And then we're going to get you to generative infrastructure from code, because that is where the market's changing. One of the cloud service providers say about all this when you present it to 'em.

So a lot of the, a lot of the vendors are in support of it. So we work with AWS, we work with Azure, uh, we work with GCP and you know, for those, the, for the vendors, like they're a, people are consuming more of their cloud resources, but also a lot of them want you to move from one cloud provider to another. And we can help that because we can translate one language, you know, one infrastructure's code that might be deployed in one provider to the next one.

So we make that migration easier for companies who, you know, maybe they're wanna reduce their cost or maybe one provider's paying them to move there, Maybe, heaven forbid, they want to go back to an on-premise environment because the workload changed, right? Mm-Hmm. Yeah.

Actually it is interesting that you brought it up, uh, because, uh, our recent, uh, support for OpenShift, uh, is to support that, those kinds of use cases that, um, there could be workloads, application workloads running without taking the name of any specific public cloud service providers in the managed Kubernetes service. And if certain customers are enterprises, they want to bring it, bring those workloads, application workloads onto Kubernetes clusters, um, especially managed by OpenShift that they're running on-prem. That's the use case that we currently added this support For.

And to your point, despite everything being open source, those configurations are not very portable, unless I have some tool that runs back off the software rather than the developer, Right? I mean, loads of people talk about, Hey, multi-cloud and we wanna move from this cloud to this cloud, but the reality is it's hard. And so, you know, unless there's a compelling business reason, which we know, you know, the cloud providers all want that money, uh, so they might entice the company to move.

Well then at that point, you know, people don't do migrations from cloud to cloud every day, but we just translate, you know, from one provider to another. And it's, it's almost like a translation layer. All right, we are coming up on 2025.

What's next for you guys? We just keep building and keep selling. You Know, We are very happy with, uh, all the traction and the interest that we are getting.

Uh, and the way actually we are thinking about it, one of the thing that instantly resonates in the very first meeting with any of the prospective customers, and we are targeting large enterprises, is the vision that we are carrying. You know, and as I laid it out, and as Daniel just laid it out, that, uh, we are giving them an approach. There are two distinct things.

One is they can adopt Stack Gen in a crawl, walk, run kind of approach. And we have built a platform that meets them where they exact they, they actually are today, which means we have the support for custom resources. Bring your own Terraform modules, bring your own helm charts, right?

Bring your own policies. So we are literally taking the platform to where they are, and then slowly, metaphorically speaking, uh, we are handholding them and taking them to the promised land, right? Which is infrastructure from code, so that they don't ever have to worry about the Terraform files and have charts going forward.

All right. Cool. Hey guys, thanks for stopping by.

Thanks for having us. Thank you so much. It was nice.

Say, if you can see your process, it's probably broken. Infrastructure's code is probably broken. We'll be back in a minute, guys.

And stay tuned for the next episode. This is Textron tv. com here.

We're live at CubeCon in Salt Lake City, where it's been snowing. I've got a chance to break out all that winter, uh, clothing that I've had packed away in my closet. But we're here and we're interviewing people and meeting people.

It's a great cube con. I think they're expecting probably the largest cube con in North America to date. I want to introduce you to my friend Alex.

Y Alex is here. He is the CEO of a company called G-M-I-G-M-I, Cloud. Cloud.

Yeah. And if you, if you missed it, I, I actually did an interview with Alex about two weeks ago, um, on regular tech strong tv, but we took advantage of us both being in the same place this week to, to catch up again. So, first of all, Alex, welcome.

Is this the first time you've been to Cube Con or, Uh, to Cube Con also Utah. And this is the first snow, uh, of, of the year for me. Is it?

Yeah. Well, I, I don't wanna embarrass anyone but one of our camera people, this is the first time he's seen snow coming down too. Oh, okay.

He was very excited for it. Um, but I, I've actually been to Salt Lake City before, but it's a great cube con. You could tell how big the absolutely showcase floor is, but there's also some great content.

Alex, for people who maybe didn't see our first text on TV interview and they're not familiar with GMI cloud, give us kind of the short version. Yeah. So first of all, GMI stands for General Machine Intelligence.

We're here to build the a GI future. So does that mean, right? We wanna build, uh, a cloud or a AI platform that allows anyone, or any engineers or any founders to build an AI application instantly, right?

So think, uh, I would say Wix or Squarespace for ai, we wanna make it seamless, make it easy, abstract all the difficulties on deploying ai, uh, including infrastructure to model selection, to data ingestion, migration, all of that under one view, one panel. You know what, one of the things I got out of our last interview was, look, there's gonna be plenty of infrastructure providers, hardware providers, right? That's right.

Who we're gonna offer you sort of, let's call it GPU as a service, but that's not the GMI model. No, yeah, it's not pure GPU as a service. It's actually that's prepackaged AI applications in here.

That'll, or maybe not applications, let's call 'em AI building blocks that allow you to build your application really rapidly. It's almost, you know, rapid application development for AI apps. Correct.

Uh, on state-of-the-art GPUs as well. And that's, you know, it's kind of a unique kind of offering right now in the market, I would say. So, so I think here's what I, what I see, like, you, you, you're absolutely right.

So the current state of the market is people are just selling boxes, essentially. Yeah. Here's, here's some GPUs, if they break, we'll try to solve it and, uh, please don't come, come, come, come back to us if, uh, if it breaks that, that's kind of the mentality.

And then if you don't, if you're not, uh, ordering, for example, this is pro for high per scalers, right? If you're not ordering in a large quantity of say, say 10, 20 million bucks per year of cloud spend, then we're not even giving you a, I would say, a, uh, a account manager to support you and not to mention adding the features that, that you want. Um, where we do differently is we want to offer a service.

I think, I think GPUs are cool and, but people, well, people come to us, uh, buying GPUs, not because they think GPUs are cool, it's just buy for fun. Right? But they're, but maybe for fun, but to build a solution well, To, to, to experiment at this exactly.

Between a lot of them To, it's to, to experiment, to build a solution. And we're here to help them to build that solution. So there's founders who are building biotech, founders who are consolidating all the weather patterns together and predict, I would say agriculture yields or, uh, predict, I would say the, the, the next, uh, potential disasters with disaster recovery, all all that stuff, right?

And we want to enable them to build that. And it's, we see that it's so difficult to build an AI application. And so we, you, we just want to enable that and make, make their life much easier.

So instead of hiring 20, 30 people, including infrastructure, including, uh, ML engineers, including full stack engineers, you just hire data scientists, and then we handle all the difficulty, all the infrastructure. Uh, So I mean, obviously you think this, but this, this is the model for a new age going forward. I think So, right?

Don't, don't spend money trying to find difficult to find folks who, who, who play in that space, right? Yeah. All, as you mentioned, the full stack people, the, the infrastructure folks, all of that.

cloud, Gmi cloud do ai. That's right. Okay.

Wanna make sure people get that? Alright, let's turn to CubeCon a little bit. Yeah.

Look, cloud native has become sort of the, the compute stack of choice. That's Right. Right.

Especially greenfield if you're building a new application Yeah. On a brownfield, I think something like 80% will Everyone's building on on right. On Kubernetes containers, microservices.

How is what you are doing at GMI work with that, play with that. Uh, So we actually offer a lot more flexibility. So, uh, I gotta say two things.

One, we can connect their on-prem, if they wanna choose on-prem or, uh, our public cloud or hybrid, we can offer those solutions for them. And we have our Kubernetes, uh, man kuber managed Kubernetes environment sitting on top. So we built a orchestration software, um, that's built on OpenStack and Kubernetes that we can decouple from our GP services.

And so for companies that already bought the hardware, uh, and bare metal, frankly is a bit difficult to use Mm-Hmm. So we actually can license that entire stack to them so that they have a, call it AWS on the go and, and for their on-prem services. Yeah.

So those are, I guess, one differences, but aside from, uh, using, uh, K eights, we actually can offer people, uh, manage, I would say bare metal to vm, uh, HPC slum container and ate. So we have that options for The Whole spectrum. Exactly.

Exactly. So it's a, I would say it's a grander and larger architecture that allows people to have really, uh, high flexibilities on the type of workloads they want, because some people want route access, right. And then to, to, to, for, for their workloads, and they have their orchestration then, you know, we want, we don't wanna interfere with that.

So, I mean, you as a service provider here, you want to give people ultimate flexibility, cover any option they may want. Looking in your crystal ball though, do you see cloud native being the dominant compute stack here for, for AI apps going forward? Or do you think it's gonna be, I, I think so.

I mean, if you think about GCP or Azure or, or AWS, how, how they, uh, grow to the size. I mean, if you think about what these clouds are, they're essentially a wrapper on serv servers. Mm-Hmm.

Right? And then if you call AWS, like, oh, so they're just selling storage essentially. I think that's a, that's, that's not fair to fair to them, but that is the, the current state of the market, it's the GPUs.

Can you imagine, like right now the state is actually, you can go to brokers and say, Hey, I need, uh, say one year of GPUs, and they'll just find you that, that I would say basically EC2, right? Somewhere, somewhere from a random vendor. Right.

It, it's unimaginable to, to, uh, I would say the traditional world. And so I think that will consolidate, move to, uh, I would say a, a cloud environment, but frankly for last year or so, it's just because the supply chain is so constrained, right? All you have to do is just like, Hey, I got, I got a thousand boxes, so rent from me.

Right? But as that supply matches, ma matches up to demand, people will require more, I would say cloud native solutions or, uh, or solutions that enable them to build better applications. They're, they're not Gonna c Exactly no way metal.

That's, that's, that's not how it works. You Know, you said something in our last interview that I remember you said, I wanna sell the picks and shovels. Right.

And, and it's true. I think the people today who are saying, I've got GPU boxes are saying, look at this gold dust. Yeah.

Right? And eventually, I, okay, Go ahead. Actually, I wanna revise that.

Okay. So go ahead. Nvidia is the one that sells picks and shovels.

I'm the one that buys a lot of, a lot of picks, a lot of shovels. And I, so, And Nvidia manufactures the picks and shovels. You wanna be Walmart?

Yeah. Not Walmart. Or I buy those, I buy those axis and I wash it clean and lease it to people.

Okay. And when they're done with that, I take it by and wash it again and give someone else. And aside from just having patient shovels that to rent to people, I also have the gold depending, uh, thing, right.

And also washer All, Whatever they need, like the goal for them is like, I want to help you find gold as soon as possible. So whatever machinery, we got it. Right?

I got it. But it's not just buying a GPU. No.

So all the stack from, from finding a gold, right? Yeah. And, and I think that's an important, again, I'm gonna emphasize that it's not even just the cloud native stack.

Yeah. It's the app building blocks on top of these things. Super important.

Yeah. So I'm gonna put you on the spot. We're here.

It's, it's early, right? We, we've doing this early in Q con, it's, it's still not even open here. Um, but we're almost at the end of the year.

Hmm. What are you doing for a second act? What's, what's new coming up at GMII?

Yeah, So you could talk about it. Yeah, yeah, of course, of course. So right now we're focusing on, I would say the infrastructure.

So we wanna build a vertical solution, but you need to have a very strong, strong foundation, right? Just building a tree in a very strong roots that goes into, that's why we, we chose a much bigger architecture using, uh, OpenStack so that we have a very strong foundation. But, so that is, we call it the cluster engine, basically a very powerful orchestration software that managed and oversees and predict all the potential failure of the, of the GPUs, right?

The next step is, I would say we call it the inference engine, right? So that, that will be rolling out end of this year, uh, sometime Q1 next year. 99%, which is, does not exist in this environment, right?

Because the GPUs fail so much. Do they, I don't know if people realize that For, for the people who are, for the people who are training, uh, with their, uh, They realize it, they live, They know, they will know. Like for, for example, like, uh, when meta, well, this is Publix.

So when meta is training LAMA three, I think it failed a hundred plus times in a, in first 30 or 45 minutes, five days. So on average, they break down every three hours. Wow.

I think their SLA was like 50%. Can you imagine that? 50%.

50%. So I've been in, I was in the data center business Yeah. The turn of the century, that sense hope.

But back then, you know, we were promising five nines, right? That was the standard five nines. CPU is e much easier.

CPU is much obviously the, So GPUs is, is super hard to manage. Um, and so one thing is having a very, very strong, I would say SOP to manage the GPUs, make sure when, when things fail, we have a very robust team that can re that can react in, in 15, 30 minutes to, to help customers. But more important is, I, I think on the software, because we cannot prevent the, the GPUs from failing.

That's just, it's just a mathematical non-zero chance. It's Part of the, it's right now anyway, it's part of The Yeah, it's 200,000 points per, per server, right? So rules, yeah.

It, it, it's math, right? Math are big numbers. And so what we do differently is essentially we'll kick in all the, all the, I would say, uh, all the available GPUs in when, whenever one goes off.

So to, to the customer, they don't care, right? They just say, Hey, I got, I got 100 tarros. Right?

And then that's, that's what we will promise them and they can give us a constraint. What You do on the backend Exactly. Your business.

Exactly. Exactly. So we, we are, we we're rolling that out and no one's offering that this moment.

I'm really, And you pulling that in inference, Inference engine. Yeah. I love it.

Yeah. Not to put the, you know, I don't wanna put you on the spot, but when do you think we might see this inference engine? Uh, so we're rolling out beta.

Okay. Uh, to, to, uh, I would say pilot customers, uh, by before end of this year. And then, uh, ga uh, between January, February-ish.

And how do you become a beta customer? GMI Cloud Ai. ai, yeah.

Or reach out, reach out to us and I'm happy to do a design partnership with you guys. I love it. Yeah.

Alex, I think you're gonna love your first cube con when you get back home, reach out to me. We'll do a text on TV and we'll compare notes and see how it went for you. Sounds good.

All right, man. Hey, thank you. Congratulations.

Great to see you in person. Good to see you as well. ai here at CubeCon.

We're gonna take a break. We'll be back. We've got a lot of CubeCon coverage coming your way.

Hello and welcome to the digital CXO Leadership Insight series. I'm Amanda Ani, and I'm excited to be here today with Mario Pania. And he is with Anello Photonics.

He is the CEO. How are you doing today? Good.

How are you doing? Doing well. Glad to have you on our show.

Can you share, share a little bit about your company and what services do you provide? Sure. So we're, uh, uh, a startup, but now we're four and a half years old, so it's not so much a startup anymore.

But, uh, we're out here in Silicon Valley, uh, and what we've done is we've created the world's first optical gyro that's fabricated based on integrated silicon photonics. And so you say, well, first of what's an optical gyro? Well, there's two types of gyros.

Um, there's a gyros in your phone, which you can use for when you, every time you lift up your phone, your EarPods, your iWatches, there's these what's called MEMS based gys mechanical machine to membranes. They're dirt cheap billions of units a year, but they're not very accurate. They're okay for motion, but if you wanted to do high precision navigation, they're not very good.

If you go to the second class of gyros, you get what's called fiber optic gyros. And these are based on sending light to a coil of fiber. And as that coil rotates light going into different directions, moves at a different path length as you rotate the light going in the same direction is, goes a shorter distance than the others called the SAG neck effect.

And you can correlate that path length difference to a phase difference of light. These fiber optic gys have been around for a long time. This is a 3D print of a, a typical fiber gyro.

They're coffee can size, and so maybe the reas readers will remember what coffee can, uh, terminology is. But they're, they work great. They're in all the ICBMs fighter jets, submarines of, you know, if you look at a submarine, it's probably got a, a gyro the size of half of your desk.

But it's very accurate and very precise. And so when we started looking at the autonomy world, autonomous cars, autonomous trucks, we need high precision. But you can't afford a 30, 40, $50,000 fiber gyro in a box for the autonomous marker for the mass market.

So we decided to create a completely new way of designing fiber gyros. And we've created what we call side fog. It's a spoof off of fiber optic gyro, silicon photonics, optical gyro.

And this is the silicon photonics, optical gyro that we've created. 3 volts, not susceptible to temperature, not susceptible to vibration, but very accurate. But more importantly, because it's based on semiconductors and pick and place, you can actually produce this in high volume, which means you can actually drive the cost down.

So now we've created this first new gyro in 20 years that provides high precision that can be mass produced. Wow. So that's the core technology at annel.

Yes. Much smaller. The difference there is considerable.

And so those are much more affordable as well. Yeah. And so now the key thing is, so we don't sell sfog.

So while this is the core technology, we put it into systems, and that's how we get the navigation solution. So if I take an the sfog and I put it into a box, this is our, one of our products. I'll explain how it works.

This has two GPS chips. These are two antennas. It has a CPU in here for intelligence.

And A CPU allows it to do functionality. We can take algorithms in, we can take what's called central fusion cameras lidar radar. And it's in a sealed unit.

It's hardened stalled spray. You can throw this in the pool, but there's one optical optical technology. So for land vehicles, even though you're moving around up and down, but you're on the ground, you're constrained to one dimension.

So we are shipping this product today into customers in agriculture, uh, farming, you can imagine, um, construction mine. So places where you can lose GPS, right? And so I'll now explain afterwards how this works.

And this is for land vehicles with GPS, if you don't have GPS and you're in a building, we have the similar product, but this is without the GPS. And this is for robots, an indoor navigation where you're, where you don't have any GPS to start with. And then the cool thing is, if I take three of these and I put 'em in a cube, now think of this.

I have a, a hand, this is the world's smallest three axis IMU and this is now for things that move in three dimensions. So drones and maritime, if you're in the water, right? That move around.

And so look at the comparison. Oh wow, this is the state of the art today. This is what we've launched with the, we call it the X three, three times.

mm-Hmm. Um, and this is what we're shipping today to customers in maritime and for drones. Wow.

So you gave, um, uh, some examples of where we could find these. Uh, are there specific examples you can share of where you can find this today and and the use cases of, of those vehicles? Yeah, Let's let, let me explain how this works.

And this is where the combination of a system comes together. So let's take a use case of orchards. People wanna do spraying in orchards, right?

It's a nasty thing. They wanna fertilize, and they typically do it at nighttime. They don't want people there.

It's dusty, dirty, uh, dark. So cameras while they work, they don't work that great. You can use lidar, but it's very expensive.

Um, but you comment, combine those things. So the agriculture problem is very simple. Let's take an orchard, for example.

You're going up and down a row that row's roughly a half a mile long tractors running three to five miles an hour. And you have to stay within a row because if you drift, you'll hit the trees on the side. Right?

Now, in the fall, if you can imagine this, an orchard has leaves. And in the fall, the leaves come in and the water and the leaves absorb GPS signal. So in a dense orchard by, and we were just, we've been testing down in Fresno here in California by September, October, there's lots of leaves before they start falling off.

And every time you go into the orchard, it's like going into a tunnel. So when you drive your car and you're in a tunnel, there's no GPS. So what happens, we have a system.

If you have GPS use it, right? Every millisecond we check, and you can navigate with GPS. We have an algorithm that says, okay, I'm losing GPS as like going into this orchard, for example, as I lose GPS, we have an algorithm that weighs more of the output onto the optical gyro technology.

And if you completely lose GPS, you can then navigate entirely with the optical gyro. So we can now go up and down these rows and orchards very accurately, very precisely by simply navigating with our optical or I-G-N-S-S-I-S unit. So there's a use case of navigating in an orchard for an autonomous vehicle or autonomous sprayer.

We have been shipping this to customers. Unfortunately, two or three of the big customers do not wanna say what's in that system and give away their technology. So unfortunately we can't talk about it.

But you can imagine the big companies, if we go on our website, we have some engagements with some big companies. But this is an example of, I'll call it an agriculture use use case. Let me give you another use case, and then I'm gonna talk about spoofing.

So let's talk about long distance driving. And this is of interest more to the DOD. So now you have a vehicle, you're driving 30, 60 minutes, you're moving 30, 50, 80, 70 miles an hour.

We've demonstrated that we can take this, simply put it on your dashboard. And Gerard, we have a video that we just put on YouTube last week that we can actually send you, you can attach it, but we show it. We literally put the unit on the dashboard.

We have algorithms that correct for any misalignment. You can retrofit any vehicle in 15, 20 minutes. But now we can drive and, and when we do physical driving here, we disconnect the antenna.

So there's no GPS, but here we're driving. Think about this a hundred kilometers, I'm gonna mix and match miles per hour. We're going like a hundred kilometers of driving on a highway up and down in the mountains.

No GPS with less than a hundred meter lateral air. 1%. So think about this.

You went a hundred kilometers no GPS, and you know your distance within a hundred meter. And why do I call that A DOD use cases is because if you're out in the middle of a desert or on a battlefield, we just wanna know where the vehicles are relative to the don't, it's not a safety condition where you have to stay on the road, right? So that's jamming and that's easy.

If you're in a jammed area, you lose GPS. You can rely on anello. Let's talk about spoofing.

'cause this is where I think a lot of stuff is. So now spoofing is, and what's happening today, unfortunately, in Ukraine and Israel, because of the war torn areas, it's jamming and spoofing all day long. So if you take your phone and Israel and you drive and you wanna navigate, it sends you to Beirut or send you to Lebanon or send you, because the area's being spoofed for anything coming in that's using GPS, it's being spoofed, but you can't tell it's being spoofed.

So what do we do? We have an algorithm. Because of this accurate technology you're driving every millisecond we compare where an anello says you're at to where GPS says you're at.

And so think about this, a man, if you're driving and all of a sudden Anello says you went a hundred meters forward in a millisecond, but GPS says, you're in Texas, hey, something's wrong. You're being spoofed. 'cause the signals look the same, rely on anello.

And so we now have done lots of testing with the DOD where we've tested under real jamming and spoofing conditions where we don't get spoofed. 'cause we have algorithms that it's not just, Hey, if you're physical, like you're driving and all of a sudden you're at 90 degrees, that that's not physics. So you know, you're being spoofed.

And we look at about 10 or 15 different parameters. Hey, the elevation change or the pitch and roll change. We have all these things that we're constantly, this is the algorithm piece.

But because we have such an accurate technology, we can compare real time our position to what Anella says. And now we can't be jammed or can't be spoofed. And this is the benefit of an optical technology, because they're photons, they're light, they don't interact with anything.

So we've created a technology. Now, this is for land vehicles that can navigate for extended periods of time, whether GPS is jammed or spoofed via defense mechanisms or, or unfortunately, conflict areas. Or if you're in a barn, you're in a tunnel, you're underground, you're in a cave, you're in a orchard.

The GPS jamming is the, the result is the same. Our products and navigation solutions address those conditions. Does that make sense?

Yes. Those are some really great examples that I appreciate you sharing. It seems to me like this could even be helpful for personal use cases down the road.

Let me give you a drone use case, and then we'll talk about the personal use case. So the drone use case now is very similar, right? We have this three axis, and because of the size, weight, and power, a lot of these drones aren't very big, right?

So now you're flying a drone and the drones rely a hundred percent on GPS, the autopilots that are used navigate with GPS. So what happens now, if you lose GPS, the drone doesn't know what to do. It can't turn around and return the home.

It can't go forward. It typically sits there, hovers and crashes. And so unfortunately, these conflict areas in Ukraine and others, drones are being jammed and spoofed all day long.

So what have we done? We've seen, hey, we have a nello. It's small enough to be retrofitted into drones.

You now fly. We have an algorithm that says, Hey, you're losing GPS, don't worry, rely on anello or you're being spoofed. Don't worry, relying on jail anello.

And then we can fly through those jammed regions because of the accuracy we have. And then when you come out of those reasons, regions, you can navigate back onto GPS or you continue to navigate. And here we're doing 10 to 15 kilometers, uh, of flying.

And we have other sensors. So in this case, we take wind into account. Like if you're flying and there's a big wind, you have to subtract out that wind to correct for the drift.

Um, similarly, if you're now on a boat and the world is moving to a lot of autonomous things, right? Autonomous boats for autonomous UUVs, a above water below water drones, similar thing. We're actually testing this right now out in, uh, uh, in the water.

We did some, uh, testing with Navy and the Naval X, where we take the same thing, we're up on the water, um, but we can subtract out the currents. And now when you lose GPS, and it's the same thing in the, in the water, if you turn around, there's, the cameras don't help you, right? All looks the same.

So now we've created solutions that are addressing land, air, and sea, okay? And these are the existing products we have today. But you hit on a very interesting thing.

What's coming? What can we do with this? So think about this.

What we've created was a low power, small form factor, very sensitive optical gyro. So because it's low power, you can potentially operate on batteries. And so think about this in the future, and we just won an army about two weeks ago.

If you look in our website, we had a press release with the Army X Tech. And that funding, it was a phase two proposal to build a handheld device. So think about this.

Now, you can take these, this is our first generation, and the next generations will be smaller when we integrate the more the electronics and PLAs. But now I put three of these together in a little handheld device that every soldier, every person, every emergency, uh, responder can carry. And now whether you're in a building, not in a building, you're in a GPS area, not in GPS, you can tell where you're at and navigate any place, any point with or without GPS.

We can put other sensors in there with accelerometers and tie up endometry. You can tell where you're at on the floor. And so this next evolution is going from physical big things.

The next generation is to maybe man portable, making smaller devices. So this could be the next generation device that will shrink it, right? And now you're going into more consumer drained drones in the future, if drone deliveries happen, you know, those, the, those things can be jammed or spoofed too.

And then longer term, as we continue to integrate, there's no reason in the future that this stuff can't happen in your phone, right? So if you're never using Uber or Lyft and you're on, and you wonder why sometimes you're here and it's, you're really across the street, it's because the GPS is bouncing off the buildings and your location is off. So just think about as we continue to integrate anello and integrate more and more functionality, eventually we'll have one little chip that has everything, a little laser running around in a spiral or a ring, and then we'll have a nello as the core technology in every device going forward.

That is really fascinating. My mind's turning with ideas. And I would think it, you could also put it in search and rescue robots for, um, dangerous rescue missions that, that are very dangerous to humans going into tunnels underground and things like that, that you could somehow put this in robots and use that.

Um, and, um, Absolutely. So we've done testing in tunnels already where we actually have people going through tunnels. We have robots.

It's funny you said that. We did a test, um, with some robots where we went underground in the tunnels. And you can actually sort of, you can map out, because again, you're not depending on anything, you're depending on itself.

So once you're, you know where you're at, you can then navigate using an lo, um, on a robot. And we've done these in, in various tunnels. Same thing underwater.

If you go six feet underwater, whatever, three feet, six feet, there's no GPS signal. The water absorbs everything. So unmanned surface vessels, unmanned underwater vessels, robots that work underwater, we now have a technology, because again, the fact that we're basing this on integrated photonics and high volume manufacturing, you can bring not just the size, weight area and power down, but the cost.

And that cost allows you to put it into mass market places that predominantly were only for the high end. That make sense? Yes.

Very fascinating. So when you look to the future, you've given a few examples, but, um, what do you see for the future a couple years from now with this technology? Um, I mean, when I look in the future, I just starting to see the use cases are starting to explode because a lot of customers, we're talking to the obvious ones who are using fiber gyros today, see a value of like, oh, I can shrink the size, I can shrink the performance.

Now, we're not going after submarines, right? I'm not trying to build a a submarine type jar. We're also seeing a lot of people saying, oh, I didn't know that technology existed.

Oh, I have lots of applications because of affordability. And so a derivative of what we're just talking about, we talked about farming, construction, but think about areas like in Israel or around Ukraine and Poland and all the other places because of jamming and spoofing, even the delivery vehicles. You know, people in Israel don't, can't use their phones.

So Uber, FedEx, the similar ones, uh, UPS, um, Amazon, the similar people, they can't use their phones for mapping. So we provide, potentially have a solution now from the commercial perspective to help people navigate in areas that were, because of, unfortunately, of a conflict area that are affecting the commercial area. And as we continue to improve the performance and shrink it, we're just applying it to more and more use cases.

Um, as I said, it just everywhere. When you think about anything that moves, anything that wants to be autonomy or anything that wants navigation now that we can see a sort of a mellow inside every vehicle and longer term, you know, eventually this'll be in every vehicle as a standard technology because it does provide safety, right? If you have an accurate technology that knows where you're at every point, every, that's not dependent on anything.

Now you can stop if you needed to or you know where your location is. If you're in a tunnel and something goes out, or if you lose your GPS, you can pull over to the side of the road. And then in the future maybe, you know, we'll have these things.

Not only navigate, but also communicate with each other so you can know where the position is and maybe we can stop people from crashing and other things. So I do think it's an endless, um, set of applications all based on, you know, this fundamental big, big change that we did. And by the way, this, you know, it took us quite a long time to build this first sip fog.

It was a lot of learning. Um, there were no models, there was no one, you know, we did something radically different. You had to put out a test ship, we had to create our own models, iterate it, put it together, you know, we're measuring for those in the technical audience.

If you think about phase, we're measuring 50 nano radiance of signal. That's 10 of the minus nine tiny, tiny, tiny signal with all the temperature and noise and the environment. But we measure it very accurately.

And so we're quite excited that, uh, not again, SFO is the core technology, but now we created a navigation solutions that address land, air, and sea. And then over time we'll take those to, to bigger markets. The industrial market, eventually the consumer market, and then, uh, sort of an l everywhere.

Well, congratulations. It seems like it's going to impact many different industries. If there was one key takeaway you could leave our audience today with, what would that be?

So the question should ask your audience is, what does a MELO mean? So an Melo is Italian for Ring, so the name also is tied to the Gyro. Um, well, for the audience's warning is we have lots of information on the website.

We have a YouTube channel where we just showed some actual drive data where I actually went in the car and it was just on impromptu. And the, the team actually ended up video it where it was just, we put this in the vehicle, we drove around, I disconnected the impedice. 'cause a lot of people don't believe it until you see it.

And so watch that video, it's a couple minutes, but it gives you a sense of, of what we can do and for the audience is, you know, what, what navigation problems do you have? What can we do for you? And how can we take our technology and apply it to a use case that helps solve your problem.

Love to work. I enjoy, uh, talking to customers. We enjoy working on difficult problems that are technology.

com, there's an info section where you can apply and send an email to us and love to, to engage with more customers. All right, wonderful. Sounds great.

I wanna thank you for coming on our show today and sharing all about this technology. And first of all, thank you for having us, and, uh, look forward to hearing from your audience. Thank you.

All right. And thanks to our audience, stay tuned. There's more.

I am Bonnie Schneider, sustainability contributor to the Techron Group. I'm excited to introduce you to a groundbreaking new initiative from Techron Research, the sustainability pulse meter. The pulse meter offers valuable insights into how environmental responsibility factors into tech purchasing decisions for key players in the industry.

Position your company as a leader in the industry and differentiate from your competitors with the sustainability pulse meter offered exclusively from tech strong research. All right, action PEC infrastructure matters. We don't have a whole lot of time for banter.

We are talking about Microsoft Ignite Coup Con AWS reinvent is coming up. NetApp earnings Super Compute 24. And this is the one year anniversary of VMware by Barcom.

It's, it's, someone told me that it went by fast, and I'm like, oh, I don't know how fast it fell, fell for many people. You know, Everything else is so much more positive. Do we really wanna drag that one out?

No. We'll, we'll save it. We'll, you know what?

We'll, let's talk about that first. I have with me Diane SCL and LY base. Uh, I'm Keith Townsend and you're listening to Infrastructure Matters.

Let's start out with like, on the low note, one year VMware, uh, being acquired by Broadcom. How has it gone? Well, I think it's safe to say that, uh, in the quote I heard, um, just a, uh, a week ago, is that customers are miserable.

Um, but Broadcom has declaring success. Revenue is up there. They think that the been good for them, uh, despite price rate, uh, uh, increases of 200 to 500%, and you can no longer pick and choose the support services.

You gotta buy the whole thing. At and t has dragged them in the court. Um, but Broadcom thinks it's been good overall for the, for them as a business.

So, you know, there's at least that to say for it. Yeah, I think I concur the mi uh, miserably miserable results. From a end user perception perspective, there has been some innovation.

If you are in the wheelhouse of beware Cloud Foundation, then it has been a good, you are the rare customer. This has been a good transaction because Broadcom has narrowed VMware's focus reduced a ton of SKUs. Uh, if you were, uh, aria, uh, uh, cloud-based Aria using which user, which is their observability and configuration management and IT management platform, you'll, you'll be a little bit disappointed if you use VMware cloud on AWS, you'll be a little bit dis disappointed.

But if you're buying into ho's, uh, vision of private cloud, displacing some of your public cloud spend, you, you're probably a little encouraged. It's a interesting situ. I think we've got another six months of this gnashing of teeth to go on as people finalize their strategy around this and the numbers, and they go through the final licensing, et cetera.

But, um, I think hopefully by June we're not talking about this anymore because, you know, between AI, cybersecurity and VMware, that's, I think that's all I talked about for the last year. Yeah, the two topics have been AI and v and, and migrating from VMware, vsp. So Diane, you put this one in the rundown and video day Happy Nvidia Day.

The, well, we'll post Nvidia Day, it's kind of like Nvidia boxing day now, but, uh, Nvidia earnings, well, it was, uh, a beat on the top and bottom line like everybody expected. I mean, the, the, the, the demands that this, uh, that, that being put on the stock are just tremendous. Uh, 'cause the, the street is, uh, you know, expecting Nvidia to blow the doors off every single quarter.

But they did. Uh, so, you know, earnings were up 94% year over year, um, there, you know, to 35 billion. That's a astounding, uh, all on the back of AI chips.

You know, this is a, a company that, you know, until recently was making most of its money off of crypto and gaming. And now ai, you know, they, they're now the AI company and the, they're now the world's largest company of any kind. Um, you know, this is an, uh, an amazing result.

Uh, um, you know, and it's all because of GPUs. Uh, now we're hearing persistent, you know, rumors that Blackwell has problems. First they had the, the chip mask issue.

Uh, now there's a, there rumors are, there's a cooling issue, but there, there, there they can sell every blackwell they make. Um, and then some for a long time to come. Uh, the demand for, uh, you know, the infrastructure around AI is just insatiable.

And Nvidia is the, is the company, you know, uh, you know, with 90% of the market, uh, because of the Cuda stack. And so, uh, you know, their, uh, the stock was down a little bit, uh, you know, after the, you know, they didn't blow the doors off, uh, and, and then some. Um, but now they're, they're, you know, they're, they're doing well again.

And it's, uh, it's, it's a great story to see. And, and it's, it's so good to see that Jensen do do as well as he, he is done, you know, he is doing the company since the very beginning. Um, and, uh, it's one of the really bright stories in the industry.

The one item that I, um, kind of pulled out out of the earnings was the data center revenue. And I know this is ridiculous, but it was only 112% year to year up as opposed to 154% the quarter before, or 426% the, the quarter before that. Okay.

So it's, it's the quarter to quarter change is seven. It was about the same, um, from quarter to quarter. Um, I'm not sure if that really means anything at this point.

Um, I know that there's, you know, we're, I think part of it was that there's this huge purchase that was done last year on the GPUs, and maybe they, they've sat there kind of and not completely been deployed, um, on those numbers. And when they say data center revenues, I'm assuming, you know, that's all those GPUs about whether or not it's going to AWS Me MSP or the enterprise. So they're not slicing it by that.

So that was just one, not item that came out. And then when I was reading some of the, um, financial guys, uh, reviews on that, that seemed to be a piece that they kind of went, what's going on here? Uh, yeah.

Well, you know, interesting is, uh, people forget how much it budgets really matter. You know, we talked about whether we're talking about a Broadcom, you know, it takes a, it takes a year. Uh, there's a yearly cycle.

It makes a decision in one year for what they're gonna in the next year. And it takes a lot of work to change that. And, and, uh, this time of year is always the end of last year's budget where they, and they've probably already spent most of their yearly budget by this time.

So I wonder how much that has to do with it. Yeah. And then, uh, I think I'm going to send a recommendation to Nvidia that they just take off all the doors.

The, the blowing off the doors no longer impresses the street. So, uh, keeping on this earnings trend, NetApp earnings, Yes. Uh, NetApp is continuing to, um, build on their success, um, you know, as a core data protect data storage company that is kind of like, is data storage at interest you right now?

Yes, it is for when we'll talk about supercomputing, but, um, they've, uh, you know, delivered some really strong revenues. Um, you know, they're up about, I think it was 9% of the revenue, but more importantly, there was two pieces, two numbers that came out. Um, and I haven't gone all the way through the, the transcript and read all the numbers, but they're up 19% year to year on.

They're all flash. And part of that is because they have a very large entity, um, set of customers that are, are hybrid, um, and they're just still moving over. And, and George is, George Curry has been talking about this for quite some time, is that we have a very large install base that is still there that hasn't moved over.

Um, and I think at some point in time it was like 60 or 70%. So they're, they're pulling those people out and they're making, doing success, I'm sure, with their c-series, which is the QLC. The second thing that was really good to see is they, um, for their cloud first party, um, storage offering, they were up 43%.

Um, it's still not a huge, massive number. I mean, it's not, you know, they're on their way to building in that sort, in that environment for an annual number. Um, but they have, are finally seeing that uptick that we had expected to see over the years in term of being, when I say cloud first party, it's sold, um, by AWS, it's sold by a Azure, and it's sold by Google, not marketplace, but it's sold core to their, their products.

So as we go into this next stage of ai, expecting to see some of the, that their, uh, file system capability be implemented, uh, along with a core, uh, operating a core block system, core file system for core type of, um, transactional processing. Yeah. NetApp has actually done a really exceptional job, I have to say, of transitioning from a storage only company to a data company.

And pervasiveness of their solution throughout the three cloud providers is honestly leading the market in how you transition from a on-premises company to a cloud-based company with, uh, without sacrificing a lot of that on-prem revenue. Speaking of, on-prem, Diane and I spent a good eight hours, or collectively between dinner and, uh, our focus group about 10 hours with nine CIOs and CTOs. Mm-Hmm.

Uh, in Seattle. And Diane, let's reflect back on some of the higher level trends that you saw amongst that group. We had folks from biopharm to manufacturing, farming, high tech, enterprise financial services.

Yeah. Uh, financial services. Yeah.

A good group of folks. Yeah, it was, it was, uh, really excellent to kind of take the pulse of what's going on, uh, these days in it. And we had the opportunity in this focus group, uh, to kinda ask them, what are the biggest challenges they're facing today?

What's really top of mind? Uh, and, uh, you know, they, uh, there was, there was a lot of things. It was, uh, it was very interesting, but, uh, topping them all was making AI safe.

Uh, they were, uh, universal saying that that was, that was the most important thing, uh, that they're focused on in terms of, uh, the challenges that they have. Uh, but the next one is really, uh, um, really interesting too, is, uh, a value as a service. They really want an easy way to be able to tap into delivering value to their customers, uh, in a turnkey fashion.

Uh, you know, it is just as hard as it's ever been these days. It's, it's the, the level of complexity and sophistication as a, at a high watermark, uh, is only gonna get worse. Uh, and so they're really looking for ways that they, they can say, how, how do I get by to my customers, uh, very quickly, uh, very straightforward.

That's really important for me. And then I was really encouraged to hear it. Now, I think we do, did have really enlightened IT folks, um, uh, in general in, in the, in the session.

And that was by design, uh, but tracking success of it after rollout, um, most of the time it declares, uh, you know, once they, they, they've delivered a system to the, the internal, uh, end customer, uh, that, you know, they, they declare victory. And, uh, you know, and that's usually, that's usually step one. And the success of an IT system is rolling it out.

You then you is a long customer adoption, customer success, uh, patterns is what we've, what we've seen on the, the, the external side with SaaS. And now that's finally moving into it. And so they really want to track success of it after rollout, making it a success really.

And then rounding out the, you know, the, the strongest signals was the changing workforce. We see a second generation of Gen Z arriving. Um, gen Z's been the dominant, uh, new arrival in the workforce.

And, and they're, uh, the first generation that doesn't look at, uh, their paycheck as the number one thing they wanna do good in the world. Uh, but they're, they're, they very much see that, just trying to attract that, that talent, making sure that, that they feel like they're, they're getting their other needs, not just, um, um, a, a good paycheck, a good compensation as being the number one, um, benefit that they've received. It has to make the IT department a very appealing place to work if they expect this new generation.

And these guys are definitely feeling that. So that, that kind of was some of the top, uh, the, the most, the, the strongest signals we saw. So as you were talking about it as a service or as a value, a value service being delivered.

And, um, is there then a, a trend at all that you picked up from that group about buying systems that are fully integrated to more rapidly deliver? I mean, we've talked about, we see a lot of this coming out for the AI systems because it's so difficult to deploy quickly and they need to move fast. And much of what we're seeing the client, the, uh, vendors do is how did they integrate with all the partners all the way up the stack?

Is that something they're looking, you see, did they talk about looking at those type of offerings in order to bring more value to the market. We, we talked about a little bit, uh, one of the, the, the signals we, we got, um, was this real concern about IT fragmentation. So you could, you could flip that and say that.

You can argue that that's the real challenge is that, that they do have all these siloed systems. They're being required increasingly to deliver any given solution. You gotta pull data from all over the place, not just your own, uh, uh, data sources.

But now you have your, your data's increasingly being, being spread across all these cloud systems, all these cloud platforms and SaaS, uh, offerings. You have to, that fragmentation is a real problem. And, and keeping it all secure while you're accessing all this federated data that you have across all these applications.

It did have half of them reported that that was a, a significant challenge. Yeah. And Diane, I, I thought what was really interesting, because you did have a good mix of really enlightened IT leaders, and we found some of the data points that they shared very contrary to some of the data points that you've, uh, collected over your larger set of CIOs.

And this was a, uh, I think, uh, outlier that these folks who are thinking much beyond, well beyond the average CIO. Yeah, no, I, I absolutely agree with that. Uh, and, and that's what we, we tend to do, you know, when we do broader, uh, CIO surveys, it, you know, teases up, uh, you know, automation, uh, cybersecurity and ransomware, uh, as being the top concerns.

And, and these folks are really more concerned about having positive impact with their internal customers, um, trying to create a, you know, appealing workforce so they can continue to attract the best talent. Uh, those are talents also, you know, appears in our broader survey. But, but, uh, these folks put it, you know, uh, really head and shoulders above other things, Really.

And I love what you said about, you know, delivering AI in a secure fashion. Yeah. Um, because that's why I think one of the things that I've been talking about is how that, you know, as we get into the enterprise, as they start delivering these applications, it's gonna slow down as they diligently look at, have we trained this right?

Do we have this right? Are we assured that we're not gonna have some really weird thing happen out there, that it's gonna hurt the company, hurt somebody, hurt the brand? You know, And this is a classic IT pattern that they often, uh, hurt someone in the short term is to go fast.

Uh, sometimes means you have to start slow. Yeah. And a lot of people forget that.

Yep. All right. So let's move from having real discussions with real customers to having real discussions with real customers and vendors at several shows that we've been to over the past three weeks.

KubeCon Super Compute and Microsoft Ignite three really major shows, uh, with growing enterprise interests. I think when it comes to KubeCon and Super Compute. But Microsoft Ignite really in the wheelhouse of most enterprises and where most enterprises are not just doing AI work, but also work, uh, on around keeping the lights on.

Let's start with, uh, Kimberly has been a, uh, it is been a blur of the past two weeks. Remind me, were you at Kku Con? No, I was in Scottsdale.

I was, I was, I was chumming it with my friends at Veeam and, and enjoying the, the wonderful place down there as they were brought in all their executives. You went to CubeCon? Yes, I went to CubeCon.

I was also, I I, I spent a couple of days with Veeam, which by the way, Veeam Nice. Work on the sneakers that that was, that was a surprise. If you, if you're not sure what I mean, check out the socials.

Uh, KKU Con was, obviously there's going to be conversation around ai, but there was plenty of conversation around VMware alternatives. But I wanna call out, uh, a growing segment of this, which is observability. Kku Con has always been a really great conference for observability in general.

And when you think observability monitoring, et cetera, you're going to stink. Think of Splunk, and actually you say it stink. I mean, a lot of companies will say their investment in Splunk is, uh, uh, uh, a, a never ending drain of hardware.

But Crile was a big point of conversation. We don't have it in the notes, but Crile, uh, if you're not familiar with it, is the open source alternative to Splunk. And they, I just saw they got a few hundred million dollars in funding just recently.

So, uh, there was a lot of mature conversations around not just how you, we've gone be gone beyond how to deploy Kubernetes and talking more how do you, uh, take Kubernetes cloud native infrastructure and make it invisible infrastructure? How do you make it something that's just there and you count on and it becomes that API to the data center. And as a result, the API to ai, there was obviously a lot of conversation around AI and how do you manage AI in a DevOps type of methodology.

And for what it's worth, we're gonna talk about Supercomputing in a bit. There was no observability and no security guys there That the, the, you know what, let's get into super compute. 'cause Kimberly, this is my, I didn't get as much time on the show floor, but there had to have been at least 400, uh, vendors on the show floor of Super Compute.

It was a massive show. Close to 20,000 people now. Yeah.

Yeah. So Super Compute has been the domain of the professors, the PhDs, and the graduate students along with all the research labs that come out of the major universities worldwide, and the labs, the research labs that we have, like Lawrence Livermore, JPL, Fermi Lab, et cetera. Um, in the past maybe 5,000 people, you saw a lot of posters being presented, which are papers, you know, that are being presented by the graduate students.

Um, that was the kind of vibe that you had there. Very, very, very much so technical. I'd go to a session and my glaze completely over because I'm listening to these HPC, high performance computing people talk about whatever, and it's, you know, I'm, I'm not that smart, Amy.

Nobody hired me to Bridge did National Labs. So this has fundamentally completely changed. Um, and this is ai.

This is called going into the enterprise and the where the market is going with generative ai. And we have a mix the labs. It's not that we're going beyond the labs.

The labs are changing as well. You, if you look at, listen to some of the people that presented, they are going from an HPC, pure HPC environment, which is a lot of bash processing, et cetera, to an environment that they're doing more data simulation and gen ai, and it's completely different. Um, IO configuration data infrastructure, um, CPU systems, GPUs, et cetera.

And they're having to build for the next generation of research as well, because there are researchers coming in and saying, we're gonna be using this. We're gonna be going into the next direction. So when you start to, and when you look at this entire, that the show floor, um, number one, the biggest thing I felt like was there was all about liquid cooling, because we're burning up the, all the power.

I mean, liquid cooling is front and center, and I mean, there was a zillion guys out there with something to do. Everything from the piping to the oil or the glycol and the water cooling and the design of it and everything else, how they would do it, plus the rack systems that you had. And then of course, all the, you know, processors from all the different vendors, the data file systems, uh, you name it, it was there.

And, and, and I called it the world class petting zoo for technology, because you really got to see a whole lot of gear, including some quantum computers that were on the floor. So, really cool. Yeah.

If it had to do with cooling or power, it was at super compute. Uh, the immersion, uh, water cooling Lenovo talked about how they're, uh, using and redistributing, uh, 45 c water to cool and, uh, heat and recycling that water. And this is specifically water cooling.

Somebody asked me, uh, you know, they said, you know, quote unquote liquid instead of, do you mean liquid Keith? And not water? No water in Submersive, I saw they had an intel board.

So, uh, sub first in, uh, liquid cooling, the numbers are unmistakable. The, we're starting to go from the typical 15 kilowatt rack in the data center to 60 kilowatt racks being common to 120 kilowatt racks. Now I'm becoming the, uh, the little bit of future proofing and the most advanced research, uh, happening is happening at that 500 kilowatt rack, uh, level.

And you imagine 500 kilowatts of power going into Iraq. Now, remember, most traditional data center racks two use full with, uh, two use full with dual core servers all the way up to the top of a 42 U rack. It's about 15 kilowatts.

You're looking at, you know, uh, just one, uh, one AI server taking up all that power at a minimum. So it's, it's, it's an amazing, I double check those halan, uh, fire control systems that, you know, yeah, you, you're, you're, you're definitely going to put them to test. And then, uh, we also saw the drive storage rate rates, uh, solid dime debuting, uh, last week.

There are 122 terabyte SSDI got to hold it. They would not let me keep it, no matter how much I asked, they just would not, you said it Was $15,000 for that thing. Yeah, it was 15, $20,000.

2 petabytes of storage and two use of, uh, of, of, of data center Rackspace. This is an amazing pace of innovation that's been driven by the thirst of, for AI storage and processing. Huge amount of data there, data storage companies there.

Um, everything from just your typical file system companies to parallel file systems. I had a chance to talk to Sam Wener from IBM, and we were talking about GPF effort, also known as scale now. Um, and how it's just the, the numbers on there are doing terrific.

Um, and then URA re, which is Panasas relaunched with their new name, um, you had pure storage there with their blade, you know, their blade. And, you know, while it's not a parallel file system, they're definitely rolling in. And then Hammer space, you had their announcement with tier zero capability, which is what what they're doing is enabling the storage that's in the servers, um, and enabling that to be the storage and, and do be the feeding of the GPUs.

Um, and then right out to the network stores that's cashed to it, attached to those environments. So the numbers that came out from them and perf storage, um, benchmark were very, very substantial. Yeah.

The, the, your GPUs can be as fast as you want 'em to be, but if you can't get a IO to them, it really doesn't matter. So, Diane, I heard you went to a small conference here in Chicago. It's, it is, I, every time there's a major tech conference in Chicago, I don't get to go to it, but Microsoft Ignite, or did you go, or were you remote?

Uh, no, I was there. Um, I, I didn't wanna miss this one because this was really the, the, the big new big announcements that, um, Microsoft is gonna make around the hot topic in ai, which is agents, uh, agents are, are unlike LLMs, which produce content for you agents take action for you using generative ai. Uh, they can actually talk to a system using, uh, APIs, uh, to carry out tasks.

And bole, Microsoft had a lot of news, uh, uh, and, and the, it's most basic, they, uh, announced co-pilot actions, and that allows anyone to automate, uh, pretty much any task they have with simple fill in the blank prompts. Um, they, uh, announced agents for SharePoint, which of course they did. Uh, I'm not sure that people were lining up for that to begin with, but, uh, they, they had to do that because that's still one of their biggest platforms.

Uh, but they have, uh, they announced a new employee, self-service agent, uh, a language interpreter that, that operates live, uh, during calls. And those were nice. Um, but what was really interesting was the infrastructure announcements around agents that IT departments will really care about, uh, most notably the, uh, the copilot control system.

And it's a, it's a control plane designed for it to consistently, um, and declaratively, uh, drive, um, business value out of copilot, uh, agents. And it dictates how they're, how they're situated in front of users, what they can and cannot do. So it gives you all the knobs to control agents across the enterprise.

Uh, but I think most notably was their data protection, uh, news around agents. Uh, they will provide the guarantee, intelligent grounding on enterprise data, uh, while respecting any underlying permissions and controls that are, that are in place so that people can't make requests of agents to do things with data under the covers that that user maybe doesn't have access to. Uh, and then it ensures that what the agent does is accurate, done accurately.

So that that's the grounding piece. Uh, and so that you'll have agents generating new data under the covers and then putting it back into your IT systems, and it's not right. Uh, this, these are the, the, the new risks that you have by unleashing AI to directly interface with your IT systems, uh, you, they're gonna consume data and generate new data, uh, and you have to make sure that, that it's not gonna corrupt your systems and, and, you know, put hallucinations in your database.

That's, that's a concern, right? So they announced data protection, uh, around that. So I, I really liked that as well as a slew of controls around, uh, how copay co-pilots and what agents, uh, can and cannot do in your organization.

Yeah. So this is penetrating the third wall a little bit. We talked to our CIO and CTO cohort about this very topic, not just, uh, Microsoft copilot, but specifically about agents and safe ai.

This is, this is one of those subtopics within safe ai. And one of the considerations that these forward thinking CIOs or CTOs were considering is where to put that business logic. Do we trust it with a Microsoft a Service Now or ASAP, or do we build it ourselves?

That was a really interesting conversation debate. So speed to value versus this, you know, desire to not be locked into a proprietary business process and for a third party co, uh, company to own such a critical part of your capabilities. Wow, I wish I'd been there.

I'm like going, okay, I love super computing, but Wow. Yeah. These are the topics on the front line, and, and it has to deliver on all this because there, there is voracious demand for, for ai, even though a knowledge, it seems to have plateaued with knowledge workers.

Um, but we're, we're gonna see the, the business wants to put AI into everything to reduce cost, increase productivity, uh, future, you know, uh, ready organizations. And, and so it's a, yeah, really exciting times. And we look at the whole thing, the whole stack from Nvidia at the bottom and Microsoft the top.

It's, uh, we, we live in exciting times, folks, it is exciting times. We'll continue to digest all of the information that we're finding. com.

You can follow all of our musings there. As well as, uh, some housekeeping. We will not record an episode the week of Thanksgiving, but don't worry, we'll make up for it because AWS reinvent is that same weekend.

And we will come back with plenty of discussion around AI infrastructure and why all of this matters for my co-host, Kali Bass Bates, and Diane Hinchcliffe. Have a wonderful holiday break and we'll talk to you soon. Welcome to the Tech Field Day podcast, where we bring together a group of IT technical experts to discuss a single idea about key concepts in the enterprise IT industry.

This program features members of the Tech Field Day event series experts in their field on a variety of enterprise IT topics. I'd like to take a moment to introduce the guests before we jump into today's episode, starting with Jordan. Hi everyone.

I'm Jordan Martin. I'm a principal architect at Worldwide Technology focusing all things enterprise networking. Hi everybody.

This is Michelin Murphy. Uh, I am a, uh, CSC, uh, consulting systems engineer at Worldwide Technology, also focusing on networking. I call Jordan when I have a problem, though.

My name's Rob Boyd. I'm a professional talker, and since we're sticking to WWT, I host a WWT research series among other series of networking content. Yeah.

Glad to be here. And I also call Jordan. Yeah.

Alright, Jordan, what's the answer? First, What Is the question? It depends.

There you go. It depends. com.

In addition to Techstrong tv, which is another part of the Future Room group. This episode was recorded at networking Field day 35. Let's jump into the premise for this episode.

You may have heard the term network as a service recently. It's becoming a very interesting discussion in the networking space, all about how networks can be operated, more like utilities, more like subscription services, but a lot of people aren't convinced yet. And in fact, a couple of those people are sitting here in this podcast right now because the premise that they've come up with is that network as a service is more of a financial model.

Alright, Jordan, you started this. So you cannot, you cannot, you cannot set that stage saying that that's what I believe I'm saying. I'm not saying it's what you believe, but I'm saying that you kind of kick started this idea.

So can you tell me why you have this idea that network as a service is more of a financial model than an operational model? Because in some situations it is Such as, Um, well, let's start here. Let's start with this, this idea of, of network as a service.

I think what people expect is when you talk network as a service, you're thinking like, how we consume cloud and compute. Mm-Hmm. I can go pay for the amount of networking that I need, um, be somewhat of a frictionless experience and, and be able to just consume networking.

And I think that's one end of a spectrum as you talk about it. The other end is we see some major players in the market who want to provide network as a service, but it really is just leasing with a new name. The idea is I can get equipment, uh, I can maybe pay per user on equipment, uh, but the reality is I'm still deploying, I'm still responsible for maintenance and operations.

I'm still responsible for all of the things except for now I just pay for it a little bit Differently. So you're saying that if for network, as a service, when that comes up, let's say you're working with somebody and you're providing advice, maybe one of your first questions is, well, let's break that down. Yeah.

What do you mean? What Do you mean? Yeah, because you're saying it could be, it could set you up in a bad direction.

If you're consulting on a project and you're on one definition and they're on another, that That's exactly right. That's, I think that's exactly right. And you wanna be able to not just say, what do you mean?

But you also wanna know what's the customer trying to solve for? Mm-Hmm. I mean, if it's, it's even much more basic because sometimes you'll have conversations with customers and they're like, I need a, I need a an X, and, and what they're really solving for, maybe they've decided that X is the solution for the problem, but they don't know enough to know whether or not X is really the solution to the problem.

Right? So you really, I mean, there's, it's like an onion. You gotta peel it back and you gotta figure out, I think what, what is the, what's the problem that we need to solve for?

I mean, and I think in a lot of cases, I think Jordan is correct that, that what we think of as, or what is being branded or marketed as network as a service is a, it's a sub sub some kind of subscription model. And it's, it's a way to, you know, but because It still requires physical hardware and connectivity, I mean, the first time the term came up, and I was just thinking through the term just in and of itself, and it feels like it's been around a long time, but it felt a little bit like glomming on to cloud services that were becoming popular and saying, well, how could we be consumed in a more, um, flexible basis? Mm-Hmm.

Right. But then I was like, but yet it's one thing. I can host my data somewhere else, but that connectivity is still, like you mentioned the services.

So does network as a service imply that you're gonna have people there to run it, or that you just want like a leasing model? I just want the equipment on something outta my cap, my opex versus my CapEx. And the answer is, it could be either.

Yeah. Right? Like, and, and, and, and neither one of those is like a wrong answer, right?

Like, to, to Misha's point, like there are organizations and people that are really just looking for a, a, a more favorable financial model, and that's okay. And there are companies who are providing that. Some of the traditional networking companies are providing that as an ability way to consume stuff.

That used to be this huge CapEx expense upfront where I have to pay it all up front. I have to size it with a five year lifespan in mind, and I'm not paying it based off the number of users. This gives me a little bit more flexible model about how to pay for the same type of equipment.

But it doesn't change the operational model at all. It's strictly a financial model, but we see other entrants in the market. This is where it's new.

This Is where I think it gets interesting, right. Because I think this is where Right. Help make it easier on.

Sure. So, and, and we're seeing it in a couple of enterprise spaces. So we see it in, in wan Yeah.

Specifically like around SD wan. So that idea, we've, we've, we've, you know, kind of flirted with the idea of what's the right way to build a backbone and where do I put my hubs and how do I build an sd-wan? And the reality is, is the large majority of our traffic now is going to data centers or clouds.

We don't have a lot of the peer-to-peer traffic like we used to have before. We, we used to build like these big IP phone networks where I'd have to have lots of traffic to go from branch to branch. It's kind of going away as people consume that more in WebEx or teams or other places in more cloud delivered models, right?

And so now this idea is like, okay, now it's more important about how do I get to the cloud? How do I get to peer organizations, B2B type connectivity? And then maybe a little bit of getting branch to branch, but it's really branch to data center, branch to cloud.

And, and in that, we've had different models of doing that. We've built our own connectivity. We've used things like, uh, fabrics, Equinix, and those types of places where we could do that.

And the next iteration of that is, Hey, um, as a provider, I can build that whole backend for you do the segmentation that SD-WAN does, the reliability, all those additional features that SD-WAN provides, and you only need to have the device that sits at your edge. And now I can consume a WAN that I don't really have to build or configure. I just have to get to it.

And I get to it by sending the traffic to a hardware device that's still on edge. It's the only thing I'm responsible for. That's the WAN side.

We also see it in the landslide. I think it's a little bit harder of a, of an equation, right? Yeah.

Like if I'm gonna do, you know, wired and wireless access, it's still gonna be equipment that sits OnPrem. Now you say, is it a shared responsibility model of who manages that? Who deploys it?

Yeah. I think that's, I think it's a less obvious as a service than the WAN conversation, but I, it's still, I mean, we, there's multiple companies who are trying to solve that, that Access. But it, but it's also perhaps the way to go if you're both a low resourced company, perhaps you're smaller, uh, you don't want to invest in the type of talent we have in the room for a tech field day.

Um, and, and, and you're also not sure am I even gonna be in this space long? Or how am I gonna need to scale? Or am I gonna scale here or there?

So maybe I don't want a heavy investment, but yet I need some advanced capabilities that are gonna have to be enabled by. Is that, I mean, do you consider Meraki like a offering software? It's, It's funny that you bring that up because I think that Meraki was the closest to this.

Yeah. Right? Because, because you have the financial side, even, even on the other end of the spectrum, when you talk about the stuff that actually, what I consider real network as a service, like where you're actually getting something different.

Yeah. Um, you still have the financial model where I'm, I'm consuming it differently, but the operational model's really different. It's gonna be cloud managed and centrally managed in opera, which is Meraki's model.

Yeah. It's like Meraki, if I don't have to own and deploy all the endpoints, Well, 'cause I feel like your network's not gonna be a differentiator to, like, depending on what industry I'm in, more than likely I need it to work. I need it to work well, and I want to be on a base level with my peers, but at the same time, I, my ability to have the top of line it department doing something unique isn't maybe gonna make, you know, isn't gonna move the, the pile for me.

You kind of hit on a religious battle, right? Yeah. Like, like is a network a differentiator?

Uh, and, and there are people that I consider friends who are very, very smart who say, have You lost some friends? Yeah. Yeah.

Yeah. That, that would say absolutely. Like every company, like their network is supposed to be a differentiator.

I don't see the world through that lens. Yeah. I, I think about the large retail organizations of the world, you know, thousands and thousands of branches, their differentiator is the data, not how the data gets around.

Yeah. I need that. I need that to be super consistent and cookie cutter at all those branches.

So I can manage it easier. I can see that being very popular. Yeah.

Right? And so, and so, like in these, you know, thousands of branches all the same. Even for that land access model, being able to be cloud delivered, having this real consistent way to deploy it, very, very prescriptive way to way to put it out there, I think is a very attractive option.

But that goes back to my original point, which was talking about what problem you're trying to solve that solves, right? Yeah. You know, for, for the small company that doesn't maybe have the, you know, deep well of knowledge, you know, They're solving for a talent Shortage.

Yeah. They're, they're solving for an entirely different problem than say the, you know, the, the retail giants of the world who need to have consistent models for every time, every two months when they roll out a new store. That's an entirely different problem.

Yep. But it goes back to like those basic questions that you have to ask, you know, what, what, what problem am I trying to solve? And as soon as you fi, when you figure that out, you can now root around in your, in your, your tool chest and figure out, well, what root tools Yeah.

That I have that, you know, or solutions that are available to me, um, can help me solve this problem. Or, or do I have to go and innovate something? Plus I want it to be constantly updated.

I want, I want the latest and greatest when they're, although I don't think the innovation changes that much. Most of our customers we're just trying to get them up to something modern. But, um, No comment.

Yeah. But, But that brings nothing To say, but brings a good point because historically, this idea of purchasing equipment and having someone else operate, it was entirely the domain of managed service providers, right? We would hire somebody to come in and rack and stacks equipment and run it and make sure that it's patched and it's, it's not broken.

Mm-Hmm. But now that model seems to be shifting away. Yes, there are always gonna be managed service providers, but there are also a large number of people out there that are saying, well, why am I paying somebody else to do that when I can do it instead?

And we've seen a large number of, of entrance into the market, whether it's Nile or Meter or Ramen, who are trying to offer that service, whether it's wireless connectivity or, you know, end user connectivity or WAN connectivity. And they're saying, we can do this better, faster, cheaper than the other people. And you don't have to management or incur the costs.

So is this more of a matter of the entrance into the market, trying to capture that existing relationship that maybe they had with a managed service provider and redirect that funding into what they want to do? Maybe, uh, I think that managed service providers a good, at least analog or early analog to what this all is. Because that's, at the end of the day, what we're talking about is mm-Hmm.

Another organization managing the connectivity or the access for, for your network. Um, I, I think where it shifted is, I feel like managed service provider before was just like, Hey, we need to have this thing. We're gonna go pay for it.

And, and we then we don't need to, we don't need to worry about ourselves. It's something we can do. And I think that same impetus is there, but the technology has gotten more difficult.

And so as technology continues to become more complex, this is what we saw in cloud. Like when you think about what, like a cloud connectivity and how all those services are patched together, that's an incredibly complex environment. And the reason why it's complex is 'cause you add all of these features and capabilities where you can just go check a box and make something happen.

Where before that would've been weeks worth of work. We want to have that same capability and networking it requires additional complexity. So I think that what, what's happening is the scope of the organization that's willing to accept that type of model is growing.

It used to be that it was just a very, a smaller organization that just couldn't staff technical, technical people. Now, I think that you see larger organizations who say, our differentiator isn't the way that we, you know, deploy an access portal. It isn't the way that we choose to do segmentation on our wan.

Our differentiator is the way we run our business. And that is the data we collect, how we service the customers, how we do whatever. Like that's really the differentiator.

So if I can pay somebody just like in the cloud, I don't have to become, and I don't have to staff experts in BGP and in overlay networking and all of these other things that as, as things just continue to progress and become more difficult, the idea is I can just essentially outsource it. I can, I can pay someone else to be those experts. I always wonder about, because when the, who's making those decisions?

'cause if it's a, if it's a company that didn't even understand why they might need one network type versus another perhaps or something, then it gets into, well, if they don't, then they're just saying, well, I just need connectivity. Each individual just needs good connectivity for us to be able to do our thing. I don't know, I, I feel like it's one of those like cloud and maybe it's a follow on to you see cloud grow and then there's a little bit of a correction.

Yep. Uh, as people go, wow, that's expensive, right? Mm-Hmm.

Um, same type of thing. It feels like could happen this network as a service where you go in because it's easy, you need to get started, but then some reality sets in. But the reality, perhaps the setting in is your maturity has improved so that you're better able to maybe make decisions with or without a network as a service provider to be able to say, we do need to do this on our own, or we don't, we can continue to invest in this pay by the drink.

But at the same time, to that point, one of the things that we see a lot in the enterprise space is this idea. It's not necessarily the sunk cost fallacy, but it's that opportunity cost. If I'm paying on a monthly basis for cloud, what I'm expecting is, is that whatever I want to be available is available.

Yeah. If I want to turn on 10 extra servers, I know there's a cost to it, but those 10 servers are available for me to purchase. Whereas if I've purchased a million dollars worth of gear from my headquarters, I am stuck at that functional level as long as that gear is in my headquarters.

So a good example of this would be wifi access points. Mm-Hmm. If you refresh your access points five years ago, you are two technology revisions behind because you're operating off of uh, uh, wifi 5, 8 0 2 point 11 AC wave two for those of you who are nerds like me.

So we've already gone to AX wifi six and six gigahertz wifi six E and we're on the cusp of seven. And so there are a lot of companies out there that see the bigger numbers and say, we're missing out. Even though realistically speaking, the network's probably fast enough.

There aren't a whole lot of clients that can do seven right now. And I guarantee you nobody has anyone in their desktop or their iPhone. But it's that idea that they're missing out on something they could enable.

You know, this goes back to the days when I was learning how to compile Linux kernels and I was just checking every box because I don't know if I'm ever gonna use this, but I want that in the kernel in case I need it. And I was unfortunately slowing everything down, right? Because I didn't realize that you need to optimize for operational efficiency, which is what you're talking about.

Getting rid of operational inefficiency makes my business stronger. And if one of my operational inefficiencies is the way that my network has operated, we'll get rid of the people who operate it that way. And that becomes a pendulum, right?

Because for a while we push on one end of it and then we come back. Um, that's all of tech. Yeah.

Yeah. That's client Server central versus remote. You know, I mean, We've been talking about this a lot this week too.

'cause we're talking about scheduled networks, which is just going back to circuit switch networks versus packet switch networks. I mean, like it's, we we love the pendulum. That's a different name.

Yeah. Right. But I, I think to your point there, I, I think the challenge that is trying to be addressed in this, it's like the same challenge that we see why like Sassy's taking over and that is like, how do you buy a firewall that can do SSL decryption on a hundred percent of traffic and how do I buy that with a five year horizon so that I don't undersize it today?

'cause this thing has to last me until whatever. And you know, I have no idea how many acquisitions or divestitures or things are gonna happen to my company, but I still have to buy a piece of equipment today that's gonna meet my needs for five years. Or I can pay a premium small premium on that monthly service and scale up and down as I need.

Is it really more expensive at the end of the day than putting all of that, uh, CapEx model money out at the beginning to try to make that happen? I think people will see that in the network as well. 'cause we see that same thing with speeds and feeds and capabilities you're talking about, about wireless market.

Yeah. These things. Yep.

You can, you can sign up with Apple and get a new one of these every year. So you're not missing out now you're paying more per month to get that function. But there are people who are happy to do that.

But you, you don't own the phone at that point. You're basically leasing it and giving it back at the end of every year. Whereas someone might want buy their phone outright and hold onto it as long as possible.

And there's always gonna be both models. So can network as a service appeal to the people who want to own the network at the end of the day? Is there a model that works for them to be able to have that latest and greatest technology?

But if I decide to stop paying the bill this month or this year, or I go with a different provider, you're not gonna come in to rip all my equipment out. Yeah. Well that was the one thing I, it that disturbed me about some of Meraki was I was on Meraki and my home network because I worked for them, you know?

And Mm-Hmm. They gave me keys. Well, as soon as I don't have keys, stuff's useless.

Yeah. And it's some beautiful hardware, brick. And it was a brick.

Yeah. And, and then that made me uncomfortable. Of course when that reality sets in, it was fine when it was, I worked within my free cost basis.

But I always, the companies you were seeing start up in this space, do they, I, I don't know how much you know, but is there, are we seeing a niche that they're exploiting? Is there, is it, is it mainly the psychology, as you said, of Oh, I've gotta have something that's that's, you know, the best that's meeting my needs on a regular basis? Again, I don't think we can talk about the market as one market because, because we see network as a service kind of going into different spaces.

I think that the, the land space is a question mark. Yeah. Like that these companies that are there, they're developing good products.

I don't know how they're doing when it comes to, to actually like winning deals and getting into places where there's interest. Um, companies are interested in talking about them, but it's still very, very early. I think the wan space makes a lot more sense.

Not for everybody, but the wan space makes a lot more sense 'cause we're already doing that. The level people who are leveraging, like I said, like Equinix fabric, like I'm gonna go there and I'm gonna use their fabric as a backbone. I'm already kind of doing network as a service, but I've only like dipped a toe.

This just says, let's just go the rest of the way and say, I don't have to build the segmentation to, to them. Well this comment's probably a little off-prem, but the notion of it, it makes me wonder about what are ISPs doing these days to take advantage of this? 'cause it feels like, it feels like in a loose sense, 'cause I'm not in that market, but that they're fumbling a little bit with regards to how things are shifting to an Equinix and others and the blinds are getting blurred.

Well, I know, Didn't we have, We can't count on long distance lines anymore. We didn't. We have graph on.

Yeah. Last year they, they've done field Daniel And, and, and they rolled out Tech Field day two years ago. And you know, when they, they, they came and they talked us to us the, the first year of the rollout.

You know, one of, I think one of us asked, you know, where do you see your, your competition? And, and they thought they were gonna have to fight tooth and nail with the ISPs. And it turned out that the ISPs became, you know, their customers, their biggest customers.

Yeah. Because as you know, ISPs grow and they need capacity. It was easier for them to be able to say, well, we're going to dial into Grapht and use them to help us be, be, you know, more flexible in our capacity.

And, uh, so smart, you know, that was Yeah. The ISP point's really astute. And I think we can see how it's going to evolve based on what happened around sd-wan.

'cause SD-WAN was gonna eat the ISPs lunch, right? Like they were gonna come in, we're gonna get rid of MPLS, everything's gonna be internet based circuit. It's good to be like, you know, one 20 or one fit the cost of what I used to pay for circuits.

And the reality is that ISPs came in just embraced sd-wan and said, you know what? We'll give you sd-wan suddenly the cost difference, right? We'll, we'll give it to you and it will work great and we can leverage both MPLS and whatever.

And like they were able to adjust into that and the ISPs did not lose because of sd-wan. They're doing just fine. But, but They were doing, they were being astute about It.

Right. And I think that network of service will be, will be something similar. And if we, if we really are being genuinely honest when we talk about the WAN as, as that, when we talk about what like graph's doing, it's not wildly different than what the old NPLS networks used to be.

No. Right. Like I go to my ISP Yeah.

I tell 'em I want a WAN and I have one edge device that connects to them and they do everything in between now. Yep. And they do everything in between.

That is a way oversimplification, right? So if you look at what, like what the likes of grapht are doing in providing connectivity and some of the things that they're doing, they are way more flexible than what the traditional NPLS networks were. And they give you a lot more independence and, and, and tunability.

But it's not a completely separate analog. They're, they're live in similar spaces. But To that point, the reason why an MPLS network operates the way that it does is because of hardware limitations.

Because when we implemented them, that was the state of the art hardware at the time. And one of the things that we've learned over the years about it, ISPs, is every day they can operate that old gear is a day they don't have to buy new gear, new gear profitable. Whereas with a network as a service model, they're paying per month no matter what.

So if they can refresh that gear or offer new services that increase their revenue, then as long as what they're paying is less than what they're making, then it's a win for them because they don't have to go out and write a new check every four years for that giant refrigerator sized router that makes them all squeak. And I think that that comes back to the whole discussion that you mentioned about the financial model thing. Maybe network as a service is just a way of amortizing those big connections that you have to do every three or four or five years.

But doing it in such a way as to keep people from squeaking. And so now I can more closely match my outlay of revenue through opex to what I'm getting in profit and it makes the bean counters happy. So maybe, maybe network as a service is really just a way to make the accountants happier.

Aren't we always just trying to work that direction? Yeah. I think to some degree, yeah.

I, again, like I don't, I don't think that any conversation around network as a service can be had without talking about the operational model. And so while I disagree with the premise in, in this saying that it is only an operational model, although you can certainly approach it that way, operational model is gonna be, or I'm sorry, cost model is gonna be part of the whole thing. Like whether you either into the spectrum that you're on, the reason why you go this direction is because you wanna normalize that cost, make it predictable, and, and then you also don't want to get yourself locked in on hardware that may not meet your needs going forward and you end up with a surprise upgrade or something that you weren't expecting.

Well, I think that the premise for this episode that it's just a financial model is of course not entirely correct because network as a service is actually a business decision. It's something that I do to make my business go faster. Because quite honestly, if we didn't have a business, we wouldn't need a network.

But there's more decisions that go into it rather than just operational model or financial model. We have to take everything as it comes and make sure that we're looking at our network as an asset and not a cost center. And however we have to do that is the best way to transform it.

And if you are on the journey or beginning the journey to decide whether a network is a service is right for you, don't forget to pull in the rest of the people in your business to help understand what makes them happy and more capable and ensure that you are including that in your decision making. Because if you don't, I promise you, you're gonna be the one who's being serviced out of the organization before you know it. That'll just about do it for this episode of the Tech Field Day podcast.

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