Techstrong TV September 19, 2025

Hey everyone. Alan Shimmel here. We're back your Techstrong tv.

I'm happy to have my next guest back on here. I don't know if you'll remember him from the last time he is on, but not to worry. I'll give you his name.

It's Gary Bartlett. Gary Bartlett is public sector CTO for Illumio, the microsegmentation people. And well, and more than that, that's when they first started.

But anyway. Hey, Gary, welcome back. How you been Doing?

Great. Thanks for having me back, Alan. Appreciate it.

I appreciate having you on. We were talking off camera a bit. We didn't get a chance to hook up.

You missed black hat this year. I did. Unfortunately, I had a, uh, uh, conflict that just prevented me from being there this year.

Well, I could give you the load down, but you didn't miss a heck of a lie. It was just another black hat. Um, on other news, RSA is earlier this year, uh, you know, speaking, uh, uh, the speaking session submissions are closed.

I expect that'll be coming out soon, but maybe we'll see you there. Yeah, definitely. We'll be at RSA this year.

Very cool. So, Gary, before we get into Illumio, and we're gonna talk a little salt typhoon and stuff like that, give people a, i, I remember your background, but you know, not everyone out here does give people a little sense of your background. Sure.

Well, as you mentioned, I'm the public sector CTO here at Illumio, uh, about three and a half years now. Uh, prior to joining Illumio, I was the, uh, CIO at the office of the Inspector General from the United States Postal Service. Uh, so I served as a Fed CIO for just shy of 10 years, right.

At 10 years. Um, and before that, I was a cyberspace operations officer in the Air Force. Did that for a short 20 years, A short 20 As opposed to a long 20.

Right. Yeah, I get you. I, uh, you know, I'll tell you, when one of the companies I had helped co-found still secure, we did a lot of work with DOD and some of the agencies, and we did some bit of work with the Air Force.

We were out in Colorado. So it was a lot of bases out that way. A Lot of bases out there.

Yep. And, um, oh, that, look, the Air Force had it going on, right? It was, And they still do, they're still in, in my opinion, leading the DOD as far as zero trust and, and those types of things.

Not that the other services are lagging, uh, but, you know, I'm, I'm a little, I'm a little partial. Right. I can't, I can't claim to be completely impartial.

So yeah. Maybe there's a little bit of a blue tinted lenses there that are, that are affecting my outlook. Well, we, we gotta get out of the, calling it the DOD now.

Right? It's not that the d That's right. W or whatever he did Department of War now, right?

Yeah. Let's not go there. Um, so Gary, let's talk a little bit about Illumio.

You know, know a little tongue in cheek. I said the microsegmentation company, but not so tongue in cheek. It is kind of what Illumio does at its heart, right?

Uh, is, is, you know, kinda Absolutely. So, so, yeah. And we, we really look, uh, view ourselves as the breach containment company, right?

Mm-hmm. So we're all about doing a couple of things. Number one, uh, given our customers, uh, really granular visibility of what's actually going on, on their enterprise, uh, specifically when you're talking about application to application communications, uh, looking at how things are actually, uh, communicating and how they're interconnected, um, from a net, from a network agnostic perspective.

And by that I mean that we look at, we look at enterprises the same way that adversaries look at enterprises. When an adversary comes in and starts trying to map out your enterprise, they're not really interested in the routers and switches part of it. They're interested in what devices can talk to which effort, which, which other devices, right?

It doesn't matter if they're in the same rack and the same data center or on opposite sides of the world. If they can talk to each other, that's what adversaries care about, right? That lateral Lu and be able to compromise one box, and then where can I go from here?

You know, what other devices can I touch? They don't care how those things are communicating. Uh, they care that they are communicating with each other.

And that's what we do, is we provide our customers with visibility that they can actually see that. Um, it helps, uh, like security teams and CISOs, uh, be able to really understand and start to map attack vectors and shut down attack vectors. And that's where the segmentation piece comes in, is really being able to start to isolate things and shut down a lot of unnecessary communications that are in place on most enterprises that really don't need to be there.

And they're nothing but an open avenue, uh, for adversaries. Absolutely. Absolutely.

com. Yes, Sir. Thank you.

Okay. Let me kind of switch gears a little bit here. And we're gonna talk kinda public sector security or public sector cyber, if you will.

Um, you know, salt Typhoon is, uh, you Ms. Black hat. They had all kinds of robots that were projecting to be salt typhoon and, and all of this stuff.

There was a lot of soul typhoon going on there, but clearly this is something that targeted our government though. It, it wasn't just the government. Right.

But, you know, not everyone on our audience is a security expert as we've got DevOps people and Cloud native for those. Maybe let's start here. For those who don't know Soul Typhoon, what, when we say soul typhoon, what are we talking about?

Sure. So Typhoon is a, is a name for a, uh, series of attacks that were attributed back to China, back to the, uh, uh, intelligence sector of, of the Chinese government. Uh, and it was primarily, as you mentioned, right?

Targeted towards, um, governmental, uh, you know, department of Defense, department of War, uh, entities. Um, they went after the telecoms. That's where they were first discovered, is going after the telecons, the, the, all the big telecommunications, uh, uh, companies.

Uh, and people were like, well, what does that have to do with DOD? Well, they were specifically going after, uh, you know, government officials, right? They were, they were literally looking for conversations, relationships, locations, identity information of government officials, right?

And looking to get access to where were they, what were they talking about? Who were they talking to? Um, you know, so it was, it was very, from a, from a national perspective, um, it was quite the, you know, quite the effort, uh, to, to attribute to the Chinese government that they were going after civilian companies that obviously are supporting the government, uh, and, and using them as a target of opportunity to get to, to try to compromise or get information about our government officials.

Um, and then it expanded into, uh, going after National Guard units. Um, state local governments have, have been affected. Uh, so it's been a very widespread campaign, uh, of, of espionage.

I mean, there's no other way to, no, no other word for it, other than it was, it is literally espionage of going in and looking for what information could be stolen. Uh, and then, you know, you, you can talk about what they do with it once they steal it, but that's really, it was about targeting, uh, companies to steal information. So, let me say, I, I have been in the cyber world a long time, and this is though the name Sol Typhoon may be relatively new.

This behavior is not, you know, I remember, uh, it's gotta be almost 20 years ago, maybe 18 years ago, uh, one of the companies I helped found were NAC Network Access Control. Yes, sir. And then, so we had the ability to kind of quarantine any devices coming on the network, test them, make sure they, you know, met a, you know, golden sort of config rule.

Well, we could, we could test them for anything you want to tell you truth, right? And then if they did, put 'em on the network, if not, keep 'em off the network or put 'em on a guest thing or whatever. And I remember we got a call from SEC D'S office one day and said, can you check, can you check to see if the USB ports are enabled on laptops?

I said, yeah, it shouldn't be too hard, but why would you want 'em all disabled? How are you gonna get stuff on and off? They said, well, don't worry about that.

We just wanted make sure they're disabled. You know? And then a couple years later, of course, we all, most of us in the cyber arena know there was this campaign of people just threw USB thumb drives in the parking lot at the Pentagon.

Right. And how many people were silly enough to pick 'em up and plug them in there in their machines, and thereby give access some claim. You know, the, the plans for the stealth fighter that China, China's first gen stealth fighters, Right?

Yeah. Airplanes, um, were still stolen that way. Yeah.

Wasactually, I was actually on the Air Force CIO staff when that happened. Um, and it was quite the, uh, uh, it was quite the event to deal with, uh, and, and to try to figure out, you know, how to deal with it. And, and, and like you said, it was a very, um, widespread attack, uh, that was executed in, in a way that people weren't thinking about, um, necessarily.

Uh, and unfortunately, you know, that continues today. Right. You know, you know, that's where we always talk about the fact that, you know, the adversaries are always gonna be ahead of the defenders, right?

They, they're, they're just, they can be more creative. They can, they can think of ways around defenses. Uh, you know, it's just, it's, it's always gonna be an ongoing cat and mouse game, unfortunately.

Agreed. A agreed it, you know, it's enough to make security pros depressed a little bit. Yeah.

Gary, I, I, I feel like compel to draw a distinction though, you know, there are nation state actors, I think, which is the case in so typhoon, it's really coming out of, most of the Chinese stuff come out of the people's arm, PPLA, right? Right. Um, and then there are not state sponsored, per se, but under the cover of a benevolent state, you know, wink, wink, they let them operate under their umbrella in their country, though they're not officially part of the state.

Usually those are more with financial, uh, packing, right. Financial benefit. Right.

Yeah. You're looking at ransomware that, you know, that's where you get into Yeah. That kind of thing.

Making financial demands. And, you know, and there's lots of conversations about, you know, I've been asked repeatedly by people, you know, well, why would a country, you know, allow that? Well, depends on what kind of kickback you're getting, right?

It depends on, you know, what kind of, you know, the individuals that are involved, right. What kind of financial incentive are, are, are they receiving as, as a benefit of it? And not to mention the fact that, um, just imagine the other intelligence that they're able to gather, you know, while being about, you know, while officially it's not them, uh, you know, but, you know, I'm, I'm sure they've got access to information that's being compromised, and I'm sure that they, you know, they're talking to, you know, potential groups and, and talking about potential targets.

So, you know, it's a very symbiotic relationship that you can understand why they're doing it Well, just the chaos that they sow. Absolutely. Yes.

Alone, You know, it was weakening, weakening your adversary or a friend of me, or whatever you want to call them, right? Um, and then there are some, you know, they estimate that the North Korea may, may, in fact, 25, 30% of their GDP may in fact come from cyber hacking in theft. Right.

And like I say, it is, it is still big money, right? It is, unfortunately, uh, you know, and, and again, it goes back to, I think still today, unfortunately, there's a lot of companies out there, uh, that are still very focused on keeping the bad guys out. They think that if they just throw enough money, buy the right piece of technology, implement the, the, the right piece of governance or guidance or policy, that somehow they're gonna magically keep the bad guy out.

You know, I've been doing this for 35 years. We've been talking about keeping the bad guys out for 35 years, haven't been successful yet, right? Um, and, and, you know, and that's the problem, right?

Is we, we, I don't believe are ever gonna keep the bad guys out. Uh, I think the best that we can do is figure out how do we fight through the attack? You know, how do we, how do we maintain resilience?

How do we ensure that that an attack doesn't turn into a disaster, right? That they don't get to the crown jewel information they're looking for. Sure.

They compromise the web server, or they compromise somebody's laptop, but they couldn't get from there to the actual data that you draft, right? The actual server that contains the, the crown jewels, right? That's, that's really to, you know, in my opinion, you know, that's where the focus ought to be, is how do we, how do we stop these attacks from spreading as opposed to thinking that we're somehow gonna magically stop all these attacks.

I agree, agree with you. Um, you know, I, again, thinking back to when I was actively involved in this market, I, I don't know if people realize the, just the sheer number of attacks, the sheer amount of, of attack. I mean, back then we were, you know, we were helping to protect one of the largest private networks in the world that was run by a couple of service, well, one service branch, right?

And, um, back then, and this is again, 2005, 2006, seven, back then they were seeing four to 600,000 intrusion attempts a day. A day. Yeah, absolutely.

I mean, I was, you know, I was in a similar role back in the early two thousands, uh, you know, defending the networks of the Pacific when I was a, uh, uh, network, operat security center, uh, uh, in charge of the Pacific Nosc. And we were receiving hundreds and hundreds of thousands of attacks, you know, like you said, every Day. It was, it was very routine.

Yeah. It, so it, it, it really does get like that. But, you know, Gary, we live in interesting times.

We're living in an area of budget cuts and AI will do it for us, uh, just frankly, political infighting. You know, we ceases the, the very charter for Cesar and its funding was almost extinguished and then turned back on at the last second. Uh, who's maintaining the CVE database nist their funding?

How do you think this all plays into the future of US intelligence and cyber, cyber defense? So, I'm, I'm an optimist, right? I'm, I'm not gonna lie, I'm an optimist.

Um, here, here's my hope, right? I, my hope is the fact that, you know, sometimes in, in austere times, you know, things become more efficient because out of necessity, right? You stop doing, uh, things that maybe aren't, aren't as mission focused.

Um, I know in my experience in the military, anytime we went through budget cuts, uh, you know, a lot of things that a lot of us looked at and said, why are we doing this? Those, the, those are the things oftentimes that went away first. Uh, you know, so again, I'm an optimist, right?

I'm hoping that, you know, you know, maybe with some of this focus on, you know, trying to be good steward of tax dollars, uh, you know, try to look for efficiencies. I'm hoping that maybe we'll cut out some redundancies. Um, you know, we'll cut out a lot of, I think in the government, there's a lot of overlapping responsibilities, uh, you know, and, and, you know, the, the whole too many chefs in the kitchen kind of kind of thing.

Uh, so I'm trying to look, I'm trying to be optimistic, looking forward and hoping that things are gonna become a little more streamlined, a little more mission focused, you know, less distractions on, on maybe ancillary things. Uh, so I'm, I'm, like I say, I'm trying to be optimistic. I, I, I'm hoping that that's the way things are gonna play out.

I, I hope so too, my friend. In the meantime, for our friends in the public sector, or, you know, if you, as we mentioned, as you mentioned, the phone companies that service as public sector, the, you know, so-called Beltway bandits, the big contractors, the, the, uh, the Northrop's and the s aics and the, you know, so forth. Uh, what, what can they do, Gary, to try to, it is a cat and mask, and we are playing catch up.

What's your advice to, I'm short of going out and buying a lumio? Of course. Okay, well, you just stole my thunder.

I don't know what now, now, now I'm out of advice. Uh, you know, so, so I think there's a couple things, right? Number one is, and you know, I think some of this is common sense, right?

Number one is, uh, don't get trapped into believing that there's a, a magic button out there that's gonna solve all your woes, right? You know, don't, don't buy into some of the marketing hype of out there. Uh, if, you know, there are companies out there that say, oh, if you just buy us, you'll be a hundred percent safe.

You know, that's, that's just not true, right? Let's just be honest. That's not true.

I wouldn't say that about Illumio. I, I, you know, you know, I don't think there's any company out there that should be touting themselves as saying, if you just buy us, you know, we're you're, you're gonna be, you're gonna be secure, right? Um, there's got to be a, uh, combined effort of both tools, you know, uh, people, you know, let's not forget, I, I worry a little bit that, that people think AI is gonna be the magic solution for everything.

Um, it's not, no, I'm sorry. Hate, hate, hate to burst everybody's bubble. It's not gonna be the magic, magic solution for everything.

Uh, you know, can it be a, a huge enhancing tool for cyber defense? Absolutely. I think it can.

Um, but is it gonna solve everything? Is it gonna make every, every company, you know, 100% secure? Absolutely not.

Uh, you know, 'cause the, the attackers are using AI just like the defenders are, and I hate to break it to the defenders out there. Uh, the attackers are going to gonna always have a, an edge, because they're not constrained by law. They're not constrained by morality.

Uh, right? So they, they can get all, they can be a lot more creative, uh, than, than the defenders can, I think. Uh, so AI's not gonna solve it, right?

So for the companies out there, I would say, you know, think about asking the question of, you know, what am I doing from a defensive perspective? How am I looking at my tool integrations? And then, you know, what next, what happens when there is a breach?

How do I ensure things like that? I don't have to shut my company down? How do I minimize the impact of the attack?

Um, you know, what kind of rings of defenses do I have internally? Uh, you know, I really worry that companies spend so much time focusing externally, though they're not looking inwards. I would love to see CIOs out there and CISOs out there be graded on.

Yes, it's great if you were, if if you're, if you get a, a passing grade on, I was never attacked. I was never, never compromised. That's getting a harder test for anybody to pass.

I think that really it should be a ma a matter of how successful were you in, in, in surviving the attack, right? What had you done in place to protect the company, protect the data, right? Ensure that didn't get exfiltrated right.

You know, what have you put in place to prevent those types of things? Got it. Excellent, excellent advice.

Gary. Hey, we're about outta time, Gary. So we mentioned seeing each other at RSA, but that's March.

Yeah, You will have, you'll have news before then, so come back on and keep us posted. Okay. Absolutely.

Would love to. Anytime Alrightyy Gary Bartlett, public sector CTO at Illumio here on Textron tv, talking Soul Typhoon and more. We're gonna take a break here on the Textron tv.

We'll be right back. Hey guys, thanks with Throw, we're here with Chuck Hering, who's field CISO for F five, and we're talking about quantum computing and a, what are some of the actual real world applications today, and B um, we're gonna dive into cryptography a little bit and what's gonna be required and what we should be concerned about, and maybe what's a little more fanciful. Chuck, welcome to the show.

Thanks Very much, Mike. It's great to be here. I think we all think of quantum computing as some awesome thing that's gonna happen three to five years out, but there are applications being used today.

There are APIs and cloud services. So what are you seeing in folks actually doing with this stuff? I mean, The, there's certain fields where it's already making a difference, you know, uh, materials, engineering, medicine, things like that.

But I haven't seen a lot of broad adoption yet. But there are live quantum computers that you can go and rent space for, you know, right now, and have been for, for some time. Um, what we haven't seen yet, what's not real yet, as far as we know, are, um, the biggest areas of concern for security practitioners, which would be what we call a cryptographically relevant quantum computer, or A-C-R-Q-C.

So, jargon alert, there, there are some specific terms that, uh, uh, you know, some of our viewers may, may not have heard before. So I'll try to spell those out, you know, without getting into acronym, uh, acronym stew here. But what we don't think that we, any, any quantum computers exist that can break modern encryption and modern key strings now.

But we do know that they're coming and we've seen a great deal of investment in, uh, into quantum just in the last month, for example. Well, this month was a big watershed month. We had, uh, one quantum computer company go public.

We saw it for a billion dollars in inflow from VC going into quantum players. So we're, we're definitely getting to a, a critical mass takeoff point that defenders need to be ready for. Yeah, we hear a lot of people talking about Q Day, which is the day when these things can break some of these more relevant cryptography algorithms.

But, um, no one's quite sure when that's gonna be. Some folks are, you know, pointing to the end of the decade, and other folks say, well, it may have already happened, and we just don't know it. So where are we on this curve?

Yeah, right, right there with you. Um, if it exists today, it is most likely in the hand of one of the nation states and it's poor strategy to, for them to tell us that it exists. Um, so I, I don't, I don't want to get into the, uh, you know, the dark sections of speculation too much there.

But, but what I would say for the, um, for the defenders who are trying to figure out, like, when do I need to start tackling this? The time is now. I don't think that it's time to panic, but now is the time to start laying the groundwork, because there's a lot more to this and getting ready for the world of, of, you know, where post quantum, uh, cryptography becomes something we actually have to worry about every single day.

There's more to it than just swapping out a cipher. There's a great deal of inventory, supply chain stuff. I think people are, are not factoring in the amount of GRC type of compliance that we're gonna have to deal with from a supply chain and ecosystem perspective.

Testing, integration testing, uh, IOT devices, you know, OT devices, things that don't have a clear upgrade path. This is gonna take some time. So, uh, as, as we're telling folks, you know, we're, we're closer to 2030 than we are 2020, and and you are not gonna be over prepared for this.

Um, there are a lot of good reasons to solve problems today by reaching what we call the, the, the crypto agility target state, where you can roll your encryption whenever you need to without starting a new quantum project. Um, and this is a key point that I wanted to, to kind of bring the, the viewers into the target state for, this isn't a one-time upgrade. The, the target state for getting ready is crypto agility.

So we're recommending things like, you know, start thinking of crypto as a service where you centralize your libraries and you centralize services for cryptography across your applications to the degree that you can, so that when you have to roll your ciphers in the future, it's a much lower lift than it would be today, right? Because the, the computers that we're trying to defend against or protect against, they, to our knowledge, haven't been built yet. And these new standards, even though they went through very rigorous testing from NIST when they were ratified, right at a year ago in August of last year, the first set was ratified.

They've never really been run at scale in the real world. So there's a lot of stuff we really don't know yet about how it's gonna go. We don't wanna try to do all this all at the same time in the panic that now we have to do this, you know, in the next three months, right?

This is gonna be a longer tail effort than this. So it is time to get started and start laying that groundwork, especially when it comes to stuff like creating internal business cases for this, this is a very technical, kind of esoteric topic, and to your point, it's always been a future problem. I think CISOs and CIOs are gonna have to do a lot of internal education about what is this?

Why do we need to do it? How much do we think it's gonna cost? Uh, what is the impact to our supply chain?

I don't think this is as much a security issue, although the clearly security implications, this is a, this is a business continuity and supply chain governance issue. Like this is a much bigger thing than if you think like patching open SSL for heart bleed, right? That there's a lot more moving parts to this, and it's gonna take some, some coordination and governance.

Uh, we, we need to get started. Now, To your point, um, this isn't really an event. It's gonna become more of an ongoing process.

And I say that because won't the quantum computers just get more and more powerful so that, which we think today is quantum resistant, might not be quantum resistant. Three to five years out, Totally eight character passwords used to be just fine, then 12 character passwords were fine. Now, you know, anything, but, but, but passphrases and pass keys is, you know, almost immediately vulnerable and, and passwords in general are broken, uh, without MFA.

So, you know, as, as the capabilities for for the attackers continue to, to escalate, we're gonna have to continue to respond and, and hopefully respond as quickly as we can. Because, you know, a lot of critical industries, if you can't keep your secrets, you, you know, you can't play along, you can't be in that space if you, if you can't secure your encryption, you can't, like, you know, be a bank, for example. Um, and so what we may see, and what I think we'll probably see is I think we'll see compliance requirements actually driving a lot of the timeframes.

Um, when we talk about 20, 29, 20 30 windows that we're seeing pop up, you know, in the federal space here in the US New Zealand, for example, just published a paper that said, uh, we haven't defined standards yet, but as soon as we do, you've got two years from that date to get ready. So we, we think that compliance is gonna drive a lot of these timelines, and I hope that the compliance timelines are conservative enough so they actually front run Q day, but we don't know, right? And so if history's any guide compliance mandates will be the bare minimum, right?

And that may not be good enough anyway, A hundred percent. I, I I, I, there's very little, I I really struggle with more than compliance driven security, right? Compliance is the bare minimum.

Like being compliant is like showing up to work mostly sober wearing pants most days. You know, it, it is not the hallmark of a well run shop to meet the minimums that somebody else said you had to do to be a responsible participant in your industry. That's not the target.

Uh, it shouldn't be the target. It's the bare minimum to avoid getting fired or excluded. Um, so yeah, I really hope that that that doesn't wind up being the end all be all benchmark, uh, because there's a lot more business value you can unlock by actually having a good handle on your inventory and your cryptographic assets.

Mm-hmm. Right? There's good business reasons to get this under control.

So what will be required here, and I think a lot of organizations are struggling with this because they're saying, well, you're gonna tell me that some of my data will be exposed three to five years from now. I don't care about that data three to five years from now. So do I gotta pick my shots here about what data I do need to maybe upgrade?

But at the same time, they'll also say, well, I'm gonna get new infrastructure and I'll probably have new applications in that timeline that will come with PPQC capabilities. So what is this journey gonna look like? Yeah, totally.

And, and you're spot on some of the data that we need to protect every day. Like, let's take credit card numbers, for example. Um, mosque's theorem is a good, uh, is a good sort of way to explain the, the time factor here, uh, for pqc.

And that basically says, um, how long do you need to protect a certain set of data and add that to how long it's gonna be to get ready for PQC and migrate your stack over? And if those two things are longer than the date that we expect a, a, a full fledged, uh, cryptographically relevant quantum computer, then you've got a today problem. But to your point, not all of our data we need to keep safe forever.

Credit cards, they expire every few years. You know, I'm not worried about a credit card number 20 years from now getting exposed, right? That that's, that's a, it's, it's a temporal thing.

But other things, intellectual property, state secrets, uh, source code, um, internal information that, that you wanna keep secret for long periods of time. Medical records, banking records, financial transactions, and the ability to, to impersonate and spoof, uh, official parties, right? Because it's not just the confidentiality, but there's also the, the message digest and hashing and the binding of that encryption to the signing object.

All of that stuff is, is gonna be, is gonna be relevant, and, and we need to prioritize that based on what, what's the longest length of time that you need to secure particular data and really start there first and focus on, uh, the, the asymmetric encryption, right? So symmetric encryption, like a ES, um, we've had a lot of speculation about, um, whether or not symmetric ciphers were gonna be as dramatically impacted. It looks like they won't be.

And, um, further, when you actually break down how an attack against a ES works, for example, I've seen very recent research that says maybe a ES 1 28 is actually gonna be fine. Um, so we know where we can focus and we know we need to focus on asymmetric topography and long-lived data, and that's where we can start. And for companies that don't have an idea of where to start, I recommend starting with your business continuity program.

Hopefully you've got a BCP that shows what your critical apps are, where they live, who they own, who you know, who they're owned by, uh, and things like that. So you don't have to do it all at once. Absolutely not.

Is this just a quantum issue? And I asked this 'cause I've seen some research that suggests that people are using GPUs and conventional computers to crack some encryption codes as well. And this could become a broader problem that goes beyond just quantum.

It could be sooner than we think because somebody's gonna do some sort of technical advance. We weren't thinking about Yeah, Well, to totally. Um, and, and I don't know about what specific is, is going to, um, is gonna break next, but I will say that we are living in an exponential age.

And so if you look just, just in 2025, just this year before January, or excuse me, before February of this year, uh, we had no way, uh, to have a stable enough environment that you could put a thousand qubits or a million qubits on a single chip. Well, now we think we do. Microsoft said in, in February that they've got a clear path with, with their breakthroughs in Miana to get a million qubits on a single chip.

And that's what they're targeting. In May of this year, just three months later, the estimate that we would would need 20 million noisy qubits to crack modern encryption, Google researchers released a paper and said, nah, we think we can reduce that by about 95%, so we need about a million noisy qubits. Uh, and so that was three months in, in three months we went from needing 20 million to 1 million and also, uh, a path to 1 million on a single chip.

This is happening fast. I, I don't know what the next convergence is gonna be, but I do know that the, the, the more advanced AI gets and the models that we're using now are amazing, and they're only getting smarter. Things are gonna move faster than we think.

I don't think Q Day is a 20 35, 20 40 problem. Um, and humans aren't very good at predicting this exponential adoption curve, right. In 2021, if you asked a bunch of AI experts, when do you think we may see a GI?

The consensus was 2040 to 2070. That was just four years ago. I don't think anybody says we're 25 to 40 years away from a GI, you know, sitting here in September of 2025.

If we haven't hit it already, it's right around the corner. Mm-hmm. Um, when you kind of piece this together for a minute, we've always talked about data security and compliance and all that.

Well and good, but is this also starting to be elevated into a national security issue where because of the nation states that are involved and what they're gonna do with that data, governments around the world are gonna be paying a lot more attention to this? A hundred percent. A hundred percent.

If you're in a government supply chain, this will impact you, uh, and it will impact you on the government's timelines, not necessarily yours. But when you think about the, the geopolitics, uh, of, of the situation, which is notable in material, because I'm glad you brought it up. There's really two parallel race conditions that the US and China are, are on, and there are others that are in this race, but the, the most consequential, I believe are, are the US and China as the major superpowers sort of military powers.

Uh, that's AI and quantum, uh, AI supremacy. AI dominance means potential global dominance. Uh, it's very hard to fight 'em an en an enemy militarily that's smarter than you are.

And quantum dominance also means, uh, you know, potential geopolitical dominance, uh, at the intersection of AI and quantum, who knows what's gonna happen. So a hundred percent, the the nation states are, are running at this. Both the US and China are on very, uh, combative and adversarial, uh, footing.

And neither one is, is really making much provision for off-ramps. So we're, we're in this race condition, and, and I don't see a way out of it, uh, without, uh, a substantial shift in relations between the superpowers. Uh, and I I don't see that happening in the next few years.

So what's your best advice then, to cybersecurity people about how to have this conversation, you know, with business folks in a way that, you know, they'll listen and they don't mix. Don't sound like, you know, here's another chicken, little skies falling thing happening. A hundred percent.

I really encourage, especially for, for organizations that are part of, uh, industry groups, uh, for example, we spend a lot of time in, in banking. I come from banking. I was a bank and, uh, insurance company, CISO for a long time.

Uh, groups like FSI, sac, uh, the Financial Services Information Sharing and Analysis Center, they, they're, they're pushing and we're advocating and we're supporting an ecosystem view of this, right? So, so that the, the member banks can go and say, Hey, everybody's doing this. The banking industry is moving this way.

And take the pressure away from, you know, Chuck presenting a compelling business case internally, or Mike presenting an internal business case that's compelling. We're saying, look, we're all going this way. We all need to do this.

And, and take the attention away from the individual necessarily that's bringing it. I think that'll help. And the other is, I think to frame it in just a, a credible business continuity type situation, that this isn't just a security issue, this is integrity, it's availability, it's confidentiality, it's, it's all of it.

Um, and start with, we need to do some discovery. We need to understand how big this is gonna be for us so that we can come back with better numbers for how much we're gonna actually gonna need to, to remediate this. But there's gonna be some long tail stuff with you're, you're gonna have to deal with suppliers and physical devices and things don't have upgrade paths and HSMs and things.

So I think it's worthwhile to explain kind of the basics. The entire industry that you're in is moving this way, or maybe you're a key supplier to somebody that's moving this way and you have to do it, or you're gonna be replaced as part of, you know, their, their supply chain management. And let's get our arms around this, see how big it is, and then come back with some credible numbers and, and describe the actual work that you have to do.

But most companies really haven't even started with the inventory yet outside of banking, telecoms, and government. All right. Hey folks, you heard it.

Here. We have an opportunity to do something historic. For the first time ever, the cybersecurity industry could be ahead of a problem rather than chasing one.

Hey, Chuck. Thanks Pete, on the show. You got it.

Thanks very much, Mike. All right. Hey, back to you guys in the studio.

Hey, everyone, we're back here. Hey, this is our last interview for Swamp Up 2025. Woo.

I think I am gonna wear my jfr hat. How's that? Oh, You look beautiful.

All right. I won't mess my hair up. Yeah.

Um, so let me introduce you to our guest for our last interview today. There're two folks from Adobe. On my far left we have Shiba, Shiba, RA.

Thank you. We call him Shibu. Shibu.

Yeah. I go by Shibu. Yep.

Shibu is here. And to my immediate left, we have Vishal Reyna. Yes, sir.

Right. And we're just gonna call you Vishal. Yes, sir.

No shortened names there, gentlemen. Welcome and thank you for being our last guest here on Swamp Up 2025. Before we go further, I mentioned you both with Adobe.

Mm-hmm. And we, and as we were talking offline, we actually did a whole, what I considered a great series of interview with the Adobe security team around security and ai and how Adobe kind of eats their own dog food, if you will, or drinks their own champagne around security and to secure the products because all of us have Adobe accounts and we don't want that information Getting Act. Um, and we did a series of articles on it, you know, it was a whole treatment.

But you guys, you know those fellas from the security team? Yes. But you're on a different team.

Correct. Tell us about your team. So I'll introduce our team.

Um, we are the platforming group at Adobe. So when any developer wants to build something and ship it to their customers in one way or the other, we are providing the capability to those developers to make it happen. And, um, we, the pa the organization is named developer platforms, uh, and we partner very closely with Security organization, uh, led by Brian and Sure.

Chlorine and others who joined you in the past. And, uh, we work with them closely and, um, yeah, that's, that's our mandate, help our developer ship software faster to our customers, Better software. So when you say developer platform, is it like a true IDP At this?

Yes, at this. com. Mm-hmm.

Yeah. org group. Awesome.

Unit. Um, so I know a little bit about Enough to get in trouble about IDP. Is the IDP sort of like based on like a backstage type of Yes.

Thing, and is it, do you want to talk about that or, I know it's not really part of what we were gonna talk here, but I'm Curious. Well, I can talk about it. I think, um, in fact, Adobe was one of the first companies who worked with the industry, and we actually put out a lot of content back in 2022 when IDP as a term was picking up.

And yeah, we go and look at, uh, the different journals, I'm sure including some of yours, you would find that Adobe had made contribution. So we were the first few adopters of the IDP concept, and we implemented at our company, we built it on top of open source software like, uh, backstage, which you talked about. That is the portal that our developers use.

But it is powered by a lot of the CNCF community open source software. Um, we are a big consumer of, uh, Argo. Yes.

Uh, we are a big consumer of Kubernetes, and there are many more, Well, the, all the backstage stuff has Kubernetes at the heart mm-hmm. And then of course the Argo GI Ops. Yeah.

And all of this is now, you know. Yeah. It's, so I'm proud to say that we are probably one of the biggest, uh, installs of, uh, GitHub software in the industry.

I think we really set really big scale. We have really collaborated, uh, very closely with the community to scale the infrastructure. In fact, there is A-C-N-C-F blog that we have published on how we have scaled, uh, Argo set for ourselves to meet the needs where the, the off the shelf, the open source software doesn't meet our needs.

Uh, and I'll probably send you the link and you feel free to forward, you Well, may not be what we wanted to talk about. Hey. But Q Con is coming Absolutely right.

Q con cloud native con will be, uh, I guess it's it November Yes. In Atlanta. And of course we'll be there live the whole time.

Um, so, and that'll be both for our cloud native now and platform engineering sites. So maybe we'll, we'll talk absolutely more about that. I need to shift though, 'cause we are here at For J Rog Jfr and talk about what you're doing at Swamp Up.

I'll let that, uh, Vishal. So, uh, We, we did a database migration. Um, and as you know, most of the database migrations need downtime.

We were able to accomplish a zero downtime for our end users, and we wanted to come in here and share the best practices with our peers. I thought because we don't have AI in our subject or presentation, we are not going to get any audience. Turned out the room was full and we got a lot of exci engagement right up to the point where we were meeting co couple of industry colleagues here.

The goal was like how, how we came up with an eight hour downtime and that got shot down, and how did we pivot in less than 28 days and made a zero downtime using cloud architecture, um, to accomplish a, and many of historical Jfr Artifactory users who are on MySQL or Microsoft, um, SQO will need to do this to come to the Postgres. And we shared our best practices, both in terms of how we solve it with technology and also best practices in terms of processes and people and communication. And at the end, how we accomplish that whole, uh, zero downtime.

That's A great case study, a great case study. Let me ask a question just between us. Yeah.

Um, is the fact that it didn't have AI in it a, a reason why there were so many people in the room? I don't know. Maybe Have we all maybe AIed out a little bit?

Absolutely. You know, and I'm not downplaying AI or badmouthing ai, but it's refreshing to have a discussion that's not necessarily leading with ai. Um, you mentioned Postgres, right?

Yeah. Now Postgres is sort of one of the best kept secrets. It is not a secret, but you know, it doesn't get the de the, the what it deserves, the acclaim it deserves.

It really has become an engine, you know, and it started, I'm not, again, not taking sides, but when my, when Oracle bought my sequel mm-hmm. It set Postgres on fire. Fire.

Yep. Yeah. And, and since then, you know, you have, there are several different Postgres, uh, providers now in versions and some pure open source, some open core mm-hmm.

And what have you. But it really has become sort of the database or record, if you will Correct. For, for a lot of these large, large, you know, hyperscale kind of environments.

So, you know, that's something that, um, you know, I think a lot of our audience realizes it, but bear it's worth repeating. It's worth saying out loud. Yeah.

What I can attest is the performance issues we saw prior years when we were running MySQL with a lot of optimization hacks and everything else since we did the migration platform just scaled up and has been performing awesomely and we were apprehensive, like is it just one of those things that we have to do it with no gains, but we are seeing real benefits of this migration on top of it. Those of you who are running Artifactory do consider using direct downloads. It just is cherry on the, uh, cake and will give you more performance.

Really? Yeah. Direct downloads from Artifactory.

Yeah. Just my 2 cents on progress, um, Means it has become, um, such a good database and persistent choice that in the recent years, at least in the last five years, anything that we have that my team has built in-house has leaned to Postgres as the persistent solution. So the developers who are on the ground writing a lot of code day in and day out, it's their choice to do relational databases and persistence.

So plus one to what you said, Postgres has become that thing where, where probably Oracle of the last decade are. Uh, so like, but but it has become that like Database. No, it is, it is.

So I've been in this world a long time. MySQL was the standard Yeah, yeah. In SQL database because, you know, you weren't locked into a vendor and it was, you had the community developing it in essence.

And, and maybe it was, it was probably still a, a small handful of people who were contributing code, but you had the community driving the, the, the development visions and, you know, featured set requests and, and quite frankly, you know, Martin Kins and the people who were running it back then. Yeah. It was, it was a great open source success start.

Yep. Yeah. So for any project beyond the con core contributors, it's the ecosystem around it.

Yes. Like the different use cases. Oh, I, I, Hey, just a conversation just between us, like, Hey, I'm trying to build this app in this scale.

Go use Postgres, here's what you should do. Yep. So these things which we just take for granted, basically make the, somebody wrote a blog post or we came in and spoke about it's success in just specific to artifact.

These things do add up Absolutely. To, or as technology more successful Now. You know, you look at Swamper and I've been to a lot of Swamp up in many ways.

This is the company and the conference that Artifactory built. Yes. Mm-hmm.

Right? That was the acorn that this oak tree mm-hmm. Grew from.

But there's more to Jfr here. There's more to swamp up than just Artifactory. We saw today, you know, this week we, we saw, uh, uh, uh, JFR fly the, the agent AI repository.

We saw the AI catalog. We saw a lot. Yeah.

How does that fit in with your mission at Adobe and your, I maintaining your, uh, IDPs and, and your developers? Are they using these new tools yet, or you think they'll want to use these new tools? Uh, we go ahead.

Going after you. I, so, Um, we just started, uh, we were locked in Origins because of the database migrations. We just started opening up.

We are current and now we are in a position to start exploring and getting benefits from the machine learning repos coming in, or the catalog. And certainly the agent take workflows. We, we are going to go in and see where all working with Jfr, uh, our partners see how we can tap into these new offerings that have come in.

And let's not forget about the SBO m uh, AppSec, uh, offering that has come into. So we, we are going to go and explore these. No, we are very interested.

And so I think, um, there are two sides to it. One is, as a platform group, whatever we are offering our customers, we want to make those capabilities more urgent tech. So we, between Vishal and myself and our teams, we need to build more agents.

And the capabilities that kind of were, uh, published in this year's sw up some of that. We are very interested into, um, looking at and see how that can help. Uh, the second side of it is, as our product teams are taking that agent journey and bringing in agent features into the products product like Photoshop, illustrator and several others, they need a platform where they can run agents.

So we are solving that agent platform problem as well as we are building agents for ourselves, which would let us kind of expose our capabilities back to, so on both sides, the, the, the, um, the announcement that came from jfr, the excites, uh, the Excite us, be it AI catalog or any other feature, I feel that can really help us. Um, so we will go back and start looking at them and see how we can factor them into our, um, our use cases. I love it.

You know, um, people don't realize about Adobe. You know, Adobe is, look, it's kind of a Blue blood, a royalty name in, in the software world, we all came up using Adobe products, whether it's for video or graphics or PDF or what have you. But I don't know how many people out here really realize Adobe is a company that's very transparent about how they build, how they secure what they do internally, like their their own best customer in some ways, right?

We we're gonna show you what we think are best practices and you should feel free then to use them, right? We, we've already paid the idiot tax in some respect, learning these things, and we're trying to save you from paying that tax going forward. I don't think they get enough credit.

I mean, you make great Photoshop, you make great Acrobat, but really being a good, a good community member Yeah. Right. In the software industry is, is commendable.

And, and I, you know, congratulations to you not just that you two, you but the whole organization. Yeah, yeah. For the, for the way you do it.

It's, it's really, I wish more companies were like that. Absolutely. No, I think, uh, this has been a practice in the company since long time before we began our stint here.

And we are just continuing that, right? So our leaders tell us, like, whatever we learn, it's our responsibility to go and pass on to the community. And we are doing it.

Vishal and his team did extremely great job of this really difficult migration. I want to thank him and his team and all of the people who really did the work on the ground, and his team is coming in and sharing all of that with the community. And it, it, there's a lot of interest.

I'm sure other teams are going to do the same. And, uh, this is going to have A lot you've well received. Yeah.

Where's, where's, where's the next conference you're presenting at? I haven't decided yet, but we'll identify something soon. Yeah.

Our group is, um, going to CubeCon. We have some presentation. We Will be, we'll be a CubeCon going live.

com site. Yeah. To find out more what you're doing with Platform and how you're building it out.

Yeah. Because this is, you know, DevOps, cloud native platform engineering, these are all just different pieces of today's software factory, including ai. You know, AI plays on all of them.

Yeah. It, it, it just basically, uh, compressing, uh, I was talking to one of the, uh, conference attendees. What AI or generating AI in particular has done it, has flattened the learning curve, like getting a particular sector or a piece of technology or coding for that matter where, which is what Shibu and I are closest to the Getting a prompt in and start learning about, or basically porting a technology which was written on one technology to another technology.

It's not completely solved, but it certainly is easier. You can understand legacy codes better. All of these have intangible, uh, benefits and that's why we'll see more software coming faster at us, which basically puts stress on all the underlying plumbing or the CICD supply chain.

That's where the, the platforms had to come up to basically, um, deal with the new throughput of, um, innovation coming in and making sure that each of the right customers. Absolutely. Gentlemen, I want to thank you.

Thank you, Micha. Pleasure. Shibu.

Thank you. We're gonna wrap up our, our swamp up coverage. I hope you've enjoyed it.

We will be back. Well, I guess we'll be back tomorrow with more texture on gang, just not out here in beautiful Napa. But until then, this is Alan Shimel on behalf of Jay Frog and all of our guests, thank you for watching and staying with us, and, uh, we hope it was valuable to you.

We'll talk soon. Bye-Bye. Hi everyone, welcome back here to our day two coverage of Jfr Swamp Up event in, uh, beautiful Napa Valley.

We're at the Meritage Resort, and if you've never been here, highly, highly recommend. It is a full on resort and spa with wineries on and vineyards on premises. It's really a lot of fun.

I I really do, do recommend it all. You. Um, let me introduce you to our next guest, though.

We have two guests here. We have Amman, Sarna, and I hopefully get this right. Vijay Kumar.

Hey. Hi, Aman and Vijay work for a large financial, financial institution. And they're here talking about, you know, in a hybrid AI world, how, you know, how large financial institutions can get a hold of their, or it can, you know, manage their CICD pipeline, their software, supply chain, security of it, and everything else.

So Armand is closest to me here, vj, to my far left gentleman, welcome to Textron tv. It's great to have you on here. Yeah.

Thank you so much. Yeah, we are, we appreciate the opportunity to be here and in this beautiful Napa Valley. Yeah, this beautiful day, This worst, worst places to be.

Sure. Um, so let, let us talk a little bit about you guys presented actually. Yes, yes, we did.

So if you wouldn't mind, share with the audience a little bit about your presentation. Sure. So, uh, we gave a talk yesterday.

It was, uh, a good opportunity to come here and, and president in front of like a large crowd talking about like how, uh, a large financial institution might do, uh, a resident release of their workload, especially in a hybrid cloud setup, where the complexities are very different, right? I mean, uh, uh, typically like companies, they start small, uh, going on-prem, especially in large financial institution. Uh, there's a lot of legacy stuff that still runs on-prem, right?

I mean, uh, especially in bank financial domain. Uh, companies started with building the infrastructure, uh, in eighties, nineties, early nineties. And that infrastructure still runs on-prem.

But the challenge is that, uh, in order to compete in the marketplace, uh, companies have to evolve and, and make sure that, uh, they, they are able to seamlessly integrate with FinTech, uh, especially like the, the new age companies, modern age companies. And there is a pull, like on, uh, on the other side to build modern software. And that brings a unique opportunity as well for the companies to start looking at how they can modernize their existing workload.

But the challenge is it's very hard for the companies to migrate everything and in one single shot. So the strategic choice that company has is to invest in hybrid cloud capabilities, which doesn't come for free. I mean, there are challenges, uh, that we can talk about, but definitely, uh, there are a lot of opportunities that show up with hybrid cloud where companies can scale, they have a capacity burst.

Um, and then a lot of like where advantages when it comes to like innovation, making use of like, um, a lot of like different, like new technologies that are being developed and, and are cloud first. So that kind of like bridges sort of like the gap with hybrid cloud, where companies can still run the critical workload on-prem, but then at the same time, they've find a way to sort of like, uh, gradually move, uh, to cloud in a phased approach in a phased manner. Excellent.

You know, I, I think, well, I'll speak for myself. I'm not gonna speak for everyone. That's kind of the way I always envisioned it, right?

That you don't, I remember, I, I was at an IBM conference eight years ago, seven, eight years ago, talking to the CIO of Hertz, the car rental company, and, and he said they decided to go to the cloud. And what they did is they built from, from scratch all new cloud-based applications, and soon as they had those up and running, they literally just shut down their old on-prem data center applications and switched over. Well, it was a disaster.

Hertz wound up filing bankruptcy, if you remember a few years back. Yeah. He lost his job.

Yeah. And, and so I always knew that that was not the way to do a cloud migration, right? You don't do it that way.

You had to do it over time, and you're gonna have this hybrid model and that, and there's nothing that matter. That hybrid model may last forever. Quite frankly.

There's nothing saying that you gotta move everything into the public cloud, right? Yeah. I mean, if you look at, right, we are kind of home of innovation right here in, uh, California, and as you go from Napa Valley to south, you start seeing the innovation every, every mile, every minute, right?

Yeah. So if you look at this space and the, not just fintechs, the large electronics company, you know, the apples and Googles, how they innovat it last, uh, you know, one and a half, uh, um, a decade. And if you look at all these things happening together, they're integrating with financial institution, they're integrating with healthcare and whatnot, right?

So if you see the innovation is happening and financial institution cannot be left behind, right? So they need to be, they need to make sure that the customer experience is retained. Customer wants everything on the fingertips.

So all these digital payments coming together, it's, it's, it cannot stay on the legacy because legacy may not meet the customer expectations. So I, bridging the gap requires, you know, the resiliency everywhere, right? And we have a kind of a environment where customer is at the center and everything needs to be delivered quickly to the customer.

So that's where the, the cloud and the DevOps and automation comes into the play, and that finances services are catching up if they were behind, but they are not too far from getting, you know, no, uh, to the space where they're supposed to. So, I, I'll tell you a, a funny, not funny, but I'll tell you an observation I've had, right? com, it was 2013, so this is 12 years already.

Yeah. And, um, yes, traditionally, finops financial institutions being conservative and highly regulated don't necessarily have bleeding edge, right? They make sure something's tried and proven before they, they leap into it.

But when it came to DevOps, and then DevSecOps, right? I saw financial institutions take the lead. And the reason for it was, quite frankly, where they were, was not a good space from a security point.

They were being attacked and hacked, and they had to do something. They had to get better control of that, number one. Number two, the market was changing.

You had this new breed of financial institution that was, was born in the cloud, that was born on the internet that was more nimble, right? Because customers, you know, when I was a little boy, we didn't have ATMs even yet. You had to write a check.

You wait online at the bank to the teller. Yeah. Yeah.

And they would give you the money. ATMs came out, but then apps came out on the phone, the cell phone, right? Yeah.

It just changed it. All of a sudden, people were, how often do you actually go in a bank anymore? How often do you deal with a human at your financial institution group?

Only if there's a problem, basically. Yeah. So as a result of this, I, I think the market flipped finance became a leader, right?

In customer, you know, giving the customer what they want, when they want, how they want, which was primarily through an app. Yeah. Not through a brick and mortar.

Mm-hmm. And, um, so my experience is, is that they have led the way in DevOps, they have led the way in a lot of these innovations. However, they still gotta worry about highly reg being in a highly regulated industry.

Right. Let me though, ask you again, you, you made this move into this hybrid environment. Do you envision going total cloud, or will you always, you know, I look, a a lot of financial institutions still also have mainframes, right?

Yeah. And you're not gonna move, you know, to walk away from your mainframe. Yeah.

That's a statement, right? Right. That, that, that's, that's not easy.

Yeah. com and their text drawing, they have, you know, they maintain a sy a system of record and a system of engagement, right? Yeah.

Record being usually a mainframe at a data center somewhere. And engagement may be up in the cloud, right? Is that how you guys envision your go forward?

Yeah. I mean, the way I say is that, never say never. Okay.

But at the same time, as an organization, and depending upon how you are set up, you build the strategy and the strategy as the time passes because of the other factors. You know, you may plan and say, okay, I want to move into cloud, you know, but as you see the opportunity, you could probably shift and then get rid of the on-prem, or you think that Yes, probably in the long term strategy, I have the midterm milestone to determine whether I can get rid of, or I still need to maintain. So the ag organizations build their strategy, depending on the size of organization, depending on the customers they are serving, depending upon the partners they do have, they make the strategy in general.

There are a lot of organization they can get rid of this, um, on-prem setup just because the way they are set up and the customers they are serving in probably our case. And there are some similar cases, probably it might be a time to see, you know, in next couple of years or few years to see that, oh, now we have moved enough. Probably it's time to, you know, get completely, uh, other side of the bridge.

So that, that's kind of strategy, you know, as, as, as we go. So, so short answer is we are yet to see that, how the strategy evolves to, you know, get to the fully cloud and we stay onto hybrid mode. Yeah.

And just to add to like what we just said, I think, which was very well said, um, I think companies also have to make sure that they're doing it in a very sustainable manner, right? So, um, I think we just alluded a little bit, uh, on that as well, that it should not be like a big bank sort of like move to cloud. Uh, of course, I mean, it's a learning opportunity for a larger institutions, right?

I mean, where, uh, they might have like thousands and thousands of applications running on-prem. Um, they have like few applications running in cloud. Now there are challenges that show up, right?

I mean, you might have a data sitting on-prem, there might be regulations right around how you store the data. Uh, you might have to be in compliance with, with your data, right? So, uh, sometimes you might want to move the compute to cloud, uh, to the cloud, but then you might have, uh, some restrictions that you cannot move the data to cloud.

Uh, there might be some, uh, innovations that might have to be done in order to be able to move the data to cloud. Uh, but I think that's probably, uh, uh, kind of like a, uh, uh, an approach that company can take where they can take some steps in a phased approach before they finally land in, in a, in a, in a state where they can declare that they're fully running into the cloud. But I think that that should be probably the mantra for any company.

I mean, that could be the north go north star for the company, but again, there are various factors that can, that could influence that journey, uh, towards that North Star. Agreed. Yeah, agreed.

You know, another phenomenon, so I hybrid to me was always obvious. Yeah. You know, what wasn't obvious to me, multi-cloud, right?

So do you see an institution like yours going multi-cloud using more than one hyperscaler cloud provider? Yeah. Maybe I can just quickly, uh, throw some light on that.

So definitely there are like a lot of different cloud providers, public cloud provider, and every cloud provider has their own sort of like, niche, right? Yep. Uh, you can look at my Microsoft Azure, Google Cloud, Amazon Web Services, uh, all of these like big cloud providers, I think, uh, they, they all are innovating.

Um, they are sort of equally good, but some cloud providers have services that, that, that probably might be like more niche and more sort of like cater to a certain sort of like, uh, industry, right? So, um, I think in general, companies are sort of like investing, uh, in one major cloud provider, but also being at the same time cautious about the fact that, uh, there has to be some sort of like a risk management approach that has to take Well, You don't want to locked In. Yeah, you don't want already locked in.

But at the same time, uh, it's also a conversation around like the cost management. Uh, you don't wanna put all your eggs in one basket. Yeah, that is true.

At the same time, if you divest too much, then uh, you are also kind of like, uh, not reaping the full benefit of like having a cost, sort of like optimization by putting more workload in, in one single cloud provider, and then kind of like being able to negotiate, uh, a price point that serves you well, right? So, uh, it kind of like, it can go either way, but then of course, I mean, you have to have a balanced approach as to like how much you diversify, but at the same time how much you concentrate and, and can like, get the cost optimization. Yeah.

To add to, among what he said, like if you look at probably no organization, which is using a service as a SaaS is insulated from multiple cloud, you know, um, uh, environment, probably directly running its own workload or probably via a service provider, there could be likelihood that you are using underneath, right? But the important point is that if, depending upon the size of the company, the customer, it is serving the geographic location and pricing point, the organization chooses to be, you know, into the multi-cloud versus single cloud now, and then the on-prem, right? So if you look at the landscape, they are, you know, in the multi-cloud strategy probably is better in certain cases when you are like global company and then you are serving the, you know, different type of, uh, um, customers and services, and then, you know, um, the kind of, uh, product you are offering.

And in that case, sometimes you may, you may have, we not have a choice other than going to multi-cloud. So those factors come in. But if you are like a small organization, probably you may opt in to have probably two providers, and probably you are happy with that.

And so you can negotiate the pricing and do other things. But at the same time, if you are, say if you're going to a CF aspect reason, and you do not have that cloud provider capability, you are bound to have used another cloud provider, which is already there because you want to serve your customer. So those factors kick in.

But certainly from the, from the financial institution or, you know, the global companies which are serving the customer, they probably make those, uh, smart choices depending upon their business strategy, uh, in global landscape. I love it. Gentlemen.

I apologize. We got a lot of background noise. Hopefully it's coming out well in our microphones.

Um, last subject, ai, how's that playing into this? I think no company is shielded from ai. Uh, I think that's, given that in order to stay ahead, uh, companies have to make investments into ai.

But again, it at the same time, financial institution, uh, banking, and lot of like different industries have to be very cautious about like how they use AI in a responsible manner. I think one of the biggest challenges, uh, especially when it, when, when, like, when it, when it relates to like financial matters, right? Um, AI can sometimes make a decision that may not, uh, be very well in kind of like aligned with regulators, right?

So in general, um, AI has a lot of potential, but I think there is still, uh, some work that needs to be done to make sure that AI is used in a very, very responsible manner. Now, there are use cases where, uh, AI can be easily used, right? I mean, uh, we have seen financial institution investing like in deploying AI in call center applications just to help agents serve better, uh, for the customer.

But I think what we have seen, like in the industry in general, is AI being adopted in a core sort of like, processing is still sort of like something that has to be, uh, uh, has to be, well, kind of like, um, uh, there has, I mean, it, it requires some sort of like investigation as to how it can be incorporated in a responsible manner. Because I mean, anything that you do has to be explainable, right? And sometimes the challenge with AI is that it, it's not very conducive to explain like how decisions were made, like, uh, by the ai Yeah.

For certain industry it might be simpler, you know? Yeah. If you go to manufacturing, it might be simpler because you are doing mechanical in most of the cases.

So it's a simple, it's a repeatable process, you know, you're not making a lot of decisions there. But if you go to the healthcare or, you know, uh, into the spaces where humanists are involved, you know, decisions are involved, financials are involved. I think it's, it's, it's very, you know, the area where it's not easy To not in the highly regulated, You can go move forward with that.

Highly Regulated in Yeah, exactly. So, agreed. So those considerations, you know, are always there.

But as AI matures, who knows, you know, in next few years things may change differently. You know, what if the public, if your customers demand that sort of functionality, you're not gonna have a choice. That is true.

I mean, that, I mean, customer comes first. It's A led Business. Yes, he is.

Yep. Anyway, Hey guys, thank you for coming on, For having us today, z Thank you. Good.

Swamp up. Thank you. Yeah, thank you so much.

Yeah. All right. Vj, Oman.

Aman, yes. Here on Techstrong tv. We're gonna take a break.

We'll be back in a moment. Hey everyone, it's Shimmy, and welcome to this week. Shimmy says, we're back on track on Thursday.

I hope you're able to join us or wherever you're watching this, whenever you're watching it. Thank you. You know, I, I'm going to throw back to some Hillary Clinton in the People's Republic of China, years and years ago, I think it was 96 or something, when she said, women's rights are human rights.

And, and that became a bit of a, a cliche, well, in my best, Hillary Clinton, I'm not a good Hillary Clinton impersonator. I'm here to tell you today that digital transformation is AI transformation. It's been replaced.

It's been disrupted. You know, I always felt that digital transformation was one of the most overused, misunderstood words in technology. What exactly did we mean about digital transformation?

Well, when I first heard it, I, and I don't know, maybe I'm a child of my generation. Well, if we're doing a digital transformation, we must be transforming from an analog world to a digital world. And to a certain extent, some digital transformations were like that.

It was about moving from a brick and mortar store to a online e-commerce situation during COVID. This became a must have, right? Because if we didn't have a, a way of reaching people who were stuck in their homes and getting the goods they ordered, 'cause some of it was digital that they could download, and that's easy.

But getting physical goods to them required us integrating a digital selling delivery, logistics, operational method into our analog world. And, and you know, what? Necessity's, the mother of invention, so many industries, so many companies got with it quick.

And we saw the biggest move to digital away from brick and mortar, probably ever during COVID. But there was other kinds, there's other kinds of digital transformation. You may already be digital for some people, digital transformation was moving from a private data center to a cloud public cloud.

For others, it was moving from a mainframe to modern, uh, modern architecture, cloud architecture, or a hybrid architecture, or a multi-cloud architecture. It was the cloud native digital transformation became anything where you were transforming your organizational business model, processes, practices into something more modern. And we, we slapped the DT table on that label, on that digital transformation.

Now, what we've seen in the last two and a half years though, is a move to AI transformation. And I think this level, this AI transformation is gonna totally replace digital transformation. Because what we're doing here is everything is being transformed and disrupted by ai.

So it's not enough just to move your brick and mortar store to some app or your financial, your bank from a brick and mortar branch to an app. Now we're enabling them with AI so that the AI can, in essence, do it for you. We, I saw just this week, probably three or four different pitches come my way of agentic AI handling your finances.

Don't worry about balancing your checkbook, paying your bills, or doing any, or managing your investments. The agents will take care of it personally, I don't know if I'm ready to trust an agent to handle my finances by un un unhinged or unmanaged by me. But this is the kind of AI transformation that we're seeing.

We're seeing it in writing code for applications. We're seeing it in migrations to public cloud, back from public cloud to private cloud, to bare metal to the edge, to endpoints. AI is handling all of this for us.

Um, and, you know, this is the year of AG agentic ai. I don't even think we've seen the full extent of, you know, a lot of these agents are just being rolled out. But whether you are using it for travel to arrange your travel, to do your schedule, to respond to your email, virtually every task we think of AI is transforming the way we're doing it.

So I sit here today and tell you that digital transformation is AI transformation. You, if you are transforming things you are doing, your organization's doing without building AI into that process, you're just wasting your time. 'cause you're gonna have to redo it real soon.

So, if you're thinking about a transformation project, think along the lines of AI transformation. So remember, you heard it here from Shimmy, right? Digital transformation is AI transformation.

What are doing for AI transformation today? I'd love to hear about it. com.

And I, I'd love to hear your story. Maybe we get you on a shimmy says, or a text drug TV interview or something. But we're looking for AI transformation stories Until next week, enjoy the weekend, be safe, and well, I'm out.

Good morning everyone. Good morning, panelists. Uh, my name is Manny Calero.

I'm a consulting solutions architect, dita. We're an edge management and orchestration platform to help our customers solve business and technology challenges at the Edge. Today, we want to jump in and talk about understanding containers and, uh, workloads at the edge and different approaches.

So let me start with a question. Do all edge workloads really look the same? And the answer is really no.

Some workloads are large, heavy, distributed cloud native applications that may require Kubernetes, and Kubernetes is fantastic for those. But, um, some edge workloads are smaller. Maybe a connector, single analytics engine, IOT broker, or perhaps a lightweight multi-service application.

For those maybe Docker composed makes a lot of sense, and that's the right tool. It's fast. Familiar developers, um, are used to, uh, using Docker compose locally on their laptops ideal for Brownfield or, you know, resource constraints sites.

So to the point we support both, um, and you can choose with, with our platform, you can run either Kubernetes where it makes sense or Docker compose, where that's a better fit. And, um, now let's talk about if developers are already using Docker Compose, why is it important that we bring that to the edge? So one of the biggest challenges, um, at the edge is diversity of workload.

So in most environments, um, you don't have one type of application. You typically have many. Um, you've got legacy VMs running, you know, that have been running for years to, uh, maybe Windows machines.

At the same time, your developers are delivering modern containerized apps, often defined with Docker compose and looking ahead, there's always new container frameworks that are being introduced and services that are being introduced. So, what makes us unique is that we don't force you to choose one model. We support them both.

And instead, uh, we provide a platform where you can run all of those workloads side by side and on the same edge node. So the bottom line is whatever workload you you have today, and whatever you add tomorrow, we will support it and we can orchestrate them. So here's the, the real strength of our platform, and it comes down to flexibility.

Um, most edge environments are often clean slates. Um, you've got legacy applications that are still running in VMs. Uh, you've not containerized apps, but some are defined in Docker, composed for those that are containerized.

And, uh, you may also have other, uh, modern container frameworks that are emerging. So with us, it doesn't make you choose one model. Um, and whether you have 10 nodes or 10,000 nodes, we'll provide the same zero touch provisioning and policy-based orchestration to make sure everything's consistent and scalable.

So, repeatable architecture is really important to us, and to be able to bring scale, uh, to the edge is really important, which is kind of what Docker composed lax, and it's get the scalability piece, and that's what we bring to the table in, uh, delivering a Docker composed solution. So whatever workloads you have today, and, you know, whatever you bring tomorrow, we can help you and our platform can orchestrate them. Hey, Manny, it sounded like you said that most edge deployments are clean slates.

Is that what you Said? Thank you. For point of note, they're not clean slates that we typically have a lot of legacy apps running And, and devices and devices exactly.

That you wanna reuse if you can. Okay. Yeah, and that's one of the cool things I think more Borg mentioned was, uh, about, uh, EVOS, which is, it can run on very, you know, very lightweight, uh, very small form factor, uh, type of hardware.

Um, so it's really powerful in that sense to support legacy, um, smaller applications. So let's talk about how this works, uh, from the user perspective. So typically it'll be either a developer or enterprise user.

They're deploying, uh, containers, they're creating their apps, they're containerizing it, and then they're typically using Docker composed. That's a very simple tool. It's very powerful.

It's very quick, very streamlined. Um, and then from, from that perspective, they'll create the application. They'll have their YAML file already defined, and then from our market marketplace, what they can do is they can, uh, from the global marketplace, import into their local marketplace, what we call a, a Docker composed runtime.

And then they can deploy their apps on there. So the runtime is in our app, it's maintained by zaida, so it's very important, right? We patch it, we update it.

The whole lifecycle management is care and fed by zaida. Um, and then once it's in place, the user can simply take their docker compose YAML files, their existing, uh, configurations that they're using today, and deploy them in the runtime. So the result is the applications are instantiated and running on the edge node fully orchestrated and supported by Zita.

So from the the customer's point of view, it's a straight and simple flow user marketplace. Put your YAML files in an app and orchestrate it, um, on the, um, on the runtime. So the benefits that we see and how we make it, uh, scalable to, to our, you know, our customers is speed, right?

Uh, fast onboarding in minutes, uh, same YAML files that they're currently using. Uh, we're flexible, um, because we could not only support VMs and, uh, Docker composed runtime, but also Kubernetes, uh, when needed. And then the, the really important part that, uh, and the gap that we fill is the scalability piece, right?

If there's one missing piece to, to Docker compose is the fact that it's, it doesn't scale very well. It works very well in local environments, you know, maybe small, you know, five, 10 sites. But as you start to scale, uh, in the distributed edge, it becomes really important to have platform that can take that repeatable architecture across geographies, and then maintain that single control plane, roll out updates, roll them back, keep visibility across a fleet, and then of course, consistency, uh, repeatable architecture.

So taking the same, uh, YAML files that you may be, you know, compiling on your, uh, on your laptop. And take that to, uh, this adida orchestration, and then create those predictable outcomes across dev test production and lower, you know, the operational risk that makes, uh, adoption frictionless. So now I wanna show you just a quick diagram.

Um, I'm gonna run a demo in, uh, after this slide here. And what I'm doing is from this adida platform, I'll be orchestrating onto two edge nodes, um, the same application. So to show you kind of how we de deploy across the, the fleet, um, so you can see it in action.

And then I'm gonna sprinkle Terraform in that as well. I love Terraform, and that's, we're very proud of our Terraform provider. So, um, I'm gonna be doing some of the deployment through that.

Um, I'm gonna show how, uh, I can deploy the infrastructure to the point where we deploy the runtime, and then I'll kind of stagger it a little bit, deploy the runtime, and then deploy the apps, and then show you what they look like, um, in the, in the, uh, the marketplace. So here, I'm gonna start the demo, and this is what our, our UI looks like. So we log in here, the first thing I want to do is, uh, show our, um, our dashboard, and then go through the different sections to show that there's no elements created.

Uh, there's no networks, there's no edge nodes, um, there's no marketplace apps. And then the first thing is show the Global Edge apps. So if you go into our global marketplace and you click ZA data, you're gonna see that we have three Docker composed runtimes.

Um, they're different flavors. I'm gonna go ahead and import the large flavor into our local marketplace. So now you'll see if I click on here, there it is.

Uh, and then once I go inside, you can see some of the particular elements within that runtime. So, four CPUs, eight gigs of memory, storage size. And then what I typically like to do, especially for the demo, is I cloned the app.

I don't necessarily have to use that. I can clone it and make some changes. In this case, what I did is I, I cloned it, and I'm going to reduce the persistent storage size of 20 gigs.

The original had a 200 gig, but it shows that we can kind of tweak, uh, those applications in terms of sizing, and then I'm gonna keep all the defaults the same after that. So here, I've got a cloned, uh, application. So now what I'm gonna do is I'm gonna pull up my Terraform code here.

I kind of show the, the diagram again, of what I was gonna deploy. But, um, I'm gonna go through the, the Terraform code and kind of walk through what it takes to build the infrastructure. So it starts with a project that's kind of the umbrella, and then everything falls under that.

You have, uh, your images, you have your storage repositories, of course, your edge nodes for onboarding, uh, and then of course, the applications where you define them, the, uh, the network instances and all in, you know, a single Terraform file. And then I, I'm gonna deploy it to the point where I'm gonna have my projects, my data store. This is where, uh, I would store applications, the image, this is where the, the package would be.

And then, uh, a couple of networks and, and, uh, the applications that you're gonna see in the marketplace that I'm gonna have, uh, deployed through here. And these are the YAMA files. I don't know if you can see it on my screen, but I feed the YAML file to the Terraform, and then the end result is in the marketplace.

You're gonna see the application, and then you're gonna see the YAML file. So here I did a plan and apply, and then I'm going to show you how I created a couple of edge noes. I created network instances for those, and for the runtimes, I created the Edge apps.

So I created four edge apps. I created, you know, very common apps that we see, like Grafana Ignition, uh, and Splunk. And then within those, uh, the yamo files are, uh, are configured.

Uh, here, I'm gonna wait a little bit. Uh, it takes a couple minutes for, um, the, Yeah. Quick question, while this is, while this is coming up here.

Yeah. Um, let's say I'm using some orchestration, uh, software that's not Terraform based. Can this be consumed with a API, right?

Can I drive the Zita dashboard and cloud from that API? Yeah, absolutely. So Zita is 100% API driven.

Even the web UI that you see there is driving an API on the backend. So we have our, our API is, uh, published, so you can leverage, uh, Terraform, you can leverage our rest, API, um, and also we have our ZCLI. So it's, it's a very flexible platform.

Many ways I configure it. I happen to love Terraform. So I, that's the way I kind of orchestrate all of my, uh, uh, my environments.

And then here, uh, you can see the, the edge node came up. So they're green light, that means they're onboarded. What a typical experience for a customer is, this gets shipped to a customer, they plug it in, turns on phones home, it's registered, and then that becomes a registered endpoint where you can start deploying apps.

You can deploy your runtimes from that marketplace. So here I'm just showing a, some details around the, uh, the edge nodes, uh, the adapters that are available, uh, some detail on that. And then here, what I'm gonna do is now that the edge nodes are up and running, I'm gonna go ahead and deploy the runtimes.

I can still do this from the marketplace just by launching it. Um, I wanted to show the flexibility of our platform. So I'm doing, I'm doing it through Terraform.

So I just do, uh, a plan and apply here. And then as we go back to the dashboard, you're gonna see that now I've got a couple of run times that are coming up. There's one that's already downloading, and then within a couple of minutes, they're up and running their green light.

That runtime is ready for you to execute those yamo files that I mentioned before, um, that I also created. So once they're online, you can deploy your apps here. Now, you can deploy straight from here, and you can see as, as I click on, on the application, you can see the YAML information in particulars for each, uh, for each app.

And then you can deploy it straight from here. I'm gonna go ahead and deploy it through Terraform just to show the automation piece of this. Um, right after I show you this last YAML file for Ignition, um, ignition is very popular app for our manufacturing, oil and gas customers, very common application, um, automotive, uh, plants.

So here is where I start deploying the apps. So I'm gonna deploy the, the application across the two, uh, edge nodes. So both, uh, Grafana, uh, Splunk, and of course Ignition as well.

And through that single entry for each one, it's gonna spray it across the different Edge nos. So I'll just do a simple plan and apply again. And of course, I can do this with a single swoop, but that would be kind of a boring, uh, boring demo.

So, um, I kind of staggered it a little bit. So now you can see that the, uh, the apps are, are being deployed. Those are the demo files that I showed you.

And now you can see how we can scale this. I don't have to go to each edge, no, and run a docker compose command to make the application come up and run. I can simply do it from a centralized location like I'm doing here.

I chose to do it through Terraform. You can also do it through, uh, the marketplace here. I kind of went in the CLI to give you an idea of what it looks like on the Edge node, and you can see that the, uh, um, the container image is being pulled, and then they start to come online.

Uh, now they're all loading, and then eventually all these will turn green, and then you'll have a, a running application. So here we got a couple that's already came up. And then, uh, in this next section, I kind of went through the, the, uh, the UIs to kind of show the apps running.

Um, I wanted to then pull the each runtime and show the IP address that's on there. So I have a one, a 1 5 8 address, and a 1 0 6 address. So that would be the target of what application you want to access.

So what I'm gonna do here is to show you the URL is I'm gonna open up all these apps. I kind of sped up the, the video a little bit on this one to get there. And then you can see 1 5 8 was my first note, and I can access Grafana.

The application is available there. And then I went in, uh, node number 2, 1 0 6 logged into Splunk. So basically, both apps are running on both Edge nodes.

Um, and then of course, ignition here. Um, I show how we can automate the deployment of Ignition. It already pre configures with a username and password, and I can take it further and configure, um, you know, MQTT endpoints.

And that is my demo. That concludes what I'm showing in the demo here. I have a question regarding sequencing.

It seems like you have to install Docker compose on the edge nodes before you can install all those apps using Docker Compose. Is there something intelligent on the node side that understands the sequencing of the dependencies, or is that something you have to put into your Terraform configuration or your, your script? So our, our system is built to queue things.

For example, I can create an Edge node and deploy network instances. It knows that the Edge Noe isn't up, so accuse that job. Once the Edge Noe is up, then deploys the application.

Same applies here. Uh, when I deploy the, I, I can, with a single code, I can run the entire thing, and it knows the wait for, it's kind of a staggered approach. It has to, it knows that it has to wait for, um, the, um, the, the edge note to come up and the runtime to come up, and then the application to be deployed.

So it, it knows how to queue up, uh, jobs in sequence. And the, the different compose options you were showing, like the small, medium, large, that determines the size of the, I guess it's a virtual machine on the edge node that gets provisioned for running the docker compose apps, correct? Yeah, that defines the sizing.

So the small, medium and large. So if you have a very small edge compute, um, you can deploy the smaller. Now, those are predefined.

However, as you saw, I can clone it and I can edit and even make it smaller, you know, kind of reduces the footprint of the storage, um, you know, even add networks and, and kind of tweak it in a way. Uh, the, the, the, the remaining element that stays consistent is the actual software that we manage in Care Feed. So that would be the op the operating system is gonna run the Docker.

What degree can I, uh, change the size of that, that VM without any downtime? Or does it require, if I want to add a network interface or change the number of CPUs, does that require rebooting all the apps on that node? Um, so you can make those changes.

And then the apps would, uh, kind of go into like a halted state and then kind of, uh, come back online and redeploy. Uh, what, what sort of, um, uh, SDLC capabilities can you support here? This is a powerful deployment and rollback tool, but I'm just wondering, um, uh, if there's anything inherent in the platform or if, or if, uh, it would be a partner or some third party using, uh, using the API to enable that for, for, for developing and, and managing the lifecycle of, of an Edge app.

Um, so that can, you know, that can be a, a, a customer directly doing it from their themselves, their IT department, their developers, um, or, you know, we have partners that are in the ecosystem that are trained and, uh, are fully ready to support, uh, customers and our platform. Um, so we have it covered end to end. And then, uh, we have a very, um, a very talented, uh, customer support team that kind of takes over, um, as the, they go into production.

Um, so they're, you know, full end to end support, either through the ecosystem of partners or, you know, from, uh, our own CX team, which is always involved. Hi, my name's Chris Clark. I'm a, uh, solutions architect, uh, for the data.

I'm based outta Kansas City, and today I'm going to be discussing the Data Edge Kubernetes service, and when you would want to, uh, use it. So that's really what I wanna start with today, is when do you want to use Kubernetes, right? It's, it's very complex.

There's, there's a lot of moving parts that go along with it. And so, uh, really, if, if you look at your stack, is it, uh, a complex application that needs to be to, needs to be managed? Is it a distributed workload that needs to run across multiple nodes?

Do you need a high scalability? Um, then you're probably gonna want to deploy on micro Kubernetes, if not Kubernetes itself. And, uh, one thing I do like about Kubernetes is that it has a very active, uh, community and of developers, uh, around it.

So it's very easy to support. And, uh, there's always new features that are coming out. Now, SATA has our own Kubernetes service built into the platform.

Uh, I'm gonna go through a demo of that here in a minute, but before I do that, I wanted to show you guys just very briefly, the architecture. And the reason is, uh, a, just to let you know all of the, the hard work that went into it, but, uh, b, that, uh, we made, uh, it very simple to use. So while this looks very complex, it's very point and click, create a cluster, deploy an application.

However, if you don't want to use the, the data cloud to, um, interact with that cluster, you can do it directly with your, uh, cube CTL commands. Uh, or you can use Cube CTL via ZA Data Cloud. Uh, and there's, there's a lot of, um, ways to interact with that, whether you're using ZA Data Cloud itself or using the Kubernetes API directly.

So, let's jump over and take a look at how to create a, uh, cluster. So what are you looking at? Here is the ZA Data Cloud, and there's, there's a whole lot that we can do on the left hand side, but we're gonna focus in solely on the, uh, Kubernetes service.

So when I hover over that, you'll see that we have a bunch of different options. We can create clusters from the cluster section. There's a Kubernetes marketplace, uh, section where you could, uh, import applications.

You can see what applications have been deployed. Uh, you can take a look at cluster grouping, and you can even add your Git repositories. Um, so it's really very an all-inclusive system.

Now, the creation of the cluster is quite simple. We click that on notice that we have a number of clusters already created here in the data cloud. I can add new up in the upper right hand side.

We'll just give it a name test, go next, select one of our projects, and from here we select one or then three or more nodes to add into that cluster. So we'll just kind of grab three random nodes there, we'll tell, uh, the, uh, the configuration, which network adapters to use for this particular cluster. Once we do that, we hit next, and then we can finally add it down below.

Now, it will take a couple of minutes to deploy. So in the interest of time, we're gonna just jump right back to the clusters here and utilize one that's already installed this Edge AI cluster. So if we wanted to see additional details, we could actually click into this.

But before we go that deep, I wanna show you the actual application deployment. So here's the Kubernetes marketplace I was talking about a moment ago. Uh, from here, it's very similar to what you, uh, saw with, uh, managed presentation.

Uh, so it's a very streamlined, um, uh, experience between different technologies. So if we wanted to come out down here, we could take a look at something simple like, um, a guest book, right? We could select that, and you'll be presented with all of the options that can be changed.

This is done with the helm chart. We can see all the different versions that are available to us, and we can click install there. Now, if you don't wanna use that, uh, marketplace, and you'd prefer to, uh, use your own helm charts, you can, that can be done, uh, by bringing in your own GI repositories here as a data source.

And we can actually see all of the applications that have are already installed. So we have this Heller World application. If I select that, it's gonna bring up all the information, and we see that there's a service associated with that, uh, of a kind deploy, or excuse me, a service down here, and we have a service count associated with it.

And then we have a, uh, deployment above that. So this is the, the basic functionality of deploying a Kubernetes cluster. It's, as you can see, it's very, very simple.

It's not as, uh, big and complex as, uh, you're probably used to with, uh, Kubernetes clusters. And we can even take this, uh, one step further down into the weeds. We can go back to our cluster and click on it.

And without ever leaving ZA Data Cloud, we can, uh, see all of the details about all of the pods, the services, the storage, the policies. Um, so we wanted to take a look at some events that are occurring. We'll go ahead and click that.

It gets presented here, right in the web ui. We can select those to get additional detail. Maybe we wanna go over here to the workloads, take a look at what CR jobs are running.

Maybe we have a, uh, a pod that, uh, is, uh, thrashing that we wanna, uh, investigate, or we wanna delete one so it gets rebuilt. We could take a look at all of those from here as well. Uh, here's the service discovery section.

Uh, like I said, you can take a look at the, uh, storage. So you have your persistent volumes or storage classes. I mean, this is very, very, uh, all inclusive.

So from the data cloud, you can go from no Kubernetes cluster to your very own Kubernetes cluster in a matter of minutes, and then attach it to your GitHub repo, bring in your own helm charts, deploy applications, and you can start development work, uh, I mean, within 10 minutes. Yeah. Question about, it sounds like you're getting ready to, to offer up q and a there.

Yeah. Um, so quick question on the scale, you know, sometimes when we're thinking about edge clusters, right, we're not thinking very large scale, but I wanted to ask about that. Like, if, if we're thinking of pod scale, can we go up to say half rack of nodes, full rack, multiple racks?

What's the, what are kind of the upper bounds of what we think of that Zaida can do in the, the scale of running a Kubernetes cluster? Um, that's a weird question. I don't have the numbers for that on, on hand, so that, I'll have to answer that offline.

It looks like you can go pretty far, right? If we're just talking about the orchestration side, and like you said, we can bolt it into our current GI ops and Yep. Go from there.

So I'd have to imagine it's pretty high. Yeah, yeah. Over balance there, other than just how much do you wanna manage, right?

Yeah. And really all it's doing is managing the, the, the, the cluster, right? Those VMs that are actually, uh, clustered together.

They're doing all the, the communication back and forth with one another. So there's really not a whole lot of overhead. Uh, so I'd imagine there, yeah, the, uh, the upper limit is, is quite large.

I think that that highlights one of the things about scalability with Edge solutions, it tends to be a very large number of sites each with a relatively limited amount of resource. So you're not right. You, You wouldn't typically have multiple racks in, uh, uh, in each location unless it was somewhere like an oil and gas exploration.

That's the kind of use case where you might have more capacity in that, um, in the crawler that's stood in the geotech stuff. Yeah. Would you, is there, is there an option to even bolt in, like from from a CNI perspective?

Like, can I, can I roll my own CNI in the solution? Or is there something else that is already baked in from a networking perspective? Uh, the, the deployment itself's already baked in from what I understand, but, uh, the, I, the, uh, I have not messed with any of the other CNIs, but it, I think it's baked in from the actual creation of the cluster.

And then you were highlighting, uh, something about, uh, edge Hardware that I really like about this solution is I think that Kubernetes really does a very good job at, uh, complimenting edge hardware because it's super easy to swap in and out new nodes, or add capacity and scalability, uh, with something like this, you know, have evos on there, you know, plug it in, have it check in, add it to a node, and then you have initial capacity, right? So this is a aida, a ZAIDA cluster manager. Um, how, how does this compare?

I mean, I containers is kind of where it's at right now, and edge's, like right, the most active development. Mm-hmm. But I imagine quite possibly the majority of your customers right now are still running PMs mm-hmm.

Whether ESX or kbm mm-hmm. Or acorn. Um, and I'm just wondering how this experience compares if, if, if it's okay to ask that.

Um, and no one's gonna start a religious war with me about it. I'm just wondering, like from a, from, from, from an enterprise standpoint, wherever they're at, they, they're often doing both, right? Um, whether they're moving or not moving, um, from one to the other.

So I'm just wondering how the experience compares, um, if there's multiple pain of class pains of class now, and if that's inevitable. Yeah. So, uh, I, I think that the experience with this Kubernetes piece is, um, much better for developers because they, even though it's being managed by ZA data, they still have the ability to, uh, utilize the tooling that they're, they're used to, right?

So you can have, uh, your, your admins, uh, managing the cluster and the ZA data side, and seeing what data sources that we're, they're allowing to bring Helm charts in from. But the, uh, at the same time, the developers are able to, uh, use their cube, CTL or, or whatever they have integrated with their, uh, their IDs. So, um, you have multiple streams kind of going at once.

Um, right. So I, the experience I think is, is very robust in that regard. Um, when you bring over the, the VMs, uh, from, uh, somewhere else into the data, you, you have to bring 'em in.

It's managed and everything's done inside of here. So, uh, that's a little bit, um, uh, of the contrast between the two, which is why I like this quite a bit. How, how it, uh, allows you to use the tooling that, that you wanna use.

Well, that, that's endemic to, to the platform when it comes to VMs. It's, it's a, I I think it's genuinely a feature of the V of vm and, and that's why it's not really religious war, it's just a question of, uh, right. What you're trying to accomplish.

Mm-hmm. So I think, um, that what we talk to customers that the VMs are a necessary evil for them today and will be for the next few years. 'cause they have invested a lot of IP and some of those applications that are running, uh, on those, um, on those VMs and a number of, in very old versions of window.

So they're looking for the ability to continue to use those. But I think, obviously, um, everything they're doing that's new and future looking, they're trying to containerize. So all their focus is on putting new apps in some cases, um, rewriting existing apps and putting 'em in, in the container, or running them in Kubernetes.

So it's a combination of, we, they want to be able to deploy both types of, uh, runtimes, uh, for the next few years as they migrate from the VM to a, an all Kubernetes or an all container type of, um, architecture. The Kubernetes, um, version and the image, it looks like it's using K three SI, I assume that's correct. Um, correct.

Is that how close to the current version of Kubernetes, do you have burdens available in the marketplace and could someone roll their own instance of Kubernetes and deploy it to the, the cluster nodes if they didn't wanna use the data's version? Yes. The answer is, um, um, the, how close we are to the most current one.

Uh, I think we're one or two versions behind, um, when it comes to rolling their own, yes, they could. And, and there's a, there's a number of different ways we can support, uh, deployment of Kubernetes at the Edge. One obviously is one where we provide kind of a end-to-end management.

The other is where we provide them with the ability to deploy the Kubernetes one time themselves. And that is basically where they get to choose which version of Kubernetes they want to deploy. So that option exists.

Yes. Hey, everyone, if Microsoft can invest in Apple, why can't Nvidia invest in Intel? You're watching Textron Gang.

Hey everyone, happy Friday. Wow, man, this week went like this. It's Friday.

We're happy to have you here at Techstrong Gang with us. We've got a great gang lineup today, including, I hope, a special guest star where we're waiting to fly him in. We in the green room getting makeup or I don't know, something, but, um, I, I mentioned the Nvidia Intel deal.

We're gonna come back to that in our B block today. We're gonna kick things off in our A block with this YouTube versus TikTok angle. Let me introduce you to our gang members today.

I'm really happy to have Fred with No, no hat Fred, no hat Walmart today. Fred, good to see you. Good to be here.

Nice. Thank you. Thank you.

Joining Fred, I is Ann o Alhoa after all this time. Alhoa Award. Ann, good to see you.

Good morning. Nice to See you. Also from our, I guess our Texas contingent, we have two people from Texas, uh, future analyst, uh, visible Impact, uh, CTO Co-founder, guy Curer.

Hey Guy. Hi. Good to be here.

And our man in Silicon Valley, John Schwartz. Hey, John, how's it going? It is busy, busy, busy.

Yep. Uh, absent is our Chief Content officer in Yankee fan, Mike Vard. He's at a harness event today.

So no Noard, no joy of Mudville, uh, though the Yankees did one last night. Anyway, let's jump into stuff. Today we've got this YouTube versus TikTok thing going on, and do you want to, uh, kick us off on that?

Absolutely. There, there's a kind of a mixed basket of things happening this week with the two companies that are in the headlines. Uh, first notably with YouTube, they celebrated their 20th anniversary.

They launched in February, 2005. They announced and signaled that they're leaning into AI with auto editing tools, intelligent product link integration, speech to song conver, uh, conversions. They're really trying to let creators know that they're here for AI tools.

They're still cool, don't forget about them. Uh, and they've also rolled out some additional monetization features, uh, which I think are them trying to emphasize how much they believe they're paying creators. I would love to see the audit on this.

They claim a hundred billion dollars has been paid out to creators since 2021. I, I would love to see someone independently audit that, but I also, I have to wonder what percentage, uh, how how many of those are in the top 5%. Uh, that actually reaps some financial benefits.

But anyway, um, TikTok has also had a kind of big news week because the Trump administration reached a framework, uh, to deal with China to keep TikTok operating in the us, uh, with an investor, Oracle, uh, who seems to be everywhere between this and the open AI stuff. They seem to be everywhere all the time right now. Oracle's having a moment.

Um, but what was not really explicitly announced with the TikTok announcement was whether or not what this means for the intellectual property and the licensing of the algorithms, because the algorithm of TikTok is the secret sauce. And that recommendation engine is the biggest part, I would say, arguably, of the security concerns that people have expressed and why this whole thing happened. It's not really clear yet how separate or neutral that's going to be, uh, the US version of the app.

And how much will bite dance be involved in its development or support? How will the data protections be? There's really a lot unknown.

But in terms of, if you put the statistics of the two companies head to head, TikTok was technically the most downloaded app globally last year with, uh, 700 and I believe 700 million downloads. Uh, their user base is about half of what YouTube's, but they have more engagement time. The average adult in the US spends about an hour on TikTok, whereas they spend about 45 minutes on YouTube a day.

Yikes. Um, but they're both very close in the statistics when it comes to children's viewing times. So their neck and neck and poor Instagram is there with about half the view time.

Uh, they're, they're trailing, but they have a loyal user base. And so what I think is interesting is both platforms are also sort of signaling that long form video is starting to perform better. So I think we're gonna see a shift from all this short form getting into more longer form.

We've seen TikTok try and signal this move. Uh, so there's just a lot happening. Uh, but a lot remains to be seen about this TikTok deal.

And I'm really glad that you brought up the algorithm coverage of this. And I don't think it's unclear at all. What's happened with the algorithm, uh, by dance has maintained control and ownership of the algorithm.

And this new entity, because it's essentially a new entity in the United States is going to license it. Uh, there's very been very little coverage of the algorithm. It's all been, there's been a little bit of political coverage because I really didn't think we were in a company where the president of the United States, uh, starts making business decisions and interfering in commercial transactions where You been, you've been sleeping under a rock.

Actually, I did know that. Uh, we were in that country. I was being, whatever the word is, sardonic, there's been some coverage of that.

But here's the thing. TikTok has been operating illegally, thanks to said, president of the United States and the current administration for nine months now. And the United States, it was banned that ban by, by Congress.

That ban was upheld by the Supreme Court and, um, the executive branch of the United States and the president who is supposed to, whatever the constitutional words are, take care to faithfully execute the laws of the United States, has not been doing that at all. But why was TikTok banned? The algorithm is why it was banned.

The algorithm, the influence it provides, and the algorithm remains under the ownership of by Ance, which is a company like every Chinese based company that is partially controlled, if not essentially veto controlled by the Chinese government and the Chinese Communist Party. So that to me is really the story here, uh, more than the corruption and government interference and paybacks and all that other kind of crap, because we've seen that maybe for the hundredth time already. So the new news to me, and the main news, um, which John, uh, you missed in your story, um, uh, maybe understandably so, otherwise it was an excellent roundup, um, is the fact that the algorithm and the reason for the fan, it remains, you know, uh, uh, uh, continues.

And in fact, China will continue essentially endorsed Yes, It'll continue to exert their influence through the licensing of the algorithm through intellectual property arrangements. That is very clear to me. It hasn't been explicitly denied, but I think we all know what that means.

We can read between the lines. So Ann, you make a great point there. You know, for all the talk about the videos and the length of videos, the real secret source of TikTok was that algorithm and the fact that we haven't done anything to take it out of the Chinese Communist party's hands is to me, a perfect indication of taco, our taco presidency, right?

Because we talk a good game. And then at the end of the day, we, we bring in one of our chosen oligarchy friends who are going to make mint money off of it. And we let people go about doing whatever they were doing before, in this case, the, the chosen oligarch is Larry Ellison, who's now worth over $400 billion.

We're going Oracle stock going up like 34% or something this past week. And I'm going to get into that in a second. But, and, and it's, and it's not just Larry Allison, it's his son too.

'cause he, he bankrolled his gun, I think it's called Skydance or whatever, the company that bought Paramount and his, you know, and of course that was, that had to get approval from the FTC, wink Wink who, how do you get approval today? We we're seeing it play out. Um, there's talk about them putting in a, a, a, uh, a, uh, a bid for NBC universal Discovery or whatever that entity is called these days.

Warn Warner Brother Warner Brothers, Warner Brothers discovery. By the way, this is why they, you know, Stephen did a lot of people say this is why they, they sacrificed Stephen Colbert at the, at the altar of this deal, that Ellison maneuvered. And let's talk about Larry Ellison and the recent runup of Oracle stock.

Right? What a great deal this is, you want to talk this, this JP Morgan and the robber barons themselves would be proud about this deal. Oracle stock bounced 34% up, or th more than that based upon their $300 billion deal with OpenAI.

They're selling open ai, GPUs and data center, supposedly for $300 billion. Where Open AI is getting that $300 billion from is another story. Right?

Maybe they could go public, maybe they can't. That's, that's their, that's their plan. No, but let me tell you where it's coming from.

'cause at the same time, Ellison goes in and invest in open ai, they take that money that he's investing in open AI to give it to Oracle, which boosts Oracle stock. So Ellison gets more money, invests more of it in open ai. Theyve, they buy more Oracle stuff.

Oracle stock goes, but more Ellison gets more money, invest more in open air. Look, this would make jp, it's a, and the Vanderbilts proud. You know, there was a video last night from the state dinner in, uh, London or England, uh, England with the, the Trump visit and on, and they had a video, uh, showing some folks in the crowd.

And there you saw Jensen, Sam Altman, uh, Tim Cook, Blackstone, CEO, and you know, is It any different than when the gas and oil guys sit around Vlad Putin? Oh, Yeah. It Thing, it's like the Godfather.

It's the same you thing. You know, you sit Around the table and you, you carve up the empires, you carve up the business Guy. I know you have feelings about this.

Do you want to contribute? Uh, well, I mean, after my rant about, about the algorithm, I just, I do think that this is almost more a political and social story than anything else. That, that, uh, the algorithm is the thing.

And it's even worse than you say, Alan, because that story is buried. It's, it's not even really buried. It's just, you know, what people are looking at.

If they're looking at it critically, they're looking at it as the, the, the continuation of the oligarchy. And here's how businesses fall in line, and here's how, you know, a a, a government exerts pressure to, to, you know, uh, affect, you know, business decisions and all that other sort of stuff. Instead of this thing of like the whole, the whole ball game was influence of consumers of media through these algorithms whose sole purpose may be commercial to keep people stuck on the screen, but whose social effects are great.

No, no. But there was an insidious, more insidious part of it, which was the Chinese communist Party was getting all this information on people. I'm Just generalizing it.

I'm just saying, even if you, like, like, let's say for example, meta is not particularly interested. They're just interested in being huge and making money and spreading around the world and being even more powerful in that sense. Not, not a political, uh, uh, agenda, but the, the YouTube al algorithms do the same, actually.

So we can move to Google. All the algorithms have been designed intentionally to keep people stuck on the screens and the, and, and scrolling. It's trying to be more documented that the way you do that is with outrage and with feeding conspiracies and like things like that.

And, and, and Radicalizing people. Yes. Exactly.

Let's Jump to people other silos. Yeah. I to give Ian a chance, Anne, we're coming back to you.

Go ahead. I mean, I don't trust China, but I trust China to be China and I, I don't think this deal, and I think we're all agreeing this deal has no, it's all facade, Right? It stopped, stopped being about China.

Hey, we Solved this, we solved the TikTok guys like, yeah, Mo, and, and the thing is, the average American consumer does not care. They don't Care. Fist bump, and let's move on.

That, that, that's exactly what it is, unfortunately. And that's the world we live in. That's the world we live in.

It's, it's, they Don't care how the meatloaf gets made. They want their funny videos. People wanna buy the product.

The influencers wearing this is, this is where we've shifted as a society, and we can, we can cry about it. Or we, we can, as leaders in technology say, okay, let's, let's try and teach people how to responsibly use these platforms. This is why I've been on TV 95 times.

I go on to educate people about how to curate their information diets, how to avoid social media addiction. So all we can do is educate people, which is what we're doing right here. You know, I, I read an interesting, uh, story.

I, I'm remembering if it was Finland or Norway, where they're doing like mandatory education of kids about, you know, using social media responsibly, separating conspiracy and craziness from facts. Uh, you know, and, and it, It sounds like Finland to me. And to be fair, I'm finished.

Yeah, my fathers from Finland, but, Okay, so Finish The whole time. That's when we got Al Hoa, I remember, but a hula, but no, aah, but a hula. But they're doing it there and it works.

That's the point. It works Well there. The society have prioritized truths over lies.

They, they are not looking for truth, a novel Lies, Which is what the US does. Can I throw a, so hang On, let's, let's throw that The last word. Go, Fred.

Can I throw a little dissenting, uh, o opinion on this? Uh, sure. So, so I appreciate the context and also the color given the current political environment we live in.

But there's also an opportunity here to reshape the, they they can license the algorithm they choose to. I don't, I don't know if there's enough details. I'm, I'm anxious to hear today what happens, uh, in the conversation with, with China to, to ferret this out.

But I mean, even if you've licensed the algorithm for a year to figure out the, both the trend and behavior, the US has been very broad breaching in the sense that all of any US company and the reach of any US company globally for folks that access or utilize that company also have the ability to go get all the data. So, you know, if, if I were sitting in a chair thinking three years out and I thought, Hmm, I don't have this algorithm. I want this algorithm.

This is a great opportunity to gimme a licensing opportunity and access to 170 million people using it. I could probably figure this out. And in addition to that, I can also revoke the license in a year and roll our own thing.

I can also start to customize the way and the behavior that people utilize the app for the current things they do today. So there is a possibility here that there is something larger at scale. I, I, I don't disagree with the assertions you guys are making, but I, I would hope that there's an opportunity here where we can take you know this and turn it into something broader.

Uh, it's certainly a big enough deal that we should, Well, but Fred, that's an excellent point. And here's the thing. You know what, what was the company Windsurfer or something?

They licensed their IP and everyone said, oh, they, what's left of the company? They licensed the ip and then, then they got sold a couple days later because there was more. Because what happens, Fred, and we don't know the particulars.

You're right, maybe they licensed this algorithm as it exists today, and now you could go do what you want using this algorithm, but in the meantime, the Chinese are gonna continue to develop that algorithm and make it better. And I don't ne you don't necessarily get a license to the next versions of it, right? Um, you get, you get licensed to version two, but as I come out with version 3, 4, 5, and six, you don't have that.

Yeah. So the curious thing is whether or not we top the tree here and I think that's what, yeah, that's what's gonna be intriguing to see happen. Absolutely.

Alright, we spent a lot of time on this one. We're going come back to our, uh, b block, the Intel Nvidia deal. Maybe we'll have a special guest you're watching Text Gang Discover Textron Group, the epicenter of tech innovation.

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Hey everyone, welcome back. Hey, I promised you a, uh, a special guest for today. And, you know, sometimes it works out.

I was able to grab a couple of minutes of Daniel Newman's time Fu, CEO here, and, and he's kind of, uh, much more of an expert than I am on what goes on in the semiconductor space and markets and everything else. Daniel, welcome to the gang again. It's great to have you on.

How's everything? Good morning. It's been busy since 4:00 AM Pacific time here.

Uh, some big announcements today. Yeah. But, uh, in this AI cycle, there really is no safe, slow weeks.

Even the ones you think aren't gonna be busy seem to end up busy. And so all, all, well, Alan, thanks for having me. A pleasure.

So guys, look, the big news Daniel's referring to, of course, is Nvidia taking a stake about a 4% stake in Intel for a mere $5 billion, 4%, 5 billion, sounds like a bargain. Um, you know, I, as I teased in the opening to today's show, it reminded me sort of where Microsoft invested in Apple, because, you know, back then they did it so that they wouldn't be an M word, right? They, well, they were an M word Microsoft, but they didn't wanna be the other M word monopoly.

And so by propping up Apple, they had a viable competitor, not the case here. Daniel, I'm gonna ask you to kick it off. What do, what's your take on this deal?

Well, there's two parts to the deal. There's the investment part, and then of course there's the technology partnership. There's a commitment between the two companies to build, uh, it's, you know, a chip design that's going to sit on the, you know, on the X 86 system that's going to basically enable NV link, uh, and data center designs.

And then on the RTX designs, basically C-P-U-G-P-U connectivity in these future A IPC designs. So it's an interesting one because there's like all these different moving pieces. First of all, um, this was a very defensive move by Nvidia, as ARM has been pretty vocal that it is planning to enter the AI and custom AI chip space.

Uh, it corners a MD because ad's had a ton of success with their data center CPUs and their A MD Epic CPUs with NVIDIA has been a popular combination. So, you know, accelerating, uh, NV link versus PCIE is going to give some advantages to an Intel Nvidia solution. And then of course, um, you know, Nvidia also knows that at some point it might may want to take advantage of Intel's foundry capacity, and this investment is gonna give it some merit there.

And it's also gonna give it, uh, a bit of a boost. We saw a 30 ish percent bump in the stock. So for Nvidia, it wasn't a big, it wasn't really all that big of a risk.

There are five billions already worth seven and a half. Uh, they made money instantaneously. So, and, and there's one other thing, and no one's gonna probably, you know, be as fast to say this as I will here, but, uh, it probably doesn't hurt Jenssen's relationship with President Trump that he's now backing the US chip champion and the US Foundry champion that they want to annoy.

So there's a lot of winning here. Um, for all the players, it's, it props up intel, which is, it needs, it basically corners its competition and it's going to drive a, in, in my opinion, uh, a significant cycle, uh, and market, uh, growth run for Intel that it's direly needed for some time. Absolutely.

But, you Know, you, I think it's really interesting. Uh, go ahead guy. Dan, I think it's really interesting, Daniel, that you mentioned the, the stock price and the stock bump.

'cause that was one of the things I noticed about it. What do you think about the fact that, um, Nvidia was able to buy the Intel stock, you know, at market rate? 'cause normally with these kinds of investment, there's at least a little bit of a bump incentive, but in this case, I didn't see that.

Well, these investments at these size actually often come at a discount. Yeah. And, uh, if you remember the us, they were able to buy at a discount when, uh, SoftBank came in.

They were buying at a discount. But you realize now you have something over 10% of the companies now held by Nvidia, SoftBank and the US government government. So closer To 20%, No, it's like 12, right?

It's something Like, well, no, the US government has 10% itself. Okay, so it's ten five And then you got 4% to Nvidia 16%. So it's, it's about 16%.

Mm-hmm. Um, and of course it's king making, you know, it's been anointed, you know, people can argue, do we want truly free markets or not? Uh, but now that it's been sort of decided at the administration level that Intel needs to succeed, I think this is a bit of a wave.

SoftBank saw the wave and that's why I said I, I wouldn't be surprised to see an arm, uh, an Intel Foundry relationship. Now, Nvidia is doing the same thing. I can see some, you know, pressures coming in the long run from tariff and tax.

So there's kind of the two sides, like the technology partnership's really interesting 'cause the technology is going to create more powerful, more efficient, uh, PCs and data center designs that are going to encompass smarter networking in the, you know, in the, in the infrastructure itself. But like I said, on the other side, I think there was a bit of a chess move here for the longer term to give the company some leverage. And like I said, it, it puts in, it puts a arm in a bit of a corner.

'cause arm's now gonna have to make its run at its AI business, and it's going to probably limit the grace part of the, uh, Grace Black Wall Grace Hopper, because now they're gonna have a competitive alternative. And I think it really corners a MD because I so that, that, that's my point. Well, yeah, so Daniel, you spoke about the winners, those are the losers, right?

A MD has been playing a second fiddle to Intel for as long as I can remember, and this sort of locks them into second fiddle. They're, they're kind of shut out on this. What about TSMC?

Right. Well, first of all, a MD was always and always has been and has been pretty happy being a strong number two and strong by like tiny market share. I mean, realistically, like it's in, in, they've had a real growth though in CPU, which is why this is most influential is their data center.

CCP has done well, and especially in cloud and especially so, so it's interesting there because the company is gonna have to react to that. Well, this Is a board Now started making NVIDIA's making an X 86 champion now. So they're picking a winner in X 86.

Um, tsmc, I, I mean, look, that's the number one name on our AI 15 future of equities name. Um, it's, it's an absolute monopoly. You said that M word in the last block you were talking about, uh, Microsoft and or you said that about Microsoft Apple, which I also had that common, you know, lip Booo is no Steve Jobs, but there is a feeling of this sort of re you know, revival that's being put into place to enable, um, Intel to be successful.

And I think it's to NVIDIA's benefit and you know, that, that Intel does succeed. Um, but you know, I think TSMC has so much leverage because between Apple, Nvidia, A MD, Broadcom, Qualcomm, um, they get so much volume. They have complete pricing control to some extent.

This could be Nvidia, you know, who's kind of had to take whatever TSMC gives them price wise and saying, look, we want to send a bit of a signal that like we are the king. You're not the king. And and like I said, I think Jenssen's doing that a lot these days.

It's the way he postures about China. It's the way he, uh, you know, it's the way he sort of, uh, you know, decides to law at a certain OEM versus another one. OEM has, you know, a partnership with a MD and another's all in on Nvidia.

You'll hear Jensen say, go this company, not that. So he's using his, his power, even picking neo clouds, you know, they're investing in core weave. They're, you know, they're picking which companies going to get the, the, the volume.

So, you know, when you have a, you know, five growing towards $5 trillion company, and you have the type of balance sheet, I mean, five billion's rounding here for them right now. Yeah, I know this was a small, small investment. Let me talk about another potential loser here.

And that's the market, the market in general. You know, I saw an old video clip of Ronald Reagan that bleeding heart liberal talking about tariffs and co government protection of companies that initially it makes it sound like you are propping up intel and you're making Intel stronger. But in the long run is, is Intel gonna be in, in this sort of false bubble of competitiveness because of the government investment?

Because the gover, you know, the government has anointed them as a, as a favorite. And so Nvidia invested with them and arm invest with them, all the curry favor here in the government, but as a result, Intel's not truly competing in the world marketplace. Right.

And and does the market in general suffer? Yeah, I, I, I, I think you, and I'll have a hard time finding common ground on this one. Um, foundry is just so hard, Alan, that, you know, there's certain things that I think the point is, you don't want government intervening the problem.

And the reason TSMC has so much asymmetric power is because what they do, it's kind like as ML with, with ev, no one can do what they do. So they have the ultimate power and control over the market. TSMC is the same situation.

So, you know, we have an issue, and this is a, there's a lot of geopolitics at play here with, um, with TC. Like they're making these hundreds of billions of investment in the us which is great. That's part of the goal of all this posturing and, and, and, and fighting and taring that we're doing is to bring more manufacturing here.

Problem is they're not gonna bring their leading IP here. And so if the China Taiwan thing ends up becoming escalated and China invaded Taiwan, for instance, and they, all of the leading edge intellectual property sits in Taiwan, they're not sending their best people here. So they bring the, the technology here, but they leave the innovation and RD back there.

And so we would basically be stuck on whatever node that would be at at that time, if there was some conflict or war or escalation in the us Unfortunately doesn't, didn't have. Now again, whether Intel and its 18 a 14 A, these are the next generation chips, these are the competitive nodes, these are the future. And the US needs to bring the talent, they need the ip.

This is what we're leveraging, this is what we're bargaining for. This is the fight that we're having is, you know, the US provides, uh, national security to Taiwan. And Taiwan provides us, uh, the capacity in manufacturing and leading edge chips.

So the question is, Alan, do we wanna solve that problem? And so, 'cause right now, the only company that could solve that problem, and they have not succeeded yet, they have not been able to get the yield, they have not been able to, to get the, the confidence. So there is a bit of king making in the sense of the US wanting to force the hands of companies like Nvidia or a MD or Broadcom to use Intel boundary.

But most of them are fighting that. But at the same time, I think they're fighting it now, but they're saying we're willing to invest to help them get there because we don't wanna be completely beholden to not just Taiwan, 'cause Taiwan's our ally. They don't wanna be beholden to, to the potential risks associated with an ongoing Conflict with China.

Right? Taiwan's an ally, but it's, but it's a risky ally is what, what it comes down to. Oh no, there's Oracle, Larry, Larry has $400 billion.

He's sitting on himself. Why would an Oracle invest in this? Again, you've got SoftBank, you've got the US government, you've got Nvidia.

This might actually become a bit of a, of a, of a, of a train in, in ways where you're gonna see, uh, Hokan make a commitment. You're gonna see Lisa Sue make a commitment. You know, at last year, Intel AD announced a partnership on X 86 of co-development.

I mean, we are not beyond the point where every one of the fabulous companies could be basically brought in a room beaten over the head by, by Secretary Lutnick to, and again, I'm not saying this is right, I'm just saying this is probably what is going to happen. But what is right is to make sure the US can continue to innovate and build leading edge chips without being a hundred percent dependent on any other country. So that solving, I just, is this the answer?

It's the best option that we've had. That's, No, it's the leading option out there. You always want an option B and C.

There is, we hope we we look at that. But Guy, you, you and Daniel, I gotta respect your time. Last question.

Go ahead, guy. Well, I wanted to add one, one technical, technological, technical element to this too as well. Daniel and, and, and, and team, which is software.

Um, A MD is, uh, roughly behind when it comes to enabling software. Nvidia is the clear leader in software for AI development, uh, and GP usage. Intel also has been the clear leader.

These companies have invested for years in top flight software platforms for development on their chips. And I think that that will bring the m word back. You're creating a semi monopoly here, um, to enable the market to use this, this tighter combination of chips.

I don't know if you have any thoughts on that, Daniel, but that's, well, that, that is something that I don't think has been as heavily covered. 'cause it's, it's more technical. It's more about development of the applications.

The, I think a lot hardware, lot of people, yeah, a lot of people understand guy that NVIDIA's Cuda for training development is certainly has a ton of lock in. I think there's also a lot of people that believe this inference era that's coming is going to, uh, obstruct away some of the complexity. 'cause the need for software is different.

Um, but yeah, I mean, look there, the lack of ability for Rocko to truly dent the Cuda moat has been a big slowdown. And I mean, I've been the most vocal that AMD's lack of like, clarity on how much growth they see coming from their instinct and their GPU business, uh, while NVIDIA's, you know, in the hundreds of billions. And our forecast says 583 billion of AI chips, uh, AI data center infrastructure chips, uh, by the end of 2029.

And, you know, NVIDIA's gonna have like almost 400 billion of that at this rate if, if a MD can't make it dent. So, and then Broadcom became the big number two by their custom business being so ed, the In. Sure.

Yeah. It's a, it's exciting. It's interesting.

And I mean, it was a great moment for, for Intel for those, uh, that have been, um, you know, in on Intel as an investor or just those that were rooting for Intel because it's been a really, really dark ride for some time. So Nvidia did definitely give it a, a lifeline here. I, I think, I think Intel, the prospects there are better than they've been maybe since the Pentium.

But, um, anyway, Hey, Daniel, I gotta respect your time. I know you've got a lot of, you're gonna, I'm sure be on all the Fox business news and Yahoos and CNBCs, but remember he was on here first today. Thank you, Daniel.

We'll see you soon. We're gonna take a break here on the gang. We'll come back.

We've got more to go. com is the leading resource for news analysis and education on challenges facing the cybersecurity industry. com covers all aspects of cybersecurity, including data security, DevSecOps, cloud security, application security, network security, security threats, and more.

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Home of security bloggers network. Hey everyone, we're back here, ch we're gonna go into our C block Friday, so this is our last block of the week. We'll try to end it on a, on a high note.

Uh, this block is about AI agents go shopping, isn't it? Every person's dream to have an an agent that would go out and do shopping for you, people would pay people to do this for them. Guy, what, what's this one about?

Well, it's definitely my dream. I mean, this is great. I think actually, like, so uncharacteristically, I, I, I think this is terrific.

I'm not really seeing downsides. I would like to hear about downsides, but I will say that, that, that there's a certain assumption here, sort of along the lines of what Fred said at the, the start of the show about, Hey, listen, you know, we're all going all negative on, on the TikTok algorithm and licensing and stuff. And he pointed out like, licensing doesn't necessarily last forever.

Um, in the same way that that is a, that's an optimistic way to look at that. And I optimistic, look, look at this as there's just simply no way that AI shopping will do that thing that you would fear of it buys a whole bunch of stuff and you have no way out of it, and you don't want the stuff, and you spend money and you're, you know, I just, I can't see that happening. There's a lot of deregulation of lack of regulation in commerce in the United States, at least these days, um, in various ways and lacks lacks of co consumer protection and that sort of thing.

But the, the market simply would not stand, um, AI agents buying stuff for you without, you know, Google is, is very helpfully and visa as well. They're very helpfully talking about transparency here. Transparency is a good start.

But ultimately you need to be protected such that an AI agent doing something for you, um, remains under your control and your ability to, um, easily and quickly, uh, return what's been bought or cancel an order or whatever else it is. This is just great. I can just go through my life and maybe groceries will be shopped for, for me, and I can, you know, keep feedback, keep my feedback loop to the agents so that it, uh, only buys peaches of a certain shape or color or whatever it's gonna be that I happen to like.

So this is one of these ways where our, our lives are gonna be improved. I will note one thing, which is that they will probably, our lives will probably be more improved with the more affluent or wealthier higher class or higher tier you are. Um, but hey, there's nothing new there that's already going on on This Is America baby, right?

That's America. That's America. I take, that's the world.

Ain't even just America. Fred. Fred, you're our security expert.

What could go wrong here? What could be bad? I Have a feeling Mc p's gonna get mentioned.

Yeah, I'm actually gonna leave MCP out of this for a second. Oh, and the cool part about this is it operates with MCP and A two A, right? Mm-hmm.

So there's an opportunity to incorporate this into every payment processing exercise you go through some of the cool things I think about here. Um, I mean, how many times did you wait in line at Ticketmaster to never get the tickets you wanted? How many times do bots from, you know, uh, uh, people that get those tickets and then the scalpers resell them for some ridiculous amount, right?

It takes a lot of this sort of secondary marketplace out, and it reduces a lot of fraud. So what you get is you get the shopping agent, you get a merchant agent like you have today. You get a, you know, a, a a retailer that you buy something from, and you got a p person that's buying stuff, I want to get tickets, or I want to attract this particular airline flight, and I'm not gonna sit there all day and do it, and my bot isn't doing it for me.

And then you have a credential provider and a merchant processor, right? Same thing that you have today. Visa might be a, you know, a merchant processor, so obviously they're gonna get on board with this.

And then you have a networking issuer. So the challenge we have today, right? When you think about card not present transactions, there's still a ton of fraud that happens here.

And what if you thought about the vehicle for something like this? There's inherently a chain of the transaction, every single transaction that happens from, you know, the shopping agent to the merchant agent, and it is provided to both. So on the transparency, super good, you've got authorization, you've got authenticity, and you've got accountability.

It's super, super powerful. And you've got 60 member organizations that are looking to utilize this in the same way that originally Visa's early warning, and the whole Visa network part wa was aligned there. Now, to Anne's point, okay, if you took that moment and said, okay, well let's incorporate this into everybody's insecure use of MCP, well, you know, you have some opportunities there where this can possibly go wrong, but the question will be, how much of that fraudulent behavior is lawn transactional?

How much of that will we not see? How much of that is something that we can't also relegate to certain users that as visa's done over the years, you're either a member bank or you're a non-member bank, you're either a member of this organization or not. And if you, you know, can't securely transact, then you're gonna get kicked out of it.

So ultimately, today it's a payment processing problem and a percentage and all the things that we look at for the rate of fraud. So four to 6% of fraud, you know, for mass compromise and these other things, point of sale transaction stuff, this is probably going to reduce that to a much smaller number, and it's gonna make the American buyer so much more empowered to do the right thing with the money. They don't have to call up their bank and argue about whether or not that's a legitimate charge.

I think it's awesome. Yeah, I mean, I, I love the optimism from both of you guys, uh, but I think we can agree that AI agents are an attractive target for cyber criminals. I think, I think that the exciting thing for me in this, all of this is the, you know, visa signaling, yes, we're using MCP because I love MCP, I'm hawkish on it.

Um, but I think the value is that Visa is positioning themselves as the transaction trust layer, right? So they're providing all of that security to this. So the hope is that this might be a good test case for other payment gateways, um, to expand their AI driven commerce, which sounds great in theory, but I'm just very, I'm very skeptical.

Well, I think the thing that this does actually may be counter to what you suggest. I think this may be the thing that breaks visa's halt on the universe of payment process. And for that, right?

I'm thrill. Uh, so imagine that a smaller bank, right, has the same leverage and legitimacy to conduct transactions. Regional banks, uh, organizationally have the same level of credibility, you know, as a visa.

I think this could really change the playing field on the security side. I mean, there's a lot of concerns about what that introduces, but if you look at the conduit of what A two P provides and AP two will authorize, then I think there's a lot of really important use cases around, you know, how that gets leveraged in genic behavior. And, and some of those simple use cases are like, Hey, man, look like, I don't wanna like wait in line for stuff.

I don't want to have to track the price of the availability. John Doesn't wanna wait in line for his Taylor Swift tickets. I, I mean, who does, if I want to go see Taytay, I want, I, I want access, and I don't wanna get denied my daughter.

I called Travis directly. Let, let, lemme throw little red meat. Lemme throw a little red meat.

They live, You know, they, they were living here in Boca, by the way, but Yeah, let, lemme throw a little red meat at Allen. So, so I think Visa's involvement here and Visa, uh, offering MCP services is a really interesting development. Maybe encouraging why?

Because US law dating from the seventies protects consumers against credit card fraud and theft by holding the credit card companies and the, and the participating banks responsible. And the result of that has been, I think, a little bit visa's monopoly on transac or, or, you know, uh, uh, dominance of transactions because they help solve the problem. I don't remember the economic turns offhand right now, but you know, it becomes a collective problem.

It's like insurance, like gets shared across many, many organizations of fraud and crime and everything, and the cost. So the consumers don't bear the cost, the card issuers bear the cost, right? And so now here is a new lever and mechanism, a commercial one potentially, I'm not saying certainly for helping solve the MCP and prompt injection and all those other kind of problems, security problems around ai.

And that gives this a greater, uh, uh, potential, um, beneficial impact outside of just e-commerce and transactions. And Alan, it is all because of this regulation of an industry imposed in the seventies, that kind of regulation that we seem to be unable to impose anymore. That's my red meat for you, Ain't it?

The truth, ain't it The truth. Hey guys, we are, we're over time, but we had a busy, it was a busy show. It's the end of the week, so we're gonna, we'll end it right here.

Um, and Guy Fred, John, as always, thank you. Thank you to Daniel for popping in. Thank you for watching.

It's been a great, I I had a lot of fun this week on the Gang. If you, if you can catch some of our earlier shows this week, go back and check them out on our YouTube TV channel or techron, uh, TV or our Tech strong TV app, OTT app for Apple or iOS and Amazon and Fire, Amazon Fire Roku, and Google Play. Um, have a great weekend everyone.

We've got techron TV following this, so you'll be able to see that as well. And, uh, we'll pick it up on Monday. Until then, there's Alan Hummel, we're out.

Hey everyone. Alan Shimel here. We're back at Techron tv.

I'm happy to have my next guest back on here. I don't know if you'll remember him from the last time he is on, but not to worry. I'll give you his name.

It's Gary Bartlett. Gary Bartlett is public sector CTO for Illumio, the microsegmentation people. And well, and more than that, that's when they first started.

But anyway, Hey Gary, welcome back. How you been Doing? Great.

Thanks for having me back, Alan. Appreciate it. I appreciate having you on.

We were talking off camera a bit. We didn't get a chance to hook up. You missed Black hat this year.

I did. Unfortunately, I had a, uh, uh, conflict that just prevented me from being there this year. Well, I could give you the load down, but you didn't miss a heck of a lie.

It was just another black hat. Um, on other news, RSA is earlier this year, uh, you know, speaking, uh, uh, the speaking session submissions are closed. I expect that'll be coming out soon, but maybe we'll see you there.

Yeah, definitely. We'll be at RSA this year. Very cool.

So Gary, before we get into Illumio, and we're gonna talk a little salt typhoon and stuff like that, give people a, i I remember your background, but you know, not everyone out here does give people a little sense of your background. Sure. Well, as you mentioned, I'm the public sector CTO here at Illumio, uh, about three and a half years now.

Uh, prior to joining Illumio, I was the, uh, CIO at the office of the Inspector General for the United States Postal Service. Uh, so I served as a Fed CIO for just shy of 10 years, right. At 10 years.

Um, and before that I was a cyberspace operations officer in the Air Force. Did that for a short 20 years, A short 20 As opposed to a long 20, right? Yeah, I get you.

I, uh, you know, I'll tell you, when one of the companies I had helped co-fund still secure, we did a lot of work with DOD and some of the agencies, and we did some bit of work with the Air Force. We were out in Colorado. So it was a lot of bases out that way.

A lot of bases out there. Yeah. And, um, oh, that, look, the Air Force had it going on, right?

It was, And they still do, they're still in, in my opinion, leading the DOD as far as zero trust and, and those types of things. Not that the other services are lagging, uh, but you know, I'm, I'm a little, I'm a little partial, right? I can't, I can't claim to be completely impartial.

So yeah, maybe there's a little bit of blue tinted lenses there that are, that are affecting my outlook. Well, we, we gotta get out of the, calling it the DOD now, right? It's not the, the DW or whatever it Department of War now, right?

Yeah. Let's not go there. Um, so Gary, let's talk a little bit about Illumio.

You know, a little tongue in cheek. I said the microsegmentation company, but not so tongue in cheek. It is kind of what Illumio does at its heart, right?

Uh, is, is, you know, kinda Absolutely. So, so, yeah. And we, we really look, uh, view ourselves as the breach containment company, right?

Mm-hmm. So we're all about doing a couple of things. Number one, uh, given our customers, uh, really granular visibility of what's actually going on on their enterprise, uh, specifically when you're talking about application to application communications, uh, looking at how things are actually, uh, communicating and how they're interconnected, um, from a net, from a network agnostic perspective.

And by that I mean that we look at, we look at enterprises the same way that adversaries look at enterprises. When an adversary comes in and starts trying to map out your enterprise, they're not really interested in the routers and switches part of it. They're interested in what devices can talk to which effort, which, which other devices, right?

It doesn't matter if they're in the same rack and the same data center or on opposite sides of the world. If they can talk to each other, that's what adversaries care about, right? That lateral Lu and be able to compromise one box, and then where can I go from here?

You know, what other devices can I touch? They don't care how those things are communicating. Uh, they care that they are communicating with each other.

And that's what we do, is we provide our customers with visibility that they can actually see that. Um, it helps, uh, like security teams and CISOs, uh, be able to really understand and start to map attack vectors and shut down attack vectors. And that's where the segmentation piece comes in, is really being able to start to isolate things and shut down a lot of unnecessary communications that are in place on most enterprises that really don't need to be there.

And they're nothing but an open avenue, uh, for adversaries. Absolutely. Absolutely.

com. Yes, sir. Thank you.

Okay. Let me kinda switch gears a little bit here. And we're gonna talk kinda public sector security, public sector cyber, if you will.

Um, you know, salt Typhoon is, uh, you Ms. Black Hat. They had all kinds of robots that were projecting to be soul typhoon and, and all of this stuff.

There was a lot of soul typhoon going on there, but clearly this is something that targeted our government though. It, it wasn't just the government, right? But, you know, not everyone on our audience is a security expert as we've got DevOps people and Cloud native for those.

Maybe let's start here. For those who don't know sa Typhoon, what, when we say sa Typhoon, what are we talking about? Sure.

So, SA Typhoon is a, is a name for a, uh, series of attacks that were attributed back to China, back to the, uh, uh, intelligence sector of, of the Chinese government. Uh, and it was primarily, as you mentioned, right? Targeted towards, um, governmental, uh, you know, department of Defense, department of War, uh, entities.

Um, they went after the telecoms. That's where they were first discovered, is going after the telecoms, the, the, all the big telecommunications, uh, uh, companies. Uh, and people were like, well, what does that have to do with DOD?

Well, they were specifically going after, uh, you know, government officials, right? They were, they were literally looking for conversations, relationships, locations, identity information of government officials, right? And looking to get access to where were they, what were they talking about?

Who were they talking to? Um, you know, so it was, it was very, from a, from a national perspective, um, it was quite the, you know, quite the effort, uh, to, to attribute to the Chinese government that they were going after civilian companies that obviously are supporting the government, uh, and, and using them as a target of opportunity to get to, to try to compromise or get information about our government officials. Um, and then it expanded into, uh, going after National Guard units, um, state local governments have, have been affected.

Uh, so it's been a very widespread campaign, uh, of, of espionage. I mean, there's no other way to, no, no other word for it other than it was, is literally espionage of going in and looking for what information could be stolen. Uh, and then, you know, you, you can talk about what they do with it once they steal it, but that's really, it was about targeting, uh, companies to steal information.

So, let me say, I, I have been in the cyber world a long time, and this is though the name Soul Typhoon may be relatively new. This behavior is not, you know, I remember, oh, it's gotta be almost 20 years ago, maybe 18 years ago, uh, one of the companies I helped found were NAC Network Access Control. Yes, sir.

And so we had the ability to kind of quarantine any devices coming on the network, test them, make sure they, you know, met a, you know, golden sort of config rule. Well, we could, we could test them for anything you want to tell you truth, right? And then if they did, put 'em on the network, if not, keep 'em off the network or put 'em on a guest thing or whatever.

And I remember we got a call from SEC D'S office one day and said, can you check, can you check to see if the USB ports are enabled on laptops? I said, yeah, it shouldn't be too hard, but why would you want 'em all disabled? How are you gonna get stuff on and off?

They said, well, don't worry about that. We just wanna make sure they're disabled. You know?

And then a couple years later, of course, we all, most of us in the cyber arena know there was this campaign of people just threw USB thumb drives in the parking lot at the Pentagon, right. And how many people were silly enough to pick 'em up and plug them in their, in their machines, and thereby give access some claim. You know, the, the plans for the stealth fighter that China, China's first gen stealth fighters, Right?

Airplanes. Yeah. Um, were, yeah, I was on, I was actually on the Air Force CIO staff when that happened.

Um, and it was quite the, uh, uh, it was quite the event to deal with, uh, and, and to try to figure out, you know, how to deal with it. And, and, and like you said, it was a very, um, widespread attack, uh, that was executed in, in a way that people weren't thinking about, uh, necessarily. Uh, and unfortunately, you know, that continues today.

Right. You know, you know, that's where we always talk about the fact that, you know, the adversaries are always gonna be ahead of the defenders, right? They, they're, they're just, they can be more creative.

They can, they can think of ways around defenses. Uh, you know, it's just, it's, it's always gonna be an ongoing cat and mouse game, unfortunately. Agreed.

Agreed. It, you know, it's enough to make security pros depressed. Hello, babe.

Yeah, Gary, I, I, I feel like compelled to draw a distinction though. You know, there are nation state actors, I think, which is the case in Soul Tai food. It's really coming out of, most of the Chinese stuff come out of the people's arm, PPLA, right?

Um, and then there are not state sponsored per se, but under the cover of a benevolent state, you know, wink, wink, they let them operate under their umbrella in their country, though they're not officially part of the state. Usually those are more with financial, uh, packing, right. Financial benefit, right?

Yeah. You're looking at ransomware that, you know, that's where you get into Yeah. That kind of thing.

Making financial demands and, you know, and there's lots of conversations about, you know, I've been asked repeatedly by people, you know, well, why would a country, you know, allow that? Well, depends on what kind of kickback you're getting, right? It depends on, you know, what kind of, you know, the individuals that are involved, right?

What kind of financial incentive are, are, are they receiving as, as a benefit of it? And not to mention the fact that, um, just imagine the other intelligence that they're able to gather, you know, while being about, you know, well officially it's not them, uh, you know, but you know, I'm, I'm sure they've got access to information that's being compromised, and I'm sure that, that, you know, they're talking to, you know, potential groups and, and talking about potential targets. So, you know, it's a very symbiotic relationship that you can understand why they're doing it Well, just the chaos that they sow.

Absolutely. Yes. Alone, you know, it is weakening, weakening your ad adversary or a friend of me, or whatever you want to call them, right?

Um, then there are some, you know, they estimate that the North Korea may, may, in fact, 25, 30% of their GDP may in fact come from cyber hacking and theft. Right. And like I say, it is, it is still big money, right?

It is, unfortunately, uh, you know, and, and again, it goes back to, I think still today, unfortunately, there's a lot of companies out there, uh, that are still very focused on keeping the bad guys out. They think that if they just throw enough money, buy the right piece of technology, implement the, the, the right piece of governance or guidance or policy, that somehow they're gonna magically keep the bad guy out. You know, I've been doing this for 35 years.

We've been talking about keeping the bad guys out for 35 years, haven't been successful yet, right? Um, and, and you know, and that's the problem, right? Is we, we, I don't believe are ever gonna keep the bad guys out.

Uh, I think the best that we can do is figure out how do we fight through the attack? You know, how do we, how do we maintain resilience? How do we ensure that that an attack doesn't turn into a disaster, right.

That they don't get to the crown jewel information they're looking for. Sure. They compromise the web server, or they compromise somebody's laptop, but they couldn't get from there to the actual data that you're after, right?

The actual server that contains the, the crown jewels, right? That's, that's really to, you know, in my opinion, you know, that's where the focus ought to be, is how do we, how do we stop these attacks from spreading as opposed to thinking that we're somehow gonna magically stop all these attacks. I agree, agree with you.

Um, you know, I, again, thinking back to when I was actively involved in this market, I, I don't know if people realized the, just the sheer number of attacks, the sheer amount of, of attack. I mean, back then we were, you know, we were helping to protect one of the largest private networks in the world that was run by a couple of service, well, one service branch. Right.

And, um, back then, and this is again, 2005, 2006, seven, back then they were seeing four to 600,000 intrusion attempts A day. A day. Yeah, absolutely.

I mean, I was, you know, I was in a similar role back in the early two thousands, uh, you know, defending the networks of the Pacific when I was a, uh, uh, network, operat security center, uh, uh, in charge of the Pacific nos. And we were receiving hundreds and hundreds of thousands of attacks. You know, like you said, every Day.

It was, it was very routine. Yeah. It's, uh, it, it, it really does get like that.

But, you know, Gary, we live in interesting times. We're living in an area of budget cuts in AI will do it for us. Uh, just frankly, political infighting.

You know, we ceases the, the very charter for Cesar and its funding. It was almost extinguished and then turned back on at the last second. Uh, who's maintaining the CVE database nist, their funding.

How do you think this all plays into the future of US intelligence and cyber crime or cyber defense? So, I'm, I'm an optimist, right? I'm, I'm not gonna lie, I'm an optimist.

Um, uh, here, here's my hope, right? I, my hope is the fact that, you know, sometimes in, in austere times, you know, things become more efficient because out of necessity, right? You stop doing, uh, things that maybe aren't, aren't as mission focused.

Um, I know in my experience in the military, anytime we went through budget cuts, uh, you know, a lot of things that a lot of us looked at and said, why are we doing this? Those, the, those are the things oftentimes that went away first. Uh, you know, so again, I'm an optimist, right?

I'm hoping that, you know, you know, maybe with some of this focus on, you know, trying to be good steward of tax dollars, uh, you know, try to look for efficiencies. I'm hoping that maybe we'll cut out some redundancies. Um, you know, we'll cut out a lot of, I think in the government, there's a lot of overlapping responsibilities, uh, you know, and, and, you know, the, the whole too many chefs in the kitchen kind of kind of thing.

Uh, so I'm trying to look, I'm trying to be optimistic, looking forward and hoping that things are gonna become a little more streamlined, a little more mission focused, you know, less distractions on, on maybe ancillary things. Uh, so I'm, I'm, like I say, I'm trying to be optimistic. I, I, I'm hoping that that's the way things are gonna play out.

I, I hope so too, my friend. In the meantime, for our friends in the public sector, or, you know, if you, as we mentioned, as you mentioned, the phone companies that service public sector, the, you know, so-called Beltway Bandits, the big contractors, the, the, uh, the Northrop's and the s aics and the, you know, so forth. Uh, what, what can they do, Gary to China, uh, it is a cat and mask, and we are playing catch up.

What's your advice to them? Short of going out and buying Lumio? Of course.

Okay. Well, you just stole my thunder. I don't know what now, now, now I'm out of advice.

Uh, you know, so, so I think there's a couple things, right? Number one is, and you know, I think some of this is common sense, right? Number one is, uh, don't get trapped into believing that there's a, a magic button out there that's gonna solve all your woes, right?

You know, don't, don't buy into some of the marketing hype of out there, of, you know, there are companies out there that say, oh, if you just buy us, you'll be a hundred percent safe. You know, that's, that's just not true, right? Let's just be honest.

That's not true. I wouldn't say that about Illumio. I, I, you know, I, you know, I don't think there's any company out there that should be touting themselves as saying, if you just buy us, you know, we're, you're, you're gonna be, you're gonna be secure, right?

Um, there's got to be a, uh, combined effort of both tools, you know, uh, people, you know, let's not forget, I, I worry a little bit that, that people think AI is gonna be the magic solution for everything. Um, if not, no, I'm sorry. Hate, hate, hate to burst everybody's bubble.

It's not gonna be the magic, magic solution for everything. Uh, you know, can it be a, a huge enhancing tool for cyber defense? Absolutely.

I think it can. Um, but is it gonna solve everything? Is it gonna make every, every company, you know, 100% secure?

Absolutely not. Uh, you know, 'cause the, the attackers are using AI just like the defenders are, and I hate to break it to the defenders out there. Uh, the attackers are going to gonna always have a, an edge, because they're not constrained by law.

They're not constrained by morality. Uh, right? So they, they can get all, they can be a lot more creative, uh, than, than the defenders can, I think.

Uh, so AI's not gonna solve it, right? So for the companies out there, I would say, you know, think about asking the question of, you know, what am I doing from a defensive perspective? How am I looking at my tool integrations?

And then, you know, what next, right? What happens when there is a breach? How do I ensure things like that?

I don't have to shut my company down, right? How do I minimize the impact of the attack? Um, you know, what kind of rings of defenses do I have internally?

Uh, you know, I really worry that companies spends so much time focusing externally that they're not looking inwards, right? I would love to see CIOs out there and CISOs out there. It'd be graded on.

Yes, it's great if you were, if if you're, if you get a, a passing grade on, I was never attacked. I was never, never compromised. That's getting a harder test for anybody to pass.

I think that really it should be a ma a matter of how successful were you in, in, in surviving the attack, right? What had you done in place to protect the company, protect the data, right? Ensure that didn't get exfiltrated right.

You know, what have you put in place to prevent those types of things? Got it. Excellent, excellent advice.

Gary. Hey, we're about outta time, Gary. So we mentioned seeing each other at RSA, but that's March.

Yeah. We'll have, you'll have news before then, so come back on and keep us posted. Okay.

Absolutely. Would love to. Anytime.

Alrighty. Gary Bartlett, public sector CTO at Illumio here on Textron tv, talking Soul Typhoon and more. We're gonna take a break here on the Textron tv.

We'll be right back. Hey guys, thanks with Throw, we're here with Chuck Hern, who's field CISO for F five, and we're talking about quantum computing and a, what are some of the actual real world applications today, and B um, we're gonna dive into cryptography a little bit and what's gonna be required and what we should be concerned about, and maybe what's a little more fanciful. Chuck, welcome to the show.

Thanks very much, Mike. It's great to be here. I think we all think of quantum computing as some awesome thing that's gonna happen three to five years out, but there are applications being used today.

There are APIs and cloud services. So what are you seeing folks actually doing with this stuff? I mean, there, There's certain fields where it's already making a difference, you know, uh, uh, materials, engineering, medicine, things like that.

But I haven't seen a lot of broad adoption yet. But there are live quantum computers that you can go and rent space for, you know, right now, and have been for, for some time. Um, what we haven't seen yet, what's not real yet, as far as we know, are, um, the biggest areas of concern for security practitioners, which would be what we call a cryptographically relevant quantum computer, or A-C-R-Q-C.

So, jargon alert, there, there are some specific terms that, uh, uh, you know, some of our viewers may, may not have heard before. So I'll try to spell those out. You know, without getting into acronym, uh, acronym stew here.

But what we don't think that we, any, any quantum computers exist that can break modern encryption and modern key strings now. But we do know that they're coming and we've seen a great deal of investment in, uh, into quantum just in the last month, for example. Well, this month was a big watershed month.

We had, uh, one quantum computer company go public. We saw over a billion dollars in inflow from VC going into quantum players. So we're, we're definitely getting to a, a critical mass takeoff point that defenders need to be ready for.

Yeah, we hear a lot of people talking about Q Day, which is the day when these things can break some of these more relevant cryptography algorithms. But, um, no one's quite sure when that's gonna be. Some folks are, you know, pointing to the end of the decade, and other folks say, well, uh, it may have already happened, and we just don't know it.

So, where are we on this curve? Yeah, right, right there with you. Um, if it exists today, it is most likely in the hand of one of the nation states, and its poor strategy for them to tell us that it exists.

Um, so I, I don't, I don't want to get into the, uh, you know, the dark web sections of speculation too much there. But, but what I would say for the, um, for the defenders who are trying to figure out, like, when do I need to start tackling this? The time is now.

I don't think that it's time to panic, but now is the time to start laying the groundwork, because there's a lot more to this. And getting ready for the world of, of, you know, where post quantum, uh, cryptography becomes something we actually have to worry about every single day. There's more to it than just swapping out a cipher.

There's a great deal of inventory, supply chain stuff. I think people are, are not factoring in the amount of GRC type of compliance that we're gonna have to deal with from a supply chain and ecosystem perspective. Testing, integration testing, uh, IOT devices, you know, OT devices, things that don't have a clear upgrade path.

This is gonna take some time. So, uh, as, as we're telling folks, you know, we're, we're closer to 2030 than we are 2020, and and you are not gonna be over prepared for this. Um, there are a lot of good reasons to solve problems today by reaching what we call the, the, the crypto agility target state, where you can roll your encryption whenever you need to without starting a new quantum project.

Um, and this is a key point that I wanted to, to kind of bring the, the viewers into the target state for, this isn't a one-time upgrade. The, the target state for getting ready is crypto agility. So we're recommending things like, you know, start thinking of crypto as a service where you centralize your libraries and you centralize services for cryptography across your applications to the degree that you can, so that when you have to roll your ciphers in the future, it's a much lower lift than it would be today, right?

Because the, the computers that we're trying to defend against or protect against, they, to our knowledge, haven't been built yet. And these new standards, even though they went through very rigorous testing from NIST when they were ratified, right at a year ago in August of last year, the first set was ratified. They've never really been run at scale in the real world.

So there's a lot of stuff we really don't know yet about how it's gonna go. We don't wanna try to do all this all at the same time in the panic that now we have to do this, you know, in the next three months, right? This is gonna be a longer tail effort than this.

So it is time to get started and start laying that groundwork, especially when it comes to stuff like creating internal business cases for this, this is a very technical, kind of esoteric topic, and to your point, it's always been a future problem. I think CISOs and CIOs are gonna have to do a lot of internal education about what is this? Why do we need to do it?

How much do we think it's gonna cost? Uh, what is the impact to our supply chain? I don't think this is as much a security issue, although the clearly security implications, this is a, this is a business continuity and supply chain governance issue.

Like this is a much bigger thing than if you think of like patching open SSL for heart bleed, right? That there's a lot more moving parts to this, and it's gonna take some, some coordination and governance. Uh, we, we need to get started.

Now, To your point, um, this isn't really an event. It's gonna become more of an ongoing process. And I say that because won't the quantum computers just get more and more powerful so that, which we think today is quantum resistant, might not be quantum resistant.

Three to five years out, Totally eight character passwords used to be just fine, then 12 character passwords were fine. Now, you know, anything, but, but, but passphrases and pass keys, keys is, you know, almost immediately vulnerable and, and passwords in general are broken without MFA. So, you know, as, as the capabilities for for the attackers continue to, to escalate, we're gonna have to continue to respond and, and hopefully respond as quickly as we can.

Because, you know, a lot of critical industries, if you can't keep your secrets, you, you know, you can't play along, you can't be in that space if you, if you can't secure your encryption, you can't, like, you know, be a bank, for example. Um, and so what we may see, and what I think we'll probably see is I think we'll see compliance requirements actually driving a lot of the timeframes. Um, when we talk about 20, 29, 20 30 windows that we're seeing pop up, you know, in the federal space here in the US New Zealand, for example, just published a paper that said, uh, we haven't defined standards yet, but as soon as we do, you've got two years from that date to get ready.

So we, we think that compliance is gonna drive a lot of these timelines, and I hope that the compliance timelines are conservative enough so they actually front run Q day, but we don't know, Right? And even so, if history's any guide, compliance mandates will be the bare minimum, right? And that may not be good enough anyway, A hundred percent.

I, I I, I, there's very little, I I really struggle with more than compliance driven security, right? Compliance is the bare minimum. Like being compliant is like showing up to work mostly sober wearing pants most days.

You know, it, it is not the hallmark of a well-run shop to meet the minimums that somebody else said you had to do to be a responsible participant in your industry. That's not the target. It shouldn't be the target.

It's the bare minimum to avoid getting fired or excluded. Um, so yeah, I really hope that that that doesn't wind up being the end all be all benchmark, uh, because there's a lot more business value you can unlock by actually having a good handle on your inventory in your cryptographic assets, right? There's good business reasons to get this under control.

So what will be required here, and I think a lot of organizations are struggling with this because they're saying, well, you're gonna tell me that some of my data will be exposed three to five years from now. I don't care about that data three to five years from now. So do I gotta pick my shots here about what data I do need to maybe upgrade?

But at the same time, they'll also say, well, I'm gonna get new infrastructure and I'll probably have new applications in that timeline that will come with PPQC capabilities. So what is this journey gonna look like? Yeah, totally.

And, and you're spot on some of the data that we need to protect every day. Like, let's take credit card numbers, for example. Um, mosque's theorem is a good, uh, is a good sort of way to explain the, the time factor here, uh, for p qc.

And that basically says, um, how long do you need to protect a certain set of data and add that to how long it's gonna be to get ready for PQC and migrate your stack over? And if those two things are longer than the date that we expect a, a, a full fledged, uh, cryptographically relevant quantum computer, then you've got a today problem. But to your point, not all of our data we need to keep safe forever.

Credit cards, they expire every few years. Yeah. I'm not worried about a credit card number 20 years from now getting exposed, right?

That that's, that's a, it's, it's a temporal thing. But other things, intellectual property, state secrets, uh, source code, um, internal information that, that you want to keep secret for long periods of time. Medical records, banking records, financial transactions, and the ability to, to impersonate and spoof, uh, official parties, right?

Because it's not just the confidentiality, but there's also the, the message digest and hashing and the binding of that encryption to the signing object. All of that stuff is, is gonna be, is gonna be relevant, and, and we need to prioritize that based on what, what's the longest length of time that you need to secure particular data and really start there first and focus on, uh, the, the asymmetric encryption, right? So symmetric encryption, like a ES, um, we've had a lot of speculation about, um, whether or not symmetric ciphers were gonna be as dramatically impacted.

It looks like they won't be. And, um, further, when you actually break down how an attack against a ES works, for example, I've seen very recent research that says maybe a S 1 28 is actually gonna be fine. Um, so we know where we can focus and we know we need to focus on asymmetric topography and long lived data.

And that's where we can start. For companies that don't have an idea of where to start, I recommend starting with your business continuity program. Hopefully you've got a BCP that shows what your critical apps are, where they live, who they own, who you know, who they're owned by, uh, and things like that.

So you don't have to do it all at once. Absolutely not. Is this just a quantum issue?

And I asked this 'cause I've seen some research that suggests that people are using GPUs and conventional computers to crack some encryption codes as well. And this could become a broader problem that goes beyond just quantum. It could be sooner than we think because somebody's gonna do some sort of technical advance.

We weren't thinking about Yeah, well, to totally. Um, and, and I don't know about what specific is, is going to, um, is gonna break next, but I will say that we are living in an exponential age. And so if you look just, just in 2025, just this year before January, or excuse me, before February of this year, uh, we had no way, uh, to have a stable enough environment that you could put a thousand qubits or a million qubits on a single chip.

Well, now we think we do. Microsoft said in, in February that they've got a clear path with, with their breakthroughs in MI to get a million qubits on a single chip. And that's what they're targeting.

In May of this year, just three months later, the estimate that we would would need 20 million noisy qubits to crack modern encryption, Google researchers released a paper and said, nah, we think we can reduce that by about 95%, so we need about a million noisy qubits. Uh, and so that was three months in, in three months, we went from needing 20 million to 1 million and also, uh, a path to 1 million on a single chip. This is happening fast.

I, I don't know what the next conversion is gonna be, but I do know that the, the, the more advanced AI gets and the models that we're using now are amazing, and they're only getting smarter. Things are gonna move faster than we think. I don't think Q Day is a 20 35, 20 40 problem.

Um, and humans aren't very good at predicting this exponential adoption curve, right. In 2021, if you asked a bunch of AI experts, when do you think we may see a GI? The consensus was 2040 to 2070.

That was just four years ago. I don't think anybody says we're 25 to 40 years away from a GI, you know, sitting here in September of 2025. If we haven't hit it already, it's right around the corner.

Mm-hmm. Um, when you kind of piece this together for a minute, we've always talked about data security and compliance and all that. Well and good, but is this also starting to be elevated into a national security issue where because of the nation states that are involved and what they're gonna do with that data, governments around the world are gonna be paying a lot more attention to this?

A hundred percent. A hundred percent. If you're in a government supply chain, this will impact you, uh, and it will impact you on the government's timelines, not necessarily yours.

But when you think about the, the geopolitics, uh, of, of the situation, which is notable in material, because I'm glad you brought it up. There's really two parallel race conditions that the US and China are, are on. And there are others that are in this race, but the, the most consequential, I believe are, are the US and China as the major superpowers sort of military powers.

Uh, that's AI and quantum, uh, AI supremacy. AI dominance means potential global dominance. Uh, it's very hard to fight 'em in an enemy militarily that's smarter than you are.

And quantum dominance also means, uh, you know, potential geopolitical dominance, uh, at the intersection of AI and quantum, who knows what's gonna happen. So a hundred percent, the the nation states are, are run at this. Both the US and China are on very, uh, combative and adversarial, uh, footing.

And neither one is, is really making much provision for off-ramps. So we're, we're in this race condition, and, and I don't see a way out of it, uh, without, uh, a substantial shift in relations between the superpowers. Uh, and I I don't see that happening in the next few years.

So what's your best advice then, to cybersecurity people about how to have this conversation, you know, with business folks in a way that, you know, they'll listen and they don't make, don't sound like, you know, here's another chicken, little skyes falling thing happening. A hundred percent. I really encourage, especially for, for organizations that are part of, uh, industry groups, uh, for example, we spend a lot of time in, in banking.

I come from banking. I was a bank and, uh, insurance company, CISO for a long time. Uh, groups like fs-isac, uh, the Financial Services Information Sharing and Analysis Center, they, they're, they're pushing and we're advocating and we're supporting an ecosystem view of this, right?

So, so that the, the member banks can go and say, Hey, everybody's doing this. The banking industry is moving this way. And take the pressure away from, you know, Chuck presenting a compelling business case internally, or Mike presenting an internal business case that's compelling.

We're saying, look, we're all going this way. We all need to do this. And, and take the attention away from the individual necessarily that's bringing it.

I think that'll help. And the other is, I think to frame it in just a, a credible business continuity type situation, that this isn't just a security issue, this is integrity, it's availability, it's confidentiality, it's, it's all of it. Um, and start with, we need to do some discovery.

We need to understand how big this is gonna be for us so that we can come back with better numbers for how much we're gonna actually gonna need to, to remediate this. But there's gonna be some long tail stuff with you're, you're gonna have to deal with suppliers and physical devices and things don't have upgrade paths and HSMs and things. So I think it's worthwhile to explain kind of the basics.

The entire industry that you're in is moving this way, or maybe you're a key supplier to somebody that's moving this way and you have to do it, or you're gonna be replaced as part of, you know, their, their supply chain management. And let's get our arms around this, see how big it is, and then come back with some credible numbers and, and describe the actual work that you have to do. But most companies really haven't even started with the inventory yet outside of banking, telecoms, and government.

All right. Hey folks, you heard it. Here.

We have an opportunity to do something historic. For the first time ever, the cybersecurity industry could be ahead of a problem rather than chasing one. Hey, Chuck, thanks for being on the show.

You Got it. Thanks very much, Mike. All right it back to you guys in the studio.

Hey, everyone, we're back here. Hey, this is our last interview for Swamp Up 2025. Woo.

I think I am gonna wear my jfr hat. How's that? Oh, you look beautiful.

All right. I won't mess my hair up. Yeah.

Um, so let me introduce you to our guest for our last interview today. They're two folks from Adobe. On my far left we have Shiba, Shiba, RA.

Thank you. We call him Shibu. Shibu.

Yeah. I go by Shibu. Yep.

Shibu is here. And to my immediate left, we have Vishal Reyna. Yes, sir.

Right. And we're just gonna call you Vishal. Yes, sir.

No shortened names there, gentlemen. Welcome. And thank you for being our last guest here on Swamp Up 2025.

Before we go further, I mentioned you both with Adobe. Mm-hmm. And we, and as we were talking offline, we actually did a whole, what I considered a great series of interview with the Adobe security team around security and ai, and how Adobe kind of eats their own dog food, if you will, or drinks their own champagne around security and to secure the products because all of us have Adobe accounts and we don't want that information getting hacked.

Um, and we did a series of articles on it, you know, it was a whole treatment. But you guys, you know those fellas from the security team? Yes.

But you're on a different team. Correct. Tell us about your team.

So I'll introduce our team. Um, we are the platforming group at Adobe. So when any developer wants to build something and ship it to their customers in one way or the other, we are providing the capability to those developers to make it happen.

And, um, we, the pa the organization is named developer platforms, uh, and we partner very closely with Security Organization, uh, led by Brian and Sure. Chlorine and others who joined you in the past. And, uh, we work with them closely.

And, um, yeah, that's, that's our mandate, help our developer ship software faster to our customers, better software. So when you say developer platform, is it like a true IDP At this? Yes, at this.

com mm-hmm. org group. Awesome.

Unit. Um, so I know a little bit about Enough to get in trouble about IDP. Is the IDP sort of like based on like a backstage type of Yes.

Thing. And is it, do you want to talk about that or, I know it's not really part of what we were gonna talk here, but I'm curious. I can talk about it.

I think, um, in fact, Adobe was one of the first companies who worked with the industry, and we actually put out a lot of content back in 2022 when IDP as a term was picking up. And yeah, go and look at, uh, the different journals, I'm sure, including some of yours. You would find that Adobe had me contribution.

So we were the first few adopters of the IDP concept, and we implemented at our company, we built it on top of open source software like, uh, backstage, which you talked about. That is the portal that our developers use. But it is powered by a lot of the CNCF community open source software.

Um, we are a big consumer of, uh, Argo. Yes. Uh, we are a big consumer of Kubernetes, and there are many more, Well, the, all the backstage stuff has Kubernetes at the heart mm-hmm.

And then of course the Argo GI Ops. Yeah. And all of this is now, you know.

Yeah. It's, so, I'm proud to say that we are probably one of the biggest, uh, installs of, uh, GitHub software in the industry. I think we really set really big scale.

We have really collaborated, uh, very closely with the community to scale the infrastructure. In fact, there is A-C-N-C-F blog that we have published on how we have scaled, uh, Argo setup for ourselves to meet the needs where the, the off the shelf, the open source software doesn't meet our needs. Uh, and I'll probably send you the link and you feel free to forward Please Do.

Well, may not be what we wanted to talk about today, but Q con is coming Absolutely right. Q Con cloud Native con will be, uh, I guess it's in November. Yes.

In Atlanta. And of course we'll be there live the whole time. Um, so, and that'll be both for our cloud native now and platform engineering sites.

So maybe, we'll, we'll talk more about that. I need to shift though, 'cause we are here at What J Rog Jfr and talk about what you're doing at Swamp Up. I'll let that, uh, al uh, we, We did a database migration.

Um, and as you know, most of the database migrations need downtime. We were able to accomplish a zero downtime for our end users, and we wanted to come in here and share the best practices with our peers. I thought because we don't have AI in our subject or presentation, we are not going to get any audience.

Turned out that room was full, and we got a lot of exci engagement right up to the point where we were meeting co couple of industry colleagues here. The goal was like, how, how we came up with an eight hour downtime and that got shot down, and how did we pivot in less than 28 days and made a zero downtime using cloud architecture, um, to accomplish a, and many of historical Jfr Artifactory users who are on MySQL or Microsoft, um, SQO will need to do this to come to the Postgres. And we shared our best practices, both in terms of how we solve it with technology and also best practices in terms of processes and people and communication.

And at the end, how we accomplish that whole, uh, zero downtime. That's A great case study, a great case study. Let me ask a question just between us.

Yeah. Um, is the fact that it didn't have AI in it a, a reason why there were so many people in the room? I don't know.

Maybe Have we all maybe AI out a little bit? Absolutely. You know, and I'm not downplaying AI or badmouthing ai, but it's refreshing to have a discussion that's not necessarily leading with ai.

Um, you mentioned Postgres, right? Yeah. Now Postgres is sort of one of the best kept secrets.

It is not a secret, but you know, it doesn't get the de the, the the and what it deserves, the acclaim it deserves. It really has become an engine, you know, and it started, I'm not, again, I'm not taking sides, but when my, when Oracle bought MySQL mm-hmm. It set Postgres on fire.

Fire. Yep. Yeah.

And, and since then, you know, you have, there are several different Postgres, uh, providers now in versions and some pure open source, some open core mm-hmm. What have you. But it really has become sort of the database or record, if you will Correct.

For, for a lot of these large, large, you know, hyperscale kind of environments. So, you know, that's something that, um, you know, I think a lot of our audience realizes it, but there it's worth repeating. It's worth saying out loud.

Yeah. What I can attest is the performance issues we saw prior years when we were running MySQL with lot of optimization hacks and everything else since we did the migration platform just scaled up and has been performing awesomely. And we were apprehensive, like, is it just one of those things that we have to do it with no gains, but we are seeing real benefits of this migration on top of it.

Those of you who are running Artifactory do consider using direct downloads. It just is cherry on the, uh, cake and will give you more performance. Really.

Yeah. Direct downloads from Artifactory. Yeah.

Just to my 2 cents on progress, um, means it has become, um, such a good database and persistent choice that in the recent years, at least in the last five years, anything that we have that my team has built in-house has leaned to Postgres as the persistent solution. So the developers who are on the ground writing a lot of code day in and day out, it's their choice to do relational databases and persistence. So plus one to what you said, Postgres has become that thing where, where probably Oracle of the last decade or, uh, so like, but, but it has become that like Database.

No, it is, it is. So I've been in this world a long time. My SQL was the standard Yeah, yeah.

In SQL database because, you know, you weren't locked into a vendor and it was, you had the community developing it in essence. And, and maybe it was, it was probably still a, a small handful of people who were contributing code, but you had the community driving the, the, the, the development visions and, you know, feature set requests and, and quite frankly, you know, Martin Kins and the people who were running it back then. Yeah.

It was, it was a great open source success start. Yep. Yeah.

So for any project beyond the con core contributors, it's the ecosystem around it. Yes. Like the different use cases.

Oh, I, I, Hey, just a conversation just between us, like, Hey, I'm trying to build this app in this scale. Go use Postgres. Here's what you should do.

Yep. So these things which we just take for granted, basically make the, somebody wrote a blog post or we came in and spoke about its success in just specific to artifact. These things do add up and Absolutely Do, or as technology more successful Now, you know, you look at Swamp Up and I've been to a lot of Swamp Up in many ways.

This is the company and the conference that Artifactory built. Yes. Mm-hmm.

Right? That was the acorn that this oak tree grew from. But there's more to Jfr here.

There's more to swamp up than just Artifactory. We saw today, you know, this week we, we saw, uh, uh, uh, JFR fly the, the agent AI repository. We saw the AI catalog.

We saw a lot. Yeah. How does that fit in with your mission at Adobe and your, I maintaining your, uh, IDPs and, and your developers?

Are they using these new tools yet, or you think they'll want to use these new tools? Uh, do I, go ahead. Go after you.

I, So, um, we just started, uh, we were locked in to Origins because of the database migrations we just started opening up via current. And now we are in a position to start exploring and getting benefits from the machine learning repos coming in, or the catalog. And certainly the agent take workflows.

We, we are going to go in and see where all working with Jfr, uh, our partners, see how we can tap into these new offerings that have come in. And let's not forget about the SBO m uh, AppSec, uh, offering that has come too. So we, we are going to go and explore these.

No, we are very interested. And so I think, um, there are two sides to it. One is, as a platform group, whatever we are offering our customers, we want to make those capabilities more urgent tech.

So we, between Vishal and myself and our teams, we need to build more agents. And the capabilities that kind of are, uh, published in this year's sw up some of that. We are very interested into, um, looking at and see how that can help.

Uh, the second side of it is, as our product teams are taking that agent journey and bringing in agent features into the products product like Photoshop, illustrator and several others, they need a platform where they can run agents. So we are solving that agent platform problem as well as we are building agents for ourselves, which would let us kind of expose our capabilities back to, so on both sides, the, the, the, um, the announcement that came from jfr, the excites, uh, the Excite Us, be it AI catalog, uh, any other feature I feel that can really help us. Um, so we will go back and start looking at them and see how we can factor them into our, um, our use cases.

I love it. You know, um, people don't realize about Adobe. You know, Adobe is, look, it's kind of a Blue Blood, a royalty name in, in the software world, we all came up using Adobe products, whether it's for video or graphics or PDF or what have you.

But I don't know how many people out here really realize Adobe is a company that's very transparent about how they build, how they secure what they do internally, like their their own best customer in some ways. Right? We we're gonna show you what we think at best practices, and you should feel free then to use them, right?

We, we've already paid the idiot tax in some respect, learning these things, and we're trying to save you from paying that tax going forward. I don't think they get enough credit. I mean, you make great Photoshop, you make great Acrobat, but really being a good, a good community member Yeah.

Right. In the software industry is, is commendable. And, and I, you know, congratulations to you, not just to you two, you but the whole organization.

Yeah, yeah. For the, for the way you do it. It's, it's really, I wish more companies were like that.

Absolutely. No, I think, uh, this has been a practice in the company since long time before we began our stint here. And we are just continuing that, right?

So, um, our leaders tell us, like, whatever we learn, it's our responsibility to go and pass on to the community. And we are doing it. Vishal and his team did extremely great job of this really difficult migration.

I want to thank him and his team and all of the people who really did the work on the ground, and his team is coming in and sharing all of that with the community. And it, it, there's a lot of interest. I'm sure other teams are going to do the same.

And, uh, this is Going to help a lot. You've well received. Yeah.

Where's, where's, where's the next conference you're presenting at? I haven't decided yet, but we'll identify something soon. Yeah.

Our group is, um, going to CubeCon. We have some presented, We will be, we'll be a CubeCon going live. com site Yeah.

To find out more what you're doing with platform and how you're building it out. Yeah. Because this is, you know, DevOps, cloud native platform engineering, these are all just different pieces of today's software factory, including ai.

You know, AI plays on all of them. Yeah. But it, it, it just basically, uh, compressing, uh, I was talking to one of the, uh, conference attendees.

What AI or generating AI in particular has done it, has flattened the learning curve, like getting a particular sector or a piece of technology or coding for that matter, where, which is what Shibu and I are closest to the getting a prompt in and start learning about, or basically porting a technology which was written on one technology to another technology. It's not completely solved, but it certainly is easier. You can understand legacy codes better.

All of these have intangible, uh, benefits, and that's why we'll see more software coming faster at us, which basically puts stress on all the underlying plumbing or the CICD supply chain. That's where the, the platforms had to come up to basically, um, deal with the new throughput of, um, innovation coming in and making sure that each of the right customers. Absolutely.

Gentlemen, I want to thank you. Thank you, Micha. Pleasure.

Shibu. Thank You. We're gonna wrap up our, our swamp up coverage.

I hope you've enjoyed it. We will be back. Well, I guess we'll be back tomorrow with more texture on gang, just not out here in beautiful Napa.

But until then, this is Alan Shimel on behalf of Jay Frog and all of our guests, thank you for watching and staying with us, and, uh, we hope it was valuable to you. We'll talk soon. Bye-Bye.

Hi, everyone, welcome back here to our day two coverage of Jfr Swamp Up event in a beautiful Napa Valley or at the Meritage Resort. And if you've never been here, highly, highly recommend. It is a full on resort and spa with wineries on and vineyards on premises.

It's really a lot of fun. I, I really do, do recommend Italia you. Um, let me introduce you to our next guest, though.

We have two guests here. We have Aman Sana, and I hopefully get this right. Vijay Kumar.

Hey. Hi, Aman and Vijay work for a large financial financial institution. And they're here talking about, you know, in a hybrid AI world, how, you know, how large financial institutions can get a hold of their, or it can, you know, manage their CICD pipeline, their software, supply chain, security of it, and everything else.

So, Armand's closest to me here, vj to my far left. Gentlemen, welcome to Textron tv. It's great to have you on here.

Yeah, thank you so much. Yeah, we are, we appreciate the opportunity to be here and in this beautiful Napa Valley. Yeah, this beautiful day.

There's worst, worst places to be. Sure. Um, so let, let us talk a little bit about you guys presented actually.

Yes, yes, we did. So if you wouldn't mind, share with the audience a little bit about your presentation. Sure.

So, uh, we gave a talk yesterday. It was, uh, uh, good opportunity to come here and, and present in front of like a large crowd talking about like how, uh, a large financial institution might do, uh, uh, a resident release of their workload, especially in a hybrid cloud setup where the complexities are very different, right? I mean, uh, uh, typically like companies, they start small, uh, going on-prem, especially in large financial institution.

Uh, there's a lot of legacy stuff that still runs on-prem, right? I mean, uh, especially in bank financial domain. Uh, companies started with building the infrastructure, uh, in eighties, nineties, early nineties.

And that infrastructure still runs on-prem. But the challenge is that, uh, in order to compete in the marketplace, uh, companies have to evolve and, and make sure that, uh, they, they are able to seamlessly integrate with FinTech, uh, especially like the, the new age companies, modern age companies. And there is a pull, like on, uh, on the other side to build modern software.

And that brings a unique opportunity as well for the companies to start looking at how they can modernize their existing workload. But the challenge is it's very hard for the companies to migrate everything and in one single shot. So the strategic choice that company has is to invest in hybrid cloud capabilities, which doesn't come for free.

I mean, there are challenges, uh, that we can talk about, but definitely, uh, there are a lot of opportunities that show up with hybrid cloud where companies can scale, they have a capacity burst. Um, and then a lot of like where advantages when it comes to like innovation, making use of like, um, a lot of like different, like new technologies that are being developed and, and are cloud first. So that kind of like bridges sort of like the gap with hybrid cloud, where companies can still run the critical workload on-prem, but then at the same time, they find a way to sort of like, uh, gradually move, uh, to cloud in a phased approach in a phased manner.

Excellent. You know, I, I think, well, I'll speak for myself. I'm not gonna speak for everyone.

That's kind of the way I always envisioned it, right? That you don't, I remember, I, I was at an IBM conference eight years ago, seven, eight years ago, talking to the CIO of Hertz, the car rental company, and, and he said they decided to go to the cloud. And what they did is they built from, from scratch all new cloud-based applications.

And soon as they had those up and running, they literally just shut down their old on-prem data center applications and switched over. Well, it was a disaster. Kurtz wound up filing bankruptcy, if you remember a few years back.

Yeah. He lost his job. Yeah.

And, and so I always knew that that was not the way to do a cloud migration. Right? You don't do it that way.

You had to do it over time, and you're gonna have this hybrid model and that, and there's nothing a matter, that hybrid model may last forever, quite frankly. There's nothing saying that you move everything into the public cloud, Right? Yeah.

I mean, if you look at, right, we are kind of home of innovation right here in, uh, California, and as you go from Napa Valley to south, you start seeing the innovation every, every mile, every minute, right? Yeah. So if you look at this space and the, not just fintechs, the large electronics company, you know, the apples and Googles, how they innovat it last, uh, you know, one and a half, uh, um, uh, decade.

And if you look at all these things happening together, they're integrating with financial institution, they're integrating with healthcare and whatnot, right? So if you see the innovation is happening and financial institution cannot be left behind, right? So they need to be, they need to make sure that the customer experience is retained.

Customer wants everything on the fingertips. So all these digital payments coming together, it's, it's, it cannot stay on the legacy because legacy may not meet the customer expectations. So I, bridging the gap requires, you know, the resiliency everywhere, right?

And we have a kind of a environment where customer is at the center and everything needs to be delivered quickly to the customer. So that's where the, the cloud and the DevOps and automation comes into the play and the finances services are catching up if they were behind, but they are not too far from getting, you know, no, uh, to the space where they're supposed to. So I, I'll tell you a, a funny, not funny, but I'll tell you an observation I've had, right?

com, it was 2013, so this is 12 years already. Yeah. And, um, yes, traditionally, finops financial institutions being conservative and highly regulated don't necessarily have bleeding edge, right?

They make sure something's tried and proven before they, they leap into it. But when it came to DevOps and then DevSecOps, right? I saw financial institutions take the lead.

And the reason for it was, quite frankly, where they were, was not a good space from a security point. They were being attacked and hacked, and they had to do something. They had to get better control of that, number one.

Number two, the market was changing. You had this new breed of financial institution that was, was born in the cloud, that was born on the internet that was more nimble, right? Because customers, you know, when I was a little boy, we didn't have ATMs even yet.

You had to write a check, you'd wait online at the bank to the teller. Yeah. Yeah.

And they would give you the money, and ATMs came out, but then apps came out on the phone, the cell phone, right? Yeah. It just changed it.

All of a sudden people were, how often do you actually go in a bank anymore? How often do you deal with the human at your financial institution group? Only if there's a problem, basically.

Yeah. So as a result of this, I, I think the market flipped finance became a leader, right? In customer, you know, giving the customer what they want, when they want, how they want, right.

Which was primarily through a app. Yeah. Not through a brick and mortar.

Mm-hmm. And, um, so my experiences is that they have led the way in DevOps, they have led the way in a lot of these innovations. However, they still gotta worry about highly reg being in a highly regulated industry.

Right. Let me though, ask you again, you, you made this move into this hybrid environment. Do you envision going total cloud or will you always, you know, I look a a lot of financial institutions still also have mainframes, right?

Yeah. And you're not gonna move, you know, to walk away from your mainframe. Yeah.

That's a statement, right? That, that that's, that's not easy. Yeah.

com and their text drawing, they have, you know, they maintain a sys a system of record and a system of engagement, right? Yeah. Record being usually a mainframe at a data center somewhere, and engagement may be up in the cloud, right?

Is that how you guys envision your go forward? Yeah, I mean, the way I say is that, never say never. Okay.

But at the same time, as an organization, and depending upon how you are set up, you build a strategy and the strategy as the time passes because of the other factors, you know, you may plan and say, okay, I want to move into cloud, you know, but as you see the opportunity, you could probably shift and then get rid of the on-prem, or you think that Yes, probably in the long-term strategy, I have the midterm milestone to determine whether I can get rid of or I still need to maintain. So the ag organizations build their strategy depending on the size of organization, depending on the customers they are serving, depending upon the partners they do have, they make the strategy in general. There are a lot of organization they can get rid of this, um, on-prem setup just because the way they are set up and the customers they are serving in probably our case.

And there are some similar cases, probably it might be a time to see, you know, in next couple of years or few years to see that, oh, now we have moved enough. Probably it's time to, you know, get completely, uh, other side of the bridge. So that's, that's kind of strategy, you know, as, as, as we go.

So, so short answer is we are yet to see that how the strategy evolves to, you know, get to the fully cloud and we stay onto hybrid mode. Yeah. And just to add to like what we just said, I think, which was very well said, um, I think companies also have to make sure that they're doing it in a very sustainable manner, right?

So, um, I think we just alluded a little bit, uh, on that as well, that it should not be like a big bank sort of like move to cloud. Uh, of course, I mean, it's a learning opportunity for a larger institutions, right? I mean, where, uh, they might have like thousands and thousands of applications running on-prem.

Um, they have like few applications running in cloud. Now there are challenges that show up, right? I mean, you might have a data sitting on-prem and there might be regulations right around how you store the data.

Uh, you might have to be in compliance with, with your data, right? So, uh, sometimes you might want to move the compute to cloud, uh, to the cloud, but then you might have, uh, some restrictions that you cannot move the data to cloud. Uh, there might be some, uh, innovations that might have to be done in order to be able to move the data to cloud.

Uh, but I think that's probably, uh, uh, kind of like a, uh, uh, an approach that company can take where they can take some steps in a phased approach before they finally land in, in a, in a, in a state where they can declare that they're fully running into the cloud. But I think that that should be probably the mantra for any company. I mean, that could be the north go north star for the company, but again, there are various factors that can, that could influence that journey, uh, towards that North Star.

Agreed. Yeah, agreed. You know, another phenomenon, so I hybrid to me was always obvious.

Yeah. You know, what wasn't obvious to me, multi-cloud, right? So do you see an institution like yours going multi-cloud using more than one hyperscaler Cloud provider?

Yeah. Maybe I can just quickly, uh, uh, throw some light on that. So definitely there are like a lot of different cloud providers, public cloud provider, and every cloud provider has their own sort of like niche, right?

Yep. Uh, you can look at my Microsoft Azure, uh, Google Cloud, Amazon Web Services, uh, all of these like big cloud providers, I think, uh, they, they all are innovating. Um, they are sort of equally good.

Uh, but some cloud providers have services that pro that pro that probably might be like more niche and most of like cater to a certain sort of like, uh, uh, industry, right? So, um, I think in general, companies are sort of like investing, uh, in one major crowd provider, but also being at the same time cautious about the fact that, uh, there has to be some sort of like a risk management approach that has, well, you don't want to locked in. Yeah, you don't want worry locked in.

But at the same time, uh, it's also, uh, conversation around like the cost management. Uh, you don't want to put all your eggs in one basket. Yeah, that is true.

At the same time, if you divest too much, then uh, you are also kind of like, uh, not reaping the full benefit of like having a cost, sort of like optimization by putting more workload in, in one single cloud provider and then kind of like being able to negotiate, uh, a price point that serves you well, right? So, uh, it kind of like, it can go either way, but then of course, I mean, you have to have a balanced approach as to like how much you diversify, but at the same time how much you concentrate and then kind of like get the cost optimization. Yeah.

To add to, among what he said, like if you look at probably no organization, which is using a service as a SaaS is insulated from multiple cloud, you know, um, uh, environment, probably directly running its own workload or probably via a service provider, there could be likelihood that you are using underneath, right? But the important point is that if, depending upon the size of the company, the customer, it is serving the geographic location and pricing point, the organization chooses to be, you know, into the multi-cloud versus single cloud now, and then the on-prem, right? So if you look at the landscape, they are, you know, in the multi-cloud strategy probably is better in certain cases when you are like global company and then you are serving the, you know, different type of, uh, um, customers and services and then, you know, um, the kind of, uh, product you are offering.

And in that case, sometimes you may, you may have, we not have a choice other than going to multi-cloud. So those factors come in. But if you are like a small organization, probably you may opt in to have probably two providers, and probably you are happy with that.

And so you can negotiate the pricing and do other things. But at the same time, if you are, say if you're going to a CF aspect reason, and you do not have that cloud provider capability, you are bound to have use another cloud provider, which is already there because you want to serve your customer. So those factors kick in.

But certainly from the, from the financial institution or you know, the global companies which are serving the customer, they probably make those, uh, smart choices depending upon their business strategy, uh, in global landscape. I love it, gentlemen. I apologize.

We've got a lot of background noise. Hopefully it's coming out well. And microphones, um, last subject, ai, how's that playing into this?

I think no company is shielded from ai. Uh, I think that's, given that in order to stay ahead, uh, companies have to make investments into ai. But again, it at the same time, financial institution, um, banking and lot of like different industries have to be very cautious about like how they use AI in a responsible manner.

I think one of the biggest challenges, uh, especially when it, when, when, like, when it, when it relates like financial matters, right? Um, AI can sometimes make a decision that may not, uh, be very well and kind of like aligned with regulators, right? So in general, um, AI has a lot of potential, but I think there is still, uh, some work that needs to be done to make sure that AI is used in a very, very responsible manner.

Uh, there are use cases where, uh, AI can be easily used, right? I mean, uh, we have seen financial institution investing like deploying AI and call center applications just to help agents serve better, uh, for the customer. But I think what we have seen, like in the industry in general, is AI being adopted in a core sort of like processing is still sort of like something that has to be, uh, uh, has to be, well, kind of like, um, uh, there has, I mean, it, it requires some sort of like investigation as to how it can be incorporated in a responsible manner.

Because I mean, anything that you do has to be explainable, right? And sometimes the challenge with AI is that it, it's not very conducive to explain like how decisions were made, like, uh, by the ai Yeah, For certain industry it might be simpler, you know, if you go to manufacturing, it might be simpler because you are doing mechanical in most of the cases. So it's a simple, it's a repeatable process, you know, you're not making a lot of decisions there.

But if you go to the healthcare or, you know, uh, into the spaces where humanists are involved, you know, decisions are involved, financials are involved. I think it's, it's, it's very, you know, the area where it's not easy to Not in the highly regulated Go move forward with that. Highly regulated.

Yeah, exactly. So, agreed. So with those considerations, you know, are you always there?

But as AI matures, who knows, you know, in next few years things may change differently. You know, what if the public, if your customers demand that sort of functionality, you're not gonna have a choice. That is true.

I mean, that, I mean, customer comes first. I it's a Customer led business. Yes.

Yes. Yep. Anyway, Hey guys, thank you for coming on, For having us today.

Thank You. Swamp up. Thank you.

Yeah, thank you so much. Yeah. All right.

Vj, Oman, Aman here on Techstrong tv. We're gonna take a break. We'll be back in a moment.

Hey everyone, it's Shimmy, and welcome to this week. Shimmy says, we're back on track on Thursday. I hope you're able to join us or wherever you are watching this, whenever you're watching it.

Thank you. You know, I, I'm gonna throw back to some Hillary Clinton in the People's Republic of China, years and years ago, I think it was 96 or something, when she said, women's rights are human rights. And, and that became a bit of a, a cliche, well, in my best, Hillary Clinton, I'm not a good Hillary Clinton impersonator.

I'm here to tell you today that digital transformation is AI transformation. It's been replaced. It's been disrupted.

You know, I always felt that digital transformation was one of the most overused, misunderstood words in technology. What exactly did we mean about digital transformation? Well, when I first heard it, I, and I don't know, maybe I'm a child of my generation.

Well, if we're doing a digital transformation, we must be transforming from an analog world to a digital world. And to a certain extent, some digital transformations were like that. It was about moving from a brick and mortar store to a online e-commerce situation during COVID.

This became a must have, right? Because if we didn't have a, a way of reaching people who were stuck in their homes and getting the goods they ordered, 'cause some of it was digital that they could download, and that's easy. But getting physical goods to them required us integrating a digital selling delivery, logistics, operational method into our analog world.

And, and you know, what? Necessities, the mother of invention, so many industries, so many companies got with it quick. And we saw the biggest move to digital away from brick and mortar, probably ever during COVID.

But there was other kinds, there's other kinds of digital transformation. You may already be digital for some people, digital transformation was moving from a private data center to a cloud public cloud. For others, it was moving from a mainframe to modern, uh, modern architecture, cloud architecture, or a hybrid architecture, or a multi-cloud architecture.

It was the cloud native digital transformation became anything where you were transforming your organizational business model, processes, practices into something more modern. And we, we slapped the DT LA table on that label, on that digital transformation. Now, what we've seen in the last two and a half years though, is a move to AI transformation.

And I think this level, this AI transformation is gonna totally replace digital transformation. Because what we're doing here is everything is being transformed and disrupted by ai. So it's not enough just to move your brick and mortar store to some app or your financial, your bank from a brick and mortar branch to an app.

Now we're enabling them with AI so that the AI can, in essence, do it for you. We, I saw just this week, probably three or four different pitches come my way of agentic AI handling your finances. Don't worry about balancing your checkbook, paying your bills, or doing any, or managing your investments.

The agents will take care of it personally, I don't know if I'm ready to trust an agent to handle my finances by un un unhinged or unmanaged by me. But this is the kind of AI transformation that we're seeing. We're seeing it in writing code for applications.

We're seeing it in migrations to public cloud, back from public cloud to private cloud, to bare metal to the edge, to endpoints. AI is handling all of this for us. Um, and, you know, this is the year of AG agentic ai.

I don't even think we've seen the full extent of, you know, a lot of these agents are just being rolled out. But whether you are using it for tra to arrange your travel, to do your schedule, to respond to your email, virtually every task we think of AI is transforming the way we're doing it. So I sit here today and tell you that digital transformation is AI transformation.

You, if you are transforming things you are doing, your organization's doing without building AI into that process, you're just wasting your time. 'cause you're gonna have to redo it real soon. So, if you're thinking about a transformation project, think along the lines of AI transformation.

So remember, you heard it here from Shimmy, right? Digital transformation is AI transformation. What are you doing for AI transformation today?

I'd love to hear about it. com. And I, I'd love to hear your story.

Maybe we get you onto Shimmy says, or a tech junk TV interview or something. But we're looking for AI transformation stories Until next week, enjoy the weekend, be safe, and well, I'm out. Good morning everyone.

Good morning, panelists. Uh, my name is Manny Calero. I'm a consulting solutions architect, dita.

We're an edge management and orchestration platform to help our customers solve business and technology challenges at the Edge. Today, we want to jump in and talk about understanding containers and, uh, workloads at the edge and different approaches. So let me start with a question.

Do all edge workloads really look the same? And the answer is really no. Some workloads are large, heavy distributed cloud native applications that may require Kubernetes, and Kubernetes is fantastic for those.

But, um, some edge workloads are smaller. Maybe a connector, single analytics engine, IOT broker, or perhaps a lightweight multi-service application. For those maybe Docker Compose makes a lot of sense, and that's the right tool.

It's fast. Familiar developers, um, are used to, uh, using Docker compose locally on their laptops ideal for Brownfield or, you know, resource constraints sites. So to the point we support both, um, and you can choose with our platform, you can run either Kubernetes where it makes sense or Docker compose, where that's a better fit.

And, um, now let's talk about if developers are already using Docker Compose, why is it important that we bring that to the edge? So of the biggest challenges, um, at the edge is diversity of workload. So in most environments, um, you don't have one type of application.

You typically have many. Um, you've got legacy VMs running, you know, that have been running for years to, uh, maybe Windows machines. At the same time, your developers are delivering modern containerized apps, often defined with Docker compose and looking ahead, there's always new container frameworks that are being introduced and services that are being introduced.

So what makes us unique is that we don't force you to choose one model. We support them both. And instead, uh, we provide a platform where you can run all of those workloads side by side and on the same edge node.

So the bottom line is whatever workload you you have today, and whatever you add tomorrow, we will support it and we can orchestrate them. So here's the, the real strength of our platform, and it comes down to flexibility. Um, most edge environments are often clean slates.

Um, you've got legacy applications that are still running in VMs. Uh, you've not containerized apps, but some are defined in Docker, composed for those that are containerized. And, uh, you may also have other, uh, modern container frameworks that are emerging.

So with us, it doesn't make you choose one model. Um, and whether you have 10 nodes or 10,000 nodes, we'll provide the same zero touch provisioning and policy-based orchestration to make sure everything's consistent and scalable. So repeatable architecture is really important to us, and to be able to bring scale, uh, to the edge is really important, which is kind of what Docker composed lacks.

And it's get the scalability piece, and that's what we bring to the table in, uh, delivering a Docker composed solution. So whatever workloads you have today, and, you know, whatever you bring tomorrow, we can help you and our platform can orchestrate them. Hey, Manny, it sounded like you said that most edge deployments are clean slates.

Is that what you Said? Thank you for point of No, they're not clean slates that we typically have a lot of legacy apps running And, and devices and devices that you wanna reuse if you can. Okay.

Yeah, and that's one of the cool things I think more Borg mentioned is, uh, about, uh, e os, which is, it can run on very, you know, very lightweight, uh, very small form factor, uh, type of hardware. Um, so it's really powerful in that sense, that support legacy, um, smaller applications. So let's talk about how this works, uh, from the user perspective.

So typically it'll be either a developer or enterprise user. They're deploying, uh, containers, they're creating their apps, they're containerizing it, and then they're typically using Docker composed. That's a very simple tool.

It's very powerful. It's very quick, very streamlined. Um, and then from, from that perspective, they'll create the application.

They'll have their YAML file already defined, and then from our market marketplace, what they can do is they can, uh, from the global market base import into their local marketplace, what we call a, uh, Docker composed runtime, and then they can deploy their apps on there. So the runtime is in our app, it's maintained by Zaida, so it's very important, right? We patch it, we update it.

The whole lifecycle management is care and fed by Zaida. Um, and then once it's in place, the user can simply take their docker compose YAML files, their existing, uh, configurations that they're using today, and deploy them in the runtime. So the result is the applications are instantiated and running on the edge node fully orchestrated and supported by Zita.

So from the the customer's point of view, it's a straight and simple flow user marketplace. Put your Yam o files in an app and orchestrate it, um, on the, um, on the runtime. So the benefits that we see and how we make it, uh, scalable to, to our, you know, our customers is speed, right?

Uh, fast onboarding in minutes, uh, same YAML files that they're currently using. Uh, we're flexible, um, because we can not only support VMs and, uh, Docker composed runtime, but also Kubernetes, uh, when needed. And then the, the really important part that, uh, and the gap that we fill is the scalability piece, right?

If there's one missing piece to, to Docker compose is the fact that it's, it doesn't scale very well. It works very well in local environments, you know, maybe small, you know, five, 10 sites. But as you start to scale, uh, in the distributed edge, it becomes really important to have a platform that can take that repeatable architecture across geographies, and then maintain that single control plane, roll out updates, roll them back, keep visibility across a fleet, and then of course, consistency, uh, repeatable architecture.

So taking the same, uh, YAML files that you may be, you know, compiling on your, uh, on your laptop, and take that to, uh, the adida orchestration, and then create those predictable outcomes across dev test production and lower, you know, the operational risk that makes, uh, adoption frictionless. So now I wanna show you just a quick diagram. Um, I'm gonna run a demo and, uh, after this slide here, and what I'm doing is from this adida platform, I'll be orchestrating onto two edge noes, um, the same application.

So to show you kind of how we deploy across the, the fleet, um, so you can see it in action. And then I'm gonna sprinkle Terraform in that as well. I love Terraform, and that's, we're very proud of our Terraform provider.

So, um, I'm gonna be doing some of the deployment through that. Um, I'm gonna show how, uh, I can deploy the infrastructure to the point where we deploy the runtime, and then I'll kind of stagger it a little bit, deploy the runtime, and then deploy the apps, and then show you what they look like, um, in the, in the, uh, the marketplace. So here, I'm gonna start the demo, and this is what our, our UI looks like.

So we log in here, the first thing I want to do is, uh, show our, um, our dashboard, and then go through the different sections to show that there's no elements created. Uh, there's no networks, there's no edge nodes, um, there's no marketplace apps. And then the first thing is show the Global Edge apps.

So if you go into our global marketplace and you click the data, you're gonna see that we have three Docker composed runtimes. Um, they're different flavors. I'm gonna go ahead and import the large flavor into our local marketplace.

So now you'll see if I click on here, there it is. Um, and then once I go inside, you can see some of the particular elements within that runtime. So, four CPUs, eight gigs of memory, storage size.

And then what I typically like to do, especially for the demo, is I cloned the app. I don't necessarily have to use that. I can clone it and make some changes.

In this case, what I did is I, I cloned it, and I'm going to reduce the persistent storage size of 20 gigs. The original had a 200 gig, but it shows that we can kind of tweak, uh, those applications in terms of sizing, and then I'm gonna keep all the defaults the same after that. So here, I've got a cloned, uh, application.

So now what I'm gonna do is I'm gonna pull up my Terraform code here. I kind of show the, the diagram again, of what I was gonna deploy. But, um, I'm gonna go through the, the Terraform code and kind of walk through what it takes to build the infrastructure.

So it starts with a project that's kind of the umbrella, and then everything falls under that. You have, uh, your images, you have your storage repositories, of course, your edge nodes for onboarding, uh, and then of course, the applications where you define them, the, uh, the network instances and all in, you know, a single Terraform file. And then I, I'm gonna deploy it to the point where I'm gonna have my projects, my data store.

This is where, uh, I would store applications, the image, this is where the, the package would be. And then, uh, a couple of networks and, and, uh, the applications that you're gonna see in the marketplace that I'm gonna have, uh, deployed through here. And these are the YAML files.

I don't know if you can see it on my screen, but I feed the YAML file to the Terraform, and then the end result is in the marketplace. You're gonna see the application, and then you're gonna see the YAML file. So here I did a plan and apply, and then I'm going to show you how I created a couple of edge noes.

I created network instances for those, and for the runtimes, I created the Edge apps. So I created four edge apps. I created, you know, very common apps that we see, like Grafana Ignition, uh, and Splunk.

And then within those, uh, the YAML files are, uh, are configured. Uh, here, I'm gonna wait a little bit. Uh, it takes a couple minutes for, um, the, Yeah.

Quick question, while this is, while this is coming up here. Yeah. Um, let's say I'm using some orchestration, uh, software that's not Terraform based.

Can this be consumed with a API, right? Can I drive the Zita dashboard and cloud from that API? Yeah, absolutely.

So Zaida is 100% API driven. Even the web UI that you see there is driving an API on the backend. So we have our, our API is, uh, published, so you can leverage, uh, Terraform, you can leverage our rest, API, um, and also we have our ZCLI.

So it's, it's a very flexible platform. Many ways of configure it. I happen to love Terraform, so I, that's the way I kind of orchestrate all of my, uh, uh, my environments.

And then here, uh, you can see the, the Edge noes came up. So they're green light, that means they're onboarded. What a typical experience for a customer is, this gets shipped to a customer, they plug it in, turns on phones home, it's registered, and then that becomes a registered endpoint where you can start deploying apps.

You can deploy your runtimes from that marketplace. So here I'm just showing a, some details around the, uh, the edge nodes, uh, the adapters that are available, uh, some detail on that. And then here, what I'm gonna do is now that the edge nodes are up and running, I'm gonna go ahead and deploy the runtimes.

I can still do this from the marketplace just by launching it. Um, I wanted to show the flexibility of our platform. So I'm doing, I'm doing it through Terraform.

So I just do, uh, a plan and apply here. And then as we go back to the dashboard, you're gonna see that Now I've got a couple of run times that are coming up. There's one that's already downloading, and then within a couple of minutes, they're up and running.

They're green light. That runtime is ready for you to execute those yamo files that I mentioned before, um, that I also created. So once they're online, you can deploy your apps here.

Now, you can deploy straight from here, and you can see as, as I click on, on the application, you can see the YAML information in particulars for each, uh, for each app. And then you can deploy it straight from here. I'm gonna go ahead and deploy it through Terraform just to show the automation piece of this.

Um, right after I show you this last YAML file for Ignition, um, ignition is very popular app for our manufacturing, oil and gas customers, very common application, um, automotive, uh, plants. So here is where I start deploying the app. So I'm gonna deploy the, the application across the two, uh, edge nodes.

So both, uh, Grafana, uh, Splunk, and of course Ignition as well. And through that single entry for each one, it's gonna spray it across the different edge nodes. So I'll just do a simple plan and apply again.

And of course, I can do this with a single swoop, but that would be kind of a boring, uh, boring demo. So, um, I kind of staggered it a little bit. So now you can see that the, uh, the apps are, are being deployed.

Those are the demos files that I showed you. And now you can see how we can scale this. I don't have to go to each edge node and run a docker compose command to make the application come up and run.

I can simply do it from a centralized location like I'm doing here. I chose to do it through Terraform. You can also do it through, uh, the marketplace here.

I kind of went in the CLI to give you an idea what it looks like on the Edge node, and you can see that the, uh, um, the container image is being pulled, and then they start to come online. Uh, now they're all loading, and then eventually all these will turn green, and then you'll have a, a running application. So here we got a couple that's already came up.

And then, uh, in this next section, I kind of went through the, the, uh, the UIs to kind of show the apps running. Um, I wanted to then pull the each runtime and show the IP address that's on there. So I have a one, a 1 5 8 address, and a 1 0 6 address.

So that would be the target of what application you want to access. So what I'm gonna do here is to show you the URL is I'm gonna open up all these apps. I kind of sped up the, the video a little bit on this one to get there.

And then you can see 1 5 8 was my first node, and I can access Grafana. The application is available there. And then I went in, uh, node number 2, 1 0 6 logged into Splunk.

So basically, both apps are running on both Edge nodes. Um, and then of course, ignition here. Um, I show how we can automate the deployment of Ignition.

It already pre configures with a username and password, and I can take it further and configure, um, you know, MQTT endpoints. And that is my demo. That concludes what I'm showing in the demo here.

I Have a question regarding sequencing. It seems like you have to install Docker compose on the edge nodes before you can install all those apps using Docker Compose. Is there something intelligent on the node side that understands the sequencing of the dependencies, or is that something you have to put into your Terraform configuration or your, your script?

So our, our system is built to queue things. For example, I can create an Edge node and deploy network instances. It knows that the edge node isn't up, so it queues that job.

Once the edge node is up, then deploys the application. Same applies here. Uh, when I deploy the, I, I can, with a single code, I can run the entire thing.

And it knows the wake for, it's kind of a staggered approach. It has to, it knows that it has to wake for, um, the, um, the, the edge note to come up and the runtime to come up, and then the application to be deployed. So it, it knows how to queue up, uh, jobs sequence.

And the, the different compose options you were showing, like the small, medium, large, that determines the size of the, I guess it's a virtual machine on the edge node that gets provisioned for running the docker compose apps, Correct? Yeah, that defines the sizing. So the small, medium and large.

So if you have a very small edge compute, um, you can deploy the smaller. Now those are predefined. However, as you saw, I can clone it and I can edit and even make it smaller, you know, kind of reduces the footprint of the storage, um, you know, even add networks and, and kind of tweak it in a way.

Uh, the, the, the, the remaining element that stays consistent is the actual software that we manage in Care Feed. So that would be the o the operating system's gonna run the Docker. What degree can I, uh, change the size of that, that VM without any downtime?

Or does it require, if I want to add a network interface or change the number of CPUs, does that require rebooting all the apps on that node? Um, so you can make those changes. And then the apps would, uh, kind of go into like a halted state and then kind of, uh, come back online and redeploy.

Uh, what, what sort of, um, uh, SDLC capabilities can you support here? This is a powerful deployment and rollback tool, but I'm just wondering, um, uh, if there's anything inherent in the platform or if, or if, uh, it would be a partner or some third party using, uh, using the API to enable that for, for, for developing and, and managing the lifecycle of, of an Edge app. Um, so that can, you know, that can be a, a, a customer directly doing it from their themselves, their IT department, their developers, um, or, you know, we have partners that are in the ecosystem that are trained and, uh, are fully ready to support, uh, customers and our platform.

Um, so we have it covered end-to-end. And then, uh, we have a very, um, uh, very talented, uh, customer support team that kind of takes over, um, as the, they go into production. Um, so they're, you know, full end-to-end support, either through the ecosystem of partners or, you know, from, uh, our own CX team, which is always involved.

Hi, my name's Chris Clark. I'm a, uh, solutions architect, uh, through the data. I'm based at Kansas City, and today I'm going to be discussing the Data Edge Kubernetes service, and when you would want to, uh, use it.

So that's really what I wanna start with today, is when do you want to use Kubernetes, right? It's, it's very complex. There's, there's a lot of moving parts that go along with it.

And so, uh, really, if, if you look at your stack, is it, uh, a complex application that needs to be to, needs to be managed? Is it a distributed workload that needs to run across multiple nodes? Do you need a high scalability?

Um, then you're probably gonna want to deploy on micro Kubernetes, if not Kubernetes itself. And, uh, one thing I do like about Kubernetes is that it has a very active, uh, community and of developers, uh, around it. So it's very easy to support.

And, uh, there's always new features that are coming out. Now, SATA has our own Kubernetes service built into the platform. Uh, I'm gonna go through a demo of that here in a minute, but before I do that, I wanted to show you guys just very briefly, the architecture.

And the reason is, uh, a, just to let you know all of the, the hard work that went into it, but, uh, b, that, uh, we made, uh, it very simple to use. So while this looks very complex, it's very point and click, create a cluster, deploy an application. However, if you don't want to use the, the data cloud to, um, interact with that cluster, you can do it directly with your, uh, cube CTL commands.

Uh, or you can use Cube CTL via ZA data Cloud. Uh, and there's, there's a lot of, um, ways to interact with that, whether you're using the data cloud itself or using the Kubernetes API directly. So let's jump over and take a look at how to create a, uh, cluster.

So what you're looking at here is the ZA Data cloud, and there's, there's a whole lot that we can do on the left hand side, but we're gonna focus in solely on the, uh, Kubernetes service. So when I hover over that, you'll see that we have a bunch of different options. We can create clusters from the cluster section.

There is a Kubernetes marketplace, uh, section where you could, uh, import applications. You can see what applications have been deployed. Uh, you can take a look at cluster grouping, and you can even add your Git repositories.

Um, so it's really very an all-inclusive system. Now, the creation of the cluster is quite simple. We click that.

You'll notice that we have a number of clusters already created here in the data cloud. I can add new up in the upper right hand side, we'll just give it a name test, go next, select one of our projects, and from here we select one or then three or more nodes to add into that cluster. So we'll just kind of grab three random nodes there, we'll tell, uh, the, uh, the configuration, which network adapters to use for this particular cluster.

Once we do that, we hit next, and then we can finally add it down below. Now, it will take a couple of minutes to deploy. So in the interest of time, we're gonna just jump right back to the clusters here and utilize one that's already installed this Edge AI cluster.

So if we wanted to see additional details, we could actually click into this. But before we go that deep, I wanna show you the actual application deployment. So here's the Kubernetes marketplace I was talking about a moment ago.

Uh, from here, it's very similar to what you, uh, saw with, uh, man's presentation. Uh, so it's a very streamlined, um, uh, experience between different technologies. So if we wanted to come out down here, we could take a look at something simple like, um, a guest book, right?

We could select that, and you'll be presented with all of the options that can be changed. This is done with the helm chart. We can see all the different versions that are available to us, and we can click install there.

Now, if you don't wanna use that, uh, marketplace, and you'd prefer to, uh, use your own helm charts, you can, that can be done, uh, by bringing in your own GI repositories here as a data source. And we can actually see all of the applications that have are already installed. So we have this Heller World application.

If I select that, it's gonna bring up all the information, and we see that there's a service associated with that, uh, of a kind deploy, or excuse me, a service down here, and we have a service count associated with it. And then we have a, uh, deployment above that. So this is the, the basic functionality of deploying a Kubernetes cluster.

It's, as you can see, it's very, very simple. It's not as, uh, big and complex as, uh, you're probably used to with, uh, Kubernetes clusters. Now we can even take this, uh, one step further down into the weeds.

We can go back to our cluster and click on it. And without ever leaving the data cloud, we can, uh, see all of the details about all of the pods, the services, the storage, the policies. Um, so we wanted to take a look at some events that are occurring.

We'll go ahead and click that. It gets presented here, right? The web ui, we can select those to get additional detail.

Maybe we wanna go over here to the workloads, take a look at what CR jobs are running. Maybe we have a, uh, a pod that, uh, is, uh, thrashing that we wanna, uh, investigate or we wanna delete one so it gets rebuilt. We could take a look at all of those from here as well.

Uh, here's the service discovery section. Uh, like I said, you can take a look at the, uh, storage. So you have your persistent volumes, your storage classes.

I mean, this is very, very, uh, all inclusive. So from the data cloud, you can go from no Kubernetes cluster to your very own Kubernetes cluster in a matter of minutes, and then attach it to your GitHub repo, bring in your own helm charts, deploy applications, and you can start development work, uh, I mean within 10 minutes. Yeah.

Question about, it sounds like you're getting ready to, to offer up q and a there. Yeah. Um, so quick question on the scale, you know, sometimes when we're thinking about edge clusters, right, we're not thinking very large scale, but I wanted to ask about that.

Like, if, if we're thinking of pod scale, can we go up to say half rack of nodes, full rack, multiple racks? What's the, what are kind of the upper bounds of what we think of that sida can do in the, the scale of running a Kubernetes cluster? Um, that's really weird question.

I don't have the numbers for that on, on hand, so that, I'll have to answer that offline. It looks like you can go pretty far, right? If we're just talking about the orchestration side, and like you said, we can bolt it into our current GI ops and Yep.

Go from there. So I'd have to imagine it's pretty high. Yeah, yeah.

Over balance there, other than just how much do you wanna manage, right? Yeah. And really all it's doing is managing the, the, the cluster, right?

Those VMs that are actually, uh, clustered together, they're doing all the, the communication back and forth with one another. So there's really not a whole lot of overhead. Uh, so I'd imagine there, yeah, the, uh, the upper limit is the, is quite large.

I think that that highlights one of the things about scalability with Edge solutions, it tends to be a very large number of sites each with a relatively limited amount of resource. So you're not right. You, You wouldn't typically have multiple racks in, uh, in each location unless it was somewhere like an oil and gas exploration.

That's the kind of use case where you might have more capacity in that, um, in the crawler that stood in the geotech stuff. Yeah. Would you, is there, is there an option to even bolt in, like from from a CNI perspective?

Like, can I, can I roll my own CNI in the solution? Or is there something else that is already baked in from a networking perspective? Uh, the, the deployment itself, it's already baked in from what I understand, but, uh, the, I, the, uh, I have not messed with any of the other CNIs, but I, I think it's baked in from the actual creation of the cluster.

And then you were highlighting, uh, something about, uh, edge Hardware that I really like about this solution is I think that Kubernetes really does a very good job at, uh, complimenting edge hardware because it's super easy to swap in and out new nodes or add capacity and scalability, uh, with something like this, you know, have evos on there, you know, plug it in, have it check in, add it to a node, and then you have additional capacity, right? So this is aida, a ZAIDA cluster manager. Um, how, how does this compare?

I mean, I containers is kind of where it's at right now, and as is like the most active development. Mm-hmm. But I imagine quite possibly the majority of your customers right now are still running PMs mm-hmm.

Whether ESX or kbm mm-hmm. Or Acorn. Um, and I'm just wondering how this experience compares if, if, if it's okay to ask that.

Um, and no one's gonna start a religious war with me about it. I'm just wondering, like from a, from, from, from an enterprise standpoint, wherever they're at, they, they're often doing both, right? Um, whether they're moving or not moving, um, from one to the other.

So I'm just wondering how the experience compares, um, if there's multiple payment cla pains in class now, and if that's inevitable. Yeah. So, uh, I, I think that the experience with this Kubernetes piece is, um, much better for developers because they, even though it's being managed by sata, they still have the ability to, uh, utilize the tooling that they're, they're used to, right?

So you can have, uh, your, your admins, uh, managing the cluster and the data side and seeing what data sources that're they're allowing to bring Helm charts in from. But the, uh, at the same time, the developers are able to, uh, use their cube CTL or, or whatever they have integrated with their, uh, their IDs. So, um, you have multiple streams kind of going at once.

Um, right. So I, the experience I think is, is very robust in that regard. Um, when you bring over the, the VMs, uh, from, uh, somewhere else into the data, you, you have to bring 'em in and it's managed and everything's done inside of here.

So, uh, that's a little bit, um, uh, of the contrast between the two, which is why I like this quite a bit. How, how it, uh, allows you to use the tooling that, that you wanna use. Well, that, that's endemic to, to the platform when it comes to VMs.

It's, it's a, I I think it's genuinely a feature of the V of vm and, and that's why it's not really religious war, it's just a question of, uh, right. Of what you're trying to accomplish. Mm-hmm.

So I think, um, that what we talk to customers that the VMs are a necessary evil for them today and will be for the next few years. 'cause they have invested a lot of IP and some of those applications that are running, uh, on those, um, on those EMS and a number of, in very old versions of window. So they're looking for the ability to continue to use those.

But I think obviously, um, everything they're doing that's new and future looking, they're trying to containerize. So all their focus is on putting new apps in some cases, um, rewriting existing apps and putting 'em in, in a container or running them in, in Kubernetes. So it's a combination of we, they want to be able to deploy both types of, uh, runtimes, uh, for the next few years as they migrate from the VM to a, an all Kubernetes are in all containers type of, um, architecture, The Kubernetes, um, version and the image, it looks like it's using K three SI, I assume that's correct.

Um, correct. Is that how close to the current version of Kubernetes, do you have burdens available in the marketplace and could someone roll their own instance of Kubernetes and deploy it to the, the cluster nodes if they didn't wanna use the data's version? Yes.

The answer is, um, um, the, how close we are to the most current one. Uh, I think we're one or two versions behind, um, when it comes to rolling their own, yes, they could. And, and there's a, there's a number of different ways we can support, uh, deployment of Kubernetes at the Edge.

One obviously is one where we provide kind of a end-to-end management. The other is where we provide them with the ability to deploy the Kubernetes runtime themselves. And that is basically where they get to choose which version of Kubernetes they want to deploy.

So that option exists, yes.