Techstrong Gang – October 22, 2024

Hello everybody. I'm Mike Biard. We're gonna be talking about the sum of our insecurities with our friends from Tech Field Day.

Then we're gonna have a little chat about the rise of DataOps and what that means. And finally, we're gonna have some tips about how to be more sustainable. You're watching Textron Gang, we'll be back in a minute.

Welcome back, everybody. We have our guests for the day. We have, of course, way out in California where it's still a little bit early.

John Schwartz. John, how are you? I'm good, Mike.

Congratulations to the Yankees. And, um, I might even support 'em in the World Series this year. I think everybody outside of a small region of Southern California might be rooting for the Yankees.

We'll see. Yeah. Yeah.

Well, I don't know. We'll see about that. There's these folks in Ohio.

Yeah, I'm, I'm suspecting that those of us here in Cleveland may find our strangely supportive of the Dodgers this time around. Um, you know, it, it is a funny situation where we had the top three payrolls in baseball going against what, number 17 or something. And, um, you know, two of the top three are going to the World Series.

It's, it's like, it's like the a LL star team versus the NLL Star team. Um, but at least it's not a subway series. Well pay, I was rooting for that Subway series, but I'll take the Yankees versus Dodgers classics.

I cannot remember how many times they have played against each other on the World Series over the years, but I'm sure this one will be another amazing series. And finally, down in Boca, we have Bonnie. Bonnie, how you doing?

I'm doing Great. Great to be here. Looking forward to talking about sustainable it.

All right. Awesome. Well, let's jump into this a little bit.

Steven. You guys had a security week event and you had a lot of folks come together to talk about these issues. And I feel like we're kind of in a seminal moment here for security.

The bad guys are getting smarter. Our tools are maybe not as good as they used to be, and there's this whole AI thing happening, right? Yeah.

That, and that's, uh, all that is what came up at Security Field Day this week. Um, you know, or last week we had, uh, as you mentioned, we had a, a great group of, uh, delegates in, in, uh, California there for that. Um, you know, talking to each other.

Uh, one of my favorite things about Field Day is when we can have these round table discussions and, and delegate presentations, but also talking to companies like SonicWall. Uh, they had Citrix come in and talking about NetScaler, uh, Dell Security Group and DigiCert. And through it all, you know, there were some trends that I would say, uh, emerged as all as they always do at our field day events.

Um, and, and I think a lot of that reflects the thinking of the industry right now. Um, certainly the, the questions that you brought up, uh, digital trust, uh, is a, is a huge issue for everyone. Um, you know, there's been lots and lots of discussion about supply chain attacks.

Uh, and I don't mean, um, necessarily hardware, though, of course that's something that happens, but also data supply chain, which is something that we're gonna be getting into, I think here in the next block of Textron Gang. Since data underpins so much of what we're doing in business as well as in modern AI applications, you really have to question where does your data come from? Where, what are the inputs that are being put into your systems, and especially your AI systems, and how can nefarious actors manipulate and, um, inject bad data, inject bad results into your systems?

And, and, and once you've got, uh, AI applications up and running, how can you be sure to trust them? I know that's something that came up with you as well at BMC. And then the final big thing that I wanna bring up is this whole concept of the Secure services edge.

This is basically a, um, the next step bet behind the concept, which we've been talking about for a long time. Secure Access Service Edge. And this doesn't just mean that they took out the word access.

What it means is it's a, um, a highly focused effort to make sure that the security components of the stack are designed to safeguard access to modern applications, including, um, cloud native applications, web services, as well as private network applications. And SSE is one of those things that is, yes, a buzzword, but also a very, very smart refocus on security. Because I think sometimes we, we get lost a little bit talking about, uh, security in the bigger picture.

And we lose focus about the fact that we need specific things like, like secure web gateways and, um, zero trust, network access, and, um, cloud access security brokers and data loss prevention and threat intelligence and anomaly detection, and all these very specific tools and technologies. Security shouldn't be just a collection of tools, but it also can't be just a big picture discussion of things. We have to have a combination of tools and practices.

And for me, those are the real themes that emerge throughout Security Field day. What was the general sense of the, the attitude towards all these emerging technologies? And I asked the question, 'cause one of the frustrating things that I've always seen with security is, you look at any survey and everybody's got a firewall and everybody's got A VPN, and then everything else drops to below 50%.

And are, are people realizing they need more than that? Or are they just kind of just checking that box and hoping for the best? Depends on what you mean by people.

Um, I will guarantee that the Field day delegates and other IT security professionals are not just focused on that and not just aware of that, but, uh, keenly aware of that need. However, they're also sensitive to what you just brought up, which is that in the eyes of too many of us, security is still treated like an eggshell. It's still that Castle Walls approach to security, which is, we've got a firewall, we're good here.

And that is really not the case. It wasn't the case in 1994. It wasn't the case in 2004 or 2014, and it's certainly not the case in 2024.

And I think that these folks that we had around the table, I mean, we had some of my favorite security de uh, field day delegates, uh, you know, uh, Jennifer Minelli, somebody familiar here from Textron Gang, uh, Mitch, uh, was there. And, uh, I would say that all of those folks are very keenly aware of the fact that the new applications, the new app stack, the new configuration of infrastructure and SaaS applications, and especially AI needs security integrated through and through this whole concept of zero trust security is something that I absolutely can get behind. It basically says, look, you know, we can't just have a castle wall.

You know, we can't have eggshell, we have to have, uh, security through everything. And we have to assume that every actor could be a bad actor and verify that they are who they say they are, that their, um, instructions are valid, and that the data that we're passing back and forth to them isn't tampered with. Every time I look at a breach these days, it seems like the ultimate root cause is something pretty simple, pretty fundamental.

It's a phishing attack, or somebody lost their credentials or whatever it is. Um, and yet, you know, we'll see all these fantastic stories about, you know, awesome new malware that's been created that, you know, works on a Tuesday every third month of the year. And that gets all the attention.

Are we not focused enough on the fundamentals of security? And part of the, part of our issue is we're just making it too easy for the bad guys. Well, maybe we are.

Um, but again, uh, depending on who we is, I would say that, you know, one of the things that a lot of security pros don't want to do and don't want to focus on because it's not good for them, but hey, I can say it, and that's that so many security flaws are due to people, uh, the, the, the, the users of the application and just an overall lack of security focus among everyone. And, and the problem is that it really doesn't require, um, a massive failure of, of people. It just requires a couple of people to get sloppy.

If we look at some of the recent intrusions and hacks that have happened with some of these, um, major corporations as well as some highly publicized, um, in intrusions on political, uh, candidates, for example, it wasn't that there was a widespread lack of, uh, security culture. Now sure, there was a lack of security culture, but it wasn't that, you know, people were actively undermining security. It's that one person was actively undermining security.

And oftentimes that somebody from a different organization or somebody that feels, you know, maybe it's a very high level person, somebody that feels that they're not subject to the security regulations or they feel like that's somebody else's problem, or simply somebody who's just not with it, not with the times in terms of best security practices. And, and for me, that's the most pernicious thing here. It doesn't take a massive breakdown in your security posture to enable intruders to get in.

It unfortunately just takes one hole in the wall. And then as we saw in, uh, season two of rings of power, the orcs come pouring in and you're done. Okay, well, that's a, that's a bad metaphor, but let me, um, let me think about this for two seconds.

'cause here's what always perplexes me, right? Every day I'll read about how the cybersecurity folks, the toil is too much, the stress is too much, and they are, you know, just under siege. And yet I go sit down and with each one of them, and I have a chat.

And yeah, the one thing that comes across is they are just born optimists. I mean, you know, it's like they expect to win, and yet there's contrary to the evidence every day when they lose. So, did you get a sense from an emotional perspective, where are these folks and what makes 'em keep coming back for more?

Wow, that's, That's a hard one, man. I, I would say that, uh, they are indeed, I, I don't wanna say optimist, maybe that's not the right, uh, maybe techno optimists, you know, there, there're people who feel like the next, um, the next thing we do is it's gonna work this time, this time, for sure. You know, Hey, Rocky, let me, let me pull security outta my hat.

And, and I see that. So, so are you saying that the average CISO is, is is Bullwinkle? Where are you going with that?

Yes, But you know, you know, you think of an optimist and you think of somebody with a smile on his face. I don't think I've ever seen a CISO with a smile on or her face. Well, what was their sense of ai?

Was AI gonna finally save us from ourselves? Or were they skeptical? And we're basically like, you know, this is more, uh, I would say that there's a widespread culture of skepticism of AI among security professionals.

I think their biggest concern is the ways in which AI is going to, um, be used in new attacks. Certainly there are a lot of tools that are leveraging ai. And AI is a very, very useful tool.

I mean, large language models are an excellent way of processing data and in an and abstract and flexible way. And of course that's a great way that, that's a great, um, technology to apply to security. But there's definitely a lot of concern among security professionals and certainly among the folks that were at Security Field Day, that AI is widely being deployed by the bad guys now.

And in terms of, um, developing ever more, uh, uh, I don't wanna say sensitive ever, more clever phishing attacks, um, evermore, um, in incredible fuzzing attacks against firewalls and against applications. And, uh, basically just, uh, multiplying the amount of force that's being put against these, uh, metaphorical security walls. I think that's the biggest concern.

And of course, also, there's a lot of concern about, um, the data aspect. You know, back to that whole idea of, of how is AI going to be polluting our data? How is it going to be, um, polluting the models that we're relying on?

And how is it going to allow people to basically do bad stuff to us without preaching the firewall, just by, by modifying the underlying data? So I I, I'm very concerned about that personally. I, I've already seen that, um, phishing attacks have gone from laughably ridiculous to actually, Hey, that one's pretty good in the last year or so.

And I, I think many of our listeners may have experienced that as well. Um, the days of, you know, ridiculous phishing emails that are obviously not the CEO are, are rapidly becoming, you know, Hey, this one actually sounds pretty good. I'm not gonna fall for it.

Maybe I'll fall for the next one. John, I know you covered a lot of this AI and security stuff, and to Steven's earlier point, um, doesn't seem like any users are particularly concerned about what sensitive data that they are showing in these LLMs regardless of what policies and rules that might be in place. Yeah, you know, it's interesting what, what Steven said kind of resonates throughout Silicon Valley.

I, I believe the tech field day was in San Francisco. I, I remember talking to Mitch about this for Friday's show. And, and what's interesting is this incredible amount of enthusiasm for ai, but then there's that underlying dread over what could go wrong.

And it always comes back to security. Like that is a continuous necessary obsession among those, especially, um, the vendors. And it, it's, it, it always comes down to this one kind of core, uh, flummox points.

We've got security which kind of evolves slowly versus a leaps and bounds trajectory of ai. And the greatest fear is that trust is being undercut through the security and the what if scenarios. And there's this kind of core message at every product announcement or any evaluation of a new technology of, of what could go wrong.

And that always shows up in the surveys, and it shows up actually in the scripts. So, for instance, at the Salesforce event, they spend a fair amount of time talking about security. Um, uh, that was Dreamforce Lenovo last week in Seattle.

They spent an equal amount of time, more time than I was, I was surprised by the amount of time they talked about security. And, and Mike, you, you mentioned, I mean, there's a new model, there's a report, I think from, from VentureBeat of this new model from Nvidia that blows past whatever OpenAI and philanthropic can do in terms of benchmark testing. So again, there's this, this escalation and acceleration of the technology, but the underlying concern is that we're gonna end up with some sort of breach or compromise data that that always is always in the back of the minds of the folks here.

And they have to also address it for, um, obviously for corporate reasons to protect themselves, um, in terms of regulation and, and lawmakers. So there's this, this, this tension that's been going on. So there's a huge upside, but then in the recesses of their minds, there's this paranoia.

All right? And just to make matters more interesting that Chinese are saying that they're using quantum computing to now at least crack at least three encryption algorithms and possibly more on the way. So, um, Steven, are things gonna get worse before they get better?

I'm not sure they're gonna get much worse on the topic of quantum, because remember where they only cracked a 22 bit key, which is not exactly terrifying, but, you know, maybe, uh, but I do think that the security industry is still in its, uh, in its, uh, growth phase. I think there's a lot more to be done. Uh, there's a lot more work to be done, and security professionals are really kind of, uh, arming themselves with a lot of new tools, uh, that are gonna be quite effective, uh, against today's threats, but might not be so effective against the next generation.

So certainly we're gonna be keeping an eye on this space. Um, you know, check out the Security Field Day videos, which are gonna be posted, uh, this week, maybe even by the time this segment airs, uh, on the Tech Field Day YouTube channel. And, uh, keep an eye on Techstrong TV for replays of our Delegate Round table discussions and podcasts from Security Field Day.

All right, folks, you heard it here. Hey, you know, security folks get blamed for just about everything, and they're generally not responsible for any of it. It's stuff that we did, and they're just trying to help us out.

And, um, yeah, I know not everybody loves them. And they might do things that, you know, make it inconvenient for you to access an application. But take a minute and thank them.

Heck, hug me and me. See if they go, man, they might not bite you, but we'll see. Um, but in the meantime, we're gonna be back in a minute.

'cause you know, we're only here 'cause well, the security guys made this possible. 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. All right, folks, we're back and we're gonna have a little chat about DataOps. And if you're not up on it, it's basically the data community is kind of cribbing the DevOps methodology to figure out how to programmatically manage data.

And this is why you see more titles like data engineers these days. And of course, these people are instrumental for AI because I gotta feed, uh, whether it's a rag technique or something else, feeding data to an LLM that customize and extended, and these folks are at the core of this next wave of things that we're doing. Steven, do you think we have a full appreciation for data ops just yet?

I don't think we have a full appreciation for it, but I think that people are starting to get the, uh, data ops message. That's was what I've seen at the, uh, events that I've attended. And certainly in talking to companies that are key in the data space, like BMC, that, um, there is a, uh, a need to, uh, really professionalize the whole practice of data operations throughout the data pipeline.

And as we spoke about previously in, in the last segment, uh, regarding security and ai, uh, data is really critical for ai. Some of these, uh, discussions that y'all recorded, um, at the BMC event, uh, demonstrate that, but certainly that's been the topic of many of the discussions that we've had at our field day events, including our recent AI field day event where we talk to companies in the data space and they're really seeing a, um, a need to sort of look beyond the, uh, introduction to AI that we've all been struggling through for the last year or so, and start kind of kind of getting real and saying, uh, what data is being used to train or to fine tune these models? Um, what data is the, are the models relying on to produce their answers?

And how can we have, uh, really a full circle, um, lifecycle of that data so that for example, uh, we can make sure that data is ingested, labeled and processed correctly, that it's prepared for use in training or fine tuning or rag. And that once the answers come out that we're actually rechecking that and making sure that those answers are correct and that we're sure of what data is being used to generate those. It really is, um, a whole exploding universe of, of data management.

And there's a lot of people really focused on these questions. A lot of the folks that had previously been very, you know, kind of focused in the areas of business, uh, IT analytics and structured data are now, uh, turning their attention and their techno or their, uh, expertise toward, uh, making sure that data is as good as it can for this, uh, ai uh, operated, AI oriented, uh, wave of, uh, enterprise applications. Yeah, there's two things that BMC was talking about that I really like.

And you can find some of those interviews over on six five media, so we invite you to go check that out as well. Um, the first is we can get the right data to the right LLM, uh, in a reasonable amount of time, because the issue is there's so much of this unstructured data out there, and it's just generally been a mess. I mean, I think we do a reasonably good job of managing structured data, but let's be honest, all that unstructured data, it's everywhere and anywhere, and nobody's quite sure what it is and what value it has.

The second thing that I liked about it though, is it also means that, well, maybe we can get past data hoarding, right? There's a tendency right now in the land of AI where it's like, well, I don't know what data's gonna have any kind of meaning or use, so let's just collect it all and store it in a data lake and, you know, just watch the cost go through the roof. And of course, I haven't met a cloud service provider who doesn't think that's a great idea, but the fact of the matter is it gets really expensive in a hurry.

Um, John, you cover a lot of AI stuff. I mean, are you starting to hear more about the AI community focusing in on really the fundamentals of data management? Yes.

Yes. That's, I it was interesting 'cause I watched a couple of your interviews. You did a lot from, um, I think it was Las Vegas and BMC conference, and, you know, it kind of, this might be a stretch, and I think Steven alluded to it in the first segment, but it made me think about data integrity, and it made me think about supply chain managements and what happened in the Middle East.

I know that was something that was years in the making, and it would've been all but impossible to stop. But I think about now all the data points, all the management of data where there are more data than ever in, in this whole idea of susceptibility, whether intentional or or by mistake. And, you know, you saw that with CloudFlare, and so it just got me to thinking about this, and this was very interesting because it's, it's natural ex expansion or a natural, um, evolution from DevOps to DataOps.

I think it's absolutely necessary, and you're right, Mike, um, out here, it's, it always comes down to, okay, well this is all, this is all the different things we can do, but we don't, we we don't wanna land in hot water. I mean, that, that's the press does. And I'm guil I was as guilty as anybody of doing it is, once something goes wrong, you seize on that and you kind of overlook all the good that is, is possible.

And you look at what possibly could go wrong, because at the very heart of the matter, most people don't trust technology when they first encounter it, if it's new, and then they eventually become its greatest advocates. So that's kind of like the path we're taking right now. And we're kind of at the early stages with AI where we're not quite sure about it.

We need some assurances. And once that happens, and once it becomes much more secure than it is now, then it, it takes off. That's, that's when the timeline takes off and when the industry really, really homes.

I, I agree. I think also with, when it comes to data ops, one of the things I just was learning about with, um, the Sustainable IT conference I was at is that, um, not just to save costs, but also to save energy with getting rid of data or not, or just not using it, putting it a lower tier, um, that you're not using regularly can make a difference. That was a topic of discussion in the data and DevOps part of the conference quite a bit about energy efficiency, um, as well as reducing costs and how those two can go together.

So, um, from the standpoint of energy efficiency, I think it's a great idea. Yeah, thanks for bringing that up, Bonnie. 'cause that's been, uh, you know, in my career in enterprise storage, uh, that has been one of the continual concepts that, that we've been aware of.

Uh, people tend to turn up their noses at technologies like tape, but frankly, uh, tape is incredibly energy efficient. And if you can use it properly, it can really be a lifesaver in terms of handling large volumes of data. I know it's not cool and sexy to say, you know, Hey, let's stream this data off to tape.

But if you really have to retain it for long term, uh, that's really the only, uh, game in town in terms of reducing your carbon footprint, reducing the energy required to store that data. And in fact, a dirty secret of a lot of cloud service providers, including a very big one, beginning with the letter A, is that some of their tiers of storage are tape, or at least are offline disc not online storage. And that I think is something that maybe can serve as an inspiration to some of us in terms of better managing data.

And, um, because I, I'll take issue with one of the things that, uh, you know, Mike said there. Um, I'm not sure that we're gonna get smarter about storing less data. In fact, I think quite to the contrary, I think the explosion of the availability of AI is gonna cause us to store ever more data just in case we need it, just in case we wanna train it just in case we wanna run some analytics job against it.

And, um, I think that what we're gonna end up doing is, is increasing the resolution of sensors and the resolution of cameras and increasing data collection. And that's gonna drive us to have to figure out ways of more economically storing data, which requires data management. Wait, I'm hearing that truck backing up in the garage here going beep, beep beep, and it's full of tapes.

Is that how we're gonna do this thing? Absolutely. You can't beat the bandwidth of a station wagon full of tapes.

You know what I mean? I think that one thing that is changing though, is if you look at the history of, uh, data processing, it was all very much dependent upon batch oriented kind of things that we're fairly good at. But all this AI stuff, or at least a, a good portion of it needs to be, uh, under a millisecond.

So we're talking about processing massive amounts of data in real time. Are we capable of doing that at scale? I'm not sure that we are capable of doing that at scale, but I sure think we're gonna try it.

Um, you know, one of the things that's been interesting to me to watch this last, uh, the last few years, uh, you know, kind of putting on my old guy hat here is the reemergence of the term ETL, which is a, uh, mainframe era term for basically preparing data to be used in a batch process. And I think what we're seeing in many cases when it comes to AI training is, uh, an idea that we have to have this big ETL process. Maybe they don't call it that, but that is absolutely what is happening.

When companies are preparing to train or fine tune AI models, they are extracting data, they're transforming it, they're preparing it, they're categorizing it, they're loading it, and then they're saying, okay, training model, go at it. But then we look at, you know, how, um, these things are evolving. You know, you look at, uh, at rag, I think that there certainly is an an ETL aspect to preparing data to be used for a retrieval augmented generation.

I think that's implicit in the architecture, but I think that there's an, an idea or a, or a, or a desire to get back that and get to what you're suggesting there, that there would be a lot more realtime processing of data. We're certainly seeing that on the iot and edge space where companies are using, um, IOT sensors and cameras, and they're doing realtime processing of that data. I mean, literally real time.

I actually just over the weekend, uh, got frit up and running to do realtime, uh, processing of video camera data in my house. Um, I think you could call that absolutely an ai, uh, realtime processing, uh, uh, application. And I think we're seeing that happening a lot at the edge.

And, um, increasingly I think we'll see it in, in, uh, corporate data and analytics as well. All right, for all you wiper snappers out there, ETL stands for extract, transform, and load. So just so you know, and to your point, I was talking to somebody about this the other day and they said, well, actually the whole thing has been flipped around and it's now load, transform and extract.

So did we flip it around? Hmm. That's an interesting thought.

I'm gonna have to give that a, I'm gonna have to give that a a little bit of consideration. Thanks, man. All, um, John, back in the day, and you're in the valley, and you know, allegedly all the AI companies are the hottest thing going, but it seems to me that the companies who process data might wind up being the real winners here in much the same way that, you know, the guys who sold shovels for the gold Rush made all the money, right?

It, that's usually what happens, right? And also we start thinking about how like a decades old industry, something like even the nuclear plants, right? With all the activity that Amazon, Microsoft, and Google are doing, getting into that in terms of energy efficiency and managing data.

So yes, the old industries in the ends benefit from the new industries is, is kind of like a third party partnership. And I, I think that actually is going to be the case. So we, we will see a number of AI companies that are name companies now, or emerging companies that are gonna go by the wayside, but those who actually are, who rise with the tide might be some of the more venerable companies, um, who we don't even think about when we think about ai.

And that's just a, that's a consequence of all, almost every industry. And when it grows, It's, it's kind of like the same thing with those guys who make the pros. I mean, they get all the noise out there, but they're not really building the models for the most part.

I mean, they make a few here and there, but, um, I guess Steven, what's your sense? Do we, are we too focused on, you know, the open AI of the world and not enough on the infrastructure? Uh, yeah, absolutely.

Um, where, you know, I don't know if it's about, I don't know if, if I, if we wanna make our metaphor shovels, um, but I will say this, that if, if we decide that the gold is in the data, then the companies that are able to, uh, understand, transform, um, process and analyze data, that's where the money is. And so I'm actually pretty bullish on some, uh, old familiar names. Uh, you know, you mentioned BMC, uh, Qlik, uh, Delphix, companies like that, as well as some of these modern names.

You know, you look at, uh, company like Salesforce, I mean, that's where there's so much of, uh, modern enterprise data as well as a lot of these companies to, uh, that are, that are figuring out ways of transforming and processing data. You know, you look at things like ServiceNow, um, you look at some of these modern low code, no code and analytics, uh, processing things. And of course, uh, I wanna bring up, uh, some of the next generation companies that are already deeply involved in enterprise data pipelines.

Companies like Elastic, um, you know, min io, uh, that are out there, uh, storing and transferring and analyzing data. Um, in, in fact, we recently saw, uh, Satter another company doing some really interesting things, um, doing some analysis to what, what you were saying earlier, Mike, about taking unstructured data and trying to figure out the metadata, uh, dynamically and autonomously. So yeah, I'm pretty bullish on the companies that are touching the data and transforming the data because I think that's where the next wave of interest and, uh, technical development is gonna be.

Well, guys, I'm gonna end this conversation here because if you think back in time, and we're doing this for decades upon decades, and the one constant has always been, it's about the data, stupid. We'll be back in a minute. I'm Bonnie Schneider, sustainability contributor to the Techstrong Group.

I'm excited to introduce you to a groundbreaking new initiative from Techstrong Research, the sustainability pulse meter. The pulse meter offers valuable insights into how environmental responsibility factors into tech purchasing decisions for key players in the industry. Position your company as a leader in the industry and differentiate from your competitors with a sustainability pulse meter offered exclusively from Techstrong Research.

Hi everyone. Welcome back to the Techstrong Gang. org held their annual conference along with, uh, Delphix and Perforce that had a data ops, uh, day as well.

It was really exciting because the amount of people that were there doubled from this year to last. So that shows the interest in sustainable, it is really growing, and there were people from all sorts of corporations that maybe you wouldn't think of, like MasterCard, PepsiCo, all the way to, well-known software companies as well. So the reason I'm mentioning all this is being more sustainable in it is becoming top of mind, but for developers it can be overwhelming because there's a lot of pressure on how do we code more green, what can we do?

So I decided to break it down and show you at least five simple, maybe not even obvious ways that developers can be a little more green in their IT practices. Hi everyone, I'm Bonnie Schneider with your ecotech Analyst Insights ready to green up your IT game. Let's explore five ways IT practitioners can drive sustainability in their daily operations.

These are strategies that go beyond the obvious and are within teams direct decision making authority first tip, code smarter, not harder. Embracing low code, no-code platforms can significantly improve energy efficiency and software development. By eliminating redundancies and leveraging low-code platforms, IT practitioners can reduce power consumption by up to 50% in software applications and cut development time by up to 90%.

Second, follow a smart shutdown protocol. Too many devices are burning energy 24 7, even when no one's using them. Configure systems to automatically power down when idle and wake up only when needed.

This helps to reduce energy drain across large networks, particularly in offices with hundreds of endpoints. Third, optimize data storage. Not all data needs to be kept in high performance systems.

IT teams can classify data based on frequency of access, also known as data tiering, shift cold data to lower energy systems that require less power. This reduced costs and EBIT extends the life of more energy intensive resources. Fourth, leverage AI for good.

While AI itself consumes a lot of power, it can be a game changer in optimizing energy use. IT teams can create intelligent management policies using machine learning. This data-driven approach has been shown to reduce energy consumption by up to 25% in data centers.

AI's ability to identify inefficiencies and optimize performance makes it a valuable tool in driving sustainability. And finally, consider repurposing outdated hardware before recycling it. Instead of immediately discarding older servers or equipment look for new ways to use them, how well consider these items for tasks like backups, archival storage, or internal testing.

This extends the hardware's lifespan and delays the need for recycling. By targeting operational inefficiencies and crafting smart policies, IT teams can reduce energy consumption without overhauling entire systems. It's about making intelligent incremental choices compounding over time.

org. One of the reasons the green coding and being more green in it is escalating. And this was a big topic of conversation since this conference was global, and I spoke to people from all over the world.

org is working on. And they have metrics on their website and lots of tips and resources. That's why I mentioned in my piece to check out their website as well as, uh, the Green Software Foundation.

Just, uh, just from covering this sector of the industry, I can see the growth continues and the interest continues, as I mentioned, not just from tech companies, but anybody that's doing manufacturing and shipping. Like for example, one of the companies that was there was Nordstrom's. And if you're a female like me, you're familiar with that store.

But, uh, they were talking all about how do they make their their supply chain more sustainable and, and what are the techniques they do with that. So it really, and I, I met their IT director for all of Nordstrom's, and we talked about that. So it was really interesting to see how this topic touches on so many different sectors all relating back to tech and to it.

Hey, hey, I've been in Nordstrom's. They have a lovely pub where you can watch a ballgame. Now someone else is shopping.

I Need, oh my gosh, you too. I, let me tell you, I am a Nordstrom believer. Almost everything in my closet comes from there.

And, uh, this goes to one of your points, actually, your last point you just made Bonnie, which is repurposing outdated hardware. Um, my wife may not like it, but I'm a big fan of, of buying high quality clothes that last a long time and, uh, wearing them for a long time. Uh, so yes, absolutely, uh, Nordstrom for The win.

Yeah, they were honored, um, along with other companies for the way they're, they're actually managing their supply chain, but also how do they dispose of, of, of e-waste. You know, it's a big operation. Every company is thinking about that.

And I, I spoke with someone from PepsiCo Europe who told me one of their biggest concerns is agriculture, which I was kind of surprised at first. That's not what you think of with PepsiCo, but then he was talking about Frito-Lay and other companies that they own. So, um, the tech supply chain, um, is just one aspect of it, but using sustainable it as an overarching, um, theme is just really incredible when you see it all in one place and all the, all the interested parties talking about it.

I think this is gonna be something we'll be talking about more. I know I'll be talking about it more, but it, I'd be interested in hearing your perspective of if you've seen this movement grow and, um, some of the techniques that I listed, uh, anything out there that maybe you didn't know or you think is something that it's underutilized. Yeah, I, I wanna get back to that repurposing concept because we've definitely heard about this more and more in enterprise tech.

In fact, if you look at the overall sort of the macro picture of, uh, it spend, you'll notice that it spend has slowed down in the last couple of years. One of the reasons for that is because the hyperscalers and many enterprises as well are doing exactly what you suggest. They are trying to extend the life's lifespan of their servers.

They're trying to repurpose old hardware and rebuild systems, um, and, and, and, and, and reuse things that, uh, maybe didn't have a use previously. So, um, you know, a very concrete example is, um, I was working with an enterprise where they took their entire, um, uh, VMware estate and repurposed that into a software-defined storage, uh, infrastructure to support their new, uh, it, uh, virtualization platform. I think that's really, really smart because you can get some serious long-term lifespan out of it.

Uh, IT equipment. I just realized that the web server I'm using for all of our, uh, web, uh, applications, it's eight years old now. I didn't know that, but, um, still runs fine.

Uh, nobody would notice the difference. And I think that we're seeing that if you're smart about reusing and repurposing old equipment, you can really, uh, get some some huge benefits. Another thing that I, I wanna call out on that note as well is, um, I, I was pretty bullish on the CXL technology, which lets you access memory instead of over a memory bus over a PCI bus.

Sounds pretty esoteric and technical, but one of the emerging applications for that is reusing outdated DDR R four memory in modern servers as, uh, to extend not just the lifespan of that, uh, memory, which will probably just go into a recycler or a landfill, but actually to increase the capabilities of those servers in the AI world. So instead of having a, a server with, uh, just, you know, maybe a terabyte of locally attached memory, you could have a server with a hundred terabytes of, uh, CXL attached memory, and that's a much, much better server. So sometimes you can actually repurpose, uh, uh, hardware in a way that even new hardware can't touch.

So Steven, you like your tech, like your clothes, you basically want high quality that lasts a long time and fashion be damn. Absolutely, my friend. Absolutely.

Um, body's point, one of the things that I feel is underutilized is this whole movement around finops. And as far as I'm concerned, if I can focus on cost and I can drive down the amount of compute that we are using, I will help the climate, right? Because ultimately those two things are kind of linked.

Bonnie, do you think the finops community and the sustainability community or talking to each other? Yeah. Or where, where are we in This conversation?

Yeah, their, their, uh, partnership is, is under heading of Green Ops, and they are definitely working together. In fact, that was, I had the privilege of, of doing, hosting a fireside chat with the chief sustainability officer of Dell. And we, I had prepared a few questions and just like everything happens, you know, when you're live, um, we had more time, so I thought of some more on the fly.

And actually that's when I got the most interesting answer because we talked about that, and she said that just starting in this past year, that whenever they're talking about being more green and everything is now with accounting in play, they're the, the money and they're, they're working together the CFO and her, and it's, it's more in sync than it ever was before because of that. So in real time, that is absolutely happening where the Green Ops, uh, umbrella is working together with being more financially, um, you know, uh, effective as well in, in terms of saving money. And she said that that's come up just this year and it's going to continue because of, as I mentioned, they're gonna have to do more ESG reporting.

So, um, that's a timely question. So is it Green Ops because of the color of money, or is it because it's One way to look at it. All right, folks, we're gonna end this conversation here, but we have more to come on this very topic and other cloud related topics later this week.

Steven, what do you got going on? Well, we got Cloud Field Day live streaming on Textron tv Wednesday and Thursday tomorrow and the day after, um, you'll, uh, be able to see, uh, the latest in, uh, cloud infrastructure and platforms. Uh, we're gonna hear from a, a little company that's getting a lot of news VMware by Broadcom, along with, uh, platform nine.

Uh, speaking of finops, uh, who are very, very much focused on that topic as well as Qumulo, which, uh, goes to some of the points that, uh, Bonnie made in her, uh, smarter not harder, and optimizing data storage, uh, envir, uh, discussion. Uh, also, I'm, I'm really thrilled that we're gonna have some more, uh, delegate presentations and round table discussions, uh, check out, uh, my coverage of that, um, uh, the, the overall themes from that episode on, um, or that event on the, the next Tuesday episode of Textron Gang. All right, folks, you heard it here.

Hey, there's always something good happening on that Tech Field Day site, so by all means, go check that out. Bonnie, thank you for your report for the week. My pleasure.

All right, and thank you all for watching the latest episode of Textron Gang. Please stay tuned there as an awesome lineup of content right behind us. And once again, thanks for watching.