HPE and Juniper Networks Merger: Implications and Insights | TSG Ep. 871

Hey, everyone. The HPE Juniper Networks merger is on. You're watching Textron Gang.

Hi everyone, it's Alan Shimo for Textron Gang. Welcome to our Tuesday show. We've got some great stories to cover today.

I mentioned the HPE Juniper merger. We're gonna be talking a little bit about Open Telemetry and the infinite workday. We've got a All Star panel, an epic panel to go over to talk about this today.

Let me introduce you to them, um, as is our custom, our written, you know, panel members who've been here before. We're not gonna spend a lot of time introducing them, but real quickly, we've got Steven Foskett, JP Morgenthal, Mitchell, Ashley, Barney Schneider. Let's call out the new guy.

It's his first time on Techron Gang. He is Futurum, COO friend of ours, Dan o Dan O'Brien. Dan, welcome to the Gang.

It's great to have you on here, man. Yeah, great to be here. Thanks, Alan.

Appreciate you having me on. My pleasure. Hey, Dan, be being, it's your first time.

Just real quick, if you could give people a little bit of your background so they know where, where you're coming from. Yeah, absolutely. Yeah.

I've spent my whole career in tech, uh, spent about a decade in semiconductors, um, semiconductor industry, uh, about five years on Wall Street. Most recently. Spent about seven years running the Annals Relations Organization at IBM and joined in January as, uh, Fu and Group President, COO.

Excellent. Hey, man, it's great to have you on Dan L. All right, let's jump into things.

So, you know, this wasn't a surprise to me. I knew they were going to somehow settle it. I just didn't know how, but Mike, HPE and Juniper are a go.

What's the deal? Yeah. And as these things go, this one's a little more peculiar than most.

Apparently there's some licensing and source code from the AI stuff that HPE built, and then they're gonna get rid of a business unit that seems to be just basically hanging off the edge of HP as it is. But Steven, you track all this a little more closely than I do. What's your take?

Well, it's an interesting, uh, situation, as you said, because of all of those reasons. I mean, the big news, and I think the thing that we should really focus on is that this is a big victory for HPE and in poses a significant, uh, challenge to Cisco. Finally, uh, Cisco is the undisputed 800 pound gorilla of the networking space.

They have fought hard, uh, whenever there has been a new networking, uh, opportunity, market opportunity that has appeared, uh, lately, they've been really battling in the AI networking space, both in terms of networking for AI and using AI to manage networks. Now, one of the big competitors for, uh, the, the latter there especially is, uh, Juniper with their incredible missed AI operations AIOps, uh, software. And that is one of the angles that has been, uh, taken on by the DOJ here.

So, so first off, um, what does this mean to, to HPE? Well, it means that HPE is gonna be a credible competitor to Cisco at the high end of the market, which is good for the market, it's good for customers. It's certainly good for HPE, and frankly, it'll probably be good for Cisco long term as well, because, you know, everybody benefits from strong and healthy competition.

But what is the cost? Well, apart from, uh, what is it, $14 billion? The cost is that, uh, HPE will have to offload a couple of elements in order to make the DOJ happy.

One of those elements, as you mentioned, is the instant on Aruba networking, uh, platform, which, you know, that's sort of an interesting thing That is a small, uh, product for small businesses. It's an interesting one. It's a good one.

It's one I've actually personally used. And frankly, I think that it will be a, um, a useful acquisition for some competitor in that space. Um, though pretty much everybody in that space already has something going on there.

Uh, but I think that, I think that it'll be scooped up pretty quickly. The big thing that's got my head scratching is the AIOps offload. So a as you said, the agreement says that HPE has to offload, um, or not really, uh, partially offload enable other companies to use mist AIOps source code.

Essentially, they're gonna have an auction where the DOJ will allow up to three competitors, uh, that they are allowed to veto, to bid on access to Thet AIOps source code, and access to some key engineers who developed it. Now, they won't actually take it over. They're gonna allow two buyers that will be actually able to take that source code and solicit and, and hire those engineers, but they won't get the missed name.

And HPE will also be able to continue with this as well. So essentially what we're seeing here, if this goes the way that, that it might go, I is that Juniper missed, AIOps might become the defacto AIOps software in networking, uh, if let's say a company like Cisco or Arista was to be the winning bidders on those licenses. But I guess the question is why would they want it if it's not exclusive?

I, I guess, uh, the only thing that they're really getting here, apart from the source code, is the access to those key engineers. But there again, they actually have to hire them. They actually have to attract them and bring them in.

So it's a bit of a head scratcher. Yeah, it, it, it's definitely unusual. So Steven, I have a slightly different take.

I don't think this was as much about making HP compat competitive with Cisco as it, from the DOJs point of view, as it is setting up a market where it's HPE and Cisco and just HPE and Cisco. There's the who you mentioned, Arista. I mean, I think between these two companies, they probably glom up 70 to 80% of the market.

That's a two company market in my mind. No, because the leader in AI networking is a company you may have heard of called nvidia, and frankly, all of these companies leverage Broadcom's switching silicon. So I think there is a competitive market, and, and Arista is a lot more powerful than you might guess In terms of market share.

Where are they? Um, distant. I guess it depends on the market, but, uh, yeah, they're, they're a solid competitor, uh, but they're not near Cisco.

Okay. Then the other thing is though, I'm sorry, go ahead. Wouldn't Cisco and Arista be an automatic veto or, you know, are, are they allowed to get that source code?

'cause at the very least, they, they got it. They would just slow HPE down like crazy. Well, it from the sound of it, well, this is another weird thing.

It sounds like it has to be two, it can't be one buyer and it can't be three buyers. It has to be exactly two buyers, which makes me think they know which two those are. And I suggest that it's gonna be Cisco and Ata.

To me, it's such an unnatural act though. Why not just open source it and give it to a foundation In a way they almost are open. So like they, they're, they're going to, you know, kind of pseudo open source it by getting these other folks in.

And it's gonna be like a fork, right? Where you're gonna have, you know, everybody's starting from the same place and then the, the buyers will all take it and they're kind of unique. Well, not everybody, just the three companies, if they open source it, that opens it to a whole new, anyone can go in and try to do something.

The first projects were, you know, there are two or three main contributors and not a lot else going on. Maybe they don't want Chinese companies to take it either. So as part of That and that, that, you know, what, that very well may be the case, Mike, right?

That that is, and I, I think that's what the veto is all about, is to make sure that Huawei is not the company that takes it Or bite dance. Just kidding. Just kidding.

Um, so when does this deal close? And it's unclear. I don't think they actually have a hard date on it yet.

Steven, did you see a hard date? I'm scratching my head. I don't know.

I think it's gonna close pretty quickly though. My contacts with the folks at HPE, well, first they are excited. They are happy, they are ready to go.

And so I think the answer is as soon as humanly possible, because HPE wants to run with this. Well, I'm sure they will hope to announce it last week at Discover. Let me ask this question though.

So I've been looking at this, you know, we're gonna kick Cisco's butt for the last two decades plus, and Juniper couldn't do it, and HPE couldn't do it. And what makes you think that Juniper plus HPE is gonna make a fundamental difference, Steven? Well, I think that it will make a solid difference simply because of, um, the fact that Juniper already has a really good products and really good customers, and the HPE will automatically get product and customer access like they've dreamed of for years.

I think that, that this, there's so much synergy here. There's actually surprisingly little overlap considering how strong HPE is in sort of the broader picture of networking. When you look at the networking verticals where Juniper plays and the networking verticals where HPE plays, there really isn't as much overlap as you might think.

And I think that is gonna be hugely additive. I think HPE made a really good deal here. You know, speaking of a good deal, I remember a time, Dan, you were on Wall Street, right?

$14 billion. That's a big deal, man. 14 billion in today's world.

Nah, it's 14 billion. It's not like, it's not like, uh, Maan is building a new city in Arizona or something. Yeah, Yeah.

Uh, it's not a big number anymore. I mean, you've seen, uh, you know, VMware, you know, Google, you know, in their acquisition for Wizz, I mean, uh, the IBM Red Hat deal. I mean, there's been a lot of deals that have gone north of that.

Nothing north of a hundred yet. Uh, maybe that's the ceiling, uh, the kind of new ceiling at this point, but, uh, maybe, yeah, more of a mid-size acquisition for tech these days. But doesn't it, I look, I'm a child of my age, right?

com, you know, bubble came on the scene, Juniper was the greatest thing since sliced bread. Seeing it go for 14, a mere $14 billion seems like a bargain to me. I Think, doesn't it really also, you know, go to the state of, uh, movement to the cloud as a whole in general, away from data center, I mean, infrastructure build out, uh, you know, where companies were spending a lot of that money on building, what, what did we lose after COVID?

We lost people going to offices and we lost build out of data centers, right? With the cloud. So you see a diminishing number of, you know, enterprise buyers for this technology at this point in time.

And you have companies who are now owning that technology for themselves that own the entire supply chain that do build out data centers. So, I I, you know, it's not, it's not like Juju did anything wrong. I think the market changed on them and they just, their buyer is Dissipating.

It's true. That's true. com bubble, I mean, the amount of money pledged to these, whatever you want to call AI data centers, is, is staggering.

Is there a place, is there a place for Cisco, HP and Juniper? D hp, Juniper, I assume would say hp. Cisco's Already in there.

Cisco's already in there as a partner for a lot of these. But, and, and like I said, you know, the Amazon and the Google, they have their, they, they're their own supplier, right? They own their supply Chain.

They own for a lot of on Broadcom silicon, as Steven mentioned, certainly. And hey, networking and the enterprise isn't going away. And that's, that's HB strength.

But also you get the wireless, you get the core networking outta Juniper. It's a great match. I think it bolsters up.

I mean, HP is acquired who Threecom and, you know, Meraki untold number of, uh, companies And don't think that, um, you know, Juniper was asleep at the wheel here. They're not some lumbering giant who missed the phase. They are really competitive in the AI data center.

And, and as I said at the top, Juniper's missed, AI Ops is probably the best AI ops platform in the industry, and they have some of the greatest engineers. Juniper has really been running forward to try to move into new markets. And that's all HPE now.

Um, I think this is just incredible. I think that's the bigger picture, Steven, to, you know, take a step back. This, this is a good deal.

It's made sense for a long time. You know, it's great to see some of the roadblocks cleared, but, uh, you know, the competition for these companies are the biggest companies in tech and, you know, getting to a size and scale and a portfolio breadth, uh, that could be competitive with Hyperscalers and Nvidia. Uh, I mean, you know, certainly I think as we've seen the AI data data center build out, networking is in many ways become kind of a critical bottleneck.

And, you know, bringing the compute side together with storage on the HP side now with a more enhanced networking portfolio, uh, I mean, you certainly, if you look at what HPE was talking about last week at Discover, you know, it was all about networking, AI data center. Uh, let's not forget AP HP's acquisition of Cray in the high performance computing space. I mean, all of these things really do build a more compelling portfolio out.

I think the big question for them is, you know, how much of the AI processing and networking is gonna happen, you know, in the cloud versus not in the cloud. You know, that, that's really kind of the big question for this combined entity going forward. Yeah, I agree.

Let me bring up another thing then. It's something a hark back to something I said right off to, to Steven, happy for HPE and Juniper and I, and Steven, you're right, a good, a good competitor is gonna bring out the best in Cisco. Part of the DOJs antitrust mission is to make sure we have markets that are open and allow for new competitors with ai, especially with these kinds of deals and the kinds of money being invested, the capital requirements here.

Is this, is this just a big boys game? Is this in, you know, the gen, the new version of the gentleman's clubs where it's gonna be impossible for up in commerce to break in? Are we, are we setting ourselves up for that?

I think you look at all the big markets where CapEx is really the name of the game, Foundry hyperscale data centers, they've all really gravitated to, you know, one dominant player with a couple other strong competitors, right? Um, you know, at the level of spend, um, that, you know, these, these things require, I think it is gonna be, you know, you know, some sort of oligopoly type market setup And that, that's actually the word Dan on oligarchy kind of, you know, Steve, I think you're on mute, Steven. Sorry about that.

I, I'll just point out right now, in terms of the AI networking market, it is Nvidia that is the dominant player, even in ethernet. Nvidia rules, the AI interconnect. So they've got ethernet and InfiniBand, um, everybody is gunning for them.

Cisco is, uh, HPE is Dell is, that's another company we haven't mentioned. Dell is really trying to sell into that AI data center market. I think there's an opportunity to have some real competition there, and there's huge amounts of money being invested there, not just on GPUs, but on networking hardware.

I think the proof in pudding, proof in the pudding is gonna be whether or not prices actually move. Because so much of what we see among these cloud infrastructure providers is the prices don't move all that much. And it's a fine line between what Dan's calling and oligarchy and what other people might Oligopoly, oligopoly Oli.

Okay. So he's combining, I think there's another part of this networking. The, the real boom in networking in data centers is EastWest traffic, GPU to GPU, and, uh, there's a lot of, well, That's where Nvidia shines.

Yeah, that's where Nvidia, there's a lot of interesting startups there in, um, Juniper, I believe it's their ex series. They've got some, some devices that are specialized in East West. I'm not sure if they're that heavy into GPU traffic or not, but that could be an opening for them as well in the data center business.

Listen, the Advent Center, Nvidia has become so dominant that, you know, the big problem I think we have in the market is that we really need one good, good alternative. And I think right now we've got a large number of kind of, so-so alternatives and, you know, this deal and, you know, similar deals to it, it, I think are really good for the market because ultimately we need a good NVIDIA competitor. And there's probably not gonna be a market where we end up with 10 good NVIDIA competitors.

A market where we end up with one or two is probably the best that we could hope for. And if you're interested in the technical aspects of this, I'll just put in a quick buzz. Um, we've actually had all these companies present IT networking and AI infrastructure field day.

We've had, you know, uh, Nvidia, HPE, Juniper, Arista, Broadcom, Dell, they've all given their pitch. Cisco Too. Steven, Cisco, I'm sorry, I I'm sorry I missed it.

It's so many. Yes. And, and, and if you look at those videos, you'll see the apps, the aspect of each of those products.

They're all available on Techstrong tv. All right, that's our plug right there. Hey, let's break on this sec.

On this, uh, block. We're gonna come back and talk about open telemetry consumption, energy consumption, and resource consumption. You know, someone's gotta pay for it.

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Contact us today and tell your story to the world in the most powerful way with Techron Group. Welcome back to the Techron Gang. We are talking about energy use and in the past of our ecotech Insight segments, we've been talking about AI and green it.

But here's something we haven't really dug deep into observability and took a closer look at Dynatrace and what they're doing to improve the modification of energy consumption for open telemetry. Uh, particularly based on a talk that they they had at CubeCon in Europe. And you'll see a little bit of that as well as a closer look at the analysis behind this.

New idea. Tools meant to monitor system efficiency are now being scrutinized for their own environmental cost. Open telemetry widely used for observability is emitting more than just data.

It's consuming energy, memory and compute at a scale that's prompting a second look at CubeCon Europe. Dynatrace's, Adriana Veia presented benchmarking results using Kepler, a tool that tracks energy output in Kubernetes pods. Her findings, custom-built open telemetry collectors used less memory and less power than standard versions according to the CMCF.

This type of observability framework has more than 500 active contributors. With adoption increasing, the focus is shifting to its own operational overhead. Framing performance around emissions resonates more with developers than cost metrics telling a team their app emits as much CO2 as 30 cars due in traffic.

Well, that gets more traction than citing cloud costs. Dynatrace is also leveraging Cube Green, a time-based auto-scaling tool that lets Kubernetes pods sleep during off hours. They've integrated it into internal observability pipelines without relying on Prometheus to cut back on processing overhead and reduce overnight idle usage.

As telemetry infrastructure becomes more embedded in critical systems, its own performance characteristics are attracting greater scrutiny. The focus is shifting from what observability tools deliver to how efficiently they operate. So it's an exciting movement with a Dynatrace and the efforts that they're doing.

And they, um, also shared some other information at CubeCon. And Mitch Ashley was actually there, and he's the person who, uh, told me all about this. So Mitch, I'd be curious to see, um, and hear about your thoughts on it.

Yeah, no, the Dynatrace folks, well, and Adriana Vila who gave the presentation there, uh, fantastic speaker as well. It's interesting. Open Telemetry has become sort of the Swiss Army knife of, of not just monitoring, but metrics and measuring and collecting and then presenting that into whatever tool, uh, substrate that you want to use that in.

And, and it could be anything from what are the effects of the user experience, what is the performance of servers? Now we're talking about energy consumption. So the Open Telemetry, open source environment has, I don't know what the total number of companies now.

It's well over a hundred that are contributing to that and are part of it. It's one of the most healthiest open source projects I think that we have. And they've started to really focus on the sustainability factor of it.

'cause there's a great place to take both existing telemetry data, but also take in new sustainability, uh, telemetry data from tools like things like Kepler, they can integrate with, uh, with Open Telemetry or Tel and really give you a better picture. There's things that they've added into, uh, Kubernetes, for example, turning down clusters during off period of hours that it may not already be configured for. You can, you can just imagine the number of places that we could save money, uh, by turning things off or, or putting into more of a, a standby mode.

They're also working on some of the semantics that they have in their model, their data model of how they represent this information. There's a lot of really good foundational work going on, and I think it's very much in line with where companies are looking to, how do we measure the results of what we're doing in sustainability and kind of demonstrate the actual value of those efforts. And, uh, Tel has a big role to play there.

Alan, is Alan, is this too much of a good thing? And I'm laughing 'cause I'm kind of like thinking back for the last decade or more, banging a drum about let's instrument more applications, instrument more applications so we can do DevOps. Well, now we have, Yeah, because it's open.

So two, there's two lessons there, Mike. I'm gonna hit 'em both. But Mitch, to your point, open Telemetry is actually the second largest project in the CNCF, which has over 200 projects, right?

It's behind only Kubernetes itself. Yeah. Right?

That, that gives you an idea of how Open Telemetry has, has cut in. But to me, this is, open Telemetry is a poster child of the, just because we can, doesn't mean we should school of thought, right? All of a sudden we can measure everything.

We could monitor everything, we could log everything, right? The Splunk School of Thought, and no one really thought about, well, what does that really entail from a cost point of view, right? Well, in Splunk, the money, how much did you pay for storing all that data?

That very quickly became a thing. But with Open Telemetry putting all these collectors all over, no one really thought about the con energy consumptions and the cost behind it. We were so enamored with just being able to do it, right?

So it reminds me of the old security adage, right? That I've learned a long time ago is people don't care. Vendors don't care about security until their customers do.

Vendors won't care about their open telemetry consumption kind of graph until their customers do. Until someone says, oh my God, look how much I'm paying. You know, I, I, someone shows me how much I'm paying for it and I do something about it.

And I, I think from, you know, this report an excellent video, Bonnie, from it, we're, we're starting to see, at least Dynatrace has gotten the religion right. They realize there's an opportunity here. Kudos to Dynatrace of saying, Hey, someone should be measuring this.

Someone should be measuring what we're doing around energy consumption all along with our infrastructure. Because even though we're, you know, rushing headlong into building these AI data centers with hundreds of billions of dollars, someone's gotta pay this bill month in and month out for what you're using. That's the model.

And Well, is it that the costs are, are the problem, Alan? Or is it that we're not getting enough value from what we're getting for those costs, right? I mean, you know, collecting all the data is great.

Maybe we're not doing enough with it. I mean, I, I do feel like, you know, the complexity of these, you know, enterprise infrastructure estates has gotten to the point where, you know, the only way really to optimize it is gonna be through automation and ai, you know, and, you know, getting these data points really allows us to, you know, take our a PM data, our observability data, our cloud, you know, carbon footprint data, our finops data, and really get to a point where we can kind of define for any given workload, what is kind of the optimum mix of all these trade-offs we make across performance and cost and security. I, I think it's kind of a double helix where, okay, this is what I get out of it.

This is the good right? That, that comes out of it. This is the cost, and someone's gotta make that determination is the good worth the cost.

So I, I, I worked with a, uh, I worked with a client, I developed their, uh, observability strategy guide for them. They're a, a platform company. And, you know, this was really right before AI became mainstream, which oddly to say was 2023.

So I'm writing this in 2023, and nobody's saying, Hey, let's throw a chat GPT at this yet, right? So it, that's how, that's how early on in this game and how quickly this is really erupted, right? Um, and you know, the reason why that guide was important is because for the operations team, they were turn, they, they were using Datadog and they're turning on all these sensors.

But the truth of the matter is, before you turn on a sensor, you really need to think about what are the important metrics and what do I, and the, and the reality is that for a brand new platform, nobody knows exactly what the right metrics are. You know, I, I'm using 22 different components and I have distributed computing going on, I have networking, I have dynamic load balancing, I have Kubernetes spinning stuff up and eating up memory. I have physical memory, you know, physical constraints.

I have logical constraints, right? What, you know, for most humans, this rapidly expands beyond their capability to comprehend. Now we take that data, like you were saying, Dan, and we hand it to ai, ai, you know, the first thing AI can do is kind of just give you a direction.

Say, I I am looking at your platform and I'm understanding the types of components that you're using, and here are the top five metrics that you probably wanna look at initially for health, right? And then you, you start with these, and if you have an outage, you may want to expand to these, it'll do that for you. I think that's important, right?

That's the thing that AI can do that humans aren't able to do today, is take 44 variables and consolidate it down into a operational direction. Something that a human can actually look at and go, yep, yep, I get this. Okay, I can comprehend this.

And it's a, it's a way to minimize all of that energy waste, right? I'm not gonna turn on all the sensors in the entire factory and see, and 'cause you're gonna get noise. Your signal to noise ratio is gonna be unbearable, right?

This is a way using the, using humans and AI together that you can work as a coupling to say, what's the right things to look at? What do I turn on? And I do it from a bottom up versus a top down.

And right now, I think a lot of people who are in operations approach observability from a top down perspective trying to figure out, well, I've got all this data, let me see you, let me see what I can learn from it, what I can glean from it. And the truth of the matter is, that's not the right approach to, to take. You don't have a baseline.

So you're, you don't know what you're gleaning. Even AI doesn't, You know, I'm actually working on a, a, uh, a future of observability paper right now for futurum. And one of the key factors that we don't off often talk enough, kind of to your point too, JP, is it's because we can do something doesn't mean it's gonna get used either, right?

And I think the companies who are really good at not just, let's take this data and put it to use, or let's find a use for this data. The next step is, well then let's find the people who would actually use it and will they use it. And since Dynatrace gave this, this talk, and that's one of the, the several companies that I've talked to in the last 30 days, uh, getting updates on their strategies is Dynatrace has done a really good job, I think is a good model for other observability companies of moving observability to a different place in the organization.

They've done a great job of instrumenting Kubernetes and getting it to platform engineers and getting it to the IT ops team. They've done a great job of moving observability upstream into use by developers. So it both can be used during development, but also to better instrument their code.

And we'll see, I suspect, and they're also, by the way, I think doing a great job in the ai, uh, observability space too, and which is, you know, new for them, like it is for everybody. But we'll see how that develops. So to the degree, I think to your point, Bonnie, that they can align with who in the organization that determine drives those value from that, and those, those metrics have resulted in, you know, bottom line dollars or KPIs or whatever it might be that has been achieved.

I think that will help be that segment of observability, identify that it's successful or not, Did not strike you as kind of odd that every time we seem to be talking about anything these days, it all comes back to storage and networking. And at the end of the day, a lot of the data that we are collecting is, as they say in Scotland, crap. Well, it's all about storage, isn't it?

It's all about storage. Um, no, I, I would, I just wanna say first off, uh, that as somebody who's been in it for my entire career, and that is a few decades now, uh, one of the biggest challenges was the fact that, that most of the telemetry data, we didn't really call it that, but you know, it is telemetry. Most of that was siloed.

And thanks to Open Telemetry, it's not. And I just, you know, I, one of the reasons this product, this project has been so successful has, is because it's right there in the name Open Telemetry. In fact, uh, last year at Share, we had Broadcom talking about, um, exporting, uh, mainframe data through open telemetry to many of these same systems and really integrating that kind of data.

Now, if you can have everything from the mainframe to the cloud to on-prem to the edge, all bringing data in, it is exciting, as JP was saying, to think about what AI can do and not chat bots, as you said, ai, you know, large language models or specialty models trained to do, sort of find the needle in the haystack. But I do wanna bring in one interesting factoid. Now, I was doing some research on this story ahead of this, and in the future of intelligence, uh, uh, platform, I looked up to see what the deployment of, of telemetry data is.

And, and shockingly, it, it's interesting, there's a pattern here. Um, it's just under 70% for public cloud, uh, 66%, like two thirds for on-prem. Um, but it's only 38% for edge and only 10% for co-location.

In other words, there's still an opportunity to bring more data and more applications online. And I, I think this shows that maybe we're drowning in data, maybe we're gonna have it gonna run outta storage. Maybe we're gonna run outta energy, but there's still more to do in the telemetry space.

There'll be a little something extra in your stocking this year. Thank you Steven, for that mention. But let me, let me, let me put on my green hat for a second.

Yes. We could talk about the value of the data versus the cost of the energy to, to produce it, store it, use it, and, and that's a very, that's meth. It's meth, right?

Kilowatt hours, however you want to do it. Bigger issue, Steven, and I'm surprised you're not on your stool about this. One is, guys, we've got to do something in this world about the energy consumption.

We can't just keep saying, we're gonna spend trillions of dollars building out AI data centers in cities and all of these things without fundamentally changing the equation on making this energy that we use for it renewable recyclable cleaner better, because drill, you know, just drilling more and spending and burning more fossil fuels so that we could collect more log data is probably forget our little world that we live in here. We're all it geeks. Our children and their children have to live in a planet where we need to do something about this.

And, you know, how do we, how do we make that part of it? Steven, I, I know you are the, you're a solar GU guru, right? Don't we need to really look at it from that angle?

Uh, you know, I would love to see the real energy impact of telemetry data compared to literally everything else we're doing. And maybe, maybe it's true. Maybe telemetry is taking up a huge amount of resources that was the subject of this Dynatrace presentation that kicked all this off from CubeCon, which by the way, looks like is online now.

So if you, if you missed CubeCon, um, I think that you can find that on YouTube. Um, I wasn't able to watch it yet, so I wasn't able to see their data. Um, did, did they talk about what the real impact is in terms of, you know, hard numbers?

Yeah, I believe so. And they, they showed the platform and there's other, um, additional lectures on YouTube that they've previously done and webinars. So there's, there's a lot of data on those as well.

Go check them out now. You know, Let's compare it to the number of TikTok videos that are completely mindless and brainless that are produced. Agreed, agreed.

Right. Let, let's pick our fights where they make sense. There is a lot of energy consumed on mindless.

Yes. I'll leave it at that. All right, anything else on this?

Otherwise, we're gonna take a break, Bonnie. Great. Great story, by the way.

Thank you. All right. And as usual, you can get Bonnie's videos again on Textron tv, on our OTT channel.

com. That's right. Absolutely.

Thank you. Alright, we're gonna take a break here on the gang. We're coming back for a C block and it's infinite workdays.

I think we've all been there. You're watching. 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. com has the largest selection of security content featuring breaking news, blog posts, podcasts, and more. com to learn more.

com. Home of Security Bloggers Network. Hello, we're back.

And we're talking about this new study that Microsoft put out called The Infinite Workday. It's a little ironic maybe that Microsoft's the author of this thing, but we'll jump into that in a minute. But the premise of this thing, let's start with JP, is that we're overwhelmed with too much information and we're being inundated with various messages all day, and we don't have enough time to answer them all.

And who knows, maybe AI's making that better or worse. We'll see how that comes out in a minute, I'm sure. But jp, what's your take here?

So, I Don't know where everybody else has been. I've been living this for 15, 20 years now. Um, sometimes it feels like PTSD and I think that there's a cultural aspect to this as well, where there's a certain shaming that one feels if they don't respond right.

Am am I letting a team down? Am I, are people gonna think that I'm lazy? Is, you know, are people not gonna take me seriously as a professional if I'm not there when they need me?

And how do you professionally shut people down without worrying about, you know, how you are perceived, right? So it is a lot behind this. It's cultural.

Now the question is, you know, how all these new AI assistants play? How are they gonna participate and what's gonna be acceptable to everyone else? We've seen a lot of people sending note the joke, I should say, the meme where people are sending their note takers to meetings instead of themselves.

And it's just one person speaking in a room full of note takers. Um, is that the future? Is that the right way to go?

Meeting's a waste of time. Um, and if I have something important to say, I'll glean it and then set up some time to discuss it further. Uh, but these are the, this is a reality that we face and I do think that it needs to be attacked, uh, you know, from a, from a cultural perspective, not just a technological perspective.

Agreed. I mean, look to me, you know, the advent, I wish I had it with me, but I don't even, I don't have my phone with me. I can't believe it.

But, you know, the, the advent of the cell phone was the ultimate tether. It tethered us all. And we all thought we were so smart.

You know, what independence does this give us? We can communicate whoever we want, whatever we want, whenever we want. But really it tethered us to our jobs for most of us, right?

It tethered us to our jobs. We were in constant communication. Now, jp, like you, I've led this life also for 20, 25 plus years.

In my case, I didn't think of it as work, right? Bond. My wife's watching a chick flick, no big deal.

I'm going on Slack or whatever. I'll, I'll look at, you know, I'm doing some work stuff. It's just what I do.

But the, uh, there was a crucial point during c when the work from Home Revolution really became mainstream. And I realized it. 'cause in talking to people, people didn't know there was an off button.

There was an off button. And most people that I, especially younger people, and I'm not, you know, disparaging anyone, they have a hard time finding the off button and everyone needs an off button, otherwise, you get burned out. And I thought about you this morning on my walker, Alan, you Thought about me.

Yeah, I think about Alan all the time. Thank you. I, I, well, usually when I'm walking, the first thing I do is I pick, um, a podcast or YouTube to listen to while I'm walking.

And I read something this weekend, so I decided to try it where, just turn everything. It's your off time. Don't add anything.

Just, you know, do your walk bike. So I was thinking, what do you do when you bike? Do you listen to stuff or is that your escape time?

Is that your off time? I, I'm gonna tell you, I'm glad you asked me. So there was a time where I used to listen to podcasts while I'm biking.

I cut that out because it was taking away from my, my exercise, the endorphin stimulation. I listen to Apple Music, classic rock station. I, I, I will advertise it here.

And, but I will tell you, my mind expands like I'm on microdosing or something while I'm bicycling. 'cause I wind up spending a lot of time thinking about work stuff. But in a very non-structured, free forming, creative way that works a hundred times better than listening to some podcasts or checking my email or messages or slacks or whatever.

And so I, you know, There are other podcasts in the world that don't have anything to do with technology, right? You're, you get that right? I heard they, there are, you know, there's a whole nother aspect to this.

And that is, yes, it's the devices, it's also the software. How much are we inundated by? It wasn't just email anymore.

Yeah. That, that's an ungodly base beast. We still haven't tamed, but we've added to that every app on our device wants to send us notifications and it's binary, all of them or nothing.

And you, you total that up. And even with, you know, new things like apple's done with summarizing notification, I just get more summaries than it's still way too much stuff. And I don't know what those summaries mean.

This would be a great place for better product design and really understanding what, what are the notifications that matter to me? I don't really care about 99% of those. And what are the ways that I can fine tune those or AI could fine tune that for me better.

I think hopefully we can be smart about how we apply AI to this, but I don't want the software folks to get off for free on this. This is, they're just as guilty as everybody owning three devices and, and watching all three screens and not talking to their family. I think there's also the cultural aspect of it too that, uh, was mentioned earlier that an email, it's okay, you can respond in in due time, but when someone sends you a text and it could be, you know, a work colleague, you really do feel obligated.

I better respond within due time because they can see you Reddit, they know that you have your phone with you at all times. So there's that cultural pressure as well. Absolutely.

Yeah. O'Brien, what's your take on how this is gonna play out in the age of ai? Because I've already noticed that it's a lot easier for PR people or whoever to create a message.

And so there's more crap being created than ever, but the ability of the people than the cognitive load of the people who received that has not increased. So it feels like there's an imbalance in the system. There is, yeah.

I mean, a few thoughts for you, Mike. I mean, as we talk about, I guess kind of the nine to five becoming kind of the five to nine, you know, 5:00 AM to 9:00 PM we do still need to sleep. Um, but you know, I, I think, you know, my big thought here is, I think we all know this from leading teams, but you know, when you ask people to do more, you, you also need to ask that question, what are we gonna stop doing?

Right? And I think that's kind of the big challenge is we've added all of this, you know, kind of extracurricular outside of kind of the, you know, kinda set workday where we're proactively working, where we're doing a lot of reactive work kind of in the off hours. Um, you know, I I think at some point you gotta ask, what are we gonna stop doing?

And maybe that's, you know, uh, blowing up the construct of, you know, I'm at my desk for eight, for eight hours straight. You know, we maybe need more flexibility, you know, kind of during, uh, you know, during kind of that, that typical on time, uh, to give people the balance that they want. But I, I really worry about the AI side of this, Mike.

I mean, I, I I I feel like we're heading into a world where somebody uses AI to write a report. Somebody uses AI to summarize that report. Somebody uses AI to, you know, synthesize the notes from the summary of that report and nobody's actually writing it.

Nobody's actually reading anything anymore. Um, you know, we've just got our AI kind of flowing back and forth and, you know, how how do people actually consume information in a meaningful way where it sticks, it registers, it's got context. Um, and we've actually got, you know, kind of an agreement between the parties within these communications, what we're actually saying, what we're actually committing to.

I need that email with five bullet points and I'd be happy. Right? Well, may or maybe you like, don't use Slack, just kidding, Mike.

But, um, we've had that argument. Let me, let me, let me, I want to emphasize something though, and I, 'cause I don't want us to overlook it. I wanna make sure we hit on this, the Microsoft study called it a crisis, a crisis engulfing modern Employees.

And that crisis is not that we're doing more work or that we are tethered like this. The crisis goes to burnout. Burnout is real.

It's, it's, it's a recognized condition now by the World Health Organization. Uh, it's something my friend Jean Kim has explored a lot in the, in the DevOps enterprise summits and whatever he calls them now, um, I've, I've interviewed several experts in it over the years. Burnout is real.

And, and it's getting worse because I'm telling you, people don't know how to shut off. And Dan, I wish it was just five tonight, but I'll tell you the truth, I've been on with you past nine o'clock at night. I've been on with you, Mitchell, Mike, past nine o'clock at night.

I know as a team leader, when when stuff happens, I reach out and it's, I'm almost glad sometimes that people are on the West coast. 'cause I pick up three hours, right? So it may be 11 or 12 my time, but it's still semi-okay to reach out to them.

It's before nine. Um, but, you know, do we expect this as employers? Do we acquiesce to it as employees?

And what, how do we recognize when we've crossed that line into burnout? And it's, and it's, you know, it's detrimental to our health and not only to our individual health, but to the functioning of our company. I, if I can jump in on this some, you know, some practical things that I've learned about this.

Um, number one, um, I agree with, with all of what y'all are saying, I, you know, it it, it pains me as somebody who's worked from home and worked in an office to see people, uh, just sort of unequivocally saying working from home is better because, better for who, better for you really. Um, are you sure it's better for you? Um, you know, if you can't proactively manage your time while working from home, you never leave work.

I, I think that's the thing that, that, that, that really challenges some people. I think that whole commute and going into the office and being in a different place, I think that helps people organize their time. On the flip side, I think as you know, Dan was just saying, I think there's also a lot of value in those of us who've worked from home effectively to changing the nature of that nine to five workday.

And, and frankly, I feel like the the biggest thing that we have to do to avoid this crisis, because I agree it is a crisis. I see it, I see it with people that we work with internally at future, and I see it with, with my customers and I see it with my friends. We have to proactively manage this ourselves, each of us individually.

Like, you know, one of the, one of the easy, easiest and most effective methods that I've been known to do is, is schedule things on my calendar for myself. You know, I have, uh, at the suggestion of my wife a uh, an hour for lunch scheduled on my calendar every day. It's not like, I don't know what time lunch is, but it helps to make sure that I've got some time to eat.

You know, and similarly, you know, Dan asked me to work on a, a project. I scheduled blocks of time on my own calendar for myself to work on that project because I knew I needed to get it done. And I knew the only way to get it done was to the Microsoft, uh, report was to not have calls interrupting me every 30 minutes.

Uh, during that time that I'm trying to get something done, I need some time to focus. And those of us who've worked effectively from home realize as well that it's okay to schedule dog walking time. It's okay to schedule, you know, time for a, a visit to the coffee shop or whatever.

And it, and it's okay to work into the night if that's what works for you. It just is a matter of, of being more proactive in owning and managing our own time and recognizing that if we don't have on time and off time, we will never have off time. So you have to have specific on time and specific off time, and you have to manage yourself as much as you're managing other people and, and your customers and, and coworkers.

So, Steven, I, I've, okay, I got a i I like you. I've also set aside time. I have a 45 minute lunch break.

But what I find, as soon as something comes up that I feel like I have to do or should be done, that is the first time that I sacrifice. Oh yeah, me too. Totally.

So there's a little discipline I think that has to go with that. Yeah. I'm not an expert at it, but I do think that it comes to, you know, you have to manage yourself and you have to reflect on this.

And, and I'll just say out there if, if some of you who are finding challenges of this, maybe it would benefit you to go to a coworking space or something like that because then you feel like you're kind of have on time and off time. At the very least, you have to have an like a home office with a door that you can close and, and not try to do this while your life is revolving around you. You have to have space.

Hey, I would just remind you of an old joke that says, you know, when you're married and you have a full-time job and a couple of kids, what's the definition of quality time? It's the drive to and from work. There was a time I used to take the Long Island Railroad into New York.

Right. And you'd, you'd actually read a newspaper. Yeah.

You remember those days. JP Dan, you work from home. How do you, how do you deal it?

How do you deal with it? Yeah, I mean, we've all heard the term work-life balance, right? And I feel like it's, it's probably not the right mental framework for that because it really kind of puts the two at odds where one is a trade off versus the other.

I've, I've heard the phrase, uh, before called work-life harmony. And I think that's kind of what we're describing here is that, you know, it's a, it's a proactive stance. You've gotta really take a personal responsibility on it yourself, uh, to draw those boundaries, right?

I mean, me personally, I carry two phones. Um, when I'm getting good quality family time, I can leave my business phone in the drawer, right? And I know I've got no interruptions.

Um, I tend to do my work, you know, kind of only from my home office here and don't let that bleed into the rest of the house. Um, you know, I, I prioritize sleep. I've got, you know, kinda some limits as far as how late I'll go and you know, back at it when I wake up in the morning.

So, uh, those are at least some of the things that work for me. But to me it's much more about that kinda work li life harmony, drawing some kind of clear boundaries and you know, kind of that set of personal responsibility to make sure that you're taking care of your own wellness and mental health and you know, making sure you're getting everything done on the job as well. Agreed.

I'm gonna give you the last word on that one. Hey, I think it's time we get a little work life harmony 'cause we've already done enough of our tech term gang today. We're over time.

What a great discussion panel today. Thank you all. Steven, jp, Mitch, Mike, Bonnie.

Thank you, Dan. Now you've done this once. We we're expecting you on regularly, right?

Alright, I'll be happy to be a recurring guest. Thanks. All righty.

Thank you. Thank you for watching again. Hey, we've got a full day of Techstrong.

Well, not a full day, but we've got another three, four hours of tech Drunk TV coming at you immediately following the gang. You could watch this as well on demand, on Tech Drunk TV or our Text Drunk tv, YouTube channel or the OTT uh, channel as well. Just search Text Drunk tv.

I think we've deconstructed the gang too, where you could actually just watch individual segments of the gang. Not all three. So you've got no excuse.

But until tomorrow everyone, thanks for joining us On behalf of our gang, have a great day. We're outta here.