>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Hey, welcome back to the Fira in Barcelona. My name is Dave Vellante. I'm here with David Nicholson, day four of MWC '23. Show's winding down a little bit, but it's still pretty packed here. Lot of innovation, planes, trains, automobiles, and we're talking 5G all week, private networks, connected breweries. It's super exciting. Really happy to have Warren Jackson here as the Edge Gateway Product Technologist at Dell Technologies, and Scott Waller, the CTO of the 5G Open Innovation Lab. Folks, welcome to theCUBE. >> Good to be here. >> Really interesting stories that we're going to talk about. Let's start, Scott, with you, what is the Open Innovation Lab? >> So it was hatched three years ago. Ideated about a bunch of guys from Microsoft who ran startup ventures program, started the developers program over at Microsoft, if you're familiar with MSDN. And they came three years ago and said, how does CSPs working with someone like T-Mobile who's in our backyard, I'm from Seattle. How do they monetize the edge? You need a developer ecosystem of applications and use cases. That's always been the thing. The carriers are building the networks, but where's the ecosystem of startups? So we built a startup ecosystem that is sponsored by partners, Dell being one sponsor, Intel, Microsoft, VMware, Aspirant, you name it. The enterprise folks who are also in the connectivity business. And with that, we're not like a Y Combinator or a Techstars where it's investment first and it's all about funding. It's all about getting introductions from a startup who might have a VR or AI type of application or observability for 5G slicing, and bring that in front of the Microsoft's of the world, or the Intel's and the Dell's of the world that they might not have the capabilities to do it because they're still a small little startup with an MVP. So we really incubate. We're the connectors and build a network. We've had 101 startups over the last three years. They've raised over a billion dollars. And it's really valuable to our partners like T-Mobile and Dell, et cetera, where we're bringing in folks like Expedo and GenXComm and Firecell. Start up private companies that are around here they were cohorts from our program in the past. >> That's awesome because I've often, I mean, I've seen Dell get into this business and I'm like, wow, they've done a really good job of finding these guys. I wonder what the pipeline is. >> We're trying to create the pipeline for the entire industry, whether it's 5G on the edge for the CSPs, or it's for private enterprise networks. >> Warren, what's this cool little thing you got here? >> Yeah, so this is very unique in the Dell portfolio. So when people think of Dell, they think of servers laptops, et cetera. But what this does is it's designed to be deployed at the edge in harsh environments and it allows customers to do analytics, data collection at the edge. And what's unique about it is it's got an extended temperature range. There's no fan in this and there's lots of ports on it for data ingestion. So this is a smaller box Edge Gateway 3200. This is the product that we're using in the brewery. And then we have a bigger brother of this, the Edge Gateway 5200. So the value of it, you can scale depending on what your edge compute requirements are at the edge. >> So tell us about the brewery story. And you covered it, I know you were in the Dell booth, but it's basically an analog brewery. They're taking measurements and temperatures and then writing it down and then entering it in and somebody from your company saw it and said, "We can help you with this problem." Explain the story. >> Yeah, so Scott and I did a walkthrough of the brewery back in November timeframe. >> It's in Framingham, Mass. >> Framingham, Mass, correct. And basically, we talked to him, and we said, what keeps you guys up at night? What's a problem that we can solve? Very simple, a kind of a lower budget, didn't have a lot money to spend on it, but what problem can we solve that will realize great benefit for you? So we looked at their fermentation process, which was completely analog. Somebody was walking around with a clipboard looking at analog gauges. And what we did is we digitized that process. So what this did for them rather than being completely reactive, and by the time they realized there was something going wrong with the fermentation process, it's too late. A batch of scrap. This allowed them to be proactive. So anytime, anywhere on the tablet or a phone, they can see if that fermentation process is going out of range and do something about it before the batch gets scrapped. >> Okay. Amazing. And Scott, you got a picture of this workflow here? >> Yeah, actually this is the final product. >> Explain that. >> As Warren mentioned, the data is actually residing in the industrial side of the network So we wanted to keep the IT/OT separation, which is critical on the factory floor. And so all the data is brought in from the sensors via digital connection once it's converted and into the edge gateway. Then there's a snapshot of it using Telit deviceWISE, their dashboarding application, that is decoding all the digital readings, putting them in a nice dashboard. And then when we gave them, we realized another problem was they're using cheap little Chromebooks that they spill beer on once a week and throw them out. That's why they bought the cheap ones 'cause they go through them so fast. So we got a Dell Latitude Rugged notebook. This is a brand new tablet, but they have the dashboarding software. So no matter if they're out there on the floor, but because the data resides there on the factory they have access to be able to change the parameters. This one's in the maturation cycle. This one's in the crashing cycle where they're bringing the temperature back down, stopping the fermentation process, getting it ready to go to the canning side of the house. >> And they're doing all that from this dashboard. >> They're doing all from the dashboard. They also have a giant screen that we put up there that in the floor instead of walking a hundred yards back behind a whole bunch of machinery equipment from a safety perspective, now they just look up on the screen and go, "Oh, that's red. That's out of range." They're actually doing a bunch of cleaning and a bunch of other things right now, too. So this is real time from Boston. >> Dave: Oh okay. >> Scott: This is actually real time from Boston. >> I'm no hop master, but I'm looking at these things flashing at me and I'm thinking something's wrong with my beer. >> We literally just lit this up last week. So we're still tweaking a few things, but they're also learning around. This is a new capability they never had. Oh, we have the ability to alert and monitor at different processes with different batches, different brews, different yeast types. Then now they're also training and learning. And we're going to turn that into eventually a product that other breweries might be able to use. >> So back to the kind of nuts and bolts of the system. The device that you have here has essentially wifi antennas on the back. >> Warren: Correct. >> Pull that up again if you would, please. >> Now I've seen this, just so people are clear, there are also paddle 5G antennas that go on the other side. >> Correct. >> That's sort of the connection from the 5G network that then gets transmogrified, technical term guys, into wifi so the devices that are physically connected to the brew vats, don't know what they're called. >> Fermentation tanks. >> Fermentation tanks, thank you. Those are wifi. That's a wifi signal that's going into this. Is that correct? >> Scott: No. >> No, it's not. >> It's a hard wire. >> Okay, okay. >> But, you're right. This particular gateway. >> It could be wifi if it's hard wire. >> It could be, yes. Could be any technology really. >> This particular gateway is not outfitted with 5G, but something that was very important in this application was to isolate the IT network, which is on wifi and physically connected from the OT network, which is the 5G connection. So we're sending the data directly from the gateway up to the cloud. The two partners that we worked with on this project were ifm, big sensor manufacturer that actually did the wired sensors into an industrial network called IO-Link. So they're physically wired into the gateway and then in the gateway we have a solution from our partner Telit that has deviceWISE software that actually takes the data in, runs the analytics on it, the logic, and then visualizes that data locally on those panels and also up to their cloud, which is what we're looking at. So they can look at it locally, they're in the plant and then up in the cloud on a phone or a tablet, whatever, when they're at home. >> We're talking about a small business here. I don't know how many employees they have, but it's not thousands. And I love that you're talking about an IT network and an OT network. And so they wanted, it is very common when we talk about industrial internet of things use cases, but we're talking about a tiny business here. >> Warren: Correct. >> They wanted to separate those networks because of cost, because of contention. Explain why. >> Yeah, just because, I mean, they're running their ERP system, their payroll, all of their kind of the way they run their business on their IT network and you don't want to have the same traffic out on the factory floor on that network, so it was pretty important. And the other thing is we really, one of the things that we didn't want to do in this project is interrupt their production process at all. So we installed this entire system in two days. They didn't have to shut down, they didn't have to stop. We didn't have to interrupt their process at all. It was like we were invisible there and we spun the thing up and within two days, very simple, easy, but tremendous value for their business. >> Talk about new markets here. I mean, it's like any company that's analog that needs to go digital. It's like 99% of the companies on the planet. What are you guys seeing out there in terms of the types of examples beyond breweries? >> Yeah, I could talk to that. So I spent a lot of time over the last couple years running my own little IoT company and a lot of it being in agriculture. So like in Washington state, 70% of the world's hops is actually grown in Washington state. It's my hometown. But in the Ag producing regions, there's lack of connectivity. So there's interest in private networks because the carriers aren't necessarily deploying it. But because we have the vast amount of hops there's a lot of IPAs, a lot of hoppy IPAs that come out of Seattle. And with that, there's a ton of craft breweries that are about the same size, some are a little larger. Anheuser-Busch and InBev and Heineken they've got great IoT platforms. They've done it. They're mass scale, they have to digitize. But the smaller shops, they don't, when we talk about IT/OT separation, they're not aware of that. They think it's just, I get local broadband and I get wifi and one hotspot inside my facility and it works. So a little bit of it was the education. I have got years in IT/OT security in my background so that education and we come forward with a solution that actually does that for them. And now they're aware of it. So now when they're asking questions of other vendors that are trying to sell them some type of solution, they're inherently aware of what should be done so they're not vulnerable to ransomware attacks, et cetera. So it's known as the Purdue Model. >> Well, what should they do? >> We came in and keep it completely separated and educated them because in the end too we'll build a design guide and a starter kit out of this that other brewers can use. Because I've toured dozens of breweries in Washington, the exact same scenario, analog gauges, analog process, very manual. And in the end, when you ask the brewer, what do they want out of this? It keeps them up at night because if the temperature goes out of range, because the chiller fails, >> They ruined. >> That's $30,000 lost in beer. That's a lot to a small business. However, it's also once they start digitizing the data and to Warren's point, it's read-only. We're not changing any of the process. We augmented on top of their existing systems. We didn't change their process. But now they have the ability to look at the data and see batch to batch consistency. Quality doesn't always mean best, it means consistency from batch to batch. Every beer from exhibit A from yesterday to two months from now of the same style of beer should be the same taste, flavor, boldness, et cetera. This is giving them the insights on it. >> It's like St. Louis Buds, when we were kids. We would buy the St. Louis Buds 'cause they tasted better than the Merrimack Buds. And then Budweiser made them all the same. >> Must be an East coast thing. >> It's an old guy thing, Dave. You weren't born yet. >> I was in high school. Yeah, I was in high school. >> We like the hops. >> We weren't 21. Do me a favor, clarify OT versus IT. It's something we talk about all the time, but not everyone's familiar with that separation. Define OT for me. >> It's really the factory floor. You got IT systems that are ERP systems, billing, you're getting your emails, stuff like that. Where the ransomware usually gets infected in. The OT side is the industrial control network. >> David: What's the 'O' stand for? >> Operation. >> David: Operation? >> Yeah, the operations side. >> 'Cause some people will think objects 'cause we think internet of things. >> The industrial operations, think of it that way. >> But in a sense those are things that are connected. >> And you think of that as they are the safety systems as well. So a machine, if someone doesn't push the stop button, you'd think if there's a lot of traffic on that network, it isn't guaranteed that that stop button actually stops that blade from coming down, someone's going to lose their arm. So it's very tied to safety, reliability, low latency. It is crafted in design that it never touches the internet inherently without having to go through a security gateway which is what we did. >> You mentioned the large companies like InBev, et cetera. You're saying they're already there. Are they not part of your target market? Or are there ways that you can help them? Is this really more of a small to mid-size company? >> For this particular solution, I think so, yeah. Because the cost to entry is low. I mean, you talk about InBev, they have millions of dollars of budgets to spend on OT. So they're completely automated from top to bottom. But these little craft brewers, which they're everywhere in the US. Vermont, Washington state, they're completely manual. A lot of these guys just started in their garage. And they just scaled up and they got a cult kind of following around their beers. One thing that we found here this week, when you talk around edge and 5G and beer, those things get people excited. In our booth we're serving beer, and all these kind of topics, it brings people together. >> And it lets the little guy compete more effectively with the big giants. >> Correct. >> And how do you do more with less as the little guy is kind of the big thing and to Warren's point, we have folks come up and say, "Great, this is for beer, but what about wine? What about the fermentation process of wine?" Same materials in the end. A vessel of some sort, maybe it's stainless steel. The clamps are the same, the sensors are the same. The parameters like temperature are key in any type of fermentation. We had someone talking about olive oil and using that. It's the same sanitary beverage style equipment. We grabbed sensors that were off the shelf and then we integrated them in and used the set of platforms that we could. How do we rapidly enable these guys at the lowest possible cost with stuff that's at the shelf. And there's four different companies in the solution. >> We were having a conversation with T-Mobile a little earlier and she mentioned the idea of this sounding scary. And this is a great example of showing that in fact, at a relatively small scale, this technology makes a lot of sense. So from that perspective, of course you can implement private 5G networks at an industrial scale with tens of millions of dollars of investment. But what about all of the other things below? And that seems to be a perfect example. >> Yeah, correct. And it's one of the things with the gateway and having flexibility the way Dell did a great job of putting really good modems in it. It had a wide spectrum range of what bands they support. So being able to say, at a larger facility, I mean, if Heineken wants to deploy something like this, oh, heck yeah, they probably could do it. And they might have a private 5G network, but let's say T-Mobile offers a private offering on their public via a slice. It's easy to connect that radio to it. You just change the sims. >> Is that how the CSPs fit here? How are they monetized? >> Yeah, correct. So one of our partners is T-Mobile and so we're working with them. We've got other telco partners that are coming on board in our lab. And so we'll do the same thing. We're going to take this back and put it in the lab and offer it up as others because the baseline building blocks or Lego blocks per se can be used in a bunch of different industries. It's really that starter point of giving folks the idea of what's possible. >> So small manufacturing, agriculture you mentioned, any other sort of use cases we should tune into? >> I think it's environmental monitoring, all of that stuff, I see it in IoT deployments all over the world. Just the simple starter kits 'cause a farmer doesn't want to get sold a solution, a platform, where he's got to hire a bunch of coders and partner with the big carriers. He just wants something that works. >> Another use case that we see a lot, a high cost in a lot of these places is the cost of energy. And a lot of companies don't know what they're spending on electricity. So a very simple energy monitoring system like that, it's a really good ROI. I'm going to spend five or $10,000 on a system like this, but I'm going to save $20,000 over a year 'cause I'm able to see, have visibility into that data. That's a lot of what this story's about, just giving visibility into the process. >> It's very cool, and like you said, it gets people excited. Is it a big market? How do you size it? Is it a big TAM? >> Yeah, so one thing that Dell brings to the table in this space is people are buying their laptops, their servers and whatnot from Dell and companies are comfortable in doing business with Dell because of our model direct to customer and whatnot. So our ability to bring a device like this to the OT space and have them have that same user experience they have with laptops and our client products in a ruggedized solution like this and bring a lot of partners to the table makes it easy for our customers to implement this across all kinds of industries. >> So we're talking to billions, tens of billions. Do we know how big this market is? What's the TAM? I mean, come on, you work for Dell. You have to do a TAM analysis. >> Yes, no, yeah. I mean, it really is in the billions. The market is huge for this one. I think we just tapped into it. We're kind of focused in on the brewery piece of it and the liquor piece of it, but the possibilities are endless. >> Yeah, that's tip of the spear. Guys, great story. >> It's scalable. I think the biggest thing, just my final feedback is working and partnering with Dell is we got something as small as this edge gateway that I can run a Packet Core on and run a 5G standalone node and then have one of the small little 5G radios out there. And I've got these deployed in a farm. Give the farmer an idea of what's possible, give him a unit on his tractor, and now he can do something that, we're providing connectivity he had never had before. But as we scale up, we've got the big brother to this. When we scale up from that, we got the telco size units that we can put. So it's very scalable. It's just a great suite of offerings. >> Yeah, outstanding. Guys, thanks for sharing the story. Great to have you on theCUBE. >> Good to be with you today. >> Stop by for beer later. >> You know it. All right, Dave Vellante for Dave Nicholson and the entire CUBE team, we're here live at the Fira in Barcelona MWC '23 day four. Keep it right there. (upbeat music)

>> From the Cube Studios in Palo Alto in Boston bringing you data-driven insights from the Cube and ETR. This is Breaking Analysis with Dave Vellante. >> The unraveling of market enthusiasm continued in Q4 of 2022 with the earnings reports from the US hyperscalers, the big three now all in. As we said earlier this year, even the cloud is an immune from the macro headwinds and the cracks in the armor that we saw from the data that we shared last summer, they're playing out into 2023. For the most part actuals are disappointing beyond expectations including our own. It turns out that our estimates for the big three hyperscaler's revenue missed by 1.2 billion or 2.7% lower than we had forecast from even our most recent November estimates. And we expect continued decelerating growth rates for the hyperscalers through the summer of 2023 and we don't think that's going to abate until comparisons get easier. Hello and welcome to this week's Wikibon Cube Insights powered by ETR. In this Breaking Analysis, we share our view of what's happening in cloud markets not just for the hyperscalers but other firms that have hitched a ride on the cloud. And we'll share new ETR data that shows why these trends are playing out tactics that customers are employing to deal with their cost challenges and how long the pain is likely to last. You know, riding the cloud wave, it's a two-edged sword. Let's look at the players that have gone all in on or are exposed to both the positive and negative trends of cloud. Look the cloud has been a huge tailwind for so many companies like Snowflake and Databricks, Workday, Salesforce, Mongo's move with Atlas, Red Hats Cloud strategy with OpenShift and so forth. And you know, the flip side is because cloud is elastic what comes up can also go down very easily. Here's an XY graphic from ETR that shows spending momentum or net score on the vertical axis and market presence in the dataset on the horizontal axis provision or called overlap. This is data from the January 2023 survey and that the red dotted lines show the positions of several companies that we've highlighted going back to January 2021. So let's unpack this for a bit starting with the big three hyperscalers. The first point is AWS and Azure continue to solidify their moat relative to Google Cloud platform. And we're going to get into this in a moment, but Azure and AWS revenues are five to six times that of GCP for IaaS. And at those deltas, Google should be gaining ground much faster than the big two. The second point on Google is notice the red line on GCP relative to its starting point. While it appears to be gaining ground on the horizontal axis, its net score is now below that of AWS and Azure in the survey. So despite its significantly smaller size it's just not keeping pace with the leaders in terms of market momentum. Now looking at AWS and Microsoft, what we see is basically AWS is holding serve. As we know both Google and Microsoft benefit from including SaaS in their cloud numbers. So the fact that AWS hasn't seen a huge downward momentum relative to a January 2021 position is one positive in the data. And both companies are well above that magic 40% line on the Y-axis, anything above 40% we consider to be highly elevated. But the fact remains that they're down as are most of the names on this chart. So let's take a closer look. I want to start with Snowflake and Databricks. Snowflake, as we reported from several quarters back came down to Earth, it was up in the 80% range in the Y-axis here. And it's still highly elevated in the 60% range and it continues to move to the right, which is positive but as we'll address in a moment it's customers can dial down consumption just as in any cloud. Now, Databricks is really interesting. It's not a public company, it never made it to IPO during the sort of tech bubble. So we don't have the same level of transparency that we do with other companies that did make it through. But look at how much more prominent it is on the X-axis relative to January 2021. And it's net score is basically held up over that period of time. So that's a real positive for Databricks. Next, look at Workday and Salesforce. They've held up relatively well, both inching to the right and generally holding their net scores. Same from Mongo, which is the brown dot above its name that says Elastic, it says a little gets a little crowded which Elastic's actually the blue dot above it. But generally, SaaS is harder to dial down, Workday, Salesforce, Oracles, SaaS and others. So it's harder to dial down because commitments have been made in advance, they're kind of locked in. Now, one of the discussions from last summer was as Mongo, less discretionary than analytics i.e. Snowflake. And it's an interesting debate but maybe Snowflake customers, you know, they're also generally committed to a dollar amount. So over time the spending is going to be there. But in the short term, yeah maybe Snowflake customers can dial down. Now that highlighted dotted red line, that bolded one is Datadog and you can see it's made major strides on the X-axis but its net score has decelerated quite dramatically. Openshift's momentum in the survey has dropped although IBM just announced that OpenShift has a a billion dollar ARR and I suspect what's happening there is IBM consulting is bundling OpenShift into its modernization projects. It's got a, that sort of captive base if you will. And as such it's probably not as top of mind to the respondents but I'll bet you the developers are certainly aware of it. Now the other really notable call out here is CloudFlare, We've reported on them earlier. Cloudflare's net score has held up really well since January of 2021. It really hasn't seen the downdraft of some of these others, but it's making major major moves to the right gaining market presence. We really like how CloudFlare is performing. And the last comment is on Oracle which as you can see, despite its much, much lower net score continues to gain ground in the market and thrive from a profitability standpoint. But the data pretty clearly shows that there's a downdraft in the market. Okay, so what's happening here? Let's dig deeper into this data. Here's a graphic from the most recent ETR drill down asking customers that said they were going to cut spending what technique they're using to do so. Now, as we've previously reported, consolidating redundant vendors is by far the most cited approach but there's two key points we want to make here. One is reducing excess cloud resources. As you can see in the bars is the second most cited technique and it's up from the previous polling period. The second we're not showing, you know directly but we've got some red call outs there. Reducing cloud costs jumps to 29% and 28% respectively in financial services and tech telco. And it's much closer to second. It's basically neck and neck with consolidating redundant vendors in those two industries. So they're being really aggressive about optimizing cloud cost. Okay, so as we said, cloud is great 'cause you can dial it up but it's just as easy to dial down. We've identified six factors that customers tell us are affecting their cloud consumption and there are probably more, if you got more we'd love to hear them but these are the ones that are fairly prominent that have hit our radar. First, rising mortgage rates mean banks are processing fewer loans means less cloud. The crypto crash means less trading activity and that means less cloud resources. Third lower ad spend has led companies to reduce not only you know, their ad buying but also their frequency of running their analytics and their calculations. And they're also often using less data, maybe compressing the timeframe of the corpus down to a shorter time period. Also very prominent is down to the bottom left, using lower cost compute instances. For example, Graviton from AWS or AMD chips and tiering storage to cheaper S3 or deep archived tiers. And finally, optimizing based on better pricing plans. So customers are moving from, you know, smaller companies in particular moving maybe from on demand or other larger companies that are experimenting using on demand or they're moving to spot pricing or reserved instances or optimized savings plans. That all lowers cost and that means less cloud resource consumption and less cloud revenue. Now in the days when everything was on prem CFOs, what would they do? They would freeze CapEx and IT Pros would have to try to do more with less and often that meant a lot of manual tasks. With the cloud it's much easier to move things around. It still takes some thinking and some effort but it's dramatically simpler to do so. So you can get those savings a lot faster. Now of course the other huge factor is you can cut or you can freeze. And this graphic shows data from a recent ETR survey with 159 respondents and you can see the meaningful uptick in hiring freezes, freezing new IT deployments and layoffs. And as we've been reporting, this has been trending up since earlier last year. And note the call out, this is especially prominent in retail sectors, all three of these techniques jump up in retail and that's a bit of a concern because oftentimes consumer spending helps the economy make a softer landing out of a pullback. But this is a potential canary in the coal mine. If retail firms are pulling back it's because consumers aren't spending as much. And so we're keeping a close eye on that. So let's boil this down to the market data and what this all means. So in this graphic we show our estimates for Q4 IaaS revenues compared to the "actual" IaaS revenues. And we say quote because AWS is the only one that reports, you know clean revenue and IaaS, Azure and GCP don't report actuals. Why would they? Because it would make them look even, you know smaller relative to AWS. Rather, they bury the figures in overall cloud which includes their, you know G-Suite for Google and all the Microsoft SaaS. And then they give us little tidbits about in Microsoft's case, Azure, they give growth rates. Google gives kind of relative growth of GCP. So, and we use survey data and you know, other data to try to really pinpoint and we've been covering this for, I don't know, five or six years ever since the cloud really became a thing. But looking at the data, we had AWS growing at 25% this quarter and it came in at 20%. So a significant decline relative to our expectations. AWS announced that it exited December, actually, sorry it's January data showed about a 15% mid-teens growth rate. So that's, you know, something we're watching. Azure was two points off our forecast coming in at 38% growth. It said it exited December in the 35% growth range and it said that it's expecting five points of deceleration off of that. So think 30% for Azure. GCP came in three points off our expectation coming in 35% and Alibaba has yet to report but we've shaved a bid off that forecast based on some survey data and you know what maybe 9% is even still not enough. Now for the year, the big four hyperscalers generated almost 160 billion of revenue, but that was 7 billion lower than what what we expected coming into 2022. For 2023, we're expecting 21% growth for a total of 193.3 billion. And while it's, you know, lower, you know, significantly lower than historical expectations it's still four to five times the overall spending forecast that we just shared with you in our predictions post of between 4 and 5% for the overall market. We think AWS is going to come in in around 93 billion this year with Azure closing in at over 71 billion. This is, again, we're talking IaaS here. Now, despite Amazon focusing investors on the fact that AWS's absolute dollar growth is still larger than its competitors. By our estimates Azure will come in at more than 75% of AWS's forecasted revenue. That's a significant milestone. AWS is operating margins by the way declined significantly this past quarter, dropping from 30% of revenue to 24%, 30% the year earlier to 24%. Now that's still extremely healthy and we've seen wild fluctuations like this before so I don't get too freaked out about that. But I'll say this, Microsoft has a marginal cost advantage relative to AWS because one, it has a captive cloud on which to run its massive software estate. So it can just throw software at its own cloud and two software marginal costs. Marginal economics despite AWS's awesomeness in high degrees of automation, software is just a better business. Now the upshot for AWS is the ecosystem. AWS is essentially in our view positioning very smartly as a platform for data partners like Snowflake and Databricks, security partners like CrowdStrike and Okta and Palo Alto and many others and SaaS companies. You know, Microsoft is more competitive even though AWS does have competitive products. Now of course Amazon's competitive to retail companies so that's another factor but generally speaking for tech players, Amazon is a really thriving ecosystem that is a secret weapon in our view. AWS happy to spin the meter with its partners even though it sells competitive products, you know, more so in our view than other cloud players. Microsoft, of course is, don't forget is hyping now, we're hearing a lot OpenAI and ChatGPT we reported last week in our predictions post. How OpenAI is shot up in terms of market sentiment in ETR's emerging technology company surveys and people are moving to Azure to get OpenAI and get ChatGPT that is a an interesting lever. Amazon in our view has to have a response. They have lots of AI and they're going to have to make some moves there. Meanwhile, Google is emphasizing itself as an AI first company. In fact, Google spent at least five minutes of continuous dialogue, nonstop on its AI chops during its latest earnings call. So that's an area that we're watching very closely as the buzz around large language models continues. All right, let's wrap up with some assumptions for 2023. We think SaaS players are going to continue to be sticky. They're going to be somewhat insulated from all these downdrafts because they're so tied in and customers, you know they make the commitment up front, you've got the lock in. Now having said that, we do expect some backlash over time on the onerous and generally customer unfriendly pricing models of most large SaaS companies. But that's going to play out over a longer period of time. Now for cloud generally and the hyperscalers specifically we do expect accelerating growth rates into Q3 but the amplitude of the demand swings from this rubber band economy, we expect to continue to compress and become more predictable throughout the year. Estimates are coming down, CEOs we think are going to be more cautious when the market snaps back more cautious about hiring and spending and as such a perhaps we expect a more orderly return to growth which we think will slightly accelerate in Q4 as comps get easier. Now of course the big risk to these scenarios is of course the economy, the FED, consumer spending, inflation, supply chain, energy prices, wars, geopolitics, China relations, you know, all the usual stuff. But as always with our partners at ETR and the Cube community, we're here for you. We have the data and we'll be the first to report when we see a change at the margin. Okay, that's a wrap for today. I want to thank Alex Morrison who's on production and manages the podcast, Ken Schiffman as well out of our Boston studio getting this up on LinkedIn Live. Thank you for that. Kristen Martin also and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our Editor-in-Chief over at siliconangle.com. He does some great editing for us. Thank you all. Remember all these episodes are available as podcast. Wherever you listen, just search Breaking Analysis podcast. I publish each week on wikibon.com, at siliconangle.com where you can see all the data and you want to get in touch. Just all you can do is email me david.vellante@siliconangle.com or DM me @dvellante if you if you got something interesting, I'll respond. If you don't, it's either 'cause I'm swamped or it's just not tickling me. You can comment on our LinkedIn post as well. And please check out ETR.ai for the best survey data in the enterprise tech business. This is Dave Vellante for the Cube Insights powered by ETR. Thanks for watching and we'll see you next time on Breaking Analysis. (gentle upbeat music)

(uplifting music) >> Hello, welcome back to theCUBE's coverage of CloudNativeSecurityCon, the inaugural event, in Seattle. I'm John Furrier, host of theCUBE, here in the Palo Alto Studios. We're calling it theCUBE Center. It's kind of like our Sports Center for tech. It's kind of remote coverage. We've been doing this now for a few years. We're going to amp it up this year as more events are remote, and happening all around the world. So, we're going to continue the coverage with this segment focusing on the data stack, entrepreneurial opportunities around all things security, and as, obviously, data's involved. And our next guest is a friend of theCUBE, and CUBE alumni from 2013, entrepreneur himself, turned, now, venture capitalist angel investor, with his own firm, Opher Kahane, Managing Director, Sonoma Ventures. Formerly the founder of Origami, sold to Intuit a few years back. Focusing now on having a lot of fun, angel investing on boards, focusing on data-driven applications, and stacks around that, and all the stuff going on in, really, in the wheelhouse for what's going on around security data. Opher, great to see you. Thanks for coming on. >> My pleasure. Great to be back. It's been a while. >> So you're kind of on Easy Street now. You did the entrepreneurial venture, you've worked hard. We were on together in 2013 when theCUBE just started. XCEL Partners had an event in Stanford, XCEL, and they had all the features there. We interviewed Satya Nadella, who was just a manager at Microsoft at that time, he was there. He's now the CEO of Microsoft. >> Yeah, he was. >> A lot's changed in nine years. But congratulations on your venture you sold, and you got an exit there, and now you're doing a lot of investments. I'd love to get your take, because this is really the biggest change I've seen in the past 12 years, around an inflection point around a lot of converging forces. Data, which, big data, 10 years ago, was a big part of your career, but now it's accelerated, with cloud scale. You're seeing people building scale on top of other clouds, and becoming their own cloud. You're seeing data being a big part of it. Cybersecurity kind of has not really changed much, but it's the most important thing everyone's talking about. So, developers are involved, data's involved, a lot of entrepreneurial opportunities. So I'd love to get your take on how you see the current situation, as it relates to what's gone on in the past five years or so. What's the big story? >> So, a lot of big stories, but I think a lot of it has to do with a promise of making value from data, whether it's for cybersecurity, for Fintech, for DevOps, for RevTech startups and companies. There's a lot of challenges in actually driving and monetizing the value from data with velocity. Historically, the challenge has been more around, "How do I store data at massive scale?" And then you had the big data infrastructure company, like Cloudera, and MapR, and others, deal with it from a scale perspective, from a storage perspective. Then you had a whole layer of companies that evolved to deal with, "How do I index massive scales of data, for quick querying, and federated access, et cetera?" But now that a lot of those underlying problems, if you will, have been solved, to a certain extent, although they're always being stretched, given the scale of data, and its utility is becoming more and more massive, in particular with AI use cases being very prominent right now, the next level is how to actually make value from the data. How do I manage the full lifecycle of data in complex environments, with complex organizations, complex use cases? And having seen this from the inside, with Origami Logic, as we dealt with a lot of large corporations, and post-acquisition by Intuit, and a lot of the startups I'm involved with, it's clear that we're now onto that next step. And you have fundamental new paradigms, such as data mesh, that attempt to address that complexity, and responsibly scaling access, and democratizing access in the value monetization from data, across large organizations. You have a slew of startups that are evolving to help the entire lifecycle of data, from the data engineering side of it, to the data analytics side of it, to the AI use cases side of it. And it feels like the early days, to a certain extent, of the revolution that we've seen in transition from traditional databases, to data warehouses, to cloud-based data processing, and big data. It feels like we're at the genesis of that next wave. And it's super, super exciting, for me at least, as someone who's sitting more in the coach seat, rather than being on the pitch, and building startups, helping folks as they go through those motions. >> So that's awesome. I want to get into some of these data infrastructure dynamics you mentioned, but before that, talk to the audience around what you're working on now. You've been a successful entrepreneur, you're focused on angel investing, so, super-early seed stage. What kind of deals are you looking at? What's interesting to you? What is Sonoma Ventures looking for, and what are some of the entrepreneurial dynamics that you're seeing right now, from a startup standpoint? >> Cool, so, at a macro level, this is a little bit of background of my history, because it shapes very heavily what it is that I'm looking at. So, I've been very fortunate with entrepreneurial career. I founded three startups. All three of them are successful. Final two were sold, the first one merged and went public. And my third career has been about data, moving data, passing data, processing data, generating insights from it. And, at this phase, I wanted to really evolve from just going and building startup number four, from going through the same motions again. A 10 year adventure, I'm a little bit too old for that, I guess. But the next best thing is to sit from a point whereby I can be more elevated in where I'm dealing with, and broaden the variety of startups I'm focused on, rather than just do your own thing, and just go very, very deep into it. Now, what specifically am I focused on at Sonoma Ventures? So, basically, looking at what I refer to as a data-driven application stack. Anything from the low-level data infrastructure and cloud infrastructure, that helps any persona in the data universe maximize value for data, from their particular point of view, for their particular role, whether it's data analysts, data scientists, data engineers, cloud engineers, DevOps folks, et cetera. All the way up to the application layer, in applications that are very data-heavy. And what are very typical data-heavy applications? FinTech, cyber, Web3, revenue technologies, and product and DevOps. So these are the areas we're focused on. I have almost 23 or 24 startups in the portfolio that span all these different areas. And this is in terms of the aperture. Now, typically, focus on pre-seed, seed. Sometimes a little bit later stage, but this is the primary focus. And it's really about partnering with entrepreneurs, and helping them make, if you will, original mistakes, avoid the mistakes I made. >> Yeah. >> And take it to the next level, whatever the milestone they're driving with. So I'm very, very hands-on with many of those startups. Now, what is it that's happening right now, initially, and why is it so exciting? So, on one hand, you have this scaling of data and its complexity, yet lagging value creation from it, across those different personas we've touched on. So that's one fundamental opportunity which is secular. The other one, which is more a cyclic situation, is the fact that we're going through a down cycle in tech, as is very evident in the public markets, and everything we're hearing about funding going slower and lower, terms shifting more into the hands of typical VCs versus entrepreneur-friendly market, and so on and so forth. And a very significant amount of layoffs. Now, when you combine these two trends together, you're observing a very interesting thing, that a lot of folks, really bright folks, who have sold a startup to a company, or have been in the guts of the large startup, or a large corporation, have, hands-on, experienced all those challenges we've spoken about earlier, in turf, maximizing value from data, irrespective of their role, in a specific angle, or vantage point they have on those challenges. So, for many of them, it's an opportunity to, "Now, let me now start a startup. I've been laid off, maybe, or my company's stock isn't doing as well as it used to, as a large corporation. Now I have an opportunity to actually go and take my entrepreneurial passion, and apply it to a product and experience as part of this larger company." >> Yeah. >> And you see a slew of folks who are emerging with these great ideas. So it's a very, very exciting period of time to innovate. >> It's interesting, a lot of people look at, I mean, I look at Snowflake as an example of a company that refactored data warehouses. They just basically took data warehouse, and put it on the cloud, and called it a data cloud. That, to me, was compelling. They didn't pay any CapEx. They rode Amazon's wave there. So, a similar thing going on with data. You mentioned this, and I see it as an enabling opportunity. So whether it's cybersecurity, FinTech, whatever vertical, you have an enablement. Now, you mentioned data infrastructure. It's a super exciting area, as there's so many stacks emerging. We got an analytics stack, there's real-time stacks, there's data lakes, AI stack, foundational models. So, you're seeing an explosion of stacks, different tools probably will emerge. So, how do you look at that, as a seasoned entrepreneur, now investor? Is that a good thing? Is that just more of the market? 'Cause it just seems like more and more kind of decomposed stacks targeted at use cases seems to be a trend. >> Yeah. >> And how do you vet that, is it? >> So it's a great observation, and if you take a step back and look at the evolution of technology over the last 30 years, maybe longer, you always see these cycles of expansion, fragmentation, contraction, expansion, contraction. Go decentralize, go centralize, go decentralize, go centralize, as manifested in different types of technology paradigms. From client server, to storage, to microservices, to et cetera, et cetera. So I think we're going through another big bang, to a certain extent, whereby end up with more specialized data stacks for specific use cases, as you need performance, the data models, the tooling to best adapt to the particular task at hand, and the particular personas at hand. As the needs of the data analysts are quite different from the needs of an NL engineer, it's quite different from the needs of the data engineer. And what happens is, when you end up with these siloed stacks, you end up with new fragmentation, and new gaps that need to be filled with a new layer of innovation. And I suspect that, in part, that's what we're seeing right now, in terms of the next wave of data innovation. Whether it's in a service of FinTech use cases, or cyber use cases, or other, is a set of tools that end up having to try and stitch together those elements and bridge between them. So I see that as a fantastic gap to innovate around. I see, also, a fundamental need in creating a common data language, and common data management processes and governance across those different personas, because ultimately, the same underlying data these folks need, albeit in different mediums, different access models, different velocities, et cetera, the subject matter, if you will, the underlying raw data, and some of the taxonomies right on top of it, do need to be consistent. So, once again, a great opportunity to innovate, whether it's about semantic layers, whether it's about data mesh, whether it's about CICD tools for data engineers, and so on and so forth. >> I got to ask you, first of all, I see you have a friend you brought into the interview. You have a dog in the background who made a little cameo appearance. And that's awesome. Sitting right next to you, making sure everything's going well. On the AI thing, 'cause I think that's the hot trend here. >> Yeah. >> You're starting to see, that ChatGPT's got everyone excited, because it's kind of that first time you see kind of next-gen functionality, large-language models, where you can bring data in, and it integrates well. So, to me, I think, connecting the dots, this kind of speaks to the beginning of what will be a trend of really blending of data stacks together, or blending of models. And so, as more data modeling emerges, you start to have this AI stack kind of situation, where you have things out there that you can compose. It's almost very developer-friendly, conceptually. This is kind of new, but kind of the same concept's been working on with Google and others. How do you see this emerging, as an investor? What are some of the things that you're excited about, around the ChatGPT kind of things that's happening? 'Cause it brings it mainstream. Again, a million downloads, fastest applications get a million downloads, even among all the successes. So it's obviously hit a nerve. People are talking about it. What's your take on that? >> Yeah, so, I think that's a great point, and clearly, it feels like an iPhone moment, right, to the industry, in this case, AI, and lots of applications. And I think there's, at a high level, probably three different layers of innovation. One is on top of those platforms. What use cases can one bring to the table that would drive on top of a ChatGPT-like service? Whereby, the startup, the company, can bring some unique datasets to infuse and add value on top of it, by custom-focusing it and purpose-building it for a particular use case or particular vertical. Whether it's applying it to customer service, in a particular vertical, applying it to, I don't know, marketing content creation, and so on and so forth. That's one category. And I do know that, as one of my startups is in Y Combinator, this season, winter '23, they're saying that a very large chunk of the YC companies in this cycle are about GPT use cases. So we'll see a flurry of that. The next layer, the one below that, is those who actually provide those platforms, whether it's ChatGPT, whatever will emerge from the partnership with Microsoft, and any competitive players that emerge from other startups, or from the big cloud providers, whether it's Facebook, if they ever get into this, and Google, which clearly will, as they need to, to survive around search. The third layer is the enabling layer. As you're going to have more and more of those different large-language models and use case running on top of it, the underlying layers, all the way down to cloud infrastructure, the data infrastructure, and the entire set of tools and systems, that take raw data, and massage it into useful, labeled, contextualized features and data to feed the models, the AI models, whether it's during training, or during inference stages, in production. Personally, my focus is more on the infrastructure than on the application use cases. And I believe that there's going to be a massive amount of innovation opportunity around that, to reach cost-effective, quality, fair models that are deployed easily and maintained easily, or at least with as little pain as possible, at scale. So there are startups that are dealing with it, in various areas. Some are about focusing on labeling automation, some about fairness, about, speaking about cyber, protecting models from threats through data and other issues with it, and so on and so forth. And I believe that this will be, too, a big driver for massive innovation, the infrastructure layer. >> Awesome, and I love how you mentioned the iPhone moment. I call it the browser moment, 'cause it felt that way for me, personally. >> Yep. >> But I think, from a business model standpoint, there is that iPhone shift. It's not the BlackBerry. It's a whole 'nother thing. And I like that. But I do have to ask you, because this is interesting. You mentioned iPhone. iPhone's mostly proprietary. So, in these machine learning foundational models, >> Yeah. >> you're starting to see proprietary hardware, bolt-on, acceleration, bundled together, for faster uptake. And now you got open source emerging, as two things. It's almost iPhone-Android situation happening. >> Yeah. >> So what's your view on that? Because there's pros and cons for either one. You're seeing a lot of these machine learning laws are very proprietary, but they work, and do you care, right? >> Yeah. >> And then you got open source, which is like, "Okay, let's get some upsource code, and let people verify it, and then build with that." Is it a balance? >> Yes, I think- >> Is it mutually exclusive? What's your view? >> I think it's going to be, markets will drive the proportion of both, and I think, for a certain use case, you'll end up with more proprietary offerings. With certain use cases, I guess the fundamental infrastructure for ChatGPT-like, let's say, large-language models and all the use cases running on top of it, that's likely going to be more platform-oriented and open source, and will allow innovation. Think of it as the equivalent of iPhone apps or Android apps running on top of those platforms, as in AI apps. So we'll have a lot of that. Now, when you start going a little bit more into the guts, the lower layers, then it's clear that, for performance reasons, in particular, for certain use cases, we'll end up with more proprietary offerings, whether it's advanced silicon, such as some of the silicon that emerged from entrepreneurs who have left Google, around TensorFlow, and all the silicon that powers that. You'll see a lot of innovation in that area as well. It hopefully intends to improve the cost efficiency of running large AI-oriented workloads, both in inference and in learning stages. >> I got to ask you, because this has come up a lot around Azure and Microsoft. Microsoft, pretty good move getting into the ChatGPT >> Yep. >> and the open AI, because I was talking to someone who's a hardcore Amazon developer, and they said, they swore they would never use Azure, right? One of those types. And they're spinning up Azure servers to get access to the API. So, the developers are flocking, as you mentioned. The YC class is all doing large data things, because you can now program with data, which is amazing, which is amazing. So, what's your take on, I know you got to be kind of neutral 'cause you're an investor, but you got, Amazon has to respond, Google, essentially, did all the work, so they have to have a solution. So, I'm expecting Google to have something very compelling, but Microsoft, right now, is going to just, might run the table on developers, this new wave of data developers. What's your take on the cloud responses to this? What's Amazon, what do you think AWS is going to do? What should Google be doing? What's your take? >> So, each of them is coming from a slightly different angle, of course. I'll say, Google, I think, has massive assets in the AI space, and their underlying cloud platform, I think, has been designed to support such complicated workloads, but they have yet to go as far as opening it up the same way ChatGPT is now in that Microsoft partnership, and Azure. Good question regarding Amazon. AWS has had a significant investment in AI-related infrastructure. Seeing it through my startups, through other lens as well. How will they respond to that higher layer, above and beyond the low level, if you will, AI-enabling apparatuses? How do they elevate to at least one or two layers above, and get to the same ChatGPT layer, good question. Is there an acquisition that will make sense for them to accelerate it, maybe. Is there an in-house development that they can reapply from a different domain towards that, possibly. But I do suspect we'll end up with acquisitions as the arms race around the next level of cloud wars emerges, and it's going to be no longer just about the basic tooling for basic cloud-based applications, and the infrastructure, and the cost management, but rather, faster time to deliver AI in data-heavy applications. Once again, each one of those cloud suppliers, their vendor is coming with different assets, and different pros and cons. All of them will need to just elevate the level of the fight, if you will, in this case, to the AI layer. >> It's going to be very interesting, the different stacks on the data infrastructure, like I mentioned, analytics, data lake, AI, all happening. It's going to be interesting to see how this turns into this AI cloud, like data clouds, data operating systems. So, super fascinating area. Opher, thank you for coming on and sharing your expertise with us. Great to see you, and congratulations on the work. I'll give you the final word here. Give a plugin for what you're looking for for startup seats, pre-seeds. What's the kind of profile that gets your attention, from a seed, pre-seed candidate or entrepreneur? >> Cool, first of all, it's my pleasure. Enjoy our chats, as always. Hopefully the next one's not going to be in nine years. As to what I'm looking for, ideally, smart data entrepreneurs, who have come from a particular domain problem, or problem domain, that they understand, they felt it in their own 10 fingers, or millions of neurons in their brains, and they figured out a way to solve it. Whether it's a data infrastructure play, a cloud infrastructure play, or a very, very smart application that takes advantage of data at scale. These are the things I'm looking for. >> One final, final question I have to ask you, because you're a seasoned entrepreneur, and now coach. What's different about the current entrepreneurial environment right now, vis-a-vis, the past decade? What's new? Is it different, highly accelerated? What advice do you give entrepreneurs out there who are putting together their plan? Obviously, a global resource pool now of engineering. It might not be yesterday's formula for success to putting a venture together to get to that product-market fit. What's new and different, and what's your advice to the folks out there about what's different about the current environment for being an entrepreneur? >> Fantastic, so I think it's a great question. So I think there's a few axes of difference, compared to, let's say, five years ago, 10 years ago, 15 years ago. First and foremost, given the amount of infrastructure out there, the amount of open-source technologies, amount of developer toolkits and frameworks, trying to develop an application, at least at the application layer, is much faster than ever. So, it's faster and cheaper, to the most part, unless you're building very fundamental, core, deep tech, where you still have a big technology challenge to deal with. And absent that, the challenge shifts more to how do you manage my resources, to product-market fit, how are you integrating the GTM lens, the go-to-market lens, as early as possible in the product-market fit cycle, such that you reach from pre-seed to seed, from seed to A, from A to B, with an optimal amount of velocity, and a minimal amount of resources. One big difference, specifically as of, let's say, beginning of this year, late last year, is that money is no longer free for entrepreneurs, which means that you need to operate and build startup in an environment with a lot more constraints. And in my mind, some of the best startups that have ever been built, and some of the big market-changing, generational-changing, if you will, technology startups, in their respective industry verticals, have actually emerged from these times. And these tend to be the smartest, best startups that emerge because they operate with a lot less money. Money is not as available for them, which means that they need to make tough decisions, and make verticals every day. What you don't need to do, you can kick the cow down the road. When you have plenty of money, and it cushions for a lot of mistakes, you don't have that cushion. And hopefully we'll end up with companies with a more agile, more, if you will, resilience, and better cultures in making those tough decisions that startups need to make every day. Which is why I'm super, super excited to see the next batch of amazing unicorns, true unicorns, not just valuation, market rising with the water type unicorns that emerged from this particular era, which we're in the beginning of. And very much enjoy working with entrepreneurs during this difficult time, the times we're in. >> The next 24 months will be the next wave, like you said, best time to do a company. Remember, Airbnb's pitch was, "We'll rent cots in apartments, and sell cereal." Boy, a lot of people passed on that deal, in that last down market, that turned out to be a game-changer. So the crazy ideas might not be that bad. So it's all about the entrepreneurs, and >> 100%. >> this is a big wave, and it's certainly happening. Opher, thank you for sharing. Obviously, data is going to change all the markets. Refactoring, security, FinTech, user experience, applications are going to be changed by data, data operating system. Thanks for coming on, and thanks for sharing. Appreciate it. >> My pleasure. Have a good one. >> Okay, more coverage for the CloudNativeSecurityCon inaugural event. Data will be the key for cybersecurity. theCUBE's coverage continues after this break. (uplifting music)

>>We are back in the final stretch at Supercomputing 22 here in Dallas. I'm your host Paul Gillum with my co-host Dave Nicholson, and we've been talking to so many smart people this week. It just, it makes, boggles my mind are next guest. J Poso is the HPC and AI technology strategist at Dell. Jay also has a PhD in astronomy from the University of Texas. And I'm guessing you were up watching the Artemis launch the other night? >>I, I wasn't. I really should have been, but, but I wasn't, I was in full super computing conference mode. So that means discussions at, you know, various venues with people into the wee hours. >>How did you make the transition from a PhD in astronomy to an HPC expert? >>It was actually really straightforward. I did theoretical astrophysics and I was modeling what white dwarfs look like when they create matter and then explode as type one A super Novi, which is a class of stars that blow up. And it's a very important class because they blow up almost exactly the same way. So if you know how bright they are physically, not just how bright they appear in the sky, but if you can determine from first principles how bright they're, then you have a standard ruler for the universe when they go off in a galaxy, you know how far the galaxy is about how faint it is. So to model these though, you had to understand equations of physics, including electron degeneracy pressure, as well as normal fluid dynamics kinds of of things. And so you were solving for an explosive burning front, ripping through something. And that required a supercomputer to have anywhere close to the fat fidelity to get a reasonable answer and, and hopefully some understanding. >>So I've always said electrons are degenerate. I've always said it and I, and I mentioned to Paul earlier, I said, finally we're gonna get a guest to consort through this whole dark energy dark matter thing for us. We'll do that after, after, after the segment. >>That's a whole different, >>So, well I guess super computing being a natural tool that you would use. What is, what do you do in your role as a strategist? >>So I'm in the product management team. I spend a lot of time talking to customers about what they want to do next. HPC customers are always trying to be maximally productive of what they've got, but always wanting to know what's coming next. Because if you think about it, we can't simulate the entire human body cell for cell on any supercomputer day. We can simulate parts of it, cell for cell or the whole body with macroscopic physics, but not at the, you know, atomic level, the entire organism. So we're always trying to build more powerful computers to solve larger problems with more fidelity and less approximations in it. And so I help people try to understand which technologies for their next system might give them the best advance in capabilities for their simulation work, their data analytics work, their AI work, et cetera. Another part of it is talking to our great technology partner ecosystem and learning about which technologies they have. Cause it feeds the first thing, right? So understanding what's coming, and Dell has a, we're very proud of our large partner ecosystem. We embrace many different partners in that with different capabilities. So understanding those helps understand what your future systems might be. That those are two of the major roles in it. Strategic customers and strategic technologies. >>So you've had four days to wander the, this massive floor here and lots of startups, lots of established companies doing interesting things. What have you seen this week that really excites you? >>So I'm gonna tell you a dirty little secret here. If you are working for someone who makes super computers, you don't get as much time to wander the floor as you would think because you get lots of meetings with people who really want to understand in an NDA way, not just in the public way that's on the floor, but what's, what are you not telling us on the floor? What's coming next? And so I've been in a large number of customer meetings as well as being on the floor. And while I can't obviously share the everything, that's a non-disclosure topic in those, some things that we're hearing a lot about, people are really concerned with power because they see the TDP on the roadmaps for all the silicon providers going way up. And so people with power comes heat as waste. And so that means cooling. >>So power and cooling has been a big topic here. Obviously accelerators are, are increasing in importance in hpc not just for AI calculations, but now also for simulation calculations. And we are very proud of the three new accelerator platforms we launched here at the show that are coming out in a quarter or so. Those are two of the big topics we've seen. You know, there's, as you walk the floor here, you see lots of interesting storage vendors. HPC community's been do doing storage the same way for roughly 20 years. But now we see a lot of interesting players in that space. We have some great things in storage now and some great things that, you know, are coming in a year or two as well. So it's, it's interesting to see that diversity of that space. And then there's always the fun, exciting topics like quantum computing. We unveiled our first hybrid classical quantum computing system here with I on Q and I can't say what the future holds in this, in this format, but I can say we believe strongly in the future of quantum computing and that this, that future will be integrated with the kind of classical computing infrastructure that we make and that will help make quantum computing more powerful downstream. >>Well, let's go down that rabbit hole because, oh boy, boy, quantum computing has been talked about for a long time. There was a lot of excitement about it four or five years ago, some of the major vendors were announcing quantum computers in the cloud. Excitement has kind of died down. We don't see a lot of activity around, no, not a lot of talk around commercial quantum computers, yet you're deep into this. How close are we to have having a true quantum computer or is it a, is it a hybrid? More >>Likely? So there are probably more than 20 and I think close to 40 companies trying different approaches to make quantum computers. So, you know, Microsoft's pursuing a topol topological approach, do a photonics based approach. I, on Q and i on trap approach. These are all different ways of trying to leverage the quantum properties of nature. We know the properties exist, we use 'em in other technologies. We know the physics, but trying the engineering is very difficult. It's very difficult. I mean, just like it was difficult at one point to split the atom. It's very difficult to build technologies that leverage quantum properties of nature in a consistent and reliable and durable way, right? So I, you know, I wouldn't wanna make a prediction, but I will tell you I'm an optimist. I believe that when a tremendous capability with, with tremendous monetary gain potential lines up with another incentive, national security engineering seems to evolve faster when those things line up, when there's plenty of investment and plenty of incentive things happen. >>So I think a lot of my, my friends in the office of the CTO at Dell Technologies, when they're really leading this effort for us, you know, they would say a few to several years probably I'm an optimist, so I believe that, you know, I, I believe that we will sell some of the solution we announced here in the next year for people that are trying to get their feet wet with quantum. And I believe we'll be selling multiple quantum hybrid classical Dell quantum computing systems multiple a year in a year or two. And then of course you hope it goes to tens and hundreds of, you know, by the end of the decade >>When people talk about, I'm talking about people writ large, super leaders in supercomputing, I would say Dell's name doesn't come up in conversations I have. What would you like them to know that they don't know? >>You know, I, I hope that's not true, but I, I, I guess I understand it. We are so good at making the products from which people make clusters that we're number one in servers, we're number one in enterprise storage. We're number one in so many areas of enterprise technology that I, I think in some ways being number one in those things detracts a little bit from a subset of the market that is a solution subset as opposed to a product subset. But, you know, depending on which analyst you talk to and how they count, we're number one or number two in the world in supercomputing revenue. We don't always do the biggest splashy systems. We do the, the frontier system at t, the HPC five system at ENI in Europe. That's the largest academic supercomputer in the world and the largest industrial super >>That's based the world on Dell. Dell >>On Dell hardware. Yep. But we, I think our vision is really that we want to help more people use HPC to solve more problems than any vendor in the world. And those problems are various scales. So we are really concerned about the more we're democratizing HPC to make it easier for more people to get in at any scale that their budget and workloads require, we're optimizing it to make sure that it's not just some parts they're getting, that they are validated to work together with maximum scalability and performance. And we have a great HPC and AI innovation lab that does this engineering work. Cuz you know, one of the myths is, oh, I can just go buy a bunch of servers from company X and a network from company Y and a storage system from company Z and then it'll all work as an equivalent cluster. Right? Not true. It'll probably work, but it won't be the highest performance, highest scalability, highest reliability. So we spend a lot of time optimizing and then we are doing things to try to advance the state of HPC as well. What our future systems look like in the second half of this decade might be very different than what they look like right. Now. >>You mentioned a great example of a limitation that we're running up against right now. You mentioned an entire human body as a, as a, as an organism >>Or any large system that you try to model at the atomic level, but it's a huge macro system, >>Right? So will we be able to reach milestones where we can get our arms entirely around something like an entire human organism with simply quantitative advances as opposed to qualitative advances? Right now, as an example, let's just, let's go down to the basics from a Dell perspective. You're in a season where microprocessor vendors are coming out with next gen stuff and those next NextGen microprocessors, GPUs and CPUs are gonna be plugged into NextGen motherboards, PCI e gen five, gen six coming faster memory, bigger memory, faster networking, whether it's NS or InfiniBand storage controllers, all bigger, better, faster, stronger. And I suspect that systems like Frontera, I don't know, but I suspect that a lot of the systems that are out there are not on necessarily what we would think of as current generation technology, but maybe they're n minus one as a practical matter. So, >>But yeah, I mean they have a lifetime, so Exactly. >>The >>Lifetime is longer than the evolution. >>That's the normal technologies. Yeah. So, so what some people miss is this is, this is the reality that when, when we move forward with the latest things that are being talked about here, it's often a two generation move for an individual, for an individual organization. Yep. >>So now some organizations will have multiple systems and they, the system's leapfrog and technology generations, even if one is their real large system, their next one might be newer technology, but smaller, the next one might be a larger one with newer technology and such. Yeah. So the, the biggest super computing sites are, are often running more than one HPC system that have been specifically designed with the latest technologies and, and designed and configured for maybe a different subset of their >>Workloads. Yeah. So, so the, the, to go back to kinda the, the core question, in your opinion, do we need that qualitative leap to something like quantum computing in order to get to the point, or is it simply a question of scale and power at the, at the, at the individual node level to get us to the point where we can in fact gain insight from a digital model of an entire human body, not just looking at a, not, not just looking at an at, at an organ. And to your point, it's not just about human body, any system that we would characterize as being chaotic today, so a weather system, whatever. Do you, are there any milestones that you're thinking of where you're like, wow, you know, I have, I, I understand everything that's going on, and I think we're, we're a year away. We're a, we're, we're a, we're a compute generation away from being able to gain insight out of systems that right now we can't simply because of scale. It's a very, very long question that I just asked you, but I think I, but hopefully, hopefully you're tracking it. What, what are your, what are your thoughts? What are these, what are these inflection points that we, that you've, in your mind? >>So I, I'll I'll start simple. Remember when we used to buy laptops and we worried about what gigahertz the clock speed was Exactly. Everybody knew the gigahertz of it, right? There's some tasks at which we're so good at making the hardware that now the primary issues are how great is the screen? How light is it, what's the battery life like, et cetera. Because for the set of applications on there, we we have enough compute power. We don't, you don't really need your laptop. Most people don't need their laptop to have twice as powerful a processor that actually rather up twice the battery life on it or whatnot, right? We make great laptops. We, we design for all of those, configure those parameters now. And what, you know, we, we see some customers want more of x, somewhat more of y but the, the general point is that the amazing progress in, in microprocessors, it's sufficient for most of the workloads at that level. Now let's go to HPC level or scientific and technical level. And when it needs hpc, if you're trying to model the orbit of the moon around the earth, you don't really need a super computer for that. You can get a highly accurate model on a, on a workstation, on a server, no problem. It won't even really make it break a sweat. >>I had to do it with a slide rule >>That, >>That >>Might make you break a sweat. Yeah. But to do it with a, you know, a single body orbiting with another body, I say orbiting around, but we both know it's really, they're, they're both ordering the center of mass. It's just that if one is much larger, it seems like one's going entirely around the other. So that's, that's not a super computing problem. What about the stars in a galaxy trying to understand how galaxies form spiral arms and how they spur star formation. Right now you're talking a hundred billion stars plus a massive amount of inter stellar medium in there. So can you solve that on that server? Absolutely not. Not even close. Can you solve it on the largest super computer in the world today? Yes and no. You can solve it with approximations on the largest super computer in the world today. But there's a lot of approximations that go into even that. >>The good news is the simulations produce things that we see through our great telescopes. So we know the approximations are sufficient to get good fidelity, but until you really are doing direct numerical simulation of every particle, right? Right. Which is impossible to do. You need a computer as big as the universe to do that. But the approximations and the science in the science as well as the known parts of the science are good enough to give fidelity. So, and answer your question, there's tremendous number of problem scales. There are problems in every field of science and study that exceed the der direct numerical simulation capabilities of systems today. And so we always want more computing power. It's not macho flops, it's real, we need it, we need exo flops and we will need zeta flops beyond that and yada flops beyond that. But an increasing number of problems will be solved as we keep working to solve problems that are farther out there. So in terms of qualitative steps, I do think technologies like quantum computing, to be clear as part of a hybrid classical quantum system, because they're really just accelerators for certain kinds of algorithms, not for general purpose algorithms. I do think advances like that are gonna be necessary to solve some of the very hardest problem. It's easy to actually formulate an optimization problem that is absolutely intractable by the larger systems in the world today, but quantum systems happen to be in theory when they're big and stable enough, great at that kind of problem. >>I, that should be understood. Quantum is not a cure all for absolutely. For the, for the shortage of computing power. It's very good for certain, certain >>Problems. And as you said at this super computing, we see some quantum, but it's a little bit quieter than I probably expected. I think we're in a period now of everybody saying, okay, there's been a lot of buzz. We know it's gonna be real, but let's calm down a little bit and figure out what the right solutions are. And I'm very proud that we offered one of those >>At the show. We, we have barely scratched the surface of what we could talk about as we get into intergalactic space, but unfortunately we only have so many minutes and, and we're out of them. Oh, >>I'm >>J Poso, HPC and AI technology strategist at Dell. Thanks for a fascinating conversation. >>Thanks for having me. Happy to do it anytime. >>We'll be back with our last interview of Supercomputing 22 in Dallas. This is Paul Gillen with Dave Nicholson. Stay with us.

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> This past week we saw two of the Big 3 cloud providers present the latest update on their respective cloud visions, their business progress, their announcements and innovations. The content at these events had many overlapping themes, including modern cloud infrastructure at global scale, applying advanced machine intelligence, AKA AI, end-to-end data platforms, collaboration software. They talked a lot about the future of work automation. And they gave us a little taste, each company of the Metaverse Web 3.0 and much more. Despite these striking similarities, the differences between these two cloud platforms and that of AWS remains significant. With Microsoft leveraging its massive application software footprint to dominate virtually all markets and Google doing everything in its power to keep up with the frenetic pace of today's cloud innovation, which was set into motion a decade and a half ago by AWS. Hello and welcome to this week's Wikibon CUBE Insights, powered by ETR. In this Breaking Analysis, we unpack the immense amount of content presented by the CEOs of Microsoft and Google Cloud at Microsoft Ignite and Google Cloud Next. We'll also quantify with ETR survey data the relative position of these two cloud giants in four key sectors: cloud IaaS, BI analytics, data platforms and collaboration software. Now one thing was clear this past week, hybrid events are the thing. Google Cloud Next took place live over a 24-hour period in six cities around the world, with the main gathering in New York City. Microsoft Ignite, which normally is attended by 30,000 people, had a smaller event in Seattle, in person with a virtual audience around the world. AWS re:Invent, of course, is much different. Yes, there's a virtual component at re:Invent, but it's all about a big live audience gathering the week after Thanksgiving, in the first week of December in Las Vegas. Regardless, Satya Nadella keynote address was prerecorded. It was highly produced and substantive. It was visionary, energetic with a strong message that Azure was a platform to allow customers to build their digital businesses. Doing more with less, which was a key theme of his. Nadella covered a lot of ground, starting with infrastructure from the compute, highlighting a collaboration with Arm-based, Ampere processors. New block storage, 60 regions, 175,000 miles of fiber cables around the world. He presented a meaningful multi-cloud message with Azure Arc to support on-prem and edge workloads, as well as of course the public cloud. And talked about confidential computing at the infrastructure level, a theme we hear from all cloud vendors. He then went deeper into the end-to-end data platform that Microsoft is building from the core data stores to analytics, to governance and the myriad tooling Microsoft offers. AI was next with a big focus on automation, AI, training models. He showed demos of machines coding and fixing code and machines automatically creating designs for creative workers and how Power Automate, Microsoft's RPA tooling, would combine with Microsoft Syntex to understand documents and provide standard ways for organizations to communicate with those documents. There was of course a big focus on Azure as developer cloud platform with GitHub Copilot as a linchpin using AI to assist coders in low-code and no-code innovations that are coming down the pipe. And another giant theme was a workforce transformation and how Microsoft is using its heritage and collaboration and productivity software to move beyond what Nadella called productivity paranoia, i.e., are remote workers doing their jobs? In a world where collaboration is built into intelligent workflows, and he even showed a glimpse of the future with AI-powered avatars and partnerships with Meta and Cisco with Teams of all firms. And finally, security with a bevy of tools from identity, endpoint, governance, et cetera, stressing a suite of tools from a single provider, i.e., Microsoft. So a couple points here. One, Microsoft is following in the footsteps of AWS with silicon advancements and didn't really emphasize that trend much except for the Ampere announcement. But it's building out cloud infrastructure at a massive scale, there is no debate about that. Its plan on data is to try and provide a somewhat more abstracted and simplified solutions, which differs a little bit from AWS's approach of the right database tool, for example, for the right job. Microsoft's automation play appears to provide simple individual productivity tools, kind of a ground up approach and make it really easy for users to drive these bottoms up initiatives. We heard from UiPath that forward five last month, a little bit of a different approach of horizontal automation, end-to-end across platforms. So quite a different play there. Microsoft's angle on workforce transformation is visionary and will continue to solidify in our view its dominant position with Teams and Microsoft 365, and it will drive cloud infrastructure consumption by default. On security as well as a cloud player, it has to have world-class security, and Azure does. There's not a lot of debate about that, but the knock on Microsoft is Patch Tuesday becomes Hack Wednesday because Microsoft releases so many patches, it's got so much Swiss cheese in its legacy estate and patching frequently, it becomes a roadmap and a trigger for hackers. Hey, patch Tuesday, these are all the exploits that you can go after so you can act before the patches are implemented. And so it's really become a problem for users. As well Microsoft is competing with many of the best-of-breed platforms like CrowdStrike and Okta, which have market momentum and appear to be more attractive horizontal plays for customers outside of just the Microsoft cloud. But again, it's Microsoft. They make it easy and very inexpensive to adopt. Now, despite the outstanding presentation by Satya Nadella, there are a couple of statements that should raise eyebrows. Here are two of them. First, as he said, Azure is the only cloud that supports all organizations and all workloads from enterprises to startups, to highly regulated industries. I had a conversation with Sarbjeet Johal about this, to make sure I wasn't just missing something and we were both surprised, somewhat, by this claim. I mean most certainly AWS supports more certifications for example, and we would think it has a reasonable case to dispute that claim. And the other statement, Nadella made, Azure is the only cloud provider enabling highly regulated industries to bring their most sensitive applications to the cloud. Now, reasonable people can debate whether AWS is there yet, but very clearly Oracle and IBM would have something to say about that statement. Now maybe it's not just, would say, "Oh, they're not real clouds, you know, they're just going to hosting in the cloud if you will." But still, when it comes to mission-critical applications, you would think Oracle is really the the leader there. Oh, and Satya also mentioned the claim that the Edge browser, the Microsoft Edge browser, no questions asked, he said, is the best browser for business. And we could see some people having some questions about that. Like isn't Edge based on Chrome? Anyway, so we just had to question these statements and challenge Microsoft to defend them because to us it's a little bit of BS and makes one wonder what else in such as awesome keynote and it was awesome, it was hyperbole. Okay, moving on to Google Cloud Next. The keynote started with Sundar Pichai doing a virtual session, he was remote, stressing the importance of Google Cloud. He mentioned that Google Cloud from its Q2 earnings was on a $25-billion annual run rate. What he didn't mention is that it's also on a 3.6 billion annual operating loss run rate based on its first half performance. Just saying. And we'll dig into that issue a little bit more later in this episode. He also stressed that the investments that Google has made to support its core business and search, like its global network of 22 subsea cables to support things like, YouTube video, great performance obviously that we all rely on, those innovations there. Innovations in BigQuery to support its search business and its threat analysis that it's always had and its AI, it's always been an AI-first company, he's stressed, that they're all leveraged by the Google Cloud Platform, GCP. This is all true by the way. Google has absolutely awesome tech and the talk, as well as his talk, Pichai, but also Kurian's was forward thinking and laid out a vision of the future. But it didn't address in our view, and I talked to Sarbjeet Johal about this as well, today's challenges to the degree that Microsoft did and we expect AWS will at re:Invent this year, it was more out there, more forward thinking, what's possible in the future, somewhat less about today's problem, so I think it's resonates less with today's enterprise players. Thomas Kurian then took over from Sundar Pichai and did a really good job of highlighting customers, and I think he has to, right? He has to say, "Look, we are in this game. We have customers, 9 out of the top 10 media firms use Google Cloud. 8 out of the top 10 manufacturers. 9 out of the top 10 retailers. Same for telecom, same for healthcare. 8 out of the top 10 retail banks." He and Sundar specifically referenced a number of companies, customers, including Avery Dennison, Groupe Renault, H&M, John Hopkins, Prudential, Minna Bank out of Japan, ANZ bank and many, many others during the session. So you know, they had some proof points and you got to give 'em props for that. Now like Microsoft, Google talked about infrastructure, they referenced training processors and regions and compute optionality and storage and how new workloads were emerging, particularly data-driven workloads in AI that required new infrastructure. He explicitly highlighted partnerships within Nvidia and Intel. I didn't see anything on Arm, which somewhat surprised me 'cause I believe Google's working on that or at least has come following in AWS's suit if you will, but maybe that's why they're not mentioning it or maybe I got to do more research there, but let's park that for a minute. But again, as we've extensively discussed in Breaking Analysis in our view when it comes to compute, AWS via its Annapurna acquisition is well ahead of the pack in this area. Arm is making its way into the enterprise, but all three companies are heavily investing in infrastructure, which is great news for customers and the ecosystem. We'll come back to that. Data and AI go hand in hand, and there was no shortage of data talk. Google didn't mention Snowflake or Databricks specifically, but it did mention, by the way, it mentioned Mongo a couple of times, but it did mention Google's, quote, Open Data cloud. Now maybe Google has used that term before, but Snowflake has been marketing the data cloud concept for a couple of years now. So that struck as a shot across the bow to one of its partners and obviously competitor, Snowflake. At BigQuery is a main centerpiece of Google's data strategy. Kurian talked about how they can take any data from any source in any format from any cloud provider with BigQuery Omni and aggregate and understand it. And with the support of Apache Iceberg and Delta and Hudi coming in the future and its open Data Cloud Alliance, they talked a lot about that. So without specifically mentioning Snowflake or Databricks, Kurian co-opted a lot of messaging from these two players, such as life and tech. Kurian also talked about Google Workspace and how it's now at 8 million users up from 6 million just two years ago. There's a lot of discussion on developer optionality and several details on tools supported and the open mantra of Google. And finally on security, Google brought out Kevin Mandian, he's a CUBE alum, extremely impressive individual who's CEO of Mandiant, a leading security service provider and consultancy that Google recently acquired for around 5.3 billion. They talked about moving from a shared responsibility model to a shared fate model, which is again, it's kind of a shot across AWS's bow, kind of shared responsibility model. It's unclear that Google will pay the same penalty if a customer doesn't live up to its portion of the shared responsibility, but we can probably assume that the customer is still going to bear the brunt of the pain, nonetheless. Mandiant is really interesting because it's a services play and Google has stated that it is not a services company, it's going to give partners in the channel plenty of room to play. So we'll see what it does with Mandiant. But Mandiant is a very strong enterprise capability and in the single most important area security. So interesting acquisition by Google. Now as well, unlike Microsoft, Google is not competing with security leaders like Okta and CrowdStrike. Rather, it's partnering aggressively with those firms and prominently putting them forth. All right. Let's get into the ETR survey data and see how Microsoft and Google are positioned in four key markets that we've mentioned before, IaaS, BI analytics, database data platforms and collaboration software. First, let's look at the IaaS cloud. ETR is just about to release its October survey, so I cannot share the that data yet. I can only show July data, but we're going to give you some directional hints throughout this conversation. This chart shows net score or spending momentum on the vertical axis and overlap or presence in the data, i.e., how pervasive the platform is. That's on the horizontal axis. And we've inserted the Wikibon estimates of IaaS revenue for the companies, the Big 3. Actually the Big 4, we included Alibaba. So a couple of points in this somewhat busy data chart. First, Microsoft and AWS as always are dominant on both axes. The red dotted line there at 40% on the vertical axis. That represents a highly elevated spending velocity and all of the Big 3 are above the line. Now at the same time, GCP is well behind the two leaders on the horizontal axis and you can see that in the table insert as well in our revenue estimates. Now why is Azure bigger in the ETR survey when AWS is larger according to the Wikibon revenue estimates? And the answer is because Microsoft with products like 365 and Teams will often be considered by respondents in the survey as cloud by customers, so they fit into that ETR category. But in the insert data we're stripping out applications and SaaS from Microsoft and Google and we're only isolating on IaaS. The other point is when you take a look at the early October returns, you see downward pressure as signified by those dotted arrows on every name. The only exception was Dell, or Dell and IBM, which showing slightly improved momentum. So the survey data generally confirms what we know that AWS and Azure have a massive lead and strong momentum in the marketplace. But the real story is below the line. Unlike Google Cloud, which is on pace to lose well over 3 billion on an operating basis this year, AWS's operating profit is around $20 billion annually. Microsoft's Intelligent Cloud generated more than $30 billion in operating income last fiscal year. Let that sink in for a moment. Now again, that's not to say Google doesn't have traction, it does and Kurian gave some nice proof points and customer examples in his keynote presentation, but the data underscores the lead that Microsoft and AWS have on Google in cloud. And here's a breakdown of ETR's proprietary net score methodology, that vertical axis that we showed you in the previous chart. It asks customers, are you adopting the platform new? That's that lime green. Are you spending 6% or more? That's the forest green. Is you're spending flat? That's the gray. Is you're spending down 6% or worse? That's the pinkest color. Or are you replacing the platform, defecting? That's the bright red. You subtract the reds from the greens and you get a net score. Now one caveat here, which actually is really favorable from Microsoft, the Microsoft data that we're showing here is across the entire Microsoft portfolio. The other point is, this is July data, we'll have an update for you once ETR releases its October results. But we're talking about meaningful samples here, the ends. 620 for AWS over a thousand from Microsoft in more than 450 respondents in the survey for Google. So the real tell is replacements, that bright red. There is virtually no churn for AWS and Microsoft, but Google's churn is 5x, those two in the survey. Now 5% churn is not high, but you'd like to see three things for Google given it's smaller size. One is less churn, two is much, much higher adoption rates in the lime green. Three is a higher percentage of those spending more, the forest green. And four is a lower percentage of those spending less. And none of these conditions really applies here for Google. GCP is still not growing fast enough in our opinion, and doesn't have nearly the traction of the two leaders and that shows up in the survey data. All right, let's look at the next sector, BI analytics. Here we have that same XY dimension. Again, Microsoft dominating the picture. AWS very strong also in both axes. Tableau, very popular and respectable of course acquired by Salesforce on the vertical axis, still looking pretty good there. And again on the horizontal axis, big presence there for Tableau. And Google with Looker and its other platforms is also respectable, but it again, has some work to do. Now notice Streamlit, that's a recent Snowflake acquisition. It's strong in the vertical axis and because of Snowflake's go-to-market (indistinct), it's likely going to move to the right overtime. Grafana is also prominent in the Y axis, but a glimpse at the most recent survey data shows them slightly declining while Looker actually improves a bit. As does Cloudera, which we'll move up slightly. Again, Microsoft just blows you away, doesn't it? All right, now let's get into database and data platform. Same X Y dimensions, but now database and data warehouse. Snowflake as usual takes the top spot on the vertical axis and it is actually keeps moving to the right as well with again, Microsoft and AWS is dominant in the market, as is Oracle on the X axis, albeit it's got less spending velocity, but of course it's the database king. Google is well behind on the X axis but solidly above the 40% line on the vertical axis. Note that virtually all platforms will see pressure in the next survey due to the macro environment. Microsoft might even dip below the 40% line for the first time in a while. Lastly, let's look at the collaboration and productivity software market. This is such an important area for both Microsoft and Google. And just look at Microsoft with 365 and Teams up into the right. I mean just so impressive in ubiquitous. And we've highlighted Google. It's in the pack. It certainly is a nice base with 174 N, which I can tell you that N will rise in the next survey, which is an indication that more people are adopting. But given the investment and the tech behind it and all the AI and Google's resources, you'd really like to see Google in this space above the 40% line, given the importance of this market, of this collaboration area to Google's success and the degree to which they emphasize it in their pitch. And look, this brings up something that we've talked about before on Breaking Analysis. Google doesn't have a tech problem. This is a go-to-market and marketing challenge that Google faces and it's up against two go-to-market champs and Microsoft and AWS. And Google doesn't have the enterprise sales culture. It's trying, it's making progress, but it's like that racehorse that has all the potential in the world, but it's just missing some kind of key ingredient to put it over at the top. It's always coming in third, (chuckles) but we're watching and Google's obviously, making some investments as we shared with earlier. All right. Some final thoughts on what we learned this week and in this research: customers and partners should be thrilled that both Microsoft and Google along with AWS are spending so much money on innovation and building out global platforms. This is a gift to the industry and we should be thankful frankly because it's good for business, it's good for competitiveness and future innovation as a platform that can be built upon. Now we didn't talk much about multi-cloud, we haven't even mentioned supercloud, but both Microsoft and Google have a story that resonates with customers in cross cloud capabilities, unlike AWS at this time. But we never say never when it comes to AWS. They sometimes and oftentimes surprise you. One of the other things that Sarbjeet Johal and John Furrier and I have discussed is that each of the Big 3 is positioning to their respective strengths. AWS is the best IaaS. Microsoft is building out the kind of, quote, we-make-it-easy-for-you cloud, and Google is trying to be the open data cloud with its open-source chops and excellent tech. And that puts added pressure on Snowflake, doesn't it? You know, Thomas Kurian made some comments according to CRN, something to the effect that, we are the only company that can do the data cloud thing across clouds, which again, if I'm being honest is not really accurate. Now I haven't clarified these statements with Google and often things get misquoted, but there's little question that, as AWS has done in the past with Redshift, Google is taking a page out of Snowflake, Databricks as well. A big difference in the Big 3 is that AWS doesn't have this big emphasis on the up-the-stack collaboration software that both Microsoft and Google have, and that for Microsoft and Google will drive captive IaaS consumption. AWS obviously does some of that in database, a lot of that in database, but ISVs that compete with Microsoft and Google should have a greater affinity, one would think, to AWS for competitive reasons. and the same thing could be said in security, we would think because, as I mentioned before, Microsoft competes very directly with CrowdStrike and Okta and others. One of the big thing that Sarbjeet mentioned that I want to call out here, I'd love to have your opinion. AWS specifically, but also Microsoft with Azure have successfully created what Sarbjeet calls brand distance. AWS from the Amazon Retail, and even though AWS all the time talks about Amazon X and Amazon Y is in their product portfolio, but you don't really consider it part of the retail organization 'cause it's not. Azure, same thing, has created its own identity. And it seems that Google still struggles to do that. It's still very highly linked to the sort of core of Google. Now, maybe that's by design, but for enterprise customers, there's still some potential confusion with Google, what's its intentions? How long will they continue to lose money and invest? Are they going to pull the plug like they do on so many other tools? So you know, maybe some rethinking of the marketing there and the positioning. Now we didn't talk much about ecosystem, but it's vital for any cloud player, and Google again has some work to do relative to the leaders. Which brings us to supercloud. The ecosystem and end customers are now in a position this decade to digitally transform. And we're talking here about building out their own clouds, not by putting in and building data centers and installing racks of servers and storage devices, no. Rather to build value on top of the hyperscaler gift that has been presented. And that is a mega trend that we're watching closely in theCUBE community. While there's debate about the supercloud name and so forth, there little question in our minds that the next decade of cloud will not be like the last. All right, we're going to leave it there today. Many thanks to Sarbjeet Johal, and my business partner, John Furrier, for their input to today's episode. Thanks to Alex Myerson who's on production and manages the podcast and Ken Schiffman as well. Kristen Martin and Cheryl Knight helped get the word out on social media and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE, who does some wonderful editing. And check out SiliconANGLE, a lot of coverage on Google Cloud Next and Microsoft Ignite. Remember, all these episodes are available as podcast wherever you listen. Just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. And you can always get in touch with me via email, david.vellante@siliconangle.com or you can DM me at dvellante or comment on my LinkedIn posts. And please do check out etr.ai, the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE Insights, powered by ETR. Thanks for watching and we'll see you next time on Breaking Analysis. (gentle music)

>> From theCUBE studios in Palo Alto in Boston bringing you data driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> The term Supercloud is somewhat new, but the concepts behind it have been bubbling for years, early last decade when NIST put forth a definition of cloud computing it said services had to be accessible over a public network essentially cutting the on-prem crowd out of the cloud conversation. Now a guy named Chuck Hollis, who was a field CTO at EMC at the time and a prolific blogger objected to that criterion and laid out his vision for what he termed a private cloud. Now, in that post, he showed a workload running both on premises and in a public cloud sharing the underlying resources in an automated and seamless manner. What later became known more broadly as hybrid cloud that vision as we now know, really never materialized, and we were left with multi-cloud sets of largely incompatible and disconnected cloud services running in separate silos. The point is what Hollis laid out, IE the ability to abstract underlying infrastructure complexity and run workloads across multiple heterogeneous estates with an identical experience is what super cloud is all about. Hello and welcome to this week's Wikibon cube insights powered by ETR and this breaking analysis. We share what we hope to learn from super cloud 22 next week, next Tuesday at 9:00 AM Pacific. The community is gathering for Supercloud 22 an inclusive pilot symposium hosted by theCUBE and made possible by VMware and other founding partners. It's a one day single track event with more than 25 speakers digging into the architectural, the technical, structural and business aspects of Supercloud. This is a hybrid event with a live program in the morning running out of our Palo Alto studio and pre-recorded content in the afternoon featuring industry leaders, technologists, analysts and investors up and down the technology stack. Now, as I said up front the seeds of super cloud were sewn early last decade. After the very first reinvent we published our Amazon gorilla post, that scene in the upper right corner here. And we talked about how to differentiate from Amazon and form ecosystems around industries and data and how the cloud would change IT permanently. And then up in the upper left we put up a post on the old Wikibon Wiki. Yeah, it used to be a Wiki. Check out my hair by the way way no gray, that's how long ago this was. And we talked about in that post how to compete in the Amazon economy. And we showed a graph of how IT economics were changing. And cloud services had marginal economics that looked more like software than hardware at scale. And this would reset, we said opportunities for both technology sellers and buyers for the next 20 years. And this came into sharper focus in the ensuing years culminating in a milestone post by Greylock's Jerry Chen called Castles in the Cloud. It was an inspiration and catalyst for us using the term Supercloud in John Furrier's post prior to reinvent 2021. So we started to flesh out this idea of Supercloud where companies of all types build services on top of hyperscale infrastructure and across multiple clouds, going beyond multicloud 1.0, if you will, which was really a symptom, as we said, many times of multi-vendor at least that's what we argued. And despite its fuzzy definition, it resonated with people because they knew something was brewing, Keith Townsend the CTO advisor, even though he frankly, wasn't a big fan of the buzzy nature of the term Supercloud posted this awesome Blackboard on Twitter take a listen to how he framed it. Please play the clip. >> Is VMware the right company to make the super cloud work, term that Wikibon came up with to describe the taking of discreet services. So it says RDS from AWS, cloud compute engines from GCP and authentication from Azure to build SaaS applications or enterprise applications that connect back to your data center, is VMware's cross cloud vision 'cause it is just a vision today, the right approach. Or should you be looking towards companies like HashiCorp to provide this overall capability that we all agree, or maybe you don't that we need in an enterprise comment below your thoughts. >> So I really like that Keith has deep practitioner knowledge and lays out a couple of options. I especially like the examples he uses of cloud services. He recognizes the need for cross cloud services and he notes this capability is aspirational today. Remember this was eight or nine months ago and he brings HashiCorp into the conversation as they're one of the speakers at Supercloud 22 and he asks the community, what they think, the thing is we're trying to really test out this concept and people like Keith are instrumental as collaborators. Now I'm sure you're not surprised to hear that mot everyone is on board with the Supercloud meme, in particular Charles Fitzgerald has been a wonderful collaborator just by his hilarious criticisms of the concept. After a couple of super cloud posts, Charles put up his second rendition of "Supercloudifragilisticexpialidoucious". I mean, it's just beautiful, but to boot, he put up this picture of Baghdad Bob asking us to just stop, Bob's real name is Mohamed Said al-Sahaf. He was the minister of propaganda for Sadam Husein during the 2003 invasion of Iraq. And he made these outrageous claims of, you know US troops running in fear and putting down their arms and so forth. So anyway, Charles laid out several frankly very helpful critiques of Supercloud which has led us to really advance the definition and catalyze the community's thinking on the topic. Now, one of his issues and there are many is we said a prerequisite of super cloud was a super PaaS layer. Gartner's Lydia Leong chimed in saying there were many examples of successful PaaS vendors built on top of a hyperscaler some having the option to run in more than one cloud provider. But the key point we're trying to explore is the degree to which that PaaS layer is purpose built for a specific super cloud function. And not only runs in more than one cloud provider, Lydia but runs across multiple clouds simultaneously creating an identical developer experience irrespective of a state. Now, maybe that's what Lydia meant. It's hard to say from just a tweet and she's a sharp lady, so, and knows more about that market, that PaaS market, than I do. But to the former point at Supercloud 22, we have several examples. We're going to test. One is Oracle and Microsoft's recent announcement to run database services on OCI and Azure, making them appear as one rather than use an off the shelf platform. Oracle claims to have developed a capability for developers specifically built to ensure high performance low latency, and a common experience for developers across clouds. Another example we're going to test is Snowflake. I'll be interviewing Benoit Dageville co-founder of Snowflake to understand the degree to which Snowflake's recent announcement of an application development platform is perfect built, purpose built for the Snowflake data cloud. Is it just a plain old pass, big whoop as Lydia claims or is it something new and innovative, by the way we invited Charles Fitz to participate in Supercloud 22 and he decline saying in addition to a few other somewhat insulting things there's definitely interesting new stuff brewing that isn't traditional cloud or SaaS but branding at all super cloud doesn't help either. Well, indeed, we agree with part of that and we'll see if it helps advanced thinking and helps customers really plan for the future. And that's why Supercloud 22 has going to feature some of the best analysts in the business in The Great Supercloud Debate. In addition to Keith Townsend and Maribel Lopez of Lopez research and Sanjeev Mohan from former Gartner analyst and principal at SanjMo participated in this session. Now we don't want to mislead you. We don't want to imply that these analysts are hopping on the super cloud bandwagon but they're more than willing to go through the thought experiment and mental exercise. And, we had a great conversation that you don't want to miss. Maribel Lopez had what I thought was a really excellent way to think about this. She used TCP/IP as an historical example, listen to what she said. >> And Sanjeev Mohan has some excellent thoughts on the feasibility of an open versus de facto standard getting us to the vision of Supercloud, what's possible and what's likely now, again, I don't want to imply that these analysts are out banging the Supercloud drum. They're not necessarily doing that, but they do I think it's fair to say believe that something new is bubbling and whether it's called Supercloud or multicloud 2.0 or cross cloud services or whatever name you choose it's not multicloud of the 2010s and we chose Supercloud. So our goal here is to advance the discussion on what's next in cloud and Supercloud is meant to be a term to describe that future of cloud and specifically the cloud opportunities that can be built on top of hyperscale, compute, storage, networking machine learning, and other services at scale. And that is why we posted this piece on Answering the top 10 questions about Supercloud. Many of which were floated by Charles Fitzgerald and others in the community. Why does the industry need another term what's really new and different? And what is hype? What specific problems does Supercloud solve? What are the salient characteristics of Supercloud? What's different beyond multicloud? What is a super pass? Is it necessary to have a Supercloud? How will applications evolve on superclouds? What workloads will run? All these questions will be addressed in detail as a way to advance the discussion and help practitioners and business people understand what's real today. And what's possible with cloud in the near future. And one other question we'll address is who will build super clouds? And what new entrance we can expect. This is an ETR graphic that we showed in a previous episode of breaking analysis, and it lays out some of the companies we think are building super clouds or in a position to do so, by the way the Y axis shows net score or spending velocity and the X axis depicts presence in the ETR survey of more than 1200 respondents. But the key callouts to this slide in addition to some of the smaller firms that aren't yet showing up in the ETR data like Chaossearch and Starburst and Aviatrix and Clumio but the really interesting additions are industry players Walmart with Azure, Capital one and Goldman Sachs with AWS, Oracle, with Cerner. These we think are early examples, bubbling up of industry clouds that will eventually become super clouds. So we'll explore these and other trends to get the community's input on how this will all play out. These are the things we hope you'll take away from Supercloud 22. And we have an amazing lineup of experts to answer your question. Technologists like Kit Colbert, Adrian Cockcroft, Mariana Tessel, Chris Hoff, Will DeForest, Ali Ghodsi, Benoit Dageville, Muddu Sudhakar and many other tech athletes, investors like Jerry Chen and In Sik Rhee the analyst we featured earlier, Paula Hansen talking about go to market in a multi-cloud world Gee Rittenhouse talking about cloud security, David McJannet, Bhaskar Gorti of Platform9 and many, many more. And of course you, so please go to theCUBE.net and register for Supercloud 22, really lightweight reg. We're not doing this for lead gen. We're doing it for collaboration. If you sign in you can get the chat and ask questions in real time. So don't miss this inaugural event Supercloud 22 on August 9th at 9:00 AM Pacific. We'll see you there. Okay. That's it for today. Thanks for watching. Thank you to Alex Myerson who's on production and manages the podcast. Kristen Martin and Cheryl Knight. They help get the word out on social media and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE. Does some really wonderful editing. Thank you to all. Remember these episodes are all available as podcasts wherever you listen, just search breaking analysis podcast. I publish each week on wikibon.com and Siliconangle.com. And you can email me at David.Vellantesiliconangle.com or DM me at Dvellante, comment on my LinkedIn post. Please do check out ETR.AI for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE insights powered by ETR. Thanks for watching. And we'll see you next week in Palo Alto at Supercloud 22 or next time on breaking analysis. (calm music)

>>Welcome to this Q conversation. I'm Dave Nicholson. And today we are joined by Andrew ish and Chris Y Moran, both from Gentech. Andrew is the vice president of marketing. Chris John is the, uh, vice president of product engineering, gentlemen, welcome to the cube. >>Welcome David. Thanks for having us. Hey, >>David, thanks for having us on your show. >>Absolutely. Give us just, let's start out by, uh, giving us some background on, on Gentech. How would you describe to a relative coming over and asking you what you do for a living? What Genotech does? >>Well, I'll take a shot at that. I'm the marketing guy, David, but, uh, I think the best way to think of Genotech first and foremost is a software company. We, uh, we do a really good job of bringing together all of that physical security sensor network onto a platform. So people can make sense out of the data that comes from video surveillance, cameras, access control, reads, license plate recognition, cameras, and from a whole host of different sensors that can live out there in the world. Temperature, sensors, microwaves, all sorts of stuff. So we're a company that's really good at making sense of complex data from sensors. That's kind of, I think that's kind of what we >>Do and, and, and we focus specifically on like larger, complex, critical infrastructure type projects, whether they be airports, uh, large enterprise campuses and whatnot. So we're not necessarily your well known consumer type brand. >>So you mentioned physical, you mentioned physical security. Um, what about the intersection between physical security and, and cyber security who are, who are the folks that you work with directly as customers and where do they, where do they sit in that spectrum of cyber versus physical? >>So we predominantly work with physical security professionals and, uh, they typically are responsible for the security of a facility, a campus, a certain area. And we'll talk about security cameras. We'll talk about access control devices with card readers and, and, and locks, uh, intrusion detection, systems, fences, and whatnot. So anything that you would see that physically protects a facility. And, uh, what's actually quite interesting is that, you know, cybersecurity, we, we hear about cybersecurity and depressed all the time, right. And who's been hacked this week is typically like, uh, a headline that we're all like looking at, uh, we're looking for in the news. Um, so we actually do quite a lot of, I would say education work with the physical security professional as it pertains to the importance of cyber security in the physical security system, which in and of itself is an information system. Right. Um, so you don't wanna put a system in place to protect your facility that is full of cybersecurity holes because at that point, you know, your physical security systems becomes, uh, your weakest link in your security chain. Uh, the way I like to say it is, you know, there's no such thing as physical security versus cyber security, it's just security. Uh, really just the concept or a context of what threat vectors does this specific control or mechanism actually protects against >>Those seem to be words to live by, but are, are they aspirational? I mean, do you, do you see gaps today, uh, between the worlds of cyber and physical security? >>I mean, for sure, right? Like we, physical security evolved from a different part of the enterprise, uh, structure then did it or cyber security. So they, they come at things from a different angle. Um, so, you know, for a long time, the two worlds didn't really meet. Uh, but now what we're seeing, I would say in the last 10 years, Christian, about that, there's a huge convergence of cyber security with physical security. It, so information technology with operation technology really coming together quite tightly in the industry. And I think leading companies and sophisticated CISOs are really giving a big pitcher thought to what's going on across the organization, not just in cybersecurity. >>Yeah. I think we've come a long way from CCTV, which stands for closed circuit television, uh, which was typically like literally separated from the rest of the organization, often managed by the facilities, uh, part of any organization. Uh, and now we're seeing more and more organizations where this is converging together, but there's still ways to go, uh, to get this proper convergence in place. But, you know, we're getting there. >>How, how does Gentech approach its addressable market? Is this, is this a direct model? Uh, do you work with partners? What, what does that look like in your world? >>Well, we're a, we're a partner led company Gentech, you know, model on many friends is all about our partners. So we go to market through our integration channel. So we work with really great integrators all around the world. Um, and they bring together our software platform, which is usually forms the nucleus of sort of any O T security network. Uh, they bring that together with all sorts of other things, such as the sensor network, the cabling, all of that. It's a very complex multiplayer world. And also in that, you know, partnership ecosystem and Christian, this is more your world. We have to build deep integrations with all of these companies that build sensors, whether that's access, Bosch, Canon, uh, Hanoi, you know, we're, we're really working with them them. And of course with our storage and server partners >>Like Dell >>Mm-hmm <affirmative>. Yeah. So we have, we have like hundreds of, I would say ecosystem partners, right? Camera manufacturers, uh, access control reader, controller manufacturers, intrusion detection, manufacturers, late LIDAR radar, you know, the list goes on and on and on. And, and basically we bring this all together. The system integrator really is going to pick best of breed based on a specific end customer's I would say requirements and then roll out the system. According >>That's very interesting, you know, at, at Silicon angle on the cube, um, we've initiated coverage of this subject of the question, does hardware still matter? And, and you know, of course we're, we're approaching that primarily from kind of the traditional it, uh, perspective, but you said at the outset, you you're a software company mm-hmm <affirmative>, but clearly correct me if I'm wrong, your software depends upon all of these hardware components and as they improve, I imagine you can do things that maybe you couldn't do before those improvements. The first thing that comes to mind is just camera resolution. Um, you know, sort of default today is 4k, uh, go back five years, 10 years. I imagine that some of the sophisticated things that you can do today weren't possible because the hardware was lagging. Is that, is that a, is that a fair assessment? >>Oh, that's a fair assessment. Just going back 20 years ago. Uh, just VGA resolution on a security camera was like out of this world resolution, uh, even more so if it was like full motion, 30 images per second. So you typically have like, probably even like three 20 by 2 44 images per second, like really lousy resolution, just from a resolution perspective, the, the imagery sensors have, have really increased in terms of what they can provide, but even more so is the horsepower of these devices. Mm-hmm, <affirmative> now it's not uncommon to have, uh, pretty, pretty powerful Silicon in those devices now that can actually run machine learning models and you can actually do computer vision and analytics straight into the device. Uh, as you know, in some of the initial years, you would actually run this on kind of racks of servers in this data center. >>Now you can actually distribute those workloads across on the edge. And what we're seeing is, you know, the power that the edge provides is us as a software company, we have the opportunity to actually bring our workloads where it makes most sense. And in some cases we'll actually also have a ground station kind of in between the sensors and potentially the cloud, uh, because the use case just, uh, calls for it. Uh, just looking from a, from a, from a video security perspective, you know, when you have hundreds or thousands of cameras on an airport, it's just not economical or not even feasible in some cases to bring all that footage to the cloud even more so when 99% of that footage is never watched by anybody. So what's the point. Uh, so you just wanna provide the clips that, that actually do matter to the cloud and for longer term retention, you also want to be able to have sometimes more resilient systems, right? So what happens if the cloud disconnects, you can stop the operations of that airport or stop that operations of that, of that prison, right? It needs to continue to operate and therefore you need higher levels of resiliency. So you do need that hardware. So it's really a question of what it calls for and having the right size type of hardware so that you don't overly complexify the installation, uh, and, and actually get the job done. Are >>You comparing airports to prisons >>Christian? Well, nowadays they're pretty much prepared <laugh>, >>But I mean, this is exactly it, David, but I mean, this payload, especially from the video surveillance, like the, the workload that's going through to the, these ground stations really demands flexible deployment, right? So like we think about it as edge to cloud and, uh, you know, that's, what's really getting us excited because it, it gives so much more flexibility to the, you know, the C I S O and security professionals in places like prisons, airports, also large scale retail and banking, and, uh, other places, >>Universities, the list goes on and on and on, and >>On the flexibility of deployment just becomes so much easier because these are lightweight, you usually word deploying on a Linux box and it can connect seamlessly with like large scale head end storage or directly to, uh, cloud providers. It's, it's really a sophisticated new way of looking at how you architect out these networks. >>You've just given, you've just given a textbook example of why, uh, folks in the it world have been talking about hybrid cloud for, for, for such a long time, and some have scoffed at the idea, but you just, you just present a perfect use case for that combination of leveraging cloud with, uh, on-premises hardware and tracking with hardware advances, um, uh, on, on the subject of camera resolution. I don't know if you've seen this meme, but there's a great one with the, the first deep field image from the, from the, I was gonna say humble, the James web space telescope, uh, in contrast with a security camera F photo, which is really blurry of someone in your driveway <laugh>, uh, which is, which is, uh, sort of funny. The reality though, is I've seen some of these latest generation security cameras, uh, you know, beyond 4k resolution. And it's amazing just, you know, the kind of detail that you can get into, but talk about what what's, what's exciting in your world. What's, what's Gentech doing, you know, over the next, uh, several quarters that's, uh, particularly interesting what's on the leading edge of your, of your world. >>Well, I think right now what's on the leading edges is being driven by our end users. So the, so the, the companies, the governments, the organizations that are implementing our software into these complex IOT networks, they wanna do more with that data, right? It's not just about, you know, monitoring surveillance. It's not just about opening and closing doors or reading license plates, but more and more we're seeing organizations taking this bigger picture view of the data that is generated in their organizations and how they can take value out of existing investments that they've made in sensor networks, uh, and to take greater insight into operations, whether that can be asset utilization, customer service efficiency, it becomes about way more than just, you know, either physical security or cyber security. It becomes really an enterprise shaping O T network. And to us, that is like a massive, massive opportunity, uh, in the, in the industry today. >>Yeah. >>Now you're you're you're oh, go ahead. I'm sorry, Christian, go ahead. Yeah, >>No, it's, it's, it's good. But, you know, going back to a comment that I mentioned earlier about how it was initially siloed and now, you know, we're kind of discovering this diamond in the rough, in terms of all these sensors that are out there, which a lot of organizations didn't even know existed or didn't even know they had. And how can you bring that on kind of across the organizations for non-security related applications? So that's kind of one very interesting kind of, uh, direction that we're, that we've been undergoing for the last few years, and then, you know, security, uh, and physical security for that matter often is kind of the bastard step child. Doesn't get all the budget and, you know, there's lots of opportunities for, to help them increase and improve their operations, uh, as, as Andrew pointed out and really help bringing them into the 21st century. >>Yeah. >>And you're, you're headquartered in Montreal, correct? >>Yes. >>Yeah. So, so the reason, the reason why that's interesting is because, um, and, you know, correct me if I'm, if I'm off base here, but, but you're sort of the bridge between north America and Europe. Uh, and, and, uh, and so you sit at that nexus where, uh, you probably have more of an awareness of, uh, trends in security, which overlap with issues of privacy. Yeah. Where Europe has led in a lot of cases. Um, some of those European like rules are coming to north America. Um, is there anything in your world that is particularly relevant or that concerns you about north America catching up, um, or, or do those worlds of privacy and security not overlap as much as I might think they do? >>Ah, thank you. Any >>Thoughts? >>Absolutely not. No, no. <laugh> joking aside. This is, this is, this is, >>Leave me hanging >><laugh>, uh, this is actually core to our DNA. And, and, and we, we often say out loud how, like Europe has really paved the way for a different way, uh, of, of looking at privacy from a security setting, right. And they're not mutually exclusive. Right. You can have high security all while protecting people's privacy. And it's all of a question of ensuring that, you know, how you kind of, I would say, uh, ethically, uh, use said technology and we can actually put some safeguards in it. So to minimize the likelihood of there being abuse, right? There's, there's something that we do, which we call the privacy protector, which, you know, for all intents and purposes, it's not that complex of an idea. It's, it's really the concept of you have security cameras in a public space or a more sensitive location. And you have your security guards that can actually watch that footage when nothing really happens. >>You, you want to protect people's privacy in these situations. Uh, however, you still want to be able to provide a view to the security guard so they can still make out that, you know, there there's actually people walking around or there's a fight that broke out. And in the likelihood that something did happen, then you can actually view the overall footage. So, and with, with the details that the cameras that you had, you know, the super high mega pixel cameras that you have will provide. So we blur the images of the individuals. We still keep the background. And once you have the proper authorization, and this is based on the governance of the organization, so it can be a four I principle where it could be the chief security officer with the chief privacy officer need to authorize this footage to be kind of UN blurred. And at that point you can UN blur the footage and provide it to law enforcement for the investigation, for example. >>Excellent. I've got Andrew, if you wanted, then I, then I'm. Well, so I, I've a, I have a final question for you. And this comes out of a game that, uh, some friends and I, some friends of mine and I devised over the years, primarily this is played with strangers that you meet on airplanes as you're traveling. But the question you ask is in your career, what you're doing now and over the course of your careers, um, what's the most shocking thing <laugh> that people would learn from what, you know, what do you, what do you find? What's the craziest thing. When you go in to look at these environments that you see that people should maybe address, um, well, go ahead and start with you, Andrew. >>I, >>The most shocking thing you see every day in your world, >>It's very interesting. The most shocking thing I think we've seen in the industry is how willing, uh, some professionals are in our industry to install any kind of device on their networks without actually taking the time to do due diligence on what kind of security risks these devices can have on a network. Because I think a lot of people don't think about a security camera as first and foremost, a computer, and it's a computer with an IP address on a network, and it has a visual sensor, but we always get pulled in by that visual sensor. Right. And it's like, oh, it's a camera. No, it's a computer. And, you know, over the last, I would say eight years in the industry, we've spent a lot of time trying to sensitize the industry to the fact that, you know, you can't just put devices on your, your network without understanding the supply chain, without understanding the motives behind who's put these together and their track record of cybersecurity. So probably the weirdest thing that I've seen in my, um, you know, career in this industry is just the willingness of people not to take time to do due diligence before they hook something up on onto their corporate network where, you know, data can start leaking out, being exfiltrated by those devices and malevolent actors behind them. So gotta ask questions about what you put on your network. >>Christian, did he steal your, did he steal your thunder? Do you have any other, any other thoughts? >>Well, so first of all, there's things I just cannot say on TV. Okay. But you can't OK. >>You can't. Yeah, yeah, yeah. Saying that you're shocked that not everyone speaks French doesn't count. Okay. Let's just get, let's get past that, but, but go, but yeah, go ahead. Any thoughts? >>So, uh, you know, I, I would say something that I I've seen a lot and, and specifically with customers sometimes that were starting to shop for a new system is you'd be surprised by first of all, there's a camera, the likelihood of actually somebody watching it live while you're actually in the field of view of that camera is close to Neil first and foremost, second, there's also a good likelihood that that camera doesn't even record. It actually is not even functional. And, and I would say a lot of organizations often realize that, you know, that camera was not functioning when they actually knew do need to get the footage. And we've seen this with some large incidents, uh, very, uh, bad incidents that happened, uh, whether in the UK or in Boston or whatnot, uh, when they're, when law enforcement is trying to get footage and they realize that a lot of cameras actually weren't recording and, and, and goes back to Andrew's point in terms of the selection process of these devices. >>Yeah. Image resolution is important, like, because you need an, an image that it actually usable so that you can actually do something with it forensically, but you know, these cameras need to be recorded by a reliable system and, and should something happen with the device. And there's always going to be something, you know, power, uh, uh, a bird ate the lens. I don't know what it might be, or squirrel ate the wire. Um, and the camera doesn't work anymore. So you have to replace it. So having a system that provides, you know, you with like health insights in terms of, of, of if it's working or not is, is actually quite important. It needs to be managed like any it environment, right? Yeah. You have all these devices and if one of them goes down, you need to manage it. And most organizations it's fire and forget, I sign a purchase order. I bought my security system, I installed it. It's done. We move on to the next one and seven years later, something bad happens. And like, uhoh, >>It's not a CCTV system. It's a network. Yeah. Life cycle management counts. >>Well, uh, I have to say on that, uh, I'm gonna be doing some research on Canadian birds and squirrels. I, I had no idea, >>Very hungry. >>Andrew, Chris, John, thank you so much. Great conversation, uh, from all of us here at the cube. Thanks for tuning in. Stay tuned. The cube from Silicon angle media, we are your leader in tech coverage.

>>Hey, everyone. Welcome to the AWS partner, showcase women in tech. I'm Lisa Martin from the cube. And today we're gonna be looking into the exciting evolution of women in the tech industry. I'm going to be joined by Danielle GShock, the ISP PSA director at AWS. And we have the privilege of speaking with some wicked smart women from Teradata NetApp. JFI a 10th revolution group, company and honeycomb.io. We're gonna look at some of the challenges and biases that women face in the tech industry, especially in leadership roles. We're also gonna be exploring how are these tech companies addressing diversity, equity and inclusion across their organizations? How can we get more young girls into stem earlier in their careers? So many questions. So let's go ahead and get started. This is the AWS partner showcase women in tech. Hey, everyone. Welcome to the AWS partner showcase. This is season one, episode three. And I'm your host, Lisa Martin. I've got two great guests here with me to talk about women in tech. Hillary Ashton joins us the chief product officer at Terry data. And Danielle Greshaw is back with us, the ISV PSA director at AWS ladies. It's great to have you on the program talking through such an important topic, Hillary, let's go ahead and start with you. Give us a little bit of an intro into you, your background, and a little bit about Teradata. >>Yeah, absolutely. So I'm Hillary Ashton. I head up the products organization. So that's our engineering product management office of the CTO team. Um, at Teradata I've been with Terra data for just about three years and really have spent the last several decades. If I can say that in the data and analytics space, um, I spent time, uh, really focused on the value of, of analytics at scale, and I'm super excited to be here at Teradata. I'm also a mom of two teenage boys. And so as we talk about women in tech, I think there's, um, uh, lots of different dimensions and angles of that. Um, at Teradata, we are partnered very deeply with AWS and happy to talk a little bit more about that, um, throughout this discussion as well. >>Excellent. A busy mom of two teen boys. My goodness. I don't know how you do it. Let's now look, Atter data's views of diversity, equity and inclusion. It's a, the, it's a topic that's important to everyone, but give us a snapshot into some of the initiatives that Terra data has there. >>Yeah, I have to say, I am super proud to be working at Teradata. We have gone through, uh, a series of transformations, but I think it starts with culture and we are deeply committed to diversity, equity and inclusion. It's really more than just a statement here. It's just how we live our lives. Um, and we use, uh, data to back that up. Um, in fact, we were named one of the world's most ethical companies for the 13th year in a row. Um, and all of our executive leadership team has taken an oath around D E and I that's available on LinkedIn as well. So, um, in fact, our leadership team reporting into the CEO is just about 50 50, um, men and women, which is the first time I've worked in a company where that has been the case. And I think as individuals, we can probably appreciate what a huge difference that makes in terms of not just being a representative, but truly being on a, on a diverse and equitable, uh, team. And I think it really, uh, improves the behaviors that we can bring, um, to our office. >>There's so much value in that. It's I impressive to see about a 50 50 at the leadership level. That's not something that we see very often. Tell me how you, Hillary, how did you get into tech? Were you an engineering person by computer science, or did you have more of a zigzaggy path to where you are now? >>I'm gonna pick door number two and say more zigzaggy. Um, I started off thinking, um, that I started off as a political science major or a government major. Um, and I was probably destined to go into, um, the law field, but actually took a summer course at Harvard. I did not go to Harvard, but I took a summer course there and learned a lot about multimedia and some programming. And that really set me on a trajectory of how, um, data and analytics can truly provide value and, and outcomes to our customers. Um, and I have been living that life ever since. Um, I graduated from college, so, um, I was very excited and privileged in my early career to, uh, work in a company where I found after my first year that I was managing, um, uh, kids, people who had graduated from Harvard business school and from MIT Sloan school. Um, and that was super crazy, cuz I did not go to either of those schools, but I sort of have always had a natural knack for how do you take technology and, and the really cool things that technology can do, but because I'm not a programmer by training, I'm really focused on the value that I'm able to help, um, organizations really extract value, um, from the technology that we can create, which I think is fantastic. >>I think there's so much value in having a zigzag path into tech. You bring Danielle, you and I have talked about this many times you bring such breadth and such a wide perspective. That really is such a value. Add to teams. Danielle, talk to us from AWS's perspective about what can be done to encourage more young women to get and under and underrepresented groups as well, to get into stem and stay. >>Yeah, and this is definitely a challenge as we're trying to grow our organization and kind of shift the numbers. And the reality is, especially with the more senior folks in our organization, unless you bring folks with a zigzag path, the likelihood is you won't be able to change the numbers that you have. Um, but for me, it's really been about, uh, looking at that, uh, the folks who are just graduating college, maybe in other roles where they are adjacent to technology and to try to spark their interest and show that yes, they can do it because oftentimes it's really about believing in themselves and, and realizing that we need folks with all sorts of different perspectives to kind of come in, to be able to help really, um, provide both products and services and solutions for all types of people inside of technology, which requires all sorts of perspectives. >>Yeah, the diverse perspectives. There's so much value and there's a lot of data that demonstrates how much value revenue impact organizations can make by having diversity, especially at the leadership level. Hillary, let's go back to you. We talked about your career path. You talked about some of the importance of the focus on de and I at Tarana, but what are, what do you think can be done to encourage, to sorry, to recruit more young women and under groups into tech, any, any carrot there that you think are really important that we need to be dangling more of? >>Yeah, absolutely. And I'll build on what Danielle just said. I think the, um, bringing in diverse understandings, um, of, of customer outcomes, I mean, I, the we've really moved from technology for technology's sake and I know AWS and entirety to have had a lot of conversations on how do we drive customer outcomes that are differentiated in the market and really being customer centric and technology is wonderful. You can do wonderful things with it. You can do not so wonderful things with it as well, but unless you're really focused on the outcomes and what customers are seeking, um, technology is not hugely valuable. And so I think bringing in people who understand, um, voice of customer who understand those outcomes, and those are not necessarily the, the, the folks who are PhD in mathematics or statistics, um, those can be people who understand a day in the life of a data scientist or a day in the life of a citizen data scientist. And so really working to bridge the high impact technology with the practical kind of usability, usefulness of data and analytics in our cases, I think is something that we need more of in tech and sort of demystifying tech and freeing technology so that everybody can use it and having a really wide range of people who understand not just the bits and bites and, and how to program, but also the value in outcomes that technology through data and analytics can drive. >>Yeah. You know, we often talk about the hard skills, but this, their soft skills are equally, if not more important that even just being curious, being willing to ask questions, being not afraid to be vulnerable, being able to show those sides of your personality. I think those are important for, for young women and underrepresented groups to understand that those are just as important as some of the harder technical skills that can be taught. >>That's right. >>What do you think about from a bias perspective, Hillary, what have you seen in the tech industry and how do you think we can leverage culture as you talked about to help dial down some of the biases that are going on? >>Yeah. I mean, I think first of all, and, and there's some interesting data out there that says that 90% of the population, which includes a lot of women have some inherent bias in their day, day behaviors when it comes to to women in particular. But I'm sure that that is true across all kinds of, of, um, diverse and underrepresented folks in, in the world. And so I think acknowledging that we have bias and actually really learning how, what that can look like, how that can show up. We might be sitting here and thinking, oh, of course I don't have any bias. And then you realize that, um, as you, as you learn more about, um, different types of bias, that actually you do need to kind of, um, account for that and change behaviors. And so I think learning is sort of a fundamental, um, uh, grounding for all of us to really know what bias looks like, know how it shows up in each of us. >>Um, if we're leaders know how it shows up in our teams and make sure that we are constantly getting better, we're, we're not gonna be perfect anytime soon. But I think being on a path to improvement to overcoming bias, um, is really, is really critical. And part of that is really starting the dialogue, having the conversations, holding ourselves and each other accountable, um, when things aren't going in, in a, in a Coptic way and being able to talk openly about that, that felt, um, like maybe there was some bias in that interaction and how do we, um, how do we make good on that? How do we change our, our behavior? Fundamentally of course, data and analytics can have some bias in it as well. And so I think as we look at the, the technology aspect of bias, um, looking at at ethical AI, I think is a, a really important, uh, additional area. And I'm sure we could spend another 20 minutes talking about that, but I, I would be remiss if I didn't talk more about sort of the bias, um, and the over the opportunity to overcome bias in data and analytics as well. >>Yeah. The opportunity to overcome it is definitely there you bring up a couple of really good points, Hillary. It, it starts with awareness. We need to be aware that there are inherent biases in data in thought. And also to your other point, hold people accountable ourselves, our teammates, that's critical to being able to, to dial that back down, Daniel, I wanna get your perspective on, on your view of women in leadership roles. Do you think that we have good representation or we still have work to do in there? >>I definitely think in both technical and product roles, we definitely have some work to do. And, you know, when I think about, um, our partnership with Teradata, part of the reason why it's so important is, you know, Teradata solution is really the brains of a lot of companies. Um, you know, the what, how, what they differentiate on how they figure out insights into their business. And it's, it's all about the product itself and the data and the same is true at AWS. And, you know, we really could do some work to have some more women in these technical roles, as well as in the product, shaping the products. Uh, just for all the reasons that we just kind of talked about over the last 10 minutes, um, in order to, you know, move bias out of our, um, out of our solutions and also to just build better products and have, uh, better, you know, outcomes for customers. So I think there's a bit of work to do still. >>I agree. There's definitely a bit of work to do, and it's all about delivering those better outcomes for customers at the end of the day, we need to figure out what the right ways are of doing that and working together in a community. Um, we've had obviously a lot had changed in the last couple of years, Hillary, what's your, what have you seen in terms of the impact that the pandemic has had on this status of women in tech? Has it been a pro is silver lining the opposite? What are you seeing? >>Yeah, I mean, certainly there's data out there that tells us factually that it has been, um, very difficult for women during COVID 19. Um, women have, uh, dropped out of the workforce for a wide range of, of reasons. Um, and, and that I think is going to set us back all of us, the, the Royal us or the Royal we back, um, years and years. Um, and, and it's very unfortunate because I think we we're at a time when we're making great progress and now to see COVID, um, setting us back in, in such a powerful way. I think there's work to be done to understand how do we bring people back into the workforce. Um, how do we do that? Understanding work life balance, better understanding virtual and remote, working better. I think in the technology sector, um, we've really embraced, um, hybrid virtual work and are, are empowering people to bring their whole selves to work. >>And I think if anything, these, these zoom calls have, um, both for the men and the women on my team. In fact, I would say much more. So for the men on my team, I'm seeing, I was seeing more kids in the background, more kind of split childcare duties, more ability to start talking about, um, other responsibilities that maybe they had, uh, especially in the early days of COVID where maybe daycares were shut down. And, um, you had, you know, maybe a parent was sick. And so we saw quite a lot of, um, people bringing their whole selves to the office, which I think was, was really wonderful. Um, uh, even our CEO saw some of that. And I think, um, that that really changes the dialogue, right? It changes it to maybe scheduling meetings at a time when, um, people can do it after daycare drop off. >>Um, and really allowing that both for men and for women makes it better for, for women overall. So I would like to think that this hybrid working, um, environment and that this, um, uh, whole view into somebody's life that COVID has really provided for probably for white collar workers, if I'm being honest for, um, people who are in a, at a better point of privilege, they don't necessarily have to go into the office every day. I would like to think that tech can lead the way in, um, you know, coming out of the, the old COVID. I don't know if we have a new COVID coming, but the old COVID and really leading the way for women and for people, um, to transform how we do work, um, leveraging data and analytics, but also, um, overcoming some of the, the disparities that exist for women in particular in the workforce. >>Yeah, I think there's, there's like we say, there's a lot of opportunity there and I like your point of hopefully tech can be that guiding light that shows us this can be done. We're all humans at the end of the day. And ultimately if we're able to have some sort of work life balance, everything benefits, our work or more productive, higher performing teams impacts customers, right? There's so much value that can be gleaned from, from that hybrid model and embracing for humans. We need to be able to, to work when we can, we've learned that you don't have to be, you know, in an office 24, 7 commuting, crazy hours flying all around the world. We can get a lot of things done in a ways that fit people's lives rather than taking command over it. Wanna get your advice, Hillary, if you were to talk to your younger self, what would be some of the key pieces of advice you would say? And Danielle and I have talked about this before, and sometimes we, we would both agree on like, ask more questions. Don't be afraid to raise your hand, but what advice would you give your younger self and that younger generation in terms of being inspired to get into tech >>Oh, inspired and being in tech? You know, I think looking at technology as, in some ways, I feel like we do a disservice to, um, inclusion when we talk about stem, cuz I think stem can be kind of daunting. It can be a little scary for people for younger people. When I, when I go and talk to folks at schools, I think stem is like, oh, all the super smart kids are over there. They're all like maybe they're all men. And so, um, it's, it's a little, uh, intimidating. Um, and stem is actually, you know, especially for, um, people joining the workforce today. It's actually how you've been living your life since you were born. I mean, you know, stem inside and out because you walk around with a phone and you know how to get your internet working and like that is technology right. >>Fundamentally. And so demystifying stem as something that is around how we, um, actually make our, our lives useful and, and, and how we can change outcomes. Um, through technology I think is maybe a different lens to put on it. So, and there's absolutely for, for hard sciences, there's absolutely a, a great place in the world for folks who wanna pursue that and men and women can do that. So I, I don't want to be, um, uh, setting the wrong expectations, but I, I think stem is, is very holistic in, um, in the change that's happening globally for us today across economies, across global warming, across all kinds of impactful issues. And so I think everybody who's interested in, in some of that world change can participate in stem. It just may be through a different, through a different lens than how we classically talk about stem. >>So I think there's great opportunity to demystify stem. I think also, um, what I would tell my younger self is choose your bosses wisely. And that sounds really funny. That sounds like inside out almost, but I think choose the person that you're gonna work for in your first five to seven years. And it might be more than one person, but be, be selective, maybe be a little less selective about the exact company or the exact title. I think picking somebody that, you know, we talk about mentors and we talk about sponsors and those are important. Um, but the person you're gonna spend in your early career, a lot of your day with a lot, who's gonna influence a lot of the outcomes for you. That is the person that you, I think want to be more selective about, um, because that person can set you up for success and give you opportunities and set you on course to be, um, a standout or that person can hold you back. >>And that person can put you in the corner and not invite you to the meetings and not give you those opportunities. And so we're in an economy today where you actually can, um, be a little bit picky about who you go and work for. And I would encourage my younger self. I actually, I just lucked out actually, but I think that, um, my first boss really set me, um, up for success, gave me a lot of feedback and coaching. Um, and some of it was really hard to hear, but it really set me up for, for, um, the, the path that I've been on ever since. So it, that would be my advice. >>I love that advice. I it's brilliant. I didn't think it choose your bosses wisely. Isn't something that we primarily think about. I think a lot of people think about the big name companies that they wanna go after and put on a resume, but you bring up a great point. And Danielle and I have talked about this with other guests about mentors and sponsors. I think that is brilliant advice and also more work to do to demystify stem. But luckily we have great family leaders like the two of you helping us to do that. Ladies, I wanna thank you so much for joining me on the program today and talking through what you're seeing in de and I, what your companies are doing and the opportunities that we have to move the needle. Appreciate your time. >>Thank you so much. Great to see you, Danielle. Thank you Lisa, to see you. >>My pleasure for my guests. I'm Lisa Martin. You're watching the AWS partner showcase season one, episode three. Hey everyone. Welcome to the AWS partner showcase. This is season one, episode three, with a focus on women in tech. I'm your host, Lisa Martin. I've got two guests here with me, Sue Peretti, the EVP of global AWS strategic alliances at Jefferson Frank, a 10th revolution group company, and Danielle brushoff. One of our cube alumni joins us ISV PSA director, ladies. It's great to have you on the program talking about a, a topic that is near and dear to my heart at women in tech. >>Thank you, Lisa. >>So let's go ahead and start with you. Give the audience an understanding of Jefferson Frank, what does the company do and about the partnership with AWS? >>Sure. Um, so let's just start, uh, Jefferson Frank is a 10th revolution group company. And if you look at it, it's really talent as a service. So Jefferson Frank provides talent solutions all over the world for AWS clients, partners and users, et cetera. And we have a sister company called revelent, which is a talent creation company within the AWS ecosystem. So we create talent and put it out in the ecosystem. Usually underrepresented groups over half of them are women. And then we also have, uh, a company called rubra, which is a delivery model around AWS technology. So all three companies fall under the 10th revolution group organization. >>Got it. Danielle, talk to me a little bit about from AWS's perspective and the focus on hiring more women in technology and about the partnership. >>Yes. I mean, this has definitely been a focus ever since I joined eight years ago, but also just especially in the last few years we've grown exponentially and our customer base has changed. You know, we wanna have, uh, an organization interacting with them that reflects our customers, right. And, uh, we know that we need to keep pace with that even with our growth. And so we've very much focused on early career talent, um, bringing more women and underrepresented minorities into the organization, sponsoring those folks, promoting them, uh, giving them paths to growth, to grow inside of the organization. I'm an example of that. Of course I benefit benefited from it, but also I try to bring that into my organization as well. And it's super important. >>Tell me a little bit about how you benefited from that, Danielle. >>Um, I just think that, um, you know, I I've been able to get, you know, a seat at the table. I think that, um, I feel as though I have folks supporting me, uh, very deeply and wanna see me succeed. And also they put me forth as, um, you know, a, represent a representative, uh, to bring more women into the organization as well. And I think, um, they give me a platform, uh, in order to do that, um, like this, um, but also many other, uh, spots as well. Um, and I'm happy to do it because I feel that, you know, if you always wanna feel that you're making a difference in your job, and that is definitely a place where I get that time and space in order to be that representative to, um, bring more, more women into benefiting from having careers in technology, which there's a lot of value there, >>A lot of value. Absolutely. So back over to you, what are some of the trends that you are seeing from a gender diversity perspective in tech? We know the, the numbers of women in technical positions, uh, right. There's so much data out there that shows when girls start dropping up, but what are some of the trends that you are seeing? >>So it's, that's a really interesting question. And, and Lisa, I had a whole bunch of data points that I wanted to share with you, but just two weeks ago, uh, I was in San Francisco with AWS at the, at the summit. And we were talking about this. We were talking about how we can collectively together attract more women, not only to, uh, AWS, not only to technology, but to the AWS ecosystem in particular. And it was fascinating because I was talking about, uh, the challenges that women have and how hard to believe, but about 5% of women who were in the ecosystem have left in the past few years, which was really, really, uh, something that shocked everyone when we, when we were talking about it, because all of the things that we've been asking for, for instance, uh, working from home, um, better pay, uh, more flexibility, uh, better maternity leave seems like those things are happening. >>So we're getting what we want, but people are leaving. And it seemed like the feedback that we got was that a lot of women still felt very underrepresented. The number one thing was that they, they couldn't be, you can't be what you can't see. So because they, we feel collectively women, uh, people who identify as women just don't see enough women in leadership, they don't see enough mentors. Um, I think I've had great mentors, but, but just not enough. I'm lucky enough to have a pres a president of our company, the president of our company, Zoe Morris is a woman and she does lead by example. So I'm very lucky for that. And Jefferson, Frank really quickly, we put out a hiring a salary and hiring guide a career and hiring guide every year and the data points. And that's about 65 pages long. No one else does it. Uh, it gives an abundance of information around, uh, everything about the AWS ecosystem that a hiring manager might need to know. But there is what, what I thought was really unbelievable was that only 7% of the people that responded to it were women. So my goal, uh, being that we have such a very big global platform is to get more women to respond to that survey so we can get as much information and take action. So >>Absolutely 7%. So a long way to go there. Danielle, talk to me about AWS's focus on women in tech. I was watching, um, Sue, I saw that you shared on LinkedIn, the Ted talk that the CEO and founder of girls and co did. And one of the things that she said was that there was a, a survey that HP did some years back that showed that, um, 60%, that, that men will apply for jobs if they only meet 60% of the list of requirements. Whereas with females, it's far, far less, we've all been in that imposter syndrome, um, conundrum before. But Danielle, talk to us about AWS, a specific focus here to get these numbers up. >>I think it speaks to what Susan was talking about, how, you know, I think we're approaching it top and bottom, right? We're looking out at what are the, who are the women who are currently in technical positions and how can we make AWS an attractive place for them to work? And that's all a lot of the changes that we've had around maternity leave and, and those types of things, but then also, um, more flexible working, uh, can, you know, uh, arrangements, but then also, um, early, how can we actually impact early, um, career women and actually women who are still in school. Um, and our training and certification team is doing amazing things to get, um, more girls exposed to AWS, to technology, um, and make it a less intimidating place and have them look at employees from AWS and say like, oh, I can see myself in those people. >>Um, and kind of actually growing the viable pool of candidates. I think, you know, we're, we're limited with the viable pool of candidates, um, when you're talking about mid to late career. Um, but how can we, you know, help retrain women who are coming back into the workplace after, you know, having a child and how can we help with military women who want to, uh, or underrepresented minorities who wanna move into AWS, we have a great military program, but then also just that early high school, uh, career, you know, getting them in, in that trajectory. >>Sue, is that something that Jefferson Frank is also able to help with is, you know, getting those younger girls before they start to feel there's something wrong with me. I don't get this. Talk to us about how Jefferson Frank can help really drive up that in those younger girls. >>Uh, let me tell you one other thing to refer back to that summit that we did, uh, we had breakout sessions and that was one of the topics. What can cuz that's the goal, right? To make sure that, that there are ways to attract them. That's the goal? So some of the things that we talked about was mentoring programs, uh, from a very young age, some people said high school, but then we said even earlier, goes back to you. Can't be what you can't see. So, uh, getting mentoring programs, uh, established, uh, we also talked about some of the great ideas was being careful of how we speak to women using the right language to attract them. And some, there was a teachable moment for, for me there actually, it was really wonderful because, um, an African American woman said to me, Sue and I, I was talking about how you can't be what you can't see. >>And what she said was Sue, it's really different. Um, for me as an African American woman, uh, or she identified, uh, as nonbinary, but she was relating to African American women. She said, your white woman, your journey was very different than my journey. And I thought, this is how we're going to learn. I wasn't offended by her calling me out at all. It was a teachable moment. And I thought I understood that, but those are the things that we need to educate people on those, those moments where we think we're, we're saying and doing the right thing, but we really need to get that bias out there. So here at Jefferson, Frank, we're, we're trying really hard to get that careers and hiring guide out there. It's on our website to get more women, uh, to talk to it, but to make suggestions in partnership with AWS around how we can do this mentoring, we have a mentor me program. We go around the country and do things like this. We, we try to get the education out there in partnership with AWS. Uh, we have a, a women's group, a women's leadership group, uh, so much that, that we do, and we try to do it in partnership with AWS. >>Danielle, can you comment on the impact that AWS has made so far, um, regarding some of the trends and, and gender diversity that Sue was talking about? What's the impact that's been made so far with this partnership? >>Well, I mean, I think just being able to get more of the data and have awareness of leaders, uh, on how <laugh>, you know, it used to be a, a couple years back, I would feel like sometimes the, um, uh, solving to bring more women into the organization was kind of something that folks thought, oh, this is Danielle is gonna solve this. You know? And I think a lot of folks now realize, oh, this is something that we all need to solve for. And a lot of my colleagues who maybe a couple years ago, didn't have any awareness or didn't even have the tools to do what they needed to do in order to improve the statistics on their, or in their organizations. Now actually have those tools and are able to kind of work with, um, work with companies like Susan's work with Jefferson Frank in order to actually get the data and actually make good decisions and feel as though, you know, they, they often, these are not lived experiences for these folks, so they don't know what they don't know. And by providing data and providing awareness and providing tooling and then setting goals, I think all of those things have really turned, uh, things around in a very positive way. >>And so you bring up a great point about from a diversity perspective, what is Jefferson Frank doing to, to get those data points up, to get more women of, of all well, really underrepresented minorities to, to be able to provide that feedback so that you can, can have the data and gleamy insights from it to help companies like AWS on their strategic objectives. >>Right? So as I, when I go back to that higher that, uh, careers in hiring guide, that is my focus today, really because the more data that we have, I mean, the, and the data takes, uh, you know, we need people to participate in order to, to accurately, uh, get a hold of that data. So that's why we're asking, uh, we're taking the initiative to really expand our focus. We are a global organization with a very, very massive database all over the world, but if people don't take action, then we can't get the right. The, the, the data will not be as accurate as we'd like it to be. Therefore take better action. So what we're doing is we're asking people all over the, all over the world to participate on our website, Jefferson frank.com, the se the high, uh, in the survey. So we can learn as much as we can. >>7% is such a, you know, Danielle and I we're, we've got to partner on this just to sort of get that message out there, get more data so we can execute, uh, some of the other things that we're doing. We're, we're partnering in. As I mentioned, more of these events, uh, we're, we're doing around the summits, we're gonna be having more ed and I events and collecting more information from women. Um, like I said, internally, we do practice what we preach and we have our own programs that are, that are out there that are within our own company where the women who are talking to candidates and clients every single day are trying to get that message out there. So if I'm speaking to a client or one of our internal people are speaking to a client or a candidate, they're telling them, listen, you know, we really are trying to get these numbers up. >>We wanna attract as many people as we can. Would you mind going to this, uh, hiring guide and offering your own information? So we've gotta get that 7% up. We've gotta keep talking. We've gotta keep, uh, getting programs out there. One other thing I wanted to Danielle's point, she mentioned, uh, women in leadership, the number that we gathered was only 9% of women in leadership within the AWS ecosystem. We've gotta get that number up, uh, as well because, um, you know, I know for me, when I see people like Danielle or, or her peers, it inspires me. And I feel like, you know, I just wanna give back, make sure I send the elevator back to the first floor and bring more women in to this amazing ecosystem. >>Absolutely. That's not that metaphor I do too, but we, but to your point to get that those numbers up, not just at AWS, but everywhere else we need, it's a help me help use situation. So ladies underrepresented minorities, if you're watching go to the Jefferson Frank website, take the survey, help provide the data so that the woman here that are doing this amazing work, have it to help make decisions and have more of females and leadership roles or underrepresented minorities. So we can be what we can see. Ladies, thank you so much for joining me today and sharing what you guys are doing together to partner on this important. Cause >>Thank you for having me, Leah, Lisa, >>Thank you. My pleasure for my guests. I'm Lisa Martin. You're watching the cubes coverage of the AWS partner showcase. Thanks for your time. Hey everyone. Welcome to the AWS partner showcase season one, episode three women in tech. I'm your host, Lisa Martin. We've got two female rock stars here with me next. Stephanie Curry joins us the worldwide head of sales and go to market strategy for AWS at NetApp and Danielle GShock is back one of our QM ISV PSA director at AWS. Looking forward to a great conversation, ladies, about a great topic, Stephanie, let's go ahead and start with you. Give us an overview of your story, how you got into tech and what inspired you. >>Thanks so much, Lisa and Danielle. It's great to be on this show with you. Um, thank you for that. Uh, my name's Stephanie cur, as Lisa mentioned, I'm the worldwide head of sales for, uh, AWS at NetApp and run a global team of sales people that sell all things AWS, um, going back 25 years now, uh, when I first started my career in tech, it was kind of by accident. Um, I come from a different background. I have a business background and a technical background from school, um, but had been in a different career and I had an opportunity to try something new. Um, I had an ally really that reached out to me and said, Hey, you'd be great for this role. And I thought, I'd take a chance. I was curious. Um, and, uh, it, it turned out to be a 25 year career, um, that I'm really, really excited about and, and, um, really thankful for that person, for introducing me to the, to the industry >>25 years in counting. I'm sure Danielle, we've talked about your background before. So what I wanna focus on with you is the importance of diversity for high performance. I know what a machine AWS is, and Stephanie'll come back to you with the same question, but talk about that, Danielle, from your perspective, that importance, um, for diversity to drive the performance. >>Yeah. Yeah. I truly believe that, you know, in order to have high performing teams, that you have to have people from all different types of backgrounds and experiences. And we do find that oftentimes being, you know, field facing, if we're not reflecting our customers and connecting with them deeply, um, on, on the levels that they're at, we, we end up missing them. And so for us, it's very important to bring people of lots of different technical backgrounds experiences. And of course, both men, women, and underrepresented minorities and put that forth to our customers, um, in order to make that connection and to end up with better outcomes. So >>Definitely it's all about outcomes, Stephanie, your perspective and NetApp's perspective on diversity for creating highly performant teams and organizations. >>I really aligned with Danielle on the comment she made. And in addition to that, you know, just from building teams in my, um, career know, we've had three times as many women on my team since we started a year ago and our results are really showing in that as well. Um, we find the teams are stronger, they're more collaborative and to Danielle's point really reflective, not only our partners, but our customers themselves. So this really creates connections, which are really, really important to scale our businesses and, and really, uh, meet the customer where they're at as well. So huge proponent of that ourselves, and really finding that we have to be intentional in our hiring and intentional in how we attract diversity to our teams. >>So Stephanie let's stay with you. So a three X increase in women on the team in a year, especially the kind of last year that we've had is really incredible. I, I like your, I, your thoughts on there needs to be a, there needs to be focus and, and thought in how teams are hired. Let's talk about attracting and retaining those women now, especially in sales roles, we all know the number, the percentages of women in technical roles, but what are some of the things that, that you do Stephanie, that NetApp does to attract and retain women in those sales roles? >>The, the attracting part's really interesting. And we find that, you know, you, you read the stats and I'd say in my experience, they're also true in the fact that, um, a lot of women would look at a job description and say, I can't do a hundred percent of that, that, so I'm not even going to apply with the women that we've attracted to our team. We've actually intentionally reached out and targeted those people in a good way, um, to say, Hey, we think you've got what it takes. Some of the feedback I've got from those women are, gosh, I didn't think I could ever get this role. I didn't think I had the skills to do that. And they've been hired and they are doing a phenomenal job. In addition to that, I think a lot of the feedback I've got from these hires are, Hey, it's an aggressive sales is aggressive. Sales is competitive. It's not an environment that I think I can be successful in. And what we're showing them is bring those softer skills around collaboration, around connection, around building teams. And they do, they do bring a lot of that to the team. Then they see others like them there and they know they can be successful cuz they see others like them on the team, >>The whole concept of we can't be what we can't see, but we can be what we can't see is so important. You said a couple things, Stephanie, that really stuck with me. And one of them was an interview on the Cub I was doing, I think a couple weeks ago, um, about women in tech. And the stat that we talked about was that women will apply will not apply for a job unless they meet 100% of the skills and the requirements that it's listed, but men will, if they only meet 60. And I, that just shocked me that I thought, you know, I, I can understand that imposter syndrome is real. It's a huge challenge, but the softer skills, as you mentioned, especially in the last two years, plus the ability to communicate, the ability to collaborate are incredibly important to, to drive that performance of any team of any business. >>Absolutely. >>Danielle, talk to me about your perspective and AWS as well for attracting and retaining talent. And, and, and particularly in some of those challenging roles like sales that as Stephanie said, can be known as aggressive. >>Yeah, for sure. I mean, my team is focused on the technical aspect of the field and we definitely have an uphill battle for sure. Um, two things we are focused on first and foremost is looking at early career women and that how we, how can we bring them into this role, whether in they're in support functions, uh, cl like answering the phone for support calls, et cetera, and how, how can we bring them into this organization, which is a bit more strategic, more proactive. Um, and then the other thing that as far as retention goes, you know, sometimes there will be women who they're on a team and there are no other women on that team. And, and for me, it's about building community inside of AWS and being part of, you know, we have women on solution architecture organizations. We have, uh, you know, I just personally connect people as well and to like, oh, you should meet this person. Oh, you should talk to that person. Because again, sometimes they can't see someone on their team like them and they just need to feel anchored, especially as we've all been, you know, kind of stuck at home, um, during the pandemic, just being able to make those connections with women like them has been super important and just being a, a long tenured Amazonian. Um, that's definitely one thing I'm able to, to bring to the table as well. >>That's so important and impactful and spreads across organizations in a good way. Daniel let's stick with you. Let's talk about some of the allies that you've had sponsors, mentors that have really made a difference. And I said that in past tense, but I also mean in present tense, who are some of those folks now that really inspire you? >>Yeah. I mean, I definitely would say that one of my mentors and someone who, uh, ha has been a sponsor of my career has, uh, Matt YK, who is one of our control tower GMs. He has really sponsored my career and definitely been a supporter of mine and pushed me in positive ways, which has been super helpful. And then other of my business partners, you know, Sabina Joseph, who's a cube alum as well. She definitely has been, was a fabulous partner to work with. Um, and you know, between the two of us for a period of time, we definitely felt like we could, you know, conquer the world. It's very great to go in with a, with another strong woman, um, you know, and, and get things done, um, inside of an organization like AWS. >>Absolutely. And S I've, I've agreed here several times. So Stephanie, same question for you. You talked a little bit about your kind of, one of your, uh, original early allies in the tech industry, but talk to me about allies sponsors, mentors who have, and continue to make a difference in your life. >>Yeah. And, you know, I think it's a great differentiation as well, right? Because I think that mentors teach us sponsors show us the way and allies make room for us at the table. And that is really, really key difference. I think also as women leaders, we need to make room for others at the table too, and not forget those softer skills that we bring to the table. Some of the things that Danielle mentioned as well about making those connections for others, right. And making room for them at the table. Um, some of my allies, a lot of them are men. Brian ABI was my first mentor. Uh, he actually is in the distribution, was in distribution, uh, with advent tech data no longer there. Um, Corey Hutchinson, who's now at Hashi Corp. He's also another ally of mine and remains an ally of mine, even though we're not at the same company any longer. Um, so a lot of these people transcend careers and transcend, um, um, different positions that I've held as well and make room for us. And I think that's just really critical when we're looking for allies and when allies are looking for us, >>I love how you described allies, mentors and sponsors Stephanie. And the difference. I didn't understand the difference between a mentor and a sponsor until a couple of years ago. Do you talk with some of those younger females on your team so that when they come into the organization and maybe they're fresh outta college, or maybe they've transitioned into tech so that they can also learn from you and understand the importance and the difference between the allies and the sponsors and the mentors? >>Absolutely. And I think that's really interesting because I do take, uh, an extra, uh, approach an extra time to really reach out to the women that have joined the team. One. I wanna make sure they stay right. I don't want them feeling, Hey, I'm alone here and I need to, I need to go do something else. Um, and they are located around the world, on my team. They're also different age groups, so early in career, as well as more senior people and really reaching out, making sure they know that I'm there. But also as Danielle had mentioned, connecting them to other people in the community that they can reach out to for those same opportunities and making room for them >>Make room at the table. It's so important. And it can, you never know what a massive difference and impact you can make on someone's life. And I, and I bet there's probably a lot of mentors and sponsors and allies of mine that would be surprised to know, uh, the massive influence they've had Daniel back over. Let's talk about some of the techniques that you employ, that AWS employees to make the work environment, a great place for women to really thrive and, and be retained as Stephanie was saying. Of course that's so important. >>Yeah. I mean, definitely I think that the community building, as well as we have a bit more programmatic mentorship, um, we're trying to get to the point of having a more programmatic sponsorship as well. Um, but I think just making sure that, um, you know, both everything from, uh, recruit to onboard to ever boarding that, uh, they they're the women who come into the organization, whether it's they're coming in on the software engineering side or the field side or the sales side that they feel as that they have someone, uh, working with them to help them drive their career. Those are the key things that were, I think from an organizational perspective are happening across the board. Um, for me personally, when I run my organization, I'm really trying to make sure that people feel that they can come to me at any time open door policy, make sure that they're surfacing any times in which they are feeling excluded or anything like that, any challenges, whether it be with a customer, a partner or with a colleague. Um, and then also of course, just making sure that I'm being a good sponsor, uh, to, to people on my team. Um, that is key. You can talk about it, but you have to start with yourself as well. >>That's a great point. You you've got to, to start with yourself and really reflect on that. Mm-hmm <affirmative> and look, am I, am I embodying what it is that I need? And not that I know they need that focused, thoughtful intention on that is so importants, let's talk about some of the techniques that you use that NetApp uses to make the work environment a great place for those women are marginalized, um, communities to really thrive. >>Yeah. And I appreciate it and much like Danielle, uh, and much like AWS, we have some of those more structured programs, right around sponsorship and around mentorship. Um, probably some growth there, opportunities for allies, because I think that's more of a newer concept in really an informal structure around the allies, but something that we're growing into at NetApp, um, on my team personally, I think, um, leading by example's really key. And unfortunately, a lot of the, um, life stuffs still lands on the women, whether we like it or not. Uh, I have a very, uh, active husband in our household, but I still carry when it push comes to shove it's on me. Um, and I wanna make sure that my team knows it's okay to take some time and do the things you need to do with your family. Um, I'm I show up as myself authentically and I encourage them to do the same. >>So it's okay to say, Hey, I need to take a personal day. I need to focus on some stuff that's happening in my personal life this week now, obviously to make sure your job's covered, but just allowing some of that softer vulnerability to come into the team as well, so that others, um, men and women can feel they can do the same thing. And that it's okay to say, I need to balance my life and I need to do some other things alongside. Um, so it's the formal programs, making sure people have awareness on them. Um, I think it's also softly calling people out on biases and saying, Hey, I'm not sure if you know, this landed that way, but I just wanted to make you aware. And usually the feedback is, oh my gosh, I didn't know. And could you coach me on something that I could do better next time? So all of this is driven through our NetApp formal programs, but then it's also how you manifest it on the teams that we're leading. >>Absolutely. And sometimes having that mirror to reflect into can be really eye-opening and, and allow you to, to see things in a completely different light, which is great. Um, you both talked about, um, kind of being what you, uh, can see, and, and I know both companies are upset customer obsessed in a good way. Talk to me a little bit, Danielle, go back over to you about the AWS NetApp partnership. Um, some of that maybe alignment on, on performance on obviously you guys are very well aligned, uh, in terms of that, but also it sounds like you're quite aligned on diversity and inclusion. >>Well, we definitely do. We have the best partnerships with companies in which we have these value alignments. So I think that is a positive thing, of course, but just from a, from a partnership perspective, you know, from my five now plus years of being a part of the APN, this is, you know, one of the most significant years with our launch of FSX for NetApp. Um, with that, uh, key key service, which we're making available natively on AWS. I, I can't think of a better Testament to the, to the, um, partnership than that. And that's doing incredibly well and it really resonates with our customers. And of course it started with customers and their need for NetApp. Uh, so, you know, that is a reflection, I think, of the success that we're having together. >>And Stephanie talk to, uh, about the partnership from your perspective, NetApp, AWS, what you guys are doing together, cultural alignment, but also your alignment on really bringing diversity into drive performance. >>Yeah, I think it's a, a great question. And I have to say it's just been a phenomenal year. Our relationship has, uh, started before our first party service with FSX N but definitely just, um, uh, the trajectory, um, between the two companies since the announcement about nine months ago has just taken off to a, a new level. Um, we feel like an extended part of the family. We worked together seamlessly. A lot of the people in my team often say we feel like Amazonians. Um, and we're really part of this transformation at NetApp from being that storage hardware company into being an ISV and a cloud company. And we could not do this without the partnership with AWS and without the, uh, first party service of Fs XM that we've recently released. Um, I think that those joint values that Danielle referred to are critical to our success, um, starting with customer obsession and always making sure that we are doing the right thing for the customer. >>We coach our team teams all the time on if you are doing the right thing for the customers, you cannot do anything wrong. Just always put the customer at the, in the center of your decisions. And I think that there is, um, a lot of best practice sharing and collaboration as we go through this change. And I think a lot of it is led by the diverse backgrounds that are on the team, um, female, male, um, race and so forth, and just to really, uh, have different perspectives and different experiences about how we approach this change. Um, so we definitely feel like a part of the family. Uh, we are absolutely loving, uh, working with the AWS team and our team knows that we are the right place, the right time with the right people. >>I love that last question for each of you. And I wanna stick with you Stephanie advice to your younger self, think back five years. What advice would you seen what you've accomplished and maybe the thet route that you've taken along the way, what would you advise your youngest Stephanie self. >>Uh, I would say keep being curious, right? Keep being curious, keep asking questions. And sometimes when you get a no, it's not a bad thing, it just means not right now and find out why and, and try to get feedback as to why maybe that wasn't the right opportunity for you. But, you know, just go for what you want. Continue to be curious, continue to ask questions and find a support network of people around you that wanna help you because they are there and they, they wanna see you be successful too. So never be shy about that stuff. >><laugh> absolutely. And I always say failure does not have to be an, a bad F word. A no can be the beginning of something. Amazing. Danielle, same question for you. Thinking back to when you first started in your career, what advice would you give your younger self? >>Yeah, I think the advice I'd give my younger self would be, don't be afraid to put yourself out there. Um, it's certainly, you know, coming from an engineering background, maybe you wanna stay behind the scenes, not, not do a presentation, not do a public speaking event, those types of things, but back to what the community really needs, this thing. Um, you know, I genuinely now, uh, took me a while to realize it, but I realized I needed to put myself out there in order to, um, you know, allow younger women to see what they could be. So that would be the advice I would give. Don't be afraid to put yourself out there. >>Absolutely. That advice that you both gave are, is so fantastic, so important and so applicable to everybody. Um, don't be afraid to put yourself out there, ask questions. Don't be afraid of a, no, that it's all gonna happen at some point or many points along the way. That can also be good. So thank you ladies. You inspired me. I appreciate you sharing what AWS and NetApp are doing together to strengthen diversity, to strengthen performance and the advice that you both shared for your younger selves was brilliant. Thank you. >>Thank you. >>Thank you >>For my guests. I'm Lisa Martin. You're watching the AWS partner showcase. See you next time. Hey everyone. Welcome to the AWS partner showcase season one, episode three women in tech. I'm your host, Lisa Martin. I've got two female rock stars joining me. Next Vero Reynolds is here engineering manager, telemetry at honeycomb, and one of our cube alumni, Danielle Ock ISV PSA director at AWS. Join us as well. Ladies. It's great to have you talking about a very important topic today. >>Thanks for having us. >>Yeah, thanks for having me. Appreciate it. >>Of course, Vera, let's go ahead and start with you. Tell me about your background and tech. You're coming up on your 10th anniversary. Happy anniversary. >>Thank you. That's right. I can't believe it's been 10 years. Um, but yeah, I started in tech in 2012. Um, I was an engineer for most of that time. Uh, and just recently as a March, switched to engineering management here at honeycomb and, um, you know, throughout my career, I was very much interested in all the things, right. And it was a big FOMO as far as trying a few different, um, companies and products. And I've done things from web development to mobile to platforms. Um, it would be apt to call me a generalist. Um, and in the more recent years I was sort of gravitating more towards developer tool space. And for me that, uh, came in the form of cloud Foundry circle CI and now honeycomb. Um, I actually had my eye on honeycomb for a while before joining, I came across a blog post by charity majors. >>Who's one of our founders and she was actually talking about management and how to pursue that and whether or not it's right, uh, for your career. And so I was like, who is this person? I really like her, uh, found the company. They were pretty small at the time. So I was sort of keeping my eye on them. And then when the time came around for me to look again, I did a little bit more digging, uh, found a lot of talks about the product. And on the one hand they really spoke to me as the solution. They talked about developers owning their coding production and answering questions about what is happening, what are your users seeing? And I felt that pain, I got what they were trying to do. And also on the other hand, every talk I saw at the time was from, uh, an amazing woman <laugh>, which I haven't seen before. Uh, so I came across charity majors again, Christine Y our other founder, and then Liz Jones, who's our principal developer advocate. And that really sealed the deal for me as far as wanting to work here. >>Yeah. Honeycomb is interesting. This is a female founded company. You're two leaders. You mentioned that you like the technology, but you were also attracted because you saw females in the leadership position. Talk to me a little bit about what that's like working for a female led organization at honeycomb. >>Yeah. You know, historically, um, we have tried not to over index on that because there was this, uh, maybe fear awareness of, um, it taking away from our legitimacy as an engineering organization, from our success as a company. Um, but I'm seeing that, uh, rhetoric shift recently because we believe that with great responsibility, uh, with great power comes great responsibility, and we're trying to be more intentional as far as using that attribute of our company. Um, so I would say that for me, it was, um, a choice between a few offers, right. And that was a selling point for sure, because again, I've never experienced it and I've really seen how much they walk that walk. Um, even me being here and me moving into management, I think were both, um, ways in which they really put a lot of trust and support in me. And so, um, I it's been a great ride. >>Excellent. Sounds like it. Before we bring Danielle in to talk about the partnership. I do wanna have you there talk to the audience a little bit about honeycomb, what technology it's delivering and what are its differentiators. >>Yeah, absolutely. Um, so honeycomb is an observability tool, uh, that enables engineers to answer questions about the code that runs in production. And, um, we work with a number of various customers. Some of them are Vanguards, slack. Hello, fresh, just to name a couple, if you're not familiar with observability tooling, it's akin to traditional application performance monitoring, but we believe that observability is succeeding APM because, uh, APM tools were built at the time of monoliths and they just weren't designed to help us answer questions about complex distributed systems that we work with today, where things can go wrong anywhere in that chain. And you can't predict what you're gonna need to ask ahead of time. So some of the ways that we are different is our ability to store and query really rich data, which we believe is the key to understanding those complex systems. >>What I mean by rich data is, um, something that has a lot of attributes. So for example, when an error happens, knowing who it happened to, which user ID, which, um, I don't know, region, they were in, um, what, what, what they were doing at the time and what was happening at the rest of your system. And our ingest engine is really fast. You can do it in as little as three seconds and we call data like this. I said, kind of rich data, contextual data. We refer it as having high ality and high dimensionality, which are big words. But at the end of the day, what that means is we can store and we can query the data. We can do it really fast. And to give you an example of how that looks for our customers, let's say you have a developer team who are using comb to understand and observe their system. >>And they get a report that a user is experiencing a slowdown or something's wrong. They can go into comb and figure out that this only happens to users who are using a particular language pack with their app. And they operated their app last week, that it only happens when they are trying to upload a file. And so it's this level of granularity and being able to zoom in and out, um, under your data that allows you to understand what's happening, especially when you have an incident going on, right. Or your really important high profile customer is telling you that something's wrong. And we can do that. Even if everything else in your other tools looks fine, right? All of your dashboards are okay. You're not actually getting paged on it, but your customers are telling you that something's wrong. Uh, and we believe that's where we shine in helping you there. >>Excellent. It sounds like that's where you really shine that real time visibility is so critical these days. Danielle, Danielle, wanna bring you into the conversation. Talk to us a little bit about the honeycomb partnership from the AWS lens. >>Yeah. So excuse me, observability is obviously a very important, uh, segment in the cloud space, very important to AWS, um, because a lot of all of our customers, uh, as they build their systems distributed, they need to be able to see where, where things are happening in the complex systems that they're building. And so honeycomb is a, is an advanced technology partner. Um, they've been working with us for quite some time and they have a, uh, their solution is listed on the marketplace. Um, definitely something that we see a lot of demand with our customers and they have many integrations, uh, which, you know, we've seen is key to success. Um, being able to work seamlessly with the rest of the services inside of the AWS platform. And I know that they've done some, some great things with people who are trying to develop games on top of AWS, uh, things in that area as well. And so, uh, very important partner in the observa observability market that we have >>Back to you, let's kind of unpack the partnership, the significance that honeycomb ha is getting from being partners with an organization as potent and pivotal as AWS. >>Yeah, absolutely. Um, I know this predates me to some extent, but I know for a long time, AWS and honeycomb has really pushed the envelope together. And, um, I think it's a beneficial relationship for both ends. There's kind of two ways of looking at it. On the one side, there is our own infrastructure. So honeycomb runs on AWS and actually one of our critical workloads that supports that fast query engine that I mentioned uses Lambda. And it does so in a pretty Orthodox way. So we've had a longstanding conversation with the AWS team as far as drawing outside those lines and kind of figuring out how to use this technology in a way that works for us and hopefully will work for other customers of theirs as well. Um, that also allows us to ask for early access for certain features when they become available. >>And then that way we can be sort of the Guinea pigs and try things out, um, in a way that migrates our system and optimizes our own performance, but also allows again, other customers of AWS to follow in that path. And then the other side of that partnership is really supporting our customers who are both honeycomb users and AWS users, because it's, as you imagine, quite a big overlap, and there are certain ways in which we can allow our customers to more easily get their data from AWS to honeycomb. So for example, last year we built a tool, um, based on the new Lambda extension capability that allowed our users who run their applications in Lambdas to get that telemetry data out of their applications and into honeycomb. And it man was win, win. >>Excellent. So I'm hearing a lot of synergies from a technology perspective, you're sticking with you, and then Danielle will bring you in, let's talk about how honeycomb supports D and I across its organization. And how is that synergistic with AWS's approach? Yeah, >>Yeah, absolutely. So I sort of alluded to that hesitancy to over index on the women led aspect of ourselves. Um, but again, a lot of things are shifting, we're growing a lot. And so we are recognizing that we need to be more intentional with our DEI initiatives, and we also notice that we can do better and we should do better. And to that, and we're doing a few things differently, um, that are pretty recent initiatives. We are partnering with organizations that help us target specific communities that are underrepresented in tech. Um, some examples would be after tech hu Latinas in tech among, um, a number of others. And another initiative is DEI head start. That's something that is an internal, um, practice that we started that includes reaching out to underrepresented applicants before any new job for honeycomb becomes live. So before we posted to LinkedIn, before it's even live on our job speech, and the idea there is to kind of balance our pipeline of applicants, which the hope is will lead to more diverse hires in the long term. >>That's a great focus there. Danielle, I know we've talked about this before, but for the audience, in terms of the context of the honeycomb partnership, the focus at AWS for D E and I is really significant, unpack that a little bit for us. >>Well, let me just bring it back to just how we think about it, um, with the companies that we work with, but also in, in terms of, you know, what we want to be able to do, excuse me, it's very important for us to, you know, build products that reflect, uh, the customers that we have. And I think, you know, working with, uh, a company like honeycomb that is looking to differentiate in a space, um, by, by bringing in, you know, the experiences of many different types of people I genuinely believe. And I'm sure Vera also believes that by having those diverse perspectives, that we're able to then build better products for our customers. Um, and you know, it's one of, one of our leadership principles, uh, is, is rooted in this. I write a lot, it asks for us to seek out diverse perspectives. Uh, and you can't really do that if everybody kind of looks the same and thinks the same and has the same background. So I think that is where our de and I, um, you know, I thought process is rooted and, you know, companies like honeycomb that give customers choice and differentiate and help them, um, to do what they need to do in their unique, um, environments is super important. So >>The, the importance of thought diversity cannot be underscored enough. It's something that is, can be pivotal to organizations. And it's very nice to hear that that's so fundamental to both companies, Barry, I wanna go back to you for a second. You, I think you mentioned this, the DEI head start program, that's an internal program at honeycomb. Can you shed a little bit of light on that? >>Yeah, that's right. And I actually am in the process of hiring a first engineer for my team. So I'm learning a lot of these things firsthand, um, and how it works is we try to make sure to pre-load our pipeline of applicants for any new job opening we have with diverse candidates to the best of our abilities, and that can involve partnering with the organizations that I mentioned or reaching out to our internal network, um, and make sure that we give those applicants a head start, so to speak. >>Excellent. I like that. Danielle, before we close, I wanna get a little bit of, of your background. We've got various background in tag, she's celebrating her 10th anniversary. Give me a, a short kind of description of the journey that you've navigated through being a female in technology. >>Yeah, thanks so much. I really appreciate, uh, being able to share this. So I started as a software engineer, uh, back actually in the late nineties, uh, during the, the first.com bubble and, uh, have, have spent quite a long time actually as an individual contributor, um, probably working in software engineering teams up through 2014 at a minimum until I joined AWS, uh, as a customer facing solutions architect. Um, I do think spending a lot of time, hands on definitely helped me with some of the imposter syndrome, um, issues that folks suffer from not to say I don't at all, but it, it certainly helped with that. And I've been leading teams at AWS since 2015. Um, so it's really been a great ride. Um, and like I said, I'm very happy to see all of our engineering teams change, uh, as far as their composition. And I'm, I'm grateful to be part of it. >>It's pretty great to be able to witness that composition change for the better last question for each of you. And we're almost out of time and Danielle, I'm gonna stick with you. What's your advice, your recommendations for women who either are thinking about getting into tech or those who may be in tech, maybe they're in individual positions and they're not sure if they should apply for that senior leadership position. What do you advise them to do? >>I mean, definitely for the individual contributors, tech tech is a great career, uh, direction, um, and you will always be able to find women like you, you have to maybe just work a little bit harder, uh, to join, have community, uh, in that. But then as a leader, um, representation is very important and we can bring more women into tech by having more leaders. So that's my, you just have to take the lead, >>Take the lead, love that there. Same question for you. What's your advice and recommendations for those maybe future female leaders in tech? >>Yeah, absolutely. Um, Danielle mentioned imposter syndrome and I think we all struggle with it from time to time, no matter how many years it's been. And I think for me, for me, the advice would be if you're starting out, don't be afraid to ask, uh, questions and don't be afraid to kind of show a little bit of ignorance because we've all been there. And I think it's on all of us to remember what it's like to not know how things work. And on the flip side of that, if you are a more senior IC or, uh, in a leadership role, also being able to model just saying, I don't know how this works and going and figuring out answers together because that was a really powerful shift for me early in my career is just to feel like I can say that I don't know something. >>I totally agree. I've been in that same situation where just ask the question because you I'm guaranteed, there's a million outta people in the room that probably has the, have the same question and because of imposter syndrome, don't wanna admit, I don't understand that. Can we back up, but I agree with you. I think that is, um, one of the best things. Raise your hand, ask a question, ladies. Thank you so much for joining me talking about honeycomb and AWS, what you're doing together from a technology perspective and the focus efforts that each company has on D E and I, we appreciate your insights. Thank you so much for having us great talking to you. My pleasure, likewise for my guests, I'm Lisa Martin. You're watching the AWS partner showcase women in check. Welcome to the AWS partner showcase I'm Lisa Martin, your host. This is season one, episode three, and this is a great episode that focuses on women in tech. I'm pleased to be joined by Danielle Shaw, the ISV PSA director at AWS, and the sponsor of this fantastic program. Danielle, it's great to see you and talk about such an important topic. >>Yes. And I will tell you, all of these interviews have just been a blast for me to do. And I feel like there has been a lot of gold that we can glean from all of the, um, stories that we heard on these interviews and good advice that I myself would not have necessarily thought of. So >>I agree. And we're gonna get to set, cuz advice is one of the, the main things that our audience is gonna hear. We have Hillary Ashton, you'll see from TETA there, Reynolds joins us from honeycomb, Stephanie Curry from NetApp and Sue Paris from Jefferson Frank. And the topics that we dig into are first and foremost, diversity equity and inclusion. That is a topic that is incredibly important to every organization. And some of the things Danielle that our audiences shared were really interesting to me. One of the things that I saw from a thematic perspective over and over was that like D Reynolds was talking about the importance of companies and hiring managers and how they need to be intentional with de and I initiatives. And that intention was a, a, a common thing that we heard. I'm curious what your thoughts are about that, that we heard about being intentional working intentionally to deliver a more holistic pool of candidates where de I is concerned. What are your, what were some of the things that stuck out to you? >>Absolutely. I think each one of us is working inside of organizations where in the last, you know, five to 10 years, there's been a, you know, a strong push in this direction, mostly because we've really seen, um, first and foremost, by being intentional, that you can change the, uh, the way your organization looks. Um, but also just that, you know, without being intentional, um, there was just a lot of, you know, outcomes and situations that maybe weren't great for, um, you know, a healthy, um, and productive environment, uh, working environment. And so, you know, a lot of these companies have made a big investments and put forth big initiatives that I think all of us are involved in. And so we're really excited to get out here and talk about it and talk about, especially as these are all partnerships that we have, how, you know, these align with our values. So >>Yeah, that, that value alignment mm-hmm <affirmative> that you bring up is another thing that we heard consistently with each of the partners, there's a cultural alignment, there's a customer obsession alignment that they have with AWS. There's a D E and I alignment that they have. And I, I think everybody also kind of agreed Stephanie Curry talked about, you know, it's really important, um, for diversity on it, on, on impacting performance, highly performant teams are teams that are more diverse. I think we heard that kind of echoed throughout the women that we talked to in >>This. Absolutely. And I absolutely, and I definitely even feel that, uh, with their studies out there that tell you that you make better products, if you have all of the right input and you're getting all many different perspectives, but not just that, but I can, I can personally see it in the performing teams, not just my team, but also, you know, the teams that I work alongside. Um, arguably some of the other business folks have done a really great job of bringing more women into their organization, bringing more underrepresented minorities. Tech is a little bit behind, but we're trying really hard to bring that forward as well to in technical roles. Um, but you can just see the difference in the outcomes. Uh, at least I personally can just in the adjacent teams of mine. >>That's awesome. We talked also quite a bit during this episode about attracting women and underrepresented, um, groups and retaining them. That retention piece is really key. What were some of the things that stuck out to you that, um, you know, some of the guests talked about in terms of retention? >>Yeah. I think especially, uh, speaking with Hillary and hearing how, uh, Teradata is thinking about different ways to make hybrid work work for everybody. I think that is definitely when I talk to women interested in joining AWS, oftentimes that might be one of the first, uh, concerns that they have. Like, am I going to be able to, you know, go pick my kid up at four o'clock at the bus, or am I going to be able to, you know, be at my kids' conf you know, conference or even just, you know, have enough work life balance that I can, um, you know, do the things that I wanna do outside of work, uh, beyond children and family. So these are all very important, um, and questions that especially women come and ask, but also, um, you know, it kind of is a, is a bellwether for, is this gonna be a company that allows me to bring my whole self to work? And then I'm also gonna be able to have that balance that I need need. So I think that was something that is, uh, changing a lot. And many people are thinking about work a lot differently. >>Absolutely. The pandemic not only changed how we think about work, you know, initially it was, do I work from home or do I live at work? And that was legitimately a challenge that all of us faced for a long time period, but we're seeing the hybrid model. We're seeing more companies be open to embracing that and allowing people to have more of that balance, which at the end of the day, it's so much better for product development for the customers, as you talked about there's, it's a win-win. >>Absolutely. And, you know, definitely the first few months of it was very hard to find that separation to be able to put up boundaries. Um, but I think at least I personally have been able to find the way to do it. And I hope that, you know, everyone is getting that space to be able to put those boundaries up to effectively have a harmonious, you know, work life where you can still be at home most of the time, but also, um, you know, have that cutoff point of the day or at least have that separate space that you can feel that you're able to separate the two. >>Yeah, absolutely. And a lot of that from a work life balance perspective leads into one of the next topics that we covered in detail with, and that's mentors and sponsors the differences between them recommendations from, uh, the women on the panel about how to combat imposter syndrome, but also how to leverage mentors and sponsors throughout your career. One of the things that, that Hillary said that I thought was fantastic, advice were mentors and sponsors are concerned is, is be selective in picking your bosses. We often see people, especially younger folks, not necessarily younger folks. I shouldn't say that that are attracted to a company it's brand maybe, and think more about that than they do the boss or bosses that can help guide them along the way. But I thought that was really poignant advice that Hillary provided something that I'm gonna take into consideration myself. >>Yeah. And I honestly hadn't thought about that, but as I reflect through my own career, I can see how I've had particular managers who have had a major impact on helping me, um, with my career. But, you know, if you don't have the ability to do that, or maybe that's not a luxury that you have, I think even if you're able to, you know, find a mentor for a period of time or, um, you know, just, just enable for you to be able to get from say a point a to point B just for a temporary period. Um, just so you can grow into your next role, have a, have a particular outcome that you wanna drive, have a particular goal in mind find that person who's been there and done that and can really help you get through. If you don't have the luxury of picking your manager mentor, who can help you get to the next step. >>Exactly. That, that I thought that advice was brilliant and something that I hadn't really considered either. We also talked with several of the women about imposter syndrome. You know, that's something that everybody, I think, regardless of gender of your background, everybody feels that at some point. So I think one of the nice things that we do in this episode is sort of identify, yes, imposter syndrome is real. This is, this is how it happened to me. This is I navigated around or got over it. I think there's some great advice there for the audience to glean as well about how to dial down the imposter syndrome that they might be feeling. >>Absolutely. And I think the key there is just acknowledging it. Um, but also just hearing all the different techniques on, on how folks have dealt with it because everybody does, um, you know, even some of the smartest, most confident men I've, I've met in, uh, industry still talk to me about how they have it and I'm shocked by it oftentimes, but, um, it is very common and hopefully we, we talk about some good techniques to, to deal with that. >>I think we do, you know, one of the things that when we were asking the, our audience, our guests about advice, what would they tell their younger selves? What would they tell young women or underrepresented groups in terms of becoming interested in stem and in tech and everybody sort of agreed on me, don't be afraid to raise your hand and ask questions. Um, show vulnerabilities, not just as the employee, but even from a leadership perspective, show that as a leader, I, I don't have all the answers. There are questions that I have. I think that goes a long way to reducing the imposter syndrome that most of us have faced at some point in our lives. And that's just, don't be afraid to ask questions. You never know, oh, how can people have the same question sitting in the room? >>Well, and also, you know, for folks who've been in industry for 20, 25 years, I think we can just say that, you know, it's a, it's a marathon, it's not a sprint and you're always going to, um, have new things to learn and you can spend, you know, back to, we talked about the zing and zagging through careers, um, where, you know, we'll have different experiences. Um, all of that kind of comes through just, you know, being curious and wanting to continue to learn. So yes, asking questions and being vulnerable and being able to say, I don't know all the answers, but I wanna learn is a key thing, uh, especially culturally at AWS, but I'm sure with all of these companies as well, >>Definitely I think it sounded like it was really ingrained in their culture. And another thing too, that we also talked about is the word, no, doesn't always mean a dead end. It can often mean not right now or may, maybe this isn't the right opportunity at this time. I think that's another important thing that the audience is gonna learn is that, you know, failure is not necessarily a bad F word. If you turn it into opportunity, no isn't necessarily the end of the road. It can be an opener to a different door. And I, I thought that was a really positive message that our guests, um, had to share with the, the audience. >>Yeah, totally. I can, I can say I had a, a mentor of mine, um, a very, uh, strong woman who told me, you know, your career is going to have lots of ebbs and flows and that's natural. And you know that when you say that, not right now, um, that's a perfect example of maybe there's an ebb where it might not be the right time for you now, but something to consider in the future. But also don't be afraid to say yes, when you can. <laugh> >>Exactly. Danielle, it's been a pleasure filming this episode with you and the great female leaders that we have on. I'm excited for the audience to be able to learn from Hillary Vera, Stephanie Sue, and you so much valuable content in here. We hope you enjoy this partner showcase season one, episode three, Danielle, thanks so much for helping >>Us with it's been a blast. I really appreciate it >>All audience. We wanna enjoy this. Enjoy the episode.

>> From theCUBE studios in Palo Alto in Boston bringing you data driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> Despite fears of inflation, supply chain issues skyrocketing energy and home prices and global instability caused by the Ukraine crisis CIOs and IT buyers continue to expect overall spending to increase more than 6% in 2022. Now, while this is lower than our 8% prediction that we made earlier this year in January, it remains in line with last year's roughly six to 7% growth and is holding firm with the expectations reported by tech executives on the ETR surveys last quarter. Hello and welcome to this week's wiki bond cube insights powered by ETR in this breaking analysis, we'll update you on our latest look at tech spending with a preliminary take from ETR's latest macro drill down survey. We'll share some insights to which vendors have shown the biggest change in spending trajectory. And we'll tap our technical analysts to get a read on what they think it means for technology stocks going forward. The IT spending sentiment among IT buyers remains pretty solid. >> In the past two months, we've had conversations with dozens of CIOs, chief digital officers data executives, IT managers, and application developers, and across the board, they've indicated that for now at least their spending levels remain largely unchanged. The latest ETR drill down data which will share shortly, confirms these anecdotal checks. However, the interpretation of this data it's somewhat nuanced. Part of the reason for the spending levels being you know reasonably strong and holding up is inflation. Stuff costs more so spending levels are higher forcing IT managers to prioritize. Now security remains the number one priority and is less susceptible to cuts, cloud migration, productivity initiatives and other data projects remain top priorities. >> So where are CIO's robbing from Peter to pay Paul to focus on these priorities? Well, we've seen a slight uptick in certain speculative. IT projects being put on hold or frozen for a period of time. And according to ETR survey data we've seen some hiring freezes reported and this is especially notable in the healthcare sector. ETR also surveyed its buyer base to find out where they were adjusting their budgets and the strategies and tactics they were using to do so. Consolidating IT vendors was by far the most cited tactic. Now this makes sense as companies in an effort to negotiate better deals will often forego investments in newer so-called best of breed products and services, and negotiate bundles from larger suppliers. You know, even though they might not be as functional, the buyers >> can get a better deal if they bundle together from one of their larger suppliers. Think Microsoft or a Dell or other, you know, large companies. ETR survey respondents also cited cutting the cloud bill where discretionary spending was in play was another strategy or tactic that they were using. We certainly saw this with some of the largest snowflake customers this past quarter. Where even though they were still growing consumption rapidly certain snowflake customers dialed down their consumption and pushed spending off to future quarters. Now remember in the case of snowflake, anyway, customers negotiate consumption rates and their pricing based on a total commitment over a period of time. So while they may consume less in one quarter, over the lifetime of the contract, snowflake, as do many other cloud companies, have good visibility on the lifetime value of a deal. Now this next chart shows the latest ETR spending expectations among more than 900 respondents. The bars represent spending growth expectations from the periods of December, 2021 that's the gray bars, March of 2022 survey in the blue, and the most recent June data, That's the yellow bar. So you can see spending expectations for the quarter is down slightly in the mid 5% range. But overall for the year expectations remain in the mid 6% range. Now it's down from 8%, 8.3% in December where it looked like 2022 was going to really be a breakout year and have more momentum than even last year. Now, remember this was before Russia invaded Ukraine which occurred in mid-February of this year. So expectations were a little higher. So look, generally speaking CIOs have told us that their CFOs and CEOs have lowered their earnings outlooks and communicated that to Wall Street. They've told us that unless and until these revised forecasts appear at risk, they continue to expect their budget levels to remain pretty constant. Now there's still plenty of momentum and spending velocity on specific vendor platforms. Let's take a look at that. >> This chart shows the companies with the greatest spending momentum as measured by ETRs proprietary net score methodology. Net score essentially measures the net percent of customers spending more on a particular platform. That measurement is shown on the Y axis. The red line there that's inserted that red dotted line at 40%, we consider to be a highly elevated mark. And the green dots are companies in the ETR survey that are near or above that line. The X axis measures the presence in the data set, how much, you know sort of pervasiveness, if you will, is in the data. It's kind of a proxy for market presence. Now, of course we all know Kubernetes is not a company, but it remains an area where organizations are spending lots of resources and time particularly to modernize and mobilize applications. Snowflake remains the company which leads all firms in spending velocity, but as you'll see momentarily, despite its highest position relative to everybody else in the survey, it's still down from its previous levels in the high seventies and low 80% range. AWS is incredibly impressive because it has an elevated level but also a big presence in the data set in the survey. Same with Microsoft, same with ServiceNow which also stands out. And you can see the other smaller vendors like HashiCorp which is increasingly being seen as a strategic cross cloud enabler. They're showing, spending momentum. The RPA vendors you see in there automation anywhere and UI path are in the mix with numerous security companies, CrowdStrike, CyberArk, Netskope, Cloudflare, Tenable Okta, Zscaler Palo Alto networks, Sale Point Fortunate. A big number of cybersecurity firms hovering at or above that 40% mark you can see pure storage remains elevated as do PagerDuty and Coupa. So plenty of good news here, despite the recent tech crash. So that was the good, here's the not so good. So >> there is no 40% line on this chart because all these companies are well below that line. Now this doesn't mean these companies are bad companies. They just don't have the spending velocity of the ones we showed earlier. A good example here is Oracle. Look how they stand out on the X axis with a huge market presence. And Oracle remains an incredibly successful company selling to high end customers and really owning that mission critical data and application space. And remember ETR measures spending activity, but not actual spending dollars. So Oracle is skewed as a result because Oracle customers spend big bucks. But the fact is that Oracle has a large legacy install base that pulls down their growth rates. And that does show up in the ETR survey data. Broadcom is another example. They're one of the most successful companies in the industry, and they're not going after growth at all costs at all. They're going after EBITDA and of course ETR doesn't measure EBIT. So just keep that in mind, as you look at this data. Now another way to look at the data and the survey, is exploring the net score movement over the last period amongst companies. So how are they moving? What's happening to the net score over time. And this chart shows the year over year >> net score change for vendors that participate in at least three sectors within the ETR taxonomy. Remember ETR taxonomy has 12, 15 different segments. So the names above or below the gray dotted line are those companies where the net score has increased or decreased meaningfully. So to the earlier chart, it's all relative, right? Look at Oracle. While having lower net scores has also shown a more meaningful improvement in net score than some of the others, as have SAP and Teradata. Now what's impressive to me here is how AWS, Microsoft, and Google are actually holding that dotted line that gray line pretty well despite their size and the other ironically interesting two data points here are Broadcom and Nutanix. Now Broadcom, of course, as we've reported and dug into, is buying VMware and, and of, of course most customers are concerned about getting hit with higher prices. Once Broadcom takes over. Well Nutanix despite its change in net scores, in a good position potentially to capture some of that VMware business. Just yesterday, I talked to a customer who told me he migrated his entire portfolio off VMware using Nutanix AHV, the Acropolis hypervisor. And that was in an effort to avoid the VTEX specifically. Now this was a smaller customer granted and it's not representative of what I feel is Broadcom's ICP the ideal customer profile, but look, Nutanix should benefit from the Broadcom acquisition. If it can position itself to pick up the business that Broadcom really doesn't want. That kind of bottom of the pyramid. One person's trash is another's treasure as they say, okay. And here's that same chart for companies >> that participate in less than three segments. So, two or one of the segments in the ETR taxonomy. Only three names are seeing positive movement year over year in net score. SUSE under the leadership of amazing CEO, Melissa Di Donato. She's making moves. The company went public last year and acquired rancher labs in 2020. Look, we know that red hat is the big dog in Kubernetes but since the IBM acquisition people have looked to SUSE as a possible alternative and it's showing up in the numbers. It's a nice business. It's going to do more than 600 million this year in revenue, SUSE that is. It's got solid double digit growth in kind of the low teens. It's profitability is under pressure but they're definitely a player that is found a niche and is worth watching. The SolarWinds, What can I say there? I mean, maybe it's a dead cat bounce coming off the major breach that we saw a couple years ago. Some of its customers maybe just can't move off the platform. Constant contact we really don't follow and don't really, you know, focus on them. So, not much to say there. Now look at all the high priced earning stocks or infinite PE stocks that have no E and divide by zero or a negative number and boom, you have infinite PE and look at how their net scores have dropped. We've reported extensively on snowflake. They're still number one as we showed you earlier, net score, but big moves off their highs. Okta, Datadog, Zscaler, SentinelOne Dynatrace, big downward moves, and you can see the rest. So this chart really speaks to the change in expectations from the COVID bubble. Despite the fact that many of these companies CFOs would tell you that the pandemic wasn't necessarily a tailwind for them, but it certainly seemed to be the case when you look back in some of the ETR data. But a big question in the community is what's going to happen to these tech stocks, these tech companies in the market? We reached out to both Eric Bradley of ETR who used to be a technical analyst on Wall Street, and the long time trader and breaking analysis contributor, Chip Symington to get a read on what they thought. First, you know the market >> first point of the market has been off 11 out of the past 12 weeks. And bare market rallies like what we're seeing today and yesterday, they happen from time to time and it was kind of expected. Chair Powell's testimony was broadly viewed as a positive by the street because higher interest rates appear to be pushing commodity prices down. And a weaker consumer sentiment may point to a less onerous inflation outlook. That's good for the market. Chip Symington pointed out to breaking analysis a while ago that the NASDAQ has been on a trend line for the past six months where its highs are lower and the lows are lower and that's a bad sign. And we're bumping up against that trend line here. Meaning if it breaks through that trend it could be a buying signal. As he feels that tech stocks are oversold. He pointed to a recent bounce in semiconductors and cited the Qualcomm example. Here's a company trading at 12 times forward earnings with a sustained 14% growth rate over the next couple of years. And their cash flow is able to support their 2.4, 2% annual dividend. So overall Symington feels this rally was absolutely expected. He's cautious because we're still in a bear market but he's beginning to, to turn bullish. And Eric Bradley added that He feels the market is building a base here and he doesn't expect a 1970s or early 1980s year long sideways move because of all the money that's still in the system. You know, but it could bounce around for several months And remember with higher interest rates there are going to be more options other than equities which for many years has not been the case. Obviously inflation and recession. They are like two looming towers that we're all watching closely and will ultimately determine if, when, and how this market turns around. Okay, that's it for today. Thanks to my colleagues, Stephanie Chan, who helps research breaking analysis topics sometimes, and Alex Myerson who is on production in the podcast. Kristin Martin and Cheryl Knight they help get the word out and do all of our newsletters. And Rob Hof is our Editor in Chief over at siliconangle.com and does some wonderful editing for breaking analysis. Thank you. Remember, all these episodes are available as podcasts wherever you listen. All you got to do is search breaking analysis podcasts. I publish each week on wikibon.com and Siliconangle.com. And of course you can reach me by email at david.vellante@siliconangle.com or DM me at DVellante comment on my LinkedIn post and please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE insights powered by ETR. Stay safe, be well. And we'll see you next time. (soft music)

>>The cube presents, Dell technologies world brought to you by Dell. >>Good morning. Welcome to day two of the cube at Dell technologies world live from the Venetian in Las Vegas. Lisa Martin, with John farrier, Dave Nicholson guys, a lot of momentum yesterday. The vibe was amazing. We're think there's about 8,000 people here and spends yesterday a lot going on with multi-cloud with partners, with customers, John, we got Michael Dell coming on in just about 15, 20 minutes. >>Yep. The keynotes getting out, people are starting to come in. You can see them, uh, flowing through the hallway. Michael Dell will be on about 15 minutes and we're gonna ask him every year when they have the cube here, we're gonna have room with questions around digital transformation. Security is the hot thing. Obviously here, data and what's up with Dell. So we'll see what, what he is gonna say. >>We had some really good interviews yesterday. We, we had customers on, we had partners and the, the overall sentiment was people are very excited about, I mean, the momentum that Dell is coming off of from F Y 22 of first time hitting north of a, of a hundred billion or in the company's history, the partner ecosystem expanding what their acknowledgement multi-cloud is here. Yeah. The, the vibe was good. The, the partners are excited. Lot of opportunity. Yeah. >>I mean, I think the big thing story here this year is that, you know, VMware's not part of Dell technologies world, although there is some stuff kind of connecting together in terms of ownership, but it's still now on its own. So that's, that's a key, um, development that's happened since we were last here in person, but the digital transformation train continues to go down the tracks and it's getting better and better and better. And for, in terms of what is happening, but there's still more complexity at the edge. That's something that's important and security more than ever is important on a global stage. But also the cyber attacks are going up. Ransomware is, has essentially I'm so standard. Everyone needs a, a solution. So everyone's pivoting to endpoint protection, zero, zero trust. And, um, ransomware has been, you see the storage vendors go that way. So that's a big trend. Uh, a lot of people go in there and they need it too. Cuz ransomware is very dangerous. So, and then obviously cyber all over the world is, is a huge, so, you know, Dell plays a role in that. They have a lot of gear and, and I think the edge is developing nicely. >>Yeah. You talk about ransomware. I was reading some stats recently that there's one attack, every 11 seconds that organizations now it's not a matter of, are we gonna get hit it's when yeah. And I think I wrote a stat the other day that said 75% of organizations will be hit by at least one cyber attack by 2025, which is around the corner. So security is that board level, front and center conversation. Yeah. And we saw a lot of that with what they were announcing just yesterday alone. >>Yeah. And to me, the cybersecurity issue is just also a political one. Uh, the adversaries can play with open source and the threats are real. The threat vectors are increasing and there's no perimeter as everyone knows that in security and you start to see data being protected. So now you've got data protection is that's big for Dell. You know, they have a huge footprint of disaster recovery and data protection. And so that becomes a really key point for protecting the data in flight, uh, data. Engineering's a hot trend. So data as code has become huge. You're seeing that in, in all the digital applications, the role of data is becoming more and more. >>Absolutely. We talked a lot Dave about edge yesterday and especially, particularly in retail and a lot of the massive transformation and the pressure that retail is under, you know, us consumers, we bring this, we want the online experience in the connected store. And so they talked a lot about what they're doing with respect to edge at the retail yesterday and in financial services. Really interesting. What are some of your thoughts on the direction that Dell's going? >>So I've been, I've been taking a little bit of a different angle on this since I've been here prowling around looking under the covers to get an understanding of the advances in hardware that are driving the top line value per opposition. So here it's appropriate to talk about things like retail at the edge and the experience that that delivers to an end user customer Dell is still doing, however, the really hard work of optimizing systems on the back end, the stuff that a lot of people would say they don't care about. The idea is Dell makes sure that this development that happens so people at the edge don't have to care about it. So, so that's the thing that I find fascinating being a kind of an old school hardware guy myself, is that all these really cool things aren't getting talked about because we don't need to talk about them because Dell has it handled. So whether it's whether it's retail, uh, whether it's, uh, uh, advances insecurity, uh, they're all driven by highly optimized and tuned hardware. You mentioned partners, um, partnerships that Dell has behind the scenes are critical to all of that. >>I mean, I think the big thing about Dell too, is they have a co here. Um, they have Chuck Whitten, a co chief operating officer, uh, Jeff Clark, uh, Chuck Whitten's new, uh, came from BAE and you got two do Cocos. Right? Right. So you got a fledging company Dell's growing. And, and the big question is M and a right. Dave and I were talking about that last night with a bunch of folks in the, in the hallway about who does Dell buy? Do they need to buy anyone? Right? And again, uh, hardware is back. I mean, you look at what we talked about yesterday. And our wrap up day one was essentially, hardware's becoming more important. And even at Amazon reinvent, when we recovering that show role of Silicon plays a huge role. Now they run hardware in the cloud. So, um, we all know hardware, just servers, somewhere in the cloud there. So I think hardware is gonna be huge David, because, you know, edge needs more smaller, faster, cheaper Bob access to colo, uh, Equinox was on yesterday. Um, you're seeing like 5g edges deploying. So I think hardware is gonna matter. I think you'll see the home become much more device centric, smarter devices. So smart city, smart homes, hardware matters more than ever. >>Yeah. Yeah. Well, and, and from an acquisition perspective who, who knows maybe Dell would acquire VMware <laugh> crazier things have happened >>Or VMware could acquire Dell >>Or yeah. Crazier things have happened. >>They would argue that one. <laugh> >>So, so the hardware hardware's back back again. It makes me think of that M and M song slim, shady. You think we need to do some sort of parody on that <laugh> together, but what does that mean for, for the partner community? There are over 200,000 partners. We talk about Barun GSI data center, the hyperscalers, that partner. >>Yeah. I mean, I mean, the partner story is I think more important than ever. And you seeing more ecosystems develop around companies that you wouldn't think have ecosystems that's because with cloud and now the cloud operating model, which is on-premise and edge, you can do piece parts of solutions and, and the glue layers, the abstraction layers in software at scale are now available. So it's easier for customers to buy point solutions or platforms and put them together. Bet it more than every the headless retail, as an example, uh, a trend that's happening. You're seeing, look at, look at, uh, in the, in the, uh, consumer market, ghost kitchens, ghost retail. So you're starting to see delivery. And so at the consumerization of it is happening. You're gonna see more and more customs applications that are taking advantage of stacks that are configured either on the fly or, you know, most multiple partners. So I think you're gonna see, you know, the big players like AWS, uh, uh, Microsoft, Dell have real big ecosystem players and that's gonna be a huge trend continuing. >>So today Michael Dell is coming on in just minutes. Chuck Whitten is also on Jeff Clark. What are some of the things that you really want to dig into with these guys, John? Well, >>The big thing I want to ask him is how they're stress, energy, and operations fit into how their customers are consuming. Uh, Dell's got a huge customer base. I wanna find out how their, how their solutions are being operationalized by the customers. And that's gonna be coming, poking at the cloud a little bit and see how real that's going. Apex has been very popular. The security story. I also wanna ask about the changing workforce because the it departments of the old those folks are aging out. So a new generation of it is coming together. And I think those folks want things easy, push button, easy button dashboards. They've never, maybe not even racked the server before. So completely different new generation. When I see how that impacts the, uh, how they make products, >>Good point. We saw some of that in, you know, this morning they were showing some of the gaming, um, opportunities, Dave and I were in there this morning and what they're doing for that, and the gamers are all very excited about that. But the connected home was something that they were talking about. >>Yeah. Yeah. Who knew you could make a, uh, you know, a track pad on a laptop, more exciting. <laugh> it's, I mean, it's brilliant, right? They, you know, controls for, uh, you know, for, uh, home video conferencing built in, um, it, it just shows that again, kind of at that hardware level where people think, ah, it doesn't matter. No, there's a lot of room for innovation there. And back to the discussion of around partners, um, much like the big cloud players depend upon systems integrators out in the marketplace in order to deliver these solutions to end user kind customers. The channel's gonna be incredibly important. And I know that Dell is putting a lot of effort behind that right now. That's pretty clear. Yep. >>Yeah. We've seen lot of that. So exciting stuff today. I mentioned the three guys, three only of the many folks that are coming on the show today. We've got Allison Dew tomorrow, some other happy hitters guys looking forward to great day two full coverage. Stay with us. We've got a lot of content coming at you from the cube live from the show floor of Dell technologies, world 2022 from the Venetian in Las Vegas, stick around Michael Dell will be up next with John and Dave.

(upbeat music) >> Okay today, we welcome Evan Kaplan, CEO of InfluxData, the company behind InfluxDB. Welcome Evan, thanks for coming on. >> Hey John, thanks for having me. >> Great segment here on the InfluxDB story. What is the story? Take us through the history, why time series? What's the story? >> So the history history is actually pretty interesting. Paul Dix my partner in this and our founder, super passionate about developers and developer experience. And he had worked on wall street building a number of time series kind of platform, trading platforms for trading stocks. And from his point of view, it was always what he would call a yak shave. Which means you had to do a ton of work just to start doing work. Which means you had to write a bunch of extrinsic routines, you had to write a bunch of application handling on existing relational databases, in order to come up with something that was optimized for a trading platform or a time series platform. And he sort of, he just developed this real clear point of view. This is not how developers should work. And so in 2013, he went through Y Combinator, and he built something for, he made his first commit to open source InfluxDB in the end of 2013. And he basically, you know from my point of view, he invented modern time series, which is you start with a purpose built time series platform to do these kind of workloads, and you get all the benefits of having something right out of the box. So a developer can be totally productive right away. >> And how many people are in the company? What's the history of employees is there? >> Yeah, I think we're, you know, I always forget the number but something like 230 or 240 people now. I joined the company in 2016, and I love Paul's vision. And I just had a strong conviction about the relationship between time series and IOT. 'Cause if you think about it, what sensors do is they speak time series. Pressure, temperature, volume, humidity, light, they're measuring, they're instrumenting something over time. And so I thought that would be super relevant over the long term, and I've not regretted it. >> Oh no, and it's interesting at that time if you go back in history, you know, the role of database. It's all relational database, the one database to rule the world. And then as cloud started coming in, you started to see more databases proliferate, types of databases. And time series in particular is interesting 'cause real time has become super valuable from an application standpoint. IOT which speaks time series, means something. It's like time matters >> Times yeah. >> And sometimes data's not worth it after the time, sometimes it's worth it. And then you get the data lake, so you have this whole new evolution. Is this the momentum? What's the momentum? I guess the question is what's the momentum behind it? >> You mean what's causing us to grow so fast? >> Yeah the time series, why is time series- >> And the category- >> Momentum, what's the bottom line? >> Well think about it, you think about it from a broad sort of frame which is, what everybody's trying to do is build increasingly intelligent systems. whether it's a self-driving car or a robotic system that does what you want to do, or a self-healing software system. Everybody wants to build increasing intelligent systems. And so in order to build these increasing intelligent systems, you have to instrument the system well. And you have to instrument it over time, better and better. And so you need a tool, a fundamental tool to drive that instrumentation. And that's become clear to everybody that that instrumentation is all based on time. And so what happened, what happened, what happened, what's going to happen. And so you get to these applications like predictive maintenance, or smarter systems, and increasingly you want to do that stuff not just intelligently, but fast in real time. So millisecond response, so that when you're driving a self-driving car, and the system realizes that you're about to do something, essentially you want to be able to act in something that looks like real time. All systems want to do that, they want to be more intelligent, and they want to be more real time. And so we just happen to, you know, we happen to show up at the right time in the evolution of a market. >> It's interesting near real time isn't good enough when you need real time. >> Yeah, it's not, it's not. And it's like everybody wants real even when you don't need it, ironically you want it. It's like having the feature for, you know you buy a new television, you want that one feature, even though you're not going to use it. You decide that's your buying criteria. Real time is criteria for people. >> So I mean, what you're saying then is near realtime is getting closer to real time as fast as possible? >> Right. >> Okay, so talk about the aspect of data, 'cause we're hearing a lot of conversations on theCUBE in particular around how people are implementing and actually getting better. So iterating on data, but you have to know when it happened to get know how to fix it. So this is a big part of what we're seeing with people saying, "Hey, you know I want to "make my machine learning algorithms better "after the fact, I want to learn from the data." How do you see that evolving? Is that one of the use cases of sensors as people bring data in off the network, getting better with the data, knowing when it happened? >> Well, for sure what you're saying is, is none of this is non-linear, it's all incremental. And so if you take something, you know just as an easy example, if you take a self-driving car, what you're doing is you're instrumenting that car to understand where it can perform in the real world in real time. And if you do that, if you run the loop which is, I instrument it, I watch what happens, oh that's wrong, oh I have to correct for that. I correct for that in the software. If you do that for a billion times, you get a self-driving car. But every system moves along that evolution. And so you get the dynamic of constantly instrumenting, watching the system behave and do it. And so a self driving car is one thing, but even in the human genome, if you look at some of our customers, you know, people like, people doing solar arrays, people doing power walls like all of these systems are getting smarter and smarter. >> Well, let's get into that. What are the top applications? What are you seeing with InfluxDB, the time series, what's the sweet spot for the application use case and some customers? Give some examples. >> Yeah so it's pretty easy to understand on one side of the equation, that's the physical side is, sensors are getting cheap obviously we know that. The whole physical world is getting instrumented, your home, your car, the factory floor, your wrist watch, your healthcare, you name it, it's getting instrumented in the physical world. We're watching the physical world in real time. And so there are three or four sweet spots for us, but they're all on that side, they're all about IOT. So they're thinking about consumer IOT kind of projects like Google's Nest, Tudor, particle sensors, even delivery engines like Rappi, who deliver the instant car to South America. Like anywhere there's a physical location and that's on the consumer side. And then another exciting space is the industrial side. Factories are changing dramatically over time. Increasingly moving away from proprietary equipment to develop or driven systems that run operational. Because what has to get smarter when you're building a factory is systems all have to get smarter. And then lastly, a lot in the renewables, so sustainability. So a lot, you know, Tesla, Lucid motors, Nicola motors, you know, lots to do with electric cars, solar arrays, windmills arrays, just anything that's going to get instrumented that where that instrumentation becomes part of what the purpose is. >> It's interesting the convergence of physical and digital is happening with the data. IOT you mentioned, you know, you think of IOT, look at the use cases there. It was proprietary OT systems, now becoming more IP enabled, internet protocol. And now edge compute, getting smaller, faster, cheaper. AI going to the edge. Now you have all kinds of new capabilities that bring that real time and time series opportunity. Are you seeing IOT going to a new level? Where's the IOT OT dots connecting to? Because, you know as these two cultures merge, operations basically, industrial, factory, car, they got to get smarter. Intelligent edge is a buzzword but I mean, it has to be more intelligent. Where's the action in all this? >> So the action, really, it really at the core, it's at the developer, right? Because you're looking at these things, it's very hard to get an off the shelf system to do the kinds of physical and software interaction. So the action's really happen at the developer. And so what you're seeing is a movement in the world that maybe you and I grew up in with IT or OT moving increasingly that developer driven capability. And so all of these IOT systems, they're bespoke, they don't come out of the box. And so the developer, the architect, the CTO, they define what's my business? What am I trying to do? Am I trying to sequence a human genome and figure out when these genes express themselves? Or am I trying to figure out when the next heart rate monitor is going to show up in my apple watch? Right, what am I trying to do? What's the system I need to build? And so starting with the developer is where all of the good stuff happens here. Which is different than it used to be, right. It used to be you'd buy an application or a service or a SaaS thing for, but with this dynamic, with this integration of systems, it's all about bespoke, it's all about building something. >> So let's get to the developer real quick. Real highlight point here is the data, I mean, I could see a developer saying, "Okay, I need to have an application for the edge," IOT edge or car, I mean we're going to have, I mean Tesla got applications of the car, it's right there. I mean, there's the modern application life cycle now. So take us through how does this impacts the developer. Does it impact their CICD pipeline? Is it cloud native? I mean where does this go to? >> Well, so first of all you're talking about, there was an internal journey that we had to go through as a company which I think is fascinating for anybody that's interested, is we went from primarily a monolithic software that was open sourced to building a Cloud-native platform. Which means we had to move from an agile development environment to a CICD environment. So to degree that you are moving your service, whether it's you know, Tesla monitoring your car and updating your power walls, right. Or whether it's a solar company updating the arrays, right, to a degree that that service is cloud. Then increasingly we remove from an agile development to a CICD environment, which you're shipping code to production every day. And so it's not just the developers, it's all the infrastructure to support the developers to run that service and that sort of stuff. I think that's also going to happen in a big way. >> When your customer base that you have now, and as you see evolving with in InfluxDB, is it that they're going to be writing more of the application or relying more on others? I mean obviously it's an open source component here. So when you bring in kind of old way, new way, old way was, I got a proprietary platform running all this IOT stuff, and I got to write, here's an application that's general purpose. I have some flexibility, somewhat brittle, maybe not a lot of robustness to it, but it does this job. >> A good way to think about this is- >> Versus new way which is what? >> So yeah a good way to think about this is what's the role of the developer/architect, CTO, that chain within a large, with an enterprise or a company. And so the way to think about is I started my career in the aerospace industry. And so when you look at what Boeing does to assemble a plane, they build very very few of the parts. Instead what they do is they assemble. They buy the wings, they buy the engines, they assemble, actually they don't buy the wings. That's the one thing, they buy the material for the wing. They build the wings 'cause there's a lot of tech in the wings, and they end up being assemblers, smart assemblers of what ends up being a flying airplane. Which is a pretty big deals even now. And so what happens with software people is, they have the ability to pull from you know, the best of the open source world. So they would pull a time series capability from us, then they would assemble that with potentially some ETL logic from somebody else. Or they'd assemble it with a Kafka interface to be able to stream the data in. And so they become very good integrators and assemblers but they become masters of that bespoke application. And I think that's where it goes 'cause you're not writing native code for everything. >> So they're more flexible, they have faster time to market 'cause they're assembling. >> Way faster. >> And they get to still maintain their core competency, AKA their wings in this case. >> They become increasingly not just coders but designers and developers. They become broadly builders is what we like to think of it. People who start and build stuff. By the way, this is not different than the people just up the road. Google have been doing for years or the tier one Amazon building all their own. >> Well, I think one of the things that's interesting is that this idea of a systems developing, a system architecture. I mean systems have consequences when you make changes. So when you have now cloud data center on-premise and edge working together, how does that work across the system? You can't have a wing that doesn't work with the other wing kind of thing. >> That's exactly, but that's where that Boeing or that airplane building analogy comes in. For us, we've really been thoughtful about that because IOT it's critical. So our open source edge has the same API as our cloud native stuff that has enterprise on prem edge. So our multiple products have the same API and they have a relationship with each other. They can talk with each other. So the builder builds it once. And so this is where, when you start thinking about the components that people have to use to build these services is that, you want to make sure at least that base layer, that database layer that those components talk to each other. >> So I'll have to ask you if I'm the customer, I put my customer hat on. Okay, hey, I'm dealing with a lot. >> Does that mean you have a PO for- >> (laughs) A big check, a blank check, if you can answer this question. >> Only if in tech. >> If you get the question right. I got all this important operation stuff, I got my factory, I got my self-driving cars, this isn't like trivial stuff, this is my business. How should I be thinking about time series? Because now I have to make these architectural decisions as you mentioned and it's going to impact my application development. So huge decision point for your customers. What should I care about the most? What's in it for me? Why is time series important? >> Yeah, that's a great question. So chances are, if you've got a business that was 20 years old or 25 years old, you were already thinking about time series. You probably didn't call it that, you built something on Oracle, or you built something on IBM's Db2, right, and you made it work within your system. Right, and so that's what you started building. So it's already out there, there are probably hundreds of millions of time series applications out there today. But as you start to think about this increasing need for real time, and you start to think about increasing intelligence, you think about optimizing those systems over time, I hate the word, but digital transformation. Then you start with time series, it's a foundational base layer for any system that you're going to build. There's no system I can think of where time series shouldn't be the foundational base layer. If you just want to store your data and just leave it there and then maybe look it up every five years, that's fine. That's not time series. Time series is when you're building a smarter more intelligent, more real time system. And the developers now know that. And so the more they play a role in building these systems the more obvious it becomes. >> And since I have a PO for you and a big check. >> Yeah. >> What's the value to me when I implement this? What's the end state? What's it look like when it's up and running? What's the value proposition for me? What's in it for me? >> So when it's up and running, you're able to handle the queries, the writing of the data, the down sampling of the data, the transforming it in near real time. So that the other dependencies that a system it gets for adjusting a solar array or trading energy off of a power wall or some sort of human genome, those systems work better. So time series is foundational. It's not like it's doing every action that's above, but it's foundational to build a really compelling intelligence system. I think that's what developers and architects are seeing now. >> Bottom line, final word, what's in it for the customer? What's your statement to the customer? What would you say to someone looking to do something in time series and edge? >> Yeah so it's pretty clear to us that if you're building, if you view yourself as being in the business of building systems, that you want 'em to be increasingly intelligent, self-healing autonomous. You want 'em to operate in real time, that you start from time series. But I also want to say what's in it for us, Influx. What's in it for us is, people are doing some amazing stuff. You know, I highlighted some of the energy stuff, some of the human genome, some of the healthcare, it's hard not to be proud or feel like, "Wow." >> Yeah. >> "Somehow I've been lucky, I've arrived at the right time, "in the right place with the right people "to be able to deliver on that." That's also exciting on our side of the equation. >> Yeah, it's critical infrastructure, critical of operations. >> Yeah. >> Great stuff. Evan thanks for coming on, appreciate this segment. All right, in a moment, Brian Gilmore director of IOT and emerging technology at InfluxData will join me. You're watching theCUBE, leader in tech coverage. Thanks for watching. (upbeat music)

>>Mm. Okay, we're back. Digging into the infrastructure to make hybrid work possible. High performance, cost effective, scalable and secure. That's what it's all about. So far, we've covered the rapid migration to WiFi 60 technology and the role that switching is going to play. And now we're gonna get into private five g to do that. Let's welcome Masumi here. Who is vice president and general manager of mobile cable and the Iot business at Cisco and Greg Dorey, who is the vice president of product management for the networking experiences group of Cisco. He's responsible for Catalyst access that whole portfolio enterprise five G Cisco DNA spaces, Cisco, Iasi A lot of stuff there. Uh, Greg gentlemen, welcome, >>Dave. Thank you for having us. >>Yeah, our pleasure. So let's start with you on the topic of private five g five g. What do we need to know about that? And more specifically, you know what's unique about Cisco's private five G? >>So, most importantly, delivering private five G in enterprise terms that's super important to look at five p. Many of our peer groups might have got it wrong. We're looking at private five g with the lens of enterprise. What enterprise really needs is five g going to come and displace a lot of existing technology? Or is it going to help augment the technology that enterprise has an excellent Their digitisation is you need. I wanted to start Dave with the basic premise of hybrid work, and what hybrid work really means. Is it only for knowledge worker or is it for all workers? So we strongly believe hybrid work needs to empower all workers. It's not only connecting remote workers but also bringing people things and space together. And I strongly believe the combination of WiFi six n five g for private network is going to accelerate that journey, bringing people things and space together in a very, very cohesive way. Why are our offer is so unique? We are going to create a continent. Enterprises don't have to make a hard choice. They will be using WiFi technology and five G technology hand in hand without creating a disruption on their policy and identity systems. They don't have to rethink. Do I have to go and build a new background is a common background that will support both WiFi as well as five t Most importantly, delivering this enter offer as a service with the ease of consumption is of operation and trusted environment that they can put their mission critical workloads on. >>I like it. So couple takeaways there are inclusive of all workers, not just knowledge workers non disruptive. Everybody loves to hear that. And of course, the as a service model is key. So let me stay with you. I mean, we can't wait for five g, right? It's lightning fast. They've got super low latency, very high bandwidth. So that's what everybody is excited about. The question, though, is is five g gets introduced. You know it's going to power things like Coyote Networks. Is that going to replace WiFi and legacy Wired broadband? >>Absolutely not. So we see private five years, an augmentation to the enterprise on top of WiFi WiFi. As you heard in the previous conversation, WiFi is bringing more capability with WiFi six and WiFi 16 and five G is going to be yet another augmentation. WiFi and fight. The will coexist within enterprise for many years to come. I would like my friend Greg to talk a little bit about this continuum. Greg. >>Yeah, I think it's sort of like I like to say it's an and not an AR because there's enough use cases out there. Richard Pryor Spectrum And you know, spectrum >>is a constraint, so >>you have private five G, your WiFi six and both offer opportunities. So, for example, in an indoor carpet setting where you're basically connecting your phone for basic browsing or connecting your laptop, WiFi is sufficient. But if it's a process automation, uh, factory where you need seven nines of reliability, private five g is a better technology. Similarly outdoor large areas. It's probably private. Five g right like this, you can have easy handoff between public and private, so it's use case driven, and once it's used case driven, it's going to be an are because there's so many next time use cases, whether it's a are we are drones, self driving cars, you name it right, like And so I think these two technologies five g and Y 5 60 is gonna work hand in hand to deliver awesome outcomes for our customers. >>Yeah, and just the data volumes are gonna be incredible. We always talk about the data volumes. You ain't seen nothing yet is what I always say. But the thing is, every new tech that's introduced into the enterprise, you can almost be certain that is going to bring adoption challenges. And not only that also is going to bring changes in the way you do things. And that brings new complexities from an operational standpoint. So my question is, how are you addressing this with the introduction of five g. >>Dave, this is a fantastic question, and this is why we have spent me and Greg have spent tremendous amount of time to create continual. I'll start with the foundation first, back down. So we have been building this enterprise backbone, supporting what Wild Connexion as well as WiFi Connexion. We wanted to make sure that as private five G camps within enterprise, you don't have to rethink and reimagine your background is the common backbone that will support both WiFi WiFi six WiFi 60 as well as private five g. You rest assured that it is the same backbone that we have heard in the previous section on the Cap 90 that will also support a private key access. The second aspect of private five G is as you build any new technology into enterprise. Oftentimes we get into this trap to get to an outcome. We move fast and we create asylum. And then that silo operation creates a barriers to mainstream it. So upfront we have to think about not creating another silent and how we're doing it. Number one is a device that can connecting to WiFi network or a private five G network. You don't have to reimagine or rethink how I'm going to manage. The identity will create continue of the common identity across the WiFi access or five t access in the same environment. The second aspect of that is, how are we going to reach in all our staff are enterprise staff is well trained with WiFi technology and white technology. Now five G comes with tremendous amount of value and benefit, but it also comes with inherent technology complexity, learning problems. This is where our simple to consume simple to operate model of sass comes to play. That we're going to take all those complexity away. It is a cloud deliberate service enterprise don't have to go through this massive learning car. Adopting this technology last but not list on how you're going to manage your capital. Any new technology and enterprise, Oftentimes you need a huge amount of upfront investment to adopt the technology to get to the other side of getting the outcome. So again, our business model of SARS will allow Enterprise to adopt this new technology and pay as you go model to meet with enterprise needs. Finally, I also wanted to pass to break to touch a little bit more on how we are thinking about this common identity across any access in the enterprise. Greg to your >>So we we talk about it in two different ways. One is a lot of enterprises today use our identity and secure management platform. We call it Isis Co ice platform. And so years and years of policy and identities Excess service, radio service they use, uh, etcetera are plugged in already into our eyes. Right. So if you can share that with this private five years as a service, uh, infrastructure that Muslims been building, we think we'll be able to create that bridge because we're not forcing enterprises to create new identities, a new policy. So thats sort of step one to make it easier. Uh, you also talk through something where, in the case of a public five g network, for example, the It's very convenient because you take your phone out of your pocket and it's connected to the network, right? Was this for WiFi? You have to log into an S I D in your hotel or in your home and home. It's automatic, but that's that logging process that creates friction. And that's a problem, because then you can't be seamless. So we initiated what we call us open roaming, right? Like that's, uh, identity federation that we first created between identity owners. Could be carriers could be, um, anything that anyone who owns an identity and they will share with venues. And so if the sharing happens, then that Onboarding can be automatic and once on boarding is automatic, then it's easy to pass off between five and five G. And so that's again another way in which you can lower the adoption barriers because you share across public private G and WiFi networks. So these are two concrete examples of how we thought about lowering the barriers of adoption. As we enter into this heterogeneous >>world, >>I can't wait. Let's let's talk about how this thing scales in the go to market, what are the most likely or maybe preferred or obvious routes to market for private five g Francisco >>so they stay tuned when when they announce more about it. But I can also assure you that exposed to the spectrum is a challenge for many enterprises when it comes to cellular technology. In some countries, there are more spectrum accessible by enterprise. In many countries, that's not the case. So we have talked to very carefully that how do we bring this offer to the market? Partnering with many service providers and mobile operators, where in countries where we don't have direct access to the spectrum, our partnership with mobile operators that you will hear more about as we come to mobile world Congress is going to allow our enterprise to consume this technology even if they don't have the spectrum in places where the enterprise might have direct spectrum access. We'll also bring in our relativist providers to hide the complexity of the new technology on top of our cell services or a cloud deliberate services. This is the augmentation with the partnership with menaces providers and mobile operators that will ease this journey for enterprises are most important. Primitive in this journey is to keep it simple for enterprise. Make it intuitive and trust it from day one. >>Outstanding. Okay. Assume, Greg, Thanks so much. It's great to have you guys. I really appreciate your time. >>Thank you. Thank you. Mm mm.

>>Mm. Every CEO is trying to get hybrid, right? Most people, they've been working remotely for the better part of two years now, and we've spent a lot of time and thought on how to accommodate remote workers and providing tools to make them feel connected and more productive. We've also built remote and hybrid models into our hiring ethos, making it a feature, not a drawback. But what about the underlying infrastructure that powers hybrid work? How is that evolving to be as flexible, scalable and cost effective with the lowest latency possible? Recent survey data from Enterprise Technology Research shows that 56% of executives believe productivity continues to improve, with only 14% citing recent declines in productivity. 26% say it's holding steady. The question is, how do we maintain those positives and minimise the negatives? And what role does the network and underlying infrastructure play in evolving new work models? Welcome to the network powering hybrid work on the Cube, made possible by Cisco. My name is Dave Volonte, and I'll be your host today. In this programme, you're gonna hear from experts that are going to discuss and introduce new innovations that are specifically designed to energise and support hybrid work. My first guest is Lawrence Wang, who's the vice president of product management at Cisco. And we're going to dig into WiFi six e and what it all means to the future of work. Lawrence, welcome. Good to see you. >>Hey, great to be here. Dave. Thanks for having me. I'm excited to be here today. >>You bet. Okay. My first big question is what's the big rush? It feels like we were just talking about the shift from y 55 to WiFi six just a few years ago. What's going on there? >>Yeah. I mean, you're right, right. We assets at Cisco. We introduced our first WiFi six access points back in 2019, and one of the things that we've seen is a tremendous rate of adoption moving from WiFi five to WiFi six over the past couple of years. In fact, it's one of our fastest transitions that we've seen between wireless standards. And a lot of the drivers, you know, for that were really just about, you know, making sure that there's better WiFi experiences for, you know, people in the office making sure that they can support. You know more of that. Have you got a set of clients? Reduce the amount of congestion. And over time, what we've seen is that migration has been tremendous. But it also means that we're starting to reach that capacity where five gigahertz is starting to become more crowded and so many of our customers are looking at. Well, what can I actually do to continue to expand? You know that you know that traffic, the number of lanes that I can actually support for wireless traffic And for many of them, they're looking to WiFi succeed as the answer to help them do that simply because six gigahertz as part of that standard introduces a whole new spectrum or a whole new highway that we can get client devices as long as >>well, So it sounds like you're thinking about a different role for offices and campuses going forward. So what your listeners expect to see kind of in the in the near term and the midterm and even a long term near term when they get back into the office and in the long term, how do you see this playing out? >>Yeah, that's an interesting question, right When you think about this context of hybrid work, work is not a place that you go to, but it's really a place that you could be where ultimately you are trying to get work done. It really is reporting that quality of experience, no matter where you choose to work from. And, yes, while the campus is going to evolve and play a different role, it is a critical part of that hybrid work future. And the way I see it here is that the role of the campus is going to change over time. It's not going to be the same that we saw prior to two years ago, and I think for many of our customers about what does it mean to invest in that infrastructure for us to continue to adapt, to support the ways that their employees that are expected or want to work? And a big part of that is investing in infrastructure to support new ways of working? >>Well, you know, Lawrence, I mean, I've personally been lucky because we go to studio and I've been able to come into the office since the pandemic started, but I know a lot of people. They're really excited to get back, to work in person and face to face events and the like. And I know others that say, You know what? I'm moving and I'm always gonna work remotely. I'll never work for another company that forces me to go in the office again. So this sounds like a tall order for it organisations to accommodate that diversity. How do you think they will be able to plan for and manage all this new complexity? >>Yeah. I mean, I think the reality is, you know, talent. It doesn't know any zip codes, right? And I think one of the boons of being able to support a more distributed workforce is to be able to bring in great talent no matter where they're based out of. And I think for I t team. So I think the interesting thing will be what are the drivers to bring people back into the office right? There has to be a purpose that's more meaningful than simply It's a place that I go to every single day. You know, what are the tools and applications I bring in to help support collaboration, And I think important part of making this a great experience in the context of hybrid work is that you do have to make the office a meaningful place for employees to gather, but also making sure that as you connect people around the world as part of the global employee workforce that they still have an equitable experience. So for it teams, it is about thinking about how do I actually manage this infrastructure that's more distributed? But I start to invest in my central campuses and at the same time making sure that I have great quality experiences for everyone. Unified security policies, visibility across all the clients and applications. But there's also increasing pressure from their its core constituency. We know that people are asking more of it. They want them to support you, use cases like safe return office that they want to help you contributor to global corporate initiatives like driving towards zero greenhouse gas emissions. So any number of these activities or initiatives is putting more pressure on teams. >>Interesting. I mean, so I gotta ask you, please don't hate me for this question. But was this just luck on Cisco's part that you got solutions ready for this sort of hybrid work model so quickly. In other words, was it something that you were maybe planning that was going to take years for the market to be ready for And it just got compressed because of the pandemic? Or was this architecture that allows you to be flexible? How did you land here and what appears to be a pretty strong position? >>Yeah, I mean, at Cisco, I think one of the things that we think about is, you know, it's always amazing when you look back at something and then you write the story. But I think if we're being honest with ourselves, if you look at what happened from where we were two years ago to where we are today, including our competitors and customers, I think that no one could have predicted the world that we're operating and living in. And so for us, the question becomes, How did we help our customers support this transition? And ultimately it's about investing in architectures and platforms that are flexible, that allows our customers support use cases that they were thinking of, as well as ones that they never anticipated, and I think that's really the exciting thing about what we've been doing here as part of our hybrid work investments now areas that, you know, I think we double down on and in some ways accelerated because of this. When I think about you know what our customers care about when they start bringing people back into the office. It is about some of these emerging use cases, whether it's more dynamic, way finding, be able to understand the density or the air quality of a given environment. And these are some of the technologies that we have embedded in some of our new, you know, WiFi 60 access points along with our management infrastructure era. So I think that it gives our customers and partners a lot more flexibility than what they had before to really adapt to the changing needs of today and even beyond. >>Well, that's something we've certainly learned throughout the pandemic. Is the ability to be flexible is fundamental? I gotta ask you, what's your preferred mode of work? You go back into the office, you're gonna stay remote. >>Great question. You know, I have come to appreciate, you know, working from home. You know, over the past couple years, got to spend a little more time with my kids at lunch. But I will say I am looking forward to the day when I can have the voice of being back in the office a few days a week as well as I continue to be remote as well as continued to visit my customers and partners all over this great country in the world. So looking forward to that, >>so you're a true hybrid. I guess I'm a hybrid, too. I like being in the office, but I'm travelling a lot when the world returns to the new abnormal anyway. Large. Thanks so much for kicking off the programme with me. Now in a minute, we're going to dig into the core of the network and understand the role it plays in supporting new and flexible work models. You're watching the network powering hybrid work made possible by Cisco on the Cube, your leader in global enterprise tech coverage. Mhm. Yeah,

>>Mhm. Hey there. Welcome to the cubes coverage of Splunk dot com. 21. I'm lisa martin. I've got a new guest joining me on the cube for the first time please welcome 20 pierce the senior manager of cybersecurity at the Y 20. Welcome to the program. >>Hi, glad to be here. >>So your linked in profile. I wanted to ask you about this. It states that you are delivering an evidence based approach to cybersecurity. What does that mean? An evidence based approach? And how are you and spunk helping to deliver this approach? >>Yeah. And I'd like to call it like the out case outcome based the price basically you start with what you're trying to accomplish and work with backwards. A lot of people say I've got a problem and then they go try to buy a tool or whatever to go fix the problem. I go in and I'm like all right, I got a problem. Let me figure out what's realistically I can use in the environment. So it's just basically working back so you have, you know, a breach. What if I what are all the different things that I knew to leverage to meet the controls for that breach. Right? And so um think of mitre in a way as a layered way of looking things um and the full defense and depth. So that's kind of my approach, I go when I figure out what the problem is and I answer the question and I used to do that because funk is able to give me a big data to everything. Got a guy so I like to be able to pull in all the different data types that I need to answer our questions, um, to do that. Right. And so whether it's a vulnerability management, patching your networking a good, a good example of this, like most common hacks in the world go after known vulnerabilities, right? And we get kind of caught up in all that. Um, one of the things we like to do here do, why is like we like to combine what's happening in the network. So the threat landscape in which is the network guys, the vulnerability guys who are scanning the data and then actually the patching, who is, who is actually, you know, mitigating the problem putting all those into one screen has really helped people with their risk rating. >>Talk to me a little bit about some of the changes, we've seen massive changes in the threat landscape in cybersecurity in the last year and a half during the pandemic. We've seen massive increase in ransomware. DDoS attacks, ransomware becoming a household word, the executive order that just came down a few months ago. What are some of the things that you've seen? Have you seen the acceleration of organizations coming to help? We know that it's not a matter of if we get attacked. It's when how are you, how are you seeing the last 18 months influence what you're doing. >>Oh man, it's been quite a crazy, right? And so um, by trade, I'm a instant responder, you know, uh high level investigator and possible solutions architect. So I, I get called in a lot for those kind of things. It has been kind of nuts. But you know, one of the things I always tell them when it started understanding what your threat landscaping is, um, and identify your key cyber terrain. Unfortunately most, you know, most companies as they grow, they get really big, they don't really do that. So they don't, they miss the consolidation point, right? I always say, hey, you know, if you're, if you're going to do this, if you say you have a ransomware attack, the first thing you can do is, you know, there's so many different controls that you can do to stop that you really need to know where it is and ejecting and then you can isolate if you need to um, what we're seeing in the companies. They, because they don't all have full coverage, right? And they expect their endpoint protections to actually do its job, you know, and sometimes that's, you know, don't get me wrong, there are some amazing endpoint protections out there, but you really need to be able to log it, you need to know what it looks like and you need to know where it is. So if you need a in case of a ransomware attack as it spreads through the network, you're able to isolate it and rewrite it to like, I like to call it a black hole the land and just reroute it so I can isolate it and then I can go after it. Um instead of trying to try to do every endpoint at a time because you'll get you'll get whacked >>definitely. So talk to me about working and partnering with Splunk and it's full security stuff. How does that, how is that a differentiator for you and your rule? >>Okay. So one of the things that we do here any why is we can find simmons sores one combined offering. Right? So we we try to bring the data in, we operationalize it and then we try to do something with it, right? We we find that. And then if you really think about that in a situation where the spunk products, it's the spunk or funky s and then phantom, right? And so that's the automation play. So we try to combine all those into one combined offering. So that when when bad things happen where we make a decision, we say all right, So, hey, um what we're seeing in the industry is like a lot of times people spend so much time hunting the known to to forget about the unknown. Think about the target. Hack a couple of years ago. Um the oil and gas attack just recently, you know, they miss those core things. So we try to say all right, well let's automate a lot of that known stuff so that the incident responders can focus on the unknown. And so when you combine all three of those products, you get a pretty good security staff >>when you say automating The known, is that at all in any way like helping companies get back to basics. I've been hearing a lot in the last 18 months that some from a data protection perspective and from a ransomware attack perspective. So it's it's when not if but are you saying that companies are are sort of skipping past the basics where security is concerned? Yeah, >>Well, it's I don't say it's skipping past the basics. Right? I think that sometimes people get caught up in the definitions of what it is. Right? So there's there's so many, there's so many fair more shop there. Right? So like I'm a big fan of your trust. Um a lot of instant responded to using minor, I use minor for that as as it retains the instant response. Some people like to use high trust and I think a lot of what happens is they get lost in the confusion of all these different frameworks. Right? I like to go back to basics. I've been doing cyber for Oh, oh my oh my gosh, about 20 plus years. Right. Um I'm an active hacker. I like this is what I do. I like to call a defense in depth. Right? So when you're when you're doing that, if you follow the defense and depth Satur, it doesn't matter what framework you have, you can actually go back and you can Fix that problem. Right? So going back in the automation of unknown to an unknown, we know, and IOC is 100% now, you can say IOC it's like a hash, right? So when a bad thing happens like an exploit, first thing we try to do is we try to grab that hash and then we try to build a roll around it to stop that hash from spreading and going anywhere else. That's a We know 100% of it's bad. Now can exploits change their hash. Absolute. And it happens all the time, but for that Moment in time that hash is 100%. And so we try to say, hey look, you know, we got an endpoint protection but also why don't we use automation to block it at the boundary or why don't we keep it from doing lateral movement? Why don't we why don't we activate it from a defense and depth. So you have your network. Um I like to say, hey look you have your egress ingress and your lateral movement. So if you understand all those three fact factors, you can automate the control so that it doesn't spread, you know, you had mentioned ransomware, it's been really huge, right? And everybody goes, oh well, you know, if we do zero try zero trust, talks about, you know, segmentation a whole lot and then a segmentation is usually important. It won't stop everything but it will do a good job being able to you'll ever swung we actually pull that in and we say hey you know from and why are we take all that network? And we try to put it in a single pane of glass so that we can see everything. And then once we're able to see it, once we get a good robust data set and understand that operations were able to go in and automate it and so if I can go in and say hey look all these hashes are bad. Yeah I'm not going to rely on my end point, I'm going to put another control in place. So at the end point misses it, I have another control that will actually layer it and prevent it from spreading. >>Which is absolutely critical. Talk to me about some of the outcomes that Ey and Splunk are delivering to the end user customers. Everyone's always talking about it's all about outcomes. What are some of those? >>Yeah so we have um we really embraced like the data to everything right? So I I kind of have this opinion of like uh you know everything's data so everything needs to be secured right? Uh the people who missed that tend to get whacked pretty quickly. Um So what I like to do is I'm like all right so you know like IOT is huge out there right now O. T. Is doing it. So some of the things that we've done is like from a health care perspective um We've done we've combined I. O. T. And I. T. Into a commonality solution leveraging like network simple things like pulling in from the wind, pulling in um understanding what those Mac addresses are so that you can actually do like a workplace analytics around um say R. F. I. D. Tagging right? So you know where your people are at? Um Here we also do like a call a sock in a box where we put that put everything together that every like a from a tiered perspective like a tier one tier two analysts. You know what is that they need to do to mitigate mitigate observe something, What is the investigator need? Right? So we try to simplify those conversations so that you know exactly around like a threat hunting as well like threat hunter an investigator, they're totally different roles, right? So they need to be separated. We also like tie in like the um what is it? I really hate uh like power point. I'm not a big power point guy right? So I really like to be able to give the says oh he needs to understand what risk is, right? So we try to automated so we can get to that too. He can pull up his phone and pull up his punk app and he knows at any given time what his risk rating of his company, right? So we try to combine all those in. Like again, you know there is um we do stuff around Blockchain supply chain. You know, it doesn't really matter if it's a data analytics tool. You know a lot of people look at Funk as a sim. I don't just like look at it that way. I look at as a data analytics tool that does sim. It's just one of the functions this does. If you start understanding data and all the different things that data can do, then you need to go in and you can use Funk to basically answer those questions so that you can start putting in a control set. >>What what's the differentiated value that Ey and Splunk bring together to customers. What really sets this partnership and what it delivers apart. >>Well I'm I'm I'm biased on that right? Because I run the North America 17 for you like for consulting. So I would say that those two things is innovation and time to value. Right? So for let's start with innovation for a minute because Funk is so customizable right? Because it pretty much can integrate with just two. Anything we're able to go very fast, take data in and do something with it and operationalize. It doesn't matter who the customer is is they're going to give us a question. We'll break it all the way down and we'll understand what you're going to answer A good example that is like we were doing stuff around P. C. I. Compliance. The checklist. You know the financial sector, they get a huge amount of audits, right? Especially around PC. I. So we took all the Pc. I checklist and we said harry, what can we, what can we answer those questions? And so we built a dashboard that actually sends out a report to internal audit and we call it compliance over time, right? It's looking at data in a different perspective to answer a question. Now the other thing is that we like, we try to do here is, you know, with the, as we do is Funk and funk helps us with this, right? We have a great relationship with them is um, basically, oh I have a, I lost my train of thought there for me. So uh, innovations time to value, right? So from time to value what we do is we used to say, hey look, we have a lot of stuff in our lab. But one of the things I don't like to do is I don't like to um, go to clients and say, hey look, we were going to build this for the first time. I like to say, hey look, here's these questions in the industry. Get ahead of the question and go build in our labs so that when we when we actually get on site, our time to value is not in months. You know, we can begin weeks because we already have a huge repository of um use cases now those every use case is actually tied into an automation play. And so when we say that we say hey look here's everything is flowing, let's do this, let's go answer that question and let's go automate it and you let's make a decision where where we want to automate and where do we want a human interaction. Mhm. >>Talk to me about what's next for the partnership in terms of the future, what what can you tell us where E Y. And Splunk are going together? >>So we've been partying around um I think our next things that we're really looking at is A I um we're really getting kind of into that as well as A R. And D. R. Technology. Right? So um especially around like I'm looking at like the energy companies in the financial banking and one of the things I would love to do is like um go into you know a bank A. T. M. Right? And right now it takes somebody actually has to plug into that and to do a diagnostic on it. I would love to be able to get to a point where you can just take your camera scan the QR code on the on the device and then pull up an A. R. And it runs all the diagnostics on the device as its there. Another one is like the infrastructure um instead of actually going out, plugging into like say a solar panel going out pulling out of the tablet just scanning the solar panels and it tells you if it's good or bad and that's kind of the next step that we're trying to do. We're trying to really take that uh and dated everything and just kind of turn it on its end um like and you've got to remember everything is data nowadays, right? It's not the old days where you know, things are moving around and everything is in the file folders, it's gone right? Everything is data. So everything is security, right? And we know the first thing is we need to know what our threat landscape is. We need to know what that is and we need to apply that. All right. So if we can simplify answering questions, that's so much better. And one of the things I like about flunked is it scales really well, right? And I've looked at some of these fetters and don't get me wrong, I mean everybody has their place. The one thing I like about spunk is it doesn't mean it literally scales really well. So the more data you can get into it, it actually does better. Right? Um and how you do it now, that's just our approach. That's the next steps that we're really looking at from a technology standpoint, >>exciting stuff, Tony thank you for joining me sharing what ey and Splunk are doing together. Some of the unique use cases that you're helping to solve for customers and some of the things that you're excited about. We appreciate your time on your information. >>No, this is fun. You know, like I said, I'm a big fan. I even wore my spunk shirt just for this meeting. >>Fantastic. You're on brand well, Tony. Thank you. Again. We appreciate your time. >>All right. Thank you. You have a wonderful day. >>Thanks you as well for Tony Pierce. I'm Lisa Martin. You're watching the cubes coverage of splunk.com 21. Thanks for watching, >>enjoy. Bye bye mm. Mm hmm.

>> From the theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> Well, it looks like hybrid cloud is finally here. We've seen a decade of posturing, marchitecture, slideware and narrow examples of hybrid cloud, but there's little question that the definition of cloud is expanding to include on-premises workloads in hybrid models. Now depending on which numbers you choose to represent IT spending, public cloud only accounts for actually less than 5% of the total pie. So the big question is, how will this now evolve? Customers want control, they want governance, they want security, flexibility and a feature-rich set of services to build their digital businesses. It's unlikely that they can buy all that, so they're going to have to build it with partners, specifically vendors, SI's, consultancies and their own developers. The tug of war to win the new cloud day has finally started in earnest between the hyperscalers and the largest enterprise tech companies in the world. Hello and welcome to this week's Wikibon CUBE insights, powered by ETR. In this Breaking Analysis, we'll walk you through how we see the battle for hybrid cloud, how we got here, where we are and where it's headed. First, I want to go back to 2009, in a blog post by a man named Chuck Hollis. Chuck Hollis, at the time, was a CTO and marketing guru inside of EMC who, remember, owned VMware. Chuck was kind of this hybrid, multi-tool player, pun intended. EMC at the time had a big stake, a lot at stake, as the ascendancy of AWS was threatening the historical models, which had defined enterprise IT. Now around that time, NIST published its first draft of a cloud computing definition which, as I recall, included language, something to the effect of accessing remote services over the public network, i.e., public IP networks. Now, NIST has essentially or since evolved that definition, but the original draft was very favorable to the public cloud. And the vendor community, the traditional vendor community, said hang on, we're in this game too. So that was 2009 when Chuck Hollis published this slide. He termed it Private Cloud, a term which he saw buried inside of a Gartner research post or research note that was not really fleshed out and defined. The idea was pretty compelling. The definition of cloud centered on control, where you, as the customer, had on-prem workloads that could span public and on-prem clouds, if you will, with federated security and a data plan that spanned the states. Essentially, you had an internal and an external cloud with a single point of control. This is basically what the hybrid cloud vision has become. An abstraction layer that spans on-prem and public clouds and we can extend that across clouds and out to the edge, where a customer has a single point of control and federated governance and security. Now we know this is still aspirational, but we're now seeing vendor offerings that put forth this promise and a roadmap to get there from different points of view, that we're going to talk about today. The NIST definition now reads cloud computing is a model for enabling ubiquitous, convenient on-demand network access to a shared pool of configurable computing resources, e.g., network server storage, applications and services, that can be rapidly provisioned and released with minimal management effort or service provider interaction. So there you have it, that is inclusive of on-prem, but it took the industry a decade plus to actually get where we are today. And they did so by essentially going to school with the public cloud offerings. Now in 2018, AWS announced Outposts and that was another wake up call to the on-prem community. Externally, they pointed to the validation that hybrid cloud was real. Hey, AWS is doing it so clearly they've capitulated, but most on-prem vendors at the time didn't have a coherent offering for hybrid, but the point is the on-prem vendors responded as they saw AWS moving past the demilitarized zone into enemy lines. And here's what the competitive landscape of hybrid offerings looks like today. All three US-based hyperscalers have an offering or multiple offerings in various forms, Outposts from Amazon and other services that they offer, Google Anthos and Azure Arc, they're all so prominent, but the real action today is coming from the on-prem vendors. Every major company has an offering. Now most of these stemmed from services-led and finance-led initiatives, but they're evolving to true Azure Service models. HPE GreenLake is prominent and the company's CEO, Antonio Neri, is putting the whole company behind Azure Service. HPE claims to be the first, it uses that in its marketing, with such an Azure Service offering, but actually Oracle was their first with Cloud@Customer. You know, possibly Microsoft could make a claim to being early as well, but it really doesn't matter. Let's see, Dell has responded with Apex and is going hard after this opportunity. Cisco has Cisco Plus and Lenovo has TruScale. IBM also has a long services and finance-led history and has announced pockets of Azure Service in areas like storage. And Pure Storage is an example that we chose of a segment player, of course within storage, that has a strong Azure Service offering, and there are others like that. So the landscape is getting very busy. And so, let's break this down a bit. AWS is bringing its programmable infrastructure model and its own hardware to what it calls the edge. And it looks at on-prem data centers as just another edge node. So that's how they're de-positioning the on-prem crowd, but the fact is, when you really look at what Outposts can do today, it's limited, but AWS will move quickly so expect a continued rapid evolution of their model and the services that are supported on Outposts. Azure gets its hardware from partners and has relationships with virtually everyone that matters. Anthos is, as well, a software layer and Google created Kubernetes as the great equalizer in cloud. And it was a nice open source gift to the industry and has obviously taken off. So the cloud guys have the advantage of owning a cloud. The pure on-prem players, they don't, but the on-prem crowd has rich stacks, much richer and more mature in a lot of areas, as it relates to supporting on-premises workloads and much more so than the cloud players, but they don't have mature cloud stacks. They're kind of just getting started with things like subscription billing and API-based microservices offerings. They got to figure out Salesforce compensation and just the overall Azure service mentality versus the historical product box mentality, and that takes time. And they're each coming at this from their respective different points of view and points of strength. HPE is doing a very good job of marketing and go-to market. It probably has the cleanest model, enabled by the company's split from HP, but it has some gaps that it's needed to fill and it's doing so through acquisitions. Ezmeral, for example, is it's new data play. It just bought Zerto to facilitate backup as a service. And it's expanded partnerships to fill gaps in the portfolio. Some partnerships, which they couldn't do before because it created conflicts inside of HPE or HP. Dell is all about the portfolio, the breadth of the portfolio, the go-to-market prowess and its supply chain advantage. It's very serious about Azure Service with Apex and it's driving hard to win that day. Cisco comes at this from a huge portfolio and of course, a point of strength and networking, which maybe is a bit tougher to offer as a service, but Cisco has a large and fast growing subscription business in collaborations, security and other areas, so it's cloud-like in that regard. And Oracle, of course, has the huge advantage of an extremely rich functional stack and it owns a cloud, which has dramatically improved in the past few years, but Oracle is narrow to the red stack, at least today. Oracle, if it wanted to, we think, could dominate the database cloud, it could be the database cloud, especially if it decided to open its cloud to competitive database offerings and run them in the Oracle cloud. Hmm. Wonder if Oracle will ever move in that direction. Now a big part of this shift is the appeal of OPEX versus CAPEX. Let's take a look at some ETR data that digs a bit deeper into this topic. This data is from an August ETR drill down, asking CIOs and IT buyers how their budgets are split between OPEX and CAPEX. The mid point of the yellow line shows where we are today, 57% OPEX, expecting to grow to 63% one year from now. That's not a huge difference, there's not a huge difference when you drill into global 2000, which kind of surprised me. I thought global 2000 would be heavier CAPEX, but they seem to be accelerating the shift to OPEX slightly faster than the overall base, but not really in a meaningful way. So I didn't really discern big differences there. Now, when you dig further into industries and look at subscription versus consumption models for OPEX, you see about 60/40 favoring subscription models, with most industry slowly moving toward consumption or usage based models over time. There are a couple of outliers, but generally speaking, that's the trend. What's perhaps more interesting is when you drill into subscription versus usage based models by product area, and that's what this chart shows. It shows by tech segment, the percent subscription, that's the blue, versus consumption or usage based, that's the gray bars, yellow being indifferent or maybe it's I don't know. What stands out are two areas that are more usage heavy, consumption heavy. That's database, data warehousing, and IS. So database is surely weighted by companies like Snowflake and offerings like Redshift and other cloud databases from Azure and Google and other managed services, but the IS piece, while not surprising, is, we think, relevant because most of the legacy vendor Azure Service offerings are borrowing from a SaaS-oriented subscription model with a hardware twist. In other words, as a customer, you're committing to a term and a minimum spend over the life of that term. You're locked in for a year or three years, whatever it is, to account for the hardware and headroom the vendor has to install because they want to allow you to increase your usage. So that's the usage based model. See, you're then paying by the drink for that consumption above that minimum threshold. So it's a hybrid subscription consumption model, which is actually quite interesting. And we've been saying, what would really be cool is if one of the on-prem penguins on the iceberg would actually jump in and offer a true consumption model right out of the box, as a disruptive move to the industry and to the cloud players, and take that risk. And I think that might happen once they feel comfortable with the financial model and they have nailed the product market fit, but right now, the model is what it is. And even AWS without post requires a threshold and a minimum commitment. So we'd love to see someone take that chance and offer true cloud consumption pricing to facilitate more experimentation and lower risk for the customer entry points. Now let's take a look at some of these players and see what kind of spending momentum they have. This is our popular XY chart-view that plots net score or spending velocity on the x-axis and market share or pervasiveness in the data set on the... Oh, sorry, net score or spending momentum on the y-axis and pervasiveness or market share on the x-axis. Now this is cut by cloud computing vendors, as defined by the customers responding. There were nearly 1500 respondents in the ETR survey, so a couple of points here. Note the red line is the elevated line. In other words, anything above that is considered really robust momentum. And no surprise, Azure, AWS and Google are above that line. Azure and AWS always battle it out for top share of voice in the x-axis in this survey. Now this, remember, is the July survey, but ETR, they gave me a sneak peek at the October results that they're going to be releasing in the coming week and Dell cloud and VMware cloud, which is VCF and maybe some other components, not VMware cloud and AWS, that's a separate beast, but those two are moving up in the y-axis. So they're demonstrating spending momentum. IBM is moving down and Oracle is at a respectable 20% on the y-axis. Now, interestingly, HPE and Lenovo don't show up in the cloud taxonomy, in that cloud cut, and neither does Cisco. I believe I'm correct in that this is an open-ended question, i.e., who are your cloud suppliers? So the customers are not resonating with that messaging yet, but I'm going to double check on that. Now to widen the aperture a bit, we said let's do a cut of the on-prem and cloud players within cloud accounts, so we can include HPE and Cisco and see how they're doing inside of cloud accounts. So that's what this chart does. It's a filter on 975 customers who identify themselves as cloud accounts. So here we were able to add in Cisco and HPE. Now, Lenovo still doesn't show up on the data. It shows up in laptops and desktops, but not as prominent in the enterprise, not prominent at all, but HPE Ezmeral did show up and it's moving forward in the October survey, again, part of the sneak peek. Ezmeral is HPE's data platform that they've introduced, combining the assets of MapR, BlueData and some other organic development. Now, as you can see, HPE and Cisco, they show up on the chart, as I said, and you can see the rope in the tug of war is starting to get a little bit more taut. The cloud guys have momentum and big account presence, but the on-prem folks also have big footprints, rich stacks and many have strong services arms, and a lot of customer affinity. So let's wrap with some comments about how this will shake out and what's some of the markers we can watch. Now, the first thing I'll say is we're starting to hear the right language come out of the vendor community. The idea that they're investing in a layer to abstract the underlying complexity of the clouds and on-prem infrastructure and turning the world into, essentially, a programmable interface to resources. The question is, what about giving access through that layer to underlying primitives in the public cloud? VMware has been very clear on this. They will facilitate that access. I believe Red Hat as well. So watch to the degree in which the large on-prem players are enabling that access for developers. We believe this is the right direction overall, but it's also very hard and it's going to require lots of resources and R & D. I would say at this point that each company has its respective strengths and weaknesses. I see HPE mostly focused today on making its on-prem offerings work like a cloud, whereas some of the others, VMware, Dell and Cisco, are stressing to a greater degree, in my view, enabling multi-cloud and edge connections, cross connections. Not that HPE isn't open to that when you ask them about it, but its marketing is more on-prem leaning, in my opinion. Now all of the traditional vendors, in my view, are still defensive about the cloud, although I would say much less so each day. Increasingly, they look at the public cloud as an opportunity to build value on top of that abstraction layer, if you will. As I said earlier, these on-prem guys, they all have ways to go. They're in the early stages of figuring out what a cloud operating model looks like, how it works, what services to offer, how to pay sellers and partners, but the public cloud vendors, they're miles ahead in that regard, but at the same time, they're navigating into on-prem territory. And they're very immature, in most cases. So how do they service all this stuff? How do they establish partnerships and so forth? And how do they build stacks on prem that are as rich as they are in the cloud? And what's their motivation to do that? Are they getting pulled, digging their heels in? Or are they really serious about it? Now, in some respects, Oracle is in the best position here in terms of hybrid maturity, but again, it's narrowly focused on the Red Stack. I would say the same for Pure Storage, more mature as a service, but narrowly focused, of course, on storage. Let's talk marketplace and ecosystems. One of the hallmarks of public clouds is optionality of tooling. Just all you do is go to the AWS Marketplace and you'll see what I mean. It's got this endless bevy of choices. It's got one of everything in there and you can buy directly from your AWS Console. So watch how the hybrid cloud plays out in terms of partner inclusion and ease of doing business, that's another sign of maturity. Let's talk developers and edge. This is by far the most important and biggest hole in the hybrid portfolios, outside the public cloud players. If you're going to build infrastructure as code, who do you expect to code it? How are the on-prem players cultivating developer communities? IBM paid 34 billion to buy its way in. Actually, in today's valuation terms, you might say that's looking like a good play, but still, that cash outlay is equal to one third of IBM's revenue. So big, big bet on OpenShift, but IBM's infrastructure strategy is fragmented and its cloud business, as IBM reports in its financial statements, is a services-heavy, kitchen sink set of offerings. It's very confusing. So they got to still do some clean up there, but they're serious about the architectural battle for hybrid cloud, as Arvind Krishna calls it. Now VMware, by cobbling together the misfit developer toys of the remnants from the EMC Federation, including Pivotal, is trying to get there. You know, but when you talk to customers, they're still not all in on VMware's developer affinity. Now Cisco has DevNet, but that's basically CCIE's and other trained networking engineers learning to code in languages like Python. It's not necessarily true devs, although they're upskilling. It's a start and they're investing, Cisco, that is, investing in the community, leveraging their champions, and I would say Dell could do the same with, for example, the numerous EMC storage admins that are out there. Now Oracle bought Sun to get Java, and that's a large community of developers, but even so, when you compare AWS and Microsoft ecosystems to the others, it's not even close in terms of developer affinity. So lots of work to be done there. One other point is Pure's acquisition of Portworx, again, while narrowly focused, is a good move and instructive of the changes going on in infrastructure. Now how does this all relate to the edge? Well, I'm not going to talk much about that today, but suffice to say, developers, in our view, will win the edge. And right now, they're coding in the cloud. Now they're often coding in the cloud and moving work on prem, wrapping them in containers, but watch how sticky that model is for the respective players. The other thing to watch is cadence of offerings. Another hallmark of cloud is a rapid expansion of features. The public cloud players don't appear to be slowing down and the on-prem folks seem to be accelerating. I've been watching HPE and GreenLake and their cadence of offerings, and watch how quickly the newbies of Azure Service can add functionality, I have no doubt Dell is going to be right there as well, as is Cisco and others. Also pay attention to financial metrics, watch how Azure Service impacts the income statements and how the companies deal with that because as you shift to deferred revenue models, it's going to hurt profitability. And I'm not worried about that at all because it won't hurt cashflow, or at least it shouldn't. As long as the companies communicate to Wall Street and they're transparent, i.e., they don't shift reporting definitions every year and a half or two years, but watch for metrics around retention and churn, RPO or Remaining Performance Obligations, billing versus bookings, increased average contract values, cohort selling, the impact on both gross margin and operating margin. These are the things you watch with SaaS companies and essentially, these big hardware players are becoming Azure Service slash SaaS companies. These are going to be the key indicators of success and the proof in the pudding of the transition to Azure Service. It should be positive for these companies, assuming they get the product market fit right, and can create a flywheel effect with their respective ecosystems and partner channels. Now I'm sure you can think of other important factors to watch, but I'm going to leave it here for now. Remember these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis podcast and please subscribe, check out ETR's website at etr.plus. We also publish a full report every week on wikibon.com and siliconangle.com. You can get in touch with me, email david.vellante@siliconangle.com or you can DM me @dvellante. You can comment on our LinkedIn posts. This is Dave Vellante for theCUBE Insights powered by ETR. Have a great week, everybody, stay safe, be well. And we'll see you next time. (soft music)

>>From the Bellagio hotel in Las Vegas, it's the cube covering UI path forward for brought to you by >>Welcome to the cubes coverage of UI path forward for live from Las Vegas. We're here at the Bellagio. Lisa Martin, with Dave a long time, very excited to have in-person events back ish. I'll say we're going to be talking about automation as a boardroom imperative. We have two guests joining us here, James Matras here consulting principal. America's intelligent automation leader at UI and Irv. Dennis retired EA partner, and former CFO of HUD gentlemen. Welcome to the program. Exciting topic automation as a boardroom imperative, James says COO and start with you. How do you discuss the value of automation as being a key component and driver of transformation? >>That's a great question. I think what we've seen in the last couple of years is the evolution of what automation used to be. Two is going nine. And we've seen the shift from what we call generation one, which is very RPA centric type automation to more generation two, which is the combined integration of multiple technologies. It can target an intern process and it's quite important that you understand the pivotal shift because it's not enabling us to move from a task micro top agenda to a macro agenda actually impacts an organization at a strategic level. The ability to be able to look at processes more deeply to automate them in an end to end process collectively and use these different technologies in a synergistic manner truly becomes powerful because it shifts the narrative from a micro process agenda into more systemic area. >>So gen zero is an Emmanuel gen one is RPA point tools that individual maybe getting their personal productivity out. And then now you're saying gen three is across the enterprise. Where are we in terms of, you know, take your experience from your practical experience? Where do you think the world is? It's like probably between zero and one still. Right. But the advanced folks of thinking about gen three, w what's your, >>Yeah, it's a great question. And, um, when you and I, I can do the comparison being private and public sector on this because I was 37 years with E Y then went into retirement and CFL at HUD CFO. Ed was, was a HUD was nowhere. They had to just do all the intelligence digitalization, um, throughout, uh, from scratch. The private sector is probably five or six years ahead of them. But when you think about James talks about the gen one, two and three, the private sector is probably somewhere between two and three. And I know we're talking about the board in this conversation. Um, boards probably have one and two on their radar. Some boards may have three, some may not, but that's where the real strategic focus for boards needs to be is looking forward and, and getting ahead. But I think from a public sector standpoint, lot to go private sector, more to go as well. But, uh, there's a, there's a bit of a gap, but the public sector is probably only about three or four years behind the private sector >>To be okay. Let's look at the numbers, look at, look at the progress for the quarter. And now it's like discussion on cyber discussion on digital discussion on automated issue. It really changed the narrative over the last decade. >>Yeah, I think when you think of boards today, the lots of conversation on cyber that that conversation has been around for a while. A lot of conversation on ESG today, that conversation is getting, getting very popular. But I think when you think of next three, a Jen talks that bear James talks about, um, that's got to start elevating itself if it's not within the boardroom right now, because that will be the future of the company. And the way I think of it from a board's conversation is if a company doesn't think of themselves as a technology company in all aspects, no matter what you do, you are a technology company or you need to be. And if you're not thinking along that way, you're gonna, you're gonna lose market share and you're going to start falling behind your competitors. >>Well, and how much acceleration did the pandemic bring to just that organizations that weren't digital forward last year are probably gone? >>I think it certainly has shifted quite a lot. There's been a drive, the relevance of technology and hard plays for us in the modern workforce in the modern workplace has fundamentally changed the pandemic. We reimagine how we do things. Technology has progressed in itself significantly, and that made a big difference for, for all the environments as a result of that. So certainly is one of the byproducts of the pandemic has been certainly a good thing for everybody. >>Where does automation fit in the board? Virginia? You've got compensation committee. You've probably, I mean, there's somebody in charge of cyber. You got ESG now there's automation part of a broader digital agenda. Where's what's the right word. >>You know, I, I would personally put it in a enterprise risk management from a standpoint that if you're not focused on it, it's going to be a risk to the enterprise. And, um, when you think of automation and intelligent automation and RPA, uh, I think boards have a pretty good sense of how you interface with your customers and your vendors. I think a big push ought to be looking internally at your own infrastructure. You know, what are you, what are you doing in the HR space? What are you doing in a financial statement, close process? What are you doing your procurement process? I suspect there's still a lot of very routine transactions and processing within those, that infrastructure that if you just apply some RPA artificial intelligence, that data extraction techniques, you can probably eliminate a lot of man hours from the routine stuff. And, and the many man hours is probably not the right way to think of it. You could elevate people's work from being pushing numbers around to being data analyzers. And that's where the excitement is for people to see. >>It's not how it's viewed at organizations. We're not eliminating hours. Well focusing folks on much more strategic down at a test. >>Yes. I would say that that's exactly right now in the private sector, you're always going to have the efficiency play and profitability. So there will be an element of that. I know when at HUD we're, we're focused, we were not focused on eliminating hours because we needed people and we focused on creating efficiencies within the space and having people convert from, again, being Trent routine transactions, to being data analyzers and made the jobs, I'm sure. Fund for them as well. I mean, this is a lot of fun stuff. And, and if, uh, uh, companies need to be pushing this down through their entire infrastructure, not just dealing with our customers and the third parties that they deal with >>Catalyst or have been public sector. So you mentioned they may be five or six years behind, but I've seen certain public sector organizations really lean in, they learn from, from the private sector. And then even when you think about some of the military, how advanced they are absolutely. You know, the private could learn from them and if they could open it up. But >>So, yeah, I think that's, that's well said I was in this, you know, the that's the civilian part with, with the housing and urban development. I think the catalyst is, uh, bringing the expertise in, uh, I know when I, when I came, I went to HUD to elevate their financial infrastructure. It was, it was probably the worst of the cabinet agency. The financials were a mess. There was no, there was a, uh, there was not a clean audit opinion for eight years. And I was there to fix that and we fixed it through digitalization and digital transformation, as well as a financial transformation. The catalyst is just creating the education, letting people know what is, what, what technology can do. You don't have to be a programmer, but it's like driving a car. Anybody can drive a car, but we can't mechanic, you know, work as a mechanic on it. >>So I think it's creating education, letting people know what it can do. And at HUD, for example, we did a very simple, I was telling James earlier, we did a very simple RPA project on an, an, a financial statement, close process. It was 2,600 hours, six months. Once we implemented the RPA, brought that down to 70 hours, two weeks, people's eyes exploded with it. And then all of a sudden, I said, I want everyone to go back and come back with, with any manual process, any routine process that can convert to an RPA. And I got a list of a hundred, then it came then became trying to slow everything down. We're not going to do it overnight. Yeah, exactly. >>So, but it was self-funding. It was >>Self-funded. Yes. >>And, and how do you take that message to customers that it could be self-funding how how's that resonating >>Very well. And I think it was important. I always like to say, it's a point of differentiation because you look at, uh, mentioned earlier that organizations are basically technology companies. That's what they are. But now if you look across that we no longer compete at the ERP level without got SAP, Oracle, it's not a point of differentiation. We don't compete the application layer where they've got service. Now, black line, how we use them is helpful. We competed the digital layer and with automation is a major component of that. That's where your differentiation takes place. Now, if you have a point of differentiation, that is self-funding, it fundamentally changes the game. And that's why it's so important for boards to understand this, because that risk management, if you've not doing it, somebody is getting ahead of the game much faster than you are. >>Yeah. Yeah. You mentioned ERP and it, and it triggered something in my mind. Cause I, I said this 10 years ago about data. If in the nineties, you, you couldn't have picked SAP necessarily as the winner of ERP. But if you could have picked the companies that were using ERP could have made a lot of money in the stock market because they outperform their peers. And the same thing was true with data. And I think the same thing is going to be true with automation in the coming decade. >>Couldn't agree more. And I think that's exactly the point that differential acceleration happening this. And it's harder because of the Europeans. Once you knew what it was, you can put the boundaries on it. Digital, the options are infinite. It's just continuous progress as are from there. >>I've got a question for you. You talked about some great stats about how dramatically faster things were took far less time. How does that help from an adoption perspective? I know how much cultural change is very difficult for folks in any organization, but that sort of self-serving how does that help fuel adoption? >>Well, it's interesting. Um, it's, it is a, we're actually going to talk about this tomorrow. It is a framework and it's got to start at the leadership has got to start with governance. It's got to start with a detailed plan. That's executable. And it's got to start with getting buy-in from not only your, the, the organization, but the people you're dealing with outside the organization. Um, it's, it's, uh, I think that's absolutely critical. And when you bring this back to the boardroom, they are the leaders of the companies. And, and I, James, I talked about this as we're getting ready for tomorrow's session. I think the number one thing a board can do today is an own personal self assessment. Do they understand automation? Do they understand what next generation three is? Do they understand what the different components can do? And do they understand how the companies are implementing it? And if I was a board member, uh, on our boards, I say, we need to understand that or else this is nothing's going to happen. We're going to be here at the reliance of the CEO and the CFO strategy, which may or may not include or be thinking about this next three. So leadership at the top is going to drive this. And it's so critical. >>We were talking about catalyst before. And you mentioned education and expertise. I'm always curious as to what drew you to public sector because it's, yeah, I mean, very successful, you know, you're, you're with one of the global SIS directly, you can make a lot more money and that side. So what was it did, was it a desire to it's a great country? Was it >>Take one for the team and I'm going to do a selfish plug here. I just actually wrote a book in this whole thing called transforming a federal agency. What's the name of the book transforming and federal agency. And it's, uh, I spent my time at E Y for 37 years, fully retired. I wanted to give back and do meaningful work. And we lived in Columbus, Ohio, as I was talking about earlier, I was going to go teach and I got a call from the president's personnel office to see if I wanted to come. And these, the CFO at HUD with secretary Carson and change turn the agency around, uh, that took me a little while to say yes, because I wasn't sure I wanted something full time. It was a, it was in DC. So I'd be in a commuting role back and forth. My family's in Columbus. >>Um, but it was, uh, I did it and I loved it. It was, uh, I would pray, I would ask anyone that's has the ability to go into public service at any point in their career to do it. It's it was very rewarding. It was one of my favorite three years of life. And to your point, I didn't have to do it, but, uh, if I wanted to do something and give back and that met the criteria and we were very successful in turning it around with the digital transformation and a lot of stuff that we're talking about today gave me the ability to talk about it because I helped lead it >>For sharing that and did it. So did it start with the CFO's office? Because the first time I ever even heard about our RPO RPA was at a CFO conference and I started talking to him like, oh, this is going to be game changing. Is that where it started? Is that where it lands today? >>From an infrastructure standpoint, the CFO has the wonderful ability to see most processes within a company and its entire lifestyle from beginning to end. So CFO has that visibility to understand where efficiencies can happen in the process. And so the CFO plays a dramatically important role in this. And you think about a CFO's role today versus 20 years ago, it's no longer this, the bean counter rolling up numbers that become a business advisors to the board, to the CEO and to the executive suite. Um, so the CFO, I think has probably the best visibility of all the processes on a global basis. And they can see where the, the efficiencies and the implementation of automation can happen. >>So they can be catalysts and really fueling the actual >>Redesign of work. Yes, they, they, they probably need to be the catalyst. And as a board member, you want to be asking what is the CFO's strategic imperative for the next year? And if it doesn't include this, it's just got to get on the agenda. >>Well, curve ball here is his CFO question and you know, three years or two years ago, you wouldn't have even thought, I mean, let me set it up better. One of the industries that is highly automated is crypto. Yeah. You wouldn't even thought about crypto in your balance sheet a couple of years ago, but I'm not sure it's a widespread board level discussion, but as a CFO, what do you make of the trend to put Bitcoin on balance sheets? >>Yeah, I'm probably not the right person to ask because I'm a conservative guy. >>If somebody supported me and he said, Hey, why don't we put crypto on the balance sheet? >>I would get much more educated. I wouldn't shut it down. I would put it into, let's get more educated. Let's get the experts in here. Let's understand what's really happening with it. Let's understand what the risks are, what the rewards are. And can we absorb any sort of risk or reward with it? And when you say put it on the balance sheet, you can put it on in a small way to test it out. I wouldn't put the whole, I wouldn't make the whole balance sheet for Dell on day one. So that's why I would think about it. Just tell, tell me more, get me educated. How did you think about it? How can it help our business? How can I help our shareholders? How does it grow the bottom line? And then, then you start making decisions. >>Cause CFOs, let me find nature often conservative and most CFOs that I talked to just say no way, not a chance, but you're, maybe you're not as conservative as you think. Well, >>No, but I will never say go away on anything. I mean, cause I want to learn. I want to know. I mean, um, if you like all this stuff, that's new, it's easy to say go away, right? Yeah. But all of a sudden, three years later, the go away, all your competitors are doing it at a competitive advantage. So never say go away, get yourself educated before you jump into it. >>That's good advice. Yeah. In any walk of life question for you, or have you talked about the education aspect there? I'm curious from a risk mitigation perspective, especially given the last 18, 19 months, so tumultuous, so scary for all those organizations that were very digital, they're either gone or they accelerated very quickly. How much of an education do you have to provide certain industries? And are you seeing certain industries? I think healthcare manufacturing, financial services as being leaders in the uptake? >>Well, I think the financial service industries, for sure, they, they, they get this and then they need to, uh, cause they, you know, they're, they're a transaction and based, uh, industry. Uh, so they get it completely. Um, you know, I think maybe some manufacturing distribution, some of the old line businesses are, you know, they may not be thinking of this as progressively as they should. Um, but they'll get there. They're going to have to get there eventually. Um, you know, when you think about the education, my, I thought you were gonna ask a question about the education of the workforce. And I think as a board member, I would be really focused on, uh, how am I educating my workforce of the future? And do I have the workforce of the future today? Do I have to educate them to have to bring in hiring for it? Do I have to bring third-party service providers to get us there? So as a board member really focus on, do I have the right workforce to get us to this next stage? And if not, what do I need to do to get there? Because >>We'll allocate a percentage of their budgets to training and education. And the question is where do they put it >>In? Is it the right training and education, right? >>Where do they focus though? Right now we hear you iPad talking about they're a horizontal play, but James, when you and Lisa, we were asking about industry, when you go to market, are you, are you more focused on verticals? Are you thinking, >>No, it's on two things. So which often find is regardless of the sector with some nuanced variation, the back office functions are regionally the procure to pay process as the same fundamentals, regardless of the sector where the differentiation comes in at a sector of service is when you start going to the middle of the front office, I mean a mining has only one customer. They sold their product to image the retailer has an endless number of them. So when you get to the middle and front office and really start engaging with a customer and external vendors, then a differentiation is very unique and you'd have a lot of sort of customers having sector specific nuances and variations in how you use the platform. And that's where the shift now is happening as well is the back office functions that are largely driven by the CFO. If now getting good, robust value out of it, there's pivot to make it a differentiator in the market, comes in the front and middle office. And that's where we starting to say, sector specific genres solutions, nuances really come to the fall >>Deep industry expertise. Do you think digital at all changes that the reason I ask it because I see Amazon as a retail and then they're in cloud and they're in grocery other in content Apple's in, in financial services and you're seeing these internet giants with a dual agenda, they're disrupting horizontal technology and then there's disruptive industries. And my premise is it's because of data and digital. Do you ever see that industry specialization changing that value chain >>Without a doubt? And I think it's happens initially. It starts off. When people have started looking at the process, they realize there's such key dependencies on the upstream and downstream components of the value chain that they want to control it. So they actually start bridging out of what the core practices or the core business to own a broader agenda. And with digital, you can do it. You can actively interact more systemically that installs triggering, well, maybe I have a different product offering. Maybe I can own this. Could I monetize the information I had at my disposal today in a completely new line. And that really what gets truly innovative and starts creating a revenue increase as opposed as the cost saving. And that's what they're really going after. It's how do I, >>The vertical integration is not new. The plenty of ended up Koch industries, Tyson foods, but now it's digital. So presumably you can do it faster with greater greater scale >>Without a doubt. And you don't have to move your big ERP and things like that. Cause that's the only way it takes five years to move my technology backbone with digital. I can do the interaction tomorrow and we can build up enough to be able to sustain that in the short term. >>Right. And speaking of speed, unfortunately, guys, we are out of time, but thank you. Fantastic conversation automation as a board imperative guys, that's been great James or >>Thank you for your time. Thank you so much >>For Dave a long day. I'm Lisa Martin. You're watching the queue. We are live in Las Vegas at the Bellagio at UI path forward for stick around Dave and I will be right back. Okay.