(light music) >> Hi everybody. Welcome to this Cube Conversation. I'm really pleased to announce a collaboration with Rob Strechay. He's a guest cube analyst, and we'll be working together to extract the signal from the noise. Rob is a long-time product pro, working at a number of firms including AWS, HP, HPE, NetApp, Snowplow. I did a stint as an analyst at Enterprise Strategy Group. Rob, good to see you. Thanks for coming into our Marlboro Studios. >> Well, thank you for having me. It's always great to be here. >> I'm really excited about working with you. We've known each other for a long time. You've been in the Cube a bunch. You know, you're in between gigs, and I think we can have a lot of fun together. Covering events, covering trends. So. let's get into it. What's happening out there? We're sort of exited the isolation economy. Things were booming. Now, everybody's tapping the brakes. From your standpoint, what are you seeing out there? >> Yeah. I'm seeing that people are really looking how to get more out of their data. How they're bringing things together, how they're looking at the costs of Cloud, and understanding how are they building out their SaaS applications. And understanding that when they go in and actually start to use Cloud, it's not only just using the base services anymore. They're looking at, how do I use these platforms as a service? Some are easier than others, and they're trying to understand, how do I get more value out of that relationship with the Cloud? They're also consolidating the number of Clouds that they have, I would say to try to better optimize their spend, and getting better pricing for that matter. >> Are you seeing people unhook Clouds, or just reduce maybe certain Cloud activities and going maybe instead of 60/40 going 90/10? >> Correct. It's more like the 90/10 type of rule where they're starting to say, Hey I'm not going to get rid of Azure or AWS or Google. I'm going to move a portion of this over that I was using on this one service. Maybe I got a great two-year contract to start with on this platform as a service or a database as a service. I'm going to unhook from that and maybe go with an independent. Maybe with something like a Snowflake or a Databricks on top of another Cloud, so that I can consolidate down. But it also gives them more flexibility as well. >> In our last breaking analysis, Rob, we identified six factors that were reducing Cloud consumption. There were factors and customer tactics. And I want to get your take on this. So, some of the factors really, you got fewer mortgage originations. FinTech, obviously big Cloud user. Crypto, not as much activity there. Lower ad spending means less Cloud. And then one of 'em, which you kind of disagreed with was less, less analytics, you know, fewer... Less frequency of calculations. I'll come back to that. But then optimizing compute using Graviton or AMD instances moving to cheaper storage tiers. That of course makes sense. And then optimize pricing plans. Maybe going from On Demand, you know, to, you know, instead of pay by the drink, buy in volume. Okay. So, first of all, do those make sense to you with the exception? We'll come back and talk about the analytics piece. Is that what you're seeing from customers? >> Yeah, I think so. I think that was pretty much dead on with what I'm seeing from customers and the ones that I go out and talk to. A lot of times they're trying to really monetize their, you know, understand how their business utilizes these Clouds. And, where their spend is going in those Clouds. Can they use, you know, lower tiers of storage? Do they really need the best processors? Do they need to be using Intel or can they get away with AMD or Graviton 2 or 3? Or do they need to move in? And, I think when you look at all of these Clouds, they always have pricing curves that are arcs from the newest to the oldest stuff. And you can play games with that. And understanding how you can actually lower your costs by looking at maybe some of the older generation. Maybe your application was written 10 years ago. You don't necessarily have to be on the best, newest processor for that application per se. >> So last, I want to come back to this whole analytics piece. Last June, I think it was June, Dev Ittycheria, who's the-- I call him Dev. Spelled Dev, pronounced Dave. (chuckles softly) Same pronunciation, different spelling. Dev Ittycheria, CEO of Mongo, on the earnings call. He was getting, you know, hit. Things were starting to get a little less visible in terms of, you know, the outlook. And people were pushing him like... Because you're in the Cloud, is it easier to dial down? And he said, because we're the document database, we support transaction applications. We're less discretionary than say, analytics. Well on the Snowflake earnings call, that same month or the month after, they were all over Slootman and Scarpelli. Oh, the Mongo CEO said that they're less discretionary than analytics. And Snowflake was an interesting comment. They basically said, look, we're the Cloud. You can dial it up, you can dial it down, but the area under the curve over a period of time is going to be the same, because they get their customers to commit. What do you say? You disagreed with the notion that people are running their calculations less frequently. Is that because they're trying to do a better job of targeting customers in near real time? What are you seeing out there? >> Yeah, I think they're moving away from using people and more expensive marketing. Or, they're trying to figure out what's my Google ad spend, what's my Meta ad spend? And what they're trying to do is optimize that spend. So, what is the return on advertising, or the ROAS as they would say. And what they're looking to do is understand, okay, I have to collect these analytics that better understand where are these people coming from? How do they get to my site, to my store, to my whatever? And when they're using it, how do they they better move through that? What you're also seeing is that analytics is not only just for kind of the retail or financial services or things like that, but then they're also, you know, using that to make offers in those categories. When you move back to more, you know, take other companies that are building products and SaaS delivered products. They may actually go and use this analytics for making the product better. And one of the big reasons for that is maybe they're dialing back how many product managers they have. And they're looking to be more data driven about how they actually go and build the product out or enhance the product. So maybe they're, you know, an online video service and they want to understand why people are either using or not using the whiteboard inside the product. And they're collecting a lot of that product analytics in a big way so that they can go through that. And they're doing it in a constant manner. This first party type tracking within applications is growing rapidly by customers. >> So, let's talk about who wins in that. So, obviously the Cloud guys, AWS, Google and Azure. I want to come back and unpack that a little bit. Databricks and Snowflake, we reported on our last breaking analysis, it kind of on a collision course. You know, a couple years ago we were thinking, okay, AWS, Snowflake and Databricks, like perfect sandwich. And then of course they started to become more competitive. My sense is they still, you know, compliment each other in the field, right? But, you know, publicly, they've got bigger aspirations, they get big TAMs that they're going after. But it's interesting, the data shows that-- So, Snowflake was off the charts in terms of spending momentum and our EPR surveys. Our partner down in New York, they kind of came into line. They're both growing in terms of market presence. Databricks couldn't get to IPO. So, we don't have as much, you know, visibility on their financials. You know, Snowflake obviously highly transparent cause they're a public company. And then you got AWS, Google and Azure. And it seems like AWS appears to be more partner friendly. Microsoft, you know, depends on what market you're in. And Google wants to sell BigQuery. >> Yeah. >> So, what are you seeing in the public Cloud from a data platform perspective? >> Yeah. I think that was pretty astute in what you were talking about there, because I think of the three, Google is definitely I think a little bit behind in how they go to market with their partners. Azure's done a fantastic job of partnering with these companies to understand and even though they may have Synapse as their go-to and where they want people to go to do AI and ML. What they're looking at is, Hey, we're going to also be friendly with Snowflake. We're also going to be friendly with a Databricks. And I think that, Amazon has always been there because that's where the market has been for these developers. So, many, like Databricks' and the Snowflake's have gone there first because, you know, Databricks' case, they built out on top of S3 first. And going and using somebody's object layer other than AWS, was not as simple as you would think it would be. Moving between those. >> So, one of the financial meetups I said meetup, but the... It was either the CEO or the CFO. It was either Slootman or Scarpelli talking at, I don't know, Merrill Lynch or one of the other financial conferences said, I think it was probably their Q3 call. Snowflake said 80% of our business goes through Amazon. And he said to this audience, the next day we got a call from Microsoft. Hey, we got to do more. And, we know just from reading the financial statements that Snowflake is getting concessions from Amazon, they're buying in volume, they're renegotiating their contracts. Amazon gets it. You know, lower the price, people buy more. Long term, we're all going to make more money. Microsoft obviously wants to get into that game with Snowflake. They understand the momentum. They said Google, not so much. And I've had customers tell me that they wanted to use Google's AI with Snowflake, but they can't, they got to go to to BigQuery. So, honestly, I haven't like vetted that so. But, I think it's true. But nonetheless, it seems like Google's a little less friendly with the data platform providers. What do you think? >> Yeah, I would say so. I think this is a place that Google looks and wants to own. Is that now, are they doing the right things long term? I mean again, you know, you look at Google Analytics being you know, basically outlawed in five countries in the EU because of GDPR concerns, and compliance and governance of data. And I think people are looking at Google and BigQuery in general and saying, is it the best place for me to go? Is it going to be in the right places where I need it? Still, it's still one of the largest used databases out there just because it underpins a number of the Google services. So you almost get, like you were saying, forced into BigQuery sometimes, if you want to use the tech on top. >> You do strategy. >> Yeah. >> Right? You do strategy, you do messaging. Is it the right call by Google? I mean, it's not a-- I criticize Google sometimes. But, I'm not sure it's the wrong call to say, Hey, this is our ace in the hole. >> Yeah. >> We got to get people into BigQuery. Cause, first of all, BigQuery is a solid product. I mean it's Cloud native and it's, you know, by all, it gets high marks. So, why give the competition an advantage? Let's try to force people essentially into what is we think a great product and it is a great product. The flip side of that is, they're giving up some potential partner TAM and not treating the ecosystem as well as one of their major competitors. What do you do if you're in that position? >> Yeah, I think that that's a fantastic question. And the question I pose back to the companies I've worked with and worked for is, are you really looking to have vendor lock-in as your key differentiator to your service? And I think when you start to look at these companies that are moving away from BigQuery, moving to even, Databricks on top of GCS in Google, they're looking to say, okay, I can go there if I have to evacuate from GCP and go to another Cloud, I can stay on Databricks as a platform, for instance. So I think it's, people are looking at what platform as a service, database as a service they go and use. Because from a strategic perspective, they don't want that vendor locking. >> That's where Supercloud becomes interesting, right? Because, if I can run on Snowflake or Databricks, you know, across Clouds. Even Oracle, you know, they're getting into business with Microsoft. Let's talk about some of the Cloud players. So, the big three have reported. >> Right. >> We saw AWSs Cloud growth decelerated down to 20%, which is I think the lowest growth rate since they started to disclose public numbers. And they said they exited, sorry, they said January they grew at 15%. >> Yeah. >> Year on year. Now, they had some pretty tough compares. But nonetheless, 15%, wow. Azure, kind of mid thirties, and then Google, we had kind of low thirties. But, well behind in terms of size. And Google's losing probably almost $3 billion annually. But, that's not necessarily a bad thing by advocating and investing. What's happening with the Cloud? Is AWS just running into the law, large numbers? Do you think we can actually see a re-acceleration like we have in the past with AWS Cloud? Azure, we predicted is going to be 75% of AWS IAS revenues. You know, we try to estimate IAS. >> Yeah. >> Even though they don't share that with us. That's a huge milestone. You'd think-- There's some people who have, I think, Bob Evans predicted a while ago that Microsoft would surpass AWS in terms of size. You know, what do you think? >> Yeah, I think that Azure's going to keep to-- Keep growing at a pretty good clip. I think that for Azure, they still have really great account control, even though people like to hate Microsoft. The Microsoft sellers that are out there making those companies successful day after day have really done a good job of being in those accounts and helping people. I was recently over in the UK. And the UK market between AWS and Azure is pretty amazing, how much Azure there is. And it's growing within Europe in general. In the states, it's, you know, I think it's growing well. I think it's still growing, probably not as fast as it is outside the U.S. But, you go down to someplace like Australia, it's also Azure. You hear about Azure all the time. >> Why? Is that just because of the Microsoft's software state? It's just so convenient. >> I think it has to do with, you know, and you can go with the reasoning they don't break out, you know, Office 365 and all of that out of their numbers is because they have-- They're in all of these accounts because the office suite is so pervasive in there. So, they always have reasons to go back in and, oh by the way, you're on these old SQL licenses. Let us move you up here and we'll be able to-- We'll support you on the old version, you know, with security and all of these things. And be able to move you forward. So, they have a lot of, I guess you could say, levers to stay in those accounts and be interesting. At least as part of the Cloud estate. I think Amazon, you know, is hitting, you know, the large number. Laws of large numbers. But I think that they're also going through, and I think this was seen in the layoffs that they were making, that they're looking to understand and have profitability in more of those services that they have. You know, over 350 odd services that they have. And you know, as somebody who went there and helped to start yet a new one, while I was there. And finally, it went to beta back in September, you start to look at the fact that, that number of services, people, their own sellers don't even know all of their services. It's impossible to comprehend and sell that many things. So, I think what they're going through is really looking to rationalize a lot of what they're doing from a services perspective going forward. They're looking to focus on more profitable services and bringing those in. Because right now it's built like a layer cake where you have, you know, S3 EBS and EC2 on the bottom of the layer cake. And then maybe you have, you're using IAM, the authorization and authentication in there and you have all these different services. And then they call it EMR on top. And so, EMR has to pay for that entire layer cake just to go and compete against somebody like Mongo or something like that. So, you start to unwind the costs of that. Whereas Azure, went and they build basically ground up services for the most part. And Google kind of falls somewhere in between in how they build their-- They're a sort of layer cake type effect, but not as many layers I guess you could say. >> I feel like, you know, Amazon's trying to be a platform for the ecosystem. Yes, they have their own products and they're going to sell. And that's going to drive their profitability cause they don't have to split the pie. But, they're taking a piece of-- They're spinning the meter, as Ziyas Caravalo likes to say on every time Snowflake or Databricks or Mongo or Atlas is, you know, running on their system. They take a piece of the action. Now, Microsoft does that as well. But, you look at Microsoft and security, head-to-head competitors, for example, with a CrowdStrike or an Okta in identity. Whereas, it seems like at least for now, AWS is a more friendly place for the ecosystem. At the same time, you do a lot of business in Microsoft. >> Yeah. And I think that a lot of companies have always feared that Amazon would just throw, you know, bodies at it. And I think that people have come to the realization that a two pizza team, as Amazon would call it, is eight people. I think that's, you know, two slices per person. I'm a little bit fat, so I don't know if that's enough. But, you start to look at it and go, okay, if they're going to start out with eight engineers, if I'm a startup and they're part of my ecosystem, do I really fear them or should I really embrace them and try to partner closer with them? And I think the smart people and the smart companies are partnering with them because they're realizing, Amazon, unless they can see it to, you know, a hundred million, $500 million market, they're not going to throw eight to 16 people at a problem. I think when, you know, you could say, you could look at the elastic with OpenSearch and what they did there. And the licensing terms and the battle they went through. But they knew that Elastic had a huge market. Also, you had a number of ecosystem companies building on top of now OpenSearch, that are now domain on top of Amazon as well. So, I think Amazon's being pretty strategic in how they're doing it. I think some of the-- It'll be interesting. I think this year is a payout year for the cuts that they're making to some of the services internally to kind of, you know, how do we take the fat off some of those services that-- You know, you look at Alexa. I don't know how much revenue Alexa really generates for them. But it's a means to an end for a number of different other services and partners. >> What do you make of this ChatGPT? I mean, Microsoft obviously is playing that card. You want to, you want ChatGPT in the Cloud, come to Azure. Seems like AWS has to respond. And we know Google is, you know, sharpening its knives to come up with its response. >> Yeah, I mean Google just went and talked about Bard for the first time this week and they're in private preview or I guess they call it beta, but. Right at the moment to select, select AI users, which I have no idea what that means. But that's a very interesting way that they're marketing it out there. But, I think that Amazon will have to respond. I think they'll be more measured than say, what Google's doing with Bard and just throwing it out there to, hey, we're going into beta now. I think they'll look at it and see where do we go and how do we actually integrate this in? Because they do have a lot of components of AI and ML underneath the hood that other services use. And I think that, you know, they've learned from that. And I think that they've already done a good job. Especially for media and entertainment when you start to look at some of the ways that they use it for helping do graphics and helping to do drones. I think part of their buy of iRobot was the fact that iRobot was a big user of RoboMaker, which is using different models to train those robots to go around objects and things like that, so. >> Quick touch on Kubernetes, the whole DevOps World we just covered. The Cloud Native Foundation Security, CNCF. The security conference up in Seattle last week. First time they spun that out kind of like reinforced, you know, AWS spins out, reinforced from reinvent. Amsterdam's coming up soon, the CubeCon. What should we expect? What's hot in Cubeland? >> Yeah, I think, you know, Kubes, you're going to be looking at how OpenShift keeps growing and I think to that respect you get to see the momentum with people like Red Hat. You see others coming up and realizing how OpenShift has gone to market as being, like you were saying, partnering with those Clouds and really making it simple. I think the simplicity and the manageability of Kubernetes is going to be at the forefront. I think a lot of the investment is still going into, how do I bring observability and DevOps and AIOps and MLOps all together. And I think that's going to be a big place where people are going to be looking to see what comes out of CubeCon in Amsterdam. I think it's that manageability ease of use. >> Well Rob, I look forward to working with you on behalf of the whole Cube team. We're going to do more of these and go out to some shows extract the signal from the noise. Really appreciate you coming into our studio. >> Well, thank you for having me on. Really appreciate it. >> You're really welcome. All right, keep it right there, or thanks for watching. This is Dave Vellante for the Cube. And we'll see you next time. (light music)

(slow upbeat music) >> Good afternoon and welcome back to Sin City. We're here at AWS reInvent with wall-to-wall coverage on theCUBE. My name is Savannah Peterson, joined with Dave Vellante, and very excited to have two exciting guests from Qlik and AARP with us. Molly and Samir, thank you so much for being here. Welcome to the show. >> Thank you for having us. >> Thank you for having us. >> How's it been so far for you, Molly? >> It's been a great show so far. We've got a big booth presence out here. We've had a lot of people coming by, doing demo stations and just really, really coming to the voice of the customer, so we've really enjoyed the event. >> Ah, love a good VOC conversation myself. How about for you, Samir? >> Oh, it's been great meeting a lot of product folks, meeting a lot of other people, trying to do similar things that we're doing, getting confirmation we're doing the right thing, and learning new things. And obviously, you know, here with Molly, it's been a highlight of my experience. >> What's the best thing you learned from your peers, this week? >> You know, some of the things, that we're all talking about, is how do we get data in the right place at the right time? And, you know, that's something that people are now starting to think about. >> Very hot topic. >> You know, doing it, and then not only getting it to the right place, but taking insights and taking action on it as it's getting there. So those are the conversations that are getting around, in the circle I've been hanging around with. >> You hearing the same thing at the booth or? >> Yeah, absolutely. >> And how are you guys responding? >> Well, I think, as a company, and the shifts in the market, people are really trying to determine what workloads belong in which Cloud, what belongs on-prem? And so talking about those realtime transformations, the integration points, the core systems they're coming from, and really how to unlock that data, is just really powerful and meaningful. So that's been a pretty consistent theme throughout the conference, and a lot of conversations that we have on a regular basis. >> I believe that, Molly, let's stick with you for a second. Just in case the audience isn't familiar, tell us a little more about Qlik. >> Yeah, so Qlik is a robust, end-to-end data pipeline. Starting with really looking at all of your source systems whether it's mainframe, SAP, relational database, kind of name your flavor as it's related to sources. Getting those sources over into the target landing spot whether it be Amazon, or other cloud players, or even if you're, if you're managing hybrid workloads. So that's kind of one piece of the end-to-end platform. And then the second piece is really having all that data, analytics ready, coming right through that real-time data pipeline, and really being able to use the data, to monetize the data, to make sense of the data. And then Qlik really does all that data preparation work underneath the visualization layer, which is where all the work happens. And then you get to see the output of that through the visualization of Qlik, which is, you know, the dashboards, the things that our people, people are used to seeing. >> I love that! So at AARP, what are you using Qlik for? What sort of dashboards are you pulling together? >> So when we started our journey to AWS, we knew that, you know, we're going to have our applications, they're distributed in the Cloud, but again, how do we get the data there, in the right place at the right time? So, as members are, taking action, they're calling into the call center, using our website, using our mobile apps. We want to want it to be able to take that information stream it, so we use Qlik, to take those changes when they happen as they happen, be able to stream it to Kafka and then push that data out to the applications that need it in the time that they needed it. So, instead of waiting for a batch job to happen overnight, we're able to now push this data in real time. And by doing that, we're able to personalize the engagement for our members. So if you come in, we know what you're doing, we can personalize the value that we put in front of you, and just make that engagement a lot more engaging for you. >> Yeah. >> And in the channel that you choose to want to come in with, right? Rather than a channel that we are trying to push to you. >> Everyone wants that personalized experience as we discussed, I love AARP, I've done a lot of work with AARP, I look forward to being a member, but in case the audience isn't familiar, you have the largest membership database of any company on Earth that I'm aware of. How many members does AARP have? >> We have nearly 38 million members, and 66,000 volunteers, and 2300 employees across every state in the United States. >> It's a perfect use case for Qlik, right? 'Cause you've been around for a while. You've got data in the million different places. You're trying to get, you've got a mainframe, right? You know, I hear Amazon's trying to put all the mainframes in the Cloud, but I'm guessing the business case isn't there for you. But you want the data that's coming out of that mainframe to be part of that data pipeline, right? So can you paint a picture, of how, what Molly was describing about the data pipeline, how that fits with AARP? >> Yeah, it's actually, it was a perfect use case. And you know, when we engaged with Qlik, what we wanted to be able to do is take that data in the mainframe, and get it distributed into the Cloud, accurately, securely, and make sure that we can track the lineage, and be able to say, hey, application A only needs name and address, application B needs, name, address, and payment. So we were able to do all of that within a couple of weeks, right? And getting that data out there, knowing that it's going to the right place, knowing it's secure, and knowing it's accurate, regardless of the application it goes to, we don't have to worry about seeking data across different applications. Now we know that there's a source of truth, and everything is done through the pipeline, and it's controlled in a way that, we can measure everything that's going through, how it's going through, and how it's being used by the applications, that are consuming it? >> So you've got the providence and the lineage of that data and that's what Qlik ensures, is that right? Is that your role or is that a partner role, combined? >> No, yes, that's absolutely Qlik's role. So for our new offering, Qlik Cloud data integration, it's a comprehensive solution, delivered as a service, delivers real time, automates, transformations, catalog and lineage, all extremely important. And in the case of Samir and AARP, they're trying to unlock the most valuable assets of their data in SAP and mainframe. And surprisingly, sometimes most valuable data in an organization is the hardest to actually get access to. >> Sure. >> So be, you know, just statistically, 70% of Fortune 500 companies still rely on mainframe. So when you think about that, and even when Samir and I are talking about it. >> That's a lot. >> Yeah. >> And that's a lot of scale, that's a lot of data. >> It's a lot of data. >> Yeah. >> So, you know, mainframe isn't a thing of the past. Companies are still relying on it. People have been saying that for years but when we're talking about getting the complex data out of there to really make something meaningful for AARP, we're really proud of the results, and the opportunity that we've been able to provide to really improve the member experience. And how people are able to consume AARP, and all the different offerings that they have? Kind of like you mentioned Savannah, and the way that you go about it. >> Well, it's also the high risk data. High value data, high risk data. You don't want to mess with it. You want to make sure that you've got that catalog to be able to say, okay, this is what we did with that data, this is where it came from. And then you essentially publish to other tools, analytic tools in the Cloud. Can you paint a picture of how that extends to the Cloud? >> Sure, so there's a couple of different things that we do with it. So once we get the data, into our streaming apps, we can publish it over to like our website. We can publish it to the call center, to mobile apps, to our data warehouse, where we can run analytics and AI on it. And then obviously a lot of our journeys, we use a journey orchestration tool, and we've built a CDP, a customer data platform, to get those insights in there, to drive, you know, personalization and experience. >> I'm smiling as you're talking, Samir, because I'm thinking of all the personalized experiences that my mother has with AARP, and it is so fun to learn about the technology that's serving that to her. >> Exactly. >> This segment actually becoming a bit more personal for me than I expected for a couple of reasons. So this is great. Molly, Qlik has been a part of the AWS ecosystem since the get go. How have things changed over the years? >> Yeah, so Qlik still remains the enterprise integration tool of choice for AWS especially- >> Let's call that a casual and just brag. >> Yeah. >> Because that's awesome. That's great, congratulations on that. >> Thank you for SAP and mainframe. So the relationship continues to evolve but we've been part of the ecosystem from since inception. So we look at, how we continue to evolve the partnership? And honestly, a lot of our customers landing spot is AWS. So the partnership evolves really on two fronts. One with Amazon itself, in a partnership lane, and two, with our customers, and what we're doing with them, and how we're able to really optimize what that looks like? And then secondly, earlier this year we announced an offering Amazon and Qlik, called Qlik Ramp, where we can come in and do, a half day architecture deep dive, look at SAP mainframe, and how they get to the Amazon landing spots, whether it's S3, Redshift, or EMR? So we got a lot of different things kind of going on in the Amazon ecosystem, whether it's customer forward and first, and how can we maximize the relationship spend et cetera, with Amazon. And then also how can we deliver, you know, kind of a shorter time to value throughout that process with something like a Qlik ramp, because we want to qualify, and solve customers needs, as equally as we want to you know, say when we're not the right fit. >> So data is a complicated- >> Love that honesty and transparency. >> Data is a complicated situation for most companies, right? And there's a lack of resource, lack of talent. There's hyper specialization. And you were just talking about the evolution of the Cloud and the relationship. How does automation fit into the equation? Are you able to automate a lot of that data integration through the pipeline? >> Yeah. >> Is it was a, what's your journey look like there? Were you resistant to that at first? 'Cause you got to trust the data. Take us through that. >> Yeah, so the first thing, we wanted to make sure is security right? We've got a lot of data, we're going to make sure privacy- >> Very personal data too. >> Exactly. And privacy and security is number one. So we want to make sure anything that we're doing with the data is secure, and it's not given out anywhere. In terms of automation, so what we've been able to do is being able to take these changes, and you know, in technology, the one thing you can guarantee is it's going to break. Network's going to go down, or a server goes down, a database goes down, and that's the only guarantee we have. And by using the product that we have today, we're able to take those outages, and minimize them because there's retry processes, there's ways of going back and saying, hey, I've missed this much data. How do we bring it back in? You don't want data to get out of sync because that causes downstream problems. >> Yeah. >> So all of that is done through the product, right? We don't have to worry about it. You know, we get notifications, but it's not like, oh, I've got to pay someone at two o'clock in the morning because the network's gone down and how's the data sync going to come back up, when it comes back up? All of that's done for us. >> Yeah, and just to add to that, automation, is a key component. I mean, the data engineering teams definitely see the value of automation and how we're able to deliver that. So, improving the experience but also the overall landscape of the environment is critical. >> Yeah, we've seen the stats, data scientists, data pro spend, you know, 80% of their time wrangling data, 20% of their time. >> Data preparation. >> You know extracting value from it. So. >> Yeah, it's so sad. It's such a waste of human capital, and you're obviously relieving that, and letting folks do their job more efficiently. >> The thing is too, you know, as I'm somebody who's love data you dive into the data, you get really excited then after a while you're like, Ugh! >> I'm still here. >> I'm slogging through this data. Taking a bath in it. >> But I think. >> I want to get to the insights. >> I think that world's changing a little bit. >> Yes, definitely. >> So as we're starting to get data that's coming through it's got high fidelity, and richness, right? So in the old days we'd put in a database, normalize it, and then, you know we'd go and do our magic, and hopefully, you know something comes out, and the least of frustration, you just spoke about. Well now, because it's moving in real time, and we can send the data to areas in the way we want it, and add automation, and machine learning on top of that, so that, now it becomes a commodity to massage that data into the in the format that you want it. Then you can concentrate on the value work, right? Which is really where people should be spending the time, rather than, oh, I've got to manipulate the data, make sure it's done in a consistent way, and then make sure it's compliant and done, the same way every single time. >> It may be too early to, you know quantify the business impact, but have you seen, for example, you know, what I was describing creates data silos. 'Cause nobody's going to use the data if it's not trusted. So what happens is it goes to a silo, they put a brick wall around it, and then, you know, they do their thing with it. They trust it for that one use case and then they don't share it. Has that begun to change as you've seen more integration that's automated and augmented? >> Absolutely. I mean, you know, if you're bringing in data and you're showing that it's consistent, and this is where governance and compliance comes in, right? So as long as you have a data catalog, you can make sure that this data's coming through with the lineage that you said is going to, here's the source, here's the target, here's who gets what they only need rather than giving them everything. And by being able to document that, in a way, that's automated rather than somebody going in, and running a report, it's key. Because that's where the trust comes in, rather than, oh, Samir has to go in and manipulate this stream so that, you know, Molly can get the reports she wants. Instead, hey, it's all going in there, the reports are coming out, they're audited, and that's where the trust factor comes. >> And that enables scale. >> Yeah. >> Cloud confidence and scale. Big topics of the show this week. >> Yep. >> It's been the whole thing. Molly, what's next for Qlik? >> Yeah, Qliks on a big journey. So we've released a lot of things most recently, Qlik Cloud data integration as a service, but we're just continuing to grow from a customer base, from a capabilities perspective. We also recently just became HIPAA compliant and went through some other services. >> Congratulations, that is not an easy process. >> Thank you, thank you. >> Yeah. >> And so for us it's really just about expanding and having, that same level of fidelity of the data, and really just getting all of that pushed out to the market so everybody really sees the full value of Qlik, and that we can make your data Qlik. And just for a minute, back to your earlier point. >> Beautiful pun drop there, Molly. Just going to see that. >> Thank you Savannah. >> Yeah. >> But back to your earlier point, just about the time that people are spending, when you're able to automate, and you're getting data delivered in real time, and operational systems are able to see that. 'Cause you're trying to create the least amount of disruption you can, right? 'Cause that's a critical part of the business. When you start to automate and relieve that burden then people have time to spend time on the real things. >> Right. >> Future forward, prescriptive analytics, machine learning, not data preparation, solving problems, fixing soft gaps. >> Staring a spreadsheet, yeah. >> Right? It's actually the full end-to-end pipeline. And so that's really where I feel like the power is unleashed. And as more sources and targets come to light, right? They're all over the showroom floor, so we don't have to mention any of 'em by name, but it's just continuing, to move into that world to have more SaaS integrations. And to be able to serve the customer, and meet them exactly where they're at, at the place that they want to be. And for Samir, and what we did in the transformation there, unlocking that data for mainframe and SAP, getting it into Qlik Cloud, has been a huge business driver for them. And so, because of partners like AWS and Samir and AARP, we're constantly evolving. And really trying to listen to the voice of the customer, to become better for all of you. >> Excellent. >> Love that community first attitude. Very clear that you both have it, both AARP and Qlik with that attitude. We have a new challenge this year to reInvent on theCUBE, little prompt here. >> Okay. >> We're going to put 30 seconds on the clock, although I'm not super crazy about watching the clock. So, feel comfortable with whatever however much time you need. >> Whatever works. >> Yeah, yeah, yeah, yeah, whatever works. But we're looking for equivocally, your Instagram reel, your hot take, your thought leadership, sizzle, with the key theme from this year's show. Molly, your smile is platinum and perfect. So I'm going to start with you. I feel like you've got this. >> Okay, great. >> Yeah. >> Just the closing statement is what you're looking for. >> Sure, yeah, sexy little sound bite. What do you, what's going to be your big takeaway from your experience here in Vegas this week? >> Yeah, so the experience at Vegas this week has been great but I think it's more than just the experience at Vegas, it's really the experience of the year, where we're at with the technology shift. And we're continuing to see, the need for Cloud, the move to Cloud, mixed workloads, hybrid workloads, unlocking core data, making sure that we're getting insights analytics, and value out of that. And really just working through that, kind of consistent evolution, which is exactly what it is. It's never, you never get to a point where, that's it, there's a bow on it, and it's perfect. It's continuously involving, evolving. >> Yeah. >> And I think that's the most important part that you have to take away. Samir's got his environment in a great place today but in six months, there may be some new things or transformations that he wants to look at, and we want to be there at the ready to work with him, roll up our sleeves, and kind of get into that. So the shift of the Cloud is here to stay. Qlik is a hundred percent here to stay. Here ready to serve our customers in any capacity that we can. And I think that's really my big takeaway from this week. And I've loved it, like this has been a great, this has been great with both of you. You both are super high energy. >> Aw, thank you. >> And Samir and I have had a great time over the event as well. >> Well, nailed it. You absolutely nailed it. All right, Samir, shoot your shot. >> So. >> Savannah. >> What I would say, I'm pretty, so. (laughing) >> I like to keep the smiles organic on stage, my perverse sense of humor, everyone just tolerates. >> Yeah, the one thing I think, I'm hearing a lot is, we have to look at data in motion. Streaming data is the way it's going to go. Whether it's customer data, operational data, it doesn't matter, right? We can't have these silos that you spoke about. Those days are gone, right? And if we really want to make a difference, and utilize all of the technology that's being built out there, all of the new features that were, you know, just in the keynotes. We can't have these separate silos, and the data has to go across, trusted data, it has to go across. The second thing I think we're all talking about is, we have to look at things differently. Unlearning the old is harder than learning the new. So we were just talking about event driven architecture. >> Understatement of the century. Sidebar, that was, yeah. >> So, you know, a lot of us techies are used to calling APIs. Well, now we have to push the data out, instead of pulling it. That just means retraining our brains, retraining our architects, retraining our developers, to think in a different way. And then the last thing I think I've learned is, us technology folks have put the customer first right? >> Yes, absolutely. >> What does a customer want? How do they want to feel when they engage with you? Because if we don't do that, none of this technology matters. And you know, we have to get away from the day where the IT guys go in the back black room, (laughing) coat up and then, you know, push something out, and don't think about what am I doing, and how am I impacting your mother? >> Yes, the end customer. It's no longer the person at the end of a terminal. Look at the green screen. >> And just one last thing. I think also it's fit for purpose transformations. And that's how we have to start thinking about how we're doing business. 'Cause there's a paradigm shift, right? From ETL to ELT, right? Extract, Load, Transform your data. And so as we're seeing that, I think it's really just about that fit for purpose, and looking at the transformations, the right transformations. And what's going to move the needle for the business. >> What a great closing note! Molly, Samir, thank you both for being here. >> Both: Thank you! >> This was a really fantastic chat, love where we took it. And thank all of you for tuning in to our live coverage from AWS reInvent here in fabulous Las Vegas, Nevada. I just want to give my mom a quick shout out, since she got a holler throughout this segment, as well as Stacy and all of my friends at AARP, I missed you all. My name's Savannah Peterson, joined with Dave Vellante. You're watching theCUBE. We are the technology leader in coverage for events like this. (slow upbeat music)

(upbeat music) >> The stampede to cloud and massive VC investments has led to the emergence of a new generation of object store based data lakes. And with them two important trends, actually three important trends. First, a new category that combines data lakes and data warehouses aka the lakehouse is emerged as a leading contender to be the data platform of the future. And this novelty touts the ability to address data engineering, data science, and data warehouse workloads on a single shared data platform. The other major trend we've seen is query engines and broader data fabric virtualization platforms have embraced NextGen data lakes as platforms for SQL centric business intelligence workloads, reducing, or somebody even claim eliminating the need for separate data warehouses. Pretty bold. However, cloud data warehouses have added complimentary technologies to bridge the gaps with lakehouses. And the third is many, if not most customers that are embracing the so-called data fabric or data mesh architectures. They're looking at data lakes as a fundamental component of their strategies, and they're trying to evolve them to be more capable, hence the interest in lakehouse, but at the same time, they don't want to, or can't abandon their data warehouse estate. As such we see a battle royale is brewing between cloud data warehouses and cloud lakehouses. Is it possible to do it all with one cloud center analytical data platform? Well, we're going to find out. My name is Dave Vellante and welcome to the data platform's power panel on theCUBE. Our next episode in a series where we gather some of the industry's top analysts to talk about one of our favorite topics, data. In today's session, we'll discuss trends, emerging options, and the trade offs of various approaches and we'll name names. Joining us today are Sanjeev Mohan, who's the principal at SanjMo, Tony Baers, principal at dbInsight. And Doug Henschen is the vice president and principal analyst at Constellation Research. Guys, welcome back to theCUBE. Great to see you again. >> Thank guys. Thank you. >> Thank you. >> So it's early June and we're gearing up with two major conferences, there's several database conferences, but two in particular that were very interested in, Snowflake Summit and Databricks Data and AI Summit. Doug let's start off with you and then Tony and Sanjeev, if you could kindly weigh in. Where did this all start, Doug? The notion of lakehouse. And let's talk about what exactly we mean by lakehouse. Go ahead. >> Yeah, well you nailed it in your intro. One platform to address BI data science, data engineering, fewer platforms, less cost, less complexity, very compelling. You can credit Databricks for coining the term lakehouse back in 2020, but it's really a much older idea. You can go back to Cloudera introducing their Impala database in 2012. That was a database on top of Hadoop. And indeed in that last decade, by the middle of that last decade, there were several SQL on Hadoop products, open standards like Apache Drill. And at the same time, the database vendors were trying to respond to this interest in machine learning and the data science. So they were adding SQL extensions, the likes Hudi and Vertical we're adding SQL extensions to support the data science. But then later in that decade with the shift to cloud and object storage, you saw the vendor shift to this whole cloud, and object storage idea. So you have in the database camp Snowflake introduce Snowpark to try to address the data science needs. They introduced that in 2020 and last year they announced support for Python. You also had Oracle, SAP jumped on this lakehouse idea last year, supporting both the lake and warehouse single vendor, not necessarily quite single platform. Google very recently also jumped on the bandwagon. And then you also mentioned, the SQL engine camp, the Dremios, the Ahanas, the Starbursts, really doing two things, a fabric for distributed access to many data sources, but also very firmly planning that idea that you can just have the lake and we'll help you do the BI workloads on that. And then of course, the data lake camp with the Databricks and Clouderas providing a warehouse style deployments on top of their lake platforms. >> Okay, thanks, Doug. I'd be remiss those of you who me know that I typically write my own intros. This time my colleagues fed me a lot of that material. So thank you. You guys make it easy. But Tony, give us your thoughts on this intro. >> Right. Well, I very much agree with both of you, which may not make for the most exciting television in terms of that it has been an evolution just like Doug said. I mean, for instance, just to give an example when Teradata bought AfterData was initially seen as a hardware platform play. In the end, it was basically, it was all those after functions that made a lot of sort of big data analytics accessible to SQL. (clears throat) And so what I really see just in a more simpler definition or functional definition, the data lakehouse is really an attempt by the data lake folks to make the data lake friendlier territory to the SQL folks, and also to get into friendly territory, to all the data stewards, who are basically concerned about the sprawl and the lack of control in governance in the data lake. So it's really kind of a continuing of an ongoing trend that being said, there's no action without counter action. And of course, at the other end of the spectrum, we also see a lot of the data warehouses starting to edit things like in database machine learning. So they're certainly not surrendering without a fight. Again, as Doug was mentioning, this has been part of a continual blending of platforms that we've seen over the years that we first saw in the Hadoop years with SQL on Hadoop and data warehouses starting to reach out to cloud storage or should say the HDFS and then with the cloud then going cloud native and therefore trying to break the silos down even further. >> Now, thank you. And Sanjeev, data lakes, when we first heard about them, there were such a compelling name, and then we realized all the problems associated with them. So pick it up from there. What would you add to Doug and Tony? >> I would say, these are excellent points that Doug and Tony have brought to light. The concept of lakehouse was going on to your point, Dave, a long time ago, long before the tone was invented. For example, in Uber, Uber was trying to do a mix of Hadoop and Vertical because what they really needed were transactional capabilities that Hadoop did not have. So they weren't calling it the lakehouse, they were using multiple technologies, but now they're able to collapse it into a single data store that we call lakehouse. Data lakes, excellent at batch processing large volumes of data, but they don't have the real time capabilities such as change data capture, doing inserts and updates. So this is why lakehouse has become so important because they give us these transactional capabilities. >> Great. So I'm interested, the name is great, lakehouse. The concept is powerful, but I get concerned that it's a lot of marketing hype behind it. So I want to examine that a bit deeper. How mature is the concept of lakehouse? Are there practical examples that really exist in the real world that are driving business results for practitioners? Tony, maybe you could kick that off. >> Well, put it this way. I think what's interesting is that both data lakes and data warehouse that each had to extend themselves. To believe the Databricks hype it's that this was just a natural extension of the data lake. In point of fact, Databricks had to go outside its core technology of Spark to make the lakehouse possible. And it's a very similar type of thing on the part with data warehouse folks, in terms of that they've had to go beyond SQL, In the case of Databricks. There have been a number of incremental improvements to Delta lake, to basically make the table format more performative, for instance. But the other thing, I think the most dramatic change in all that is in their SQL engine and they had to essentially pretty much abandon Spark SQL because it really, in off itself Spark SQL is essentially stop gap solution. And if they wanted to really address that crowd, they had to totally reinvent SQL or at least their SQL engine. And so Databricks SQL is not Spark SQL, it is not Spark, it's basically SQL that it's adapted to run in a Spark environment, but the underlying engine is C++, it's not scale or anything like that. So Databricks had to take a major detour outside of its core platform to do this. So to answer your question, this is not mature because these are all basically kind of, even though the idea of blending platforms has been going on for well over a decade, I would say that the current iteration is still fairly immature. And in the cloud, I could see a further evolution of this because if you think through cloud native architecture where you're essentially abstracting compute from data, there is no reason why, if let's say you are dealing with say, the same basically data targets say cloud storage, cloud object storage that you might not apportion the task to different compute engines. And so therefore you could have, for instance, let's say you're Google, you could have BigQuery, perform basically the types of the analytics, the SQL analytics that would be associated with the data warehouse and you could have BigQuery ML that does some in database machine learning, but at the same time for another part of the query, which might involve, let's say some deep learning, just for example, you might go out to let's say the serverless spark service or the data proc. And there's no reason why Google could not blend all those into a coherent offering that's basically all triggered through microservices. And I just gave Google as an example, if you could generalize that with all the other cloud or all the other third party vendors. So I think we're still very early in the game in terms of maturity of data lakehouses. >> Thanks, Tony. So Sanjeev, is this all hype? What are your thoughts? >> It's not hype, but completely agree. It's not mature yet. Lakehouses have still a lot of work to do, so what I'm now starting to see is that the world is dividing into two camps. On one hand, there are people who don't want to deal with the operational aspects of vast amounts of data. They are the ones who are going for BigQuery, Redshift, Snowflake, Synapse, and so on because they want the platform to handle all the data modeling, access control, performance enhancements, but these are trade off. If you go with these platforms, then you are giving up on vendor neutrality. On the other side are those who have engineering skills. They want the independence. In other words, they don't want vendor lock in. They want to transform their data into any number of use cases, especially data science, machine learning use case. What they want is agility via open file formats using any compute engine. So why do I say lakehouses are not mature? Well, cloud data warehouses they provide you an excellent user experience. That is the main reason why Snowflake took off. If you have thousands of cables, it takes minutes to get them started, uploaded into your warehouse and start experimentation. Table formats are far more resonating with the community than file formats. But once the cost goes up of cloud data warehouse, then the organization start exploring lakehouses. But the problem is lakehouses still need to do a lot of work on metadata. Apache Hive was a fantastic first attempt at it. Even today Apache Hive is still very strong, but it's all technical metadata and it has so many different restrictions. That's why we see Databricks is investing into something called Unity Catalog. Hopefully we'll hear more about Unity Catalog at the end of the month. But there's a second problem. I just want to mention, and that is lack of standards. All these open source vendors, they're running, what I call ego projects. You see on LinkedIn, they're constantly battling with each other, but end user doesn't care. End user wants a problem to be solved. They want to use Trino, Dremio, Spark from EMR, Databricks, Ahana, DaaS, Frink, Athena. But the problem is that we don't have common standards. >> Right. Thanks. So Doug, I worry sometimes. I mean, I look at the space, we've debated for years, best of breed versus the full suite. You see AWS with whatever, 12 different plus data stores and different APIs and primitives. You got Oracle putting everything into its database. It's actually done some interesting things with MySQL HeatWave, so maybe there's proof points there, but Snowflake really good at data warehouse, simplifying data warehouse. Databricks, really good at making lakehouses actually more functional. Can one platform do it all? >> Well in a word, I can't be best at breed at all things. I think the upshot of and cogen analysis from Sanjeev there, the database, the vendors coming out of the database tradition, they excel at the SQL. They're extending it into data science, but when it comes to unstructured data, data science, ML AI often a compromise, the data lake crowd, the Databricks and such. They've struggled to completely displace the data warehouse when it really gets to the tough SLAs, they acknowledge that there's still a role for the warehouse. Maybe you can size down the warehouse and offload some of the BI workloads and maybe and some of these SQL engines, good for ad hoc, minimize data movement. But really when you get to the deep service level, a requirement, the high concurrency, the high query workloads, you end up creating something that's warehouse like. >> Where do you guys think this market is headed? What's going to take hold? Which projects are going to fade away? You got some things in Apache projects like Hudi and Iceberg, where do they fit Sanjeev? Do you have any thoughts on that? >> So thank you, Dave. So I feel that table formats are starting to mature. There is a lot of work that's being done. We will not have a single product or single platform. We'll have a mixture. So I see a lot of Apache Iceberg in the news. Apache Iceberg is really innovating. Their focus is on a table format, but then Delta and Apache Hudi are doing a lot of deep engineering work. For example, how do you handle high concurrency when there are multiple rights going on? Do you version your Parquet files or how do you do your upcerts basically? So different focus, at the end of the day, the end user will decide what is the right platform, but we are going to have multiple formats living with us for a long time. >> Doug is Iceberg in your view, something that's going to address some of those gaps in standards that Sanjeev was talking about earlier? >> Yeah, Delta lake, Hudi, Iceberg, they all address this need for consistency and scalability, Delta lake open technically, but open for access. I don't hear about Delta lakes in any worlds, but Databricks, hearing a lot of buzz about Apache Iceberg. End users want an open performance standard. And most recently Google embraced Iceberg for its recent a big lake, their stab at having supporting both lakes and warehouses on one conjoined platform. >> And Tony, of course, you remember the early days of the sort of big data movement you had MapR was the most closed. You had Horton works the most open. You had Cloudera in between. There was always this kind of contest as to who's the most open. Does that matter? Are we going to see a repeat of that here? >> I think it's spheres of influence, I think, and Doug very much was kind of referring to this. I would call it kind of like the MongoDB syndrome, which is that you have... and I'm talking about MongoDB before they changed their license, open source project, but very much associated with MongoDB, which basically, pretty much controlled most of the contributions made decisions. And I think Databricks has the same iron cloud hold on Delta lake, but still the market is pretty much associated Delta lake as the Databricks, open source project. I mean, Iceberg is probably further advanced than Hudi in terms of mind share. And so what I see that's breaking down to is essentially, basically the Databricks open source versus the everything else open source, the community open source. So I see it's a very similar type of breakdown that I see repeating itself here. >> So by the way, Mongo has a conference next week, another data platform is kind of not really relevant to this discussion totally. But in the sense it is because there's a lot of discussion on earnings calls these last couple of weeks about consumption and who's exposed, obviously people are concerned about Snowflake's consumption model. Mongo is maybe less exposed because Atlas is prominent in the portfolio, blah, blah, blah. But I wanted to bring up the little bit of controversy that we saw come out of the Snowflake earnings call, where the ever core analyst asked Frank Klutman about discretionary spend. And Frank basically said, look, we're not discretionary. We are deeply operationalized. Whereas he kind of poo-pooed the lakehouse or the data lake, et cetera, saying, oh yeah, data scientists will pull files out and play with them. That's really not our business. Do any of you have comments on that? Help us swing through that controversy. Who wants to take that one? >> Let's put it this way. The SQL folks are from Venus and the data scientists are from Mars. So it means it really comes down to it, sort that type of perception. The fact is, is that, traditionally with analytics, it was very SQL oriented and that basically the quants were kind of off in their corner, where they're using SaaS or where they're using Teradata. It's really a great leveler today, which is that, I mean basic Python it's become arguably one of the most popular programming languages, depending on what month you're looking at, at the title index. And of course, obviously SQL is, as I tell the MongoDB folks, SQL is not going away. You have a large skills base out there. And so basically I see this breaking down to essentially, you're going to have each group that's going to have its own natural preferences for its home turf. And the fact that basically, let's say the Python and scale of folks are using Databricks does not make them any less operational or machine critical than the SQL folks. >> Anybody else want to chime in on that one? >> Yeah, I totally agree with that. Python support in Snowflake is very nascent with all of Snowpark, all of the things outside of SQL, they're very much relying on partners too and make things possible and make data science possible. And it's very early days. I think the bottom line, what we're going to see is each of these camps is going to keep working on doing better at the thing that they don't do today, or they're new to, but they're not going to nail it. They're not going to be best of breed on both sides. So the SQL centric companies and shops are going to do more data science on their database centric platform. That data science driven companies might be doing more BI on their leagues with those vendors and the companies that have highly distributed data, they're going to add fabrics, and maybe offload more of their BI onto those engines, like Dremio and Starburst. >> So I've asked you this before, but I'll ask you Sanjeev. 'Cause Snowflake and Databricks are such great examples 'cause you have the data engineering crowd trying to go into data warehousing and you have the data warehousing guys trying to go into the lake territory. Snowflake has $5 billion in the balance sheet and I've asked you before, I ask you again, doesn't there has to be a semantic layer between these two worlds? Does Snowflake go out and do M&A and maybe buy ad scale or a data mirror? Or is that just sort of a bandaid? What are your thoughts on that Sanjeev? >> I think semantic layer is the metadata. The business metadata is extremely important. At the end of the day, the business folks, they'd rather go to the business metadata than have to figure out, for example, like let's say, I want to update somebody's email address and we have a lot of overhead with data residency laws and all that. I want my platform to give me the business metadata so I can write my business logic without having to worry about which database, which location. So having that semantic layer is extremely important. In fact, now we are taking it to the next level. Now we are saying that it's not just a semantic layer, it's all my KPIs, all my calculations. So how can I make those calculations independent of the compute engine, independent of the BI tool and make them fungible. So more disaggregation of the stack, but it gives us more best of breed products that the customers have to worry about. >> So I want to ask you about the stack, the modern data stack, if you will. And we always talk about injecting machine intelligence, AI into applications, making them more data driven. But when you look at the application development stack, it's separate, the database is tends to be separate from the data and analytics stack. Do those two worlds have to come together in the modern data world? And what does that look like organizationally? >> So organizationally even technically I think it is starting to happen. Microservices architecture was a first attempt to bring the application and the data world together, but they are fundamentally different things. For example, if an application crashes, that's horrible, but Kubernetes will self heal and it'll bring the application back up. But if a database crashes and corrupts your data, we have a huge problem. So that's why they have traditionally been two different stacks. They are starting to come together, especially with data ops, for instance, versioning of the way we write business logic. It used to be, a business logic was highly embedded into our database of choice, but now we are disaggregating that using GitHub, CICD the whole DevOps tool chain. So data is catching up to the way applications are. >> We also have databases, that trans analytical databases that's a little bit of what the story is with MongoDB next week with adding more analytical capabilities. But I think companies that talk about that are always careful to couch it as operational analytics, not the warehouse level workloads. So we're making progress, but I think there's always going to be, or there will long be a separate analytical data platform. >> Until data mesh takes over. (all laughing) Not opening a can of worms. >> Well, but wait, I know it's out of scope here, but wouldn't data mesh say, hey, do take your best of breed to Doug's earlier point. You can't be best of breed at everything, wouldn't data mesh advocate, data lakes do your data lake thing, data warehouse, do your data lake, then you're just a node on the mesh. (Tony laughs) Now you need separate data stores and you need separate teams. >> To my point. >> I think, I mean, put it this way. (laughs) Data mesh itself is a logical view of the world. The data mesh is not necessarily on the lake or on the warehouse. I think for me, the fear there is more in terms of, the silos of governance that could happen and the silo views of the world, how we redefine. And that's why and I want to go back to something what Sanjeev said, which is that it's going to be raising the importance of the semantic layer. Now does Snowflake that opens a couple of Pandora's boxes here, which is one, does Snowflake dare go into that space or do they risk basically alienating basically their partner ecosystem, which is a key part of their whole appeal, which is best of breed. They're kind of the same situation that Informatica was where in the early 2000s, when Informatica briefly flirted with analytic applications and realized that was not a good idea, need to redouble down on their core, which was data integration. The other thing though, that raises the importance of and this is where the best of breed comes in, is the data fabric. My contention is that and whether you use employee data mesh practice or not, if you do employee data mesh, you need data fabric. If you deploy data fabric, you don't necessarily need to practice data mesh. But data fabric at its core and admittedly it's a category that's still very poorly defined and evolving, but at its core, we're talking about a common meta data back plane, something that we used to talk about with master data management, this would be something that would be more what I would say basically, mutable, that would be more evolving, basically using, let's say, machine learning to kind of, so that we don't have to predefine rules or predefine what the world looks like. But so I think in the long run, what this really means is that whichever way we implement on whichever physical platform we implement, we need to all be speaking the same metadata language. And I think at the end of the day, regardless of whether it's a lake, warehouse or a lakehouse, we need common metadata. >> Doug, can I come back to something you pointed out? That those talking about bringing analytic and transaction databases together, you had talked about operationalizing those and the caution there. Educate me on MySQL HeatWave. I was surprised when Oracle put so much effort in that, and you may or may not be familiar with it, but a lot of folks have talked about that. Now it's got nowhere in the market, that no market share, but a lot of we've seen these benchmarks from Oracle. How real is that bringing together those two worlds and eliminating ETL? >> Yeah, I have to defer on that one. That's my colleague, Holger Mueller. He wrote the report on that. He's way deep on it and I'm not going to mock him. >> I wonder if that is something, how real that is or if it's just Oracle marketing, anybody have any thoughts on that? >> I'm pretty familiar with HeatWave. It's essentially Oracle doing what, I mean, there's kind of a parallel with what Google's doing with AlloyDB. It's an operational database that will have some embedded analytics. And it's also something which I expect to start seeing with MongoDB. And I think basically, Doug and Sanjeev were kind of referring to this before about basically kind of like the operational analytics, that are basically embedded within an operational database. The idea here is that the last thing you want to do with an operational database is slow it down. So you're not going to be doing very complex deep learning or anything like that, but you might be doing things like classification, you might be doing some predictives. In other words, we've just concluded a transaction with this customer, but was it less than what we were expecting? What does that mean in terms of, is this customer likely to turn? I think we're going to be seeing a lot of that. And I think that's what a lot of what MySQL HeatWave is all about. Whether Oracle has any presence in the market now it's still a pretty new announcement, but the other thing that kind of goes against Oracle, (laughs) that they had to battle against is that even though they own MySQL and run the open source project, everybody else, in terms of the actual commercial implementation it's associated with everybody else. And the popular perception has been that MySQL has been basically kind of like a sidelight for Oracle. And so it's on Oracles shoulders to prove that they're damn serious about it. >> There's no coincidence that MariaDB was launched the day that Oracle acquired Sun. Sanjeev, I wonder if we could come back to a topic that we discussed earlier, which is this notion of consumption, obviously Wall Street's very concerned about it. Snowflake dropped prices last week. I've always felt like, hey, the consumption model is the right model. I can dial it down in when I need to, of course, the street freaks out. What are your thoughts on just pricing, the consumption model? What's the right model for companies, for customers? >> Consumption model is here to stay. What I would like to see, and I think is an ideal situation and actually plays into the lakehouse concept is that, I have my data in some open format, maybe it's Parquet or CSV or JSON, Avro, and I can bring whatever engine is the best engine for my workloads, bring it on, pay for consumption, and then shut it down. And by the way, that could be Cloudera. We don't talk about Cloudera very much, but it could be one business unit wants to use Athena. Another business unit wants to use some other Trino let's say or Dremio. So every business unit is working on the same data set, see that's critical, but that data set is maybe in their VPC and they bring any compute engine, you pay for the use, shut it down. That then you're getting value and you're only paying for consumption. It's not like, I left a cluster running by mistake, so there have to be guardrails. The reason FinOps is so big is because it's very easy for me to run a Cartesian joint in the cloud and get a $10,000 bill. >> This looks like it's been a sort of a victim of its own success in some ways, they made it so easy to spin up single note instances, multi note instances. And back in the day when compute was scarce and costly, those database engines optimized every last bit so they could get as much workload as possible out of every instance. Today, it's really easy to spin up a new node, a new multi node cluster. So that freedom has meant many more nodes that aren't necessarily getting that utilization. So Snowflake has been doing a lot to add reporting, monitoring, dashboards around the utilization of all the nodes and multi node instances that have spun up. And meanwhile, we're seeing some of the traditional on-prem databases that are moving into the cloud, trying to offer that freedom. And I think they're going to have that same discovery that the cost surprises are going to follow as they make it easy to spin up new instances. >> Yeah, a lot of money went into this market over the last decade, separating compute from storage, moving to the cloud. I'm glad you mentioned Cloudera Sanjeev, 'cause they got it all started, the kind of big data movement. We don't talk about them that much. Sometimes I wonder if it's because when they merged Hortonworks and Cloudera, they dead ended both platforms, but then they did invest in a more modern platform. But what's the future of Cloudera? What are you seeing out there? >> Cloudera has a good product. I have to say the problem in our space is that there're way too many companies, there's way too much noise. We are expecting the end users to parse it out or we expecting analyst firms to boil it down. So I think marketing becomes a big problem. As far as technology is concerned, I think Cloudera did turn their selves around and Tony, I know you, you talked to them quite frequently. I think they have quite a comprehensive offering for a long time actually. They've created Kudu, so they got operational, they have Hadoop, they have an operational data warehouse, they're migrated to the cloud. They are in hybrid multi-cloud environment. Lot of cloud data warehouses are not hybrid. They're only in the cloud. >> Right. I think what Cloudera has done the most successful has been in the transition to the cloud and the fact that they're giving their customers more OnRamps to it, more hybrid OnRamps. So I give them a lot of credit there. They're also have been trying to position themselves as being the most price friendly in terms of that we will put more guardrails and governors on it. I mean, part of that could be spin. But on the other hand, they don't have the same vested interest in compute cycles as say, AWS would have with EMR. That being said, yes, Cloudera does it, I think its most powerful appeal so of that, it almost sounds in a way, I don't want to cast them as a legacy system. But the fact is they do have a huge landed legacy on-prem and still significant potential to land and expand that to the cloud. That being said, even though Cloudera is multifunction, I think it certainly has its strengths and weaknesses. And the fact this is that yes, Cloudera has an operational database or an operational data store with a kind of like the outgrowth of age base, but Cloudera is still based, primarily known for the deep analytics, the operational database nobody's going to buy Cloudera or Cloudera data platform strictly for the operational database. They may use it as an add-on, just in the same way that a lot of customers have used let's say Teradata basically to do some machine learning or let's say, Snowflake to parse through JSON. Again, it's not an indictment or anything like that, but the fact is obviously they do have their strengths and their weaknesses. I think their greatest opportunity is with their existing base because that base has a lot invested and vested. And the fact is they do have a hybrid path that a lot of the others lack. >> And of course being on the quarterly shock clock was not a good place to be under the microscope for Cloudera and now they at least can refactor the business accordingly. I'm glad you mentioned hybrid too. We saw Snowflake last month, did a deal with Dell whereby non-native Snowflake data could access on-prem object store from Dell. They announced a similar thing with pure storage. What do you guys make of that? Is that just... How significant will that be? Will customers actually do that? I think they're using either materialized views or extended tables. >> There are data rated and residency requirements. There are desires to have these platforms in your own data center. And finally they capitulated, I mean, Frank Klutman is famous for saying to be very focused and earlier, not many months ago, they called the going on-prem as a distraction, but clearly there's enough demand and certainly government contracts any company that has data residency requirements, it's a real need. So they finally addressed it. >> Yeah, I'll bet dollars to donuts, there was an EBC session and some big customer said, if you don't do this, we ain't doing business with you. And that was like, okay, we'll do it. >> So Dave, I have to say, earlier on you had brought this point, how Frank Klutman was poo-pooing data science workloads. On your show, about a year or so ago, he said, we are never going to on-prem. He burnt that bridge. (Tony laughs) That was on your show. >> I remember exactly the statement because it was interesting. He said, we're never going to do the halfway house. And I think what he meant is we're not going to bring the Snowflake architecture to run on-prem because it defeats the elasticity of the cloud. So this was kind of a capitulation in a way. But I think it still preserves his original intent sort of, I don't know. >> The point here is that every vendor will poo-poo whatever they don't have until they do have it. >> Yes. >> And then it'd be like, oh, we are all in, we've always been doing this. We have always supported this and now we are doing it better than others. >> Look, it was the same type of shock wave that we felt basically when AWS at the last moment at one of their reinvents, oh, by the way, we're going to introduce outposts. And the analyst group is typically pre briefed about a week or two ahead under NDA and that was not part of it. And when they dropped, they just casually dropped that in the analyst session. It's like, you could have heard the sound of lots of analysts changing their diapers at that point. >> (laughs) I remember that. And a props to Andy Jassy who once, many times actually told us, never say never when it comes to AWS. So guys, I know we got to run. We got some hard stops. Maybe you could each give us your final thoughts, Doug start us off and then-- >> Sure. Well, we've got the Snowflake Summit coming up. I'll be looking for customers that are really doing data science, that are really employing Python through Snowflake, through Snowpark. And then a couple weeks later, we've got Databricks with their Data and AI Summit in San Francisco. I'll be looking for customers that are really doing considerable BI workloads. Last year I did a market overview of this analytical data platform space, 14 vendors, eight of them claim to support lakehouse, both sides of the camp, Databricks customer had 32, their top customer that they could site was unnamed. It had 32 concurrent users doing 15,000 queries per hour. That's good but it's not up to the most demanding BI SQL workloads. And they acknowledged that and said, they need to keep working that. Snowflake asked for their biggest data science customer, they cited Kabura, 400 terabytes, 8,500 users, 400,000 data engineering jobs per day. I took the data engineering job to be probably SQL centric, ETL style transformation work. So I want to see the real use of the Python, how much Snowpark has grown as a way to support data science. >> Great. Tony. >> Actually of all things. And certainly, I'll also be looking for similar things in what Doug is saying, but I think sort of like, kind of out of left field, I'm interested to see what MongoDB is going to start to say about operational analytics, 'cause I mean, they're into this conquer the world strategy. We can be all things to all people. Okay, if that's the case, what's going to be a case with basically, putting in some inline analytics, what are you going to be doing with your query engine? So that's actually kind of an interesting thing we're looking for next week. >> Great. Sanjeev. >> So I'll be at MongoDB world, Snowflake and Databricks and very interested in seeing, but since Tony brought up MongoDB, I see that even the databases are shifting tremendously. They are addressing both the hashtag use case online, transactional and analytical. I'm also seeing that these databases started in, let's say in case of MySQL HeatWave, as relational or in MongoDB as document, but now they've added graph, they've added time series, they've added geospatial and they just keep adding more and more data structures and really making these databases multifunctional. So very interesting. >> It gets back to our discussion of best of breed, versus all in one. And it's likely Mongo's path or part of their strategy of course, is through developers. They're very developer focused. So we'll be looking for that. And guys, I'll be there as well. I'm hoping that we maybe have some extra time on theCUBE, so please stop by and we can maybe chat a little bit. Guys as always, fantastic. Thank you so much, Doug, Tony, Sanjeev, and let's do this again. >> It's been a pleasure. >> All right and thank you for watching. This is Dave Vellante for theCUBE and the excellent analyst. We'll see you next time. (upbeat music)

>>Okay, welcome back everyone. This is the cubes coverage here in San Francisco, California, a Davis summit, 2022, the beginning of the event season, as it comes back, little smaller footprint, a lot of hybrid events going on, but this is actually a physical event to his summit in new York's coming in the summer. We'll be there too with the cube on the set. We're getting back in the Groove's psych to be back. We were at reinvent, uh, as well, and we'll see more and more cube, but you're can see a lot of virtual cube outta hybrid cube. We wanna get all those conversations, try to get more interviews, more flow going. But right now I'm excited to have Corey Quinn here on the back on the cube chief cloud economists with duct bill, a group, he's the founder, uh, and chief content person always got great angles, fun comedy, authoritative Corey. Great to see you. Thank >>You. Thanks. Coming on. Sure is a lot of words to describe is shit posting, which is how I describe what I tend to do. Most days, >>Shit posting is an art form now. And if you look at mark, Andrew's been doing a lot of shit posting lately. All a billionaires are shit posting, but they don't know how to do it. Like they're not >>Doing it right. There's something opportunity there. It's like, here's how to be even more obnoxious and incisive. It's honestly the most terrifying scenario for anyone is if I have that kind of budget to throw at my endeavors, it's like, I get excited with a nonsense I can do with a $20 gift card for an AWS credit compared to, oh well, if I could buy a midsize island to in doing this from, oh, then we're having fun. >>This shit posting trend. Interesting. I was watching a thread go on about, saw someone didn't get a job because of their shit posting and the employer didn't get it. And then someone on this side, I'll hire the guy cuz I get that's highly intelligent shit posting. So for the audience that doesn't know what shit posting is, what is shit posting? >>It's more or less talking about the world of enterprise technology, which even that sentence is hard to finish without falling asleep and toppling out of my chair in front of everyone on the livestream, but it's doing it in such a way that brings it to life that says the quiet part. A lot of the audience is thinking, but generally doesn't say either because they're polite or not a jackass or more prosaically are worried about getting fired for better or worse. I don't have have that particular constraint, >>Which is why people love you. So let's talk about what you, what you think is, uh, worthy and not worthy in the industry right now, obviously, uh, coupons coming up in Spain, which they're having a physical event, you see the growth of cloud native Amazon's evolving Adams, especially new CEO. Andy's move on to be the chief of all Amazon. Just so I, the cover of was it time magazine, um, he's under a lot of stress. Amazon's changed. Invoice has changed. What's working. What's not, what's rising, what's falling. What's hot. What's not, >>It's easy to sit here and criticize almost anything. These folks do. They're they're effectively in a fishbowl, but I have trouble imagining the logistics. It takes to wind up handling the catering for a relat a downscale event like this one this year, let alone running a 1.7 million employee company having to balance all the competing challenges and pressures and the rest. I, I just can't fathom what it would be like to look at all of AWS. And it's, it's sprawling immense that dominates our entire industry and say, okay, this is a good start, but I, I wanna focus on something with a broader remit. What is that? How do you even get into that position? And you can't win once you're there. All you can do is hold onto the tiger and hope you don't get mold. Well, >>There's a lot of force for good conversations. Seeing a lot of that going on, Amazon's trying to port eight of us is trying to portray themselves as you know, the Pathfinder, you know, you're the pioneer, um, force for good. And I get that. I think that's a good angle as cloud goes mainstream. It's still the question of, we had a guy on just earlier, who was a skydiving instructor and we were joking about the early days of cloud. Like that was like skydiving, build a parachute open, you know, and now it's saying kind of thing, as you move to edge, things are like reliable in some areas, but still new, new fringe, new areas. That's crazy. Well, >>Since the last time we've spoken, uh, Steve Schmidt is now the CISO for all of Amazon and his backfill replacement. The AWS CISO is CJ. Moses who as a hobby race as a semi-pro race car driver to my understanding, which either, I don't know what direction to take that in either. This is what he does to relax or ultimately, or ultimately it's. Huh? That, that certainly says something about risk assessment. I'm not entirely sure what, but okay. Either way, sounds like more exciting, like better >>Have a replacement ready <laugh> in case something gonna was wrong on the track, >>Highly available >>CSOs. I gotta say one of the things I do like in the recent trend is that the tech companies are getting into the formula one, which I was never a fan of until I watched that Netflix series. But when you look at the formula one, it's pretty cool. Cause it's got some tech angles, I get the whole data instrumentation thing, but the most coolest thing about formula one is they have these new rigs out. Yeah. Where you can actually race in e-sports with, there are people in pure simulation of the race car. You gotta get the latest and video graphics card, but it's basically a tricked out PC with amazing monitors and you have all the equipment of F1 and you're basically simulating racing. >>Oh, it's great too. And I can see the appeal of these tech companies getting into it because these things are basically rocket chips. When those cars go like they're sitting there, we cans instrument every last part of what is going on inside that vehicle. And then AWS crops up. And we can bill on every one of those dimensions too. And it's like slow down their hasty pudding one step at a time. But I do see the appeal. >>So I gotta ask you about, uh, what's going on in your world. I know you have a lot of great success. We've been following you in the queue for many, many years. Got a great newsletter, check out Corey Quinn's newsletter, uh, screaming in the cloud program. Uh, you're on the cutting edge and you've got a great balance between really being snarky and, and, and really being delivering content. That's exciting, uh, for people, uh, with a little bit of an edge, um, how's that going? Uh, what's the blowback, any blowback lately? Has there been uptick? What was, what are some of the things you're hearing from your audience, more Corey or Corey, and then of course the, the PR team's calling you >>The weird thing about having an audience beyond a certain size is far and away as a landslide. The most common response I get is silence where it's huh? I'm emailing an awful lot of people at last week in AWS every week and okay. They must not have heard me it. That is not actually true. People just generally don't respond to email because who responds to email newsletters, that sounds like something, a lunatic might do same story with response to live streams and podcasts. It's like, I'm gonna call into that am radio show and give them a piece of my mind. People generally don't do that. >>We should do that. Actually. I think sure would call in. Oh, I, >>I think >>I guarantee we had that right now. People would call in and say, Cory, what do you think about X? >>Yeah. It not, everyone understands the full context of what I do. And in fact, increasingly few people do and that's fine. I, I keep forgetting that sometimes people do not see what I'm doing in the same light that I do. And that's fine. Blowback has been largely minimal. Honestly, I am surprised anything about how little I have gotten over the last five years of doing this, but it would be easier to dismiss me if I weren't generally. Right. When, okay, so you launch this new service and it seems pretty crappy to me cuz when I try and build something, it falls over and begs for help. And people might not like hearing that, but it's what customers are finding too. Yeah. I really am the voice of the customer. >>You know, I always joke with Dave ante about how John Fort's always at, uh, um, reinvent getting the interview with jazzy now, Andy we're there, you're there. And so we have these rituals at the events. It's all cool. Um, one of the rituals I like about your, um, your content is you like to get on the naming product names. Um, and, and, and, and, and kind of Google from that. Now why I like is because I used to work at ETT Packard where they used to name things as like engineers, HP 1 0 5, or we can't call, we >>Have a new monitor. How are we gonna name it? Throw the wireless keyboard down the stairs again. And there you go. Yeah. >>It's and the old joke at HP was if they, if they invented SU uh, sushi, they'd say, yeah, we can't call sushi. It's cold, dead fish. That's what it is. And so the joke was cold. Dead fish is a better name than sushi. So, you know, fun. So what's the, what are the, how's the Amazon doing in there? Have they changed their naming, uh, strategy, uh, on some of their, their >>Producting. So they're going in different directions. When they named Amazon Aurora, they decided to explore a new theme of Disney princesses as they go down those paths. And some things are more descriptive. Some people are clearly getting bonused on a number of words. They can shove into it. Like the better a service is the longer it's name. Like AWS systems manager, session manager is a great one. I love the service ridiculous name. They have a systems manager, parameter store, which is great. They have secrets manager, which does the same thing. It's two words less, but that one costs my in a way that systems manage through parameter store does not. It's fun. >>What's your, what's your favorite combination of acronyms >>Combination >>Of you got E Ks. You got EMR, you got EC two, you got S3 SQS. Well, RedShift's not an acronym. You >>Gots is one of my personal favorites because it's either elastic block store or elastic bean stock, depending into highly on the context of the conversation. They still >>Up Beanstalk or is that still around? >>Oh, they never turn anything off. They like the Antigo, Google turns things off while they're still building it. Whereas Amazon is like, well, we built this thing in 2005 and everyone hates it, but while we certainly can't change it, now it has three customers on it. John three <laugh>. Okay. Simple DV still haunts our dreams. >>I, I actually got an email on, I saw one of my, uh, servers, all these C twos were being deprecated and I got an email. I'm like, couldn't figure out. Why can you just like roll it over? Why, why are you telling me just like, give me something else. Right. Okay. So let me talk about, uh, the other things I want to ask you is that like, okay, so as Amazon gets better, so areas where do they need more work in your opinion? Because obviously they're all interested in new stuff and they tend to like put it out there for their end to end customers. But then they've got ecosystem partners who actually have the same product. Yes. And, and this has been well documented. So it's, it's not controversial. It's just that Amazon's got a database, Snowflake's got a database service. So, you know, Redshift, snowflake 80 is out there. So you got this co-op petition. Yes. How's that going? And what are you hearing about the reaction to any of that stuff? >>Depends on who you ask. They love to basically trot out a bunch of their partners who will say nice things about them. And it very much has heirs of, let's be honest, a hostage video, but okay. Cuz these companies do partner with Amazon and they cannot afford to rock the boat too far. I'm not partnered with anyone. I can say what I want. And they're basically restricted to taking away my birthday at worse so I can live with that. >>All right. So I gotta ask about multi-cloud cause obviously the other cloud shows are coming up. Amazon hated that word. Multi-cloud um, a lot of people are saying, you know, it's not a real good marketing word. Like multi-cloud sounds like, you know, root canal. Mm-hmm <affirmative> right. So is there a better description for multi-cloud >>Multiple single, which >>Davey loves that term. Yeah. >>You know, you're building in multiple single points of failure, do it for the right reasons or don't do it as a default. I believe not doing it is probably the right answer. However, and if I were, if I were Amazon, I wouldn't want to talk about multi-cloud either as industry leader, let's talk about other clouds, bad direction to go in from a market cap perspective. It doesn't end well for you, but regardless of what they want to talk about, or don't want to talk about what they say, what they don't say, I tune all of it out. And I look at what customers are doing and multi-cloud exists in a variety of forms. Some brilliant, some brain dead. It depends a lot on context. But my general response is when someone gets on stage from a company and tells me to do a thing that directly benefits their company. I am skeptical at best. Yeah. When customers get on stage and say, this is what we're doing because it solves problems. That's when I shut up and listen. >>Yeah. Cool. Awesome. Corey, I gotta ask you a question cause I know you we've been, you know, fellow journeymen in the, and the cloud journey, going to all the events and then the pandemic hit. Of course, we're now in the third year, who knows what it's gonna gonna end? Certainly events are gonna look different. They're gonna be either changing footprint with the virtual piece, new group formations. Community's gonna emerge. You've got a pretty big community growing and it's growing like crazy. What's the weirdest or coolest thing, or just big changes you've seen with the pandemic, uh, from your perspective. Cause you've been in the you're in the middle of the whitewater rafting. Seeing the event you circle offline, you saw the online piece, come in, you're commentating, you're calling balls and strikes in the industry. You got a great team developing over there. Duck bill group. What's the big aha moment that you saw with the pandemic. Weird, funny, serious, real in the industry and with customers what's >>Accessibility. Reinvent is a great example. When in the before times it's open to anyone who wants to attend, who can pony up two grand and a week in Las Vegas and get to Las Vegas and wherever they happen to be by moving virtually suddenly it, it embraces the reality that talent is evenly. Distributed. Opportunity is not. And that means that suddenly these things are accessible to a wide swath of audience and potential customer base and the rest that hadn't been invited to the table previously, it's imperative that we not lose that. It's nice to go out and talk to people and have people come up and try and smell my hair from time to time, I smell delightful. Let me assure you. But it was, but it's also nice to be. >>I have some product for you if you want, you know? Oh, >>Oh excellent. I look forward to it. What is it? Pudding? Why not? <laugh> >>What else have you seen? So when accessibility for talent, yes. Which by the way is totally home run. What weird things have happened that you've seen? Um, that's >>Uh, it's, it's weird, but it's good that an awful lot of people giving presentations have learned to tight their message and get to the damn point because most people are not gonna get up from a front row seat in a conference hall, midway through your Aing talk and go somewhere else. But they will change a browser tab and you won't get them back. You've gotta be on point. You've gotta be compelling if it's going to be a virtual discussion. Yeah. >>And also turn off your iMessage too. >>Oh yes. It's always fun in the, in the meetings when you're talking to someone and colleague is messaging them about, should we tell 'em about this? And I'm sitting there reading it and it's >>This guy is really weird. Like, >>Yes I am and I bring it into the conversation and then everyone's uncomfortable. It goes, wow. Why >>Not? I love when my wife yells at me over I message. When I'm on a business call, like, do you wanna take that about no, I'm good. >>No, no. It's better off. I don't the only encourager. It's fine. >>Kids texting you. That's fun. Again. That's another weird thing. And, and then group behavior is weird. Now people are looking at, um, communities differently. Yes. Very much so, because if you're fatigued on content, people are looking for the personal aspect. You're starting to see much more of like yeah. Another virtual event. They gotta get better. One and two who's there. >>Yeah. >>The person >>That's a big part of it too is the human stories are what are being more and more interesting. Don't get up here and tell me about your product and how brilliant you are and how you built it. That's great. If I'm you, or if I wanna work with you or I want to compete with you, or I wanna put on my engineering hat and build it myself. Cause why would I buy anything? That's more than $8. But instead, tell me about the problem. Tell me me about the painful spot that you specialize in. Yeah. Tell me a story there. >>I, I think >>That gets a glimpse in a hook and makes >>More, more, I think you nailed it. Scaling storytelling. Yes. And access to better people because they don't have to be there in person. I just did a thing. I never, we never would've done the queue. We did. Uh, Amazon stepped up in sponsors. Thank you, Amazon for sponsoring international women's day, we did 30 interviews, APAC. We did five regions and I interviewed this, these women in Asia, Pacific eight, PJ, they call for in this world. And they're amazing. I never would've done those interviews cuz I never, would've seen 'em at an event. I never would've been in Japan or Singapore, uh, to access them. And now they're in the index. They're in the network. They're collaborating on LinkedIn. So a threads are developing around connections that I've never seen before. Yes. Around the content. >>Absolutely >>Content value plus network >>Effecting. And that is the next big revelation of this industry is going to realize you have different companies. And in Amazon's case, different service teams, all competing with each other, but you have the container group and you have the database group and you have the message cuing group. But customers don't really want to build things from spare parts. They want a solution to a problem. I want to build an app that does Twitter for pets or whatever it is I'm trying to do. I don't wanna basically have to pick and choose and fill my shopping cart with all these different things. I want something that's gonna basically give me what I'm trying to get as close to turnkey as possible. Moving up the stack. That is the future. And just how it gets here is gonna be >>Well we're here with Corey Quinn, the master of the master of content here in the a ecosystem. Of course we we've been following up from the beginning. It's great guy. Check out his blog, his site, his newsletter screaming podcast. Corey, final question for you. Uh, what do you hear doing what's on your agenda this week in San Francisco and give a plug for the duck build group. What are you guys doing? I know you're hiring some people what's on the table for the company. What's your focus this week and put a plug in for the group. >>I'm here as a customer and basically getting outta my cage cuz I do live here. It's nice to actually get out and talk to folks who are doing interesting things at the duck build group. We solve one problem. We fixed the horrifying AWS bill, both from engineering and architecture, advising as well as negotiating AWS contracts because it turns out those things are big and complicated. And of course my side media projects last week in aws.com, we are it's more or less a content operation where I indulge my continual and love affair with the sound of my own voice. >><laugh> and you're good. It's good content it's on, on point fun, Starky and relevant. So thanks for coming on the cube and sharing with us. Appreciate it. No, >>Thank you. Fun. >>Okay. This cube covers here in San Francisco, California, the cube is back going to events. These are the summits, Amazon web services summits that happen all over the world. We'll be in New York and obviously we're here in San Francisco this week. I'm John fur. Keep, keep it right here. We'll be back with more coverage after this short break.

More bottoms up and have more technical early adopters. And generally speaking, they're free to use. They're free to try. They're very commonly community source or open source companies where you have a large technical community that's supporting them. So there's a, there's kind of a new normal now I think in great enterprise software and it starts with great technical founders with great products and great bottoms of emotions. And I think there's no better place to, uh, service those people than in the cloud and uh, in, in your community. >>Well, first of all, congratulations, and by the way, you got a great pedigree and great background, super smart, but Myer of your work and your, and, and your founding, but let's face it. Enterprise is hot because digital transformation is all companies there's no, I mean, consumer is enterprise now, everything is what was once a niche. No, I won't say niche category, but you know, not for the faint of heart, you know, investors, >>You know, it's so funny that you say that enterprise is hot because you, and I feel that way now. <laugh> but remember, like right now there's also a tech and VC conference in Miami <laugh> and it's covering cryptocurrencies and FCS and web three. So I think beauty is definitely in the eye of the beholder <laugh> but no, I, I will tell you, >>Ts is one big enterprise, cuz you gotta have imutability you got performance issues. You have, I IOPS issues. >>Well, and, and I think all of us here that are, uh, may maybe students of history and have been involved in open source in the cloud would say that we're, you know, much of what we're doing is, uh, the predecessors of the web web three movement. And many of us I think are contributors to the web three >>Movement. The hype is definitely one web three. Yeah. >>But, >>But you know, >>For sure. Yeah, no, but now you're taking us further east of Miami. So, uh, you know, look, I think, I, I think, um, what is unquestioned with the case now? And maybe it's, it's more obvious the more time you spend in this world is this is the fastest growing part of enterprise software. And if you include cloud infrastructure and cloud infrastructure spend, you know, it is by many measures over, uh, $500 billion in growing, you know, 20 to 30% a year. So it it's a, it's a just incredibly fast, well, >>Let's get, let's get into some of the cultural and the, the shifts that are happening, cuz again, you, you have the luxury of being in enterprise when it was hard, it's getting easier and more cooler. I get it and more relevant <laugh> but there's also the hype of like the web three, for instance, but you know, for, uh, um, um, the CEO snowflake, okay. Has wrote a book and Dave Valenti and I were talking about it and uh, Frank Luman has says, there's no playbooks. We always ask the CEOs, what's your playbook. And he's like, there's no playbook, situational awareness, always Trump's playbooks. So in the enterprise playbook, oh, higher, a direct sales force and SAS kind of crushed that now SAS is being redefined, right. So what is SAS is snowflake assassin or is that a platform? So again, new unit economics are emerging, whole new situation, you got web three. So to me there's a cultural shift, the young entrepreneurs, the, uh, user experience, they look at Facebook and say, ah, you know, they own all my data and you know, we know that that cliche, um, they, you know, the product. So as this next gen, the gen Z and the millennials come in and our customers and the founders, they're looking at things a little bit differently and the tech better. >>Yeah. I mean, I mean, I think we can, we can see a lot of common across all successful startups and the overall adoption of technology. Um, and, and I would tell you, this is all one big giant revolution. I call it the user driven revolution. Right. It's the rise of the user. Yeah. And you might say product like growth is currently the hottest trend in enterprise software. It's actually like growth, right. They're one and the same. So sometimes people think the product, uh, is what is driving growth. >>You just pull the product >>Through. Exactly, exactly. And so that's that I, that I think is really this revolution that you see, and, and it does extend into things like cryptocurrencies and web three and, you know, sort of like the control that is taken back by the user. Um, but you know, many would say that, that the origins of this, but maybe started with open source where users were contributors, you know, contributors were users and looking back decades and seeing how it, how it fast forward to today. I think that's really the trend that we're all writing. It's enabling these end users. And these end users in our world are developers, data engineers, cybersecurity practitioners, right. They're really the, and they're really the, the beneficiaries and the most, you know, kind of valued people in >>This. I wanna come back to the data engineers in a second, but I wanna make a comment and get your reaction to, I have a, I'm a gen Xer technically. So for not a boomer, but I have some boomer friends who are a little bit older than me who have, you know, experienced the sixties. And I have what been saying on the cube for probably about eight years now that we are gonna hit digital hippie revolution, meaning a rebellion against in the sixties was rebellion against the fifties and the man and, you know, summer of love. That was a cultural differentiation from the other one other group, the predecessors. So we're kind of having that digital moment now where it's like, Hey boomers, Hey people, we're not gonna do that anymore. You, we hate how you organize shit. >>Right. But isn't this just technology. I mean, isn't it, isn't it like there used to be the old adage, like, you know, you would never get fired for buying IBM, but now it's like, you obviously probably would get fired if you bought IBM. And I mean, it's just like the, the, I think, I think >>During the mainframe days, those renegades were breaking into Stanford, starting the home group. So what I'm trying to get at is that, do you see the young cultural revolution also, culturally, just, this is my identity NFTs to me speak volumes about my, I wanna associate with NFTs, not single sign on. Well, >>Absolutely. And, and I think like, I think you're hitting on something, which is like this convergence of, of, you know, societal it'll trends with technology trends and how that manifests in our world is yes. I think like there is unquestionably almost a religion yeah. Around the way in which a product is built. Right. And we can use open source, one example of that religion. Some people will say, look, I'll just never try a product in the cloud if it's not open source. Yeah. I think cloud, native's another example of that, right? It's either it's, you know, it either is cloud native or it's not. And I think a lot of people will look at a product and say, look, you know, you were not designed in the cloud era. Therefore I just won't try you. And sometimes, um, like it or not, it's a religious decision, right? Yeah. It's so it's something that people just believe to be true almost without, uh, necessarily caring >>About data. Data drives all decision making. Let me ask you this next question. As a VC. Now you look at pitch, well, you've been a VC for many years, but you also have the founder entrepreneurial mindset, but you can get empathize with the founders. You know, hustle is a big part of the, that first founder check, right? You gotta convince someone to part with their ch their money and the first money in which you do a lot of it's about believing in the person. So faking it till you make it is hard. Now you, the data's there, you either have it cloud native, you either have the adaption or traction. So honesty is a big part of that pitch. You can't fake it. >>Oh, AB absolutely. You know, there used to be this concept of like the persona of an entrepreneur. Right. And the persona of the entrepreneur would be, you know, so somebody who was a great salesperson or somebody who tell a great story, and I still think that that's important, right. It still is a human need for people to believe in narratives and stories. Yeah. But having said that you're right. The proof is in the pudding, right. At some point you click download and you try the product and it does what it says it gonna it's gonna do, or it doesn't, or it either stands up to the load test or it doesn't. And so I, I feel like in the new economy that we live in, really, it's a shift from maybe the storytellers and the creators to, to the builders, right. The people that know how to build great product. And in some ways the people that can build great product yeah. Stand out from the crowd. And they're the ones that can build communities around their products. And, you know, in some ways can, um, you know, kind of own more of the narrative of because their product begins exactly >>The volume you back to the user led growth. >>Exactly. And it's the religion of, I just love your product. Right. And I, I, I, um, Doug song is the founder of du security used to say, Hey, like, you know, the, the really like in today's world of like consumption based software, like the user is only gonna give you 90 seconds to figure out whether or not you're a company that's easy to do business with. Right. And so you can say, and do all the things that you want about how easy you are to work with. But if the product isn't easy to install, if it's not easy to try, if it's not, if, if the it's gotta speak to the, >>Speak to the user, but let me ask a question now that for the people watching, who are maybe entrepreneurial entre, preneurs, um, masterclass here in session. So I have to ask you, do you prefer, um, an entrepreneur come in and say, look at John. Here's where I'm at. Okay. First of all, storytelling's fine with you an extrovert or introvert, have your style, sell the story in a way that's authentic, but do you, what do you prefer to say? Here's where I'm at? Look, I have an idea. Here's my traction. I think here's my MVP prototype. I need help. Or do, do you wanna just see more stats? What's the, what's the preferred way that you like to see entrepreneurs come in and engage? >>There's tons of different styles, man. I think the single most important thing that every founder should know is that we, we don't invest in what things are today. We invest in what we think something will become. Right. And I think that's why we all get up in the morning and try to build something different, right? It's that we see the world a different way. We want it to be a different way. And we wanna work every single moment of the day to try to make that vision a reality. So I think the more that you can show people where you want to be the, of more likely somebody is gonna align with your vision and, and wanna invest in you and wanna be along for the ride. So I, I wholeheartedly believe in showing off what you got today, because eventually we all get down to like, where are we and what are we gonna do together? But, um, no, I, you gotta >>Show the >>Path. I think the single most important thing for any founder and VC relationship is that they have the same vision. Uh, if you have the same vision, you can, you can get through bumps in the road, you can get through short term spills. You can all sorts of things in the middle. The journey can happen. Yeah. But it doesn't matter as much if you share the same long term vision, >>Don't flake out and, and be fashionable with the latest trends because it's over before you can get there. >>Exactly. I think many people that, that do what we do for a living, we'll say, you know, ultimately the future is relatively easy to predict, but it's the timing that's impossible to predict. <laugh> so you, you know, you sort of have to balance the, you know, we, we know that the world is going in this way and therefore we're gonna invest a lot of money to try to make this a reality. Uh, but some times it happens in six months. Sometimes it takes six years. Sometimes it takes 16 years. Uh, >>What's the hottest thing in enterprise that you see the biggest wave that people should pay attention to that you're looking at right now with Bel partners, Tebel dot your site. What's the big wave. What's your big >>Wave. There's three big trends that we invest in. And the they're the only things we do day in, day out one is the explosion and open source software. So I think many people think that all software is unquestionably moving to an open source model in some form or another yeah. Tons of reasons to debate whether or not that is gonna happen, an alwa timeline >>Happening forever. >>But, uh, it is, it is accelerating faster than we've ever seen. So I, I think it's, it's one big, massive wave that we continue to ride. Um, second is the rise of data engineering. Uh, I think data engineering is in and of itself now, a category of software. It's not just that we store data. It's now we move data and we develop applications on data. And, uh, I think data is in and of itself as big of a market as any of the other markets that we invest in. Uh, and finally, it's the gift that keeps on giving. I've spent my entire career in it. We still feel that security is a market that is underinvested. It is, it continues to be the place where people need to continue to invest and spend more money. Yeah. Uh, and those are the three major trends that we run >>And security, you think we all need a dessert do over, right? I mean, do we need you do over in security or is what's the core problem? I, >>I, I keep using this word underinvested because I think it's the right way to think about the problem. I think if you, I think people generally speaking, look at cybersecurity as an add-on. Yeah. But if you think about it, the whole economy is moving online. And so in, in some ways like security is core to protecting the digital economy. And so it's, it shouldn't be an afterthought, right? It should be core to what everyone is doing. And that's why I think relative to the trillions of dollars that are at stake, uh, I believe the market size for cybersecurity is run $150 billion. And it still is a fraction of what we're, >>What we're and national security even boom is booming now. So you get the convergence of national security, geopolitics, internet digital that's >>Right. You mean arguably, right? I mean, arguably again, it's the area of the world that people should be spending more time and more money given what to stake. >>I love your thesis. I gotta, I gotta say, you gotta love your firm. Love. You're doing we're big supporters, your mission. Congratulations on your entrepreneurial venture. And, uh, we'll be, we'll be talking and maybe see a Cuban. Uh, absolutely not. Certainly EU maybe even north Americans in Detroit this year. >>Huge fan of what you guys are doing here. Thank you so much for helping me on the show. >>Guess be VC Johnson here on the cube. Check him out. Founder for founders here on the cube, more coverage from San Francisco, California. After this short break, stay with us. Everyone. Welcome to the cue here. Live in San Francisco. K warn you for AWS summit 2022 we're live we're back with events. Also we're virtual. We got hybrid all kinds of events. This year, of course, summit in New York city is happening this summer. We'll be there with the cube as well. I'm John. Again, John host of the cube. Got a great guest here, Justin Kobe owner, and CEO of innovative solutions. Their booth is right behind us. Justin, welcome to the cube. >>Thank you. Thank you for having me. >>So we're just chatting, uh, uh, off camera about some of the work you're doing. You're the owner of and CEO. Yeah. Of innovative. Yeah. So tell us the story. What do you guys do? What's the elevator pitch. >>Yeah. <laugh> so the elevator pitch is we are, uh, a hundred percent focused on small to mid-size businesses that are moving to the cloud, or have already moved to the cloud and really trying to understand how to best control security, compliance, all the good stuff that comes along with it. Um, exclusively focused on AWS and, um, you know, about 110 people, uh, based in Rochester, New York, that's where our headquarters is, but now we have offices down in Austin, Texas, up in Toronto, uh, Canada, as well as Chicago. Um, and obviously in New York, uh, you know, the business was never like this, uh, five years ago, um, founded in 1989, made the decision in 2018 to pivot and go all in on the cloud. And, uh, I've been a part of the company for about 18 years, bought the company about five years ago. And it's been a great ride. >>It's interesting. The manages services are interesting with cloud cause a lot of the heavy liftings done by a of us. So we had Matt on your team on earlier talking about some of the edge stuff. Yeah. But you guys are a managed cloud service. You got cloud advisory, you know, the classic service that's needed, but the demands coming from cloud migrations and application modernization, but obviously data is a huge part of it. Huge. How is this factoring into what you guys do and your growth cuz you guys are the number one partner on the SMB side for edge. Yeah. For AWS, you got results coming in. Where's the, where's the forcing function. What's the pressure point. What's the demand like? >>Yeah. It's a great question. Every CEO I talk to, that's a small mids to size business. They're all trying to understand how to leverage technology better to help either drive a revenue target for their own business, uh, help with customer service as so much has gone remote now. And we're all having problems or troubles or issues trying to hire talent. And um, you know, tech is really at the, at the forefront and the center of that. So most customers are coming to us and they're of like, listen, we gotta move to the cloud or we move some things to the cloud and we want to do that better. And um, there's this big misnomer that when you move to the cloud, you gotta automatically modernize. Yeah. And what we try to help as many customers understand as possible is lifting and shifting, moving the stuff that you maybe currently have OnPrem and a data center to the cloud first is a first step. And then so, uh, progressively working through a modernization strategy is always the better approach. And so we spend a lot of time with small to mid-size businesses who don't have the technology talent on staff to be able to do >>That. Yeah. And they want to get set up. But the, the dynamic of like latency is huge. We're seeing that edge product is a big part of it. This is not a one-off happening around everywhere. It is not it's manufacturing, it's the physical plant or location >>Literally. >>And so, and you're seeing more IOT devices. What's that like right now from a challenge and problem statement standpoint, are the customers, not staff, is the it staff kind of old school? Is it new skills? What's the core problem. And you guys solve >>In the SMB space. The core issue nine outta 10 times is people get enamored with the latest and greatest. And the reality is not everything that's cloud based. Not all cloud services are the latest and greatest. Some things have been around for quite some time and our hardened solutions. And so, um, what we try to do with, to technology staff that has traditional on-prem, uh, let's just say skill sets and they're trying to move to a cloud-based workload is we try to help those customers through education and through some practical, let's just call it use case. Um, whether that's a proof of concept that we're doing or whether that's, we're gonna migrate a small workload over, we try to give them the confidence to be able to not, not necessarily go it alone, but, but to, to, to have the, uh, the Gusto and to really have the, um, the, the opportunity to, to do that in a wise way. Um, and what I find is that most CEOs that I talk to yeah. Feel like, listen, at the end of the day, I'm gonna be spending money in one place or another, whether that's on primer in the cloud, I just want know that I'm doing that way. That helps me grow as quickly as possible status quo. I think every, every business owner knows that COVID taught us anything that status quo is, uh, is, is no. No. Good. >>How about factoring in the, the agility and speed equation? Does that come up a lot? It >>Does. I think, um, I think there's also this idea that if, uh, if we do a deep dive analysis and we really take a surgical approach to things, um, we're gonna be better off. And the reality is the faster you move with anything cloud based, the better you are. And so there's this assumption that we gotta get it right the first time. Yeah. In the cloud, if you start down your journey in one way and you realize midway that it's not the right, let's just say the right place to go. It's not like buying a piece of iron that you put in the closet and now you own it in the cloud. You can turn those services on and off. It's a, gives you a much higher density for making decisions and failing >>Forward. Well actually shutting down the abandoning, the projects that early, not worrying about it, you got it mean most people don't abandon stuff cuz they're like, oh, I own it. >>Exactly. >>And they get, they get used to it. Like, and then they wait too long. >>That's exactly. >>Yeah. Frog and boiling water, as we used to say, oh, it's a great analogy. So I mean, this, this is a dynamic. That's interesting. I wanna get more thoughts on it because like I'm a, if I'm a CEO of a company, like, okay, I gotta make my number. Yeah. I gotta keep my people motivated. Yeah. And I gotta move faster. So this is where you guys come in. I get the whole thing. And by the way, great service, um, professional services in the cloud right now are so hot because so hot, you can build it and then have option optionality. You got path decisions, you got new services to take advantage of. It's almost too much for customers. It is. I mean, everyone I talked to at reinvent, that's a customer. Well, how many announcements did Andy jazzy announcer Adam? You know, the 5,000 announcement or whatever. They did huge amounts. Right. Keeping track of it all. Oh, is huge. So what's the, what's the, um, the mission of, of your company. How does, how do you talk to that alignment? Yeah. Not just processes. I can get that like values as companies, cuz they're betting on you and your people. >>They are, they are >>Values. >>Our mission is, is very simple. We want to help every small to midsize business leverage the power of the cloud. Here's the reality. We believe wholeheartedly. This is our vision that every company is going to become a technology company. So we go to market with this idea that every customer's trying to leverage the power of the cloud in some way, shape or form, whether they know it or don't know it. And number two, they're gonna become a 10 a company in the process of that because everything is so tech-centric. And so when you talk about speed and agility, when you talk about the, the endless options and the endless permutations of solutions that a customer can buy in the cloud, how are you gonna ask a team of one or two people in your it department to make all those decisions going it alone or trying to learn it as you go, it only gets you so far working with a partner. >>I'll just give you some perspective. We work with about a thousand small to midsize business customers. More than 50% of those customers are on our managed services. Meaning they know that we have their back and we're the safety net. So when a customer is saying, right, I'm gonna spend a couple thousand and dollars a month in the cloud. They know that that bill, isn't gonna jump to $10,000 a month going in alone. Who's there to help protect that. Number two, if you have a security posture and let's just say your high profile and you're gonna potentially be more vulnerable to security attacks. If you have a partner that's offering you some managed services. Now you, again, you've got that backstop and you've got those services and tooling. We, we offer, um, seven different products, uh, that are part of our managed services that give the customer the tooling, that for them to go out and buy on their own for a customer to go out today and go buy a new Relic solution on their own. It, it would cost 'em a four, >>The training alone would be insane. A risk factor. I mean the cost. Yes, absolutely opportunity cost is huge, >>Huge, absolutely enormous training and development. Something. I think that is often, you know, it's often overlooked technologists. Typically they want to get their skills up. They, they love to get the, the stickers and the badges and the pins, um, at innovative in 2018. When, uh, when we, he made the decision to go all in on the club, I said to the organization, you know, we have this idea that we're gonna pivot and be aligned with AWS in such a way that it's gonna really require us all to get certified. My executive assistant at the time looks at me. She said, even me, I said, yeah, even you, why can't you get certified? Yeah. And so we made, uh, a conscious, it wasn't requirement. It still isn't today to make sure everybody in the company has the opportunity to become certified. Even the people that are answering the phones at the front >>Desk and she could be running the Kubernetes clusters. I >>Love it. It's >>Amazing. >>But I'll tell you what, when that customer calls and they have a real Kubernetes issue, she'll be able to assist and get >>The right people with. And that's a cultural factor that you guys have. So, so again, this is back to my whole point out SMBs and businesses in general, small and large it staffs are turning over the gen Z and millennials are in the workforce. They were provisioning top of rack switches. Right. First of all. And so if you're a business, there's also the, I call the buildout, um, uh, return factor, ROI piece. At what point in time as an owner, SMB, do I get to ROI? Yeah. I gotta hire a person to manage it. That person's gonna have five zillion job offers. Yep. Uh, maybe who knows? Right. I got cyber security issues. Where am I gonna find a cyber person? Yeah. A data compliance. I need a data scientist and a compliance person. Right. Maybe one in the same. Right. Good luck. Trying to find a data scientist. Who's also a compliance person. Yep. And the list goes on. I can just continue. Absolutely. I need an SRE to manage the, the, uh, the sock report and we can pen test. Right. >>Right. >>These are, these are >>Like critical issues. >>This is just like, these are the table stakes. >>Yeah. And, and every, every business owner's thinking about this, >>That's, that's what, at least a million in loading, if not three or more Just to get that app going. Yeah. Then it's like, where's the app. Yeah. So there's no cloud migration. There's no modernization on the app side. No. And they remind AI and ML. >>That's right. That's right. So to try to go it alone, to me, it's hard. It it's incredibly difficult. And the other thing is, is there's not a lot of partners, so the partner, >>No one's raising their hand boss. I'll do all that exactly. In the it department. >>Exactly. >>So like, can we just call up, uh, you know, our old vendor that's >>Right. <laugh> right. Our old vendor. I like it, >>But that's so true. I mean, when I think about how, if I was a business owner starting a business today and I had to build my team, um, and the amount of investment that it would take to get those people skilled up and then the risk factor of those people now having the skills and being so much more in demand and being recruited away, that's a real, that's a real issue. And so how you build your culture around that is, is very important. It's something that we talk about every, with every one of our small to mid-size >>Businesses. So just, I want get, I want to get your story as CEO. Okay. Take us through your journey. You said you bought the company and your progression to, to being the owner and CEO of innovative yeah. Award winning guys doing great. Uh, great bet on a good call. Yeah. Things are good. Tell your story. What's your journey? >>It's real simple. I was, uh, I was a sophomore at the Rochester Institute of technology in 2003. And, uh, I knew that I, I was going to school for it and I, I knew I wanted to be in tech. I didn't know what I wanted to do, but I knew I didn't wanna code or configure routers and switches. So I had this great opportunity with the local it company that was doing managed services. We didn't call it at that time innovative solutions to come in and, uh, jump on the phone and dial for dollars. I was gonna cold call and introduced other, uh, small to midsize businesses locally in Rochester, New York go to Western New York, um, who innovative was now. We were 19 people at the time. Yeah. I came in, I did an internship for six months and I loved it. I learned more in those six months than I probably did in my first couple of years at, uh, at RT long story short. >>Um, for about seven years, I worked, uh, to really help develop, uh, sales process and methodology for the business so that we could grow and scale. And we grew to about 30 people. And, um, I went to the owners at the time in 2000 and I was like, Hey, I'm growing the value of this business. And who knows where you guys are gonna be another five years? What do you think about making me an owner? And they were like, listen, you got long ways before you're gonna be an owner. But if you stick it out in your patient, we'll, um, we'll work through a succession plan with you. And I said, okay, there were four other individuals at the time that were gonna also buy the business with me. >>And they were the owners, no outside capital, >>None zero, well, 2014 comes around. And, uh, the other folks that were gonna buy into the business with me that were also working at innovative for different reasons. They all decided that it wasn't for them. One started a family. The other didn't wanna put capital in. Didn't wanna write a check. Um, the other had a real big problem with having to write a check. If we couldn't make payroll, I'm like, well, that's kind of like, if we're own, we're gonna have to like cover that stuff. <laugh> so >>It's called the pucker factor. >>Exactly. So, uh, I sat down with the CEO in early 2015 and, uh, we made the decision that I was gonna buy the three partners out, um, go through an earn out process, uh, coupled with, uh, an interesting financial strategy that wouldn't strap the BI cuz they cared very much. The company still had the opportunity to keep going. So in 2016 I bought the business, um, became the sole owner. And, and at that point we, um, we really focused hard on what do we want this company to be? We had built this company to this point. Yeah. And, uh, and by 2018 we knew that pivoting all going all in on the cloud was important for us. And we haven't looked back. >>And at that time, the proof points were coming clearer and clearer 2012 through 15 was the early adopters, the builders, the startups and early enterprises. Yes. The capital ones of the world. Exactly the, uh, and those kinds of big enterprises. The GA I don't wanna say gamblers, but ones that were very savvy. The innovators, the FinTech folks. Yep. The hardcore glass eating enterprises >>Agreed, agreed to find a small to midsize business to migrate completely to the cloud is as infrastructure was considered, that just didn't happen as often. Um, what we were seeing where the, a lot of our small to midsize business customers, they wanted to leverage cloud based backup, or they wanted to leverage a cloud for disaster recovery because it lent itself. Well, early days, our most common cloud customer though, was the customer that wanted to move messaging and collaboration. The, the Microsoft suite to the cloud. And a lot of 'em dipped their toe in the water. But by 2017 we knew infrastructure was around the corner. Yeah. And so, uh, we only had two customers on AWS at the time. Um, and we, uh, we, we made the decision to go all in >>Justin. Great to have you on the cube. Thank you. Let's wrap up. Uh, tell me the hottest product that you have. Is it migrations? Is the app modernization? Is it data? What's the hot product and then put a plugin for the company. Awesome. >>So, uh, there's no question. Every customer is looking migrate workloads and try to figure out how to modernize for the future. We have very interesting, sophisticated yet elegant funding solutions to help customers with the cash flow, uh, constraints that come along with those migrations. So any SMB that's thinking about migrating into the cloud, they should be talking innovative solutions. We know how to do it in a way that allows those customer is not to be cash strapped and gives them an opportunity to move forward in a controlled, contained way so they can modernize. So >>Like insurance, basically for them not insurance class in the classic sense, but you help them out on the, on the cash exposure. >>Absolutely. We are known for that and we're known for being creative with those customers and being empathetic to where they are in their journey. >>And that's the cloud upside is all about doubling down on the variable win that's right. Seeing the value and ING down on it. Absolutely not praying for it. Yeah. <laugh> all right, Justin. Thanks for coming on. You really appreciate >>It. Thank you very much for having me. >>Okay. This is the cube coverage here live in San Francisco, California for AWS summit, 2022. I'm John for your host. Thanks for watching. We're back with more great coverage for two days after this short break >>Live on the floor in San Francisco for Aus summit. I'm John for host of the cube here for the next two days, getting all the actual back in person we're at AWS reinvent a few months ago. Now we're back events are coming back and we're happy to be here with the cube. Bring all the action. Also virtual. We have a hybrid cube, check out the cube.net, Silicon angle.com for all the coverage. After the event. We've got a great guest ticking off here. Matthew Park, director of solutions, architecture with innovation solutions. The booth is right here. Matthew, welcome to the cube. >>Thank you very much. I'm glad to be here. >>So we're back in person. You're from Tennessee. We were chatting before you came on camera. Um, it's great to be back through events. It's >>Amazing. This is the first, uh, summit I've been to, to in what two, three >>Years. That's awesome. We'll be at the, uh, a AWS summit in New York as well. A lot of developers and the big story this year is as developers look at cloud going distributed computing, you got on premises, you got public cloud, you got the edge. Essentially the cloud operations is running everything devs sec ops, everyone kind of sees that you got containers, you got Benet, he's got cloud native. So the, the game is pretty much laid out. Mm-hmm <affirmative> and the edge is with the actions you guys are number one, premier partner at SMB for edge. >>That's >>Right. Tell us about what you guys doing at innovative and, uh, what you do. >>That's right. Uh, so I'm the director of solutions architecture. Uh, me and my team are responsible for building out the solutions. The at our around, especially the edge public cloud for us edge is anything outside of an AWS availability zone. Uh, we are deploying that in countries that don't have AWS infrastructure in region. They don't have it. Uh, give >>An example, >>Uh, example would be Panama. We have a customer there that, uh, needs to deploy some financial tech data and compute is legally required to be in Panama, but they love AWS and they want to deploy AWS services in region. Uh, so they've taken E EKS anywhere. We've put storage gateway and, uh, snowball, uh, in region inside the country and they're running or FinTech on top of AWS services inside Panama. >>You know, what's interesting, Matthew is that we've been covering Aw since 2013 with the cube about their events. And we watched the progression and jazzy was, uh, was in charge and became the CEO. Now Adam slaps in charge, but the edge has always been that thing they've been trying to avoid. I don't wanna say trying to avoid, of course, Amazon would listens to the customer. They work backwards from the customer. We all know that. Uh, but the real issue was they were they're bread and butters EC two and S three. And then now they got tons of services and the cloud is obviously successful and seeing that, but the edge brings up a whole nother level. >>It does >>Computing. >>It >>Does. That's not centralized in the public cloud now they got regions. So what is the issue with the edge what's driving? The behavior. Outpost came out as a reaction to competitive threats and also customer momentum around OT, uh, operational technologies. And it merging. We see with the data at the edge, you got five GM having. So it's pretty obvious, but there was a slow transition. What was the driver for the edge? What's the driver now for edge action for AWS >>Data in is the driver for the edge. Data has gravity, right? And it's pulling compute back to where the customer's generating that data and that's happening over and over again. You said it best outpost was a reaction to a competitive situation. Whereas today we have over 15 AWS edge services and those are all reactions to things that customers need inside their data centers on location or in the field like with media companies. >>Outpost is interesting. We always use the riff on the cube, uh, cause it's basically Amazon in a box, pushed in the data center, running native, all this stuff, but now cloud native operations are kind of becoming standard. You're starting to see some standard. Deepak syncs group is doing some amazing work with opensource Raul's team on the AI side, obviously, uh, you got SW who's giving the keynote tomorrow. You got the big AI machine learning big part of that edge. Now you can say, okay, outpost, is it relevant today? In other words, did outpost do its job? Cause EKS anywhere seems to be getting a lot of momentum. You see local zones, the regions are kicking ass for Amazon. This edge piece is evolving. What's your take on EKS anywhere versus say outpost? >>Yeah, I think outpost did its job. It made customers that were looking at outpost really consider, do I wanna invest in this hardware? Do I, do I wanna have, um, this outpost in my datas center, do I want to manage this over the long term? A lot of those customers just transitioned to the public cloud. They went into AWS proper. Some of those customers stayed on prem because they did have use cases that were, uh, not a good fit for outpost. They weren't a good fit. Uh, in the customer's mind for the public AWS cloud inside an availability zone now happening is as AWS is pushing these services out and saying, we're gonna meet you where you are with 5g. We're gonna meet you where you are with wavelength. We're gonna meet you where you are with EKS anywhere. Uh, I think it has really reduced the amount of times that we have conversations about outposts and it's really increased. We can deploy fast. We don't have to spin up outpost hardware can go deploy EKS anywhere in your VMware environment. And it's increasing the speed of adoption >>For sure. Right? So you guys are making a lot of good business decisions around managed cloud service. That's right. Innovative. Does that get the cloud advisory, the classic professional services for the specific edge piece and, and doing that outside of the availability zones and regions for AWS, um, customers in these new areas that you're helping out are they want cloud, like they want to have modernization a modern applications. Obviously they got data machine learning and AI, all part of that. What's the main product or, or, or gap that you're filling for AWS, uh, outside of their availability zones or their regions that you guys are delivering. What's the key is that they don't have a footprint. Is it that it's not big enough for them? What's the real gap. What's why, why are you so successful? >>So what customers want when they look towards the cloud is they want to focus on what's making them money as a business. They wanna focus on their applications. They wanna focus on their customers. So they look towards AWS cloud and a AWS. You take the infrastructure, you take, uh, some of the higher layers and we'll focus on our revenue generating business, but there's a gap there between infrastructure and revenue generating business that innovative slides into, uh, we help manage the AWS environment. Uh, we help build out these things in local data centers for 32 plus year old company. We have traditional on-premises people that know about deploying hardware that know about deploying VMware to host EKS anywhere. But we also have most of our company totally focused on the AWS cloud. So we're that gap in helping deploy these AWS services, manage them over the long term. So our customers can go to just primarily and totally focusing on their revenue generating business. So >>Basically you guys are basically building AWS edges, >>Correct? >>For correct companies, correct? Mainly because the, the needs are there, you got data, you got certain products, whether it's, you know, low latency type requirements, right. And then they still work with the regions, right. It's all tied together, right. Is that how it >>Works? Right. And, and our customers, even the ones in the edge, they also want us to build out the AWS environment inside the availability zone, because we're always gonna have a failback scenario. If we're gonna deploy fin in the Caribbean, we're gonna talk about hurricanes. And we're gonna talk about failing back into the AWS availability zones. So innovative is filling that gap across the board, whether it be inside the AWS cloud or on the AWS edge. >>All right. So I gotta ask you on the, since you're at the edge in these areas, I won't say underserved, but developing areas where now have data and you have applications that are tapping into that, that requirement. It makes total sense. We're seeing that across the board. So it's not like it's a, it's an outlier it's actually growing. Yeah. There's also the crypto angle. You got the blockchain. Are you seeing any traction at the edge with blockchain? Because a lot of people are looking at the web three in these areas like Panama, you mentioned FinTech. And in, in the islands there a lot of, lot of, lot of web three happening. What's your, what your view on the web three world right now, relative >>To we, we have some customers actually deploying crypto, especially, um, especially in the Caribbean. I keep bringing the Caribbean up, but it's, it's top of my mind right now we have customers that are deploying crypto. A lot of, uh, countries are choosing crypto to underlie parts of their central banks. Yeah. Um, so it's, it's up and coming. Uh, I, I have some, you know, personal views that, that crypto is still searching for a use case. Yeah. And, uh, I think it's searching a lot and, and we're there to help customers search for that use case. Uh, but, but crypto, as a, as a, uh, technology, um, lives really well on the AWS edge. Yeah. Uh, and, and we're having more and more people talk to us about that. Yeah. And ask for assistance in the infrastructure, because they're developing new cryptocurrencies every day. Yeah. It's not like they're deploying Ethereum or anything specific. They're actually developing new currencies and, and putting them out there on >>It's interesting. I mean, first of all, we've been doing crypto for many, many years. We have our own little, um, you know, project going on. But if you look talk to all the crypto people that say, look, we do a smart contract, we use the blockchain. It's kind of over a lot of overhead and it's not really their technical already, but it's a cultural shift, but there's underserved use cases around use of money, but they're all using the blockchain just for like smart contracts, for instance, or certain transactions. And they go to Amazon for the database. Yeah. <laugh> they all don't tell anyone we're using a centralized service. Well, what happened to decentralized? >>Yeah. And that's, and that's the conversation performance issue. Yeah. And, and it's a cost issue. Yeah. And it's a development issue. Um, so I think more and more as, as some of these, uh, currencies maybe come up, some of the smart contracts get into, uh, they find their use cases. I think we'll start talking about how does that really live on, on AWS and, and what does it look like to build decentralized applications, but with AWS hardware and services. >>Right. So take me through, uh, a use case of a customer Matthew around the edge. Okay. So I'm a customer, pretend I'm a customer, Hey, you know, I'm, we're in an underserved area. I want to modernize my business. And I got my developers that are totally peaked up on cloud, but we've identified that it's just a lot of overhead latency issues. I need to have a local edge and serve my a, I also want all the benefit of the cloud. So I want the modern, and I wanna migrate to the cloud for all those cloud benefits and the goodness of the cloud. What's the answer. >>Yeah. Uh, big thing is, uh, industrial manufacturing, right? That's, that's one of the best use cases, uh, inside industrial manufacturing, we can pull in many of the AWS edge services we can bring in, uh, private 5g, uh, so that all the, uh, equipment that, that manufacturing plant can be hooked up, they don't have to pay huge overheads to deploy 5g it's, uh, better than wifi for the industrial space. Um, when we take computing down to that industrial area, uh, because we wanna do pre-procesing on the data. Yeah. We want to gather some analytics. We deploy that with a regular commercially available hardware running VMware, and we deploy EKS anywhere on that. Inside of that manufacturing plant, we can do pre-procesing on things coming out of the robotics, depending on what we're manufacturing. Right. And then we can take those refined analytics and for very low cost with maybe a little bit longer latency transmit those back, um, to the AWS availability zone, the, the standard >>For data, data lake, or whatever, >>To the data lake. Yeah. Data lake house, whatever it might be. Um, and we can do additional data science on that once it gets to the AWS cloud. Uh, but a lot of that, uh, just in time business decisions, just time manufacturing decisions can all take place on an AWS service or services inside that manufacturing plant. And that's, that's one of the best use cases that we're >>Seeing. And I think, I mean, we've been seeing this on the queue for many, many years, moving data around is very expensive. Yeah. But also compute going to the data that saves that cost yeah. On the data transfer also on the benefits of the latency. So I have to ask you, by the way, that's standard best practice now for the folks watching don't move the data unless you have to. Um, but those new things are developing. So I wanna ask you what new patterns are you seeing emerging once this new architecture's in place? Love that idea, localize everything right at the edge, manufacturing, industrial, whatever, the use case, retail, whatever it is. Right. But now what does that change in the, in the core cloud? There's a, there's a system element here. Yeah. What's the new pattern. There's >>Actually an organizational element as well, because once you have to start making the decision, do I put this compute at the point of use or do I put this compute in the cloud? Uh, now you start thinking about where business decisions should be taking place. Uh, so not only are you changing your architecture, you're actually changing your organization because you're thinking, you're thinking about a dichotomy you didn't have before. Uh, so now you say, okay, this can take place here. Uh, and maybe, maybe this decision can wait. Right. And then how do I visualize that? By >>The way, it could be a bot tube doing the work for management. Yeah. <laugh> exactly. You got observability going, right. But you gotta change the database architecture on the back. So there's new things developing. You've got more benefit. There >>Are, there are, and we have more and more people that, that want to talk less about databases and want to talk about data lakes because of this. They want to talk more about customers are starting to talk about throwing away data. Uh, you know, for the past maybe decade. Yeah. It's been store everything. And one day we will have a data science team that we hire in our organization to do analytics on this decade of data. And well, >>I mean, that's, that's a great point. We don't have time to drill into, maybe we do another session this, but the one pattern we're seeing come of the past year is that throwing away data's bad. Even data lakes that so-called turn into data swamps, actually, it's not the case. You look at data, brick, snowflake, and other successes out there. And even time series data, which may seem irrelevant efforts over actually matters when people start retrain their machine learning algorithms. Yep. So as data becomes co as we call it in our last showcase, we did a whole whole an event on this. The data's good in real time and in the lake. Yeah. Because the iteration of the data feeds the machine learning training. Things are getting better with the old data. So it's not throw away. It's not just business benefits. Yeah. There's all kinds of new scale. There >>Are. And, and we have, uh, many customers that are running petabyte level. Um, they're, they're essentially data factories on, on, on premises, right? They're, they're creating so much data and they're starting to say, okay, we could analyze this, uh, in the cloud, we could transition it. We could move petabytes of data to AWS cloud, or we can run, uh, computational workloads on premises. We can really do some analytics on this data transition, uh, those high level and sort of raw analytics back to AWS run 'em through machine learning. Um, and we don't have to transition 10, 12 petabytes of data into AWS. >>So I gotta end the segment on a, on a, kind of a, um, fun, I was told to ask you about your personal background on premise architect, Aus cloud, and skydiving instructor. How does that all work together? What tell, what does this mean? >>Yeah. Uh, I, >>You jumped out a plane and got a job. You got a customer to jump >>Out kind of. So I was, you jumped out. I was teaching Scott eing, uh, before I, before I started in the cloud space, this was 13, 14 years ago. I was a, I still am a Scott I instructor. Uh, I was teaching Scott eing and I heard out of the corner of my ear, uh, a guy that owned an MSP that was lamenting about, um, you know, storing data and how his customers are working. And he can't find enough people to operate all these workloads. So I walked over and said, Hey, this is, this is what I went to school for. Like, I'd love to, you know, I was living in a tent in the woods, teaching skydiving. I was like, I'd love to not live in a tent in the woods. So, uh, I started in the first day there, we had a, and, uh, EC two had just come out <laugh> um, and, uh, like, >>This is amazing. >>Yeah. And so we had this discussion, we should start moving customers here. And, uh, and that totally revolutionized that business, um, that, that led to, uh, that that guy actually still owns a skydiving airport. But, um, but through all of that, and through being in on premises, migrated me and myself, my career into the cloud, and now it feels like, uh, almost, almost looking back and saying, now let's take what we learned in the cloud and, and apply those lessons and those services to premises. >>So it's such a great story. You know, I was gonna, you know, you know, the, the, the, the whole, you know, growth mindset pack your own parachute, you know, uh, exactly. You know, the cloud in the early days was pretty much will the shoot open. Yeah. It was pretty much, you had to roll your own cloud at that time. And so, you know, you, you jump on a plane, you gotta make sure that parachute is gonna open. >>And so was Kubernetes by the way, 2015 or so when, uh, when that was coming out, it was, I mean, it was, it was still, and I, maybe it does still feel like that to some people, right. Yeah. But, uh, it was, it was the same kind of feeling that we had in the early days of AWS, the same feeling we have when we >>It's much now with you guys, it's more like a tandem jump. Yeah. You know, but, but it's a lot of, lot of this cutting stuff like jumping out of an airplane. Yeah. You guys, the right equipment, you gotta do the right things. Exactly. >>Right. >>Matthew, thanks for coming on the cube. Really appreciate it. Absolutely great conversation. Thanks for having me. Okay. The cubes here, lot in San Francisco for AWS summit, I'm John for your host of the cube. Uh, we'll be at a summit in New York coming up in the summer as well. Look up for that. Look at this calendar for all the cube, actually@thecube.net. We'll right back with our next segment after this break. >>Okay. Welcome back everyone to San Francisco live coverage here, we're at the cube, a summit 2022. We're back in person. I'm John furry host of the cube. We'll be at the, a us summit in New York city this summer, check us out then. But right now, two days in San Francisco getting all coverage, what's going on in the cloud, we got a cube alumni and friend of the cube, my dos car CEO, investor, a Sierra, and also an investor and a bunch of startups, angel investor. Gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see you, Pam. Cool. How are you? Good. >>How are you? >>So congratulations on all your investments. Uh, you've made a lot of great successes, uh, over the past couple years, uh, and your company raising, uh, some good cash as Sarah so give us the update. How much cash have you guys raised? What's the status of the company product what's going on? First >>Of all, thank you for having me. We're back to be business with you never while after. Great to see you. Um, so is a company started around four years back. I invested with a few of the investors and now I'm the CEO there. Um, we have raised close to a hundred million there. Uh, the investors are people like nor west Menlo, true ventures, coast, lo ventures, Ram Shera, and all those people, all known guys that Antibe chime Paul Mayard web. So a whole bunch of operating people and, uh, Silicon valley vs are involved. >>And has it gone? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISR is going after is what I call the applying AI for customer service. It operations, it help desk the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and ServiceNow to take it to the next stage? Well, >>I love having you on the cube, Dave and I, and Dave Valenti as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a, you're like a guest analyst. <laugh>, >>You know, >>You >>Get, the comment is fun to talk to you though. >>You get the commentary, you, your, your finger on the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase it. Isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud out scale. You predicted that we talked about in the cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing Docker just raised a hundred million on our $2 billion valuation back from the dead after they pivoted from an enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control, plane emerging, AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded observability there's 10 million observability companies. Data is the key. This is what's your angle on this. What's your take. Yeah, >>No, look, I think I'll give you the view that I see, right? I, from my side, obviously data is very clear. So the things that room system of record that you and me talked about, the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud native, it'll be called AI. NA NA is a new buzzword and using the AI for customer service, it operations. You talk about observability. I call it AI ops, applying AOPs for good old it operation management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events insurance. So I see a lot of work clicking for AIOps and AI service desk. What needs to be helped desk with ServiceNow BMC <inaudible> you see a new ALA emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflows, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with AI workflows. So you'll see AI going >>Off is RPA a company is AI, is RPA a feature of something bigger? Or can someone have a company on RPA UI S one will be at their event this summer? Um, or is it a product company? I mean, I mean, RPA is almost, should be embedded in everything. >>It's a feature. It is very good point. Very, very good thinking. So one is, it's a category for sure. Like, as we thought, it's a category, it's an area where RPA may change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company also, but that automation should be a, in every area. Yeah. Like we call cloud NA and AI NATO it'll become automation. NA yeah. And that's your thinking. >>It's almost interesting me. I think about the, what you're talking about what's coming to mind is I'm kind having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it was middleware. It sat between two things and then the middle and it was software was action. Now you have all kinds of workflows abstractions everywhere. Right? So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed or they integrated. I mean, these are the challenges. This is crazy. What's the, >>So don't about the databases become all polyglot databases. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area, like, as you were talking about, it should be part of ServiceNow. It should be part of ISRA, like every company, every Salesforce. So that's why you see MuleSoft and Salesforce buying RPA companies. So you'll see all the SaaS companies could cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also will have an automation as a layer <inaudible> inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind us, you got the expo hall. You got, um, we're back to vents, but you got, you know, am Clume Ove, uh, Dynatrace data dog, innovative all the companies out here that we know, we interview them all. They're trying to be suppliers to this growing enterprise market. Right. Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Deibel later today. He's a former NEA guy and we always talk to Jerry, Jen, we know all the, the VCs. What does the startups look like? What does the state of the, in your mind, cause you, I know you invest the entrepreneurial founder situation. Cloud's bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's. Yes. Basically. Data's everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to, uh, two things that I'm seeing out there. Remember leaders, how Amazon created the startups 15 years back, everybody built on Amazon now, Azure and GCP. The next layer would be is people don't just build on Amazon. They're gonna build it on top of snowflake. Companies are snowflake becomes a data platform, right? People will build on snowflake. Right? So I see my old boss flagman try to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer. Right? So I think that's the next level of <inaudible> trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis of a couple months ago called castles in the cloud where your Mo is what you do in the cloud. Not necessarily in, in the, in the IP. Um, Dave LAN and I had last reinvent, coined the term super cloud, right? He's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldman S Sachs is doing. You starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage, and guys, Charles Fitzgerald out there who we like was kind of shitting on us saying, Hey, you guys terrible, they didn't get it. Like, yeah, I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. <laugh> cause he's cool. Um, but snowflake is on Amazon. Now. They say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist. And, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. It >>Is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to build everything on Amazon where possible whatever is, I cannot build. I'll make the pass layer. Remember the middle layer pass will be snowflake so I can build it on snowflake. I can use them for data layer if I really need to size build it on force.com Salesforce. Yeah. Right. So I think that's where you'll see. So >>Basically the, if you're an entrepreneur, the, the north star in terms of the, the outcome is be a super cloud. >>It is, >>That's the application on another big CapEx ride, the CapEx of AWS or cloud, >>And that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. Yeah. >>Yeah. How are, how is Amazon and the clouds dealing with these big whales, the snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think they had Redshift. Amazon has got Redshift. Um, but Snowflake's a big customer in the, they're probably paying AWS, I think big bills too. So >>Joe on very good. Cause it's like how Netflix is and Amazon prime, right. Netflix runs on Amazon, but Amazon has Amazon prime that co-optation will be there. So Amazon will have Redshift, but Amazon is also partnering with, uh, snowflake to have native snowflake data warehouses or data layer. So I think depending on the application use case, you have to use each of the above. I think snowflake is here for a long term. Yeah. Yeah. So if I'm building an application, I want to use snowflake then writing from stats. >>Well, I think that it comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, you know, foreclose, your, you that's right with some sort of internal hack. Uh, but I think, I think the general question that I have is that I, I think it's okay to have a super cloud like that because the rising tide is still happening at some point, when does the rising tide stop and do the people shopping up their knives, it gets more competitive or is it just an infinite growth? So >>I think it's growth. You call it cloud scale, you invented the word cloud scale. So I think look, cloud will continually agree, increase. I think there's as long as there more movement from on, uh, OnPrem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations. It helpless, even the customer service service now and, uh, ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So cloud ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go >>Made. I wanna get your thoughts for the folks watching that are, uh, enterprise buyers are practitioners, not suppliers to the more market, feel free to text me or DMing. The next question's really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products, cuz you know, the big enterprises now and you know, small, medium, large and large enterprise are all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between the startup selling to, or growing startup selling to an enterprise? Um, have you seen changes there? I mean I'm seeing some stuff, but why don't get your thoughts on that? What, >>No, it is. If I growing by or 2007 or eight, when I used to talk to you back then and Amazon started very small, right? We are an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or 1% today. Most companies are already spending 20, 30% with startups. Like if I look at a CIO or line of business, it's gone. Yeah. Can it go more? I think it can in the next four, five years. Yeah. Spending on the startups. >>Yeah. And check out, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want to get your reaction because I reference the URL cause it's like, there's like a bunch of companies we've been promoting because the solutions that startups have actually are new stuff. Yes. It's bending, it's shifting for security or using data differently or um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there. Um, and goes back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona, you mentioned AIOps, we've been seeing AIOps IOPS booming and that's creating a new developer paradigm that's right. Which we call coin data as code data as code is like infrastructure is code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this data engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same thing? Do you agree? Um, do you disagree or can you share >>Yourself a lot of first is I see the AIOP solutions in the future should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone there yet. Like I spend a lot of time with data dog, Cisco app Dyna, right? Dynatrace, all this solution. We will go future towards predict to proactive solution with AOPs. But what you bring up a very good point on the data side. I think like we have a Amazon marketplace and Amazon for startup, there should be data exchange where you want to create for AOPs and AI service desk. Customers are give the data, share the data because we thought the data algorithms are useless. I can them, but I gotta train them, modify them, tweak them, make them >>Better, >>Make them better. Yeah. And I think their whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that area is very important. >>You've always been on, um, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to big data days back in 2009, you know, >>Look at, look how much data Rick has grown. >>It is. They doubled the >>Key cloud air kinda went private. So good stuff, man. What are you working on right now? Give a, give a, um, plug for what you're working on. You'll still investing. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. So right. ISRA is my number one baby right now. So I'm looking at that growing customers and my customers are some of them, you like it's zoom auto desk McAfee, uh, grand to so all the top customers, um, mainly for it help desk customer service. AIOps those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What's what's their need? What category is it? >>I think they look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on predict is one area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value problem. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service. >>Great stuff, man. Great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the cube. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of Aish summit 2022. And we're gonna be at Aus summit in San, uh, in New York in the summer. So look for that on this calendar, of course go to eight of us, startups.com. I mentioned that it's decipher all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break. >>Okay. Welcome back everyone. This the cubes coverage here in San Francisco, California, a Davis summit, 2022, the beginning of the event season, as it comes back, little bit smaller footprint, a lot of hybrid events going on, but this is actually a physical event, a summit in new York's coming in the summer. We'll be there too with the cube on the set. We're getting back in the groove psych to be back. We were at reinvent, uh, as well, and we'll see more and more cube, but you're can see a lot of virtual cube outta hybrid cube. We wanna get all those conversations, try to get more interviews, more flow going. But right now I'm excited to have Corey Quinn here on the back on the cube chief cloud economists with bill group. He's the founder, uh, and chief content person always got great angles, fun comedy, authoritative Corey. Great to see you. Thank >>You. Thanks. Coming on. Sure is a lot of words to describe is shit posting, which is how I describe what I tend to do. Most days, >>Shit posting is an art form now. And if you look at mark, Andrew's been doing a lot of shit posting lately. All a billionaires are shit hosting, but they don't know how to do it. Like they're not >>Doing it right? So there's something opportunity there. It's like here's how to be even more obnoxious and incisive. It's honestly the most terrifying scenario for anyone is if I have that kind of budget to throw at my endeavors, it's like, I get excited with a nonsense I can do with a $20 gift card for an AWS credit compared to, oh well, if I could buy a midsize island, do begin doing this from, oh, then we're having fun. >>This shit posting trend. Interesting. I was watching a thread go on about, saw someone didn't get a job because of their shit posting and the employer didn't get it. And then someone on this side I'll hire the guy cuz I get that's highly intelligent shit posting. So for the audience that doesn't know what shit posting is, what is shit posting? >>It's more or less talking about the world of enter prize technology, which even that sentence is hard to finish without falling asleep and toppling out of my chair in front of everyone on the livestream. But it's doing it in such a way that brings it to life that says the quiet part. A lot of the audience is thinking, but generally doesn't say either because they're polite or not a jackass or more prosaically are worried about getting fired for better or worse. I don't don't have that particular constraint, >>Which is why people love you. So let's talk about what you, what you think is, uh, worthy and not worthy in the industry right now, obviously, uh, coupons coming up in Spain, which they're having a physical event, you see the growth of cloud native Amazon's of all the Adams, especially new CEO. Andy's move on to be the chief of all Amazon. Just so I'm the cover of was it time met magazine? Um, he's under a lot of stress. Amazon's changed. Invoice has changed. What's working. What's not, what's rising, what's falling. What's hot. What's not, >>It's easy to sit here and criticize almost anything. These folks do. They're they're effectively in a fishbowl, but I have trouble imagining the logistics. It takes to wind up handling the catering for a relatively downscale event like this one this year, let alone running a 1.7 million employee company having to balance all the competing challenges and pressures and the rest. I, I just can't fathom what it would be like to look at all of AWS. And it's, it's sprawling immense that dominates our entire industry and say, okay, this is a good start, but I, I wanna focus on something with a broader remit. What is that? How do you even get into that position? And you can't win once you're there. All you can do is hold onto the tiger and hope you don't get mold. >>Well, there's a lot of force for good conversations. Seeing a lot of that going on, Amazon's trying to port eight of us is trying to portray themselves as you know, the Pathfinder, you know, you're the pioneer, um, force for good. And I get that and I think that's a good angle as cloud goes mainstream. There's still the question of, we had a guy on just earlier, who was a skydiving instructor and we were joking about the early days of cloud. Like that was like skydiving, build a parachute open, you know, and now same kind of thing. As you move to edge, things are like reliable in some areas, but still new, new fringe, new areas. That's crazy. Well, >>Since the last time we've spoken, uh, Steve Schmidt is now the CISO for all of Amazon and his backfill replacement. The AWS CISO is CJ. Moses who as a hobby races, a as a semi-pro race car driver to my understanding, which either, I don't know what direction to take that in either. This is what he does to relax or ultimately, or ultimately it's. Huh? That, that certainly says something about risk assessment. I'm not entirely sure what, but okay. <laugh> either way, sounds like more exciting. Like I better >>Have a replacement ready <laugh> I, in case something goes wrong on the track, highly >>Available >>CSOs. I gotta say one of the things I do like in the recent trend is that the tech companies are getting into the formula one, which I was never a fan of until I watched that Netflix series. But when you look at the formula one, it's pretty cool. Cause it's got some tech angles, I get the whole data instrumentation thing, but the most coolest thing about formula one is they have these new rigs out. Yeah. Where you can actually race in east sports with other people in pure simulation of the race car. You gotta get the latest and videographic card, but it's basically a tricked out PC with amazing monitors and you have all the equipment of F1 and you're basically simulating racing. >>Oh, it's great too. And I can see the appeal of these tech companies getting into it because these things are basically rocket shifts. When those cars go, like they're sitting there, we can instrument every last part of what is going on inside that vehicle. And then AWS crops up. And we can bill on every one of those dimensions too. And it's like slow down their hasty pudding one step at a time. But I do see the appeal. >>So I gotta ask you about, uh, what's going on in your world. I know you have a lot of great success. We've been following you in the queue for many, many years. Got a great newsletter, check out Corey Quinn's newsletter, uh, screaming in the cloud program. Uh, you're on the cutting edge and you've got a great balance between really being snarky and, and, and really being delivering content. That's exciting, uh, for people, uh, with a little bit of an edge, um, how's that going? Uh, what's the blowback, any blowback late? Has there been uptick? What was, what are some of the things you're hearing from your audience, more Corey, more Corey. And then of course the, the PR team's calling you >>The weird thing about having an audience beyond a certain size is far and away as a landslide. The most common response I get is silence where it's high. I'm emailing an awful lot of people at last week in AWS every week and okay. They must not have heard me it. That is not actually true. People just generally don't respond to email because who responds to email newsletters. That sounds like something, a lunatic might do same story with response to live streams and podcasts. It's like, I'm gonna call into that am radio show and give them a piece of my mind. People generally don't do >>That. We should do that. Actually. I think you're people would call in, oh, >>I, I think >>I guarantee we had that right now. People would call in and say, Corey, what do you think about X? >>Yeah. It not, everyone understands the full context of what I do. And in fact, increasingly few people do and that's fine. I, I keep forgetting that sometimes people do not see what I'm doing in the same light that I do. And that's fine. Blowback has been largely minimal. Honestly, I am surprised about anything by how little I have gotten over the last five years of doing this, but it would be easier to dismiss me if I weren't generally. Right. When, okay, so you launch this new service and it seems pretty crappy to me cuz when I try and build something, it falls over and begs for help. And people might not like hearing that, but it's what customers are finding too. Yeah. I really am the voice of the >>Customer. You know, I always joke with Dave Alane about how John Fort's always at, uh, um, reinvent getting the interview with jazzy now, Andy we're there, you're there. And so we have these rituals at the events. It's all cool. Um, one of the rituals I like about your, um, your content is you like to get on the naming product names. Um, and, and, and, and, and kind of goof on that. Now why I like is because I used to work at ETT Packard where they used to name things as like engineers, HP 1 0, 0 5, or we can't call, we >>Have a new monitor. How are we gonna name it? Throw the wireless keyboard down the stairs again. And then there you go. Yeah. >>It's and the old joke at HP was if they, if they invented SU sushi, they'd say, yeah, we can't call sushi. It's cold, dead fish. That's what it is. And so the joke was cold. Dead fish is a better name than sushi. So you know is fun. So what's the, what are the, how's the Amazon doing in there? Have they changed their naming, uh, strategy, uh, on some of their, their >>Producting. So they're going in different directions. When they named Amazon Aurora, they decided to explore a new theme of Disney princesses as they go down those paths. And some things are more descriptive. Some people are clearly getting bonused on number of words, they can shove into it. Like the better a service is the longer it's name. Like AWS systems manager, session manager is a great one. I love the service ridiculous name. They have a systems manager, parameter store, which is great. They have secrets manager, which does the same thing. It's two words less, but that one costs money in a way that systems manage your parameter store does not. It's fun. >>What's your, what's your favorite combination of acronyms >>Combination >>Of gots. You got EMR, you got EC two, you got S3 SQS. Well, RedShift's not an acronym you >>Gets is one of my personal favorites because it's either elastic block store or elastic bean stock, depending entirely on the context of the conversation, they >>Shook up bean stock or is that still around? Oh, >>They never turn anything off. They're like the anti Google, Google turns things off while they're still building it. Whereas Amazon is like, well, we built this thing in 2005 and everyone hates it, but while we certainly can't change it, now it has three customers on it. John three <laugh>. Okay. Simple BV still haunts our dreams. >>I, I actually got an email on, I saw one of my, uh, servers, all these C twos were being deprecated and I got an email I'm I couldn't figure out. Why can you just like roll it over? Why, why are you telling me? Just like, give me something else. All right. Okay. So let me talk about, uh, the other things I want to ask you, is that like, okay. So as Amazon better in some areas where do they need more work in your opinion? Because obviously they're all interested in new stuff and they tend to like put it out there for their end to end customers. But then they've got ecosystem partners who actually have the same product. Yes. And, and this has been well documented. So it's, it's not controversial. It's just that Amazon's got a database Snowflake's got out database service. So Redshift, snowflake data breach is out there. So you got this co-op petition. Yes. How's that going? And what do you hearing about the reaction to any of that stuff? >>Depends on who you ask. They love to basically trot out a bunch of their partners who will say nice things about them. And it very much has heirs of, let's be honest, a hostage video, but okay. Cuz these companies do partner with, and they cannot afford to rock the boat too far. I'm not partnered with anyone. I can say what I want. And they're basically restricted to taking away my birthday at worse so I can live with that. >>All right. So I gotta ask about multicloud. Cause obviously the other cloud shows are coming up. Amazon hated that word multicloud. Um, a lot of people though saying, you know, it's not a real good marketing word. Like multicloud sounds like, you know, root canal. Mm-hmm <affirmative> right. So is there a better description for multicloud? >>Multiple single >>Cloudant loves that term. Yeah. >>You know, you're building in multiple single points of failure, do it for the right reasons or don't do it as a default. I believe not doing it is probably the right answer. However, and if I were, if I were Amazon, I wouldn't want to talk about my multi-cloud either as the industry leader, let's talk about other clouds, bad direction to go in from a market cap perspective. It doesn't end well for you, but regardless of what they want to talk about, or don't want to talk about what they say, what they don't say, I tune all of it out. And I look at what customers are doing and multi-cloud exists in a variety of forms. Some brilliant, some brain dead. It depends a lot on, but my general response is when someone gets on stage from a company and tells me to do a thing that directly benefits their company. I am skeptical at best. Yeah. When customers get on stage and say, this is what we're doing because it solves problems. That's when I shut up and listen. >>Yeah, course. Awesome. Corey, I gotta ask you a question cause I know you we've been, you know, fellow journeyman and the, and the cloud journey going to all the events and then the pandemic hit. We now in the third year, who knows what it's gonna gonna end. Certainly events are gonna look different. They're gonna be either changing footprint with the virtual piece, new group formations. Community's gonna emerge. You've got a pretty big community growing and it's growing like crazy. What's the weirdest or coolest thing or just big changes you've seen with the pandemic, uh, from your perspective, cuz you've been in the you're in the middle of the whitewater rafting. You've seen the events you circle offline. You saw the online piece, come in, you're commentating, you're calling balls and strikes in the industry. You got a great team developing over there. Duck build group. What's the big aha moment that you saw with the pandemic. Weird, funny, serious, real in the industry and with customers what's >>Accessibility. Reinvent is a great example. When in the before times it's open to anyone who wants to attend, who can pony up two grand and a week in Las Vegas and get to Las Vegas from wherever they happen to be by moving virtually suddenly it, it embraces the reality that talent is evenly. Distributed. Opportunity is not. And that means that suddenly these things are accessible to a wide swath of audience and potential customer base and the rest that hadn't been invited to the table previously, it's imperative that we not lose that. It's nice to go out and talk to people and have people come up and try and smell my hair from time to time, I smelled delightful. Let me assure you. But it was, but it's also nice to be. >>I have a product for you if you want, you know? Oh, >>Oh excellent. I look forward to it. What is it? Pudding? Why not? <laugh> >>What else have you seen? So when accessibility for talent. Yes. Which by the way is totally home run. What weird things have happened that you've seen? Um, that's >>Uh, it's, it's weird, but it's good that an awful lot of people giving presentation have learned to tighten their message and get to the damn point because most people are not gonna get up from a front row seat in a conference hall, midway through your Aing talk and go somewhere else. But they will change a browser tab and you won't get them back. You've gotta be on point. You've gotta be compelling if it's going to be a virtual discussion. Yeah. >>And you turn off your iMessage too. >>Oh yes. It's always fun in the, in the meetings when you're ho to someone and their colleague is messaging them about, should we tell 'em about this? And I'm sitting there reading it and it's >>This guy is really weird. Like, >>Yes I am and I bring it into the conversation and then everyone's uncomfortable. It goes, wow. Why >>Not? I love when my wife yells at me over I message. When I'm on a business call, like, do you wanna take that about no, I'm good. >>No, no. It's better off. I don't the only entire sure. It's >>Fine. My kids text. Yeah, it's fine. Again, that's another weird thing. And, and then group behavior is weird. Now people are looking at, um, communities differently. Yes. Very much so, because if you're fatigued on content, people are looking for the personal aspect. You're starting to see much more of like yeah. Another virtual event. They gotta get better. One and two who's there. >>Yeah. >>The person >>That's a big part of it too is the human stories are what are being more and more interesting. Don't get up here and tell me about your product and how brilliant you are and how you built it. That's great. If I'm you, or if I wanna work with you or I want to compete with you or I want to put on my engineering hat and build it myself. Cause why would I buy anything? That's more than $8. But instead, tell me about the problem. Tell me about the painful spot that you specialize in. Yeah. Tell me a story there. >>I, I think >>That gets a glimpse in a hook and makes >>More, more, I think you nailed it. Scaling storytelling. Yes. And access to better people because they don't have to be there in person. I just did a thing. I never, we never would've done the queue. We did. Uh, Amazon stepped up in sponsors. Thank you, Amazon for sponsoring international women's day, we did 30 interviews, APAC. We did five regions and I interviewed this, these women in Asia, Pacific eight, PJ, they call for in this world. And they're amazing. I never would've done those interviews cuz I never, would've seen 'em at an event. I never would've been in pan or Singapore, uh, to access them. And now they're in the index, they're in the network. They're collaborating on LinkedIn. So a threads are developing around connections that I've never seen before. Yes. Around the content. >>Absolutely >>Content value plus and >>Effecting. And that is the next big revelation of this industry is going to realize you have different companies. And, and I Amazon's case different service teams all competing with each other, but you have the container group and you have the database group and you have the message cuing group. But customers don't really want to build things from spare parts. They want a solution to a problem. I want to build an app that does Twitter for pets or whatever it is I'm trying to do. I don't wanna basically have to pick and choose and fill my shopping cart with all these different things. I want something that's gonna basically give me what I'm trying to get as close to turnkey as possible. Moving up the stack. That is the future. And just how it gets here is gonna be >>Well we're here at Corey Quinn, the master of the master of content here in the a ecosystem. Of course we we've been following up from the beginning. His great guy, check out his blog, his site, his newsletter screaming podcast. Corey, final question for, uh, what are you here doing? What's on your agenda this week in San Francisco and give a plug for the duck build group. What are you guys doing? I know you're hiring some people what's on the table for the company. What's your focus this week and put a plug in for the group. >>I'm here as a customer and basically getting outta my cage cuz I do live here. It's nice to actually get out and talk to folks who are doing interesting things at the duck bill group. We solved one problem. We fixed the horrifying AWS bill, both from engineering and architecture, advising as well as negotiating AWS contracts because it turns out those things are big and complicated. And of course my side media projects last week in aws.com, we are, it it's more or less a content operation where I in my continual and ongoing love affair with the sound of my own voice. >><laugh> and you're good. It's good content it's on, on point fun, Starky and relevant. So thanks for coming to the cube and sharing with us. Appreciate it. No >>Thank you button. >>You. Okay. This the cube covers here in San Francisco, California, the cube is back going to events. These are the summits, Amazon web services summits. They happen all over the world. We'll be in New York and obviously we're here in San Francisco this week. I'm John fur. Keep, keep it right here. We'll be back with more coverage after this short break. Okay. Welcome back everyone. This's the cubes covers here in San Francisco, California, we're live on the show floor of AWS summit, 2022. I'm John for host of the cube and remember AWS summit in New York city coming up this summer, we'll be there as well. And of course reinvent the end of the year for all the cube coverage on cloud computing and AWS two great guests here from the APN global APN Sege chef Jenko and Jeff Grimes partner lead Jeff and Sege is doing partnerships global APN >>AWS global startup program. Yeah. >>Okay. Say that again. >>AWS. We'll start >>Program. That's the official name. >>I love >>It too long, too long for me. Thanks for coming on. Yeah, >>Of course. >>Appreciate it. Tell us about what's going on with you guys. What's the, how was you guys organized? You guys we're obviously we're in San Francisco bay area, Silicon valley, zillions of startups here, New York. It's got another one we're gonna be at tons of startups. A lot of 'em getting funded, big growth and cloud big growth and data secure hot in all sectors. >>Absolutely. >>So maybe, maybe we could just start with the global startup program. Um, it's essentially a white glove service that we provide to startups that are built on AWS. And the intention there is to help identify use cases that are being built on top of AWS. And for these startups, we want to pro vibe white glove support in co building products together. Right. Um, co-marketing and co-selling essentially, um, you know, the use cases that our customers need solved, um, that either they don't want to build themselves or are perhaps more innovative. Um, so the, a AWS global startup program provides white glove support. Dedicat at headcount for each one of those pillars. Um, and within our program, we've also provided incentives, programs go to market activities like the AWS startup showcase that we've built for these startups. >>Yeah. By the way, AWS startup, AWS startups.com is the URL, check it out. Okay. So partnerships are key. Jeff, what's your role? >>Yeah. So I'm responsible for leading the overall effort for the AWS global startup program. Um, so I've got a team of partner managers that are located throughout the us, uh, managing a few hundred startup ISVs right now. <laugh> >>Yeah, you got a >>Lot. We've got a lot. >>There's a lot. I gotta, I gotta ask a tough question. Okay. I'm I'm a startup founder. I got a team. I just got my series a we're grown. I'm trying to hire people. I'm super busy. What's in it for me. Yeah. What do you guys bring to the table? I love the white glove service, but translate that what's in it for what do I get out of it? What's >>A story. Good question. I focus, I think. Yeah, because we get, we get to see a lot of partners building their businesses on AWS. So, you know, from our perspective, helping these partners focus on what, what do we truly need to build by working backwards from customer feedback, right? How do we effectively go to market? Because we've seen startups do various things, um, through trial and error, um, and also just messaging, right? Because oftentimes partners or rather startups, um, try to boil the ocean with many different use cases. So we really help them, um, sort of laser focus on what are you really good at and how can we bring that to the customer as quickly as possible? >>Yeah. I mean, it's truly about helping that founder accelerate the growth of their company, right. And there's a lot that you can do with AWS, but focus is truly the key word there because they're gonna be able to find their little piece of real estate and absolutely deliver incredible outcomes for our customers. And then they can start their growth curve there. >>What are some of the coolest things you've seen with the APN that you can share publicly? I know you got a lot going on there, a lot of confidentiality. Um, but you know, we're here a lot of great partners on the floor here. I'm glad we're back at events. Uh, a lot of stuff going on digitally with virtual stuff and, and hybrid. What are some of the cool things you guys have seen in the APN that you can point to? >>Yeah, absolutely. I mean, I can point to few, you can take them. So, um, I think what's been fun over the years for me personally, I came from a startup brand sales at an early stage startup and, and I went through the whole thing. So I have a deep appreciation for what these guys are going through. And what's been interesting to see for me is taking some of these early stage guys, watching them progress, go public, get acquired and see that big day mm-hmm <affirmative>, uh, and being able to point to very specific items that we help them to get to that point. Uh, and it's just a really fun journey to watch. >>Yeah. I, and part of the reason why I really, um, love working at the AWS, uh, global startup program is working with passionate founders. Um, I just met with a founder today that it's gonna, he's gonna build a very big business one day, um, and watching them grow through these stages and supporting that growth. Um, I like to think of our program as a catalyst for enterprise is sort of scale. Yeah. Um, and through that we provide visibility, credibility and growth opportunities. >>Yeah. A lot, a lot of partners too. What I found talking to staff founders is when they have that milestone, they work so hard for it. Whether it's a B round C round Republic or get bought. Yeah. Um, then they take a deep breath and they look back at wow, what a journey it's been. So it's kind of emotional for sure. But still it's a grind. Right? You gotta, I mean, when you get funding, it's still day one. You don't stop. It's no celebrate, you got a big round or valuation. You still gotta execute >>And look it's hypercompetitive and it's brutally difficult. And our job is to try to make that a little less difficult and navigate those waters. Right. Where ever everyone's going after similar things. >>Yeah. And I think as a group element too, I observe that startups that I, I meet through the APN has been interesting because they feel part of AWS. Yeah, totally. As a group of community, as a vibe there. Um, I know they're hustling, they're trying to make things happen. But at the same time, Amazon throws a huge halo effect. I mean, that's a huge factor. I mean, you guys are the number one cloud in the business, the growth in every sector is booming. Yeah. And if you're a startup, you don't have that luxury yet. And look at companies like snowflake that built on top of AWS. I mean, people are winning by building on AWS. >>Yeah. And our, our, our program really validates their technology first. So we have, what's all the foundation's technical review that we put all of our startups through before we go to market. So that when enterprise customers are looking at startup technology, they know that it's already been vetted. And, um, to take that a step further and help these partners differentiate, we use programs like the competency programs, the DevOps competencies, the security competency, which continues to help, um, provide sort of a platform for these startups, help them differentiate. And also there's go to market benefits that are associated with that. >>Okay. So let me ask the, the question that's probably on everyone's mind, who's watching, certainly I asked this a lot. There's a lot of companies startups out there who makes the cut, is there a criteria cut? It's not like it's sports team or anything, but like sure. Like there's activate program, which is like, there's hundreds of thousands of startups out there. Not everyone is at the APN. Right? Correct. So ISVs again, that's a whole nother, that's a more mature partner that might have, you know, huge market cap or growth. How, how do you guys focus? How do you guys focus? I mean, you got a good question, you know, thousand flowers blooming all the time. Is there a new way you guys are looking at it? I know there's been some talk about restructure or, or new focus. What's the focus. >>Yeah. It's definitely not an easy task by any means. Um, but you know, I recently took over this role and we're really trying to establish focus areas, right. So obviously a lot of the ISVs that we look after are infrastructure ISVs. That's what we do. Uh, and so we have very specific pods that look after different type of partners. So we've got a security pod, we've got a DevOps pod, we've got core infrastructure, et cetera. And really, we're trying to find these ISVs that can solve, uh, really interesting AWS customer. >>You guys have a deliberate, uh, focus on these pillars. So what infrastructure, >>Security, DevOps, and data and analytics, and then line of business >>Line, business line business, like web >>Marketing, business apps, >>Owner type thing. Exactly. >>Yeah, exactly. >>So solutions there. Yeah. More solutions and the other ones are like hardcore. So infrastructure as well, like storage back up ransomware kind of stuff, or, >>Uh, storage, networking. >>Okay. Yeah. The classic >>Database, et cetera. Right. >>And so there's teams on each pillar. >>Yep. So I think what's, what's fascinating for the startups that we cover is that they've got, they truly have support from a build market sell perspective, right. So you've got someone who's technical to really help them get the technology, figured out someone to help them get the marketing message dialed and spread, and then someone to actually do the co-sell, uh, day to day activities to help them get in front of customers. >>Probably the number one request that we always ask for Amazon is can wish that sock report, oh, download it on the console, which we use all the time. <laugh> exactly. But security's a big deal. I mean, you know, ask the res are evolving, that role of DevOps is taking on dev SecOps. Um, I, I can see a lot of customers having that need for a relationship to move things faster. Do you guys provide like escalation or is that a part of a service or that not part of, uh, uh, >>Yeah, >>So the partner development manager can be an escalation for absolutely. Think of that. 'em as an extension of your business inside of AWS. >>Great. And you guys, how is that partner managers, uh, measure >>On those three pillars? Right. Got it. Are we billing, building valuable use cases? So product development go to market, so go to market activities, think blog, posts, webinars, case studies, so on and so forth. And then co-sell not only are we helping these partners win their current opportunities that they are sourcing, but can we also help them source net new deals? Yeah. Right. That's very, >>I mean, top asked from the partners is get me in front of customers. Right. Um, not an easy task, but that's a huge goal of ours to help them grow their top line. >>Right. Yeah. In fact, we had some interviews here on the cube earlier talking about that dynamic of how enterprise customers are buying. And it's interesting, a lot more POCs. I have one partner here that you guys work with, um, on observability, they got a huge POC with capital one mm-hmm <affirmative> and the enterprises are engaging the star ups and bringing them in. So the combination of open source software enterprises are leaning into that hard and bringing young growing startups in mm-hmm <affirmative>. Yep. So I could see that as a huge service that you guys can bring people in. >>Right. And they're bringing massively differentiated technology to the table. The challenge is they just might not have the brand recognition. The, at the big guys have mm-hmm <affirmative>. And so that's, our job is how do you get that great tech in front of the right situations? >>Okay. So my next question is about the show here, and then we'll talk globally. So here in San Francisco sure. You know, Silicon valley bay area, San Francisco bay area, a lot of startups, a lot of VCs, a lot of action. Mm-hmm <affirmative> so probably a big market for you guys. Yeah. So what's exciting here in SF. And then outside of SF, you guys have a global pro, have you see any trends that are geography based or is it sure areas more mature? There's certain regions that are better. I mean, I just interviewed a company here. That's doing, uh, a AWS edge really well in these cases. It's interesting that these, the partners are filling a lot of holes and gaps in the opportunities with a AWS. So what's exciting here. And then what's the global perspective. >>Yeah, totally. So obviously see a ton of partners from the bay area that we support. Um, but we're seeing a lot of really interesting technology come out of AMEA specifically. Yeah. Uh, and making a lot of noise here in the United States, which is great. Um, and so, you know, we definitely have that global presence and, and starting to see super differentiated technology come out of those regions. >>Yeah. Especially Tel Aviv. Yeah. >>Amy and real quick before you get into surge. It's interesting. The VC market in, in Europe is hot. They've got a lot of unicorns coming in. We've seen a lot of companies coming in. They're kind of rattling their own, you know, cage right now. Hey, look at us. Let's see if they crash, you know, but we don't see that happening. I mean, people have been predicting a crash now in, in the startup ecosystem for least a year. It's not crashing. In fact, funding's up. >>Yeah. The pandemic was hard on a lot of startups for sure. Yeah. Um, but what we've seen is many of these startups, they, as quickly as they can grow, they can also pivot as, as, as well. Um, and so I've actually seen many of our startups grow through the demo because their use cases are helping customers either save money, become more operationally efficient and provide value to leadership teams that need more visibility into their infrastructure during a pandemic. >>It's an interesting point. I talked to Andy jazzy and Adam Celski both say the same thing during the pandemic. Necessity's the mother of all invention. Yep. And startups can move fast. So with that, you guys are there to assist if I'm a startup and I gotta pivot cuz remember iterate and pivot, iterate and pivot. So you get your economics, that's the playbook of the ventures and the models. >>Exactly. How >>Do you guys help me do that? Give me an example of what me through. Pretend me, I'm a start up. Hey, I'm on the cloud. Oh my God. Pandemic. They need video conferencing. Hey cube. Yeah. What do I need? Search? What, what do >>I do? That's a good question. First thing is just listen. Yeah. I think what we have to do is a really good job of listening to the partner. Um, what are their needs? What is their problem statement? Where do they want to go at the end of the day? Um, and oftentimes because we've worked with, so how many successful startups that have come out of our program, we have, um, either through intuition or a playbook determined what is gonna be the best path forward and how do we get these partners to stop focusing on things that will eventually, um, just be a waste of time. Yeah. And, or not provide, or, you know, bring any fruit to the table, which, you know, essentially revenue. >>Well, we love startups here in the cube because one, um, they have good stories, they're oil and cutting edge, always pushing the envelope and they're kind of disrupting someone else. Yeah. And so they, they have an opinion. They don't mind sharing on camera. So love talking to startups. We love working with you guys on our startups. Showcases startups.com. Check out AWS startups.com and she got the showcase. So is, uh, final word. I'll give you guys the last word. What's the bottom line bumper sticker for AP globe. The global APN program summarize the opportunity for startups, what you guys bring to the table and we'll close it out. Totally. We'll start >>With you. Yeah. I think the AWS global startup programs here to help companies truly accelerate their business full stop. Right. And that's what we're here for. Love it. >>It's a good way to, it's a good way to put it. Dato yeah. >>All right. Thanks for coming out. Thanks John. Great to see you love working with you guys. Hey, startups need help. And the growing and huge market opportunities, the shift cloud scale data engineering, security infrastructure, all the markets are exploding in growth because of the digital transformation of realities here, open source and cloud. I'll making it happen here in the cube in San Francisco, California. I'm John furrier, your host. Thanks for >>Watching Cisco, John. >>Hello and welcome back to the Cube's live coverage here in San Francisco, California for AWS summit, 2022. I'm John for host of the cube. Uh, two days of coverage, AWS summit, 2022 in New York city coming up this summer will be there as well. Events are back. The cube is back of course, with the cube virtual cube hybrid, the cube.net. Check it out a lot of content this year more than ever a lot more cloud data cloud native, modern applic is all happening. Got a great guest here. Jeremy Burton, Cub alumni, uh, CEO of observe Inc in the middle of all the cloud scale, big data observability, Jeremy. Great to see you. Thanks. >>Coming on. Always great to come and talk to you on the queue, man. It's been been a few years, so, >>Um, well you, you got your hands. You're in the trenches with great startup, uh, good funding, great board, great people involved in the observability Smith hot area, but also you've been a senior executive president of Dell EMC. Um, 11 years ago you had a vision and you actually had an event called cloud meets big data. Um, yeah. And it's here, you predicted it 11 years ago. Um, look around it's cloud meets big data. >>Yeah. I mean the, the cloud thing I think, you know, was, was probably already a thing, but the big data thing I do claim credit for, for sort of catching that bus early, um, you know, we, we were on the, the, the bus early and, and I think it was only inevitable. Like, you know, if you could bring the economics and the compute of cloud to big data, you, you could find out things you could never possibly imagine. >>So you're close to a lot of companies that we've been covering deeply snowflake, obviously you involved, uh, at the board level, the other found, you know, the people there, uh, cloud, you know, Amazon, you know, what's going on here? Yeah. You're doing a startup as the CEO at the helm, uh, chief of observ, Inc, which is an observability, which is to me in the center of this confluence of data engineering, large scale integrations, um, data as code integrating into applications. I mean, it's a whole nother world developing, like you see with snowflake, it means snowflakes is super cloud as we call it. So a whole nother wave is here. What's your, what's this wave we're on what's how would you describe the wave? >>Well, a couple of things, I mean, people are, I think right in more software than, than ever before are why? Because they've realized that if, if you don't take your business online and offer a service, then you become largely irrelevant. And so you you've got a whole set of new applications. I think, I think more applications now than any point. Um, not, not just ever, but the mid nineties, I always looked at as the golden age of application development. Now, back then people were building for windows. Well, well now they're building for things like AWS is now the platform. Um, so you've got all of that going on. And then at the same time, the, the side effect of these applications is they generate data and lots of data. And the, you know, there's sort of the transactions, you know, what you bought today are something like that. But then there's what we do, which is all the telemetry, all the exhaust fumes. And I think people really are realizing that their differentiation is not so much their application. It's their understanding of the data. Can, can I understand who my best customers are, what I sell today. If people came to my website and didn't buy, then why not? Where did they drop off all of that? They wanna analyze. And, and the answers are all in the data. The question is, can you understand it >>In our last startup showcase, we featured data as code one of the insights that we got out of that, and I wanna get your opinion on our reaction to is, is that data used to be put into a data lake and turns into a data swamp or throw into the data warehouse. And then we'll do some queries, maybe a report once in a while. And so data, once it was done, unless it was real time, even real time was not good anymore after real time. That was the old way. Now you're seeing more and more, uh, effort to say, let's go look at the data, cuz now machine learning is getting better. Not just train once mm-hmm <affirmative> they're iterating. Yeah. This notion of iterating and then pivoting, iterating and pivoting. Yeah, that's a Silicon valley story. That's like how startups work, but now you're seeing data being treated the same way. So now you have another, this data concept that's now yeah. Part of a new way to create more value for the apps. So this whole, this whole new cycle of >>Yeah. >>Data being reused and repurposed and figured out and yeah, >>Yeah. I'm a big fan of, um, years ago. Uh, uh, just an amazing guy, Andy McAfee at the MIT C cell labs I spent time with and he, he had this line, which still sticks to me this day, which is look I'm I'm. He said I'm part of a body, which believes that everything is a matter of data. Like if you have enough data, you can answer any question. And, and this is going back 10 years when he was saying these kind of things and, and certainly, you know, research is on the forefront. But I think, you know, starting to see that mindset of the, the sort of MIT research be mainstream, you know, in enterprises, they they're realizing that. Yeah, it is about the data. You know, if I can better understand my data better than my competitor, then I've got an advantage. And so the question is is, is how, what, what technologies and what skills do I need in my organization to, to allow me to do that. >>So let's talk about observing you the CEO of, okay. Given you've seen the ways before you're in the front lines of observability, which again is in the center of all this action what's going on with the company. Give a quick minute to explain, observe for the folks who don't know what you guys do. What's the company doing? What's the funding status, what's the product status and what's the customer status. Yeah. >>So, um, we realized, you know, a handful of years ago, let's say five years ago that, um, look, the way people are building applications is different. They they're way more functional. They change every day. Uh, but in some respects they're a lot more complicated. They're distributed. They, you know, microservices architectures and when something goes wrong, um, the old way of troubleshooting and solving problems was not gonna fly because you had SA so much change going into production on a daily basis. It was hard to tell like where the problem was. And so we thought, okay, it's about time. Somebody looks at the exhaust fumes from this application and all the telemetry data and helps people troubleshoot and make sense of the problems that they're seeing. So, I mean, that's observability, it's actually a term that goes back to the 1960s. It was a guy called, uh, Rudolph like, like everything in tech, you know, it's, it's a reinvention of something from years gone by. >>Um, there's a guy called, um, Rudy Coleman in 1960s coiner term and, and, and the term was being able to determine the state of a system by looking at its external outputs. And so we've been going on this for, uh, the best part of four years now. Um, it took us three years just to build the product. I think, I think what people don't appreciate these days often is the barrier to entry in a lot of these markets is quite high. You, you need a lot of functionality to have something that's credible with a customer. Um, so yeah, this last year we, we, we did our first year selling, uh, we've got about 40 customers now. Um, we just we've got great investors for the hill ventures. Uh, I mean, Mike SP who was, you know, the, the guy who was the, really, the first guy in it snowflake and the, the initial investor were fortunate enough to, to have Mike and our board. And, um, you know, part of the observed story is closely knit with snowflake all of that time with your data, you know, we, we store in there. >>So I want to get, uh, yeah. Pivot to that. Mike SP snowflake, Jeremy Burton, the cube kind of, kind of same thinking this idea of a super cloud or what snowflake became. Yeah. Snowflake is massively successful on top of AWS. Mm-hmm <affirmative> and now you're seeing startups and companies build on top of snowflake. Yeah. So that's become an entrepreneurial story that we think that to go big in the cloud, you can have a cloud on a cloud, uh, like as Jerry, Jerry Chan and Greylock calls it, castles in the cloud where there are moats in the cloud. So you're close to it. I know you, you're doing some stuff with snowflake. So as a startup, what's your view on building on top of say a snowflake or an AWS, because again, you gotta go where the data is. You need all the data. >>Yeah. So >>What's your take on that? I mean, >>Having enough gray hair now, um, you know, again, in tech, I think if you wanna predict the future, look at the past. And, uh, you know, 20 years ago, 25 years ago, I was at a, a smaller company called Oracle and an Oracle was the database company. And, uh, their, their ambition was to manage all of the world's transactional data. And they built on a platform or a couple of platforms, one, one windows, and the other main one was Solaris. And so at that time, the operating system was the platform. And, and then that was the, you know, ecosystem that you would compete on top of. And then there were companies like SAP that built applications on top of Oracle. So then wind the clock forward 25 years gray hairs. <laugh> the platform, isn't the operating system anymore. The platform is AWS, you know, Google cloud. I gotta probably look around if I say that in. Yeah, >>It's okay. Columbia, but hyperscale. Yeah. CapX built out >>That is the new platform. And then snowflake comes along. Well, their aspiration is to manage all of the, not just human generated data, but machine generated data in the world of cloud. And I think they they've done an amazing job are doing for the, I'd say, say the, the big data world, what Oracle did for the relational data world, you know, way back 25 years ago. And then there are folks like us come along and, and of course my ambition would be, look, if, if we can be as successful as an SAP building on top of snowflake, uh, as, as they were on top of Oracle, then, then we'd probably be quite happy, >>Happy. So you're building on top of snowflake, >>We're building on top of snowflake a hundred percent. And, um, you know, I've had folks say to me, well, aren't you worried about that? Isn't that a risk? It's like, well, that that's a risk. You're >>Still on the board. >>Yeah. I'm still on the board. Yeah. That's a risk I'm prepared to take. I am more on snowing. >>It sounds well, you're in a good spot. Stay on the board, then you'll know what's going on. Okay. No, yeah. Serious one. But the, this is a real dynamic. It is. It's not a one off its >>Well, and I do believe as well that the platform that you see now with AWS, if you look at the revenues of AWS is in order of magnitude, more than Microsoft was 25 years ago with windows mm-hmm <affirmative>. And so I've believe the opportunity for folks like snowflake and, and folks like observe it. It's an order of magnitude more than it was for the Oracle and the SAPs of the old world. >>Yeah. And I think this is really, I think this is something that this next generation of entrepreneurship is the go big scenario is you gotta be on a platform. Yeah. >>It's quite easy >>Or be the platform, but it's hard. There's only like how seats were at that table left >>Well value migrates up over time. So, you know, when the cloud thing got going, there were probably 10, 20, 30, you know, rack space and there's 1,000,001 infrastructure, a service platform as a service. My, my old, uh, um, employee EMC, we had pivotal, you know, pivotal was a platform as a service. Don't hear so much about it these days, but initially there's a lot of players and then it consolidates. And then to, to like extract, uh, a real business, you gotta move up, you gotta add value, you gotta build databases, then you gotta build applications. So >>It's interesting. Moving from the data center of the cloud was a dream for starters within if the provision, the CapEx. Yeah. Now the CapEx is in the cloud. Then you build on, on top of that, you got snowflake. Now you got on top of that. >>The assumption is almost that compute and storage is free. I know it's not quite free. Yeah. It's almost free, but you can, you know, as an application vendor, you think, well, what can I do if I assume compute and storage is free, that's the mindset you've gotta get >>Into. And I think the platform enablement to value. So if I'm an entrepreneur, I'm gonna get a series us multiple of value in what I'm paying. Yeah. Most people don't even blanket their Avis pills unless they're like massively huge. Yeah. Then it's a repatriation question or whatever discount question, but for most startups or any growing company, the Amazon bill should be a small factor. >>Yeah. I mean, a lot of people, um, ask me, uh, like, look you build in on snowflake. Um, you, you know, you, you, you're gonna be, you're gonna be paying their money. How, how, how, how does that work with your business model? If you're paying their money, you know, do, do you have a viable business? And it's like, well, okay. I, we could build a database as well and observe, but then I've got half the development team working on something that will never be as good as snowflake. And so we made the call early on that. No, no, we, we want a eight above the database. Yeah. Right. Snowflake are doing a great job of innovating on the database and, and the same is true of something like Amazon, like, like snowflake could have built their own cloud and their own platform, but they didn't. >>Yeah. And what's interesting is that Dave <inaudible> and I have been pointing this out and he's obviously a more on snowflake. I've been looking at data bricks, um, and the same dynamics happening, the proof is the ecosystem. Yeah. I mean, if you look at Snowflake's ecosystem right now and data bricks it's exploding. Right. I mean, the shows are selling out the floor. Space's book. That's the old days at VMware. Yeah. The old days at AWS. >>Well, and for snowflake and, and any platform from VI, it's a beautiful thing because, you know, we build on snowflake and we pay them money. They don't have to sell to us. Right. And we do a lot of the support. And so the, the economics work out really, really well. If you're a platform provider and you've got a lot of >>Ecosystems. Yeah. And then also you get, you get a, um, a trajectory of, uh, economies of scale with the institutional knowledge of snowflake integrations, right. New product, you're scaling a step function with them. >>Yeah. I mean, we manage 10 petabytes of data right now. Right. When I, when I, when I arrived at EMC in 2010, we had, we had one petabyte customer. And, and so at observe, we've been only selling the product for a year. We have 10 petabytes of data under management. And so been able to rely on a platform that can manage that is inve >>You know, well, Jeremy great conversation. Thanks for sharing your insights on the industry. Uh, we got a couple minutes left, um, put a plug in for observe. What do you guys know? You got some good funding, great partners. I don't know if you can talk about your, your, your POC customers, but you got a lot of high ends folks that are working with you. You getting in traction. >>Yeah. Yeah. Scales >>Around the corner. Sounds like, are you, is that where you are scale? >>We've got a big that that's when coming up in two or three weeks, we've got, we've got new funding, um, which is always great. Um, the product is, uh, really, really close. I think, as a startup, you always strive for market fit, you know, which is at which point can you just start hiring salespeople? And the revenue keeps going. We're getting pretty close to that right now. Um, we've got about 40 SaaS companies that run on the platform. They're almost all AWS Kubernetes, uh, which is our sweet spot to begin with, but we're starting to get some really interesting, um, enterprise type customers. We're, we're, you know, F five networks we're POC in right now with capital one, we got some interest in news around capital one coming up. I, I can't share too much, but it's gonna be exciting. And, and like I said, so hill continue to, to, >>I think capital one's a big snowflake customer as well. Right. >>They were early in one of the things that attracted me to capital one was they were very, very good with snowflake early on. And, and they put snowflake in a position in the bank where they thought that snowflake could be successful. And, and today that, that is one of Snowflake's biggest accounts, >>Capital, one, very innovative cloud, obviously Atos customer, and very innovative, certainly in the CISO and CIO, um, on another point on where you're at. So you're, Prescale meaning you're about to scale, >>Right? >>So you got POCs, what's that trajectory look like? Can you see around the corner? What's, what's going on? What's on, around the corner. That you're, that you're gonna hit this straight and narrow and, and gas it fast. >>Yeah. I mean, the, the, the, the key thing for us is we gotta get the product. Right. Um, the nice thing about having a guy like Mike Pfizer on the board is he doesn't obsess about revenue at this stage. His questions that the board are always about, like is the product, right? Is the product right? Is the product right? Have you got the product right? And cuz we know when the product's right, we can then scale the sales team and, and the revenue will take care of itself. Yeah. So right now all the attention is on the product. Um, the, this year, the exciting thing is we we're, we're adding all the tracing visualizations. So people will be able to the kind of things that by in the day you could do with the new relics and AppDynamics, the last generation of, of APM tools, you're gonna be able to do that within observe. And we've already got the logs and the metrics capability in there. So for us this year is a big one, cuz we sort of complete the trifecta, you know, the, the >>Logs, what's the secret sauce observe. What if you had the, put it into a, a, a sentence what's the secret sauce? >>I, I, I think, you know, an amazing founding engineering team, uh, number one, I mean, at the end of the day, you have to build an amazing product and you have to solve a problem in a different way. And we've got great long term investors and, and the biggest thing our investors give is it actually, it's not just money. It gives us time to get the product, right. Because if we get the product right, then we can get the growth. >>Got it. Final question. While I got you here, you've been on the enterprise business for a long time. What's the buyer landscape out there. You got people doing POCs on capital one scale. So we know that goes on. What's the appetite at the buyer side for startups and what are their requirements that you're seeing? Uh, obviously we're seeing people go in and dip into the startup pool because new ways to refactor their, this restructure. So, so a lot of happening in cloud, what's the criteria. How are enterprises engaging in with startups? >>Yeah. I mean, enterprises, they know they've gotta spend money transforming the business. I mean, this was, I almost feel like my old Dell or EMC self there, but, um, what, what we were saying five years ago is happening. Um, everybody needs to figure out a way to take their business to this digital world. Everybody has to do it. So the nice thing from a startup standpoint is they know at times they need to risk or, or take a bet on new technology in order to, to help them do that. So I think you've got buyers that a have money, uh, B it prepared to take risks and it's, it's a race against time to you'll get their, their offerings in this, a new digital footprint. >>Final, final question. What's the state of AWS. Where do you see them going next? Obviously they're continuing to be successful. How does cloud 3.0, or they always say it's day one, but it's more like day 10, but what's next for Aw. Where do they go from here? Obviously they're doing well. They're getting bigger and bigger. Yeah, >>Better. It's an amazing story. I mean, you know, we're, we're on AWS as well. And so I, I think if they keep nurturing the builders and the ecosystem, then that is their superpower. They, they have an early leads. And if you look at where, you know, maybe the likes of Microsoft lost the plot in the, in the late nineties, it was, they stopped, uh, really caring about developers in the folks who were building on top of their ecosystem. In fact, they started buying up their ecosystem and competing with people in their ecosystem. And I see with AWS, they, they have an amazing headstart and if they did more, you know, if they do more than that, that's, what's gonna keep this juggernaut rolling for many years to come. >>Yeah. They got the Silicon and got the stack. They're developing Jeremy Burton inside the cube, great resource for commentary, but also founding with the CEO of a company called observing in the middle of all the action on the board of snowflake as well. Um, great startup. Thanks for coming on the cube. Always a pleasure. Okay. Live from San Francisco. It's to cube. I'm John for your host. Stay with us more coverage from San Francisco, California after the short break. >>Hello. Welcome back to the cubes coverage here live in San Francisco, California. I'm John furrier, host of the cubes cube coverage of AWS summit 2022 here in San Francisco. We're all the developers are the bay air at Silicon valley. And of course, AWS summit in New York city is coming up in the summer. We'll be there as well. SF and NYC cube coverage. Look for us. Of course, reinforcing Boston and re Mars with the whole robotics, AI. They all coming together. Lots of coverage stay with us today. We've got a great guest from Bel VC. John founding partner, entrepreneurial venture is a venture firm. Your next act, welcome to the cube. Good to see you. >>Good to see you, man. I feel like it's been forever since we've been able to do something in person. Well, >>I'm glad you're here because we run into each other all the time. We've known each other for over decade. Um, >>It's been at least 10 years, >>At least 10 years more. And we don't wanna actually go back as bring back the old school web 1.0 days. But anyway, we're in web three now. So we'll get to that in a second. We, >>We are, it's a little bit of a throwback to the path though, in my opinion, >>It's all the same. It's all distributed computing and software. We ran each other in cube con. You're investing in a lot of tech startup founders. Okay. This next level, next gen entrepreneurs have a new makeup and it's software. It's hardcore tech in some cases, not hardcore tech, but using software to take an old something old and make it better new, faster. So tell us about Bel what's the firm. I know you're the founder, uh, which is cool. What's going on. Explain >>What you, I mean, you remember I'm a recovering entrepreneur, right? So of course I, I, >>No, you're never recovering. You're always entrepreneur >>Always, but we are also always recovering. So I, um, started my first company when I was 24. If you remember, before there was Facebook and friends, there was instant messaging. People were using that product at work every day, they were creating a security vulnerability between their network and the outside world. So I plugged that hole and built an instant messaging firewall. It was my first company. The company was called IM logic and we were required by Symantec. Uh, then spent 12 years investing in the next generation of software companies, uh, early investor in open source companies and cloud companies and spent a really wonderful years, uh, at a firm called NEA. So I, I feel like my whole life I've been either starting enterprise software companies or helping founders start enterprise software companies. And I'll tell you, there's never been a better time than right now to start an enterprise software company. >>So, uh, the passion for starting a new firm was really a recognition that founders today that are starting an enterprise software company, they, they tend to be, as you said, a more technical founder, right? Usually it's a software engineer or a builder mm-hmm <affirmative>, uh, they are building that are serving a slightly different market than what we've traditionally seen in enterprise software. Right? I think traditionally we've seen it buyers or CIOs that have agendas and strategies, which, you know, purchase software that is traditionally bought and sold tops down. But you know, today I think the most successful enterprise software companies are the ones that are built more bottoms up and have more technical early adopters. And generally speaking, they're free to use. They're free to try. They're very commonly community source or open source companies where you have a large technical community that's supporting them. So there's a, there's kind of a new normal now I think in great enterprise software. And it starts with great technical founders with great products and great bottoms of motions. And I think there's no better place to, uh, service those people than in the cloud and uh, in, in your community. >>Well, first of all, congratulations, and by the way, you got a great pedigree and great background. You're super smart admire of your work and your, and, and your founding, but let's face it. Enterprise is hot because digital transformation is, is all companies there's no, I mean, consumer is enterprise now. Everything is what was once a niche, not, I won't say niche category, but you know, not for the faint of heart, you know, investors, >>You know, it's so funny that you say that enterprise is hot because you, and I feel that way now. But remember, like right now, there's also a giant tech in VC conference in Miami <laugh> and it's covering cryptocurrencies and FCS and web three. So I think beauty is definitely in the eye of the beholder <laugh> but no, I, I will tell you, well, >>MFTs is one big enterprise, cuz you gotta have imutability you got performance issues. You have, I IOPS issues. >>Well, and, and I think all of us here that are of may, maybe students of his stream have been involved in open source in the cloud would say that we're, you know, much of what we're doing is, uh, the predecessors of the web web three movement. And many of us I think are contributors to the web three >>Movement. The hype is definitely web >>Three. Yeah. But, >>But you know, >>For sure. Yeah, no, but now you're taking us further east to Miami. So, uh, you know, look, I think, I, I think, um, what is unquestioned with the case and maybe it's, it's more obvious the more time you spend in this world is this is the fastest growing part of enterprise software. And if you include cloud infrastructure and cloud infrastructure spend, you know, it is by many measures over, uh, $500 billion in growing, you know, 20 to 30 a year. So it it's a, it's a just incredibly fast >>Let's getting, let's get into some of the cultural and the, the shifts that are happening, cuz again, you, you have the luxury of being in enterprise when it was hard, it's getting easier and more cooler. I get it and more relevant <laugh> but there's also the hype of like the web three, for instance, but you know, for, uh, um, um, the CEO snowflake, okay. Has wrote a book and Dave Valenti and I were talking about it and uh, Frank Lutman has says, there's no playbooks. We always ask the CEOs, what's your playbook. And he's like, there's no playbook, situational awareness, always Trump's playbooks. So in the enterprise playbook, oh, hire a direct sales force and sass kind of crushed that now SAS is being redefined, right. So what is SAS? Is snowflake a SAS or is that a platform? So again, new unit economics are emerging, whole new situation, you got web three. So to me there's a cultural shift, the young entrepreneurs, the, uh, user experience, they look at Facebook and say, ah, you know, and they own all my data. And you know, we know that that cliche, um, they, you know, the product. So as this next gen, the gen Z and the millennials come in and our customers and the founders, they're looking at things a little bit differently and the tech better. >>Yeah. I mean, I mean, I think we can, we can see a lot of commonalities across all six of startups and the overall adoption of technology. Uh, and, and I would tell you, this is all one big giant revolution. I call it the user driven revolution. Right. It's the rise of the user. Yeah. And you might say product like growth is currently the hottest trend in enterprise software. It's actually user like growth, right. They're one in the same. So sometimes people think the product, uh, is what is driving. >>You just pull the product >>Through. Exactly, exactly. And so that's that I, that I think is really this revolution that you see, and, and it does extend into things like cryptocurrencies and web three and, you know, sort of like the control that is taken back by the user. Um, but you know, many would say that, that the origins of this movement may be started with open source where users were contributors, you know, contributors were users and looking back decades and seeing how it, how it fast forward to today. I think that's really the trend that we're all writing and it's enabling these end users. And these end users in our world are developers, data engineers, cybersecurity practitioners, right. They're really the users. And they're really the, the offic and the most, you know, kind of valued people in >>This. I wanna come back to the data engineers in a second, but I wanna make a comment and get your reaction to, I have a, I'm a gen Xer technically. So for not a boomer, but I have some boomer friends who are a little bit older than me who have, you know, experienced the sixties. And I've, I've been saying on the cube for probably about eight years now that we are gonna hit a digital hippie Revolut, meaning a rebellion against in the sixties was rebellion against the fifties and the man and, you know, summer of love. That was a cultural differentiation from the other one of group, the predecessors. So we're kind of having that digital moment now where it's like, Hey boomers, Hey people, we're not gonna do that anymore. We hate how you organize shit. >>Right. But isn't this just technology. I mean, isn't it, isn't it like there used to be the old adage, like, you know, you would never get fired for buying IBM, but now it's like, you obviously probably would get fired if you bought IBM. And I mean, it's just like the, the, I think, I think >>During the mainframe days, those renegades were breaking into Stanford, starting the home brew club. So what I'm trying to get at is that, do you see the young cultural revolution also, culturally, just, this is my identity NFTs to me speak volumes about my, I wanna associate with NFTs, not single sign on like, well, >>Absolutely. And, and I think like, I think you're hitting on something, which is like this convergence of, of, you know, societal trends with technology trends and how that manifests in our world is yes. I think like there is unquestionably almost a religion around the way in which a product is built. Right. And we can use open source. One example of that religion. Some people say, look, I'll just never try a product in the cloud if it's not open source. Yeah. I think cloud, native's another example of that, right? It's either it's, you know, it either is cloud native or it's not. And I think a lot of people will look at a product and say, look, you know, you were not designed in the cloud era. Therefore I just won't try you. And sometimes, um, like it or not, it's a religious decision, right? It's, it's something that people just believe to be true almost without, uh, necessarily. I mean, >>The data drives all decision making. Let me ask you this next question. As a VC. Now you look at pitch, well, you've been a VC for many years, but you also have the founder entrepreneurial mindset, but you can empathize with the founders. You know, hustle is a big part of the, that first founder check, right? You gotta convince someone to part with their ch their money and the first money in which you do a lot of is about believing in the first. So faking it till you make it is hard. Now you, the data's there, you either have it cloud native, you either have the adaption or traction. So honesty is a big part of that pitch. You can't fake it. Oh, >>AB absolutely. You know, there used to be this concept of like the persona of an entrepreneur, right. And the persona of the entrepreneur would be, you know, somebody who was a great salesperson or somebody who tell a great story. And I still think that that's important, right. It still is a human need for people to believe in narratives and stories. Yeah. But having said that you're right. The proof is in the pudding, right. At some point you click download and you try the product and it does what it says it's gonna, it's gonna do, or it doesn't, or it either stands up to the load test or it doesn't. And so I, I feel like in this new economy, that're, we live in really, it's a shift from maybe the storytellers and the creators to, to the builders, right. The people that know how to build great product. And in some ways the people that can build great product yeah. Stand out from the crowd. And they're the ones that can build communities around their products. And, you know, in some ways can, um, you know, kind of own more of the narrative because their product begin for exactly >>The volume you back to the user led growth. >>Exactly. And it's the religion of, I just love your product. Right. And I, I, I, um, Doug song is the founder of du security used to say, Hey, like, you know, the, the really like in today's world of like consumption based software, like the user is only gonna give you 90 seconds to figure out whether or not you're a company that's easy to do business with for right. And so you can say, and do all the things that you want about how easy you are to work with. But if the product isn't easy to install, if it's not easy to try, if it's not, if, if the it's gotta speak to the, >>Exactly. Speak to the user. But let me ask a question now that for the people watching, who are maybe entrepreneurial entre entrepreneurs, um, masterclass here is in session. So I have to ask you, do you prefer, um, an entrepreneur to come in and say, look at John. Here's where I'm at. Okay. First of all, storytelling's fine. Whether you're an extrovert or introvert, have your style, sell the story in a way that's authentic, but do you, what do you prefer to say? Here's where I'm at? Look, I have an idea. Here's my traction. I think here's my MVP prototype. I need help. Or do you wanna just see more stats? What's the, what's the preferred way that you like to see entrepreneurs come in and engage? >>There's tons of different styles, man. I think the single most important thing that every founder should know is that we, we don't invest in what things are today. We invest in what we think will become, right. And I think that's why we all get up in the morning and try to build something different, right? It's that we see the world a different way. We want it to be a different way, and we wanna work every single moment of the day to try to make that vision a reality. So I think the more that you can show people where you want to be, the more likely somebody is gonna to align with your vision and, and want to invest in you and wanna be along for the ride. So I, I wholeheartedly believe in showing off what you got today, because eventually we all get down to like, where are we and what are we gonna do together? But, um, no, I, you gotta show the path. I think the single most important thing for any founder and VC relationship is that they have the same vision. Uh, if you have the same vision, you can, you can get through bumps in the road, you can get through short term spills. You can all sorts of things in the middle of the journey can happen. Yeah. But it doesn't matter as much if you share the same long term vision, >>Don't flake out and, and be fashionable with the, the latest trends because it's over before you even get there. >>Exactly. I think many people that, that do what we do for a living will say, you know, ultimately the future is relatively easy to predict, but it's the timing that's impossible to predict. So you, you know, you sort of have to balance the, you know, we, we know that the world is going this way and therefore we're gonna invest a lot of money to try to make this a reality. Uh, but sometimes it happens ins six months. Sometimes it takes six years. Sometimes it takes 16 years. Uh, >>What's the hottest thing in enterprise that you see the biggest wave that people should pay attention to that you're looking at right now with Tebel partners, Tebel dot your site. What's the big wave. What's your big >>Wave. There there's three big trends that we invest in. And then the, the only things we do day in day out one is the explosion at open source software. So I think many people think that all software is unquestionably moving to an open source model in some form or another yeah. Tons of reasons to debate whether or not that is gonna happen an alwa timeline happening forever, but it is, it is accelerating faster than we've ever seen. So I, I think it's its one big mass of wave that we continue to ride. Um, second is the rise of data engineering. Uh, I think data engineering is in and of itself now a category of software. It's not just that we store data. It's now we move data and we develop applications on data. And, uh, I think data is in and of itself as big of a market as any of the other markets that we invest in. Uh, and finally it's the gift that keeps on giving. I've spent my entire career in it. We still feel that security is a market that is underinvested. It is, it continues to be the place where people need to continue to invest and spend more money. Yeah. Uh, and those are the three major trends that we run >>And security, you think we all need a do over, right? I mean, do we need a do over in security or is what's the core problem? I, >>I, I keep using this word underinvested because I think it's the right way to think about the problem. I think if you, I think people generally speaking, look at cyber security as an add-on. Yeah. But if you think about it, the whole like economy is moving online. And so in, in some ways like security is core to protecting the digital economy. And so it's, it shouldn't be an afterthought, right? It should be core to what everyone is doing. And that's why I think relative to the trillions of dollars that are at stake, uh, I believe the market size for cybersecurity is around 150 billion and it still is a fraction of what >>We're, what we're and even boom is booming now. So you get the convergence of national security, geopolitics, internet digital >>That's right. You mean arguably, right. Arguably again, it's the area of the world that people should be spending more time and more money given what to stake. >>I love your thesis. I gotta, I gotta say you gotta love your firm. Love who you're doing. We're big supporters of your mission. Congrat is on your entrepreneurial venture. And uh, we'll be, we'll be talking and maybe see a Cuban. Uh, >>Absolutely >>Not. Certainly EU maybe even north America's in Detroit this year. >>Huge fan of what you guys are doing here. Thank you so much for helping me on the show. >>Des bell VC Johnson here on the cube. Check him out. Founder for founders here on the cube, more coverage from San Francisco, California, after the short break, stay with us. Hey everyone. Welcome to the cue here. Live in San Francisco, California for AWS summit, 2022 we're live we're back with events. Also we're virtual. We got hybrid all kinds of events. This year, of course, 80% summit in New York city is happening this summer. We'll be there with the cube as well. I'm John. Again, John host of the cube. Got a great guest here. Justin Colby, owner and CEO of innovative solutions they booth is right behind us. Justin, welcome to the cube. >>Thank you. Thank you for having me. >>So we're just chatting, uh, off camera about some of the work you're doing. You're the owner of and CEO. Yeah. Of innovative. Yeah. So tell us the story. What do you guys do? What's the elevator pitch. Yeah. >><laugh> so the elevator pitch is we are, uh, a hundred percent focused on small to midsize businesses that are moving to the cloud or have already moved to the cloud and really trying to understand how to best control, cost, security, compliance, all the good stuff, uh, that comes along with it. Um, exclusively focused on AWS and, um, you know, about 110 people, uh, based in Rochester, New York, that's where our headquarters is. But now we have offices down in Austin, Texas up in Toronto, uh, Canada, as well as Chicago. Um, and obviously in New York, uh, you know, the, the business was never like this, uh, five years ago, um, founded in 1989, made the decision in 2018 to pivot and go all in on the cloud. And, uh, I've been a part of the company for about 18 years, bought the company about five years ago. And it's been a great ride. >>It's interesting. The manages services are interesting with cloud cause a lot of the heavy liftings done by AWS. So we had Matt on your team on earlier talking about some of the edge stuff. Yeah. But you guys are a managed cloud service. You got cloud advisory, you know, the classic service that's needed, but the demands coming from cloud migrations and application modernization and obviously data is a huge part of it. Huge. How is this factoring into what you guys do and your growth cuz you guys are the number one partner on the SMB side for edge. Yeah. For AWS, you got results coming in. Where's the, where's the forcing function. What's the pressure point. What's the demand like? Yeah. >>It's a great question. Every CEO I talk to, that's a small to mid-size business. I'll try and understand how to leverage technology better to help either drive a revenue target for their own business, uh, help with customer service as so much has gone remote now. And we're all having problems or troubles or issues trying to hire talent. And um, you know, tech is really at the, at the forefront and the center of that. So most customers are coming to us and they're like, listen, we gotta move to the out or we move some things to the cloud and we want to do that better. And um, there's this big misnomer that when you move to the cloud, you gotta automatically modernize. Yeah. And what we try to help as many customers understand as possible is lifting and shifting, moving the stuff that you maybe currently have OnPrem and a data center to the cloud first is a first step. And then, uh, progressively working through a modernization strategy is always the better approach. And so we spend a lot of time with small to midsize businesses who don't have the technology talent on staff to be able to do >>That. Yeah. They want to get set up. But the, the dynamic of like latency is huge. We're seeing that edge product is a big part of it. This is not a one-off happening around everywhere. It is. And it's not, it's manufacturing, it's the physical plant or location >>Literally. >>And so, and you're seeing more IOT devices. What's that like right now from a challenge and problem statement standpoint, are the customers, not staff, is the it staff kind of old school? Is it new skills? What's the core problem you guys solve >>The SMB space. The core issue nine outta 10 times is people get enamored with the latest and greatest. And the reality is not everything that's cloud based. Not all cloud services are the latest and greatest. Some things have been around for quite some time and are hardened solutions. And so, um, what we try to do with technology staff that has additional on-prem, uh, let's just say skill sets and they're trying to move to a cloud-based workload is we try to help those customers through education and through some practical, let's just call it use case. Um, whether that's a proof of concept that we're doing or whether that's, we're gonna migrate a small workload over, we try to give them the confidence to be able to not, not necessarily go it alone, but to, to, to have the, uh, the Gusto and to really have the, um, the, the opportunity to, to do that in a wise way. Um, and what I find is that most CEOs that I talk to, yeah, they're like, listen, the end of the day, I'm gonna be spending money in one place or another, whether that's OnPrem or in the cloud. I just want to know that I'm doing that in a way that helps me grow as quickly as possible status quo. I think every, every business owner knows that COVID taught us anything that status quo is, uh, is, is no. No. Good. >>How about factoring in the, the agility and speed equation? Does that come up a lot? It >>Does. I think, um, I think there's also this idea that if, uh, if we do a deep dive analysis and we really take a surgical approach to things, um, we're gonna be better off. And the reality is the faster you move with anything cloud based, the better you are. And so there's this assumption that we gotta get it right the first time. Yeah. In the cloud, if you start the, on your journey in one way, and you realize midway that it's not the right, let's just say the right place to go. It's not like buying a piece of iron that you put in the closet and now you own it in the cloud. You can turn those services on and off. It's a, gives you a much higher density for making decisions and failing >>Forward. Well actually shutting down the abandoning, the projects that early and not worrying about it, you got it. I mean, most people don't abandon stuff cuz they're like, oh, I own it. >>Exactly. >>And they get, they get used to it. Like, and then they wait too long. >>That's exactly. Yeah. >>Frog and boiling water as we used to say so, oh, it's a great analogy. So I mean this, this is a dynamic that's interesting. I wanna get more thoughts on it because like I'm a, if I'm a CEO of a company, like, okay, I gotta make my number. Yeah. I gotta keep my people motivated. Yeah. And I gotta move faster. So this is where you guys come in. I get the whole thing. And by the way, great service, um, professional services in the cloud right now are so hot because so hot, you can build it and then have option optionality. You got path decisions, you got new services to take advantage of. It's almost too much for customers. It is. I mean, everyone I talk to at reinvent, that's a customer. Well, how many announcements did Andy jazzy announcer Adam, you know, five, a thousand announcement or whatever they did with huge amounts. Right. Keeping track of it all. Oh, is huge. So what's the, what's the, um, the mission of, of your company. How does, how do you talk to that alignment? Yeah. Not just product. I can get that like values as companies, cuz they're betting on you and your people. >>They are, they are >>The values. >>Our mission is, is very simple. We want to help every small to mid-size business, leverage the power of the cloud. Here's the reality. We believe wholeheartedly. This is our vision that every company is going to become a technology company. So we go to market with this idea that every customer's trying to leverage the power of the cloud in some way, shape or form, whether they know it or don't know it. And number two, they're gonna become a tech company in the pro of that because everything is so tech-centric. And so when you talk about speed and agility, when you talk about the, the endless options and the endless permutations of solutions that a customer can buy in the cloud, how are you gonna ask a team of one or two people in your it department to make all those decisions going it alone or trying to learn it as you go, it only gets you so far working with a partner. >>I'll just give you some perspective. We work with about a thousand small to midsize business customers. More than 50% of those customers are on our managed services. Meaning know that we have their back and we're the safety net. So when a customer is saying, all right, I'm gonna spend a couple thousand dollars a month in the cloud. They know that that bill, isn't gonna jump to $10,000 a month going on loan. Who's there to help protect that. Number two, if you have a security posture and let's just say you're high profile and you're gonna potentially be more vulnerable to security attack. If you have a partner that's offering you some managed services. Now you, again, you've got that backstop and you've got those services and tooling. We, we offer, um, seven different products that are part of our managed services that give the customer the tooling, that for them to go out and buy on their own for a customer to go out today and go buy a new Relic solution on their own, it would cost 'em a fortune. If >>It's training alone would be insane. A risk factor not mean the cost. Yes, absolutely. Opportunity cost is huge, >>Huge, absolutely enormous training and development. Something. I think that is often, you know, it's often overlooked technologists. Typically they want to get their skills up. Yeah. They, they love to get the, the stickers and the badges and the pins, um, at innovative in 2018, when, uh, when we made the decision to go all on the club, I said to the organization, you know, we have this idea that we're gonna pivot and be aligned with AWS in such a way that it's gonna really require us all to get certified. My executive assistant at the time looks at me. She said, even me, I said, yeah, even you, why can't you get certified? Yeah. And so we made, uh, a conscious decision. It wasn't requirement isn't today to make sure everybody in the company has the opportunity to become certified. Even the people that are answering the phones at the front desk >>And she could be running the Kubernetes clusters. I >>Love it. It's amazing. So I'll tell you what, when that customer calls and they have a real Kubernetes issue, she'll be able to assist and get the right >>People involved. And that's a cultural factor that you guys have. So, so again, this is back to my whole point about SMBs and BIS is in general, small and large. It staffs are turning over the gen Z and millennials are in the workforce. They were provisioning top of rack switches. Right. First of all. And so if you're a business, there's also the, I call the build out, um, uh, return factor, ROI piece. At what point in time as an owner or SMB, do I get the why? Yeah. I gotta hire a person to manage it. That person's gonna have five zillion job offers. Yep. Uh, maybe who knows? Right. I got cyber security issues. Where am I gonna find a cyber person? Yeah. A data compliance. I need a data scientist and a compliance person. Right. Maybe one in the same. Right. Good luck. Trying to find a data scientist. Who's also a compliance person. Yep. And the list goes on. I can just continue. Absolutely. I need an SRE to manage the, the, uh, the sock report and we can pen test. Right. >>Right. >>These are, these are >>Like critical issues. This >>Is just like, these are the table stakes. >>Yeah. And, and every, every business owner's thinking about this, that's, >>That's what, at least a million in bloating, if not three or more Just to get that going. Yeah. Then it's like, where's the app. Yeah. So there's no cloud migration. There's no modernization on the app side now. Yeah. No. And nevermind AI and ML. That's >>Right. That's right. So to try to go it alone, to me, it's hard. It's incredibly difficult. And the other thing is, is there's not a lot of partners, so the partner, >>No one's raising their hand boss. I'll do all that exactly. In the it department. >>Exactly. >>Like, can we just call up, uh, you know, our old vendor that's >>Right. <laugh> right. Our old vendor. I like >>It, >>But that's so true. I mean, when I think about how, if I were a business owner starting a business today and I had to build my team, um, and the amount of investment that it would take to get those people skilled up and then the risk factor of those people now having the skills and being so much more in demand and being recruited away, that's a real, that's a real issue. And so how you build your culture around that is, is very important. And it's something that we tell, talk about every, with every one of our small to mid-size >>Businesses. So just, I wanna get, I want to get your story as CEO. Okay. Take us through your journey. You said you bought the company and your progression to, to being the owner and CEO of innovative yeah. Award winning guys doing great. Uh, great bet on a good call. Yeah. Things are good. Tell your story. What's your journey? >>It's real simple. I was, uh, I was a sophomore at the Rochester Institute of technology in 2003. And, uh, I knew that I, I was going to school for it and I, I knew I wanted to be in tech. I didn't know what I wanted to do, but I knew I didn't wanna code or configure routers and switches. So I had this great opportunity with the local it company that was doing managed services. We didn't call it at that time innovative solutions to come in and, uh, jump on the phone and dial for dollars. I was gonna cold call and introduce other, uh, small to midsize businesses locally in Rochester, New York go to Western New York, um, who innovative was now. We were 19 people at the time. And I came in, I did an internship for six months and I loved it. I learned more in those six months that I probably did in my first couple of years at, uh, at RT long story short. >>Um, for about seven years, I worked, uh, to really help develop, uh, sales process and methodology for the business so that we could grow and scale. And we grew to about 30 people. And, um, I went to the owners at the time in 2010 and I was like, Hey, on the value of this business and who knows where you guys are gonna be another five years, what do you think about making me an owner? And they were like, listen, you got long ways before you're gonna be an owner, but if you stick it out in your patient, we'll, um, we'll work through a succession plan with you. And I said, okay, there were four other individuals at the time that were gonna also buy into the business with me. >>And they were the owners, no outside capital, none >>Zero, well, 2014 comes around. And, uh, the other folks that were gonna buy into the business with me that were also working at innovative for different reasons, they all decided that it wasn't for them. One started a family. The other didn't wanna put capital in. Didn't wanna write a check. Um, the other had a real big problem with having to write a check. If we couldn't make payroll, I'm like, well, that's kind of like if we're owners, we're gonna have to like cover that stuff. <laugh> so >>It's called the pucker factor. >>Exactly. So, uh, I sat down with the CEO in early 2015, and, uh, we made the decision that I was gonna buy the three partners out, um, go through an early now process, uh, coupled with, uh, an interesting financial strategy that wouldn't strap the business, cuz they cared very much. The company still had the opportunity to keep going. So in 2016 I bought the business, um, became the sole owner. And, and at that point we, um, we really focused hard on what do we want this company to be? We had built this company to this point. Yeah. And, uh, and by 2018 we knew that pivoting going all in on the cloud was important for us and we haven't looked back. >>And at that time the proof points were coming clearer and clearer 2012 through 15 was the early adopters, the builders, the startups and early enterprises. Yes. The capital ones of the world. Exactly. And those kinds of big enterprises, the GA I don't wanna say gamblers, but ones that were very savvy. The innovators, the FinTech folks. Yep. The hardcore glass eating enterprises >>Agreed, agreed to find a small to mid-size business, to migrate completely to the cloud as, as infrastructure was considered. That just didn't happen as often. Um, what we were seeing where a lot of our small to mid-size as customers, they wanted to leverage cloud-based backup or they wanted to leverage a cloud for disaster recovery because it lent itself. Well, early days, our most common cloud customer though, was the customer that wanted to move messaging and collaboration, the Microsoft suite to the cloud. And a lot of 'em dipped their toe in the water. But by 2017 we knew infrastructure was around the corner. Yeah. And so, uh, we only had two customers on AWS at the time. Um, and we, uh, we, we made the decision to go all in >>Justin. Great to have you on the cube. Thank you. Let's wrap up. Uh, tell me the hottest product that you have. Is it migrations? Is it the app modernization? Is it data? What's the hot product and then put a plug in for the company. Awesome. >>So, uh, there's no question. Every customer is looking to migrate workloads and try to figure out how to modernize for the future. We have very interesting, sophisticated yet elegant funding solutions to help customers with the cash flow, uh, constraints that come along with those migrations. So any SMB that's thinking about migrating to the cloud, they should be talking innovative solutions. We know how to do it in a way that allows those customers not to be cash strap and gives them an opportunity to move forward in a controlled, contained way so that they can modernize. >>So like insurance, basically for them not insurance class in the classic sense, but you help them out on the, on the cash exposure. >>Absolutely. We are known for that and we're known for being creative with those customers and being empathetic to where they are in their journey. >>And that's the cloud upside is all about doubling down on the variable wind. That's right. Seeing the value and Ling down on it. Absolutely not praying for it. Yeah. <laugh> all right, Justin. Thanks for coming on. You really appreciate it. >>Thank you very much for having me. >>Okay. This is the cube coverage here live in San Francisco, California for AWS summit, 2022. I'm John for your host. Thanks for watching. We're back with more great coverage for two days after this short break, >>Live on the floor and see San Francisco for a AWS summit. I'm John ferry, host of the cube here for the next two days, getting all the action we're back in person. We're at a AWS reinvent a few months ago. Now we're back. Events are coming back and we're happy to be here with the cube. Bring all the action. Also virtual. We have a hybrid cube. Check out the cube.net, Silicon angle.com for all the coverage. After the event. We've got a great guest ticking off here. Matthew Park, director of solutions, architecture with innovation solutions. The booth is right here. Matthew, welcome to the cube. >>Thank you very much. I'm glad to be >>Here. So we're back in person. You're from Tennessee. We were chatting before you came on camera. Um, it's great to have to be back through events. >>It's amazing. This is the first, uh, summit I've been to and what two, three years. >>It's awesome. We'll be at the UHS summit in New York as well. A lot of developers and a big story this year is as developers look at cloud going distributed computing, you got on premises, you got public cloud, you got the edge. Essentially the cloud operations is running everything dev sec ops, everyone kind of sees that you got containers, you got Kubernetes, you got cloud native. So the game is pretty much laid out mm-hmm <affirmative> and the edge is with the actions you guys are number one, premier partner at SMB for edge. >>That's right. >>Tell us about what you guys doing at innovative and, uh, what you do. >>That's right. Uh, so I'm the director of solutions architecture. Uh, me and my team are responsible for building out the solutions that are around, especially the edge public cloud for us edge is anything outside of an AWS availability zone. Uh, we are deploying that in countries that don't have AWS infrastructure in region. They don't have it. Uh, give an example, uh, example would be Panama. We have a customer there that, uh, needs to deploy some financial tech and compute is legally required to be in Panama, but they love AWS and they want to deploy AWS services in region. Uh, so they've taken E EKS anywhere. We've put storage gateway and, uh, snowball, uh, in region inside the country and they're running their FinTech on top of AWS services inside Panama. >>You know, it's interesting, Matthew is that we've been covering a, since 2013 with the cube about their events. And we watched the progression and jazzy was, uh, was in charge and became the CEO. Now Adam's in charge, but the edge has always been that thing they've been trying to avoid. I don't wanna say trying to avoid, of course, Amazon would listen to the customers. They work backwards from the customer. We all know that. Uh, but the real issue was they were they're bread and butters EC two and S three. And then now they got tons of services and the cloud is obviously successful and seeing that, but the edge brings up a whole nother level. >>It does computing. It >>Does. That's not centralized in the public cloud now they got regions. So what is the issue at the edge what's driving the behavior. Outpost came out as a reaction to competitive threats and also customer momentum around OT, uh, operational technologies. And it merging. We see that the data at the edge, you got 5g having. So it's pretty obvious, but there's a slow transition. What was the driver for the edge? What's the driver now for edge action for AWS >>Data is the driver for the edge. Data has gravity, right? And it's pulling compute back to where the customer's generating that data and that's happening over and over again. You said it best outpost was a reaction to a competitive situation where today we have over 15 AWS edge services and those are all reactions to things that customers need inside their data centers on location or in the field like with media companies. >>Outpost is interesting. We always used to riff on the cube cause it's basically Amazon and a box pushed in the data center, running native, all the stuff, but now cloud native operations are kind of becoming standard. You're starting to see some standard Deepak syncs. Group's doing some amazing work with open source Rauls team on the AI side, obviously, uh, you got SW, he was giving the keynote tomorrow. You got the big AI machine learning big part of that edge. Now you can say, okay, outpost, is it relevant today? In other words, did outpost do its job? Cause EKS anywhere seems to be getting a lot of momentum. You see local zones, the regions are kicking ass for Amazon. This edge piece is evolving. What's your take on EKS anywhere versus say outpost? >>Yeah, I think outpost did its job. It made customers that were looking at outpost really consider, do I wanna invest in this hardware? Do I, do I wanna have, um, this outpost in my data center, do I want to manage this over the long term? A lot of those customers just transitioned to the public cloud. They went into AWS proper. Some of those customers stayed on prem because they did have use cases that were, uh, not a good fit for outposts. They weren't a good fit. Uh, in the customer's mind for the public AWS cloud inside an availability zone. Now what's happening is as AWS is pushing these services out and saying, we're gonna meet you where you are with 5g. We're gonna meet you where you are with wavelength. We're gonna meet you where you are with EKS anywhere. Uh, I think it has really reduced the amount of times that we have conversations about outposts and it's really increased. We can deploy fast. We don't have to spin up outpost hardware. We can go deploy EKS anywhere or in your VMware environment. And it's increasing the speed of adoption >>For sure. Right? So you guys are making a lot of good business decisions around managed cloud service. That's right. Innovative as that you get the cloud advisory, the classic professional services for the specific edge piece and, and doing that outside of the availability zones and regions for AWS, um, customers in, in these new areas that you're helping out are, they want cloud, like they want to have modernization a modern applications. Obviously they got data machine learning and AI, all part of that. What's the main product or, or, or gap that you're filling for AWS, uh, outside of their availability zones or their regions that you guys are delivering. What's the key is it. They don't have a footprint. Is it that it's not big enough for them? What's the real gap. What's why, why are you so successful? >>So what customers want when they look towards the cloud is they want to focus on, what's making them money as a business. They want on their applications. They want to focus on their customers. So they look towards AWS cloud and say, AWS, you take the infrastructure. You take, uh, some of the higher layers and we'll focus on our revenue generating business, but there's a gap there between infrastructure and revenue generating business that innovative slides into, uh, we help manage the AWS environment. Uh, we help build out these things in local data centers for 32 plus year old company. We have traditional on-premises people that know about deploying hardware that know about deploying VMware to host EKS anywhere. But we also have most of our company totally focused on the AWS cloud. So we're filling that gap in helping of these AWS services, manage them over the long term. So our customers can go to just primarily and totally focusing on their revenue generating business. So >>Basically you guys are basically building AWS edges, >>Correct? >>For correct companies, correct? Mainly because the, the needs are there, you got data, you got certain products, whether it's, you know, low latency type requirements, right. And then they still work with the regions, right. It's all tied together, right. Is that how it works? Right. >>And, and our customers, even the ones in the edge, they also want us to build out the AWS environment inside the availability zone, because we're always gonna have a failback scenario. If we're gonna deploy FinTech in the Caribbean, we talk about hurricanes and we're gonna talk about failing back into the AWS availability zones. So innovative is filling that gap across the board, whether it be inside the AWS cloud or on the AWS edge. >>All right. So I gotta ask you on the, since you're at the edge in these areas, I won't say underserved, but developing areas where you now have data and you have applications that are tapping into that, that required. It makes total sense. We're seeing that across the board. So it's not like it's, it's an outlier it's actually growing. Yeah. There's also the crypto angle. You got the blockchain. Are you seeing any traction at the edge with blockchain? Because a lot of people are looking at the web three in these areas like Panama, you mentioned FinTech. And in, in the islands there a lot of, lot of, lot of web three happening. What's your, what's your view on the web three world right now, relative >>To we, we have some customers actually deploying crypto, especially, um, especially in the Caribbean. I keep bringing the Caribbean up, but it's, it's top of my mind right now we have customers that are deploying crypto. A lot of, uh, countries are choosing crypto to underlie parts of their central banks. Yeah. Um, so it's, it's up and coming a, uh, I, I have some, you know, personal views that, that crypto is still searching for a use case. Yeah. And, uh, I think it's searching a lot and, and we're there to help customers search for that use case. Uh, but, but crypto, as a, as a, uh, technology, um, lives really well on the AWS edge. Yeah. Uh, and, and we're having more and more people talk to us about that. Yeah. And ask for assistance in the infrastructure, because they're developing new cryptocurrencies every day. Yeah. It's not like they're deploying Ethereum or anything specific. They're actually developing new currencies and, and putting them out there on it's >>Interesting. I mean, first of all, we've been doing crypto for many, many years. We have our own little, um, you know, projects going on. But if you look talk to all the crypto people that say, look, we do a smart concept. We use the blockchain. It's kind of over a lot of overhead and it's not really their technical already, but it's a cultural shift, but there's underserved use cases around use of money, but they're all using the blockchain, just for this like smart contracts for instance, or certain transactions. And they go into Amazon for the database. Yeah. <laugh> they all don't tell anyone we're using a centralized service, but what happened to decentralized. >>Yeah. And that's, and that's the conversation performance issue. Yeah. And, and it's a cost issue. Yeah. And it's a development issue. Um, so I think more and more as, as some of these, uh, currencies maybe come up, some of the smart contracts get into, uh, they find their use cases. I think we'll start talking about how does that really live on, on AWS and, and what does it look like to build decentralized applications, but with AWS hardware and services. >>Right. So take me through, uh, a use case of a customer, um, Matthew around the edge. Okay. So I'm a customer, pretend I'm a customer, Hey, you know, I'm, we're in an underserved area. I want to modernize my business. And I got my developers that are totally peaked up on cloud. Um, but we've identified that it's just a lot of overhead latency issues. I need to have a local edge and serve my ad. And I also want all the benefit of the cloud. So I want the modernization and I wanna migrate to the cloud for all those cloud benefits and the goodness of the cloud. What's the answer. Yeah. >>Uh, big thing is, uh, industrial manufacturing, right? That's, that's one of the best use cases, uh, inside industrial manufacturing, we can pull in many of the AWS edge services we can bring in, uh, private 5g, uh, so that all the, uh, equipment inside that, that manufacturing plant can be hooked up. They don't have to pay huge overheads to deploy 5g it's, uh, better than wifi for the industrial space. Um, when we take computing down to that industrial area, uh, because we wanna do pre-procesing on the data. Yeah. We want to gather some analytics. We deploy that with, uh, regular commercial available hardware running VMware, and we deploy EKS anywhere on that. Uh, inside of that manufacturing plant, uh, we can do pre-procesing on things coming out of the, uh, the robotics that depending on what we're manufacturing, right. Uh, and then we can take those refined analytics and for very low cost with maybe a little bit longer latency transmit those back, um, to the AWS availability zone, the, the standard for >>Data, data lake, or whatever, to >>The data lake. Yeah. Data lake house, whatever it might be. Um, and we can do additional data science on that once it gets to the AWS cloud. Uh, but a lot of that, uh, just in time business decisions, just in time, manufacturing decisions can all take place on an AWS service or services inside that manufacturing plant. And that's, that's one of the best use cases that we're >>Seeing. And I think, I mean, we've been seeing this on the queue for many, many years, moving data around is very expensive. Yeah. But also compute going to the data that saves that cost yep. On the data transfer also on the benefits of the latency. So I have to ask you, by the way, that's standard best practice now for the folks watching don't move the data, unless you have to, um, those new things are developing. So I wanna ask you what new patterns are you seeing emerging once this new architecture's in place? Love that idea, localize everything right at the edge, manufacturing, industrial, whatever, the use case, retail, whatever it is. Right. But now what does that change in the, in the core cloud? This is a, there's a system element here. Yeah. What's the new pattern. There's >>Actually an organizational element as well, because once you have to start making the decision, do I put this compute at the point of use or do I put this compute in the cloud out? Uh, now you start thinking about where business decisions should be taking place. Uh, so not only are you changing your architecture, you're actually changing your organization because you're thinking, you're thinking about a dichotomy you didn't have before. Uh, so now you say, okay, this can take place here. Uh, and maybe maybe decision can wait. Right? Yeah. Uh, and then how do I visualize that? By >>The way, it could be a bot too, doing the work for management. Yeah. <laugh> exactly. You got observability going, right. But you gotta change the database architecture on the back. So there's new things developing. You've got more benefit. There >>Are, there are. And, and we have more and more people that, that want to talk less about databases and want to talk more about data lakes because of this. They want to talk more about customers are starting to talk about throwing away data, uh, you know, for the past maybe decade. Yeah. It's been store everything. And one day we will have a data science team that we hire in our organization to do analytics on this decade of data. And >>Well, I mean, that's, that's a great point. We don't have time to drill into, maybe we do another session on this, but the one pattern was income of the past year is that throwing away data's bad. Even data lakes that so-called turn into data swamps, actually, it's not the case. You look at data, brick, snowflake, and other successes out there. And even time series data, which may seem irrelevant efforts over actually matters when people start retrain their machine learning algorithms. Yep. So as data becomes code, as we call it our lab showcase, we did a whole, whole, that event on this. The data's good in real time and in the lake. Yeah. Because the iteration of the data feeds the machine learning training. Things are getting better with the old data. So it's not throw away. It's not just business benefits. Yeah. There's all kinds of new scale. There >>Are. And, and we have, uh, many customers that are run petabyte level. Um, they're, they're essentially data factories on, on, uh, on premises, right? They're, they're creating so much data and they're starting to say, okay, we could analyze this, uh, in the cloud, we could transition it. We could move petabytes of data to the AWS cloud, or we can run, uh, computational workloads on premises. We can really do some analytics on this data transition, uh, those high level and sort of raw analytics back to AWS run 'em through machine learning. Um, and we don't have to transition 10, 12 petabytes of data into AWS. >>So I gotta end the segment on a, on a kind of a, um, fun note. I was told to ask you about your personal background on premise architect, a cloud and skydiving instructor. <laugh> how does that all work together? What tell, what does this mean? Yeah. >>Uh, you >>Jumped out a plane and got a job. You, you got a customer to jump out >>Kind of. So I was jump, I was teaching Scott eing, uh, before I, before I started in the cloud space, this was 13, 14 years ago. I was a, I still am a Scott I instructor. Yeah. Uh, I was teaching Scott eing and I heard out of the corner of my ear, uh, a guy that owned an MSP that was lamenting about, um, you know, storing data and, and how his cus customers are working. And he can't find enough people to operate all these workloads. So I walked over and said, Hey, this is, this is what I went to school for. Like, I'd love to, you know, uh, I was living in a tent in the woods teaching scout. I think I was like, I'd love to not live in a tent in the woods. So, uh, uh, I started in the first day there, uh, we had a, a discussion, uh, EC two, just come out <laugh> um, and, uh, like, >>This is amazing. >>Yeah. And so we had this discussion, we should start moving customers here. And, uh, and that totally revolutionized that business, um, that, that led to, uh, that that guy actually still owns a skydiving airport. But, um, but through all of that and through being an on premises migrated me and myself, my career into the cloud, and now it feels like, uh, almost, almost looking back and saying, now let's take what we learned in the cloud and, and apply those lessons and those services to >>It's. So it's such a great story, you know, I was gonna, you know, you know, the, the, the, the whole, you know, growth mindset pack your own parachute, you know, uh, exactly. You know, the cloud in the early day was pretty much will the shoot open. Yeah. It was pretty much, you had to roll your own cloud at that time. And so, you know, you, you jump on a plane, you gotta make sure that parachute is gonna open. >>And so was Kubernetes by the way, 2015 or so when, um, when that was coming out, it was, I mean, it was, it was still, and I, maybe it does still feel like that to some people. Right. But, uh, it was, it was the same kind of feeling that we had in the early days, AWS, the same feeling we have when we >>It's pretty much now with you guys, it's more like a tandem jump. Yeah. You know, but, but it's a lot of, lot of this cutting edge stuff, like jumping out of an airplane. Yeah. You guys, the right equipment, you gotta do the right things. Exactly. >>Right. >>Matthew, thanks for coming on the cube. Really appreciate it. Absolutely great conversation. Thanks for having me. Okay. The cubes here live and San Francisco for summit. I'm John Forry host of the cube. Uh, we'll be at a summit in New York coming up in the summer as well. Look up for that. look@thiscalendarforallthecubeactionatthecube.net. We'll be right back with our next segment after this break. >>Okay. Welcome back everyone to San Francisco live coverage here, we're at the cube a be summit 2022. We're back in person. I'm John fury host to the cube. We'll be at the eight of his summit in New York city. This summer, check us out then. But right now, two days in San Francisco, getting all the coverage what's going on in the cloud, we got a cube alumni and friend of the cube, my dudes, car CEO, investor, a Sierra, and also an investor and a bunch of startups, angel investor. Gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see you, sir. Chris. Cool. How are, are you >>Good? How are you? >>So congratulations on all your investments. Uh, you've made a lot of great successes, uh, over the past couple years, uh, and your company raising, uh, some good cash as Sarah. So give us the update. How much cash have you guys raised? What's the status of the company product what's going on? First >>Of all, thank you for having me back to be business with you. Never great to see you. Um, so is a company started around four years back. I invested with a few of the investors and now I'm the CEO there. Um, we have raised close to a hundred million there. Uh, the investors are people like Norwes Menlo, Tru ventures, coast, lo ventures, Ram Sheam and all those people, all well known guys. The Andy Beckel chime, Paul Mo uh, main web. So a whole bunch of operating people and, uh, Silicon valley VCs are involved >>And has it come? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISR is going after is what I call the applying AI for customer service. It operations, it help desk, uh, the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and ServiceNow to take it to the next stage? >>Well, I love having you on the cube, Dave and I, Dave Valenti as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a GE, you're like a guest analyst. <laugh> >>You know who you >>Get to call this fun to talk. You though, >>You got the commentary, you, your, your finger on the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase it. Isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud scale. You predicted that we talked about on cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing DACA just raised a hundred million on a 2 billion valuation back from the dead after they pivoted from an enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control, plane emerging, AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded, observability there's 10 million observability companies. Data is the key. What's your angle on this? What's your take. Yeah, >>No, look, I think I'll give you the view that I see right from my side. Obviously data is very clear. So the things that remember system of recorded you and me talked about the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud NA it'll be called AI, NA AI native is a new buzzword and using the AI customer service it operations. You talk about observability. I call it, AIOps applying AOPs for good old it operation management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events insurance. So I see a lot of work clicking for AIOps and service desk. What needs to be helped us with ServiceNow BMC G you see a new ELA emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflow, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with a AI workflows. So you'll see AI going >>Off is RPA a company is AI, is RPA a feature of something bigger? Or can someone have a company on RPA UI pass? One will be at their event this summer? Um, is it a product company? I mean, I mean, RPA is almost, should be embedded in everything. It's >>A feature. It is very good point. Very, very good thinking. So one is, it's a category for sure. Like, as we thought, it's a category, it's an area where RPA may change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company, or, but that automation should be embedded in every area. Yeah. Like we call cloud NA and AI NATO it'll become automation. NA yeah. And that's your thinking. >>It's almost interesting me. I think about the, what you're talking about what's coming to mind is I'm kinda having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it. It was middleware. It sat between two things and then the middle, and it was software abstraction. Now you have all, all kinds of workflows, abstractions everywhere. So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed or they integrated. I mean, these are the challenges. This is crazy. What's the, >>So don't about the databases become called poly databases. Yeah. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area like you were talking about. It should be part of service. Now it should be part of ISRA, like every company, every Salesforce. So that's why you see MuleSoft and Salesforce buying RPA companies. So you'll see all the SaaS companies, cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also have an automation as a layer <inaudible> inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind us, you've got the expo hall. We got, um, we're back to vents, but you got, you know, AMD, Clum, Ove, uh, Dynatrace data, dog, innovative, all the companies out here that we know, we interview them all. They're trying to be suppliers to this growing enterprise market. Right. Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Bel later today. He's a former NEA guy and we always talk to Jerry, Jen. We know all the, the VCs. What does the startups look like? What does the state of the, in your mind, cause you, I know you invest the entrepreneurial founder situation, clouds bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's code. Yes. Basically data is everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to, uh, two things that I'm seeing out there. Remember leaders of Amazon created the startups 15 years back. Everybody built on Amazon now, Azure and GCP. The next layer would be is people don't just build on Amazon. They're going to build it on top of snowflake. Companies are snowflake becomes a data platform, right? People will build on snowflake. Right? So I see my old boss flagman try to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer. Right? So I think that's in the of, <inaudible> trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis a couple months ago called castles in the cloud where your moat is, what you do in the cloud. Not necessarily in the, in the IP. Um, Dave LAN and I had last reinvent, coined the term super cloud, right? He's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldman S Sachs is doing. You starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage. And guys like Charles Fitzgeral out there, who we like was kind of shit on us saying, Hey, you guys terrible, they didn't get it. Like, yeah. I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. <laugh> if he's cool. Um, but snowflake is on Amazon. Yes. Now they say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist. And, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. >>It is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to build everything on Amazon where possible whatever is, I cannot build. I'll make the pass layer. Remember the middle layer pass will be snowflake. So can build it on snowflake. I can use them for data layer. If I really need to size, I'll build it on four.com Salesforce. So I think that's where you'll see. So >>Basically if you're an entrepreneur, the north star in terms of the outcome is be a super cloud. >>It is, >>That's the application on another big CapEx ride, the CapEx of AWS or cloud, >>And that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. >>Yeah. Yeah. How are, how is Amazon and the clouds dealing with these big whales? The snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think got Redshift. Amazon has got red, um, but Snowflake's a big customer. They're probably paying AWS think big bills too. >>So John, very good. Cause it's like how Netflix is and Amazon prime, right. Netflix runs on Amazon, but Amazon has Amazon prime that co-option will be there. So Amazon will have Redshift, but Amazon is also partnering with, uh, snowflake to have native snowflake data warehouse as a data layer. So I think depending on the application use case, you have to use each of the above. I think snowflake is here for a long term. Yeah. Yeah. So if I'm building an application, I want to use snowflake then writing from stats. >>Well, I think that comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, You know, foreclose your value that's right. But some sort of internal hack, but I think, I think the general question that I have is that I think it's okay to have a super cloud like that because the rising tide is still happening at some point. When does the rising tide stop >>And >>Do the people shopping up their knives, it gets more competitive or is it just an infinite growth cycle? I >>Think it's growth. You call it cloud scale. You invented the word cloud scale. So I think look, cloud will continually agree, increase. I think there's, as long as there are more movement from on, uh, OnPrem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations. It helpless, even the customer service service now and, uh, ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So cloud ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go made. >>I wanna get your thoughts for the folks watching that are, uh, enterprise buyers or practitioners, not suppliers to the market, feel free to, to XME or DMing. Next question's really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products. Cause you know, the big enterprises now and, you know, small, medium, large, and large enterprise are all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between the startup selling to, or a growing startup selling to an enterprise? Um, have you seen changes there? I mean I'm seeing some stuff, but why don't we get your thoughts on that? What, no, it is. >>If I remember going back to our 2007 or eight, it, when I used to talk to you back then when Amazon started very small, right? We are an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or 1% today. Most companies are already spending 20, 30% with startups. Like if I look at a CIO line business, it's gone. Yeah. Can it go more? I think it can double in the next four, five years. Yeah. Spending on the startups. >>Yeah. And check out, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want to get your reaction because I reference the URL cause it's like, there's like a bunch of companies we've been promoting because the solutions that startups have actually are new stuff. Yes. It's bending, it's shifting left for security or using data differently or um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there, um, and gives back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona, you mentioned AIOps, we've been seeing AIOps IOPS booming and that's creating a new developer paradigm that's right. Which we call coin data as code data as code is like infrastructure as code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this data engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same thing? Do you agree? Um, do you disagree or can you share >>Yourself? No, I have a lot of thoughts that plus I see AIOP solutions in the future should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone there yet. Like I spend a lot of time with data dog, Cisco app Dyna, right? Dynatrace, all this solution will go future towards to proactive solution with AOPs. But what you bring up a very good point on the data side. I think like we have a Amazon marketplace and Amazon for startup, there should be data exchange where you want to create for AOPs and AI service that customers are give the data, share the data because we thought the data algorithms are useless. I can come the best algorithm, but I gotta train them, modify them, tweak them, make them better, make them better. Yeah. And I think their whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that area is very important. >>You've always been on, um, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to our big data days back in 2009, you know, >>Look at, look how much data bricks has grown. >>It is uh, double, the key >>Cloud kinda went private, so good stuff. What are you working on right now? Give a, give a, um, plug for what you're working on. You'll still investing. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. So right. ISRA is my number one baby right now. So I'm looking at that growing customers and my customers are some of them, you like it's zoom auto desk, Mac of fee, uh, grandchildren, all the top customers. Um, mainly for it help desk customer service. AIOps those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What's what's their need? What category is it? >>I think they look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on predict S one area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value problem. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service, >>Great stuff, man. Doing great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the cube. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of 80 summit, 2022. And we're gonna be at 80 summit in San, uh, in New York and the summer. So look for that on this calendar, of course go to eight of us, startups.com. I mentioned that it's a site for all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break. >>Okay. Welcome back everyone. This to cubes coverage here in San Francisco, California, a Davis summit, 2022, the beginning of the event season, as it comes back a little bit smaller footprint, a lot of hybrid events going on, but this is actually a physical event, a summit new York's coming in the summer. We'll be there too with the cube on the set. We're getting back in the groove, psyched to be back. We were at reinvent, uh, as well, and we'll see more and more cube, but you're gonna see a lot of virtual cube, a lot of hybrid cube. We wanna get all those conversations, try to get more interviews, more flow going. But right now I'm excited to have Corey Quinn here on the back on the cube chief cloud economists with duck, bill groove, he founder, uh, and chief content person always got great angles, fun comedy, authoritative Corey. Great to see you. Thank you. >>Thanks. Coming on. Sure is a lot of words to describe as shit posting, which is how I describe what I tend to do. Most days, >>Shit posting is an art form now. And if you look at Mark's been doing a lot of shit posting lately, all a billionaires are shit posting, but they don't know how to do it. Like they're not >>Doing it right. Something opportunity there. It's like, here's how to be even more obnoxious and incisive. It's honestly the most terrifying scenario for anyone is if I have that kind of budget to throw at my endeavors, it's like, I get excited with a nonsense I can do with a $20 gift card for an AWS credit compared to, oh well, if I could buy a mid-size island to begin doing this from, oh, then we're having fun. This >>Shit posting trend. Interesting. I was watching a thread go on about, saw someone didn't get a job because of their shit posting and the employer didn't get it. And then someone on the other side, I'll hire the guy cuz I get that's highly intelligent shit posting. So for the audience that doesn't know what shit posting is, what is shit posting? >>It's more or less talking about the world of enterprise tech, which even that sentence is hard to finish without falling asleep and toppling out of my chair in front of everyone on the livestream. But it's doing it in such a way that brings it to life that says the quiet part. A lot of the audience is thinking, but generally doesn't say either because they're polite or not a jackass or more prosaically are worried about getting fired for better or worse. I don't have that particular constraint, >>Which is why people love you. So let's talk about what you, what you think is, uh, worthy and not worthy in the industry right now, obviously, uh, coupons coming up in Spain, which they're having a physical event, you can see the growth of cloud native Amazons, all, all the Adams let see new CEO, Andy move on to be the chief of all. Amazon just saw him. The cover of was it time magazine. Um, he's under a lot of stress. Amazon's changed. Invoice has changed. What's working. What's not, what's rising, what's falling. What's hot. What's not, >>It's easy to sit here and criticize almost anything these folks do. They they're effectively in a fishbowl, but I have trouble imagining the logistics. It takes to wind up handling the catering for a relatively downscale event like this one this year, let alone running a 1.7 million employee company having to balance all the competing challenges and pressures and the rest. I, I just can't fathom what it would be like to look at all of AWS. It's, it's sprawling, immense that dominates our entire industry and say, okay, this is a good start, but I, I wanna focus on something with a broader remit. What is that? How do you even get into that position? And you can't win once you're there. All you can do is hold onto the tiger and hope you don't get mold. Well, >>There's a lot of force for good conversations, seeing a lot of that going on, Amazon's trying to port and he was trying to portray themselves as you know, the Pathfinder, you know, you're the pioneer, um, force for good. And I get that and I think that's a good angle as cloud goes mainstream. There's still the question of, we had a guy on just earlier, who was a skydiving instructor and we were joking about the early days of cloud. Like that was like skydiving, build a parachute open, you know, and now it same kind of thing. As you move to edge, things are like reliable in some areas, but still new, new fringe, new areas. That's crazy. Well, >>Since the last time we've spoken, uh, Steve Schmidt is now the CISO for all of Amazon and his backfill replacement. The AWS CISO is CJ. Moses who as a hobby races, a as a semi-pro race car driver to my understanding, which either, I don't know what direction to take that in either. This is what he does to relax or ultimately, or ultimately it's. Huh? That, that certainly says something about risk assessment. I'm not entirely sure what, but okay. Either way, sounds like more exciting >>Replacement ready <laugh> in case something goes wrong. I, the track highly >>Available >>CSOs. I gotta say one of the things I do like in the recent trend is that the tech companies are getting into the formula one, which I was never a fan of until I watched that Netflix series. But when you look at the formula one, it's pretty cool. Cause it's got some tech angles, I get the whole data instrumentation thing, but the most coolest thing about formula one is they have these new rigs out. Yeah. Where you can actually race in e-sports with other, in pure simulation of the race car. You gotta get the latest and video graphics card, but it's basically a tricked out PC with amazing monitors and you have all the equipment of F1 and you're basically simulating racing. >>Oh, it's great too. And I can see the appeal of these tech companies getting into it because these things are basically rocket shifts. When those cars go, like they're sitting there, we can instrument every last part of what is going on inside that vehicle. And then AWS crops up. And we can bill on every one of those dimensions too. And it's like slow down their hasty pudding one step at a time. But I do see the appeal. >>So I gotta ask you about, uh, what's going in your world. I know you have a lot of great success. We've been following you in the queue for many, many years. Got a great newsletter. Check out Corey Quinn's newsletter, uh, screaming in the cloud program. Uh, you're on the cutting edge and you've got a great balance between really being snarky and, and, and really being delivering content. That's exciting, uh, for people, uh, with a little bit of an edge, um, how's that going? Uh, what's back any blow back late there been uptick. What was, what are some of the things you're hearing from your audience, more Corey, more Corey. And then of course the, the PR team's calling you >>The weird thing about having an audience beyond a certain size is far and away as a landslide. The most common response I get is silence where it's high. I'm emailing an awful lot of people at last week in AWS every week and okay. They must not have heard me it. That is not actually true. People just generally don't respond to email because who responds to email newsletters. That sounds like something, a lunatic might do same story with response to live streams and podcasts. It's like, I'm gonna call into that am radio show and give them a piece of my mind. People generally don't do that. >>We should do that. Actually. I think sure would call in. Oh, I, >>I think >>Chief, we had that right now. People would call in and say, Corey, what do you think about X? >>Yeah. It not, everyone understands the full context of what I do. And in fact, increasingly few people do and that's fine. I, I keep forgetting that sometimes people do not see what I'm doing in the same light that I do. And that's fine. Blowback has been largely minimal. Honestly, I am surprised anything by how little I have gotten over the last five years of doing this, but it would be easier to dismiss me if I weren't generally. Right. When, okay, so you launch this new service and it seems pretty crappy to me cuz when I try and build something, it falls over and begs for help. And people might not like hearing that, but it's what customers are finding too. Yeah. I really am the voice of the customer. >>You know, I always joke with Dave ante about how John Fort's always at, uh, reinvent getting the interview with jazzy now, Andy we're there, you're there. And so we have these rituals at the events. It's all cool. Um, one of the rituals I like about your, um, your content is you like to get on the naming product names. Um, and, and, and, and, and kind of goof on that. Now why I like is because I used to work at ETT Packard where they used to name things as like engineers, HP 1 0 5, or we can't, >>We have a new monitor. How are we gonna name it? Throw the wireless keyboard down the stairs again. And there you go. Yeah. >>It's and the old joke at HP was if they, if they invented sushi, they'd say, yeah, we can't call sushi. It's cold, dead fish. That's what it is. And so the joke was cold. Dead fish is a better name than sushi. So you know is fun. So what's the, what are the, how's the Amazon doing in there? Have they changed their naming, uh, strategy, uh, on some of their, their >>Producting, they're going in different directions. When they named Amazon Aurora, they decided to explore a new theme of Disney princesses as they go down those paths. And some things are more descriptive. Some people are clearly getting bonused on a number of words. They can shove into it. Like the better a service is the longer it's name. Like AWS systems manager, session manager is a great one. I love the service, ridiculous name. They have systems manager, parameter store, which is great. They have secrets manager, which does the same thing. It's two words less, but that one costs money in a way that systems manage your parameter store does not. It's >>Fun. What's your, what's your favorite combination of acronyms >>Combination of you >>Got Ks. You got EMR, you got EC two. You got S three SQS. Well, Redshift the on an acronym, you >>Gots is one of my personal favorites because it's either elastic block store or elastic bean stock, depending entirely on the context of the conversation. >>They still up bean stalk. Or is that still around? Oh, >>They never turn anything off. They're like the anti Google, Google turns things off while they're still building it. Whereas Amazon is like, wow, we built this thing in 2005 and everyone hates it. But while we certainly can't change it, now it has three customers on it. John three <laugh>. >>Okay. >>Simple BV still haunts our dreams. >>I, I actually got an email. I saw one of my, uh, servers, all these C two S were being deprecated and I got an email I'm like, I couldn't figure out. Why can you just like roll it over? Why, why are you telling me just like, give me something else. Right. Okay. So let me talk about, uh, the other things I want to ask you is that like, okay. So as Amazon gets better in some areas, where do they need more work in your opinion? Because obviously they're all interested in new stuff and they tend to like put it out there for their end to end customers. But then they've got ecosystem partners who actually have the same product. Yes. And, and this has been well documented. So it's, it's not controversial. It's just that Amazon's got a database, Snowflake's got a database service. So Redshift, snowflake database is, so you got this co-op petition. Yes. How's that going? And what are you hearing about the reaction to any of that stuff? >>Depends on who you ask. They love to basically trot out a bunch of their partners who will say nice things about them. And it very much has heirs of, let's be honest, a hostage video, but okay. Cuz these companies do partner with Amazon and they cannot afford to rock the boat too far. I'm not partnered with anyone. I can say what I want and they're basically restricted to taking away my birthday at worse so I can live with that. >>All right. So I gotta ask about multi-cloud cause obviously the other cloud shows are coming up. Amazon hated that word. Multi-cloud um, a lot of people are saying, you know, it's not a real good marketing word, like multi sounds like, you know, root canal. Mm-hmm <affirmative> right. So is there a better description for multi-cloud >>Multiple single points? >>Dave loves that term. Yeah. >>Yeah. You're building in multiple single points of failure. Do it for the right reasons or don't do it as a default. I believe not doing it is probably the right answer. However, and if I were, if I were Amazon, I wouldn't want to talk about multi-cloud either as the industry leader, talk about other clouds, bad direction to go in from a market cap perspective, it doesn't end well for you, but regardless of what they want to talk about, or don't want to talk about what they say, what they don't say, I tune all of it out. And I look at what customers are doing and multi-cloud exists in a variety of forms. Some brilliant, some brain dead. It depends a lot on context. But my general response is when someone gets on stage from a company and tells me to do a thing that directly benefits their company. I am skeptical at best. Yeah. When customers get on stage and say, this is what we're doing, because it solves problems. That's when I shut up and listen. Yeah. >>Cool. Awesome. Corey, I gotta ask you a question, cause I know you, we you've been, you know, fellow journeymen and the, and the cloud journey going to all the events and then the pandemic hit where now in the third year, who knows what it's gonna gonna end. Certainly events are gonna look different. They're gonna be either changing footprint with the virtual piece, new group formations. Community's gonna emerge. You got a pretty big community growing and it's throwing like crazy. What's the weirdest or coolest thing, or just big chain angels. You've seen with the pandemic, uh, from your perspective, cuz you've been in the you're in the middle of the whitewater rafting. You've seen the events you circle offline. You saw the online piece, come in, you're commentating. You're calling balls and strikes in the industry. You got a great team developing over there. Duck bill group. What's the big aha moment that you saw with the pandemic. Weird, fun, serious, real in the industry and with customers what's >>Accessibility. Reinvent is a great example. When in the before times it's open to anyone who wants to attend, who can pony up two grand and a week in Las Vegas and get to Las Vegas from wherever they happen to be by moving virtually suddenly it, it embraces the reality that talent is even distributed. Opportunity is not. And that means that suddenly these things are accessible to a wide swath of audience and potential customer base and the rest that hadn't been invited to the table previously, it's imperative that we not lose that. It's nice to go out and talk to people and have people come up and try and smell my hair from time to time, I smell delightful. Let make assure you, but it was, but it's also nice to be. >>I have a product for you if you want, you know. >>Oh, excellent. I look forward to it. What is it putting? Why not? <laugh> >>What else have you seen? So when accessibility for talent, which by the way is totally home run. What weird things have happened that you've seen? Um, that's >>Uh, it's, it's weird, but it's good that an awful lot of people giving presentations have learned to tighten their message and get to the damn point because most people are not gonna get up from a front row seat in a conference hall, midway through your Aing talk and go somewhere else. But they will change a browser tab and you won't get them back. You've gotta be on point. You've gotta be compelling if it's going to be a virtual discussion. >>Yeah. And also turn off your IMEs too. >>Oh yes. It's always fun in the, in the meetings when you're talking to someone and their co is messaging them about, should we tell 'em about this? And I'm sitting there reading it and it's >>This guy is really weird. Like, >>Yes I am and I bring it into the conversation and then everyone's uncomfortable. It goes, wow. >>Why not? I love when my wife yells at me over I message. When I'm on a business call, like, do you wanna take that about no, I'm good. >>No, no. It's better off. I don't. No, the only encourager it's fine. >>My kids. Excellent. Yeah. That's fun again. That's another weird thing. And, and then group behavior is weird. Now people are looking at, um, communities differently. Yes. Very much so, because if you're fatigued on content, people are looking for the personal aspect. You're starting to see much more of like yeah. Another virtual event. They gotta get better. One and two who's there. >>Yeah. >>The person >>That's a big part of it too is the human stories are what are being more and more interesting. Don't get up here and tell me about your product and how brilliant you are and how you built it. That's great. If I'm you, or if I wanna work with you or I want to compete with you, or I wanna put on my engineering hat and build it myself. Cause why would I buy anything? That's more than $8. But instead, tell me about the problem. Tell me about the painful spot that you specialize in. Tell me a story there. >>I, I >>Think that gets a glimpse in a hook and >>Makes more, more, I think you nailed it. Scaling storytelling. Yes. And access to better people because they don't have to be there in person. I just did it thing. I never, we never would've done the queue. We did. Uh, Amazon stepped up in sponsors. Thank you, Amazon for sponsoring international women's day, we did 30 interviews, APAC. We did five regions and I interviewed this, these women in Asia, Pacific eight, PJ, they called for in this world. And they're amazing. I never would've done those interviews cuz I never, would've seen 'em at an event. I never would've been in Japan or Singapore to access them. And now they're in the index. They're in the network. They're collaborating on LinkedIn. So a threads are developing around connections that I've never seen before. Yes. Around the content, >>Absolutely >>Content value plus >>The networking. And that is the next big revelation of this industry is going to realize you have different companies. And in Amazon's case, different service teams, all, all competing with each other, but you have the container group and you have the database group and you have the message cuing group. But customers don't really want to build things from spare parts. They want a solution to a problem. I want to build an app that does Twitter for pets or whatever it is I'm trying to do. I don't wanna basically have to pick and choose and fill my shopping cart with all these different things. I want something that's gonna give me what I'm trying to get as close to turnkey as possible. Moving up the stack. That is the future. And just how it gets here is gonna be >>Well we're here with Corey Quinn, the master of the master of content here in the a ecosystem. Of course we we've been following up in the beginnings. Great guy. Check out his blog, his site, his newsletter screaming podcast. Cory, final question for you. Uh, what do you hear doing what's on your agenda this week in San Francisco and give a plug for the duck build group. What are you guys doing? I know you're hiring some people what's on the table for the company. What's your focus this week and put a plug in for the group. >>I'm here as a customer and basically getting outta my cage cuz I do live here. It's nice to actually get out and talk to folks who are doing interesting things at the duck build group. We solve one problem. We fixed the horrifying AWS bill, both from engineering and architecture, advising as well as negotiating AWS contracts because it turns out those things are big and complicated. And of course my side media projects last week in aws.com, we are, it it's more or less a content operation where I indulge my continual and ongoing law of affair with the sound of my own voice. >><laugh> and you good. It's good content. It's on, on point fun, Starky and relevant. So thanks for coming to the cube and sharing with us. Appreciate it. No, thank you. Fun. You. Okay. This the cube covers here in San Francisco, California, the cube is back at to events. These are the summits, Amazon web services summits. They happen all over the world. We'll be in New York and obviously we're here in San Francisco this week. I'm John furry. Keep, keep it right here. We'll be back with more coverage after this short break. Okay. Welcome back everyone. This's the cubes covers here in San Francisco, California, we're live on the show floor of AWS summit, 2022. I'm John for host of the cube and remember AWS summit in New York city coming up this summer, we'll be there as well. And of course reinvent the end of the year for all the cube coverage on cloud computing and AWS. The two great guests here from the APN global APN se Jenko and Jeff Grimes partner leader, Jeff and se is doing partnerships global APN >>AWS global startup program. Yeah. >>Okay. Say that again. >>AWS global startup program. >>That's the official name. >>I love >>It too long, too long for me. Thanks for coming on. Yeah, of course. Appreciate it. Tell us about what's going on with you guys. What's the, how was you guys organized? You guys we're obviously were in San Francisco bay area, Silicon valley, zillions of startups here, New York. It's got another one we're gonna be at tons of startups. Lot of 'em getting funded, big growth and cloud big growth and data security, hot and sectors. >>Absolutely. >>So maybe, maybe we could just start with the global startup program. Um, it's essentially a white glove service that we provide to startups that are built on AWS. And the intention there is to help identify use cases that are being built on top of AWS. And for these startups, we want to provide white glove support in co building products together. Right. Um, co-marketing and co-selling essentially, um, you know, the use cases that our customers need solved, um, that either they don't want to build themselves or are perhaps more innovative. Um, so the, a AWS global startup program provides white glove support, dedicated headcount for each one of those pillars. Um, and within our program, we've also provided incentives, programs go to market activities like the AWS startup showcase that we've built for these startups. >>Yeah. By the way, start AWS startups.com is the URL, check it out. Okay. So partnerships are key. Jeff, what's your role? >>Yeah. So I'm responsible for leading the overall F for, for the AWS global startup program. Um, so I've got a team of partner managers that are located throughout the us, uh, managing a few hundred startup ISVs right now. <laugh> >>Yeah, I got >>A lot. We've got a lot. >>There's a lot. I gotta, I gotta ask the tough question. Okay. I'm I'm a startup founder. I got a team. I just got my series a we're grown. I'm trying to hire people. I'm super busy. What's in it for me. Yeah. What do you guys bring to the table? I love the white glove service, but translate that what's in it. What do I get out of it? What's >>A good story. Good question. I focus, I think. Yeah, because we get, we get to see a lot of partners building their businesses on AWS. So, you know, from our perspective, helping these partners focus on what, what do we truly need to build by working backwards from customer feedback, right? How do we effectively go to market? Because we've seen startups do various things, um, through trial and error, um, and also just messaging, right? Because oftentimes partners or rather startups, um, try to boil the ocean with many different use cases. So we really help them, um, sort of laser focus on what are you really good at and how can we bring that to the customer as quickly as possible? >>Yeah. I mean, it's truly about helping that founder accelerate the growth of their company. Yeah. Right. And there's a lot that you can do with AWS, but focus is truly the key word there because they're gonna be able to find their little piece of real estate and absolutely deliver incredible outcomes for our customers. And then they can start their growth curve there. >>What are some of the coolest things you've seen with the APN that you can share publicly? I know you got a lot going on there, a lot of confidentiality. Um, but you know, we're here lot of great partners on the floor here. I'm glad we're back at events. Uh, a lot of stuff going on digitally with virtual stuff and, and hybrid. What are some of the cool things you guys have seen in the APN that you can point to? >>Yeah, absolutely. I mean, I can point to few, you can take them. Sure. So, um, I think what's been fun over the years for me personally, I came from a startup, ran sales at an early stage startup and, and I went through the whole thing. So I have a deep appreciation for what these guys are going through. And what's been interesting to see for me is taking some of these early stage guys, watching them progress, go public, get acquired, and see that big day mm-hmm <affirmative>, uh, and being able to point to very specific items that we help them to get to that point. Uh, and it's just a really fun journey to watch. >>Yeah. I, and part of the reason why I really, um, love working at the AWS, uh, global startup program is working with passionate founders. Um, I just met with a founder today that it's gonna, he's gonna build a very big business one day, um, and watching them grow through these stages and supporting that growth. Um, I like to think of our program as a catalyst for enterprise sort of scale. Yeah. Um, and through that we provide visibility, credibility and growth opportunities. >>Yeah. A lot, a lot of partners too. What I found talking to staff founders is when they have that milestone, they work so hard for it. Whether it's a B round C round Republic or get bought. Yeah. Um, then they take a deep breath and they look back at wow, what a journey it's been. So it's kind of emotional for sure. Yeah. Still it's a grind. Right? You gotta, I mean, when you get funding, it's still day one. You don't stop. It's no celebrate, you got a big round or valuation. You still gotta execute >>And look it's hypercompetitive and it's brutally difficult. And our job is to try to make that a little less difficult and navigate those waters right. Where everyone's going after similar things. >>Yeah. I think as a group element too, I observe that startups that I, I meet through the APN has been interesting because they feel part of AWS. Yeah, totally. As a group of community, as a vibe there. Um, I know they're hustling, they're trying to make things happen. But at the same time, Amazon throws a huge halo effect. I mean, that's a huge factor. I mean, yeah. You guys are the number one cloud in the business, the growth in every sector is booming. Yeah. And if you're a startup, you don't have that luxury yet. And look at companies like snowflake, they're built on top of AWS. Yeah. I mean, people are winning by building on AWS. >>Yeah. And our, our, our program really validates their technology first. So we have, what's called a foundation's technical review that we put all of our startups through before we go to market. So that when enterprise customers are looking at startup technology, they know that it's already been vetted. And, um, to take that a step further and help these partners differentiate, we use programs like the competency programs, the DevOps compet, the, the security competency, which continues to help, um, provide sort of a platform for these startups, help them differentiate. And also there's go to market benefits that are associated with that. >>Okay. So let me ask the, the question that's probably on everyone's mind, who's watching. Certainly I asked this a lot. There's a lot of companies startups out there who makes the, is there a criteria? Oh God, it's not like his sports team or anything, but like sure. Like there's activate program, which is like, there's hundreds of thousands of startups out there. Not everyone is at the APN. Right? Correct. So ISVs again, that's a whole nother, that's a more mature partner that might have, you know, huge market cap or growth. How do you guys focus? How do you guys focus? I mean, you got a good question, you know, a thousand flowers blooming all the time. Is there a new way you guys are looking at it? I know there's been some talk about restructure or, or new focus. What's the focus. >>Yeah. It's definitely not an easy task by any means. Um, but you know, I recently took over this role and we're really trying to establish focus areas, right. So obviously a lot of the fees that we look after our infrastructure ISVs, that's what we do. Uh, and so we have very specific pods that look after different type of partners. So we've got a security pod, we've got a DevOps pod, we've got core infrastructure, et cetera. And really we're trying to find these ISVs that can solve, uh, really interesting AWS customer challenges. >>So you guys have a deliberate, uh, focus on these pillars. So what infrastructure, >>Security, DevOps, and data and analytics, and then line of business >>Line of business line, like web marketing >>Solutions, business apps, >>Business, this owner type thing. Exactly. >>Yeah, exactly. >>So solutions there. Yeah. More solutions and the other ones are like hardcore. So infrastructure as well, like storage, backup, ransomware of stuff, or, >>Uh, storage, networking. >>Okay. Yeah. The classic >>Database, et cetera. Right. >>And so there's teams on each pillar. >>Yep. So I think what's, what's fascinating for the startup that we cover is that they've got, they truly have support from a build market sell perspective. Right. So you've got someone who's technical to really help them get the technology, figured out someone to help them get the marketing message dialed and spread, and then someone to actually do the co-sell, uh, day to day activities to help them get in front of customers. >>Probably the number one request that we always ask for Amazon is can we waste that sock report? Oh, download it, the console, which we use all the time. Exactly. But security's a big deal. I mean, you know, SREs are evolving, that role of DevOps is taking on dev SecOps. Um, I, I could see a lot of customers having that need for a relationship to move things faster. Do you guys provide like escalation or is that a part of a service or not, not part of a, uh, >>Yeah, >>So the partner development manager can be an escalation point. Absolutely. Think of them as an extension of your business inside of AWS. >>Great. And you guys how's that partner managers, uh, measure >>On those three pillars. Right. Got it. Are we billing, building valuable use cases? So product development go to market, so go to market activities, think blog, posts, webinars, case studies, so on and so forth. And then co-sell not only are we helping these partners win their current opportunities that they are sourcing, but can we also help them source net new deals? Yeah. Right. That's >>Very important. I mean, top asked from the partners is get me in front of customers. Right. Um, not an easy task, but that's a huge goal of ours to help them grow their top >>Line. Right. Yeah. In fact, we had some interviews here on the cube earlier talking about that dynamic of how enterprise customers are buying. And it's interesting, a lot more POCs. I have one partner here that you guys work with, um, on observability, they got a huge POC with capital one mm-hmm <affirmative> and the enterprises are engaging the startups and bringing them in. So the combination of open source software enterprises are leaning into that hard and bringing young growing startups in mm-hmm <affirmative>. Yep. So I could see that as a huge service that you guys can bring people in. >>Right. And they're bringing massively differentiated technology to the table. Mm-hmm <affirmative> the challenge is they just might not have the brand recognition that the big guys have. And so that it's our job is how do you get that great tech in front of the right situations? >>Okay. So my next question is about the show here, and then we'll talk globally. So here in San Francisco sure. You know, Silicon valley bay area, San Francisco bay area, a lot of startups, a lot of VCs, a lot of action. Mm-hmm <affirmative> so probably a big market for you guys. Yeah. So what's exciting here in SF and then outside SF, you guys have a global program, you see any trends that are geography based or is it sure areas more mature? There's certain regions that are better. I mean, I just interviewed a company here that's doing, uh, AWS edge really well in these cases. It's interesting that these, the partners are filling a lot of holes and gaps in the opportunities with AWS. So what's exciting here. And then what's the global perspective. >>Yeah, totally. So obviously a ton of partners, I, from the bay area that we support. Um, but we're seeing a lot of really interesting technology coming out of AMEA specifically. Yeah. Uh, and making a lot of noise here in the United States, which is great. Um, and so, you know, we definitely have that global presence and, and starting to see super differentiated technology come out of those regions. >>Yeah. Especially Tel Aviv. Yeah. >>Amy real quick, before you get in the surge. It's interesting. The VC market in, in Europe is hot. Yeah. They've got a lot of unicorns coming in. We've seen a lot of companies coming in. They're kind of rattling their own, you know, cage right now. Hey, look at us. We'll see if they crash, you know, but we don't see that happening. I mean, people have been projecting a crash now in, in the startup ecosystem for at least a year. It's not crashing. In fact, funding's up. >>Yeah. The pandemic was hard on a lot of startups for sure. Yeah. Um, but what we've seen is many of these startups, they, as quickly as they can grow, they can also pivot as, as, as well. Um, and so I've actually seen many of our startups grow through the pandemic because their use cases are helping customers either save money, become more operationally efficient and provide value to leadership teams that need more visibility into their infrastructure during a pandemic. >>It's an interesting point. I talked to Andy jazzy and Adam Leski both say the same thing during the pandemic necessity, the mother of all invention. Yep. And startups can move fast. So with that, you guys are there to assist if I'm a startup and I gotta pivot cuz remember iterate and pivot, iterate and pivot. So you get your economics, that's the playbook of the ventures and the models. >>Exactly. How >>Do you guys help me do that? Give me an example of walk me through, pretend me I'm a startup. Hey, I am on the cloud. Oh my God. Pandemic. They need video conferencing. Hey cube. Yeah. What do I need? Surge? What, what do I do? >>That's a good question. First thing is just listen. Yeah. I think what we have to do is a really good job of listening to the partner. Um, what are their needs? What is their problem statement and where do they want to go at the end of the day? Um, and oftentimes because we've worked with so many successful startups, they have come out of our program. We have, um, either through intuition or a playbook, determined what is gonna be the best path forward and how do we get these partners to stop focusing on things that will eventually, um, just be a waste of time yeah. And, or not provide, or, you know, bring any fruit to the table, which, you know, essentially revenue. >>Well, we love star rights here in the cube because one, um, they have good stories. They're oil and cutting edge, always pushing the envelope and they're kind of disrupting someone else. Yeah. And so they have an opinion. They don't mind sharing on camera. So love talking to startups. We love working with you guys on our startup showcases startups.com. Check out AWS startups.com and you got the showcases, uh, final. We I'll give you guys the last word. What's the bottom line bumper sticker for AP the global APN program. Summarize the opportunity for startups, what you guys bring to the table and we'll close it out. Totally start >>With you. Yeah. I think the AWS global startup program's here to help companies truly accelerate their business full stop. Right. And that's what we're here for. I love it. >>It's a good way to, it's a good way to put it Dito. >>Yeah. All right, sir. Thanks for coming on. Thanks John. Great to see you love working with you guys. Hey, startups need help. And the growing and huge market opportunities, the shift cloud scale data engineering, security infrastructure, all the markets are exploding in growth because of the digital transformation of the realities here. Open source and cloud all making it happen here in the cube in San Francisco, California. I'm John furrier, your host. Thanks for watching >>John. >>Hello and welcome back to the cubes live coverage here in San Francisco, California for AWS summit, 2022. I'm John for host of the cube. Uh, two days of coverage, AWS summit, 2022 in New York city. Coming up this summer, we'll be there as well at events are back. The cube is back of course, with the cube virtual cube hybrid, the cube.net, check it out a lot of content this year, more than ever, a lot more cloud data cloud native, modern applic is all happening. Got a great guest here. Jeremy Burton, Cub alumni, uh, CEO of observe Inc in the middle of all the cloud scale, big data observability Jeremy. Great to see you. Thanks >>Always great to come and talk to you on the queue, man. It's been been a few years, so, >>Um, well you, you got your hands. You're in the trenches with great startup, uh, good funding, great board, great people involved in the observability hot area, but also you've been a senior executive president of Dell, uh, EMC, uh, 11 years ago you had a, a vision and you actually had an event called cloud meets big data. Um, yeah. And it's here. You predicted it 11 years ago. Um, look around it's cloud meets big data. >>Yeah. I mean the, the cloud thing I think, you know, was, was probably already a thing, but the big data thing I do claim credit for, for, for sort of catching that bus out, um, you know, we, we were on the, the, the bus early and, and I think it was only inevitable. Like, you know, if you could bring the economics and the compute of cloud to big data, you, you could find out things you could never possibly imagine. >>So you're close to a lot of companies that we've been covering deeply. Snowflake obviously are involved, uh, the board level, you know, the founders, you know, the people there cloud, you know, Amazon, you know, what's going on here? Yeah. You're doing a startup as the CEO at the helm, uh, chief of observ, Inc, which is an observability, which is to me in the center of this confluence of data engineering, large scale integrations, um, data as code integrating into applic. I mean, it's a whole nother world developing, like you see with snowflake, it means snowflake is super cloud as we call it. So a whole nother wave is here. What's your, what's this wave we're on what's how would you describe the wave? >>Well, a couple of things, I mean, people are, I think riding more software than, than ever fall. Why? Because they've realized that if, if you don't take your business online and offer a service, then you become largely irrelevant. And so you you've got a whole set of new applications. I think, I think more applications now than any point. Um, not, not just ever, but the mid nineties, I always looked at as the golden age of application development. Now back then people were building for windows. Well, well now they're building for things like AWS is now the platform. Um, so you've got all of that going on. And then at the same time, the, the side effect of these applications is they generate data and lots of data and the, you know, the sort of the transactions, you know, what you bought today or something like that. But then there's what we do, which is all the telemetry data, all the exhaust fumes. And I think people really are realizing that their differentiation is not so much their application. It's their understanding of the data. Can, can I understand who my best customers are, what I sell today. If people came to my website and didn't buy, then I not, where did they drop off all of that they wanna analyze. And, and the answers are all in the data. The question is, can you understand it >>In our last startup showcase, we featured data as code. One of the insights that we got out of that I wanna get your opinion on our reaction to is, is that data used to be put into a data lake and turns into a data swamp or throw into the data warehouse. And then we'll do some query, maybe a report once in a while. And so data, once it was done, unless it was real time, even real time was not good anymore after real time. That was the old way. Now you're seeing more and more, uh, effort to say, let's go look at the data cuz now machine learning is getting better. Not just train once mm-hmm <affirmative> they're iterating. Yeah. This notion of iterating and then pivoting, iterating and pivoting. Yeah, that's a Silicon valley story. That's like how startups work, but now you're seeing data being treated the same way. So now you have another, this data concept that's now yeah. Part of a new way to create more value for the apps. So this whole, this whole new cycle of >>Yeah. >>Data being reused and repurposed and figured out and >>Yeah, yeah. I'm a big fan of, um, years ago. Uh, uh, just an amazing guy, Andy McAfee at the MIT C cell labs I spent time with and he, he had this line, which still sticks to me this day, which is look I'm I'm. He said I'm part of a body, which believes that everything is a matter of data. Like if you, of enough data, you can answer any question. And, and this is going back 10 years when he was saying these kind of things and, and certainly, you know, research is on the forefront. But I, I think, you know, starting to see that mindset of the, the sort of MIT research be mainstream, you know, in enterprises, they they're realizing that yeah, it is about the data. You know, if I can better understand my data better than my competitor than I've got an advantage. And so the question is is, is how, what, what technologies and what skills do I need in my organization to, to allow me to do that. So >>Let's talk about observing you the CEO of, okay. Given you've seen the wave before you're in the front lines of observability, which again is in the center of all this action what's going on with the company. Give a quick minute to explain, observe for the folks who don't know what you guys do. What's the company doing? What's the funding status, what's the product status and what's the customer status. Yeah. >>So, um, we realized, you know, a handful of years ago, let's say five years ago that, um, look, the way people are building applications is different. They they're way more functional. They change every day. Uh, but in some respects they're a lot more complicated. They're distributed. They, you know, microservices architectures and when something goes wrong, um, the old way of troubleshooting and solving problems was not gonna fly because you had SA so much change going into production on a daily basis. It was hard to tell like where the problem was. And so we thought, okay, it's about time. Somebody looks at the exhaust fumes from this application and all the telemetry data and helps people troubleshoot and make sense of the problems that they're seeing. So, I mean, that's observability, it's actually a term that goes back to the 1960s. It was a guy called, uh, Rudolph like, like everything in tech, you know, it's, it's a reinvention of, of something from years gone by. >>But, um, there's a guy called, um, Rudy Coleman in 1960s, kinder term. And, and, and the term was been able to determine the state of a system by looking at its external outputs. And so we've been going on this for, uh, the best part of the all years now. Um, it took us three years just to build the product. I think, I think what people don't appreciate these days often is the barrier to entry in a lot of these markets is quite high. You, you need a lot of functionality to have something that's credible with a customer. Um, so yeah, this last year we, we, we did our first year selling, uh, we've got about 40 customers now. <affirmative> um, we just we've got great investors for the hill ventures. Uh, I mean, Mike SP who was, you know, the, the guy who was the, really, the first guy in it snowflake and the, the initial investor were fortunate enough to, to have Mike on our board. And, um, you know, part of the observed story yeah. Is closely knit with snowflake because all of that time data know we, we still are in there. >>So I want to get, uh, >>Yeah. >>Pivot to that. Mike Pfizer, snowflake, Jeremy Burton, the cube kind of, kind of same thinking this idea of a super cloud or what snowflake became snowflake is massively successful on top of AWS. Mm-hmm <affirmative> and now you're seeing startups and companies build on top of snowflake. Yeah. So that's become an entrepreneurial story that we think that to go big in the cloud, you can have a cloud on a cloud, uh, like as Jerry, Jerry Chan and Greylock calls it castles in the cloud where there are moats in the cloud. So you're close to it. I know you're doing some stuff with snowflake. So a startup, what's your view on building on top of say a snowflake or an AWS, because again, you gotta go where the data is. You need all the data. >>Yeah. So >>What's your take on that? >>I mean, having enough gray hair now, um, you know, again, in tech, I think if you wanna predict the future, look at the past. And, uh, you know, to many years ago, 25 years ago, I was at a, a smaller company called Oracle and an Oracle was the database company. And, uh, their, their ambition was to manage all of the world's transactional data. And they built on a platform or a couple of platforms, one, one windows, and the other main one was Solaris. And so at that time, the operator and system was the platform. And, and then that was the, you know, ecosystem that you would compete on top of. And then there were companies like SAP that built applications on top of Oracle. So then wind the clock forward 25 years gray hairs. <laugh> the platform, isn't the operating system anymore. The platform is AWS, you know, Google cloud. I gotta probably look around if I say that in. Yeah. It's >>Okay. But hyperscale, yeah. CapX built out >>That is the new platform. And then snowflake comes along. Well, their aspiration is to manage all of the, not just human generator data, but machine generated data in the world of cloud. And I think they they've done an amazing job doing for the, I'd say, say the, the big data world, what Oracle did for the relational data world, you know, way back 25 years ago. And then there are folks like us come along and, and of course my ambition would be, look, if, if we can be as successful as an SAP building on top of snow snowflake, uh, as, as they were on top of Oracle, then, then we'd probably be quite happy. >>So you're building on top of snowflake. >>We're building on top of snowflake a hundred percent. And, um, you know, I've had folks say to me, well, aren't you worried about that? Isn't that a risk? It's like, well, that that's a risk. You >>Still on the board. >>Yeah. I'm still on the board. Yeah. That that's a risk I'm prepared to take <laugh> I am long on snowflake you, >>Well, you're in a good spot. Stay on the board, then you'll know what's going on. Okay. No know just doing, but the, this is a real dynamic. It is. It's not a one off it's. >>Well, and I do believe as well that the platform that you see now with AWS, if you look at the revenues of AWS is an order of magnitude more than Microsoft was 25 years ago with windows mm-hmm <affirmative>. And so I believe the opportunity for folks like snowflake and folks like observe it's an order of magnitude more than it was for the Oracle and the SAPs of the old >>World. Yeah. And I think this is really, I think this is something that this next generation of entrepreneurship is the go big scenario is you gotta be on a platform. Yeah. >>It's quite >>Easy or be the platform, but it's hard. There's only like how many seats are at that table left. >>Well, value migrates up over time. So, you know, when the cloud thing got going, there were probably 10, 20, 30, you know, Rackspace and there's 1,000,001 infrastructure, a service platform as a service, my, my old, uh, um, employee EMC, we had pivotal, you know, pivotal was a platform as a service. You don't hear so much about it, these, but initially there's a lot of players and then it consolidates. And then to, to like extract, uh, a real business, you gotta move up, you gotta add value, you gotta build databases, then you gotta build applications. So >>It's interesting. Moving from the data center of the cloud was a dream for starters. Cause then if the provision, the CapEx, now the CapEx is in the cloud. Then you build on top of that, you got snowflake you on top of that, the >>Assumption is almost that compute and storage is free. I know it's not quite free. Yeah. It's >>Almost free, >>But, but you can, you know, as an application vendor, you think, well, what can I do if I assume compute and storage is free, that's the mindset you've gotta get into. >>And I think the platform enablement to value. So if I'm an entrepreneur, I'm gonna get a serious, multiple of value in what I'm paying. Yeah. Most people don't even blanket their Avis pills unless they're like massively huge. Yeah. Then it's a repatriation question or whatever discount question, but for most startups or any growing company, the Amazon bill should be a small factor. >>Yeah. I mean, a lot of people, um, ask me like, look, you're building on snowflake. Um, you, you know, you are, you are, you're gonna be, you're gonna be paying their money. How, how, how, how does that work with your business model? If you're paying them money, you know, do, do you have a viable business? And it's like, well, okay. I, we could build a database as well in observe, but then I've got half the development team working on in that will never be as good as snowflake. And so we made the call early on that. No, no, we, we wanna innovate above the database. Yeah. Right. Snowflake are doing a great job of innovating on the database and, and the same is true of something like Amazon, like, like snowflake could have built their own cloud and their own platform, but they didn't. >>Yeah. And what's interesting is that Dave <inaudible> and I have been pointing this out and he's actually more on snowflake. I I've been looking at data bricks, um, and the same dynamics happening, the proof is the ecosystem. Yeah. I mean, if you look at Snowflake's ecosystem right now and data bricks it's exploding. Right. I mean, the shows are selling out the floor. Space's book. That's the old days at VMware. Yeah. The old days at AWS >>One and for snowflake and, and any platform provider, it's a beautiful thing. You know, we build on snowflake and we pay them money. They don't have to sell to us. Right. And we do a lot of the support. And so the, the economics work out really, really well. If you're a platform provider and you've got a lot of ecosystems. >>Yeah. And then also you get, you get a, um, a trajectory of, uh, economies of scale with the institutional knowledge of snowflake integrations, right. New products. You're scaling that function with the, >>Yeah. I mean, we manage 10 petabytes of data right now. Right. When I, when I, when I arrived at EMC in 2010, we had, we had one petabyte customer. And, and so at observe, we've been only selling the product for a year. We have 10 petabytes of data under management. And so been able to rely on a platform that can manage that is invaluable, >>You know, but Jeremy Greek conversation, thanks for sharing your insights on the industry. Uh, we got a couple minutes left. Um, put a plug in for observe. What do you guys, I know you got some good funding, great partners. I don't know if you can talk about your, your, your POC customers, but you got a lot of high ends folks that are working with you. You getting traction. Yeah. >>Yeah. >>Scales around the corner. Sounds like, are you, is that where you are scale? >>Got, we've got a big announcement coming up in two or weeks. We've got, we've got new funding, um, which is always great. Um, the product is, uh, really, really close. I think, as a startup, you always strive for market fit, you know, which is at which point can you just start hiring salespeople? And the revenue keeps going. We're getting pretty close to that right now. Um, we've got about 40 SaaS companies run on the platform. They're almost all AWS Kubernetes, uh, which is our sweet spot to begin with, but we're starting to get some really interesting, um, enterprise type customers. We're, we're, you know, F five networks we're POC in right now with capital one, we got some interest in news around capital one coming up. I, I can't share too much, uh, but it's gonna be exciting. And, and like I saids hill continued to, to, to stick, >>I think capital one's a big snowflake customer as well. Right. They, >>They were early in one of the things that attracted me to capital one was they were very, very good with snowflake early on. And, and they put snowflake in a position in the bank where they thought that snowflake could be successful. Yeah. And, and today that, that is one of Snowflake's biggest accounts. >>So capital one, very innovative cloud, obviously AIOS customer and very innovative, certainly in the CISO and CIO, um, on another point on where you're at. So you're, Prescale meaning you're about to scale, right? So you got POCs, what's that trick GE look like, can you see around the corner? What's, what's going on? What's on, around the corner. That you're, that you're gonna hit the straight and narrow and, and gas it >>Fast. Yeah. I mean, the, the, the, the key thing for us is we gotta get the product. Right. Um, the nice thing about having a guy like Mike Pfizer on the board is he doesn't obsess about revenue at this stage is questions that the board are always about, like, is the product, right? Is the product right? Is the product right? If you got the product right. And cuz we know when the product's right, we can then scale the sales team and, and the revenue will take care of itself. Yeah. So right now all the attention is on the product. Um, the, this year, the exciting thing is we were, we're adding all the tracing visualizations. So people will be able to the kind of things that back in the day you could do with the new lakes and, and AppDynamics, the last generation of, of APM tools, you're gonna be able to do that within observe. And we've already got the logs and the metrics capability in there. So for us, this year's a big one, cuz we sort of complete the trifecta, you know, the, the logs, >>What's the secret sauce observe. What if you had the, put it into a, a sentence what's the secret sauce? I, >>I, I think, you know, an amazing founding engineering team, uh, number one, I mean, at the end of the day, you have to build an amazing product and you have to solve a problem in a different way. And we've got great long term investors. And, and the biggest thing our investors give is actually it's not just money. It gives us time to get the product, right. Because if we get the product right, then we can get the growth. >>Got it. Final question. Why I got you here? You've been on the enterprise business for a long time. What's the buyer landscape out there. You got people doing POCs on capital one scale. So we know that goes on. What's the appetite at the buyer side for startups and what are their requirements that you're seeing? Uh, obviously we're seeing people go in and dip into the startup pool because new ways to refactor their business restructure. So a lot happening in cloud. What's the criteria. How are enterprises engaging in with startups? >>Yeah. I mean, enterprises, they know they've gotta spend money transforming the business. I mean, this was, I almost feel like my old Dell or EMC self there, but, um, what, what we were saying five years ago is happening. Um, everybody needs to figure out out a way to take their, this to this digital world. Everybody has to do it. So the nice thing from a startup standpoint is they know at times they need to risk or, or take a bet on new technology in order to, to help them do that. So I think you've got buyers that a have money, uh, B prepared to take risks and it's, it's a race against time to, you know, get their, their offerings in this. So a new digital footprint, >>Final, final question. What's the state of AWS. Where do you see them going next? Obviously they're continuing to be successful. How does cloud 3.0, or they always say it's day one, but it's more like day 10. Uh, but what's next for Aw. Where do they go from here? Obviously they're doing well. They're getting bigger and bigger. >>Yeah. They're, they're, it's an amazing story. I mean, you know, we we're, we're on AWS as well. And so I, I think if they keep nurturing the builders in the ecosystem, then that is their superpower. They, they have an early leads. And if you look at where, you know, maybe the likes of Microsoft lost the plot in the, in the late it was, they stopped, uh, really caring about developers and the folks who were building on top of their ecosystem. In fact, they started buying up their ecosystem and competing with people in their ecosystem. And I see with AWS, they, they have an amazing head start and if they did more, you know, if they do more than that, that's, what's gonna keep the jut rolling for many years to come. Yeah, >>They got the silicone and they got the staff act, developing Jeremy Burton inside the cube, great resource for commentary, but also founding with the CEO of a company called observing in the middle of all the action on the board of snowflake as well. Um, great start. Thanks for coming on the cube. >>Always a pleasure. >>Okay. Live from San Francisco to cube. I'm John for your host. Stay with us more coverage from San Francisco, California after the short break. >>Hello. Welcome back to the cubes coverage here live in San Francisco, California. I'm John furrier, host of the cubes cube coverage of AWS summit 2022 here in San Francisco. We're all the developers of the bay area at Silicon valley. And of course, AWS summit in New York city is coming up in the summer. We'll be there as well. SF and NYC cube coverage. Look for us. Of course, reinforcing Boston and re Mars with the whole robotics AI thing, all coming together. Lots of coverage stay with us today. We've got a great guest from Deibel VC. John Skoda, founding partner, entrepreneurial venture is a venture firm. Your next act, welcome to the cube. Good to see you. >>Good to see you, Matt. I feel like it's been forever since we've been able to do something in person. Well, >>I'm glad you're here because we run into each other all the time. We've known each other for over a decade. Um, >><affirmative>, it's been at least 10 years now, >>At least 10 years more. And we don't wanna actually go back as frees back, uh, the old school web 1.0 days. But anyway, we're in web three now. So we'll get to that in >>Second. We, we are, it's a little bit of a throwback to the path though, in my opinion, >><laugh>, it's all the same. It's all distributed computing and software. We ran each other in cube con you're investing in a lot of tech startup founders. Okay. This next level, next gen entrepreneurs have a new makeup and it's software. It's hardcore tech in some cases, not hardcore tech, but using software is take old something old and make it better, new, faster. <laugh>. So tell us about Deibel what's the firm. I know you're the founder, uh, which is cool. What's going on. Explain >>What you're doing. I mean, you remember I'm a recovering entrepreneur, right? So of course I, I, I, >>No, you're never recovering. You're always entrepreneur >>Always, but we are also always recovering. So I, um, started my first company when I was 24. If you remember, before there was Facebook and friends, there was instant messaging. People were using that product at work every day, they were creating a security vulnerability between their network and the outside world. So I plugged that hole and built an instant messaging firewall. It was my first company. The company was called, I am logic and we were required by Symantec. Uh, then spent 12 years investing in the next generation of our companies, uh, early investor in open source companies and cloud companies and spent a really wonderful 12 years, uh, at a firm called NEA. So I, I feel like my whole life I've been either starting enterprise software companies or helping founders start enterprise software companies. And I'll tell you, there's never been a better time than right now to start enter price software company. >>So, uh, the passion for starting a new firm was really a recognition that founders today that are starting in an enterprise software company, they, they tend to be, as you said, a more technical founder, right? Usually it's a software engineer or a builder mm-hmm <affirmative>, uh, they are building products that are serving a slightly different market than what we've traditionally seen in enterprise software. Right? I think traditionally we've seen it buyers or CIOs that have agendas and strategies, which, you know, purchased software that has traditionally bought and sold tops down. But, you know, today I think the most successful enterprise software companies are the ones that are built more bottoms up and have more technical early opts. And generally speaking, they're free to use. They're free to try. They're very commonly community source or open source companies where you have a large technical community that's supporting them. So there's a, there's kind of a new normal now I think in great enterprise software. And it starts with great technical founders with great products and great and emotions. And I think there's no better place to, uh, service those people than in the cloud and uh, in, in your community. >>Well, first of all, congratulations, and by the way, you got a great pedigree and great background, super smart admire of your work and your, and, and your founding, but let's face it. Enterprise is hot because digital transformation is all companies. The is no, I mean, consumer is enterprise. Now everything is what was once a niche. No, I won't say niche category, but you know, not for the faint of heart, you know, investors, >>You know, it's so funny that you say that enterprise is hot because you, and I feel that way now. But remember, like right now, there's also a giant tech in VC conference in Miami <laugh> it's covering cryptocurrencies and FCS and web three. So I think beauty is definitely in the eye of the beholder <laugh> but no, I, I will tell you, >>Ts is one big enterprise, cuz you gotta have imutability you got performance issues. You have, I IOPS issues. Well, and, >>And I think all of us here that are, uh, maybe students of history and have been involved in, open in the cloud would say that we're, you know, much of what we're doing is, uh, the predecessors of the web web three movement. And many of us I think are contributors to the web three movement. >>The hype is definitely that three. >>Yeah. But, but >>You know, for >>Sure. Yeah, no, but now you're taking us further east to Miami. So, uh, you know, look, I think, I, I think, um, what is unquestioned with the case now? And maybe it's, it's more obvious the more time you spend in this world is this is the fastest growing part of enterprise software. And if you include cloud infrastructure and cloud infrastructure spend, you know, it is by many men over, uh, 500 billion in growing, you know, 20 to 30% a year. So it it's a, it's a just incredibly fast, >>Let's getting, let's get into some of the cultural and the, the shifts that are happening, cuz again, you, you have the luxury of being in enterprise when it was hard, it's getting easier and more cooler. I get it and more relevant, but it's also the hype of like the web three, for instance. But you know, uh, um, um, the CEO snowflake, okay. Has wrote a book and Dave Valenti and I were talking about it and uh, Frank Luman has says, there's no playbooks. We always ask the CEOs, what's your playbook. And he's like, there's no playbook, situational awareness, always Trump's playbooks. So in the enterprise playbook, oh, higher direct sales force and SAS kind of crushed the, at now SAS is being redefined, right. So what is SAS? Is snowflake a SAS or is that a platform? So again, new unit economics are emerging, whole new situation, you got web three. So to me there's a cultural shift, the young entrepreneurs, the, uh, user experience, they look at Facebook and say, ah, you know, they own all my data. You know, we know that that cliche, um, they, you know, the product. So as this next gen, the gen Z and the millennials come in and our customers and the founders, they're looking at things a little bit differently and the tech better. >>Yeah. I mean, I mean, I think we can, we can see a lot of commonalities across all successful startups and the overall adoption of technology. Uh, and, and I would tell you, this is all one big giant revolution. I call it the user driven revolution. Right. It's the rise of the user. Yeah. And you might say product like growth is currently the hottest trend in enterprise software. It's actually user like growth, right. They're one in the same. So sometimes people think the product, uh, is what is driving. You >>Just pull the >>Product through. Exactly, exactly. And so that's that I, that I think is really this revolution that you see, and, and it does extend into things like cryptocurrencies and web three and, you know, sort of like the control that is taken back by the user. Um, but you know, many would say that, that the origins of this movement maybe started with open source where users were, are contributors, you know, contributors, we're users and looking back decades and seeing how it, how it fast forward to today. I think that's really the trend that we're all writing and it's enabling these end users. And these end users in our world are developers, data engineers, cybersecurity practitioners, right. They're really the users. And they're really the, the beneficiaries and the most, you know, kind of valued people in >>This. I wanna come back to the data engineers in a second, but I wanna make a comment and get your reaction to, I have a, I'm a GenXer technically, so for not a boomer, but I have some boomer friends who are a little bit older than me who have, you know, experienced the sixties. And I've, I've been staying on the cube for probably about eight years now that we are gonna hit a digital hippie revolution, meaning a rebellion against in the sixties was rebellion against the fifties and the man and, you know, summer of love. That was a cultural differentiation from the other one other group, the predecessors. So we're kind of having that digital moment now where it's like, Hey boomers, Hey people, we're not gonna do that anymore. We hate how you organize shit. >>Right. But isn't this just technology. I mean, isn't it, isn't it like there used to be the old adage, like, you know, you would never get fired for buying IBM, but now it's like, you obviously probably would get fired if you bought IBM. And I mean, it's just like the, the, I think, I think >>It's the main for days, those renegades were breaking into Stanford, starting the home brew club. So what I'm trying to get at is that, do you see the young cultural revolution also, culturally, just, this is my identity NFTs to me speak volumes about my, I wanna associate with NFTs, not single sign on. Well, >>Absolutely. And, and I think like, I think you're hitting on something, which is like this convergence of, of, you know, societal trends with technology trends and how that manifests in our world is yes. I think like there is unquestionably almost a religion around the way in which a product is built. Right. And we can use open source, one example of that religion. Some people will say, look, I'll just never try a product in the cloud if it's not open source. Yeah. I think cloud, native's another example of that, right? It's either it's, you know, it either is cloud native or it's not. And I think a lot of people will look at a product and say, look, you know, you were not designed in the cloud era. Therefore I just won't try you. And sometimes, um, like it or not, it's a religious decision, right? It's, it's something that people just believe to be true almost without, uh, necessarily. I mean >>The decision making, let me ask you this next question. As a VC. Now you look at pitch, well, you've made a VC for many years, but you also have the founder, uh, entrepreneurial mindset, but you can get empathize with the founders. You know, hustle is a big part of the, that first founder check, right? You gotta convince someone to part with their ch their money and the first money in which you do a lot of is about believing in the person. So fing, so you make, it is hard. Now you, the data's there, you either have it cloud native, you either have the adaption or traction. So honesty is a big part of that pitch. You can't fake it. Oh, >>AB absolutely. You know, there used to be this concept of like the persona of an entrepreneur, right. And the persona of the entrepreneur would be, you know, somebody who was a great salesperson or somebody who tell a great story. You, I still think that that's important, right? It still is a human need for people to believe in narratives and stories. But having said that you're right, the proof is in the pudding, right? At some point you click download and you try the product and it does what it says it it's gonna do, or it doesn't, or it either stands up to the load test or it doesn't. And so I, I feel like in this new economy that we live in, it's a shift from maybe the storytellers and the creators to, to the builders, right. The people that know how to build great product. And in some ways the people that can build great product yeah. Stand out from the crowd. And they're the ones that can build communities around their products. And, you know, in some ways can, um, you know, kind of own more of the narrative because their products exactly >>The volume back to the user led growth. >>Exactly. And it's the religion of, I just love your product. Right. And I, I, I, um, Doug song was the founder of du security used to say, Hey, like, you know, the, the really like in today's world of like consumption based software, the user is only gonna give you 90 seconds to figure out whether or not you're a company that's easy to do business with. Right. And so you can say, and do all the things that you want about how easy you are to work with. But if the product isn't easy to install, if it's not easy to try, if it's not, if, if the, you know, it's gotta speak to >>The, speak to the user, but let me ask a question now that the people watching who are maybe entrepreneurial entrepreneur, um, masterclass here is in session. So I have to ask you, do you prefer, um, an entrepreneur to come in and say, look at John. Here's where I'm at. Okay. First of all, storytelling's fine. Whether you're an extrovert or introvert, have your style, sell the story in a way that's authentic, but do you, what do you prefer to say? Here's where I'm at? Look, I have an idea. Here's my traction. I think here's my MVP prototype. I need help. Or do you wanna just see more stats? What's the, what's the preferred way that you like to see entrepreneurs come in and engage, engage? >>There's tons of different styles, man. I think the single most important thing that every founder should know is that we, we don't invest in what things are today. We invest in what we think something will become. Right. And I think that's why we all get up in the morning and try to build something different, right? It's that we see the world a different way. We want it to be a different way, and we wanna work every single moment of the day to try to make that vision a reality. So I think the more that you can show people where you want to be, the more likely somebody is gonna align with your vision and, and want to invest in you and wanna be along for the ride. So I, I wholeheartedly believe in showing off what you got today, because eventually we all get down to like, where are we and what are we gonna do together? But, um, no, I >>Show >>The path. I think the single most important thing for any founder and VC relationship is that they have the same vision, uh, have the same vision. You can, you can get through bumps in the road, you can get through short term spills. You can all sorts of things in the middle of the journey can happen. Yeah. But it doesn't matter as much if you share the same long term vision, >>Don't flake out and, and be fashionable with the latest trends because it's over before you can get there. >>Exactly. I think many people that, that do what we do for a living will say, you know, ultimately the future is relatively easy to predict, but it's the timing that's impossible to predict. So you, you know, you sort of have to balance the, you know, we, we know that the world is going this way and therefore we're gonna invest a lot of money to try to make this a reality. Uh, but sometimes it happens in six months. Sometimes it takes six years is sometimes like 16 years. >>Uh, what's the hottest thing in enterprise that you see the biggest wave that people should pay attention to that you're looking at right now with Desel partners, Tebel dot your site. What's the big wave. What's your big >>Wave. There, there's three big trends that we invest in. And they're the, they're the only things we do day in, day out. One is the explosion and open source software. So I think many people think that all software is unquestionably moving to an open source model in some form or another yeah. Tons of reasons to debate whether or not that is gonna happen and on what timeline happening >>Forever. >>But it is, it is accelerating faster than we've ever seen. So I, I think it's, it's one big, massive wave that we continue to ride. Um, second is the rise of data engineering. Uh, I think data engineering is in and of itself now, a category of software. It's not just that we store data. It's now we move data and we develop applications on data. And, uh, I think data is in and of itself as big of a, a market as any of the other markets that we invest in. Uh, and finally, it's the gift that keeps on giving. I've spent my entire career in it. We still feel that security is a market that is under invested. It is, it continues to be the place where people need to continue to invest and spend more money. Yeah. Uh, and those are the three major trends that we run >>And security, you think we all need a dessert do over, right? I mean, do we need a do over in security or is what's the core problem? I, >>I, I keep using this word underinvested because I think it's the right way to think about the problem. I think if you, I think people generally speaking, look at cyber security as an add-on. Yeah. But if you think about it, the whole economy is moving online. And so in, in some ways like security is core to protecting the digital economy. And so it's, it shouldn't be an afterthought, right? It should be core to what everyone is doing. And that's why I think relative to the trillions of dollars that are at stake, uh, I believe the market size for cybersecurity is around 150 billion. And it still is a fraction of what we're, what >>We're and security even boom is booming now. So you get the convergence of national security, geopolitics, internet digital >>That's right. You mean arguably, right? I mean, arguably again, it's the area of the world that people should be spending more time and more money given what to stake. >>I love your thesis. I gotta, I gotta say, you gotta love your firm. Love. You're doing we're big supporters of your mission. Congratulations on your entrepreneurial venture. And, uh, we'll be, we'll be talking and maybe see a Cub gone. Uh, >>Absolutely. >>Certainly EU maybe even north America's in Detroit this year. >>Huge fan of what you guys are doing here. Thank you so much for having me on >>The show. Guess bell VC Johnson here on the cube. Check him out. Founder for founders here on the cube, more coverage from San Francisco, California. After the short break, stay with us. Everyone. Welcome to the queue here. Live in San Francisco, California for AWS summit, 2022 we're live we're back with the events. Also we're virtual. We got hybrid all kinds of events. This year, of course, 80% summit in New York city is happening this summer. We'll be there with the cube as well. I'm John. Again, John host of the cube got a great guest here. Justin Coby owner and CEO of innovative solutions. Their booth is right behind us. Justin, welcome to the cube. >>Thank you. Thank you for having me. >>So we're just chatting, uh, uh, off camera about some of the work you're doing. You're the owner of and CEO. Yeah. Of innovative. Yeah. So tell us a story. What do you guys do? What's the elevator pitch. >>Yeah. <laugh> so the elevator pitch is we are, uh, a hundred percent focused on small to midsize businesses that are moving into the cloud or have already moved to the cloud and really trying to understand how to best control, cost, security, compliance, all the good stuff, uh, that comes along with it. Um, exclusively focused on AWS and, um, you know, about 110 people, uh, based in Rochester, New York, that's where our headquarters is, but now we have offices down in Austin, Texas up in Toronto, uh, key Canada, as well as Chicago. Um, and obviously in New York, uh, you know, the, the business was never like this, uh, five years ago, um, founded in 1989, made the decision in 2018 to pivot and go all in on the cloud. And, uh, I've been a part of the company for about 18 years, bought the company about five years ago and it's been a great ride. It >>It's interesting. The manages services are interesting with cloud cause a lot of the heavy liftings done by AWS. So we had Matt on your team on earlier talking about some of the edge stuff. Yeah. But you guys are a managed cloud service. You got cloud advisory, you know, the classic service that's needed, but the demands coming from cloud migrations and application modernization and obviously data is a huge part of it. Huge. How is this factoring into what you guys do and your growth cuz you guys are the number one partner on the SMB side for edge. Yeah. For AWS, you got results coming in. Where's the, where's the forcing function. What's the pressure point. What's the demand like? >>Yeah. It's a great question. Every CEO I talk to, that's a small to midsize business. They're trying to understand how to leverage technology. It better to help either drive a revenue target for their own business, uh, help with customer service as so much has gone remote now. And we're all having problems or troubles or issues trying to hire talent. And um, you know, tech ISNT really at the, at the forefront and the center of that. So most customers are coming to us and they're like, listen, we gotta move to the cloud or we move some things to cloud and we want to do that better. And um, there's this big misnomer that when you move to the cloud, you gotta automatically modernize. Yeah. And what we try to help as many customers understand as possible is lifting and shifting, moving the stuff that you maybe currently have OnPrem and a data center to the cloud first is a first step. And then, uh, progressively working through a modernization strateg, always the better approach. And so we spend a lot of time with small to midsize businesses who don't have the technology talent on staff to be able to do >>That. Yeah. They want get set up. But then the dynamic of like latency is huge. We're seeing that edge product is a big part of it. This is not a one-off happening around everywhere. It is. And it's not, it's manufacturing, it's the physical plant or location >>Literally. >>And so, and you're seeing more IOT devices. What's that like right now from a challenge and problem statement standpoint, are the customers, not staff, is the it staff kind of old school? Is it new skills? What's the core problem you guys solve >>In the SMB space? The core issue nine outta 10 times is people get enamored with the latest and greatest. And the reality is not everything that's cloud based. Not all cloud services are the latest and greatest. Some things have been around for quite some time and are hardened solutions. And so, um, what we try to do with technology staff that has traditional on-prem, uh, let's just say skill sets and they're trying to move to a cloud-based workload is we try to help those customers through education and through some practical, let's just call it use case. Um, whether that's a proof of concept that we're doing or whether we're gonna migrate a small workload over, we try to give them the confidence to be able to not, not necessarily go it alone, but to, to, to have the, uh, the Gusto and to really have the, um, the, the opportunity to, to do that in a wise way. Um, and what I find is that most CEOs that I talk to, yeah, they're like, listen, the end of the day, I'm gonna be spending money in one place or another, whether that's OnPrem or in the cloud. I just want to know that I'm doing that in a way that helps me grow as quickly as possible status quo. I think every, every business owner knows that COVID taught us anything that status quo is, uh, is, is no. No. >>Good. How about factoring in the, the agility and speed equation? Does that come up a lot? It >>Does. I think, um, I, there's also this idea that if, uh, if we do a deep dive analysis and we really take a surgical approach to things, um, we're gonna be better off. And the reality is the faster you move with anything cloud based, the better you are. And so there's this assumption that we gotta get it right the first time. Yeah. In the cloud, if you start down your journey in one way and you realize midway that it's not the right, let's just say the right place to go. It's not like buying a piece of iron that you put in the closet and now you own it in the cloud. You can turn those services on and off. It's gives you a much higher density for making decisions and failing >>Forward. Well actually shutting down the abandoning the projects that early and not worrying about it, you got it. I mean, most people don't abandon cause like, oh, I own it. >>Exactly. And >>They get, they get used to it. Like, and then they wait too long. >>That's exactly. Yeah. >>Frog and boiling water as we used to say. So, oh, it's a great analogy. So I mean, this is a dynamic that's interesting. I wanna get more thoughts on it because like I'm a, if I'm a CEO of a company, like, okay, I gotta make my number. Yeah. I gotta keep my people motivated. Yeah. And I gotta move faster. So this is where you, I get the whole thing. And by the way, great service, um, professional services in the cloud right now are so hot because so hot, you can build it and then have option optionality. You got path decisions, you got new services to take advantage of. It's almost too much for customers. It is. I mean, everyone I talked to at reinvent, that's a customer. Well, how many announcements did am jazzy announce or Adam, you know, the 5,000 announcement or whatever. They do huge amounts. Right. Keeping track of it all. Oh, is huge. So what's the, what's the, um, the mission of, of your company. How does, how do you talk to that alignment? Yeah. Not just processes. I can get that like values as companies, cuz they're betting on you and your people. >>They are, they are, >>What's the values. >>Our mission is, is very simple. We want to help every small to midsize business leverage the power of the cloud. Here's the reality. We believe wholeheartedly. This is our vision that every company is going to become a technology company. So we go to market with this idea that every customer's trying to leverage the power of the cloud in some way, shape or form, whether they know it or don't know it. And number two, they're gonna become a tech company in the process of that because everything is so tech-centric. And so when you talk about speed and agility, when you talk about the, the endless options and the endless permutations of solutions that a customer can buy in the cloud, how are you gonna ask a team of one or two people in your, or it department to make all those decisions going it alone or trying to learn it as you go, it only gets you so far working with a partner. >>I'll just give you some perspective. We work with about a thousand small to midsize business customers. More than 50% of those customers are on our managed services. Meaning they know that we have their back Andre or the safety net. So when a customer is saying, all right, I'm gonna spend a couple thousand dollars a month in the cloud. They know that that bill, isn't gonna jump to $10,000 a month going in alone. Who's there to help protect that. Number two, if you have a security posture and let's just say you're high profile and you're gonna potentially be more vulnerable to security attack. If you have a partner, that's all offering you some managed services. Now you, again, you've got that backstop and you've got those services and tooling. We, we offer, um, seven different products, uh, that are part of our managed services that give the customer the tooling, that for them to go out and buy on their own for a customer to go out today and go buy a new Relic solution on their own. It, it would cost 'em a fortune. If >>Training alone would be insane, a factor and the cost. Yes, absolutely. Opportunity cost is huge, >>Huge, absolutely enormous training and development. Something. I think that is often, you know, it's often overlooked technologists. Typically they want to get their skills up. Yeah. They, they love to get the, the stickers and the badges and the pins, um, at innovative in 2018, when, uh, when we made the decision to go all in on the club, I said to the organization, you know, we have this idea that we're gonna pivot and be aligned with AWS in such a way that it's gonna really require us all to get certified. My executive assistant at the time looks at me. She said, even me, I said, yeah, even you, why can't you get certified? Yeah. And so we made, uh, a conscious decision. It wasn't requirement and still isn't today to make sure everybody in the company has the opportunity to become certified. Even the people that are answering the phones at the front desk >>And she could be running the Kubernetes clusters. I love it. It's amazing. >>But I'll tell you what, when that customer calls and they have a real Kubernetes issue, she'll be able to assist and get >>The right people involved. And that's a cultural factor that you guys have. So, so again, this is back to my whole point about SMBs and businesses in general, small en large, it staffs are turning over the gen Z and millennials are in the workforce. They were provisioning top of rack switches. Right. First of all. And so if you're a business, there's also the, I call the build out, um, uh, return factor, ROI piece. At what point in time as an owner or SMB, do I get the ROI? Yeah. I gotta hire a person to manage it. That person's gonna have five zillion job offers. Yep. Uh, maybe who knows? Right. I got cybersecurity issues. Where am I gonna find a cyber person? Yeah. A data compliance. I need a data scientist and a compliance person. Right. Maybe one and the same. Right. Good luck. Trying to find a data scientist. Who's also a compliance person. Yep. And the list goes on. I can just continue. Absolutely. I need an SRE to manage the, the, uh, the sock report and we can pen test. Right. >>Right. >>These are, these are >>Critical issues. This >>Is just like, these are the table stakes. >>Yeah. And, and every, every business owner's thinking about. So that's, >>That's what, at least a million in bloating, if not three or more Just to get that going. Yeah. Then it's like, where's the app. Yeah. So there's no cloud migration. There's no modernization on the app side though. Yeah. No. And nevermind AI and ML. That's >>Right. That's right. So to try to go it alone, to me, it's hard. It it's incredibly difficult. And, and the other thing is, is there's not a lot of partners, so the partner, >>No one's raising their hand boss. I'll >>Do all that >>Exactly. In it department. >>Exactly. >>Like, can we just call up, uh, you know, <laugh> our old vendor. That's >>Right. <laugh> right. Our old vendor. I like it, but that's so true. I mean, when I think about how, if I was a business owner, starting a business to today and I had to build my team, um, and the amount of investment that it would take to get those people skilled up and then the risk factor of those people now having the skills and being so much more in demand and being recruited away, that's a real, that's a real issue. And so how you build your culture around that is, is very important. And it's something that we talk about every, with every one of our small to midsize business. >>So just, I want to get, I want to get your story as CEO. Okay. Take us through your journey. You said you bought the company and your progression to, to being the owner and CEO of innovative award winning guys doing great. Uh, great bet on a good call. Yeah. Things are good. Tell your story. What's your journey? >>It's real simple. I was, uh, was a sophomore at the Rochester Institute of technology in 2003. And, uh, I knew that I, I was going to school for it and I, I knew I wanted to be in tech. I didn't know what I wanted to do, but I knew I didn't wanna code or configure routers and switches. So I had this great opportunity with the local it company that was doing managed services. We didn't call it at that time innovative solutions to come in and, uh, jump on the phone and dial for dollars. I was gonna cold call and introduce other, uh, small to midsize businesses locally in Rochester, New York go to Western New York, um, who innovative was now. We were 19 people at the time. And I came in, I did an internship for six months and I loved it. I learned more in those six months that I probably did in my first couple of years at, uh, at R I T long story short. >>Um, for about seven years, I worked, uh, to really help develop, uh, sales process and methodology for the business so that we could grow and scale. And we grew to about 30 people. And, um, I went to the owners at the time in 2010 and I was like, Hey, I'm growing the value of this business. And who knows where you guys are gonna be another five years? What do you think about making me an owner? And they were like, listen, you got long ways before you're gonna be an owner, but if you stick it out in your patient, we'll, um, we'll work through a succession plan with you. And I said, okay, there were four other individuals at the time that we're gonna also buy the business with >>Me. And they were the owners, no outside capital, >>None zero, well, 2014 comes around. And, uh, the other folks that were gonna buy into the business with me that were also working at innovative for different reasons. They all decided that it wasn't for them. One started a family. The other didn't wanna put capital in. Didn't wanna write a check. Um, the other had a real big problem with having to write a check. If we couldn't make payroll, I'm like, well, that's kind of like if we're owners, we're gonna have to like cover that stuff. <laugh> so >>It's called the pucker factor. >>Exactly. So, uh, I sat down with the CEO in early 2015, and, uh, we made the decision that I was gonna buy the three partners out, um, go through an earn out process, uh, coupled with, uh, an interesting financial strategy that wouldn't strap the business, cuz they care very much. The company still had the opportunity to keep going. So in 2016 I bought the business, um, became the sole owner. And, and at that point we, um, we really focused hard on what do we want this company to be? We had built this company to this point. Yeah. And, uh, and by 2018 we knew that pivoting all going all in on the cloud was important for us and we haven't looked back. >>And at that time, the proof points were coming clearer and clearer 2012 through 15 was the early adopters, the builders, the startups and early enterprises. Yes. The capital ones of the world. Exactly the, uh, and those kinds of big enterprises. The game don't, won't say gamblers, but ones that were very savvy. The innovators, the FinTech folks. Yep. The hardcore glass eating enterprises >>Agreed, agreed to find a small to midsize business, to migrate completely to the cloud as, as infrastructure was considered. That just didn't happen as often. Um, what we were seeing were a lot of our small to midsize business customers, they wanted to leverage cloud based backup, or they wanted to leverage a cloud for disaster recovery because it lent itself. Well, early days, our most common cloud customer though, was the customer that wanted to move messaging and collaboration. The, the Microsoft suite to the cloud and a lot of 'em dipped their toe in the water. But by 2017 we knew infrastructure was around the corner. Yeah. And so, uh, we only had two customers on eight at the time. Um, and we, uh, we, we made the decision to go all in >>Justin. Great to have you on the cube. Thank you. Let's wrap up. Uh, tell me the hottest product that you have. Is it migrations? Is the app modernization? Is it data? What's the hot product and then put a plug in for the company. Awesome. >>So, uh, there's no question. Every customer is looking to migrate workloads and try to figure out how to modernize for the future. We have very interesting, sophisticated yet elegant funding solutions to help customers with the cash flow, uh, constraints that come along with those migrations. So any SMB that's thinking about migrating to the cloud, they should be talking innovative solutions. We know how to do it in a way that allows those customers not to be cash strapped and gives them an opportunity to move forward in a controlled, contained way so that they can modernize. >>So like insurance, basically for them not insurance class in the classic sense, but you help them out on the, on the cash exposure. >>Absolutely. We are known for that and we're known for being creative with those customers, empathetic to where they are in their journey. And >>That's the cloud upside is all about doubling down on the variable wind. That's right. Seeing the value and doubling down on it. Absolutely not praying for it. Yeah. <laugh> all right, Justin. Thanks for coming on. You really appreciate it. Thank >>You very much for having >>Me. Okay. This is the cube coverage here live in San Francisco, California for AWS summit, 2022. I'm John for your host. Thanks for watching with back with more great coverage for two days after this short break >>Live on the floor in San Francisco for 80 west summit, I'm John ferry, host of the cube here for the next two days, getting all the action we're back in person. We're at AWS reinvent a few months ago. Now we're back events are coming back and we're happy to be here with the cube, bringing all the action. Also virtual, we have a hybrid cube, check out the cube.net, Silicon angle.com for all the coverage. After the event. We've got a great guest ticketing off here. Matthew Park, director of solutions, architecture with innovation solutions. The booth is right here. Matthew, welcome to the cube. >>Thank you very much. I'm glad >>To be here. So we're back in person. You're from Tennessee. We were chatting before you came on camera. Um, it's great to have to be back through events. >>It's amazing. This is the first, uh, summit I've been to and what two, three years. >>It's awesome. We'll be at the, uh, New York as well. A lot of developers and a big story this year is as developers look at cloud going distributed computing, you got on premises, you got public cloud, you got the edge. Essentially the cloud operations is running everything dev sec ops, everyone kind of sees that you got containers, you got Kubernetes, you got cloud native. So the, the game is pretty much laid out. Mm. And the edge is with the actions you guys are number one, premier partner at SMB for edge. >>That's right. >>Tell us about what you guys doing at innovative and, uh, what you do. >>That's right. Uh, so I'm the director of solutions architecture. Uh, me and my team are responsible for building out the solutions that are around, especially the edge public cloud out for us edge is anything outside of an AWS availability zone. Uh, we are deploying that in countries that don't have AWS infrastructure in region. They don't have it. Uh, give >>An example, >>Uh, example would be Panama. We have a customer there that, uh, needs to deploy some financial tech data and compute is legally required to be in Panama, but they love AWS and they want to deploy AWS services in region. Uh, so they've taken E EKS anywhere. We've put storage gateway and, uh, snowball, uh, in region inside the country and they're running their FinTech on top of AWS services inside Panama. >>You know, what's interesting, Matthew is that we've been covering Aw since 2013 with the cube about their events. And we watched the progression and jazzy was, uh, was in charge and then became the CEO. Now Adam Slosky is in charge, but the edge has always been that thing they've been trying to, I don't wanna say, trying to avoid, of course, Amazon would listen to customers. They work backwards from the customers. We all know that. Uh, but the real issue was they were they're bread and butters EC two and S three. And then now they got tons of services and the cloud is obviously successful and seeing that, but the edge brings up a whole nother level. >>It does >>Computing. It >>Does. >>That's not central lies in the public cloud. Now they got regions. So what is the issue with the edge what's driving? The behavior. Outpost came out as a reaction to competitive threats and also customer momentum around OT, uh, operational technologies. And it merging. We see with the data at the edge, you got five GM having. So it's pretty obvious, but there was a slow transition. What was the driver for the <affirmative> what's the driver now for edge action for AWS >>Data is the driver for the edge. Data has gravity, right? And it's pulling compute back to where the customer's generating that data and that's happening over and over again. You said it best outpost was a reaction to a competitive situation. Whereas today we have over fit 15 AWS edge services, and those are all reactions to things that customers need inside their data centers on location or in the field like with media companies. >>Outpost is interesting. We always used to riff on the cube, uh, cuz it's basically Amazon in a box, pushed in the data center, uh, running native, all the stuff, but now cloud native operations are kind of become standard. You're starting to see some standard Deepak sings group is doing some amazing work with open source Rauls team on the AI side, obviously, uh, you got SW who's giving the keynote tomorrow. You got the big AI machine learning big part of that edge. Now you can say, okay, outpost, is it relevant today? In other words, did outpost do its job? Cause EKS anywhere seems to be getting a lot of momentum. You see low the zones, the regions are kicking ass for Amazon. This edge piece is evolving. What's your take on EKS anywhere versus say outpost? >>Yeah, I think outpost did its job. It made customers that were looking at outpost really consider, do I wanna invest in this hardware? Do I, do I wanna have, um, this outpost in my data center, do I wanna manage this over the long term? A lot of those customers just transitioned to the public cloud. They went into AWS proper. Some of those customers stayed on prem because they did have use cases that were, uh, not a good fit for outpost. They weren't a good fit. Uh, in the customer's mind for the public AWS cloud inside an availability zone. Now what's happening is as AWS is pushing these services out and saying, we're gonna meet you where you are with 5g. We're gonna meet you where you are with wavelength. We're gonna meet you where you are with EKS anywhere. Uh, I think it has really reduced the amount of times that we have conversations about outposts and it's really increased. We can deploy fast. We don't have to spin up outpost hardware. We can go deploy EKS anywhere in your VMware environment and it's increasing the speed of adoption >>For sure. So you guys are making a lot of good business decisions around managed cloud service. Innovative does that. You have the cloud advisory, the classic professional services for the specific edge piece and, and doing that outside of the availability zones and regions for AWS, um, customers in, in these new areas that you're helping out are they want cloud, like they want to have modernization a modern applications. Obviously they got data machine learning and AI, all part of that. What's the main product or, or, or gap that you're filling for AWS, uh, outside of their available ability zones or their regions that you guys are delivering. What's the key is it. They don't have a footprint. Is it that it's not big enough for them? What's the real gap. What's why, why are you so successful? >>So what customers want when they look towards the cloud is they want to focus on, what's making them money as a business. They wanna focus on their applications. They want focus on their customers. So they look towards AWS cloud and say, AWS, you take the infrastructure. You take, uh, some of the higher layers and we'll focus on our revenue generating business, but there's a gap there between infrastructure and revenue generating business that innovative slides into, uh, we help manage the AWS environment. We help build out these things in local data centers for 32 plus year old company, we have traditional on-premises people that know about deploying hardware that know about deploying VMware to host EKS anywhere. But we also have most of our company totally focused on the AWS cloud. So we're filling that gap in helping deploy these AWS services, manage them over the long term. So our customers can go to just primarily and totally focusing on their revenue generating business. >>So basically you guys are basically building AWS edges, >>Correct? >>For correct companies, correct? Mainly because the, the needs are there, you got data, you got certain products, whether it's, you know, low latency type requirements, right. And then they still work with the regions, right. It's all tied together, right. Is that how it works? Right. >>And, and our customers, even the ones in the edge, they also want us to build out the AWS environment inside the availability zone, because we're always gonna have a failback scenario. If we're gonna deploy FinTech in the Caribbean, we're gonna talk about hurricanes and gonna talk about failing back into the AWS availability zones. So innovative is filling that gap across the board, whether it be inside the AWS cloud or on the AWS edge. >>All right. So I gotta ask you on the, since you're at the edge in these areas, I won't say underserved, but developing areas where now have data, you have applications that are tapping into that, that requirement. It makes total sense. We're seeing across the board. So it's not like it's, it's an outlier it's actually growing. Yeah. There's also the crypto angle. You got the blockchain. Are you seeing any traction at the edge with blockchain? Because a lot of people are looking at the web three in these areas like Panama, you mentioned FinTech in, in the islands. There are a lot of, lot of, lot of web three happening. What's your, what's your view on the web three world right now, relative >>To we, we have some customers actually deploying crypto, especially, um, especially in the Caribbean. I keep bringing the Caribbean up, but it's, it's top of my mind right now we have customers that are deploying crypto. A lot of, uh, countries are choosing crypto underly parts of their central banks. Yeah. Um, so it's, it's up and coming. Uh, I, I have some, you know, personal views that, that crypto is still searching for a use case. Yeah. And, uh, I think it's searching a lot and, and we're there to help customers search for that use case. Uh, but, but crypto, as a, as a tech technology, um, lives really well on the AWS edge. Yeah. Uh, and, and we're having more and more people talk to us about that. Yeah. And ask for assistance in the infrastructure because they're developing new cryptocurrencies every day. Yeah. It's not like they're deploying Ethereum or anything specific. They're actually developing new currencies and, and putting them out there on it's >>Interesting. And I mean, first of all, we've been doing crypto for many, many years. We have our own little, um, you know, projects going on. But if you look talk to all the crypto people that say, look, we do a smart contract, we use the blockchain. It's kind of over a lot of overhead. It's not really their technical already, but it's a cultural shift, but there's underserved use cases around use of money, but they're all using the blockchain, just for this like smart contracts for instance, or certain transactions. And they go into Amazon for the database. Yeah. <laugh> they all don't tell anyone we're using a centralized service, but what happened to decent centralized. >>Yeah. And that's, and that's the conversation performance. >>Yeah. >>And, and it's a cost issue. Yeah. And it's a development issue. Um, so I think more and more as, as some of these, uh, currencies maybe come up, some of the smart contracts get into, uh, they find their use cases. I think we'll start talking about how does that really live on, on AWS and, and what does it look like to build decentralized applications, but with AWS hardware and services. >>Right. So take me through a, a use case of a customer, um, Matthew around the edge. Okay. So I'm a customer, pretend I'm a customer, Hey, you know, I'm, we're in an underserved area. I want to modernize my business. And I got my developers that are totally peaked up on cloud. Um, but we've identified that it's just a lot of overhead latency issues. I need to have a local edge and serve my a and I also want all the benefits of the cloud. So I want the modernization and I wanna migrate to the cloud for all those cloud benefits and the good this of the cloud. What's the answer. Yeah. >>Uh, big thing is, uh, industrial manufacturing, right? That's, that's one of the best use cases, uh, inside industrial manufacturing, we can pull in many of the AWS edge services we can bring in, uh, private 5g, uh, so that all the, uh, equipment inside that, that manufacturing plant can be hooked up. They don't have to pay huge overheads to deploy 5g it's, uh, better than wifi for the industrial space. Um, when we take computing down to that industrial area, uh, because we wanna do pre-procesing on the data. Yeah. We want to gather some analytics. We deploy that with, uh, regular commercially available hardware running VMware, and we deploy EKS anywhere on that. Uh, inside of that manufacturing plant, uh, we can do pre-processing on things coming out of the, uh, the robotics that depending on what we're manufacturing, right. Uh, and then we can take the, those refined analytics and for very low cost with maybe a little bit longer latency transmit those back, um, to the AWS availability zone, the, the standard >>For data lake or whatever, >>To the data lake. Yeah. Data Lakehouse, whatever it might be. Um, and we can do additional data science on that once it gets to the AWS cloud. Uh, but I'll lot of that, uh, just in time business decisions, just in time, manufacturing decisions can all take place on an AWS service or services inside that manufacturing plant. And that's, that's one of the best use cases that we're >>Seeing. And I think, I mean, we've been seeing this on the queue for many, many years, moving data around is very expensive. Yeah. But also compute going of the data that saves that cost yep. On the data transfer also on the benefits of the latency. So I have to ask you, by the way, that's standard best practice now for the folks watching don't move the data unless you have to. Um, but those new things are developing. So I wanna ask you, what new patterns are you seeing emerging once this new architecture's in place? Love that idea, localize everything right at the edge, manufacture, industrial, whatever the use case, retail, whatever it is. Right. But now what does that change in the, in the core cloud? There's a, there's a system element here. Yeah. What's the new pattern. There's >>Actually an organizational element as well, because once you have to start making the decision, do I put this compute at the point of use or do I put this compute in the cloud? Uh, now you start thinking about where business decisions should be taking place. Uh, so not only are you changing your architecture, you're actually changing your organization because you're thinking, you're thinking about a dichotomy you didn't have before. Uh, so now you say, okay, this can take place here. Uh, and maybe, maybe this decision can wait. Yeah. Uh, and then how do I visualize that? By >>The way, it could be a bot tube doing the work for management. Yeah. <laugh> exactly. You got observability going, right. But you gotta change the database architecture in the back. So there's new things developing. You've got more benefit. There >>Are, there are. And, and we have more and more people that, that want to talk less about databases and want to talk more about data lakes because of this. They want to talk more about out. Customers are starting to talk about throwing away data, uh, you know, for the past maybe decade. Yeah. It's been store everything. And one day we will have a data science team that we hire in our organization to do analytics on this decade of data. And well, >>I mean, that's, that's a great point. We don't have time to drill into, maybe we do another session on this, but the one pattern we're seeing of the past year is that throwing away data's bad, even data lakes that so-called turn into data swamps, actually, it's not the case. You look at data, brick, snowflake, and other successes out there. And even time series data, which may seem irrelevant efforts over actually matters when people start retraining their machine learning algorithms. Yep. So as data becomes code, as we call it in our last showcase, we did a whole whole event on this. The data's good in real time and in the lake. Yeah. Because the iteration of the data feeds the machine learning training. Things are getting better with the old data. So it's not throw it away. It's not just business better. Yeah. There's all kinds of new scale. >>There are. And, and we have, uh, many customers that are running pay Toby level. Um, they're, they're essentially data factories on, on, uh, on premises, right? They're, they're creating so much data and they're starting to say, okay, we could analyze this, uh, in the cloud, we could transition it. We could move Aytes of data to the AWS cloud, or we can run, uh, computational workloads on premises. We can really do some analytics on this data transition, uh, those high level and sort of raw analytics back to AWS run 'em through machine learning. Um, and we don't have to transition 10, 12 petabytes of data into AWS. >>So I gotta end the segment on a, on a kind of a, um, fun note. I was told to ask you about your personal background, OnPrem architect, Aus cloud, and skydiving instructor. <laugh> how does that all work together? What tell, what does this mean? Yeah. >>Uh, you >>Jumped out a plane and got a job. You got a customer to jump out >>Kind of. So I was, you jumped out. I was teaching having, uh, before I, before I started in the cloud space, this was 13, 14 years ago. I was a, I still am a sky. I instructor, uh, I was teaching skydiving and I heard out of the corner of my ear, uh, a guy that owned an MSP that was lamenting about, um, you know, storing data and, and how his customers are working. And he can't find an enough people to operate all these workloads. So I walked over and said, Hey, this is, this is what I went to school for. Like, I'd love to, you know, uh, I was living in a tent in the woods, teaching skydiving. I was like, I'd love to not live in a tent in the woods. So, uh, uh, I started and the first day there, uh, we had a, a discussion, uh, EC two had just come out <laugh> and, uh, like, >>This is amazing. >>Yeah. And so we had this discussion, we should start moving customers here. And, uh, and that totally revolutionized that business, um, that, that led to, uh, that that guy actually still owns a skydiving airport. But, um, but through all of that, and through being in on premises, migrated me and myself, my career into the cloud, and now it feels like, uh, almost, almost looking back and saying, now let's take what we learned in the cloud and, and apply those lessons and those services tore >>It's. So it's such a great story, you know, was gonna, you know, you know, the whole, you know, growth mindset pack your own parachute, you know, uh, exactly. You know, the cloud in the early days was pretty much will the shoot open. Yeah. It was pretty much, you had to roll your own cloud at that time. And so, you know, you, you jump on a plane, you gotta make sure that parachute is gonna open. >>And so was Kubernetes by the way, 2015 or so when, uh, when that was coming out, it was, I mean, it was, it was still, and maybe it does still feel like that to some people. Right. But, uh, it was, it was the same kind of feeling that we had in the early days of AWS, the same feeling we have when we >>It's now with you guys, it's more like a tandem jump. Yeah. You know, but, but it's a lot of, lot of this cutting edge stuff, like jumping out of an airplane. Yeah. You got the right equipment. You gotta do the right things. Exactly. >>Right. >>Yeah. Thanks for coming. You really appreciate it. Absolutely great conversation. Thanks for having me. Okay. The cubes here live in San Francisco for eight of us summit. I'm John for host of the cube. Uh, we'll be at a summit in New York coming up in the summer as well. Look up for that. Look up this calendar for all the cube, actually@thecube.net. We'll right back with our next segment after this break. >>Okay. Welcome back everyone to San Francisco live coverage here, we're at the cube a be summit 2022. We're back in person. I'm John fury host of the cube. We'll be at the eighties summit in New York city this summer, check us out then. But right now, two days in San Francisco, getting all the coverage what's going on in the cloud, we got a cube alumni and friend of the cube, my dos car CEO, investor, a Sierra, and also an investor in a bunch of startups, angel investor. Gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see you. Cool. How are you? Good. >>How hello you. >>So congratulations on all your investments. Uh, you've made a lot of great successes, uh, over the past couple years, uh, and your company raising, uh, some good cash as Sarah. So give us the update. How much cash have you guys raised? What's the status of the company product what's going on? >>First of all, thank you for having me. We're back to be business with you, never after to see you. Uh, so is a company started around four years back. I invested with a few of the investors and now I'm the CEO there. We have raised close to a hundred million there. The investors are people like Norwes Menlo ventures, coastal ventures, Ram Shera, and all those people, all well known guys. And Beckel chime Paul me Mayard web. So whole bunch of operating people and, uh, Silicon valley VCs are involved >>And has it gone? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISRA is going after is what I call the applying AI for customer service. It operations, it help desk, uh, the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and service now to take you to the next stage? Well, >>I love having you on the cube, Dave and I, Dave LAN as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a, you're like a guest analyst. <laugh> >>You know, who does >>You, >>You >>Get the call fund to talk to you though. You >>Get the commentary, your, your finger in the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase it. Isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud scale. You predicted that we talked about in the cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing Docker just raised a hundred million on a $2 billion valuation back from the dead after they pivoted from enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control plan? Emerging AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded, observability there's 10 billion observability companies. Data is the key. This is what's your end on this. What's your take. >>Yeah, look, I think I'll give you the few that I see right from my side. Obviously data is very clear. So the things that rumor system of recorded you and me talked about the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud native, it'll be called AI. NA AI enable is a new buzzword and using the AI for customer service. It, you talk about observability. I call it, AIOps applying AOPs for good old it operation management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events insurance. So I see a lot of work clicking for AIOps and AI services. What used to be desk with ServiceNow BMC GLA you see a new ALA emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflows, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with AI workflows. So you, you see AI going >>Off is RPA. A company is AI, is RPA a feature of something bigger? Or can someone have a company on RPA UI S one will be at their event this summer? Um, is it a product company? I mean, or I mean, RPA is, should be embedded in everything. It's a >>Feature. It is very good point. Very, very good thinking. So one is, it's a category for sure. Like, as we thought, it's a category, it's an area where RPA may change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company also, but that automation should be embedded in every area. Yeah. Like we call cloud NATO and AI. They it'll become automation data. Yeah. And that's your, thinking's >>Interesting me. I think about the, what you're talking about what's coming to mind is I'm kinda having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it was middleware. It sat between two things and then the middle, and it was software abstraction. Now you have all kinds of workflows, abstractions everywhere. So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed. Are they integrated? I mean, these are the challenges. This is crazy. What's the, >>So remember the databases became called polyglot databases. Yeah. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area like you, you were talking about, it should be part of service. Now it should be part of ISRA. Like every company, every Salesforce. So that's why you see it MuleSoft and sales buying RPA companies. So you'll see all the SaaS companies, cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also have an automation as a layer embedded inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind, as you got the XPO hall got, um, we're back to vis, but you got, you know, AMD, Clum, Dynatrace data, dog, innovative, all the companies out here that we know, we interview them all. They're trying to be suppliers to this growing enterprise market. Right? Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Deibel later. He's a former NEA guy and we always talk to Jerry, Jen, we know all the, the VCs, what does the startups look like? What does the state of the, in your mind, cause you, I know you invest the entrepreneurial founder situation. Cloud's bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's code. Yes. Basically. Data's everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to, uh, two things that I'm seeing out there. Remember leaders of Amazon created the startups 15 years back. Everybody built on Amazon now, Azure and GCP. The next layer would be people don't just build on Amazon. They're going to build it on top of snow. Flake companies are snowflake becomes a data platform, right? People will build on snowflake, right? So I see my old boss playing ment, try to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer, right? So I think that's the next level of companies trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis a couple months ago called castles in the cloud where your moat is, what you do in the cloud. Not necessarily in the, in the IP. Um, Dave LAN and I had last re invent, coined the term super cloud, right? It's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldman S Sachs is doing. You're starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage. And guys like Charles Fitzgeral out there, who we like was kind of hitting on us saying, Hey, you guys terrible, they didn't get him. Like, yeah, I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. <laugh> cause he's cool. Um, but snowflake is on Amazon. Yes. Now they say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist and, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. >>It is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to build everything on Amazon where possible whatever is, I cannot build. I'll make the pass layer room. The middle layer pass will be snowflake. So I cannot build it on snowflake. I can use them for data layer if I really need to size, I'll build it on force.com Salesforce. Yeah. Right. So I think that's where you'll >>See. So basically the, the, if you're an entrepreneur, the, the north star in terms of the, the outcome is be a super cloud. It >>Is, >>That's the application on another big CapEx ride, the CapEx of AWS or cloud, >>And that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. Yeah. >>Yeah. How are, how is Amazon and the clouds dealing with these big whales, the snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think got Redshift. Amazon has got Redshift. Um, but snowflake big customer. The they're probably paying AWS big, >>I >>Think big bills too. >>So John, very good. Cause it's like how Netflix is and Amazon prime, right. Netflix runs on Amazon, but Amazon has Amazon prime that co-option will be there. So Amazon will have Redshift, but Amazon is also partnering with the snowflake to have native snowflake data warehouse as a data layer. So I think depending on the use case you have to use each of the above, I think snowflake is here for a long term. Yeah. Yeah. So if I'm building an application, I want to use snowflake then writing from stats. >>Well, I think that comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, you know, foreclose your value. That's right. With some sort of internal hack, but I've think, I think the general question that I have is that I think it's okay to have a super cloud like that because the rising tide is still happening at some point, when does the rising tide stop and the people shopping up their knives, it gets more competitive or is it just an infinite growth cycle? I >>Think it's growth. You call it closed skill you the word cloud scale. So I think look, cloud will continually agree, increase. I think there's as long as there more movement from on, uh, on-prem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations, it helpless. Even the customer service service. Now the ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So cloud ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go made. >>I wanna get your thoughts for the folks watching that are, uh, enterprise buyers are practitioners, not suppliers to the market. Feel free to text me or DMing. Next question is really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products. Cause you know, the big enterprises now and you know, small, medium, large, and large enterprise, they're all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between the startup selling to, or growing startup selling to an enterprise? Um, have you seen changes there? I mean seeing some stuff, but why don't we get your thoughts on that? What it >>Is you, if I remember going back to our 2007 or eight, when I used to talk to you back then when Amazon started very small, right? We are an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or one person today. Most companies are already spending 20, 30% with startups. Like if I look at a C I will line our business, it's gone. Yeah. Can it go more? I think it can double in the next four, five years. Yeah. Spending on the startups. Yeah. >>And check out, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want to get your reaction because I, I reference the URL causes like there's like a bunch of companies we've been promoting because the solution that startups have actually are new stuff. Yes. It's bending, it's shifting left for security or using data differently or um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there. Um, and goes back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona, you mentioned AIOps, we've been seeing AIOps IOPS booming and that's creating a new developer paradigm that's right. Which we call coin data as code data as code is like infrastructure as code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this data engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same thing? Do you agree? Um, do you disagree or can you share? >>I, a lot of thoughts that Fu I see the AI op solutions in the futures should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone there yet. Like I spend a lot of time with data dog, Cisco app dynamic, right? Dynatrace, all this solution will go future towards predict to pro so solution with AOPs. But what you bring up a very good point on the data side. I think like we have a Amazon marketplace and Amazon for startup, there should be data exchange where you want to create for AOPs and AI service that customers give the data, share the data because we thought the data algorithms are useless. I can give the best algorithm, but I gotta train them, modify them, make them better, make them better. Yeah. And I think their whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that area is very important. >>You've always been on, um, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to big data days back in 2009, you know that >>Look at, look how much data bricks has grown. >>It is doubled. The key cloud >>Air kinda went private, so good stuff. What are you working on right now? Give a, give a, um, plug for what you're working on. You'll still investing. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. So right. ISRA is my number one baby right now. So I'm looking year that growing customers and my customers, or some of them, you like it's zoom auto desk, McAfee, uh, grand <inaudible>. So all the top customers, um, mainly for it help desk customer service. AIOps those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What's what's their need? What category is it? >>I think they look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on, predict ours. One area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value problem. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service, >>Great stuff, man. Doing great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the cube. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of a us summit 2022. And we're gonna be at Aus summit in San, uh, in New York in the summer. So look for that on the calendar, of course, go to a us startups.com. That's a site for all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break. >>Okay. Welcome back everyone. This the cubes coverage here in San Francisco, California, a Davis summit, 2022, the beginning of the event season, as it comes back, little bit smaller footprint, a lot of hybrid events going on, but this is actually a physical event, a summit in new York's coming in the summer. We'll be two with the cube on the set. We're getting back in the Groove's psych to be back. We were at reinvent, uh, as well, and we'll see more and more cube, but you're gonna see a lot of virtual cube outta hybrid cube. We wanna get all those conversations, try to get more interviews, more flow going. But right now I'm excited to have Corey Quinn here on the back on the cube chief cloud economist with duck bill groove, he's the founder, uh, and chief content person always got great angles, fun comedy, authoritative Corey. Great to see you. Thank you. >>Thanks. Coming on. Sure is a lot of words to describe is shit posting, which is how I describe what I tend to do. Most days, >>Shit posting is an art form now. And if you look at mark, Andrew's been doing a lot of shit posting lately. All a billionaires are shit posting, but they don't know how to do it. They're >>Doing it right. There's something opportunity there. It's like, here's how to be even more obnoxious and incisive. It's honestly the most terrifying scenario for anyone is if I have that kind of budget to throw at my endeavors, it's like, I get excited with a nonsense I can do with a $20 gift card for an AWS credit compared to, oh well, if I could buy a mid-size island to begin doing this from, oh, then we're having fun. >>This shit posting trend. Interesting. I was watching a thread go on about, saw someone didn't get a job because of their shit posting and the employer didn't get it. And then someone on this side I'll hire the guy cuz I get that's highly intelligent shit posting. So for the audience that doesn't know what shit posting is, what, what is shitposting >>It's more or less talking about the world of enterprise technology, which even that sentence is hard to finish without falling asleep and toppling out of my chair in front of everyone on the livestream, but it's doing it in such a way that brings it to life that says the quiet part. A lot of the audience is thinking, but generally doesn't say either because they're polite or not a Jack ass or more prosaically are worried about getting fired for better or worse. I don't have that particular constraint, >>Which is why people love you. So let's talk about what you, what you think is, uh, worthy and not worthy in the industry right now, obviously, uh, Cuban coming up in Spain, which they're having a physical event, you see the growth of cloud native Amazon's evolving Atos, especially new CEO. Andy move on to be the chief of all. Amazon just saw him the cover of was it time magazine. Um, he's under a lot of stress. Amazon's changed. Invoice has changed. What's working. What's not, what's rising, what's falling. What's hot. What's not, >>It's easy to sit here and criticize almost anything. These folks do. They're they're effectively in a fishbowl, but I have trouble. Imagine the logistics, it takes to wind up handling the catering for a relatively downscale event like this one this year, let alone running a 1.7 million employee company having to balance all the competing challenges and pressures and the rest. I, I just can't fathom what it would be like to look at all of AWS. And it's, it's sprawling immense, the nominates our entire industry and say, okay, this is a good start, but I, I wanna focus on something with a broader remit. What is that? How do you even get into that position? And you can't win once you're there. All you can do is hold onto the tiger and hope you don't get mold. >>Well, there's a lot of force for good conversations. Seeing a lot of that going on, Amazon's trying to a, is trying to portray themselves, you know, the Pathfinder, you know, you're the pioneer, um, force for good. And I get that and I think that's a good angle as cloud goes mainstream. There's still the question of, we had a guy on just earlier, who was a skydiving instructor and we were joking about the early days of cloud. Like that was like skydiving, build a parachute open, you know, and now it's same kind of thing. As you move to edge, things are like reliable in some areas, but still new, new fringe, new areas. That's crazy. Well, >>Since the last time we've spoken, uh, Steve Schmidt is now the CISO for all of Amazon and his backfill replacement. The AWS CISO is CJ. Moses who as a hobby races, a as a semi-pro race car, our driver to my understanding, which either, I don't know what direction to take that in either. This is what he does to relax or ultimately, or ultimately it's. Huh? That, that certainly says something about risk assessment. I'm not entirely sure what, but okay. Either way, it sounds like more exciting. Like they >>Better have a replacement ready in case something goes wrong on the track, highly >>Available >>CSOs. I gotta say one of the things I do like in the recent trend is that the tech companies are getting into the formula one, which I was never a fan of until I watched that Netflix series. But when you look at the formula one, it's pretty cool. Cause it's got some tech angles, I get the whole data instrumentation thing, but the most coolest thing about formula, the one is they have these new rigs out. Yeah. Where you can actually race in e-sports with other people in pure simulation of the race car. You gotta get the latest and video graphics card, but it's basically a tricked out PC with amazing monitors and you have all the equipment of F1 and you're basically simulating racing. Oh, >>It's great too. And I can see the appeal of these tech companies getting it into it because these things are basically rocket shifts. When those cars go, like they're sitting there, we can instrument every last part of what is going on inside that vehicle. And then AWS crops up. And we can bill on every one of those dimensions too. And it's like slow down their hasty pudding one step at a time. But I do see the appeal. >>So I gotta ask you about, uh, what's going on in your world. I know you have a lot of great SA we've been following you in the queue for many, many years. Got a great newsletter. Check out Corey Quinn's newsletter, uh, screaming in the cloud program. Uh, you're on the cutting edge and you've got a great balance between really being snarky and, and, and really being delivering content. That's exciting, uh, for people, uh, with a little bit of an edge, um, how's that going? Uh, what's the blowback, any blowback late leads there been tick? What was, what are some of the things you're hearing from your audience, more Corey, more Corey. And then of course the, the PR team's calling you >>The weird thing about having an audience beyond a certain size is far and away as a landslide. The most common response I get is silence where it's hi, I'm emailing an awful lot of people at last week in AWS every week and okay. They not have heard me. It. That is not actually true. People just generally don't respond to email because who responds to email newsletters. That sounds like something, a lunatic might do same story with response to live streams and podcasts. It's like, I'm gonna call into that am radio show and give them a piece of my mind. People generally don't do that. >>We should do that. Actually. I think sure would call in. Oh, I, I >>Think >>I guarantee if we had that right now, people would call in and Corey, what do you think about X? >>Yeah. It not, everyone understands the full context of what I do. And in fact, increasingly few people do and that's fine. I, I keep forgetting that sometimes people do not see what I'm doing in the same light that I do. And that's fine. Blowback has been largely minimal. Honestly, I am surprised anything by how little I have gotten over the last five years of doing this, but it would be easier to dismiss me if I weren't generally. Right. When, okay, so you launch this new service and it seems pretty crappy to me cuz when I try and build something, it falls over and begs for help. And people might not like hearing that, but it's what customers are finding too. Yeah. I really am the voice of the customer. >>You know, I always joke with Dave Avante about how John Fort's always at, uh, um, reinvent getting the interview with jazzy now, Andy we're there, you're there. And so we have these rituals at the events. It's all cool. Um, one of the rituals I like about your, um, your content is you like to get on the naming product names. Um, and, and, and, and, and kind of goof on that. Now why I like is because I used to work at ETT Packard where they used to name things as like engineers, HP 1 0, 0 5, or we can't, we >>Have a new monitor. How are we gonna name it? Throw the wireless keyboard down the stairs again. And then there you go. Yeah. >>It's and the old joke at HP was if they, if they invented sushi, they'd say, yeah, we can't call sushi. It's cold, dead fish, but that's what it is. And so the joke was cold. Dead fish is a better name than sushi. So you know is fun. So what's the, what are the, how's the Amazon doing in there? Have they changed their naming, uh, strategy, uh, on some of their, their product >>They're going in different directions. When they named Aurora, they decided to explore a new theme of Disney princesses as they go down those paths. And some things are more descriptive. Some people are clearly getting bonus on number of words, they can shove into it. Like the better a service is the longer it's name. Like AWS systems manager, a session manager is a great one. I love the service ridiculous name. They have a systems manager, parameter store with is great. They have secrets manager, which does the same thing. It's two words less, but that one costs money in a way that systems manage through parameter store does not. It's fun. >>What's your, what's your favorite combination of acronyms >>Combination of you >>Got Ks. You got EMR, you got EC two. You got S three SQS. Well, RedShift's not an acronym. You got >>Gas is one of my personal favorites because it's either elastic block store or elastic bean stock, depending entirely on the context of the conversation, >>They still got bean stock or is that still >>Around? Oh, they never turn anything off. They're like the anti Google, Google turns things off while they're still building it. Whereas Amazon is like, wow, we built this thing in 2005 and everyone hates it. But while we certainly can't change it, now it has three customers on it, John. >>Okay. >>Simple BV still haunts our >>Dreams. I, I actually got an email on, I saw one of my, uh, servers, all these C twos were being deprecated and I got an email I'm like, I couldn't figure out. Why can you just like roll it over? Why, why are you telling me just like, gimme something else. Right. Okay. So let me talk about, uh, the other things I want to ask you is that like, okay, so as Amazon gets better in some areas where do they need more work? And you, your opinion, because obviously they're all interested in new stuff and they tend to like put it out there for their end to end customers. But then they've got ecosystem partners who actually have the same product. Yes. And, and this has been well documented. So it's, it's not controversial. It's just that Amazon's got a database Snowflake's got out database service. So, you know, Redshift, snowflake database is out there. So you've got this optician. Yes. How's that going? And what are you hearing about the reaction to any of that stuff? >>Depends on who you ask. They love to basically trot out a bunch of their partners who will say nice things about them. And it very much has heirs of, let's be honest, a hostage video, but okay. Cuz these companies do partner with Amazon and they cannot afford to rock the boat too far. I'm not partnered with anyone. I can say what I want. And they're basically restricted to taking away my birthday at worse so I can live with that. >>All right. So I gotta ask about multi-cloud cause obviously the other cloud shows are coming up. Amazon hated that word. Multi-cloud um, a lot of people are saying, you know, it's not a real good marketing word. Like multicloud sounds like, you know, root canal. Mm-hmm <affirmative> right. So is there a better description for multicloud? >>Multiple single >>Loves that term. Yeah. >>You're building in multiple single points of failure. Do it for the right reasons or don't do it as a default. I believe not doing it is probably the, the right answer. However, and if I were, if I were Amazon, I wouldn't want to talk about multi-cloud either as the industry leader, let's talk about other clouds, bad direction to go in from a market cap perspective. It doesn't end well for you, but regardless of what they want to talk about, or don't want to talk about what they say, what they don't say, I tune all of it out. And I look at what customers are doing and multi-cloud exists in a variety of some brilliant, some brain dead. It depends a lot on context. But my general response is when someone gets on stage from a company and tells me to do a thing that directly benefits their company. I am skeptical at best. Yeah. When customers get on stage and say, this is what we're doing because it solves problems. That's when I shut up and listen. >>Yeah. Cool. Awesome. Corey, I gotta ask you a question cause I know you we've been, you know, fellow journey mean in the, in the cloud journey, going to all the events and then the pandemic hit where now in the third year, who knows what it's gonna end, certainly events are gonna look different. They're gonna be either changing footprint with the virtual piece, new group formations community's gonna emerge. You've got a pretty big community growing and it's growing like crazy. What's the weirdest or coolest thing, or just big changes you've seen with the pan endemic, uh, from your perspective, cuz you've been in the you're in the middle of the whitewater rafting. You've seen the events you circle offline. You saw the online piece come in, you're commentating, you're calling balls and strikes in the industry. You got a great team developing over there. Duck bill group. What's the big aha moment that you saw with the pandemic. Weird, funny, serious, real in the industry and with customers what's >>Accessibility. Reinvent is a great example. When in the before times it's open to anyone who wants to attend, who >>Can pony. >>Hello and welcome back to the live cube coverage here in San Francisco, California, the cube live coverage. Two days, day two of a summit, 2022 Aish summit, New York city coming up in summer. We'll be there as well. Events are back. I'm the host, John fur, the Cub got great guest here. Johnny Dallas with Ze. Um, here is on the queue. We're gonna talk about his background. Uh, little trivia here. He was the youngest engineer ever worked at Amazon at the age. 17 had to get escorted into reinvent in Vegas cause he was underage <laugh> with security, all good stories. Now the CEO of company called Z know DevOps kind of focus, managed service, a lot of cool stuff, Johnny, welcome to the cube. >>Thanks John. Great. >>So tell a story. You were the youngest engineer at AWS. >>I was, yes. So I used to work at a company called Bebo. I got started very young. I started working when I was about 14, um, kind of as a software engineer. And when I, uh, it was about 16. I graduated out of high school early, um, working at this company Bebo, still running all of the DevOps at that company. Um, I went to reinvent in about 2018 to give a talk about some of the DevOps software I wrote at that company. Um, but you know, as many of those things were probably familiar with reinvent happens in a casino and I was 16. So was not able to actually go into the, a casino on my own. Um, so I'd have <inaudible> security as well as casino security escort me in to give my talk. >>Did Andy jazzy, was he aware of >>This? Um, you know, that's a great question. I don't know. <laugh> >>I'll ask him great story. So obviously you started a young age. I mean, it's so cool to see you jump right in. I mean, I mean you never grew up with the old school that I used to grew up in and loading package software, loading it onto the server, deploying it, plugging the cables in, I mean you just rocking and rolling with DevOps as you look back now what's the big generational shift because now you got the Z generation coming in, millennials on the workforce. It's changing like no one's putting and software on servers. Yeah, >>No. I mean the tools keep getting better, right? We, we keep creating more abstractions that make it easier and easier. When I, when I started doing DevOps, I could go straight into E two APIs. I had APIs from the get go and you know, my background was, I was a software engineer. I never went through like the CIS admin stack. I, I never had to, like you said, rack servers, myself. I was immediately able to scale. I was managing, I think 2,500 concurrent servers across every Ables region through software. It was a fundamental shift. >>Did you know what an SRE was at that time? >>Uh, >>You were kind of an SRE on >>Yeah, I was basically our first SRE, um, was familiar with the, with the phrasing, but really thought of myself as a software engineer who knows cloud APIs, not a SRE. All >>Right. So let's talk about what's what's going on now as you look at the landscape today, what's the coolest thing that's going on in your mind in cloud? >>Yeah, I think the, I think the coolest thing is, you know, we're seeing the next layer of those abstraction tools exist and that's what we're doing with Z is we've basically gone and we've, we're building an app platform that deploys onto your cloud. So if you're familiar with something like Carku, um, where you just click a GitHub repo, uh, we actually make it that easy. You click a GI hub repo and it will deploy on ALS using a AWS tools. So, >>Right. So this is Z. This is the company. Yes. How old's the company about >>A year and a half old now. >>All right. So explain what it does. >>Yeah. So we make it really easy for any software engineer to deploy on a AWS. It's not SREs. These are the actual application engineers doing the business logic. They don't really want to think about Yamo. They don't really want to configure everything super deeply. They want to say, run this API on S in the best way possible. We've encoded all the best practices into software and we set it up for you. Yeah. >>So I think the problem you're solving is that there's a lot of want be DevOps engineers. And then they realize, oh shit, I don't wanna do this. Yeah. And some people want to do it. They loved under the hood. Right. People love to have infrastructure, but the average developer needs to actually be as agile on scale. So that seems to be the problem you solve. Right? >>Yeah. We, we, we give way more productivity to each individual engineer, you know? >>All right. So let me ask you a question. So let me just say, I'm a developer. Cool. I build this new app. It's a streaming app or whatever. I'm making it up cube here, but let's just say I deploy it. I need your service. But what happens about when my customers say, Hey, what's your SLA? The CDN went down from this it's flaky. Does Amazon have, so how do you handle all that SLA reporting that Amazon provides? Cuz they do a good job with sock reports all through the console. But as you start getting into DevOps <affirmative> and sell your app, mm-hmm <affirmative> you have customer issues. How do you, how do you view that? Yeah, >>Well, I, I think you make a great point of AWS has all this stuff already. AWS has SLAs. AWS has contract. Aw has a lot of the tools that are expected. Um, so we don't have to reinvent the wheel here. What we do is we help people get to those SLAs more easily. So Hey, this is AWS SLA as a default. Um, Hey, we'll fix you your services. This is what you can expect here. Um, but we can really leverage S's reliability of you. Don't have to trust us. You have to trust ALS and trust that the setup is good there. >>Do you handle all the recovery or mitigation between, uh, identification say downtime for instance? Oh, the server's not 99% downtime. Uh, went down for an hour, say something's going on? And is there a service dashboard? How does it get what's the remedy? Do you have a, how does all that work? >>Yeah, so we have some built in remediation. You know, we, we basically say we're gonna do as much as we can to keep your endpoint up 24 7 mm-hmm <affirmative>. If it's something in our control, we'll do it. If it's a disc failure, that's on us. If you push bad code, we won't put out that new version until it's working. Um, so we do a lot to make sure that your endpoint stay is up, um, and then alert you if there's a problem that we can't fix. So cool. Hey S has some downtime, this thing's going on. You need to do this action. Um, we'll let you know. >>All right. So what do you do for fun? >>Yeah, so, uh, for, for fun, um, a lot of side projects. <laugh> uh, >>What's your side hustle right now. You got going on >>The, uh, it's >>A lot of tools playing tools, serverless. >>Yeah, painless. A lot of serverless stuff. Um, I think there's a lot of really cool WAM stuff as well. Going on right now. Um, I love tools is, is the truest answer is I love building something that I can give to somebody else. And they're suddenly twice as productive because of it. Um, >>It's a good feeling, isn't it? >>Oh yeah. There's >>Nothing like tools were platforms. Mm-hmm <affirmative>, you know, the expression, too many tools in the tool. She becomes, you know, tools for all. And then ultimately tools become platforms. What's your view on that? Because if a good tool works and starts to get traction, you need to either add more tools or start building a platform platform versus tool. What's your, what's your view on a reaction to that kind of concept debate? >>Yeah, it's a good question. Uh, we we've basically started as like a, a platform. First of we've really focused on these, uh, developers who don't wanna get deep into the DevOps. And so we've done all of the pieces of the stacks. We do C I C D management. Uh, we do container orchestration, we do monitoring. Um, and now we're, spliting those up into individual tools so they can be used. Awesome in conjunction more. >>All right. So what are some of the use cases that you see for your service? It's DevOps basically nano service DevOps. So people who want a DevOps team, do clients have a DevOps person and then one person, two people what's the requirements to run >>Z. Yeah. So we we've got teams, um, from no DevOps is kind of when they start and then we've had teams grow up to about, uh, five, 10 men DevOps teams. Um, so, you know, as is more infrastructure people come in because we're in your cloud, you're able to go in and configure it on top you're we can't block you. Uh, you wanna use some new AWS service. You're welcome to use that alongside the stack that we deploy >>For you. How many customers do you have now? >>So we've got about 40 companies that are using us for all of their infrastructure, um, kind of across the board, um, as well as >>What's the pricing model. >>Uh, so our pricing model is we, we charge basically similar to an engineering salary. So we charge a monthly rate. We have plans at 300 bucks a month, a thousand bucks a month, and then enterprise plan for >>The requirement scale. Yeah. So back into the people cost, you must have her discounts, not a fully loaded thing, is it? >>Yeah, there's a discounts kind of asking >>Then you pass the Amazon bill. >>Yeah. So our customers actually pay for the Amazon bill themselves. So >>Have their own >>Account. There's no margin on top. You're linking your, a analyst account in, um, got it. Which is huge because we can, we are now able to help our customers get better deals with Amazon. Um, got it. We're incentivized on their team to drive your costs down. >>And what's your unit main unit of economics software scale. >>Yeah. Um, yeah, so we, we think of things as projects. How many services do you have to deploy as that scales up? Um, awesome. >>All right. You're 20 years old now you not even can't even drink legally. <laugh> what are you gonna do when you're 30? We're gonna be there. >>Well, we're, uh, we're making it better, better, >>Better the old guy on the queue here. <laugh> >>I think, uh, I think we're seeing a big shift of, um, you know, we've got these major clouds. ALS is obviously the biggest cloud and it's constantly coming out with new services, but we're starting to see other clouds have built many of the common services. So Kubernetes is a great example. It exists across all the clouds and we're starting to see new platforms come up on top that allow you to leverage tools for multiple times. At the same time. Many of our customers actually have AWS as their primary cloud and they'll have secondary clouds or they'll pull features from other clouds into AWS, um, through our software. I think that's, I'm very excited by that. And I, uh, expect to be working on that when I'm 30. <laugh> awesome. >>Well, you gonna have a good future. I gotta ask you this question cuz uh, you know, I always, I was a computer science undergrad in the, in the, and um, computer science back then was hardcore, mostly systems OS stuff, uh, database compiler. Um, now there's so much compi, right? Mm-hmm <affirmative> how do you look at the high school college curriculum experience slash folks who are nerding out on computer science? It's not one or two things. You've got a lot of, lot of things. I mean, look at Python, data engineering and emerging as a huge skill. What's it, what's it like for college kids now and high school kids? What, what do you think they should be doing if you had to give advice to your 16 year old self back a few years ago now in college? Um, I mean Python's not a great language, but it's super effective for coding and the datas were really relevant, but it's, you've got other language opportunities you've got tools to build. So you got a whole culture of young builders out there. What should, what should people gravitate to in your opinion and stay away from or >>Stay away from? That's a good question. I, I think that first of all, you're very right of the, the amount of developers is increasing so quickly. Um, and so we see more specialization. That's why we also see, you know, these SREs that are different than typical application engineering. You know, you get more specialization in job roles. Um, I think if, what I'd say to my 16 year old self is do projects, um, the, I learned most of my, what I've learned just on the job or online trying things, playing with different technologies, actually getting stuff out into the world, um, way more useful than what you'll learn in kind of a college classroom. I think classroom's great to, uh, get a basis, but you need to go out and experiment actually try things. >>You know? I think that's great advice. In fact, I would just say from my experience of doing all the hard stuff and cloud is so great for just saying, okay, I'm done, I'm banning the project. Move on. Yeah. Cause you know, it's not gonna work in the old days. You have to build this data center. I bought all this, you know, people hang on to the old, you know, project and try to force it out there. Now you >>Can launch a project now, >>Instant gratification, it ain't working <laugh> or this is shut it down and then move on to something new. >>Yeah, exactly. Instantly you should be able to do that much more quickly. Right. So >>You're saying get those projects and don't be afraid to shut it down. Mm-hmm <affirmative> that? Do you agree with that? >>Yeah. I think it's ex experiment. Uh, you're probably not gonna hit it rich on the first one. It's probably not gonna be that idea is the genius idea. So don't be afraid to get rid of things and just try over and over again. It's it's number of reps >>That'll win. I was commenting online. Elon Musk was gonna buy Twitter, that whole Twitter thing. And someone said, Hey, you know, what's the, I go look at the product group at Twitter's been so messed up because they actually did get it right on the first time. And we can just a great product. They could never change it because people would freak out and the utility of Twitter. I mean, they gotta add some things, the added button and we all know what they need to add, but the product, it was just like this internal dysfunction, the product team, what are we gonna work on? Don't change the product so that you kind of have there's opportunities out there where you might get the lucky strike right outta the gate. Yeah. Right. You don't know. >>It's almost a curse too. It's you're not gonna hit curse Twitter. You're not gonna hit a rich the second time too. So yeah. >><laugh> Johnny Dallas. Thanks for coming on the cube. Really appreciate it. Give a plug for your company. Um, take a minute to explain what you're working on. What you're look looking for. You hiring funding. Customers. Just give a plug, uh, last minute and kind the last word. >>Yeah. So, um, John Dallas from Ze, if you, uh, need any help with your DevOps, if you're a early startup, you don't have DevOps team, um, or you're trying to deploy across clouds, check us out z.com. Um, we are actively hiring. So if you are a software engineer excited about tools and cloud, or you're interested in helping getting this message out there, hit me up. Um, find us on z.co. >>Yeah. LinkedIn Twitter handle GitHub handle. >>Yeah. I'm the only Johnny on a LinkedIn and GitHub and underscore Johnny Dallas underscore on Twitter. All right. Um, >>Johnny Dallas, the youngest engineer working at Amazon, um, now 20 we're on great new project here in the cube. Builders are all young. They're growing into the business. They got cloud at their, at their back it's tailwind. I wish I was 20. Again, this is a I'm John for your host. Thanks for watching. Thanks. >>Welcome >>Back to the cubes. Live coverage of a AWS summit in San Francisco, California events are back, uh, ADAS summit in New York cities. This summer, the cube will be there as well. Check us out there lot. I'm glad we have events back. It's great to have everyone here. I'm John furry host of the cube. Dr. Matt wood is with me cube alumni now VP of business analytics division of AWS. Matt. Great to see you. Thank >>You, John. Great to be here. >>Appreciate it. I always call you Dr. Matt wood, because Andy jazzy always says Dr. Matt, we >>Would introduce you on the he's the one and only the one and >>Only Dr. Matt wood >>In joke. I love it. >>Andy style. And I think you had walkup music too on, you know, >>Too. Yes. We all have our own personalized walk. >>So talk about your new role. I not new role, but you're running up, um, analytics, business or AWS. What does that consist of right now? >>Sure. So I work, I've got what I consider to be the one of the best jobs in the world. Uh, I get to work with our customers and, uh, the teams at AWS, uh, to build the analytics services that millions of our customers use to, um, uh, slice dice, pivot, uh, better understand their day data, um, look at how they can use that data for, um, reporting, looking backwards and also look at how they can use that data looking forward. So predictive analytics and machine learning. So whether it is, you know, slicing and dicing in the lower level of, uh Hado and the big data engines, or whether you're doing ETR with glue or whether you're visualizing the data in quick side or building models in SageMaker. I got my, uh, fingers in a lot of pies. >>You know, one of the benefits of, uh, having cube coverage with AWS since 2013 is watching the progression. You were on the cube that first year we were at reinvent 2013 and look at how machine learning just exploded onto the scene. You were involved in that from day one is still day one, as you guys say mm-hmm <affirmative>, what's the big thing now. I mean, look at, look at just what happened. Machine learning comes in and then a slew of services come in and got SageMaker became a hot seller, right outta the gate. Mm-hmm <affirmative> the database stuff was kicking butt. So all this is now booming. Mm-hmm <affirmative> that was the real generational changeover for <inaudible> what's the perspective. What's your perspective on, yeah, >>I think how that's evolved. No, I think it's a really good point. I, I totally agree. I think for machine machine learning, um, there was sort of a Renaissance in machine learning and the application of machine learning machine learning as a technology has been around for 50 years, let's say, but, uh, to do machine learning, right? You need like a lot of data, the data needs to be high quality. You need a lot of compute to be able to train those models and you have to be able to evaluate what those mean as you apply them to real world problems. And so the cloud really removed a lot of the constraints. Finally, customers had all of the data that they needed. We gave them services to be able to label that data in a high quality way. There's all the compute. You need to be able to train the models <laugh> and so where you go. >>And so the cloud really enabled this Renaissance with machine learning, and we're seeing honestly, a similar Renaissance with, uh, with data, uh, and analytics. You know, if you look back, you know, five, 10 years, um, analytics was something you did in batch, like your data warehouse ran a analysis to do, uh, reconciliation at the end of the month. And then was it? Yeah. And so that's when you needed it, but today, if your Redshift cluster isn't available, uh, Uber drivers don't turn up door dash deliveries, don't get made. It's analytics is now central to virtually every business and it is central to every virtually every business is digital transformation. Yeah. And be able to take that data from a variety of sources here, or to query it with high performance mm-hmm <affirmative> to be able to actually then start to augment that data with real information, which usually comes from technical experts and domain experts to form, you know, wisdom and information from raw data. That's kind of, uh, what most organizations are trying to do when they kind of go through this analytics journey. It's >>Interesting, you know, Dave LAN and I always talk on the cube, but out, you know, the future and, and you look back, the things we were talking about six years ago are actually happening now. Yeah. And it's not a, a, a, you know, hyped up statement to say digital transformation. It actually's happening now. And there's also times where we bang our fist on the table, say, I really think this is so important. And Dave says, John, you're gonna die on that hill <laugh>. >>And >>So I I'm excited that this year, for the first time I didn't die on that hill. I've been saying data you're right. Data as code is the next infrastructure as code mm-hmm <affirmative>. And Dave's like, what do you mean by that? We're talking about like how data gets and it's happening. So we just had an event on our 80 bus startups.com site mm-hmm <affirmative>, um, a showcase with startups and the theme was data as code and interesting new trends emerging really clearly the role of a data engineer, right? Like an SRE, what an SRE did for cloud. You have a new data engineering role because of the developer on, uh, onboarding is massively increasing exponentially, new developers, data science, scientists are growing mm-hmm <affirmative> and the, but the pipelining and managing and engineering as a system. Yeah. Almost like an operating system >>And as a discipline. >>So what's your reaction to that about this data engineer data as code, because if you have horizontally scalable data, you've gotta be open that's hard. <laugh> mm-hmm <affirmative> and you gotta silo the data that needs to be siloed for compliance and reasons. So that's got a very policy around that. So what's your reaction to data as code and data engineering and >>Phenomenon? Yeah, I think it's, it's a really good point. I think, you know, like with any, with any technology, uh, project inside an organization, you know, success with analytics or machine learning is it's kind of 50% technology and then 50% cultural. And, uh, you have often domain experts. Those are, could be physicians or drug experts, or they could be financial experts or whoever they might be got deep domain expertise. And then you've got technical implementation teams and it's kind of a natural often repulsive force. I don't mean that rudely, but they, they just, they don't talk the same language. And so the more complex the domain and the more complex the technology, the stronger that repulsive force, and it can become very difficult for, um, domain experts to work closely with the technical experts, to be able to actually get business decisions made. And so what data engineering does and data engineering is in some cases team, or it can be a role that you play. >>Uh, it's really allowing those two disciplines to speak the same language it provides. You can think of it as plumbing, but I think of it as like a bridge, it's a bridge between like the technical implementation and the domain experts. And that requires like a very disparate range of skills. You've gotta understand about statistics. You've gotta understand about the implementation. You've gotta understand about the, it, you've gotta understand and understand about the domain. And if you could pull all of that together, that data engineering discipline can be incredibly transformative for an organization, cuz it builds the bridge between those two >>Groups. You know, I was advising some, uh, young computer science students at the sophomore junior level, uh, just a couple weeks ago. And I told 'em, I would ask someone at Amazon, this questions I'll ask you since you're, you've been in the middle of of it for years, they were asking me and I was trying to mentor them on. What, how do you become a data engineer from a practical standpoint, uh, courseware projects to work on how to think, um, not just coding Python cause everyone's coding in Python mm-hmm <affirmative> but what else can they do? So I was trying to help them and I didn't really know the answer myself. I was just trying to like kind of help figure it out with them. So what is the answer in your opinion or the thoughts around advice to young students who want to be data engineers? Cuz data scientists is pretty clear in what that is. Yeah. You use tools, you make visualizations, you manage data, you get answers and insights and apply that to the business. That's an application mm-hmm <affirmative>, that's not the, you know, sta standing up a stack or managing the infrastructure. What, so what does that coding look like? What would your advice be to >>Yeah, I think >>Folks getting into a data engineering role. >>Yeah. I think if you, if you believe this, what I said earlier about like 50% technology, 50% culture, like the, the number one technology to learn as a data engineer is the tools in the cloud, which allow you to aggregate data from virtually any source into something which is incrementally more valuable for the organization. That's really what data engineering is all about. It's about taking from multiple sources. Some people call them silos, but silos indicates that the, the storage is kind of fungible or UND differentiated. That that's really not the case. Success requires you to really purpose built well crafted high performance, low cost engines for all of your data. So understanding those tools and understanding how to use 'em, that's probably the most important technical piece. Um, and yeah, Python and programming and statistics goes along with that, I think. And then the most important cultural part, I think is it's just curiosity. >>Like you want to be able to, as a data engineer, you want to have a natural curiosity that drives you to seek the truth inside an organization, seek the truth of a particular problem and to be able to engage, cuz you're probably, you're gonna have some choice as you go through your career about which domain you end up in, like maybe you're really passionate about healthcare. Maybe you're really just passionate about your transportation or media, whatever it might be. And you can allow that to drive a certain amount of curiosity, but within those roles, like the domains are so broad, you kind of gotta allow your curiosity to develop and lead, to ask the right questions and engage in the right way with your teams. So because you can have all the technical skills in the world, but if you're not able to help the team's truths seek through that curiosity, you simply won't be successful. >>We just had a guest on 20 year old, um, engineer, founder, Johnny Dallas, who was 16 when he worked at Amazon youngest engineer at >>Johnny Dallas is a great name by the that's fantastic. It's his real name? >>It sounds like a football player. Rockstar. I should call Johnny. I have Johnny Johnny cube. Uh it's me. Um, so, but he's young and, and he, he was saying, you know, his advice was just do projects. >>Yeah. That's get hands on. >>Yeah. And I was saying, Hey, I came from the old days though, you get to stand stuff up and you hugged onto the assets. Cause you didn't wanna kill the cause you spent all this money and, and he's like, yeah, with cloud, you can shut it down. If you do a project that's not working and you get bad data, no one's adopting it or you don't want like it anymore. You shut it down. Just something >>Else. Totally >>Instantly abandoned it. Move onto something new. >>Yeah. With progression. Totally. And it, the, the blast radius of, um, decisions is just way reduced, gone. Like we talk a lot about like trying to, you know, in the old world trying to find the resources and get the funding. And it's like, right. I wanna try out this kind of random idea that could be a big deal for the organization. I need 50 million in a new data center. Like you're not gonna get anywhere. You, >>You do a proposal working backwards, document >>Kinds, all that, that sort of stuff got hoops. So, so all of that is gone, but we sometimes forget that a big part of that is just the, the prototyping and the experimentation and the limited blast radius in terms of cost. And honestly, the most important thing is time just being able to jump in there, get fingers on keyboards, just try this stuff out. And that's why at AWS, we have part of the reason we have so many services because we want, when you get into AWS, we want the whole toolbox to be available to every developer. And so, as your ideas developed, you may want to jump from, you know, data that you have, that's already in a database to doing realtime data. Yeah. And then you can just, you have the tools there. And when you want to get into real time data, you don't just have kineses, but you have real time analytics and you can run SQL again, that data is like the, the capabilities and the breadth, like really matter when it comes to prototyping and, and >>That's culture too. That's the culture piece, because what was once a dysfunctional behavior, I'm gonna go off the reservation and try something behind my boss's back or cause now as a side hustle or fun project. Yeah. So for fun, you can just code something. Yeah, >>Totally. I remember my first Haddo project, I found almost literally a decommissioned set of servers in the data center that no one was using. They were super old. They're about to be literally turned off. And I managed to convince the team to leave them on for me for like another month. And I installed her DUP on them and like, got them going. It's like, that just seems crazy to me now that I, I had to go and convince anybody not to turn these service off, but what >>It was like for that, when you came up with elastic map produce, because you said this is too hard, we gotta make it >>Easier. Basically. Yes. <laugh> I was installing Haddo version, you know, beta nor 0.9 or whatever it was. It's like, this is really hard. This is really hard. >>We simpler. All right. Good stuff. I love the, the walk down memory lane and also your advice. Great stuff. I think culture's huge. I think. And that's why I like Adam's keynote to reinvent Adam. Lesky talk about path minds and trail blazers because that's a blast radius impact. Mm-hmm <affirmative> when you can actually have innovation organically just come from anywhere. Yeah, that's totally cool. Totally. Let's get into the products. Serverless has been hot mm-hmm <affirmative> uh, we hear a lot about EKS is hot. Uh, containers are booming. Kubernetes is getting adopted. There's still a lot of work to do there. Lambda cloud native developers are booming, serverless Lambda. How does that impact the analytics piece? Can you share the hot, um, products around how that translates? Sure, absolutely. Yeah, the SageMaker >>Yeah, I think it's a, if you look at kind of the evolution and what customers are asking for, they're not, you know, they don't just want low cost. They don't just want this broad set of services. They don't just want, you know, those services to have deep capabilities. They want those services to have as lower operating cost over time as possible. So we kind of really got it down. We got built a lot of muscle, lot of services about getting up and running and experimenting and prototyping and turning things off and turn turning them on and turning them off. And like, that's all great. But actually the, you really only most projects start something once and then stop something once. And maybe there's an hour in between, or maybe there's a year, but the real expense in terms of time and, and complexity is sometimes in that running cost. Yeah. And so, um, we've heard very loudly and clearly from customers that they want, that, that running cost is just undifferentiated to them and they wanna spend more time on their work and in analytics that is, you know, slicing the data, pivoting the data, combining the data, labeling the data, training their models, uh, you know, running inference against their models, uh, and less time doing the operational pieces. >>So is that why the servers focus is there? >>Yeah, absolutely. It, it dramatically reduces the skill required to run these, uh, workloads of any scale. And it dramatically reduces the UND differentiated, heavy lifting, cuz you get to focus more of the time that you would've spent on the operation on the actual work that you wanna get done. And so if you look at something just like Redshift serverless that we launched a reinvent, you know, there's a kind of a, we have a lot of customers that want to run like a, uh, the cluster and they want to get into the, the weeds where there is benefit. We have a lot of customers that say, you know, I there's no benefit for me though. I just wanna do the analytics. So you run the operational piece, you're the experts we've run. You know, we run 60 million instant startups every single day. Like we do this a lot. Exactly. We understand the operation. I >>Want the answers come on. So >>Just give the answers or just let, give me the notebook or just give the inference prediction. So today for example, we announced, um, you know, serverless inference. So now once you've trained your machine learning model, just, uh, run a few, uh, lines of code or you just click a few buttons and then yeah, you got an inference endpoint that you do not have to manage. And whether you're doing one query against that endpoint, you know, per hour or you're doing, you know, 10 million, but we'll just scale it on the back end. You >>Know, I know we got not a lot of time left, but I want, wanna get your reaction to this. One of the things about the data lakes, not being data swamps has been from what I've been reporting and hearing from customers is that they want to retrain their machine learning algorithm. They want, they need that data. They need the, the, the realtime data and they need the time series data, even though the time has passed, they gotta store in the data lake mm-hmm <affirmative>. So now the data lakes main function is being reusing the data to actually retrain. Yeah, >>That's >>Right. It worked properly. So a lot of, lot of postmortems turn into actually business improvements to make the machine learning smarter, faster. You see that same way. Do you see it the same way? Yeah, >>I think it's, I think it's really interesting. No, I think it's really interesting because you know, we talk it's, it's convenient to kind of think of analytics as a very clear progression from like point a point B, but really it's, you are navigating terrain for which you do not have a map and you need a lot of help to navigate that terrain. Yeah. And so, you know, being, having these services in place, not having to run the operations of those services, being able to have those services be secure and well governed, and we added PII detection today, you know, something you can do automatically, uh, to be able to use their, uh, any unstructured data run queries against that unstructured data. So today we added, you know, um, text extract queries. So you can just say, well, uh, you can scan a badge for example, and say, well, what's the name on this badge? And you don't have to identify where it is. We'll do all of that work for you. So there's a often a, it's more like a branch than it is just a, a normal, uh, a to B path, a linear path. Uh, and that includes loops backwards. And sometimes you gotta get the results and use those to make improvements further upstream. And sometimes you've gotta use those. And when you're downstream, you'll be like, ah, I remember that. And you come back and bring it all together. So awesome. It's um, it's, uh, uh, it's a wonderful >>Work for sure. Dr. Matt wood here in the queue. Got just take the last word and give the update. Why you're here. What's the big news happening that you're announcing here at summit in San Francisco, California, and update on the, the business analytics >>Group? Yeah, I think, you know, one of the, we did a lot of announcements in the keynote, uh, encouraged everyone to take a look at that. Uh, this morning was Swami. Uh, one of the ones I'm most excited about, uh, is the opportunity to be able to take, uh, dashboards, visualizations. We're all used to using these things. We see them in our business intelligence tools, uh, all over the place. However, what we've heard from customers is like, yes, I want those analytics. I want their visualization. I want it to be up to date, but you know, I don't actually want to have to go my tools where I'm actually doing my work to another separate tool to be able to look at that information. And so today we announced, uh, one click public embedding for quick side dashboards. So today you can literally, as easily as embedding a YouTube video, you can take a dashboard that you've built inside, quick site cut and paste the HTML, paste it into your application and that's it. That's all you have to do. It takes seconds and >>It gets updated in real time. >>Updated in real time, it's interactive. You can do everything that you would normally do. You can brand it like this is there's no power by quick site button or anything like that. You can change the colors, make it fit in perfectly with your, with your applications. So that's sitting incredibly powerful way of being able to take a, uh, an analytics capability that today sits inside its own little fiefdom and put it just everywhere. It's, uh, very transformative. >>Awesome. And the, the business is going well. You got the serverless and your tailwind for you there. Good stuff, Dr. Matt with thank you. Coming on the cube >>Anytime. Thank >>You. Okay. This is the cubes cover of eight summit, 2022 in San Francisco, California. I'm John host cube. Stay with us with more coverage of day two after this short break.

>>Hello, everyone. Welcome to the cubes presentation of the 80 minutes startup showcase. Season two, episode two, the theme is data as code, the future of analytics. I'm John furry, your host. We had a great day lineup for you. Fast growing startups, great lineup of companies, founders, and stories around data as code. And we're going to kick it off here with our opening keynote with Rahul Pathak VP of analytics at AWS cube alumni. Right? We'll thank you for coming on and being the opening keynote for this awesome event. >>Yeah. And it's great to see you, and it's great to be part of this event, uh, excited to, um, to help showcase some of the great innovation that startups are doing on top of AWS. >>Yeah. We last spoke at AWS reinvent and, uh, a lot's happened there, service loss of serverless as the center of the, of the action, but all these start-ups rock set Dremio Cribble monks next Liccardo, a HANA imply all doing great stuff. Data as code has a lot of traction. So a lot of still momentum going on in the marketplace. Uh, pretty exciting. >>No, it's, uh, it's awesome. I mean, I think there's so much innovation happening and you know, the, the wonderful part of working with data is that the demand for services and products that help customers drive insight from data is just skyrocketing and has no sign of no sign of slowing down. And so it's a great time to be in the data business. >>It's interesting to see the theme of the show getting traction, because you start to see data being treated almost like how developers write software, taking things out of branches, working on them, putting them back in, uh, machine learnings, uh, getting iterated on you, seeing more models, being trained differently with better insights, action ones that all kind of like working like code. And this is a whole nother way. People are reinventing their businesses. This has been a big, huge wave. What's your reaction to that? >>Uh, I think it's spot on, I mean, I think the idea of data's code and bringing some of the repeatability of processes from software development into how people built it, applications is absolutely fundamental and especially so in machine learning where you need to think about the explainability of a model, what version of the world was it trained on? When you build a better model, you need to be able to explain and reproduce it. So I think your insights are spot on and these ideas are showing up in all stages of the data work flow from ingestion to analytics to I'm out >>This next way is about modernization and going to the next level with cloud-scale. Uh, thank you so much for coming on and being the keynote presenter here for this great event. Um, I'll let you take it away. Reinventing businesses, uh, with ads analytics, right? We'll take it away. >>Okay, perfect. Well, folks, we're going to talk about, uh, um, reinventing your business with, uh, data. And if you think about it, the first wave of reinvention was really driven by the cloud. As customers were able to really transform how they thought about technology and that's well on her way. Although if you stop and think about it, I think we're only about five to 10% of the way done in terms of it span being on the cloud. So lots of work to do there, but we're seeing another wave of reinvention, which is companies reinventing their businesses with data and really using data to transform what they're doing to look for new opportunities and look for ways to operate more efficiently. And I think the past couple of years of the pandemic, it really only accelerated that trend. And so what we're seeing is, uh, you know, it's really about the survival of the most informed folks for the best data are able to react more quickly to what's happening. >>Uh, we've seen customers being able to scale up if they're in, say the delivery business or scale down, if they were in the travel business at the beginning of all of this, and then using data to be able to find new opportunities and new ways to serve customers. And so it's really foundational and we're seeing this across the board. And so, um, you know, it's great to see the innovation that's happening to help customers make sense of all of this. And our customers are really looking at ways to put data to work. It's about making better decisions, finding new efficiencies and really finding new opportunities to succeed and scale. And, um, you know, when it comes to, uh, good examples of this FINRA is a great one. You may not have heard of them, but that the U S equities regulators, all trading that happens in equities, they keep track of they're look at about 250 billion records per day. >>Uh, the examiner, I was only EMR, which is our spark and Hadoop service, and they're processing 20 terabytes of data running across tens of thousands of nodes. And they're looking for fraud and bad actors in the market. So, um, you know, huge, uh, transformation journey for FINRA over the years of customer I've gotten to work with personally since really 2013 onward. So it's been amazing to see their journey, uh, Pinterest, not a great customer. I'm sure everyone's familiar with, but, um, you know, they're about visual search and discovery and commerce, and, um, they're able to scale their daily lot searches, um, really a factor of three X or more, uh, drive down their costs. And they're using the Amazon Opus search service. And really what we're trying to do at AWS is give our customers the most comprehensive set of services for the end-to-end journey around, uh, data from ingestion to analytics and machine learning. And we will want to provide a comprehensive set of capabilities for ingestion, cataloging analytics, and then machine learning. And all of these are things that our partners and the startups that are run on us have available to them to build on as they build and deliver value for their customers. >>And, you know, the way we think about this is we want customers to be able to modernize what they're doing and their infrastructure. And we provide services for that. It's about unifying data, wherever it lives, connecting it. So the customers can build a complete picture of their customers and business. And then it's about innovation and really using machine learning to bring all of this unified data, to bear on driving new innovation and new opportunities for customers. And what we're trying to do AWS is really provide a scalable and secure cloud platform that customers and partners can build on a unifying is about connecting data. And it's also about providing well-governed access to data. So one of the big trends that we see is customers looking for the ability to make self-service data available to that customer there and use. And the key to that is good foundational governance. >>Once you can define good access controls, you then are more comfortable setting data free. And, um, uh, the other part of it is, uh, data lakes play a huge role because you need to be able to think about structured and unstructured data. In fact, about 80% of the data being generated today, uh, is unstructured. And you want to be able to connect data that's in data lakes with data that's in purpose-built data stores, whether that's databases on AWS databases, outside SAS products, uh, as well as things like data warehouses and machine learning systems, but really connecting data as key. Uh, and then, uh, innovation, uh, how can we bring to bear? And we imagine all processes with new technologies like AI and machine learning, and AI is also key to unlocking a lot of the value that's in unstructured data. If you can figure out what's in an imagine the sentiment of audio and do that in real-time that lets you then personalize and dynamically tailor experiences, all of which are super important to getting an edge, um, in, uh, in the modern marketplace. And so at AWS, we, when we think about connecting the dots across sources of data, allowing customers to use data, lakes, databases, analytics, and machine learning, we want to provide a common catalog and governance and then use these to help drive new experiences for customers and their apps and their devices. And then this, you know, in an ideal world, we'll create a closed loop. So you create a new experience. You observe our customers interact with it, that generates more data, which is a data source that feeds into the system. >>And, uh, you know, on AWS, uh, thinking about a modern data strategy, uh, really at the core is a data lakes built on us three. And I'll talk more about that in a second. Then you've got services like Athena included, lake formation for managing that data, cataloging it and querying it in place. And then you have the ability to use the right tool for the right job. And so we're big believers in purpose-built services for data because that's where you can avoid compromising on performance functionality or scale. Uh, and then as I mentioned, unification and inter interconnecting, all of that data. So if you need to move data between these systems, uh, there's well-trodden pathways that allow you to do that, and then features built into services that enable that. >>And, um, you know, some of the core ideas that guide the work that we do, um, scalable data lakes at key, um, and you know, this is really about providing arbitrarily scalable high throughput systems. It's about open format data for future-proofing. Uh, then we talk about purpose-built systems at the best possible functionality, performance, and cost. Uh, and then from a serverless perspective, this has been another big trend for us. We announced a bunch of serverless services and reinvented the goal here is to really take away the need to manage infrastructure from customers. They can really focus about driving differentiated business value, integrated governance, and then machine learning pervasively, um, not just as an end product for data scientists, but also machine learning built into data, warehouses, visualization and a database. >>And so it's scalable data lakes. Uh, data three is really the foundation for this. One of our, um, original services that AWS really the backbone of so much of what we do, uh, really unmatched your ability, availability, and scale, a huge portfolio of analytics services, uh, both that we offer, but also that our partners and customers offer and really arbitrary skin. We've got individual customers and estimator in the expert range, many in the hundreds of petabytes. And that's just growing. You know, as I mentioned, we see roughly a 10 X increase in data volume every five years. So that's a exponential increase in data volumes, Uh, from a purpose-built perspective, it's the right tool for the right job, the red shift and data warehousing Athena for querying all your data. Uh, EMR is our managed sparking to do, uh, open search for log analytics and search, and then Kinesis and Amex care for CAFCA and streaming. And that's been another big trend is, uh, real time. Data has been exploding and customers wanting to make sense of that data in real time, uh, is another big deal. >>Uh, some examples of how we're able to achieve differentiated performance and purpose-built systems. So with Redshift, um, using managed storage and it's led us and since types, uh, the three X better price performance, and what's out there available to all our customers and partners in EMR, uh, with things like spark, we're able to deliver two X performance of open source with a hundred percent compatibility, uh, almost three X and Presto, uh, with on two, which is our, um, uh, new Silicon chips on AWS, better price performance, about 10 to 12% better price performance, and 20% lower costs. And then, uh, all compatible source. So drop your jobs, then have them run faster and cheaper. And that translates to customer benefits for better margins for partners, uh, from a serverless perspective, this is about simplifying operations, reducing total cost of ownership and freeing customers from the need to think about capacity management. If we invent, we, uh, announced serverless redshifts EMR, uh, serverless, uh, Kinesis and Kafka, um, and these are all game changes for customers in terms of freeing our customers and partners from having to think about infrastructure and allowing them to focus on data. >>And, um, you know, when it comes to several assumptions in analytics, we've really got a very full and complete set. So, uh, whether that's around data warehousing, big data processing streaming, or cataloging or governance or visualization, we want all of our customers to have an option to run something struggles as well as if they have specialized needs, uh, uh, instances are available as well. And so, uh, really providing a comprehensive deployment model, uh, based on the customer's use cases, uh, from a governance perspective, uh, you know, like information is about easy build and management of data lakes. Uh, and this is what enables data sharing and self service. And, um, you know, with you get very granular access controls. So rule level security, uh, simple data sharing, and you can tag data. So you can tag a group of analysts in the year when you can say those only have access to the new data that's been tagged with the new tags, and it allows you to very, scaleably provide different secure views onto the same data without having to make multiple copies, another big win for customers and partners, uh, support transactions on data lakes. >>So updates and deletes. And time-travel, uh, you know, John talked about data as code and with time travel, you can look at, um, querying on different versions of data. So that's, uh, a big enabler for those types of strategies. And with blue, you're able to connect data in multiple places. So, uh, whether that's accessing data on premises in other SAS providers or, uh, clouds, uh, as well as data that's on AWS and all of this is, uh, serverless and interconnected. And, um, and really it's about plugging all of your data into the AWS ecosystem and into our partner ecosystem. So this API is all available for integration as well, but then from an AML perspective, what we're really trying to do is bring machine learning closer to data. And so with our databases and warehouses and lakes and BI tools, um, you know, we've infused machine learning throughout our, by, um, the state of the art machine running that we offer through SageMaker. >>And so you've got a ML in Aurora and Neptune for broths. Uh, you can train machine learning models from SQL, directly from Redshift and a female. You can use free inference, and then QuickSight has built in forecasting built in natural language, querying all powered by machine learning, same with anomaly detection. And here are the ideas, you know, how can we up our systems get smarter at the surface, the right insights for our customers so that they don't have to always rely on smart people asking the right questions, um, and you know, uh, really it's about bringing data back together and making it available for innovation. And, uh, thank you very much. I appreciate your attention. >>Okay. Well done reinventing the business with AWS analytics rural. That was great. Thanks for walking through that. That was awesome. I have to ask you some questions on the end-to-end view of the data. That seems to be a theme serverless, uh, in there, uh, Mel integration. Um, but then you also mentioned picking the right tool for the job. So then you've got like all these things moving on, simplify it for me right now. So from a business standpoint, how do they modernize? What's the steps that the clients are taking with analytics, what's the best practice? How do they, what's the what's the high order bit here? >>Uh, so the basic hierarchy is, you know, historically legacy systems are rigid and inflexible, and they weren't really designed for the scale of modern data or the variety of it. And so what customers are finding is they're moving to the cloud. They're moving from legacy systems with punitive licensing into more flexible, more systems. And that allows them to really think about building a decoupled, scalable future proof architecture. And so you've got the ability to combine data lakes and databases and data warehouses and connect them using common KPIs and common data protection. And that sets you up to deal with arbitrary scale and arbitrary types. And it allows you to evolve as the future changes since it makes it easy to add in a new type of engine, as we invent a better one a few years from now. Uh, and then, uh, once you've kind of got your data in a cloud and interconnected in this way, you can now build complete pictures of what's going on. You can understand all your touch points with customers. You can understand your complete supply chain, and once you can build that complete picture of your business, you can start to use analytics and machine learning to find new opportunities. So, uh, think about modernizing, moving to the cloud, setting up for the future, connecting data end to end, and then figuring out how to use that to your advantage. >>I know as you mentioned, modern data strategy gives you the best of both worlds. And you've mentioned, um, briefly, I want to get a little bit more, uh, insight from you on this. You mentioned open, open formats. One of the themes that's come out of some of the interviews, these companies we're going to be hearing from today is open source. The role opens playing. Um, how do you see that integrating in? Because again, this is just like software, right? Open, uh, open source software, open source data. It seems to be a trend. What does open look like to you? How do you see that progressing? >>Uh, it's a great question. Uh, open operates on multiple dimensions, John, as you point out, there's open data formats. These are things like JSI and our care for analytics. This allows multiple engines tend to operate on data and it'll, it, it creates option value for customers. If you're going to data in an open format, you can use it with multiple technologies and that'll be future-proofed. You don't have to migrate your data. Now, if you're thinking about using a different technology. So that's one piece now that sort of software, um, also, um, really a big enabler for innovation and for customers. And you've got things like squat arc and Presto, which are popular. And I know some of the startups, um, you know, that we're talking about as part of the showcase and use these technologies, and this allows for really the world to contribute, to innovating and these engines and moving them forward together. And we're big believers in that we've got open source services. We contribute to open-source, we support open source projects, and that's another big part of what we do. And then there's open API is things like SQL or Python. Uh, again, uh, common ways of interacting with data that are broadly adopted. And this one, again, create standardization. It makes it easier for customers to inter-operate and be flexible. And so open is really present all the way through. And it's a big part, I think, of, uh, the present and the future. >>Yeah. It's going to be fun to watch and see how that grows. It seems to be a lot of traction there. I want to ask you about, um, the other comment I thought was cool. You had the architectural slides out there. One was data lakes built on S3, and you had a theme, the glue in lake formation kind of around S3. And then you had the constellation of, you know, Kinesis SageMaker and other things around it. And you said, you know, pick the tool for the right job. And then you had the other slide on the analytics at the center and you had Redshift and all the other, other, other services around it around serverless. So one was more about the data lake with Athena glue and lake formation. The other one's about serverless. Explain that a little bit more for me, because I'm trying to understand where that fits. I get the data lake piece. Okay. Athena glue and lake formation enables it, and then you can pick and choose what you need on the serverless side. What does analytics in the center mean? >>So the idea there is that really, we wanted to talk about the fact that if you zoom into the analytics use case within analytics, everything that we offer, uh, has a serverless option for our customers. So, um, you could look at the bucket of analytics across things like Redshift or EMR or Athena, or, um, glue and league permission. You have the option to use instances or containers, but also to just not worry about infrastructure and just think declaratively about the data that you want to. >>Oh, so basically you're saying the analytics is going serverless everywhere. Talking about volumes, you mentioned 10 X volumes. Um, what are other stats? Can you share in terms of volumes? What are people seeing velocity I've seen data warehouses can't move as fast as what we're seeing in the cloud with some of your customers and how they're using data. How does the volume and velocity community have any kind of other kind of insights into those numbers? >>Yeah, I mean, I think from a stats perspective, um, you know, take Redshift, for example, customers are processing. So reading and writing, um, multiple exabytes of data there across from each shift. And, uh, you know, one of the things that we've seen in, uh, as time has progressed as, as data volumes have gone up and did a tapes have exploded, uh, you've seen data warehouses get more flexible. So we've added things like the ability to put semi-structured data and arbitrary, nested data into Redshift. Uh, we've also seen the seamless integration of data warehouses and data lakes. So, um, actually Redshift was one of the first to enable a straightforward acquiring of data. That's sitting in locally and drives as well as feed and that's managed on a stream and, uh, you know, those trends will continue. I think you'll kind of continue to see this, um, need to query data wherever it lives and, um, and, uh, allow, uh, leaks and warehouses and purpose-built stores to interconnect. >>You know, one of the things I liked about your presentation was, you know, kind of had the theme of, you know, modernize, unify, innovate, um, and we've been covering a lot of companies that have been, I won't say stumbling, but like getting to the future, some go faster than others, but they all kind of get stuck in an area that seems to be the same spot. It's the silos, breaking down the silos and get in the data lakes and kind of blending that purpose built data store. And they get stuck there because they're so used to silos and their teams, and that's kind of holding back the machine learning side of it because the machine learning can't do its job if they don't have access to all the data. And that's where we're seeing machine learning kind of being this new iterative model where the models are coming in faster. And so the silo brake busting is an issue. So what's your take on this part of the equation? >>Uh, so there's a few things I plan it. So you're absolutely right. I think that transition from some old data to interconnected data is always straightforward and it operates on a number of levels. You want to have the right technology. So, um, you know, we enable things like queries that can span multiple stores. You want to have good governance, you can connect across multiple ones. Uh, then you need to be able to get data in and out of these things and blue plays that role. So there's that interconnection on the technical side, but the other piece is also, um, you know, you want to think through, um, organizationally, how do you organize, how do you define it once data when they share it? And one of the asylees for enabling that sharing and, um, think about, um, some of the processes that need to get put in place and create the right incentives in your company to enable that data sharing. And then the foundational piece is good guardrails. You know, it's, uh, it can be scary to open data up. And, uh, the key to that is to put good governance in place where you can ensure that data can be shared and distributed while remaining protected and adhering to the privacy and compliance and security regulations that you have for that. And once you can assert that level of protection, then you can set that data free. And that's when, uh, customers really start to see the benefits of connecting all of it together, >>Right? And then we have a batch of startups here on this episode that are doing a lot of different things. Uh, some have, you know, new lake new lakes are forming observability lakes. You have CQL innovation on the front end data, tiering innovation at the data tier side, just a ton of innovation around this new data as code. How do you see as executive at AWS? You're enabling all this, um, where's the action going? Where are the white spaces? Where are the opportunities as this architecture continues to grow, um, and get traction because of the relevance of machine learning and AI and the apps are embedding data in there now as code where's the opportunities for these startups and how can they continue to grow? >>Yeah, the, I mean, the opportunity is it's amazing, John, you know, we talked a little bit about this at the beginning, but the, there is no slow down insight for the volume of data that we're generating pretty much everything that we have, whether it's a watch or a phone or the systems that we interact with are generating data and, uh, you know, customers, uh, you know, we talk a lot about the things that'll stay the same over time. And so, you know, the data volumes will continue to go up. Customers are gonna want to keep analyzing that data to make sense of it. They're going to want to be able to do it faster and more cheaply than they were yesterday. And then we're going to want to be able to make decisions and innovate, uh, in a shorter cycle and run more experiments than they were able to do. >>And so I think as long as, and they're always going to want this data to be secure and well-protected, and so I think as long as we, and the startups that we work with can continue to push on making these things better. Can I deal with more data? Can I deal with it more cheaply? Can I make it easier to get insight? And can I maintain a super high bar in security investments in these areas will just be off. Um, because, uh, the demand side of this equation is just in a great place, given what we're seeing in terms of theater and the architect for forum. >>I also love your comment about, uh, ML integration being the last leg of the equation here or less likely the journey, but you've got that enablement of the AIP solves a lot of problems. People can see benefits from good machine learning and AI is creating opportunities. Um, and also you also have mentioned the end to end with security piece. So data and security are kind of going hand in hand these days, not just the governments and the compliance stuff we're talking about security. So machine learning integration kind of connects all of this. Um, what's it all mean for the customers, >>For customers. That means that with machine learning and really enabling themselves to use machine learning, to make sense of data, they're able to find patterns that can represent new opportunities, um, quicker than ever before. And they're able to do it, uh, dynamically. So, you know, in a prior version of the world, we'd have little bit of systems and they would be relatively rigid and then we'd have to improve them. Um, with machine learning, this can be dynamic and near real time and you can customize them. So, uh, that just represents an opportunity to deepen relationships with customers and create more value and to find more efficiency in how businesses are run. So that piece is there. Um, and you know, your ideas around, uh, data's code really come into play because machine learning needs to be repeatable and explainable. And that means versioning, uh, keeping track of everything that you've done from a code and data and learning and training perspective >>And data sets are updating the machine learning. You got data sets growing, they become code modules that can be reused and, uh, interrogated, um, security okay. Is a big as a big theme data, really important security is seen as one of our top use cases. Certainly now in this day and age, we're getting a lot of, a lot of breaches and hacks coming in, being defended. It brings up the open, brings up the data as code security is a good proxy for kind of where this is going. What's your what's take on that and your reaction to that. >>So I'm, I'm security. You can, we can never invest enough. And I think one of the things that we, um, you know, guide us in AWS is security, availability, durability sort of jobs, you know, 1, 2, 3, and, um, and it operates at multiple levels. You need to protect data and rest with encryption, good key management and good practices though. You need to protect data on the wire. You need to have a good sense of what data is allowed to be seen by whom. And then you need to keep track of who did what and be able to verify and come back and prove that, uh, you know, uh, only the things that were allowed to happen actually happened. And you can actually then use machine learning on top of all of this apparatus to say, uh, you know, can I detect things that are happening that shouldn't be happening in near real time so they could put a stop to them. So I don't think any of us can ever invest enough in securing and protecting my data and our systems, and it is really fundamental or adding customer trust and it's just good business. So I think it is absolutely crucial. And we think about it all the time and are always looking for ways to raise >>Well, I really appreciate you taking the time to give the keynote final word here for the folks watching a lot of these startups that are presenting, they're doing well. Business wise, they're being used by large enterprises and people buying their products and using their services for customers are implementing more and more of the hot startups products they're relevant. What's your advice to the customer out there as they go on this journey, this new data as code this new future of analytics, what's your recommendation. >>So for customers who are out there, uh, recommend you take a look at, um, what, uh, the startups on AWS are building. I think there's tremendous innovation and energy, uh, and, um, there's really great technology being built on top of a rock solid platform. And so I encourage customers thinking about it to lean forward, to think about new technology and to embrace, uh, move to the cloud suite, modernized, you know, build a single picture of our data and, and figure out how to innovate and when >>Well, thanks for coming on. Appreciate your keynote. Thanks for the insight. And thanks for the conversation. Let's hand it off to the show. Let the show begin. >>Thank you, John pleasure, as always.

(bright upbeat music) >> Welcome back to theCube's coverage of AWS re:Invent 2021. This is "theCube". We go out to the events. We extract the signal from the noise. We're here at a live event, hybrid event, two sets. We had two remote studios prior to the event, over 100 interviews. Really excited to have George Elissaios here. He's the director of product management for EC2 Edge, really interesting topic at AWS. George, great to see you. Thanks for coming on. >> Yeah, great to be here. Thanks for having me. >> So, everybody's talking about Edge, IoT, EC2. What's the scope of your portfolio, your responsibility? >> Yeah, well, our vision here at AWS is to really bring the power of the AWS platform wherever customers need it. AWS wherever our customers want it is our long-term vision. And we have a bunch of products in this space that help us do that and help us enable our customers whatever their use case is. So we have things like Wavelength. I know we talked about Wavelength before here in "theCube", where we bring full AWS service at the edge of the 5G network, so with 5G edge computing in partnership with telcos worldwide, our partnership with Verizon in the US has been flourishing. We're up to, I think, 15 or more Wavelength zones right now in many of the major cities in the US, but also in Japan and Korea, and in Europe with Vodafone. So that's one of the portfolio kind of offerings. And that helps you as a customer of AWS if you want to have the best latency to mobile devices, whether they are sensors, or mobile phones, or what have you. But we're also feeling out that Edge portfolio with local zones. Earlier today in Werner's keynote, we announced that we're going to launch another 30 local zones in 20 new countries, everywhere from South America, Africa, Asia, Australia, and Europe, obviously. So a lot of expansion there. Very excited about that. And that is kind of a similar offering, but it basically brings you closer to customers in metropolitan areas over the internet. >> So, Wavelength's a big feature. George, I want to get just to touch on it because I think latency comes up a lot in Edge conversations, low latency issues, whether it's cars, factories. You guys gave a demo yesterday to the press corps in the press room, I was there, where you had someone in San Francisco from the Opera and someone in person here in Vegas, and you had 13 milliseconds going back and forth demoing, real time- >> Collaboration. >> The benefit of low latency in remote. It wasn't next door. It was San Francisco. This is kind of the purpose of what Edge is about. Can you explain what that means, that demo, why it was important, and what you were trying to show, and how does it mean for the Edge? >> So there is multiple use cases. One of them is human collaboration, right? Like, we spent the last two years of our lives over conferences and kind of like the teleconferences, and trying to talk over each other and unmute ourselves desperately. But existing solutions kind of work, generally, for most of the things that we do, but when it comes to music collaboration where milliseconds matter, it's a lot harder with existing solutions to get artists to collaborate when they're hundreds of miles away. Last night, we saw a really inspiring demo, I think, of how two top tier musicians, one located in San Francisco and one located in Vegas, can collaborate in opera, which is one of the most precise art forms in the music world. There are no beats in opera to kind of synchronize, so you really need to play off each other, right? So we provided a latency between them of less than 30 milliseconds, which translates, if you're thinking about audio or if you're thinking about the speed of sound, that's like being in the same stage. And that was very inspiring. But there's also a lot of use cases that are machine to machine communications, where even lower latencies matter, and we can think of latencies down to one millisecond, like single digit milliseconds when it comes to, for example, vehicles or robots, and things like that. So we're, with our products, we're enabling customers to drive down that latency, but also the jitter, which is the variation of latency. Especially in human communications, that is almost more important than latency itself. Your mind can adapt to latency, and you can start predicting what's going to happen, but if I'm keep changing that for you, that becomes even harder. >> Well, this is what I want to get to because you got outcomes and applications like this opera example. That's an application, I guess. So working backwards from the application, that's one thing, but now people are really starting to trying to figure out, "What is the Edge?" So I have to ask you, what is AWS's Edge? Is it Outpost, Wavelength? What do people buy to make the Edge work? >> Well, for us, is providing a breadth of services that our customers can either use holistically or combine multiple of those. So a really good example, for example, is DISH Wireless. I'm sure you know we're building with DISH the first in the world mobile network, 5G mobile network fully on cloud, right? So these combines Outposts and combines local zones in order to distribute the 5G network across nationwide. And different parts of their applications live in different edges, right? The local zone, the Outputs, and the region itself. So we have our customers... You know, I talked about how local zones is going to be, you know, in total, 45 cities in the world, right? We're already in 15 in the U.S. We're going to do another 30. But customers might still come, and say, "Oh, why are you not," you know, "in "in Costa Rica?" Well, we'll have Outposts in Costa Rica. So you could build your own offering there, or you could build on top of Outputs while you distribute the rest of your workload in existing AWS offering. So to answer your question, John, there is no single answer. I think that it is per use case and per workload that customers are going to combine or choose which one of- >> Okay, so let's go through local zones. Explain what a local zone is real quick. I know we covered it a bit last year with the virtual event, but local zones are now part of the nomenclature of the AWS language. >> Yes. >> And we know what a region is, right? So regions are regions. What's a local zone? >> When your region's saying new availability zones, and then we're just (chuckles)- >> You got availability zones. Now you got local zones. Take us through the topology, if you will, of how to think about this. >> Right, so a local zone is a fully-managed AWS infrastructure deployment. So it's owned and managed and operated by AWS. And because of that, it offers you the same elasticity, and security, and all of the goodies of the cloud, but it's positioned closer to your end customers or to your own deployment. So it's positioned in the local urban, metropolitan or industrial center closer to you. So if you think about the U.S., for example, we have a few regions, like, in the East Coast and in the West Coast, but now, we're basically extending these regions, and we're bringing more and more services to 15 cities. So if you are in Miami, there is a local zone there. If you are in LA, there is two locals zones actually in LA. That enables customers to run two different types of workloads. One is these distributed clouds or distributed Edge kind of workload that we've been hearing more and more about. Think of gaming, for example, right? Like, we have customers that are, like Supercell, that need to be closer to the gamers, wherever they are. So they're going to be using a bunch of local zones to deploy. And also, we have these hyper-local use cases, where we're talking, for example, about Netflix that are enabling in LA their creative artists to connect locally and get like as low as single millisecond latencies. So local zone is like an availability zone, but it's closer to you. It offers the same scalability, the same elasticity, the same security and the same services as the AWS cloud. And it connects back to the regions to offer you the full breadth of the platform. >> So just to clarify, so the Edge strategy essentially is to bring the cloud, AWS, the primitives, the APIs, to where the customers are in instances where they either can't move or won't move their resources into the cloud, or there's no connectivity? >> Right, we have a bunch of use cases where customers either need to be there because of regulation or because of some data gravity, so data is being generated in a specific place and you need to locally process it, or we'll have customers in this distributed use case. But I think that you're pointing out a very important thing, which is a common factor across all of these offerings. It's it is the cloud. It's not like a copycat of the cloud. It's the same API. It's the same services that you already know and use, et cetera. So extending the cloud rather than copying it around is our vision, and getting those customers who, well, connectivity obviously needs to be there. We were offering AWS Private 5G. We talked about it yesterday. >> Now, a premise that we've had is that a lot of Edge use cases will be driven by AI inferencing. And so... First of all, is that a reasonable premise, that's growing, we think, very quickly, and it has huge potential. What does the compute, if that's the correct premise, what does the compute look like for that type of workload? >> That is a great premise, and that's why we think that the model that we're offering is so powerful, because you have the Edge and the cloud fully cooperating and being connected together. You know, the Edge is a resource that's more limited than the full cloud in the AWS region. So when you're doing inferencing, what you really want to do is you want to train your models back up in the region where you get more scalability and the best prices. You know, you have the full scale of AWS. But for the latency-sensitive parts of your applications, you want to push those to the Edge. So when you're doing the actual inferencing, not the training of the models- >> Real time. Yeah. >> Real time, you push that to the Edge, whether that's if your connectivity is 5G, you can push that into a Wavelength zone. If your connectivity is wired, you can push it into a local zone. If you really need it to be in your data center, you can push it in your Outposts. So you see how our kind of like building out for all of those use cases. >> But in those instances, I'm interested in what the compute looks like, 'cause I presume it's got to be low power, low cost, super high performance. I mean, all of those things that are good for data-driven workloads. >> Right, the power, if we think here, is the same compute that you know and love in the cloud. So the same EC2 instance types, the EBS volumes, the S3 for storage, or RDS for your databases and EMR clusters. You can use the same service. And the compute is the same powerful all the way down from the hardware up to the service. >> And is the promise to customers that eventually those... It's not all of those services, right? I mean, you go to Outposts today, it continues to grow. >> Continuing to grow, yeah. Right, so but conceptually, as many services you could possibly push to the Edge, you intend to do so? >> We are pushing services according to customer requests, but also there is a nuance here. The nuance is that you push down the services that are truly latency-sensitive. You don't need to push everything down to the Edge when you're talking about latency- >> Like, what's an example of what you wouldn't push down? >> So management tools, right? So when you're doing monitoring and management, yeah, you don't need these to be at the Edge. You can do that, and you can scale that. Or, you know, batch processing, it doesn't have to be at the Edge because it's, by definition, not online, not like a latency service. So we're keeping those, like AWS Batch, for example, that's in the region because, you know, that's where customers really use it. But things like EC2, EBS, EMR, we're pushing those to the Edge because those are more- >> We got two minutes left. I want to get the Outposts kind of update. I remember when Outposts launched. It was really a seminal moment for re:Invent. Hybrid. "Oh, Andy Jassy said hybrid." Yeah. "I'll never say hybrid." But now hybrid's kind of translated into all cloud operations. Now you got local zones. A lot's changed from Amazon Web Services standpoint since Outposts launched. Local zones, things are happening. 5G, DISH. Now what's the status of Outposts? Are you guys happy with it? What has it morphed into? Is it still the same game? What is Outposts today, vis-a-vis what people may think it is or isn't? >> Yeah, we've been focusing in what we're talking about, building out a number of services that customers request, but also being in more and more places. So I think we're in more than 60, now, countries with Outposts. We've seen very good adoption. We've seen very good feedback. You know, half of my EBCs have been on Outposts, but this year, I think that one of the most exciting announcements were the Outposts servers. So the smaller form factors that enable an additional use cases, like for example, retail or even building your 5G networks. You know, one of our partners, Mavenir, is moving their 5G core, so the smarts of the network that does all the routing, on Outposts servers, and we can distribute those all over the place. So, we're keeping on the innovation. We're keeping on the expansion. And we've been getting very good customer feedback- >> So all steam ahead, full steam ahead? >> Full steam ahead plus 10%. (John laughs) >> All right, guys. Thank you so much, George. Really appreciate it. We're seeing the cloud expand. The definition is growing, kind of like the universe, John. Dave Vellante for John John Furrier. You're watching "theCube" at AWS re:Invent, the leader in high tech coverage globally. We'll be right back.

(bright music) >> Welcome back everyone to theCUBE's coverage of AWS re:Invent 2021 in person. So a live event, physical in-person, also virtual hybrid. So a lot of great action online, check out the website. All the videos are there on theCUBE, as well as what's going on all of the actions on site and theCUBE's here. I'm John Furrier, your host with Dave Vellante, my cohost. Finally, we've got David Brown, VP of Elastic Compute Cloud. EC2, the bread and butter. Our favorite part of Amazon. David, great to have you back on theCUBE in person. >> John, it's great to be back. It's the first time I'd been on theCUBE in person as well. A lot of virtual events with you guys, but it's amazing to be back at re:Invent. >> We're so excited for you. I know, Matt Garman and I've talked in the past. We've talked in the past. EC2 is just an amazing product. It's always been the core block of AWS. More and more action happening and developers are now getting more action and there's well, we wrote a big piece about it. What's going on? The Silicon's really paying off. You've got to also general purpose Intel and AMD, and you've got the custom silicon, all working together. What's the new update? Give us a scoop. >> Well, John, it's actually 15 years of EC2 this year and I've been lucky to be on that team for 14 years and so incredible to see the growth. It's been an amazing journey. The thing that's really driven us, two things. One is supporting new workloads. And so what are the workloads that customers have available out there trying to do on the cloud that we don't support and launch new instance types. And that's the first thing. The second one is price performance. How do we give customers more performance at a continuously decreasing price year-over-year? And that's just driven innovation across EC2 over the years with things like Graviton. All of our inferential chips are custom silicon, but also instance types with the latest Intel Ice Lake CPU's, latest Milan. We just announced the AMD Milan instance. It's just constantly innovation across the ever-increasing list of instances. So super exciting. >> So instances become the new thing. Provision an instance, spin up an instance. Instance becomes, and you can get instances, flavors, almost like flavors, right? >> David: Yeah. >> Take us through the difference between an instance and then the EC2 itself. >> That's correct, yeah. So we actually have, by end of the year, right now we have over 475 different instances available to you whether it's GPU accelerators, high-performance computing instances, memory optimized, just enormous number. We'll actually hit 500 by the end of the year, but that is it. I mean, customers are looking for different types of machines and those are the instances. >> So the Custom Silicon, it's one of the most interesting developments. We've written about it. AWS secret weapon is one of them. I wonder if you could take us back to the decision points and the journey. The Annapurna acquisition, you started working with them as a partner, then you said, all right, let's just buy the company. >> David: Yeah. >> And then now, you're seeing the acceleration, your time to tapeout is way, way compressed. Maybe what was the catalyst and maybe we can get into where it's going. >> Yeah, absolutely. Super interesting story 'cause it actually starts all the way back in 2008. In 2008, EC2 had actually been around for just a little under two years. And if you remember back then, everybody was like, will virtualize and hypervisors, specialization would never really get you the same performances, what they were calling bare metal back then. Everybody's looking at the cloud. And so we took a look at that. And I mean, network latencies, in some cases with hypervisors were as high as 200 or 300 milliseconds. And it was a number of real challenges. And so we knew that we would have to change the way that virtualization works and get into hardware. And so in 2010, 2011, we started to look at how could I offload my network processing, my IO processing to additional hardware. And that's what we delivered our first Nitro card in 2012 and 2013. We actually offloaded all of the processing of network to a Nitro card. And that Nitro card actually had a Annapurna arm chip on it. Our Nitro 1 chip. >> For the offload? >> The offload card, yeah. And so that's when my team started to code for Arm. We started to work on our Linux works for Arm. We actually had to write our own operating system initially 'cause there weren't any operating systems available we could use. And so that's what we started this journey. And over the years, when we saw how well it worked for networking, we said, let's do it for storage as well. And then we said, Hey, we could actually improve security significantly. And by 2017, we'd actually offloaded 100% of everything we did on that server to our offload cards Leaving a 100% of the server available for customers. And we're still actually the only cloud provider that does that today. >> Just to interject, in the data center today, probably 30% of the general purpose cores are used for offloads. You're saying 0% in the cloud. >> On our nitro instances, so every instance we've launched since 2017, our C5. We use 0% of that central core. And you can actually see that in our instance types. If you look at our largest instance type, you can see that we're giving you 96 cores and we're giving you, and our largest instance, 24 terabytes of memory. We're not giving you 23.6 terabytes 'cause we need some. It's all given to you as the customer. >> So much more efficient, >> Much, much more efficient, much better, better price performance as well. But then ultimately those Nitro chips, we went through Nitro 1, Nitro 2, Nitro 3, Nitro 4. We said, Hey, could we build a general purpose server chip? Could we actually bring Arm into the cloud? And in 2018, we launched the A1 instance, which was our Graviton1 instance. And what we didn't tell people at the time is that it was actually the same chip we were using on our network card. So essentially, it was a network card that we were giving to you as a server. But what it did is it sparked the ecosystem. That's why we put it out there. And I remember before launch, some was saying, is this just going to be a university project? Are we going to see people from big universities using Arm in the cloud? Was it really going to take off? And the response was amazing. The ecosystem just grew. We had customers move to it and immediately begin to see improvements. And we knew that a year later, Graviton2 was going to come out. And Graviton2 was just an amazing chip. It continues to see incredible adoption, 40% price performance improvement over other instances. >> So this is worth calling out because I think that example of the network card, I mean, innovation can come from anywhere. This is what Jassy always would say is do the experiments. Think about the impact of what's going on here. You're focused on a mission. Let's get that processing of the lowest cost, pick up some workloads. So you're constantly tinkering with tuning the engine. New discovery comes in. Nitro is born. The chip comes in. But I think the fundamental thing, and I want to get your reaction to this 'cause we've put this out there on our post on Sunday. And I said, in every inflection point, I'm old enough, my birthday was yesterday. I'm old enough to know that. >> David: I saw that. >> I'm old enough to know that in the eighties, the client server shifts. Every inflection point where development changed, the methodology, the mindset or platforms change, all the apps went to the better platform. Who wants to run their application on a slower platform? And so, and those inflects. So now that's happening now, I believe. So you got better performance and I'm imagining that the app developers are coding for it. Take us through how you see that because okay, you're offering up great performance for workloads. Now it's cloud workloads. That's almost all apps. Can you comment on that? >> Well, it has been really interesting to see. I mean, as I said, we were unsure who was going to use it when we initially launched and the adoption has been amazing. Initially, obviously it's always, a lot of the startups, a lot of the more agile companies that can move a lot faster, typically a little bit smaller. They started experimenting, but the data got out there. That 40% price performance was a reality. And not only for specific workloads, it was broadly successful across a number of workloads. And so we actually just had SAP who obviously is an enormous enterprise, supporting enterprises all over the world, announced that they are going to be moving the S/4 HANA Cloud to run on Graviton2. It's just phenomenal. And we've seen enterprises of that scale and game developers, every single vertical looking to move to Graviton2 and get that 40% price performance. >> Now we have to, as analysts, we have to say, okay, how did you get to that 40%? And you have to make some assumptions obviously. And it feels like you still have some dry powder when you looked at Graviton2. I think you were running, I don't know, it's speculated anyway. I don't know if you guys, it's your data, two and a half, 2.5 gigahertz. >> David: Yeah. >> I don't know if we can share what's going on with Graviton3, but my point is you had some dry powder and now with Graviton3, quite a range of performance, 'cause it really depends on the workload. >> David: That's right. >> Maybe you could give some insight as to that. What can you share about how you tuned Graviton3? >> When we look at benchmarking, we don't want to be trying to find that benchmark that's highly tuned and then put out something that is, Hey, this is the absolute best we can get it to and that's 40%. So that 40% is actually just on average. So we just went and ran real world workloads. And we saw some that were 55%. We saw some that were 25. It depends on what it was, but on average, it was around the 35, 45%, and we said 40%. And the great thing about that is customers come back and say, Hey, we saw 40% in this workload. It wasn't that I had to tune it. And so with Graviton3, launching this week. Available in our C7g instance, we said 25%. And that is just a very standard benchmark in what we're seeing. And as we start to see more customer workloads, I think it's going to be incredible to see what that range looks like. Graviton2 for single-threaded applications, it didn't give you that much of a performance. That's what we meant by cloud applications, generally, multi-threaded. In Graviton3, that's no longer the case. So we've had some customers report up to 80% performance improvements of Graviton2 to Graviton3 when the application was more of a single-threaded application. So we started to see. (group chattering) >> You have to keep going, the time to market is compressing. So you have that, go ahead, sorry. >> No, no, I always want to add one thing on the difference between single and multi-threaded applications. A lot of legacy, you're single threaded. So this is kind of an interesting thing. So the mainframe, migration stuff, you start to see that. Is that where that comes in the whole? >> Well, a lot of the legacy apps, but also even some of the new apps, like single threading like video transcoding, for example, is all done on a single core. It's very difficult. I mean, almost impossible to do that multi-threaded way. A lot of the crypto algorithms as well, encryption and cryptography is often single core. So with Graviton3, we've seen a significant performance boost for video encoding, cryptographic algorithms, that sort of thing, which really impacts even the most modern applications. >> So that's an interesting point because now single threaded is where the vertical use cases come in. It's not like more general purpose OS kind of things. >> Yeah, and Graviton has already been very broad. I think we're just knocking down the last few verticals where maybe it didn't support it and now it absolutely does. >> And if an ISV then ports, like an SAP's ports to Graviton, then the customer doesn't see any, I mean, they're going to see the performance difference, but they don't have to think about it. >> David: Yeah. >> They just say, I choose that instance and I'm going to get better price performance. >> Exactly, so we've seen that from our ISVs. We've also been doing that with our AWS services. So services like EMR, RDS, Elastic Cache, it will be moving and making Graviton2 available for customers, which means the customer doesn't have to do the migration at all. It's all done for them. They just pick the instance and get the price performance benefits, and so yeah. >> I think, oh, no, that was serverless. Sorry. >> Well, Lambda actually just did launch on Graviton2. And I think they were talking about a 35% price performance improvement. >> Who was that? >> Lambda, a couple of months ago. >> So what does an ISV have to do to port to Graviton. >> It's relatively straightforward, and this is actually one of the things that has slowed customers down is the, wow, that must be a big migration. And that ecosystem that I spoke about is the important part. And today, with all the Linux operating systems being available for Arm running on Graviton2, with all of the container runtimes being available, and then slowly open source applications in ISV is being available. It's actually really, really easy. And we just ran the Graviton2 four-day challenge. And we did that because we actually had an enterprise migrate one of the largest production applications in just four days. Now, I probably wouldn't recommend that to most enterprises that we see is a little too fast, but they could actually do that. >> But just from a numbers standpoint, that's insanely amazing. I mean, when you think about four days. >> Yeah. >> And when we talked on virtually last year, this year, I can't remember now. You said, we'll just try it. >> David: That's right. >> And see what happens, so I presume a lot of people have tried it. >> Well, that's my advice. It's the unknown, it's the what will it take? So take a single engineer, tell them and give them a time. Say you have one week, get this running on Graviton2, and I think the results are pretty amazing, very surprised. >> We were one of the first, if not the first to say that Arm is going to be dominant in the enterprise. We know it's dominant in the Edge. And when you look at the performance curves and the time to tape out, it's just astounding. And I don't know if people appreciate that relative to the traditional Moore's law curve. I mean, it's a style. And then when you combine the power of the CPU, the GPU, the NPU, kind of what Apple does in the iPhone, it blows away the historical performance curves. And you're on that curve. >> That's right. >> I wonder if you could sort of explain that. >> So with Graviton, we're optimizing just across every single part of AWS. So one of the nice things is we actually own that end-to-end. So when it starts with the early design of Graviton2 and Graviton3, and we obviously working on other chips right now. We're actually using the cloud to do all of the electronic design automation. So we're able to test with AWS how that Graviton3 chip is going to work long before we've even started taping it out. And so those workloads are running on high-frequency CPU's on Graviton. Actually we're using Graviton to build Graviton now in the cloud. The other thing we're doing is we're making sure that the Annapurna team that's building those CPUs is deeply engaged with my team and we're going to ultimately go and build those instances so that when that chip arrives from tapeout. I'm not waiting nine months or two years, like would normally be the case, but I actually had an instance up and running within a week or two on somebody's desk studying to do the integration. And that's something we've optimized significantly to get done. And so it allows us to get that iteration time. It also allows us to be very, very accurate with our tapeouts. We're not having to go back with Graviton. They're all A1 chips. We're not having to go back and do multiple runs of these things because we can do so much validation and performance testing in the cloud ahead of time. >> This is the epiphany of the Arm model. >> It really is. >> It's a standard. When you send it to the fab, they know what's going to work. You hit volume and it's just no fab. >> Well, this is a great thread. We'll stay on this 'cause Adam told us when we met with them for re:Invent that they're seeing a lot more visibility into use cases at the scale. So the scale gives you an advantage on what instances might work. >> And makes the economics works. >> Makes the economics work, hence the timing, the shrinking time to market, not there, but also for the apps. Talk about the scale advantage you guys have. >> Absolutely. I mean, the scale advantage of AWS plays out in a number of ways for our customers. The first thing is being able to deliver highly optimized hardware. So we don't just look at the Graviton3 CPU, you were speaking about the core count and the frequency and Peter spoke about a lot of that in his keynote yesterday. But we look at how does the Graviton3 CPU work with the rest of the instance. What is the right balance between the CPU and memory? The CPU and the Hydro. What's the performance and the drive? We just launched the Nitro SSD, which is now we've actually building our own custom SSDs for Nitro getting better performance, being able to do updates, better security, making it more cloudy. We're just saying, we've been challenged with the SSD in the parts. The other place that scales really helping is in capacity. Being able to make sure that we can absorb things like the COVID spike, or the stuff you see in the financial industry with just enormous demand for compute. We can do that because of our scale. We are able to scale. And the final area is actually in quality because I have such an enormous fleet. I'm actually able to drive down AFR. So annual failure rates, are we well below what the mathematical theoretical tenant or possibility is? So if you look at what's put on that actual sticker on the box that says you should be able to get a full percent AFR. At scale and with focus, we're actually able to get that down to significantly below what the mathematical entitlement was actually be. >> Yeah, it's incredible. I've got a great, and this is the advantage, and that's why I believe anyone who's writing applications that has includes a database, data transfer, any kind of execution of code will use the stack. >> Why would they? Really, why? We've seen this, like you said before, whether it was PC, then the fastest Pentium or somebody. >> Why would you want your app to run slower? >> Unix box, right? ISVS want it to run as fast and as cheaply as possible. Now power plays into it as well. >> Yeah, well, we do have, I agree with what you're saying. We do have a number of customers that are still looking to run on x86, but obviously customers that want windows. Windows isn't available for Arm and so that's a challenge. They'll continue to do that. And you know the way we do look at it is most law kind of died out on us in 2002, 2003. And what I'm hoping is, not necessarily bringing wars a little back, but then we say, let's not accept the 10%, 15% improvement year-over-year. There's absolutely more we can all be doing. And so I'm excited to see where the x86 world's going and they doing a lot of great stuff. Intel Ice Lakes looking amazing. Milan is really great to have an AWS as well. >> Well, I'm thinking it's fair point 'cause we certainly look what Pat's doing it at Intel and he's remaking the company. I've said he's going to follow on the Arm playbook in my mind a little bit, and which is the right thing to do. So competition is a good thing. >> David: Absolutely. >> We're excited for you and a great to see Graviton and you guys have this kind of inflection point. We've been tracking for a while, but now the world's starting to see it. So congratulations to your team. >> David: Thank you. >> Just a couple of things. You guys have some news on instances. Talk about the deprecation issue and how you guys are keeping instances alive real quick. >> Yeah, we're super customer obsessed at Amazon. And so that really drives us. And one of the worst things for us to do is to have to tell a customer that we no longer supporting a service. We recently actually just deprecated the ECG classic network. I'm not sure if you saw that and that's actually off the 10 years of continuing to support it. And the only reason we did it is we have a tiny percentage of customers still using that from back in 2012. But one of the challenges is obviously instance hardware eventually will ultimately time out and fail and have hardware issues as it gets older and older. And so we didn't want to be in a place, in EC2, where we would have to constantly go to customers and say that M1 small, that C3, whatever you were running, it's no longer supported, please move. That's just a text that customers shouldn't have to do. And if they still getting value out of an older instance, let them keep using it. So we actually just announced at re:Invent, in my keynote on Tuesday, the longevity support for EC2 instances, which means we will never come back to you again and ask you to please get off an instance, because we can actually emulate all those instances on our Nitro system. And so all of these instances are starting to migrate to Nitro. You're getting all the benefits of Nitro for now some of our older zen instances, but also you don't have to worry about that work. That's just not something you need to do to get off in all the instance. >> That's great. That's a great test service. Stay on as long as you want. When you're ready to move, move. Okay, final question for you. I know we've got time, I want to get this in. The global network, you guys are known for AWS cloud WAN serve. Gives you updates on what's going on with that. >> So Werner just announced that in his keynote and over the last two to three years or so, we've seen a lot of customers starting to use the AWS backbone, which is extensive. I mean, you've seen the slides in Werner's keynote. It really does span the world. I think it's probably one of the largest networks out there. Customers starting to use that for actually their branch office communication. So instead of going and provisioning the own international MPLS networks and that sort of thing, they say, let me onboard to AWS with VPN or direct connect, and I can actually run the AWS backbone around the world. Now doing that actually has some complexity. You got to think about transit gateways. You got to think about those inter-region peering. And AWS cloud when takes all of that complexity away, you essentially create a cloud WAN, connecting to it to VPN or direct connect, and you can even go and actually set up network segments. So essentially VLANs for different parts of the organization. So super excited to get out that out of there. >> So the ease of use is the key there. >> Massively easy to use. and we have 26 SD-WAN partners. We even partnering with folks like Verizon and Swisscom in Switzerland to telco to actually allow them to use it for their customers as well. >> We'll probably use your service someday when we have a global rollout date. >> Let's do that, CUBE Global. And then the other was the M1 EC2 instance, which got a lot of applause. >> David: Absolutely. >> M1, I think it was based on A15. >> Yeah, that's for Mac. We've got to be careful 'cause M1 is our first instance as well. >> Yeah right, it's a little confusion there. >> So it's a Mac. The EC2 Mac is with M1 silicon from Apple, which super excited to put out there. >> Awesome. >> David Brown, great to see you in person. Congratulations to you and the team and all the work you guys have done over the years. And now that people starting to realize the cloud platform, the compute just gets better and better. It's a key part of the system. >> Thanks John, it's great to be here. >> Thanks for sharing. >> The SiliconANGLE is here. We're talking about custom silicon here on AWS. I'm John Furrier with Dave Vellante. You're watching theCUBE. The global leader in tech coverage. We'll be right back with more covers from re:Invent after this break. (bright music)

>>Good morning. Welcome back to the cubes. Continuing coverage of AWS reinvent 2021. I'm Lisa Martin. We have two live sets here. We've got over a hundred guests on the program this week with our live sets of remote sets, talking about the next decade in cloud innovation. And I'm pleased to be welcoming back. One of our cube alumni timbers. She ran the founder and CPO of Jenny-O to the program. Tom is going to be talking about why 2022 is the year open data architectures surpass the data warehouse Timur. Welcome back to the >>Cube. Thanks for having me. It's great to be here. It's >>Great to be here at a live event in person, my goodness, sitting side by side with guests. Talk to me a little bit about before we kind of dig into the data lake house versus the data warehouse. I want to, I want to unpack that with you. Talk to me about what what's going on at Jemena you guys were on the program earlier this summer, but what are some of the things going on right now in the fall of 2021? >>Yeah, for us, it's a big year of, uh, a lot of product news, a lot of new products, new innovation, a company's grown a lot. We're, uh, you know, probably three times bigger than we were a year ago. So a lot of, a lot of new, new folks on the team and, uh, many, many new customers. >>It's good, always new customers, especially during the last 22 months, which have been obviously incredibly challenging, but I want to unpack this, the difference between a data lake and data lake house, but I love the idea of a lake house by the way, but talk to me about what the differences are similarities and how customers are benefiting. Sure. Yeah. >>I think you could think of the lake house as kind of the evolution of the lake, right? So we have, we've had data lakes for a while. Now, the transition to the cloud made them a lot more powerful and now a lot of new capabilities coming into the world of data lakes really make the, that whole kind of concept that whole architecture, much more powerful to the point that you really are not going to need a data warehouse anymore. Right. And so it kind of gives you the best of both worlds, all the advantages that we had with data lakes, the flexibility to use different processing engines, to have data in your own account and open formats, um, all those benefits, but also the benefits that you had with warehouses, where you could do transactions and get high performance for your, uh, BI workloads and things like that. So the lake house makes kind of both of those come together and gives you the, the benefits of both >>Elizabeth talk to me about from a customer lens perspective, what are some of the key benefits and how does the customer go about from say they've got data warehouses, data lakes to actually evolving to the lake house. >>You know, data warehouses have been around forever, right? And you know, there's, there's been some new innovation there as we've kind of moved to the cloud, but fundamentally there are very close and very proprietary architecture that gets very expensive quickly. And so, you know, with a data warehouse, you have to take your data and load it into the warehouse, right. You know, whether that's a, you know, Terra data or snowflake or any, any other, uh, you know, database out there, that's, that's what you do. You bring the data into the engine. Um, the data lake house is a really different architecture. It's one where you actually, you're having, you have data as its own tier, right? Stored in open formats, things like parquet files and iceberg tables. And you're basically bringing the engines to the data instead of the data to the engine. And so now all of a sudden you can start to take advantage of all this innovation that's happening on the same set of data without having to copy and move it around. So whether that's, you know, Dremio for high performance, uh, BI workloads and SQL type of analysis, a spark for kind of batch processing and machine learning, Flink for streaming. So lots of different technologies that you can use on the, on the same data and the data stays in the customer's own account, right? So S3 effectively becomes their new data warehouse. >>Okay. So it can imagine during the last 22 months of this scattered work from Eddie, and we're still in this work from anywhere environment with so much data being generated at the edge of the edge, expanding that bringing the engines to the data is probably now more timely than ever. >>Yeah. I think the, the growth in data, uh, you see it everywhere, right? That that's the reason so many companies like ourselves are doing so well. Right? It's, it's, there's so much new data, so many new use cases and every company wants to be data-driven right. They all want to be, you know, to, to democratize data within the organization. Um, you know, but you need the platforms to be able to do that. Right. And so, uh, that's very hard if you have to constantly move data around, if you have to take your data, you know, which maybe is landing in S3, but move it into, you know, subsets of it into a data warehouse. And then from there move, you know, substance of that into, you know, BI extracts, right? Tableau extracts power BI imports, and you have to create cubes and lots of copies within the data warehouse. There's no way you're going to be able to provide self-service and data democratization. And so really requires a new architecture. Um, and that's one of the main things that we've been focused on at Dremio, um, is really taking the, the, the lake house and the lake and making it, not just something that data scientists use for, you know, really kind of advanced use cases, but even your production BI workloads can actually now run on the lake house when you're using a SQL technology. Like, and then >>It's really critical because as you talked about this, you know, companies, every company, these days is a data company. If they're not, they have to be, or there's a competitor in the rear view mirror that is going to be able to take over what they're doing. So this really is really critical, especially considering another thing that we learned in the last 22 months is that there's no real-time data access is no longer, a nice to have. It's really an essential for businesses in any organization. >>I think, you know, we, we see it even in our own company, right? The folks that are joining the workforce now, they, they learn sequel in school, right. They, they, they don't want to report on their desk, printed out every Monday morning. They want access to the database. How do I connect my whatever tool I want, or even type sequel by hand. And I want access to the data and I want to just use it. Right. And I want the performance of course, to be fast because otherwise I'll get frustrated and I won't use it, which has been the status quo for a long time. Um, and that's basically what we're solving >>The lake house versus a data warehouse, better able to really facilitate data democratization across an organization. >>Yeah. Because there's a big, you know, people don't talk a lot about the story before the story, right. With, with a data warehouse, the data never starts there. Right. You typically first have your data in something like an S3 or perhaps in other databases, right. And then you have to kind of ETL at all into, um, into that warehouse. And that's a lot of work. And typically only a small subset of the data gets ETL into that data warehouse. And then the user wants to query something that's not in the warehouse. And somebody has to go from engineering, spend, you know, a month or two months, you know, respond to that ticket and wiring up some new ETL, uh, to get the data in. And so it's a big problem, right? And so if you can have a system that can query the data directly in S3 and even join it with sources, uh, outside of that things like your Oracle database, your, your SQL server database here, you know, Mongo, DB, et cetera. Well, now you can really have the ability to expose data to your, to your users within the company and make it very self-service. They can, they can query any data at any time and get a fast response time that that's, that's what they need >>At self-service is key there. Speaking of self-service and things that are new. I know you guys dromio cloud launched that recently, new SAS offering. Talk to me about that. What's going on there. Yeah. >>We want to stream your cloud. We, we spent about two years, um, working on that internally and, uh, really the goal was to simplify how we deliver all of the, kind of the benefits that we've had in our product. Right. Sub-second response times on the lake, a semantic layer, the ability to connect to multiple sources, but take away the pain of having to, you know, install and manage software. Right. And so we did it in a way that the user doesn't have to think about versions. They don't have to think about upgrades. They don't have to monitor anything. It's basically like running and using Gmail. Right? You log in, you, you get to use it, right. You don't have to be very sophisticated. There's no, not a lot of administration you have to do. Um, it basically makes it a lot, a lot simpler. >>And what's the adoption been like so far? >>It's been great. It's been limited availability, but we've been onboarding customers, uh, every week now. Um, many startups, many of the world's largest companies. So that's been, that's been really exciting actually. >>So quite a range of customers. And one of the things, it sounds like you want me to has grown itself during the pandemic. We've seen acceleration of, of that, of, of, uh, startups, of a lot of companies, of cloud adoption of migration. What are some, how have your customer conversations changed in the last 22 months as businesses and every industry kind of scrambled in the beginning to, to survive and now are realizing that they need to modernize, to thrive and to be competitive and to have competitive advantage. >>I think I've seen a few different trends here. One is certainly, there's been a lot of, uh, acceleration of movement to the cloud, right? With, uh, uh, you know, how different businesses have been impacted. It's required them to be more agile, more elastic, right. They don't necessarily know how much workload they're gonna have at any point in time. So having that flexibility, both in terms of the technology that can, you know, with Dremio cloud, we scale, for example, infinitely, like you can have, you know, one query a day, or you can have a thousand queries a second and the system just takes care of it. Right. And so that's really important to these companies that are going through, you know, being impacted in various different ways, right? You had the companies, you know, the Peloton and zooms of the world that were business was exploding. >>And then of course, you know, the travel and hospitality industries, and that went to zero, all of a sudden it's been recovering nicely, uh, you know, since then, but so that flexibility, um, has been really important to customers. I think the other thing is just they've realized that they have to leverage data, right? Because in parallel to this pandemic has been also really a boom in technology, right? And so every industry is being disrupted by new startups, whether it's the insurance industry, the financial services, a lot of InsureTech, FinTech, you know, different, uh, companies that are trying to take advantage of data. So if you, as a, as an enterprise are not doing that, you know, that's a problem. >>It is a problem. It's definitely something that I think every business and every industry needs to be very acutely aware of because from a competitive advantage perspective, you know, there's someone in that rear view mirror who is going to be focused on data. I have a real solid, modern data strategy. That's going to be able to take over if a company is resting on its laurels at all. So here we are at reinvent, they talked a lot about, um, I just came off of Adam psyllid speeds. So Lipsey's keynote. But talk to me about the jumbo AWS partnership. I know AWS its partner ecosystem is huge. You're one of the partners, but talk to me about what's going on with the partnership. How long have you guys been partners? What are the advantages for your customers? >>You know, we've been very close partners with AWS for, for a number of years now, and it kind of spans many different parts of AWS from kind of the, uh, the engineering organization. So very close relationship with the S3 team, the C2 team, uh, you know, just having dinner last night with, uh, Kevin Miller, the GM of S3. Um, and so that's kind of one side of things is really the engineering integration. You know, we're the first technology to integrate with AWS lake formation, which is Amazon's data lake security technology. So we do a lot of work together on kind of upcoming features that Amazon is releasing. Um, and then also they've been really helpful on the go-to-market side of things on the sales and marketing, um, whether it's, you know, blogs on the Amazon blog, where their sales teams actually promoting Dremio to their customers, um, uh, to help them be successful. So it's really been a good, good partnership. >>And there they are, every time I talked to somebody from Amazon, we always talk about their kind of customer first focus, their customer obsession sounds like you're, there's deep alignment on from the technical engineering perspective, sales and marketing. Talk to me a little bit about cultural alignment, because when you're going into customer conversations, I imagine they want to see one unified team. >>Yeah. You know, I think Amazon does have that customer first and obviously we do as well. And we, you know, we have to right as a, as a startup for us, you know, if a customer has a problem, the whole company will jump on that problem. Right. So that's where we call it customer obsession internally. Um, and I think that's very much what we've seen, you know, with, with AWS as well as the desire to make the customer successful comes before. Okay. How does this affect a specific Amazon product? Right? Because anytime a customer is, uh, you know, using Dremio on AWS, they're also consuming many different AWS services and they're bringing data into AWS. And so, um, I, I think for both of us, it's all about how do we solve customer problems and make them successful with their data in this case. Yup. >>Solving those customer problems is the whole reason that we're all here. Right. Talk to me a little bit about, um, as we have just a few more minutes here, we, when we hear terms like, future-proof, I always want to dig in with, with folks like yourself, chief product officers, what does it actually mean? How do you enable businesses to create these future-proof data architectures that are gonna allow them to scale and be really competitive? Sure. >>So yeah, I think many companies have been, have experienced. What's known as lock-in right. They, they invest in some technology, you know, we've seen this with, you know, databases and data warehouses, right? You, you start using that and you can really never get off and prices go up and you find out that you're spending 10 times more, especially now with the cloud data warehouses 10 times more than you thought you were going to be spending. And at that point it becomes very difficult. Right? What do you do? And so, um, one of the great things about the data lake and the lake house architecture is that the data stays stored in the customer's own account. Right? It's in their S3 buckets in source formats, like parquet files and iceberg tables. Um, and they can use many different technologies on that. So, you know, today the best technology for, for, you know, sequel and, you know, powering your, your mission critical BI is, is Dremio, but tomorrow they might be something else, right. >>And that customer can then take that, uh, uh, that company can take that new technology point at the same data and start using it right. That they don't have to go through some really crazy migration process. And, you know, we see that with Teradata data and Oracle, right? The, the, the old school vendors, um, that's always been a pain. And now it is with the, with the newer, uh, cloud data warehouses, you see a lot of complaints around that, so that the lake house is fundamentally designed. Especially if you choose open source formats, like iceberg tables, as opposed to say a Delta, like you're, you're really, you know, future-proofing yourself. Right. Um, >>Got it. Talk to me about some of the things as we wrap up here that, that attendees can learn and see and touch and feel and smell at the jumbo booth at this reinvent. >>Yeah. I think there's a, there's a few different things they can, uh, they can watch, uh, watch a demo or play around with the dremmel cloud and they can talk to our team about what we're doing with Apache iceberg. It's a iceberg to me is one of the more exciting projects, uh, in this space because, you know, it's just created by Netflix and apple Salesforce, AWS just announced support for iceberg with that, with their products, Athena and EMR. So it's really kind of emerging as the standard table format, the way to represent data in open formats in S3. We've been behind iceberg now for, for a while. And so that to us is very exciting. We're happy to chat with folks at the booth about that. Um, Nessie is another project that we created an source project for, uh, really providing a good experience for your data, where you have version control and branching, and kind of trying to reinvent, uh, data engineering, data management. So that's another cool project that there, uh, we can talk about at the booth. >>So lots of opportunity there for attendees to learn even thank you, Tomer for joining me on the program today, talking about the difference between a data warehouse data lake, the lake house, did a great job explaining that Jamil cloud what's going on and how you guys are deepening that partnership with AWS. We appreciate your time. Thank you. Thanks for having me. My pleasure for Tomer. She ran I'm Lisa Martin. You're watching the cube. Our coverage of AWS reinvent continues after this.

>> Voiceover: From theCUBE's Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCUBE Conversation. >> Welcome back to theCUBE's coverage of the AWS Startup Showcase. Next Big Thing in AI, Security and Life Sciences featuring Ahana for the AI Trek. I'm your host, John Furrier. Today, we're joined by two great guests, Steven Mih, Ahana CEO, and Sachin Nayyar, Securonix CEO. Gentlemen, thanks for coming on theCUBE. We're talking about the Next-Gen technologies on AI, Open Data Lakes, et cetera. Thanks for coming on. >> Thanks for having us, John. >> Thanks, John. >> What a great line up here. >> Sachin: Thanks, Steven. >> Great, great stuff. Sachin, let's get in and talk about your company, Securonix. What do you guys do? Take us through, I know you've got a slide to help us through this, I want to introduce your stuff first then jump in with Steven. >> Absolutely. Thanks again, Steven. Ahana team for having us on the show. So Securonix, we started the company in 2010. We are the leader in security analytics and response capability for the cybermarket. So basically, this is a category of solutions called SIEM, Security Incident and Event Management. We are the quadrant leaders in Gartner, we now have about 500 customers today and have been plugging away since 2010. Started the company just really focused on analytics using machine learning and an advanced analytics to really find the needle in the haystack, then moved from there to needle in the needle stack using more algorithms, analysis of analysis. And then kind of, I evolved the company to run on cloud and become sort of the biggest security data lake on cloud and provide all the analytics to help companies with their insider threat, cyber threat, cloud solutions, application threats, emerging internally and externally, and then response and have a great partnership with Ahana as well as with AWS. So looking forward to this session, thank you. >> Awesome. I can't wait to hear the news on that Next-Gen SIEM leadership. Steven, Ahana, talk about what's going on with you guys, give us the update, a lot of stuff happening. >> Yeah. Great to be here and thanks for that such, and we appreciate the partnership as well with both Securonix and AWS. Ahana is the open source company based on PrestoDB, which is a project that came out of Facebook and is widely used, one of the fastest growing projects in data analytics today. And we make a managed service for Presto easily on AWS, all cloud native. And we'll be talking about that more during the show. Really excited to be here. We believe in open source. We believe in all the challenges of having data in the cloud and making it easy to use. So thanks for having us again. >> And looking forward to digging into that managed service and why that's been so successful. Looking forward to that. Let's get into the Securonix Next-Gen SIEM leadership first. Let's share the journey towards what you guys are doing here. As the Open Data Lakes on AWS has been a hot topic, the success of data in the cloud, no doubt is on everyone's mind especially with the edge coming. It's just, I mean, just incredible growth. Take us through Sachin, what do you guys got going on? >> Absolutely. Thanks, John. We are hearing about cyber threats every day. No question about it. So in the past, what was happening is companies, what we have done as enterprise is put all of our eggs in the basket of solutions that were evaluating the network data. With cloud, obviously there is no more network data. Now we have moved into focusing on EDR, right thing to do on endpoint detection. But with that, we also need security analytics across on-premise and cloud. And your other solutions like your OT, IOT, your mobile, bringing it all together into a security data lake and then running purpose built analytics on top of that, and then having a response so we can prevent some of these things from happening or detect them in real time versus innovating for hours or weeks and months, which is is obviously too late. So with some of the recent events happening around colonial and others, we all know cybersecurity is on top of everybody's mind. First and foremost, I also want to. >> Steven: (indistinct) slide one and that's all based off on top of the data lake, right? >> Sachin: Yes, absolutely. Absolutely. So before we go into on Securonix, I also want to congratulate everything going on with the new cyber initiatives with our government and just really excited to see some of the things that the government is also doing in this space to bring, to have stronger regulation and bring together the government and the private sector. From a Securonix perspective, today, we have one third of the fortune 500 companies using our technology. In addition, there are hundreds of small and medium sized companies that rely on Securonix for their cyber protection. So what we do is, again, we are running the solution on cloud, and that is very important. It is not just important for hosting, but in the space of cybersecurity, you need to have a solution, which is not, so where we can update the threat models and we can use the intelligence or the Intel that we gather from our customers, partners, and industry experts and roll it out to our customers within seconds and minutes, because the game is real time in cybersecurity. And that you can only do in cloud where you have the complete telemetry and access to these environments. When we go on-premise traditionally, what you will see is customers are even thinking about pushing the threat models through their standard Dev test life cycle management, and which is just completely defeating the purpose. So in any event, Securonix on the cloud brings together all the data, then runs purpose-built analytics on it. Helps you find very few, we are today pulling in several million events per second from our customers, and we provide just a very small handful of events and reduce the false positives so that people can focus on them. Their security command center can focus on that and then configure response actions on top of that. So we can take action for known issues and have intelligence in all the layers. So that's kind of what the Securonix is focused on. >> Steven, he just brought up, probably the most important story in technology right now. That's ransomware more than, first of all, cybersecurity in general, but ransomware, he mentioned some of the government efforts. Some are saying that the ransomware marketplace is bigger than some governments, nation state governments. There's a business model behind it. It's highly active. It's dominating the scene and it's a real threat. This is the new world we're living in, cloud creates the refactoring capabilities. We're hearing that story here with Securonix. How does Presto and Securonix work together? Because I'm connecting the dots here in real time. I think you're going to go there. So take us through because this is like the most important topic happening. >> Yeah. So as Sachin said, there's all this data that needs to go into the cloud and it's all moving to the cloud. And there's a massive amounts of data and hundreds of terabytes, petabytes of data that's moving into the data lakes and that's the S3-based data lakes, which are the easiest, cheapest, commodified place to put all this data. But in order to deliver the results that Sachin's company is driving, which is intelligence on when there's a ransomware or possibility, you need to have analytics on them. And so Presto is the open source project that is a open source SQL query engine for data lakes and other data sources. It was created by Facebook as part of the Linux foundation, something called Presto foundation. And it was built to replace the complicated Hadoop stack in order to then drive analytics at very lightning fast queries on large, large sets of data. And so Presto fits in with this Open Data Lake analytics movement, which has made Presto one of the fastest growing projects out there. >> What is an Open Data Lake? Real quick for the audience who wants to learn on what it means. Does is it means it's open source in the Linux foundation or open meaning it's open to multiple applications? What does that even mean? >> Yeah. Open Data Lake analytics means that you're, first of all, your data lake has open formats. So it is made up of say something called the ORC or Parquet. And these are formats that any engine can be used against. That's really great, instead of having locked in data types. Data lakes can have all different types of data. It can have unstructured, semi-structured data. It's not just the structured data, which is typically in your data warehouses. There's a lot more data going into the Open Data Lake. And then you can, based on what workload you're looking to get benefit from, the insights come from that, and actually slide two covers this pictorially. If you look on the left here on slide two, the Open Data Lake is where all the data is pulling. And Presto is the layer in between that and the insights which are driven by the visualization, reporting, dashboarding, BI tools or applications like in Securonix case. And so analytics are now being driven by every company for not just industries of security, but it's also for every industry out there, retail, e-commerce, you name it. There's a healthcare, financials, all are looking at driving more analytics for their SaaSified applications as well as for their own internal analysts, data scientists, and folks that are trying to be more data-driven. >> All right. Let's talk about the relationship now with where Presto fits in with Securonix because I get the open data layer. I see value in that. I get also what we're talking about the cloud and being faster with the datasets. So how does, Sachin' Securonix and Ahana fit in together? >> Yeah. Great question. So I'll tell you, we have two customers. I'll give you an example. We have two fortune 10 customers. One has moved most of their operations to the cloud and another customer which is in the process, early stage. The data, the amount of data that we are getting from the customer who's moved fully to the cloud is 20 times, 20 times more than the customer who's in the early stages of moving to the cloud. That is because the ability to add this level of telemetry in the cloud, in this case, it happens to be AWS, Office 365, Salesforce and several other rescalers across several other cloud technologies. But the level of logging that we are able to get the telemetry is unbelievable. So what it does is it allows us to analyze more, protect the customers better, protect them in real time, but there is a cost and scale factor to that. So like I said, when you are trying to pull in billions of events per day from a customer billions of events per day, what the customers are looking for is all of that data goes in, all of data gets enriched so that it makes sense to a normal analyst and all of that data is available for search, sometimes 90 days, sometimes 12 months. And then all of that data is available to be brought back into a searchable format for up to seven years. So think about the amount of data we are dealing with here and we have to provide a solution for this problem at a price that is affordable to the customer and that a medium-sized company as well as a large organization can afford. So after a lot of our analysis on this and again, Securonix is focused on cyber, bringing in the data, analyzing it, so after a lot of our analysis, we zeroed in on S3 as the core bucket where this data needs to be stored because the price point, the reliability, and all the other functions available on top of that. And with that, with S3, we've created a great partnership with AWS as well as with Snowflake that is providing this, from a data lake perspective, a bigger data lake, enterprise data lake perspective. So now for us to be able to provide customers the ability to search that data. So data comes in, we are enriching it. We are putting it in S3 in real time. Now, this is where Presto comes in. In our research, Presto came out as the best search engine to sit on top of S3. The engine is supported by companies like Facebook and Uber, and it is open source. So open source, like you asked the question. So for companies like us, we cannot depend on a very small technology company to offer mission critical capabilities because what if that company gets acquired, et cetera. In the case of open source, we are able to adopt it. We know there is a community behind it and it will be kind of available for us to use and we will be able to contribute in it for the longterm. Number two, from an open source perspective, we have a strong belief that customers own their own data. Traditionally, like Steven used the word locked in, it's a key term, customers have been locked in into proprietary formats in the past and those days are over. You should be, you own the data and you should be able to use it with us and with other systems of choice. So now you get into a data search engine like Presto, which scales independently of the storage. And then when we start looking at Presto, we came across Ahana. So for every open source system, you definitely need a sort of a for-profit company that invests in the community and then that takes the community forward. Because without a company like this, the community will die. So we are very excited about the partnership with Presto and Ahana. And Ahana provides us the ability to take Presto and cloudify it, or make the cloud operations work plus be our conduit to the Ahana community. Help us speed up certain items on the roadmap, help our team contribute to the community as well. And then you have to take a solution like Presto, you have to put it in the cloud, you have to make it scale, you have to put it on Kubernetes. Standard thing that you need to do in today's world to offer it as sort of a micro service into our architecture. So in all of those areas, that's where our partnership is with Ahana and Presto and S3 and we think, this is the search solution for the future. And with something like this, very soon, we will be able to offer our customers 12 months of data, searchable at extremely fast speeds at very reasonable price points and you will own your own data. So it has very significant business benefits for our customers with the technology partnership that we have set up here. So very excited about this. >> Sachin, it's very inspiring, a couple things there. One, decentralize on your own data, having a democratized, that piece is killer. Open source, great point. >> Absolutely. >> Company goes out of business, you don't want to lose the source code or get acquired or whatever. That's a key enabler. And then three, a fast managed service that has a commercial backing behind it. So, a great, and by the way, Snowflake wasn't around a couple of years ago. So like, so this is what we're talking about. This is the cloud scale. Steven, take us home with this point because this is what innovation looks like. Could you share why it's working? What's some of the things that people could walk away with and learn from as the new architecture for the new NextGen cloud is here, so this is a big part of and share how this works? >> That's right. As you heard from Sachin, every company is becoming data-driven and analytics are central to their business. There's more data and it needs to be analyzed at lower cost without the locked in and people want that flexibility. And so a slide three talks about what Ahana cloud for Presto does. It's the best Presto out of the box. It gives you very easy to use for your operations team. So it can be one or two people just managing this and they can get up to speed very quickly in 30 minutes, be up and running. And that jump starts their movement into an Open Data Lake analytics architecture. That architecture is going to be, it is the one that is at Facebook, Uber, Twitter, other large web scale, internet scale companies. And with the amount of data that's occurring, that's now becoming the standard architecture for everyone else in the future. And so just to wrap, we're really excited about making that easy, giving an open source solution because the open source data stack based off of data lake analytics is really happening. >> I got to ask you, you've seen many waves on the industry. Certainly, you've been through the big data waves, Steven. Sachin, you're on the cutting edge and just the cutting edge billions of signals from one client alone is pretty amazing scale and refactoring that value proposition is super important. What's different from 10 years ago when the Hadoop, you mentioned Hadoop earlier, which is RIP, obviously the cloud killed it. We all know that. Everyone kind of knows that. But like, what's different now? I mean, skeptics might say, I don't believe you, but it's just crazy. There's no way it works. S3 costs way too much. Why is this now so much more of an attractive proposition? What do you say the naysayers out there? With Steve, we'll start with you and then Sachin, I want you to like weigh in too. >> Yeah. Well, if you think about the Hadoop era and if you look at slide three, it was a very complicated system that was done mainly on-prem. And you'd have to go and set up a big data team and a rack and stack a bunch of servers and then try to put all this stuff together and candidly, the results and the outcomes of that were very hard to get unless you had the best possible teams and invested a lot of money in this. What you saw in this slide was that, that right hand side which shows the stack. Now you have a separate compute, which is based off of Intel based instances in the cloud. We run the best in that and they're part of the Presto foundation. And that's now data lakes. Now the distributed compute engines are the ones that have become very much easier. So the big difference in what I see is no longer called big data. It's just called data analytics because it's now become commodified as being easy and the bar is much, much lower, so everyone can get the benefit of this across industries, across organizations. I mean, that's good for the world, reduces the security threats, the ransomware, in the case of Securonix and Sachin here. But every company can benefit from this. >> Sachin, this is really as an example in my mind and you can comment too on if you'd believe or not, but replatform with the cloud, that's a no brainer. People do that. They did it. But the value is refactoring in the cloud. It's thinking differently with the assets you have and making sure you're using the right pieces. I mean, there's no brainer, you know it's good. If it costs more money to stand up something than to like get value out of something that's operating at scale, much easier equation. What's your thoughts on this? Go back 10 years and where we are now, what's different? I mean, replatforming, refactoring, all kinds of happening. What's your take on all this? >> Agreed, John. So we have been in business now for about 10 to 11 years. And when we started my hair was all black. Okay. >> John: You're so silly. >> Okay. So this, everything has happened here is the transition from Hadoop to cloud. Okay. This is what the result has been. So people can see it for themselves. So when we started off with deep partnerships with the Hadoop providers and again, Hadoop is the foundation, which has now become EMR and everything else that AWS and other companies have picked up. But when you start with some basic premise, first, the racking and stacking of hardware, companies having to project their entire data volume upfront, bringing the servers and have 50, 100, 500 servers sitting in their data centers. And then when there are spikes in data, or like I said, as you move to the cloud, your data volume will increase between five to 20x and projecting for that. And then think about the agility that it will take you three to six months to bring in new servers and then bring them into the architecture. So big issue. Number two big issue is that the backend of that was built for HDFS. So Hadoop in my mind was built to ingest large amounts of data in batches and then perform some spark jobs on it, some analytics. But we are talking in security about real time, high velocity, high variety data, which has to be available in real time. It wasn't built for that, to be honest. So what was happening is, again, even if you look at the Hadoop companies today as they have kind of figured, kind of define their next generation, they have moved from HDFS to now kind of a cloud based platform capability and have discarded the traditional HDFS architecture because it just wasn't scaling, wasn't searching fast enough, wasn't searching fast enough for hundreds of analysts at the same time. And then obviously, the servers, et cetera wasn't working. Then when we worked with the Hadoop companies, they were always two to three versions behind for the individual services that they had brought together. And again, when you're talking about this kind of a volume, you need to be on the cutting edge always of the technologies underneath that. So even while we were working with them, we had to support our own versions of Kafka, Solr, Zookeeper, et cetera to really bring it together and provide our customers this capability. So now when we have moved to the cloud with solutions like EMR behind us, AWS has invested in in solutions like EMR to make them scalable, to have scale and then scale out, which traditional Hadoop did not provide because they missed the cloud wave. And then on top of that, again, rather than throwing data in that traditional older HDFS format, we are now taking the same format, the parquet format that it supports, putting it in S3 and now making it available and using all the capabilities like you said, the refactoring of that is critical. That rather than on-prem having servers and redundancies with S3, we get built in redundancy. We get built in life cycle management, high degree of confidence data reliability. And then we get all this innovation from companies like, from groups like Presto, companies like Ahana sitting on double that S3. And the last item I would say is in the cloud we are now able to offer multiple, have multiple resilient options on our side. So for example, with us, we still have some premium searching going on with solutions like Solr and Elasticsearch, then you have Presto and Ahana providing majority of our searching, but we still have Athena as a backup in case something goes down in the architecture. Our queries will spin back up to Athena, AWS service on Presto and customers will still get served. So all of these options, but what it doesn't cost us anything, Athena, if we don't use it, but all of these options are not available on-prem. So in my mind, I mean, it's a whole new world we are living in. It is a world where now we have made it possible for companies to even enterprises to even think about having true security data lakes, which are useful and having real-time analytics. From my perspective, I don't even sign up today for a large enterprise that wants to build a data lake on-prem because I know that is not, that is going to be a very difficult project to make it successful. So we've come a long way and there are several details around this that we've kind of endured through the process, but very excited where we are today. >> Well, we certainly follow up with theCUBE on all your your endeavors. Quickly on Ahana, why them, why their solution? In your words, what would be the advice you'd give me if I'm like, okay, I'm looking at this, why do I want to use it, and what's your experience? >> Right. So the standard SQL query engine for data lake analytics, more and more people have more data, want to have something that's based on open source, based on open formats, gives you that flexibility, pay as you go. You only pay for what you use. And so it proved to be the best option for Securonix to create a self-service system that has all the speed and performance and scalability that they need, which is based off of the innovation from the large companies like Facebook, Uber, Twitter. They've all invested heavily. We contribute to the open source project. It's a vibrant community. We encourage people to join the community and even Securonix, we'll be having engineers that are contributing to the project as well. I think, is that right Sachin? Maybe you could share a little bit about your thoughts on being part of the community. >> Yeah. So also why we chose Ahana, like John said. The first reason is you see Steven is always smiling. Okay. >> That's for sure. >> That is very important. I mean, jokes apart, you need a great partner. You need a great partner. You need a partner with a great attitude because this is not a sprint, this is a marathon. So the Ahana founders, Steven, the whole team, they're world-class, they're world-class. The depth that the CTO has, his experience, the depth that Dipti has, who's running the cloud solution. These guys are world-class. They are very involved in the community. We evaluated them from a community perspective. They are very involved. They have the depth of really commercializing an open source solution without making it too commercial. The right balance, where the founding companies like Facebook and Uber, and hopefully Securonix in the future as we contribute more and more will have our say and they act like the right stewards in this journey and then contribute as well. So and then they have chosen the right niche rather than taking portions of the product and making it proprietary. They have put in the effort towards the cloud infrastructure of making that product available easily on the cloud. So I think it's sort of a no-brainer from our side. Once we chose Presto, Ahana was the no-brainer and just the partnership so far has been very exciting and I'm looking forward to great things together. >> Likewise Sachin, thanks so much for that. And we've only found your team, you're world-class as well, and working together and we look forward to working in the community also in the Presto foundation. So thanks for that. >> Guys, great partnership. Great insight and really, this is a great example of cloud scale, cloud value proposition as it unlocks new benefits. Open source, managed services, refactoring the opportunities to create more value. Stephen, Sachin, thank you so much for sharing your story here on open data lakes. Can open always wins in my mind. This is theCUBE we're always open and we're showcasing all the hot startups coming out of the AWS ecosystem for the AWS Startup Showcase. I'm John Furrier, your host. Thanks for watching. (bright music)

>>Welcome back to HPD discovered 2021. The virtual edition. My name is Dave Volonte and you're watching the cubes continuous coverage of H. P. S. Big customer event. Patrick Moorehead is here of moor insights and strategy is the number one analyst in the research analyst. Business. Patrick. Always a pleasure. Great to see you, >>David. Great to see you too. And I know you're you're up there fighting for that number one spot to. It's great to see you and it's great to see you in the meetings that were in. But it's even more fun to be here on the cube. I love to be on the cube and every once in a while you'll even call me a friend of the cube, >>unquestionably my friend and so and I can't wait second half. I mean you're traveling right now. We're headed to Barcelona to mobile World Congress later on this month. So so we're gonna we're gonna see each other face to face this year. 100%. So looking forward to that. So, you know, let's get into it. Um you know, before we get into H. P. E. Let's talk a little bit about what you're seeing in the market. We've got, you know, we we we finally, it feels like the on prem guys are finally getting their cloud act together. Um, it's maybe taken a while, but we're seeing as a service models emerge. I think it's resonating with customers. The clearly not everything is moving to the cloud. There's this hybrid model emerging. Multi cloud is real despite what, you know, >>some some >>cloud players want to say. And then there's this edges like jump ball, what are you seeing in the marketplace? >>Yeah. Davis, as exciting as ever in. Just to put in perspective, I mean, the public cloud has been around for about 10 years and still only 20%. Around 20% of the data in 20% of the applications are there now, albeit very important ones. And I'm certainly not a public cloud denier, I never have been, but there are some missing pieces that need to come together. And you know, even five years ago we were debating dave the hybrid cloud and I feel like when Amazon brought out outposts, the conversation was over right now, what you have is cloud native folks building out hybrid and on prem capabilities, you have the classic on prem folks building out hybrid and as a service capabilities. And I really think it boils down 22 things. I mean it's wanting to have more flexibility and you know, I hate to use it because it sounds like a marketing word, but agility, the ability to spin up things and spin down things in a very quick way. And uh, you know what they've learned. The veterans also know, hey, let's do this in a way that doesn't lock us in too much into a certain vendor. And I've been around for a long time. David and I'm a realist too. Well, you have to lock yourself into something. It just depends on what do you want to lock yourself into, but super exciting. And what H. P. E. When they threw the acts in the sea with Green Lake, I think it was four years ago, I think really started to stir the pot. >>You know, you mentioned the term cloud denial, but you know, and I feel like the narrative from, I like to determine is I think you should use the term veteran. You know, it's very, they're ours is the only industry patrick where legacy is a pejorative, but but but so but the point I want to make is I feel like there's been a lot of sort of fear from the veteran players, but I look at it differently. I wonder what you're taking. I think, I think, I think I calculated that the Capex spending by the big four public clouds including Alibaba last year was $100 billion. That's like a gift to the world. Here, we're going to spend $100 billion like the internet here you go build. And and so I, and I feel like companies like HP are finally saying, yeah, we're gonna build, we're gonna build a layer and we're gonna hide the complexity and we're gonna add value on top. What do you think about that? >>Yeah. So I think it's now, I wish, I wish the on prem folks like HP, you would have done it 10 years ago, but I don't think anybody expected the cloud to be as big as it's become over the last 10 years. I think we saw companies like salesforce with sas taking off, but I think it is the right direction because there are advantages to having workloads on prem and if you add an as a service capability on top of the top of that, and let's say even do a Coehlo or a managed service, it's pretty close to being similar to the public cloud with the exception, that you can't necessarily swipe a credit card for a bespoke workload if you're a developer and it is a little harder to scale out. But that is the next step in the equation day, which is having, having these folks make capital expenditures, make them in a polo facility and then put a layer to swipe a credit card and you literally have the public cloud. >>Yeah. So that's, that's a great point and that's where it's headed, isn't it? Um, so let's, let's talk about the horses on the track. Hp. As you mentioned, I didn't realize it was four years ago. I thought it was, wow, That's amazing. So everybody's followed suit. You see, Dallas announced, Cisco has announced, uh, Lenovo was announced, I think IBM as well. So we, so everybody started following suit there. The reality is, is it's taken some time to get this stuff standardized. What are you seeing from, from HP? They've made some additional announcements, discover what's your take on all this. >>Yeah. So HPD was definitely the rabbit here and they were first in the market. It was good to see, first off some of their, Um, announcements on, on how it's going. And they talked about 4, $28 billion 1200 customers over 900 partners and 95% retention. And I think that's important anybody who's in the lead and remember what Aws used to do with the slide with the amount of customers would just get bigger and bigger and bigger and that's a good way to show momentum. I like the retention part two which is 95%. And I think that that says a lot uh probably the more important announcements that they made is they talked about the G. A. Of some of their solutions on Green Lake and whether it was S. A. P. Hana Ml apps HPC with Francis V. I was Citrus in video but they also brought more of what I would call a vertical layer and I'm sure you've seen the vertical ization of all of these cloud and as a service workloads. But what they're doing with Epic with EMR and looseness, with financial payments and Splunk and intel with data and risk analysis and finally, a full stack for telco five G. One of the biggest secrets and I covered this about five years ago is HPV actually has a full stack that western european carriers use and they're now extending that to five G. And um, so more horizontal uh and and more vertical. That was the one of the big swipes uh that I saw that there was a second though, but maybe we can talk about these. >>Yeah. Okay, Okay. So, so the other piece of that of course is standardization right there there because there was a, there was, there was a lot of customization leading up to this and everybody sort of, everybody always had some kind of financial game they can play and say, hey, there's an adversary as a service model, but this is definitely more of a standardized scalable move that H P E. Is making with what they call Lighthouse, Right? >>Yeah, that's exactly right. And I've talked to some Green Lake customers and they obviously gave it kudos or they wouldn't have HP wouldn't have served them up and they wouldn't have been buying it. But they did say, um, it took, it took a while, took some paperwork to get it going. It's not 100% of push button, but that's partially because hp allows you to customize the hardware. You want a one off network adapter. Hp says yes, right. You want to integrate a different type of storage? They said yes. But with Green Lake Lighthouse, it's more of a, what you see is what you get, which by the way is very much like the public cloud or you go to a public cloud product sheet or order sheet. You're picking from a list and you really don't know everything that's underneath the covers, aside from, let's say the speed of the network, the type of the storage and the amount of the storage you get. You do get to pick between, let's say, an intel processor, Graviton two or an M. D processor. You get to pick your own GPU. But that's pretty much it. And HP Lighthouse, sorry, Green Lake Lighthouse uh, is bringing, I think a simplification to Green Lake that it needs to truly scale beyond, let's say, the white house customers at HP. Yeah, >>Well done. So, you know, and I hear your point about 10 years in, you know, plus and to me this is like a mandate. I mean, this is okay. Good, good job guys about time. But if I had a, you know, sort of look at the big players, like, can we have an oligopoly here in this, in this business? It's HP, Cisco, you got Dell Lenovo, you've got, you know, IBM, they're all doing this and they all have a different little difference, you know, waste of skin of catch. And your point about simplicity, it seems like HP HP is all in Antonio's like, okay, here's what we're going to announce that, you know, while ago, so, and they seem to have done a good job with Wall Street and they get a simple model, you know, Dell's obviously bigger portfolio, much more complicated. IBM is even more complicated than that. I don't know so much about Lenovo and in Cisco of course, has acquired a ton of SAAS companies and sort of they've got a lot of bespoke products that they're trying to put together, so they've got, but they do have SAS models. So each of them is coming at it from a different perspective. How do you think? And so and the other point we got lighthouse, which is sort of Phase one, get product market fit. Phase two now is scale codify standardized and then phase three is the moat build your unique advantage that protects your business. What do you see as HP? Es sort of unique value proposition and moat that they can build longer term. >>That's a great, great question. And let me rattle off kind of what I'm seeing that some of these these players here. So Cisco, ironically, has sells the most software of any of those players that you mentioned, uh with the exception of IBM. Um, and yeah, C >>ICSDB two. Yeah, >>yeah, they're the they're the number two security player, uh, Microsoft, number one. So and I think the evaluation on the street uh indicate that shows that I feel like uh Deltek is a is a very broad play because not only do they have servers, storage, networking and security, but they also have Pcs and devices, so it's a it's a scale and end play with a focus on VM ware solutions, not exclusively, of course. Uh And um then you've got Lenovo who is just getting into the as a service game and are gosh, they're doing great in hyper scale, they've got scale there vertically integrated. I don't know if if too many people talk about that, but Lenovo does a lot of their own manufacturing and they actually manufacture Netapp storage solutions as well. So yeah, each of these folks brings a different game to the table, I think with h P E, what your bring to the table is nimble. When HP and HP split, the number one thing that I said was that uh huh H P E is going to have to be so much faster than it offsets the scale that Dell technology has and the HBs credit, although there, I don't think we're getting credit for this in the stock market yet. Um, and I know you and I are both industry folks, not financial folks, but I think their biggest thing is speed and the ability to move faster and that is what I've seen as it relates to the moat, which is a unique uh, competitive advantage. Quite frankly, I'm still looking for that day in, in, in what that is and I think in this industry it's nearly impossible and I would posit that that any, even the cloud folks, if you say, is there something that AWS can do that Azure can't, if it put it put its mind to it or G C P. I don't think so. I think it's more of a kind of land and expand and I think for H P E, when it comes to high performance computing and I'm not just talking about government installations, I'm talking about product development, drug development, I think that is a landing place where H P E already does pretty well can come in and expand its footprint, >>you know, that's really interesting um, observations. So, and I would agree with you, it's kind of like, this is a copycat industry, it's like the west coast offense, like the NFL >>and >>so, so the moat comes from, you know, brand execution and your other point about when HP and HP split, that was a game changer, because all of a sudden you saw companies like them, you always had a long term relationship with H P E but or HP, but then they came out of the woodworks and started to explode. And so it really opened up opportunities. So it really >>is an execution, >>isn't it? But go ahead, please >>Dave if I had to pick something that I think HP HPV needs to always be ahead and as a service and listen, you know, I both know announcements don't mean delivery, but there is correlation between if you start four years ahead of somebody that other company is going to have to put just, I mean they're gonna have to turn that ship and many of its competitors really big ships to be able to get there. So I think what Antonio needs to do is run like hell, right, Because it, it, I think it is in the lead and as a service holistically doesn't mean they're going to be there forever, but they have to stay ahead. They have to add more horizontal solutions. They have to add more vertical solutions. And I believe that at some point it does need to invest in some Capex at somebody like ANna Quinn x play credit card swiper on top of that. And Dave, you have the public, you have the public cloud, you don't have all the availability zones, but you have a public cloud. >>Yeah, that's going to happen. I think you're right on. So we see this notion of cloud expanding. It's no longer just remote set of services. Somewhere out in the cloud. It's as you said, outpost was the sort of signal. Okay, We're coming on prem clearly the on prem, uh, guys are connecting to the cloud. Multi cloud exists, we know this and then there's the edge but but but that brings me to that sort of vision and everybody's laying out of this this this seamless integration hiding the complexity log into my cloud and then life will be good. But the edge is different. Right? It's not just, you know, retail store or a race track. I mean there's the far edge, there's the Tesla car, there's gonna be compute everywhere. And that sort of ties into the data. The data flows, you know the real time influencing at the edge ai new semiconductor models. You you came out of the semiconductor industry, you know it inside and out arm is exploding is dominating in the edge with with with apple and amazon Alexa and things like that. That's really where the action is. So this is a really interesting cocktail and soup that we have going on. How do you >>say? Well, you know, Dave if the data most data, I think one thing most everybody agrees on is that most of the data will be created on the edge. Whether that's a moving edge a car, a smartphone or what I call an edge data center without tile flooring. Like that server that's bolted to the wall of Mcdonald's. When you drive through, you can see it versus the walmart. Every walmart has a raised tile floor. It's the edge to economically and performance wise, it doesn't make any sense to send all that data to the mother ships. Okay. And whether that's unproven data center or the giant public cloud, more efficient way is to do the compute at the closest way possible. But what it does, it does bring up challenges. The first challenge is security. If I wanted to, I could walk in and I could take that server off the Mcdonald's or the Shell gas station wall. So I can't do that in a big data center. Okay, so security, Physical security is a challenge. The second is you don't have the people to go in there and fix stuff that are qualified. If you have a networking problem that goes wrong and Mcdonald's, there's nobody there that can help uh, they can they can help you fix that. So this notion of autonomy and management and not keeping hyper critical data sitting out there and it becomes it becomes a security issue becomes a management issue. Let me talk about the benefits though. The benefits are lower latency. You want you want answers more quickly when that car is driving down the road and it has a five G V two X communication cameras can't see around corners, but that car communicating ahead, that ran into the stop sign, can I through vi to X. Talk to the car behind it and say, hey, something is going on there, you can't go to, you can't go to the big data center in the sky to make that happen, that is to be in near real time and that computer has to happen on the edge. So I think this is a tremendous opportunity and ironically the classic on prem guys, they own this, they own this space aside from smartphones of course, but if you look at compute on a light pole, companies like Intel have built Complete architectures to do that, putting compute into 5G base stations. Heck, I just, there was an announcement this week of google cloud in its gaming solution putting compute in a carrier edge to give lower latency to deliver a better experience. >>Yeah, so there, of course there is no one edge, it's highly fragmented, but I'm interested in your thoughts on kind of who's stack actually can play at the edge. And I've been sort of poking uh H P E about this. And the one thing that comes back consistently is Aruba, we we can take a room but not only to the, to the near edge, but to the far edge. And and that, do you see that as a competitive advantage? >>Oh gosh, yes. I mean, I would say the best acquisition That hp has made in 10 years has been aruba it's fantastic. And they also managed it in the right way. I mean, it was part of HB but it was it was managed a lot more loosely then, you know, a company that might get sucked into the board. And I think that paid off tremendously. They're giving Cisco on the edge a absolute run for their money, their first with new technologies. But it's about the solution. What I love about what a ruble looks at is it's looking at entertainment solutions inside of a stadium, um a information solution inside of an airport as opposed to just pushing the technology forward. And then when you integrate compute with with with Aruba, I think that's where the real magic happens. Most of the data on a permanent basis is actually video data. And a lot of it's for security uh for surveillance. And quite frankly, people taking videos off, they're off their smartphones and downloading video. I I just interviewed the chief network officer of T mobile and their number one bit of data is video, video uploaded, video download. But that's where the magic happens when you put that connectivity and the compute together and you can manage it in a, in an orderly and secure fashion >>while I have you, we have a ton of time here, but I I don't pick your brain about intel, the future of intel. I know you've been following it quite closely, you always have Intel's fighting a forefront war. You got there, battling A. M. D. There, battling your arm slash and video. They're they're taking on TSMC now and in foundry and, and I'll add china for the looming threat there. So what's your prognosis for for intel? >>Yeah, I liked bob the previous Ceo and I think he was doing a lot of of the right things, but I really think that customers and investors and even their ecosystem wanted somebody leading the company with a high degree of technical aptitude and Pat coming, I mean, Pat had a great job at VM or, I mean, he had a great run there and I think it is a very positive move. I've never seen the energy At Intel probably in the last 10 years that I've seen today. I actually got a chance to talk with pat. I visited pat uhh last month and and talk to him about pretty much everything and where he wanted to take the company the way you looked at technology, what was important, what's not important. But I think first off in the world of semiconductors, there are no quick fixes. Okay. Intel has a another two years Before we see what the results are. And I think 2023 for them is gonna be a huge year. But even with all this competition though, Dave they still have close to 85% market share in servers and revenue share for client computing around 90%. Okay. So and they've built out there networking business, they build out a storage business um with with obtain they have the leading Aid as provider with Mobileye. And and listen I was I was one of Intel's biggest, I was into one of Intel's biggest, I was Intel's biggest customer when I was a compact. I was their biggest competitor at AMG. So um I'm not obviously not overly pushing or there's just got to wait and see. They're doing the right things. They have the right strategy. They need to execute. One of the most important things That Intel did is extend their alliance with TSMC. So in 2023 we're going to see Intel compute units these tiles, they integrate into the larger chips called S. O. C S B. Manufactured by TSMC. Not exclusively, but we could see that. So literally we could have AMG three nanometer on TSMC CPU blocks, competing with intel chips with TSMC three nanometer CPU blocks and it's on with regard to video. I mean in video is one of these companies that just keeps going charging, charging hard and I'm actually meeting with Jensen wang this week and Arms Ceo Simon Segers to talk about this opportunity and that's a company that keeps on moving interestingly enough in video. If the arm deal does go through will be the largest chip license, see CPU licensee and have the largest CPU footprint on the planet. So here we have AMG who's CPU and Gpu and buying an F. P. G. A company called Xilinx, you have Intel, Cpus, Gpus machine learning accelerators and F. P. G. S. And then you've got arms slashing video bit with everything as well. We have three massive ecosystems. They're gonna be colliding here and I think it's gonna be great for competition. Date. Competition is great. You know, when there's not competition in CPUs and Gpus, we know what happens right. Uh, the beach just does not go on and we start to stagnate. And I did, I do feel like the industry on CPU started to stagnate when intel had no competition. So bring it on. This is gonna be great for for enterprises then customers to and then, oh, by the way, you have the custom Chip providers. WS has created no less than 15 custom semiconductors started with networking and nitro and building out an edge that surrounded the general computer. And then it moved to Inferential for inference trainee um, is about to come out for training Graviton and Gravitas to for general purpose CPU and then you've got apple. So innovation is huge and I love to always make fun of the software is eating the world. I always say yeah but has to run on something. And so I think the combination of semiconductors software and cloud is just really a magical combination. >>Real quick handicap the video arm acquisition. What what are the odds that that they will be successful? They say it's on track. You got a 2 to 13 to 1 10 to 1. >>I say 75%. Yes 25%. No China is always the has been the odd odd man out for the last three years. They scuttled the Qualcomm NXp deal. You just don't know what china is going to do. I think the EU with some conditions is going to let this fly. I think the U. S. Is absolutely going to let this fly. And even though the I. P. Will still stay over in the UK, I think the U. S. Wants to see wants to see this happen, Japan and Korea I think we'll allow this china is the odd man out. >>In a word, the future of h p. E is blank >>as a service >>patrick Moorehead. Always a pleasure. My friend. Great to see you. Thanks so much for coming back in the cube. >>Yeah, Thanks for having me on. I appreciate that. >>Everybody stay tuned for more great coverage from HP discover 21 this is day Volonte for the cube. The leader and enterprise tech coverage. We'll be right back.

>>Hello and welcome to the cubes coverage of dr khan 2021. I'm john Kerry, host of the cube agent I own L. C. Ceo and co founder chairman of Morantes cube alumni Adrian Great to see you. Thanks for coming on the cube here for dr khan coverage. Good to see you. Hey >>john nice to see. You gotta do. >>So obviously open source innovation continues. You guys are at the forefront of it. Great to see you what's new Miranda's, give us the update on what's happening. >>Well, I mean what's, what's interesting is we've had one of the best years ever last year and it's very much more continuous, you know, into this year. It's pretty fantastic. We wanted about 160 new customers. Kubernetes is definitely on a tear. We see customers doing bigger and bigger and more exciting things, which is absolutely great to say lens is getting tremendous destruction and I think we have a five fold increase in user base within a year. So it's a lot of fun Right now, customers are definitely pushing the boundaries of what benefits can do. And they want to get the cloud native infrastructure and they want to get there faster and they want to be big and exciting things. And we are so happy to be part of the right. >>You guys are investing in brand new open source solutions for customers. Give us an update on on why and why do they matter for your customer? >>Well, there are, let me unpack this a little bit and there are really two elements to this. One is wide. Open Source and what's new. What matters. So the open source is not new, but open source is being embraced more and more heavily. Bye bye companies everywhere because just a very flexible and cost efficient and highly innovative way to to use innovation and to continue software and a lot of innovation these days is happening the open source communities, which is why it's super exciting for many, many users now. What's new with us? I think there are two really terrific things that we brought the market that we see, get a lot of interest and attention from our customers and create value. One is this idea of delivering, including the infrastructure that's been in space as a service for some of the largest news cases out there. Very large enterprises. We want to have a cloud experience on prime just like they have it in public clouds. That is absolutely fantastic. And that's new and different and very, very exciting. Customs. The second thing that's new and compelling and exciting is the is lands which is this kubernetes, i. e. that has empowered in the meantime, close to 180,000 communities, developers around the world to make it much much easier to take advantage of genetics. So you can think of it as a I. D. And a D. Bugger for anybody who is using genetics on public clouds or on on private infrastructure. That is getting tremendous traction and adoption. >>The interest in kubernetes has been unbelievable. I mean in coop con we saw kubernetes almost become boring in the sense of like it's everyone's using it and there's still now it's enabling a lot more cloud native development. Why does that lens matter what is the benefit? Because that's that's a killer opportunity because kubernetes is actively being adopted. The general consensus is it's delivering the value. >>Yeah. So let me unpack this in two aspects why Wise Bennett is important, why people adopting it and then how it lands adding value on top of it for people who want to use humanity's common. It is tremendously important is because it solves some very, very fundamental problems for developers and operators when building cloud native applications. These are problems that are very essential to actually operating in production but are really unpleasant people to solve, like availability, scalability, reusability of services. So all of that with amenities comes right out of the box and developers no longer have to worry about it. And at the same time, the benefits gives you a standard where you can build apps on public clouds and then move them on prem or build them on trend with them on public clouds and anywhere in between. So it gives a kind of this universal cloud native standard that you as a developer can rely on. And that's extremely valuable for developers. We all remember from the java times when java came online, people really value this idea of white ones run anywhere and that's exactly what benefits does for you in a clown in the world. So it's extremely screaming valuable for people. Um now how does let's add value in this context is also very exciting. So what's happening when you build these applications on a minute? This is that you have many, many services which interact with each other in fairly complex and sometimes unpredictable ways and they're also very much interact with the infrastructure. So you have you can you can imagine kind of this jungle this label building of many different cloud native services working together to build your app, run your app well, how are you going to navigate that and debug that as a developer as you build and optimize your code. So what lengths does it gives you kind of like a real time poppet of pounds of console. You can imagine like you're a fighter pilot in this jet and you have all these instruments kind of coming out here and gives you like this fantastic real time situational awareness. So you can very quickly figure out what is it that you need to do? Either fixing a bug in your application or optimize the performance of the code of making more your rival fixing security issues. And it makes it extremely easy for developers to use. Right? But this tradition has been hard to use complicated, this makes it super fast, easy, have a lot of fun. >>You know, that is really the great theme about this conference this year and your point exactly is developer experience making it simpler and easier. Okay. And innovative is really hits the mark on productivity. I mean and that's really been a key part. So I think that's why I think people are so excited about kubernetes because it's not like some other technologies that had all the setup requirement and making things easier to get stood up and manage. Its huge. So congratulations. A great point, great call out there, great insight. The next question to ask you is you guys have coined the term software factory. Um, yeah, this kind of plays into this. If you have all the services, you can roll them up together with lens and those tools, it's gonna be easier, more productive. So that means it's more software, open source is the software factory to what does that term mean? And how >>it is leverage. Yeah, So here's what it means to us. And so, as you know, today, Soft is being produced by two groups working together to build software, uh, certainly the poor people are the developments, these are the people who create the core functionality. Imagine all the software should be architected and ultimately ship the code right? And maintain the code, but the developers today don't operate just by themselves. They have their psychics, they have their friends for often platform engineering and platform engineers. These are the people who are helping developers, you know, make some of the most important choices as to which platform states we should use, which services they should use, how they should think about governance. How should they think about cloud infrastructure they should use, which open source libraries they should use. How often they should be fresh those libraries and support. So this platform engineers create if you want the factory, the substrate and the automation, which allows these developers to be highly productive. And the analogy want to make is the chip design, right. If you imagine ship design today, you take advantage of a lot of software, a lot of tooling and a lot of free package libraries. You get your job done, you're not doing it by yourself. Uh just wiring transistors together or logical elements. You do it using a massive amount of automation and software, like recent polls. So that's that's what we aim to provide you to customers because what we discovered is that customers, I don't want to be in the business of buildings off the factories, They don't want to be in the business or building platform engineering teams. If they can avoid it, they just do it because they have no choice. But it's difficult for them to do. It's cumbersome, it's expensive. It's a one off. It really doesn't create any unique business value because the platform engineering for a bank is very similar to the platform engineering for, let's say, an oil gas company or the insurance company. Um So we do it for them turnkey as a service. So they can be focusing on what Madison's for that. >>That's a great inside. I love that platform engineering, enabling software developers because, you know, look at sas throwing features together. Being a feature developer is cool. And and and the old days of platform was the full stack developer. And now you have this notion of platform as a service in a way, in this kind of new way. What's different agents? You've seen these waves of innovation? Certainly an open source that we've been covering your career for over a decade uh with more Anderson and open stick and others. This idea of a platform that enables software. What's changed now about this new substrate, you mentioned what's different than the old platform model? >>Uh That's a wonderful question. Uh a couple of things are different. So the first thing that's different is the openness and uh, and that everything is based on open source frameworks as opposed to platforms that we that are highly opinionated and, and I lock in. So I think that's that's a very, very fundamental difference. If you're looking at the initial kind of platform as a service approaches, there were there were extremely opinionated and very rigid and not always open source or just a combination between open source and proprietary. So that's one very big difference. The second very big difference is the emphasis on, and it goes along with the first one, the emphasis on um, multi cloud and infrastructure independence, where a platform is not wedded to a particular stack, where it's a AWS stack or a uh, an Azure stack or the EMR stack. And, and but it's truly a layer above. That's completely open source center. >>Yeah. >>And the third thing that is different is the idea that it's not just the software, the software alone will not do the job, you need the software and the content and the support and the expertise. If you're looking at how platform engineering is done at the large company like Apple, for example, facebook, it's really always the combination of those three things. It's the automation framework, the software, It's the content, the open source libraries or any other libraries that you create. And then it's the expertise that goes all this together and it's being offered to developers to be able to take advantage of this like soft factory. So I think these are the major differences in terms of where we are today was five years ago, 10 years ago. >>Thank you for unpacking that for I think that's a great uh great captures the shift and value. This brings up my next uh question for you because you know, you take that to the next level. DeVOps is now also graduating to a whole another level. The future of devops uh and software engineering more and more around kubernetes and your tools like lens and others managing the point. What is the new role of devops? Obviously Deb see cops but devops is now changing to What's the future of devops in your opinion? >>Well, I believe that there is going to become more and more integrated where our option is going to become uh something like Zero Arts, where are you going to be fully automated And something that's being delivered entirely through software and developers will be able to focus entirely, on, on creating and shipping code. I think that's the major, that's a major change that's happening. The problem is still yet I think to be solved like 100% correctly is the challenge of the last mile. like deploying that code on on on the infrastructure and making sure that he's performing correctly to the sls and optimizing everything. I also believe that the complexity veneta is very powerful by the same time offers a lot of room for complexity. There are many knobs and dials that you can turn in these microservices based architecture. And what we're discovering now is that this complexity kind of exceeds the ability of the individual developer or even a group of developers who constantly optimize things. So I believe what we will see is a I machine learning, taking charge of optimizing a lot of parameters, operating parameters around the applications and that unemployment benefits to ensure those applications perform to the expectations of the illness. And that might mean performing to a very high standard security. Or it might mean performing to a very a low latency in certain geography. Might mean performing too a very low cost structure that you can expect and those things can change over time. Right? So this challenge of operating an application introduction Burnett is substrate is I think dramatically higher than on just additional cloud infrastructure or virtualization. Because you have so many services inter operating with each other and so many different parameters you can set for machine learning and Ai >>I love the machine learning. Ai and I'd love to just get your thoughts on because I love the Zero ops narrative Because that's day one zero ops now that you're here day to being discussed and people are also hyping up, you know, ai Ops and other things. But you know this notion of day to, okay, I'm shipping stuff in the cloud and I have to have zero ops on day 234 et cetera. Uh, what's your take on that? Because that seems to be a hot air that customers and enterprises are getting in and understanding the new wave, writing it and then going, wait a minute pushing new code that's breaking something over there I built months ago. So this is just notion of day to obstacle. But again, if you want to be zero ops, it's gonna be every day. >>Oh, I think you hit the nail on the head. I don't think there's going to be a difference between they want the zero they want and today chair, I think every day is going to be the zero. And the reason for that is because people will be shipping all the time. So your application will change all the time. So the application will always be fresh, so it will always be there zero. So zero ops has to be there all the time. Not just in the birthday. >>Great slogan! Every day is day zero, which means it's going well. I mean there's no no problems. So I gotta ask you the question was one of the big things that's coming up as well as this idea of an SRE not new to devops world, but as enterprises start to get into an SRE role where with hybrid and now edge becoming people not just industrial, um there's been a lot of activity going on a distributed basis. So you're gonna need to have this kind of notion of large scale and 00 ops, which essentially means automation, all those things you mentioned, >>not everyone can >>afford that. Um Not every company can afford to have you know hardcore devops groups to manage and their release process, all that stuff. So how are you helping customers and how do you see this problem being solved? Because this is the accelerant people want, they want the the easy button, they want the zero ops but they just they don't they can't pipeline people fast enough to do this role. >>Yeah. What you're describing is the central differentiator we bring to customers is this idea of as a service experience with guaranteed outcomes. So that's what makes us different versus the traditional enterprise infrastructure software model where people just consume software vendors and system integrate themselves and then are in charge of operations themselves and carrying the technical risks themselves. We deliver everything as a service with guaranteed outcomes through the through cloud native experience. That means guaranteed as L. A. Is predictable outcomes, continuous updates, continuous upgrades. Your on prem infrastructure or your edge infrastructure is going to look and feel and behave exactly like a public cloud experience where you're not going to have to worry about sRS or maintaining the underlying being delivered to you as a service. That's a big part, that's a central part of what makes us different in this space. >>That's great value proposition. Can you just expand give an example of a use case where you guys are doing that? Because this is something that I'm seeing a lot of people looking to go faster. You know speed is good but also it could kill right? So you can break things if you go to a. >>Yeah absolutely. I can give you several examples where we're doing this um very exciting company. So one companies booking dot com booking dot com as a massive on from infrastructure but they also massive public cloud consumer. And they decided they want to bring their own infrastructure to the cloud level of automation, cloud level Sophistication, in other words, they want to have their Aws on brand, they wanted to the old, so eccentric and we're delivering this to them with very high in the cell is exactly as a service turnkey Where there is nothing for them to system in grade or to tune and optimize and operate is being really operating 24/7 guaranteed sls and outcomes by us. Well, combination of soft film expertise that we have at massive scale and to the standards of booking dot com. This is one example, another example and this is a very large company um is the opposite side of the spectrum. You know, because they're not called Mexico super successful. Soft as a service company in the security space, growing in leaps and bounds in very high technical demands and security demands. And they want to have an on prem and cloud infrastructure to complement public clouds. Why? Because security is very important to them. Latency is very important to them. Control the customer experience is very important to them. Cost is very important to them. So for that reason they want that in a network of data centers around the globe And we provide that for them. Turnkey as a service than before seven, which enables them to focus 100% on building their own sense on their the functionality which matters to their customers and not have to worry about the underlying cloud infrastructure in their data centers. All of that gets provided to them has guaranteed about experience to their end users. So this would be the examples where we're doing a >>great service. People are looking for a great job. Adrian, Great to see you. Thank you for coming on the cube here, doc are gone 2021. Um, take a minute to put a plug in for the company. What are you guys up to? What you're looking for hiring? I'll see. You got great tracks with customers, congratulates on lens. Um give a quick update on what's going >>on. Happy happy to give it up in the company. So he, here are the highlights. It was super excited about about what we achieved last year and then what we're up to this year. So last year, what we're proud of is despite Covid, we haven't laid off a single person. We kept all the staff and we hired staff. We have gained 160 new customers, many of them, some of the world's largest and best companies and 300 of all existing customers have expanded their business with us last year, which is fantastic. We also had a very strong financial physical cash flow positive. It was a tremendous, tremendous here for us. Uh, this year is very much growth here for us and we would incredible focus on customer outcomes and customer experience. So what we are really, really digging in super hard on is to give the customers the technology and the services that enable them to get to ship software faster and easier to dramatically increase the productivity of dissolved the development efforts on any cloud infrastructure on crime and public clouds using containers and is and to do that as scale. So we're extremely focused on customer outcomes, custom experience and then the innovation is required to make that happen. So you will continue to see a lot of innovation around lens. So the last better release of lens that we brought about has now a cloud service and have a lot of feature where you can share all your cloud automation with your bodies, in, in uh, in uh, in your development team. So the lens used to be a single user product. Now it's a multi user and team based product, which is fantastic, continues to grow very quickly. And then container cloud as a service. Uh, it's a very big part that we're meeting on the infrastructure side. Are you get quite >>the open source cloud company. Adrian. Congratulations. We've been again following even on the many waves of innovation. Open stack, large scale open source software. Congratulations. >>Uh chris >>Thank you very much for coming on the cube. >>Yeah. >>Okay. Dr khan 2021 cube coverage. I'm john furrier here where the Gi Enel Ceo, co founder and chairman of Miranda's sharing his perspective on the open source innovation with their process and also key trends in the industry that is changing the game in accelerating cloud value cloud scales. Cloud native applications. Thanks for watching. Mhm.

(upbeat music) >> Well good to have you with us here as we continue the AWS startup showcase and we're joined now by the CEO of BigID, Dmitri Sirota. And Dmitri good afternoon to you? How are you doing today? >> I'm pretty good, it's Friday, it's sunny, it's warm, I'm doing well. >> Then that's a good start, yeah. Glad to have you with us here. First off, just about BigID and when you look at I would assume these accolades are, they are quite a showcase for you. Well economic forum technology pioneer. Forbes cloud 100, business insider startup the watch. I mean, you are getting a lot of attention, obviously for... >> Yep. >> And well-deserved, but when you see these kinds of recognitions coming your way- >> Yep. >> First of what does that do to inspire, motivate and fuel this great passion that you have? >> Yeah, look I think all of these recognitions help, I think affirm, I think what we aspire to be right? Provide the preeminent solution for helping organizations understand their data and in so doing, be able to address problems in privacy and protection and perspective. And I think that these recognitions are part of that as our customers, as our partners like AWS. So they're all part of that ad mixture. And I think they contribute to a sense that we're doing some pioneering work, right as they work from the world economic forum recognized. So I think it's important. I think it's healthy. It encourages kind of cooperative spirit at the company. And I think it's, you know, it's very encouraging for us to continue and build. >> So let's talk about BigID, a little bit for our viewers who might not be too familiar. You are a fairly new company, raised 200 million so far, five years of operations coming up on five years. >> Yep. >> But talk about your sweet spot in terms of the variety of services they provided in terms of protection and security. >> Yeah, sure. So we were founded with really this kind of precept that organizations need to have a better understanding of their data. I think when we got started about five years ago. Most organizations had some view of their data, maybe a few of their files, maybe their databases. What changed is the emerging privacy regulations like GDPR and CCPA later forced companies to rethink their approach to data understanding data knowledge, because part of the kind of the core consumption of privacy is that you and me and other individuals have a right to their data the data actually belongs to us. Similar to when you deposit a check in a bank. That money you deposited is yours. If you ever want to withdraw it, the bank has to give it back to you. And in a similar way, these privacy regulations require organizations to be able to give back your data or delete it or do other things. And as it happens there was no real technology to help companies do that, to help companies look across their vast data estates and pick out all the pieces of information all the detritus that could belong to Dimitri. So it could be my password, it could be my social security, it could be my click stream, it could be my IP address, my cookie. And so we developed from the ground up a brand new approach to technology that covers the data center and the cloud, and allow organizations to understand their data at a level of detail that never existed before. And still, I would argue doesn't exist today. Separate from BigID. And we describe that as our foundational data discovery in depth, right? We provide this kind of multidimensional view of your data to understand the content and the context of the information. And what that allows organizations to do is better understand the risk better meet certain regulatory requirements like GDPR and CCPA. But ultimately also get better value from their data. And so what was pioneering about us is not only that level of detail that we provided almost like your iPhone provides you four cameras to look at the world. We provide you kind of four lenses to look at your data. But then on top of that we introduced a platform that allowed you to take action on what you found. And that action could be in the realm of privacy so that you could solve for some of the privacy use cases like data rights or consent or consumer privacy preferences or data protection data security, so that you can remediate. You can do deal with data lifecycle management. You could deal with encryption, et cetera. Or ultimately what we call a data governance or data perspective, this idea of being able to get value from your data but doing so in a privacy and security preserving way. So that's kind of the conception we want to help you know, your data. And then we want to help you act on your data so that your data is both secure. It's both compliant , but ultimately you get value from your data. >> Now we get into this, helping me know my data better because you you've talked about data you know and data you don't right? >> Dimitri: Yeah. >> And you're saying there's a lot more that we don't or a company doesn't know. >> Dimitri: Yeah. >> Than it's aware of. And I find that still kind of striking in this day and age. I mean with kind of the sophistication of tools that we have and different capabilities that I think give us better insight. But I'm still kind of surprised when you're saying there's all a lot of data that companies are housing that they're not even aware of right now. >> They're not and candidly they didn't really want to be for a long, long time. I think the more you know sometimes the more you have to fix, right? So there needed to be a catalyzing event like these privacy regulations to essentially kind of unpack, to force a set of actions because the privacy regulation said, no, no, no you need to know whether you want to or not. So I think a lot of organizations for years and years outside of a couple of narrow fields like HIPAA, PCI unless there was a specific regulation, they didn't want to know too much. And as a consequence there, wasn't really technology to keep up with the explosion in data volumes and data platforms. Right? Think about like AWS didn't exist when a lot of these technologies were first built in the early 2000's. And so we had to kind of completely re-think things. And one thing I'll also kind of highlight is the need or necessity is not just driven by some of these emerging privacy regulations, but it's also driven by the shift to the cloud. Because when you have all your data on a server in a data center in New Jersey, you could feel a false sense of security because you have doors to that data center in New Jersey and you have firewalls to that data center in New Jersey. And if anybody asks you where your sensitive data you could say, it's in New Jersey! But now all of a sudden you move it into the cloud and data becomes the perimeter, right? It's kind of naked and exposed it's out there. And so I think there's a much greater need and urgency because now data is kind of in the ethos in the air. And so organizations are really kind of looking for additional ability for them to both understand contextualize and deal with some of the privacy security and data governance aspects of that data. >> So you're talking about data obviously AWS comes to mind, right? >> Dimitri: Yeah. And the relationship that you have with them it's been a couple of years in the making things are going really well for you and ultimately for your customers. What is it about this particular partnership that you have with AWS that you think has allowed you to bring that even more added value at the end of the day to your customer base? >> Look, our customers are going to AWS because its simplicity to kind of provision their applications, their services, the cost is incredibly attractive, the diversity of capabilities that AWS provides our customers. And so we have a lot of larger and midsize and even smaller organizations that are going to AWS. And it's important for us to be where our customers are. And so if our customers are using Red Sheriff, or using S creator, using dynamo or using Kinesis or using security hub. We have to be there, right? So we've kind of followed that pathway because of they're putting data in those places, part of our job is provide that insight and intelligence to our customers around those data assets, wherever they are. And so we build a set of capabilities and expertise around the broader AWS platform. So that we could argue that we can help you, whether you keep your data in S3 whether you keep it Dynamo, whether you keep it in EMR, RDS, Aurora, Athena the list goes on and on. We want to be that expert partner for you to kind of help you know your data and then tend to take action on your data. >> So the question about data security in general, obviously as you know, there are these major stories of tremendous breach that's right. >> Yep. >> Stayed afterwards, in some cases. >> Bad guys. >> Yeah, really bad guys and bad smart guys, unfortunately and persistent to say the least. How do you work with your clients in an environment like that? Where, you know, these threats are never ending, >> Yep. >> They're becoming more and more complex. And the tools that you have are certainly robust but at the end of the day, it's very difficult. If not impossible to say a 100% bulletproof, right? >> Yeah. >> It's if you are absolutely safe with us. But you still try, you give these insurances because of your sophistication that, should give people some peace of mind. Again, it's a tough battle your in. >> Yeah. So I think the first rule of fight club is that, to solve a problem, you need to know the problem, right? You can't fix what you can't find, right? So if you're unaware that there's a potential compromise in your data, potential risk in your data maybe you have passwords in a certain data store and there's no security around that. You need to know that you have passwords in a certain data store and there's no security around that. >> Because unless you know that first, there's no ability for you to solve it. So the first part of what we do that kind of know your data that K-Y-D, is we help organizations understand what data do they have that potentially is at risk, may violate a regulatory requirement like GDPR or CCPA, things of that sort. So that's kind of the first level of value because you can't solve for something you can't, you're unaware of, right? You need to be able to see it and you need to be able to understand it. And so our ability to kind of both understand your data and understand what it is, why it is, whose it is where it came from, the risk around it lets you take action on that. Now we don't stop there. We don't stop at just helping you kind of find the problem. We also help you understand if there's additional levels of exposure. Do you have access control around that data for instance. If that data is open to the world and you just put a bunch of passwords there or API keys or credentials, that's a problem. So we provide this kind of holistic view into your data and to some of the security controls. And then most importantly, through our application platform our own apps, we provide ways for you to take action on that. And that action could take many forms. It could be about remediating where you delegate to a security owner and say, hey, I want you to delete that data. Or I want you to encrypt that data. It could be something more automated where it just encrypts everything. But again, part of the value and virtue of our platform is that we both help you identify the potential risk points. And then we give you in the form of apps that sit on top of our platform, ways to take action on it, to secure it, to reduce it, to minimize the risk. >> Because these threats are ever evolving. Can you give us a little, maybe inside peek under the tent here, a bit about what you're looking at in terms of products or services down the road here. So if somebody is thinking, okay. What enhanced tools might be at my disposal in the near term or even in the longterm to try and mitigate these risks. Can you give us an idea about some things you guys are working on? >> Yeah. So the biggest thing we're working on I've already kind of hinted at this is really the kind of first in industry platform, in our category companies that look at data and by platform i mean, something like where you can introduce apps. So AWS has a platform. People can introduce additional capabilities on top of AWS. In the data discovery classification arena, that had never been the case because the tools were very, very old. So we're introducing these apps and these apps allow you to take a variety of actions. I've mentioned a few of them, there's retention. You can do encryption, you can do access control, you could do remediation, and you could do breach impact analysis. Each of these apps is kind of an atomic unit of functionality. So there's no different than on your iPhone or your Android phone. You may have an Uber app, when you click on it, all of a sudden your phone looks like an Uber application. You may have an app focused on Salesforce, you click on it, all of a sudden your phone looks like a Salesforce application. And so what we've done is we've kind of taken this kind of data discovery, classification and intelligence mechanism that kind of K-Y-D I referenced. And then we built a whole app platform. And what we're going to start announcing over the coming months, is more and more apps in the field of privacy, in the fields of data security or protection, and even the fields of data value what we call perspective and that's and we're actually coming out with an announcement shortly on this app marketplace. And there'll be BigID building apps, but you know what, there's going to be a lot of third parties building apps. So companies that do intrusion detection and integrations and all kinds of other things are also building apps on BigID. And that's an exciting part of what you're going to see coming from us in the coming weeks. >> Great. Well, thanks for the sneak peek and wait I feel like I just barely scratched the surface of it. Governance, compliance, right? Regulation, you have so many balls in the air but obviously you're juggling them quite well and we wish you continued success, job well done. Thanks, Dimitri. >> Dimitri: Thank you very much for having me. (upbeat music)

(upbeat music) >> Well good to have you with us here as we continue the AWS startup showcase and we're joined now by the CEO of BigID, Dmitri Sirota. And Dmitri good afternoon to you? How are you doing today? >> I'm pretty good, it's Friday, it's sunny, it's warm, I'm doing well. >> Then that's a good start, yeah. Glad to have you with us here. First off, just about BigID and when you look at I would assume these accolades are, they are quite a showcase for you. Well economic forum technology pioneer. Forbes cloud 100, business insider startup the watch. I mean, you are getting a lot of attention, obviously for... >> Yep. >> And well-deserved, but when you see these kinds of recognitions coming your way- >> Yep. >> First of what does that do to inspire, motivate and fuel this great passion that you have? >> Yeah, look I think all of these recognitions help, I think affirm, I think what we aspire to be right? Provide the preeminent solution for helping organizations understand their data and in so doing, be able to address problems in privacy and protection and perspective. And I think that these recognitions are part of that as our customers, as our partners like AWS. So they're all part of that ad mixture. And I think they contribute to a sense that we're doing some pioneering work, right as they work from the world economic forum recognized. So I think it's important. I think it's healthy. It encourages kind of cooperative spirit at the company. And I think it's, you know, it's very encouraging for us to continue and build. >> So let's talk about BigID, a little bit for our viewers who might not be too familiar. You are a fairly new company, raised 200 million so far, five years of operations coming up on five years. >> Yep. >> But talk about your sweet spot in terms of the variety of services they provided in terms of protection and security. >> Yeah, sure. So we were founded with really this kind of precept that organizations need to have a better understanding of their data. I think when we got started about five years ago. Most organizations had some view of their data, maybe a few of their files, maybe their databases. What changed is the emerging privacy regulations like GDPR and CCPA later forced companies to rethink their approach to data understanding data knowledge, because part of the kind of the core consumption of privacy is that you and me and other individuals have a right to their data the data actually belongs to us. Similar to when you deposit a check in a bank. That money you deposited is yours. If you ever want to withdraw it, the bank has to give it back to you. And in a similar way, these privacy regulations require organizations to be able to give back your data or delete it or do other things. And as it happens there was no real technology to help companies do that, to help companies look across their vast data estates and pick out all the pieces of information all the detritus that could belong to Dimitri. So it could be my password, it could be my social security, it could be my click stream, it could be my IP address, my cookie. And so we developed from the ground up a brand new approach to technology that covers the data center and the cloud, and allow organizations to understand their data at a level of detail that never existed before. And still, I would argue doesn't exist today. Separate from BigID. And we describe that as our foundational data discovery in depth, right? We provide this kind of multidimensional view of your data to understand the content and the context of the information. And what that allows organizations to do is better understand the risk better meet certain regulatory requirements like GDPR and CCPA. But ultimately also get better value from their data. And so what was pioneering about us is not only that level of detail that we provided almost like your iPhone provides you four cameras to look at the world. We provide you kind of four lenses to look at your data. But then on top of that we introduced a platform that allowed you to take action on what you found. And that action could be in the realm of privacy so that you could solve for some of the privacy use cases like data rights or consent or consumer privacy preferences or data protection data security, so that you can remediate. You can do deal with data lifecycle management. You could deal with encryption, et cetera. Or ultimately what we call a data governance or data perspective, this idea of being able to get value from your data but doing so in a privacy and security preserving way. So that's kind of the conception we want to help you know, your data. And then we want to help you act on your data so that your data is both secure. It's both compliant , but ultimately you get value from your data. >> Now we get into this, helping me know my data better because you you've talked about data you know and data you don't right? >> Dimitri: Yeah. >> And you're saying there's a lot more that we don't or a company doesn't know. >> Dimitri: Yeah. >> Than it's aware of. And I find that still kind of striking in this day and age. I mean with kind of the sophistication of tools that we have and different capabilities that I think give us better insight. But I'm still kind of surprised when you're saying there's all a lot of data that companies are housing that they're not even aware of right now. >> They're not and candidly they didn't really want to be for a long, long time. I think the more you know sometimes the more you have to fix, right? So there needed to be a catalyzing event like these privacy regulations to essentially kind of unpack, to force a set of actions because the privacy regulation said, no, no, no you need to know whether you want to or not. So I think a lot of organizations for years and years outside of a couple of narrow fields like HIPAA, PCI unless there was a specific regulation, they didn't want to know too much. And as a consequence there, wasn't really technology to keep up with the explosion in data volumes and data platforms. Right? Think about like AWS didn't exist when a lot of these technologies were first built in the early 2000's. And so we had to kind of completely re-think things. And one thing I'll also kind of highlight is the need or necessity is not just driven by some of these emerging privacy regulations, but it's also driven by the shift to the cloud. Because when you have all your data on a server in a data center in New Jersey, you could feel a false sense of security because you have doors to that data center in New Jersey and you have firewalls to that data center in New Jersey. And if anybody asks you where your sensitive data you could say, it's in New Jersey! But now all of a sudden you move it into the cloud and data becomes the perimeter, right? It's kind of naked and exposed it's out there. And so I think there's a much greater need and urgency because now data is kind of in the ethos in the air. And so organizations are really kind of looking for additional ability for them to both understand contextualize and deal with some of the privacy security and data governance aspects of that data. >> So you're talking about data obviously AWS comes to mind, right? >> Dimitri: Yeah. And the relationship that you have with them it's been a couple of years in the making things are going really well for you and ultimately for your customers. What is it about this particular partnership that you have with AWS that you think has allowed you to bring that even more added value at the end of the day to your customer base? >> Look, our customers are going to AWS because its simplicity to kind of provision their applications, their services, the cost is incredibly attractive, the diversity of capabilities that AWS provides our customers. And so we have a lot of larger and midsize and even smaller organizations that are going to AWS. And it's important for us to be where our customers are. And so if our customers are using Red Sheriff, or using S creator, using dynamo or using Kinesis or using security hub. We have to be there, right? So we've kind of followed that pathway because of they're putting data in those places, part of our job is provide that insight and intelligence to our customers around those data assets, wherever they are. And so we build a set of capabilities and expertise around the broader AWS platform. So that we could argue that we can help you, whether you keep your data in S3 whether you keep it Dynamo, whether you keep it in EMR, RDS, Aurora, Athena the list goes on and on. We want to be that expert partner for you to kind of help you know your data and then tend to take action on your data. >> So the question about data security in general, obviously as you know, there are these major stories of tremendous breach that's right. >> Yep. >> Stayed afterwards, in some cases. >> Bad guys. >> Yeah, really bad guys and bad smart guys, unfortunately and persistent to say the least. How do you work with your clients in an environment like that? Where, you know, these threats are never ending, >> Yep. >> They're becoming more and more complex. And the tools that you have are certainly robust but at the end of the day, it's very difficult. If not impossible to say a 100% bulletproof, right? >> Yeah. >> It's if you are absolutely safe with us. But you still try, you give these insurances because of your sophistication that, should give people some peace of mind. Again, it's a tough battle your in. >> Yeah. So I think the first rule of fight club is that, to solve a problem, you need to know the problem, right? You can't fix what you can't find, right? So if you're unaware that there's a potential compromise in your data, potential risk in your data maybe you have passwords in a certain data store and there's no security around that. You need to know that you have passwords in a certain data store and there's no security around that. >> Because unless you know that first, there's no ability for you to solve it. So the first part of what we do that kind of know your data that K-Y-D, is we help organizations understand what data do they have that potentially is at risk, may violate a regulatory requirement like GDPR or CCPA, things of that sort. So that's kind of the first level of value because you can't solve for something you can't, you're unaware of, right? You need to be able to see it and you need to be able to understand it. And so our ability to kind of both understand your data and understand what it is, why it is, whose it is where it came from, the risk around it lets you take action on that. Now we don't stop there. We don't stop at just helping you kind of find the problem. We also help you understand if there's additional levels of exposure. Do you have access control around that data for instance. If that data is open to the world and you just put a bunch of passwords there or API keys or credentials, that's a problem. So we provide this kind of holistic view into your data and to some of the security controls. And then most importantly, through our application platform our own apps, we provide ways for you to take action on that. And that action could take many forms. It could be about remediating where you delegate to a security owner and say, hey, I want you to delete that data. Or I want you to encrypt that data. It could be something more automated where it just encrypts everything. But again, part of the value and virtue of our platform is that we both help you identify the potential risk points. And then we give you in the form of apps that sit on top of our platform, ways to take action on it, to secure it, to reduce it, to minimize the risk. >> Because these threats are ever evolving. Can you give us a little, maybe inside peek under the tent here, a bit about what you're looking at in terms of products or services down the road here. So if somebody is thinking, okay. What enhanced tools might be at my disposal in the near term or even in the longterm to try and mitigate these risks. Can you give us an idea about some things you guys are working on? >> Yeah. So the biggest thing we're working on I've already kind of hinted at this is really the kind of first in industry platform, in our category companies that look at data and by platform i mean, something like where you can introduce apps. So AWS has a platform. People can introduce additional capabilities on top of AWS. In the data discovery classification arena, that had never been the case because the tools were very, very old. So we're introducing these apps and these apps allow you to take a variety of actions. I've mentioned a few of them, there's retention. You can do encryption, you can do access control, you could do remediation, and you could do breach impact analysis. Each of these apps is kind of an atomic unit of functionality. So there's no different than on your iPhone or your Android phone. You may have an Uber app, when you click on it, all of a sudden your phone looks like an Uber application. You may have an app focused on Salesforce, you click on it, all of a sudden your phone looks like a Salesforce application. And so what we've done is we've kind of taken this kind of data discovery, classification and intelligence mechanism that kind of K-Y-D I referenced. And then we built a whole app platform. And what we're going to start announcing over the coming months, is more and more apps in the field of privacy, in the fields of data security or protection, and even the fields of data value what we call perspective and that's and we're actually coming out with an announcement shortly on this app marketplace. And there'll be BigID building apps, but you know what, there's going to be a lot of third parties building apps. So companies that do intrusion detection and integrations and all kinds of other things are also building apps on BigID. And that's an exciting part of what you're going to see coming from us in the coming weeks. >> Great. Well, thanks for the sneak peek and wait I feel like I just barely scratched the surface of it. Governance, compliance, right? Regulation, you have so many balls in the air but obviously you're juggling them quite well and we wish you continued success, job well done. Thanks, Dimitri. >> Dimitri: Thank you very much for having me. (upbeat music)

>>Welcome to this IBM Watson health client conversation here. We're probing the dynamics of the relationship between IBM and its clients. And we're looking back, we're going to explore the present. We're going to discuss the future state of healthcare. My name is Dave Volante from the Cuban with me are Robert Stell horn. Who's associate director, H E O R at sukha, otherwise known as pharmaceuticals, America and Rena Felton. Who's with of course, IBM Watson health. Welcome folks. Great to have you. Hi, so like strong relationships, as we know, they're the foundation of any partnership. And of course over the past year, we've had to rely on both personal and professional relationships to get us through some of the most challenging times, if not the most challenging times of our lives. So let me start with you, Robert, how has the partnership with IBM helped you in 2020? >>I think it was just a continuation of the excellent relationship we have with Rena and IBM. Um, starting in March, we had really a shift to an all remote, uh, workplace environment. And I think that constant communication with Rina and IBM helped that situation because she kept us up to date with, uh, additional products and offerings. And basically we came up with some additional solutions towards the end of the year. So we're gonna watch >>Pick it up from here. Let's go, let's go a little bit deeper and maybe you can talk about some of the things that you've done with Robert and his team and, and maybe some of the accomplishments that you're most proud of in 2020. >>No, absolutely. And I have to kind of echo what you first said about the foundation and our partnerships being the foundation, um, of our past present and future. So I do want to take the opportunity to thank Rob again for joining us today. It is, um, I know, you know, with his kids home and remote learning, um, it's a lot, uh, to, to ask in addition to, you know, your day to day work. So, so thank you, Rob. Um, I guess the question that I have for you is what would be the greatest accomplishment, um, that Watseka and IBM Watson had in 2020? >>I would say it was the addition of the linked claims EMR data, the LDCD product that we were able to license in-house, uh, thanks to your attention and to show the advantages and the strengths of that data. We are able to license that in to our, uh, set up assets we have internally. And what that's gonna allow us to do is really find out more information about the patients. Uh, we're existing users of the Mark IBM, uh, market scan data. Um, this is going to allow us to tie into those same patients and find out more about them. Um, in particular, uh, a lot of our products are in the mental health space and a lot about standing questions we have are why are the patients getting different products? And with the notes are available in that link data. We're going to now be able to tap into more information about what is happening with the patient. >>Okay. Can I ask a question on that? Um, if you guys don't mind, I mean, you know, when you, when you hear about, you know, uh, EMR, uh, in the early days, it was a lot about meaningful use and getting paid. It sounds like you guys are taking it much deeper and as a, as a, you know, as an individual, right, you're, you're really happy to hear that this information is now going to be used to really improve, uh, healthcare is, do I have that right? Is that, you know, kind of the nature of where you guys are headed? >>Well, I think ultimately it's the, the, the, the main goal is to help the patients and provide the products that can really, um, help them in their daily lives. So, um, really with this data, now, we're going to be able to tap into more of the why, um, exist in claims data. We cannot really get that information, why VC information, about what diagnoses they incurred during their treatment history. And we also can see, uh, different prescriptions that are given to them, but now we're going to be able to tie that together and get more understanding to really see more focused treatment pattern for them. >>So, Reno, w w you sit down with Rob, do you have like a, sort of a planning session for 2021? Why don't you sort of bring us up to, uh, to what your thinking is there and how you guys are working together this year? >>Yeah, no, absolutely. Um, actually, before we get to that, I wanted to kind of add onto what Rob was saying as well. It's interesting given, you know, the pandemic in 2020 and what the LCD data is going to do, um, to really be able to look back. And as Rob mentioned, looking specifically at mental health, the ability to look back and start looking at the patients and what it's really done to our community and what it's really done to our country, um, and looking at patients, you know, looking back at, at sort of their, their patient journey and where we are today. Um, but Rob and I talk all the time, we talk all the time, we probably talk three or four times a day sometimes. So I would say, um, we, we text, uh, we do talk and have a lot of our strategic, um, sessions, uh, our outlook for 2021 and what the data strategy is for Otsuka. Um, in addition, additional data assets to acquire from IBM, as well as how can we sort of leverage brander IBM, um, assets like our red hat, our OpenShift, our cloud-based solutions. So, you know, Rob and I are constantly talking and we are, um, looking for new ways to bring in new solutions into Otsuka. Um, and you know, yeah, we, we, we talk a lot. What do you think, Rob? >>I think we have an excellent partnership. Uh, basically, um, I think their relationship there is excellent. Um, we have excellent communication and, you know, I find when there's situations where I may be a bind Reno's is able to help out instantly. Um, so it's, it's really a two way street and it's an excellent partnership. >>I wonder if I could double click on that. I mean, relative to maybe some of your, I mean, I'm sure you have lots of relationships with lots of different companies, but, but what makes it excellent specifically with regard to IBM? Is there, is there anything unique Rob, that stands out to you? >>It would be the follow-up, um, really, it's not just about, uh, delivering the data and say, okay, here you have your, your product work with it in basically the, the, the vendor disappears, it's the constant followup to make sure that it's being used in any way they can help and provide more information to really extract the full value out of it. >>So I'm gonna forget to ask you guys, maybe each of you, you know, both personally and professionally, I feel like, you know, 20, 20 never ended it just sort of blended in, uh, and, and, but some things have changed. We all talk about, geez, what's going to be permanent. How have you each been affected? Um, how has it helped you position for, for what's coming in in the years ahead, maybe Reena, you could start and then pick it up with, with Rob. >>Oh man. Um, you know, 2020 was definitely challenging and I think it was really challenging given the circumstances and in my position where I'm very much used to meeting with our customers and having lunch and really just kind of walking down the hallways and bumping into familiar faces and really seeing, you know, how we can provide value with our solutions. And so, you know, that was all stripped in 2020. Uh, so it's been, it's been quite challenging. I will say, working with Rob, working with some of my other customers, um, I've had, uh, I've had to learn the resilience and to be a little bit more relentless with phone calls and follow ups and, and being more agile in my communications with the customers and what their needs are, and be flexible with calendars because there's again, remote learning and, and, um, and the like, so I think, you know, positioned for 2021 really well. Um, I am excited to hopefully get back out there and start visiting our customers. But if not, I certainly learned a lot and just, um, the follow-up and again, the relentless phone calls and calling and checking up on our customers, even if it's just to say, hi, see how everyone's doing a mental check sometimes. So I think that's, that's become, um, you know, what 2020 was, and, and hopefully, you know, what, 2021 will be better and, uh, kind of continue on that, that relentless path. >>What do you think, Rob? Hi, how are you doing? >>I would echo a lot of Rina's thoughts and the fact of, yeah, definitely miss the in-person interaction. In fact, I will say that I remember the last time I was physically in the office that Scott, it was to meet with Rina. So I distinctively remember that they remember the date was March, I believe, March 9th. So it just shows how this year as has been sort of a blur, but at the same time, you remember certain milestones. And I think it's because of that relationship, um, we've developed with IBM that I can remember those distinctive milestones and events that took place. >>So Rob, I probably should have asked you upfront, maybe tell us a little bit about Alaska, uh, maybe, maybe give us the sort of quick soundbite on where you guys are mostly focused. Sure. >>Oh, it's guys, uh, a Japanese pharmaceutical company. The focus is in mental health and nephrology, really the two main business areas. Um, my role at guys to do the internal research and data analytics within the health economics and outcomes research group. Um, currently we are transitioned to a, uh, name, which is global value and real world evidence. Um, fact that transition is already happened. Um, so we're going to have more of a global presence going forward. Um, but my role is really to, uh, do the internal research across all the brands within the company. >>So, so Rena, I wonder this, thank you for that, Robert. I wonder if you could think, thinking about what you know about Scott and your relationship with Robin, your knowledge of, of the industry. Uh, there's so much that IBM can bring to the table. Rob was talking about data earlier, talking about EMR, you were talking about, you know, red hat and cloud and this big portfolio you have. So I wonder if you could sort of start a conversation for our audience just around how you guys see all those assets that you have and all the knowledge, all that data. How do you see the partnership evolving in the future to affect, uh, the industry and the, in the future of healthcare? >>Well, I would love to see, um, the entire, uh, uh, platform, um, shift to, to the IBM cloud, um, and certainly, you know, leverage the cloud pack and analytics that, that we have to offer, um, baby steps most definitely. Um, but I do think that there is, uh, the opportunity to really move, um, and transform the business into something a lot more than, than what it is. >>Rob has the pandemic effected sort of how you think about, um, you know, remote services and cloud services and the, like, were you already on the path headed there? Did accelerate things, have you, you know, have you not had time because things have been so busy or maybe you could comment? >>Yeah, I think it's really a combination. And so I think you hit on a, a fair point there, just the time, uh, aspect. Um, it's definitely been a challenge and your, um, I have two children and remote learning has definitely been a challenge from that perspective. So time has definitely been, uh, on the short side. Um, I do see that there are going to in the future be more and more users of the data. So I think that shift to a potential cloud environment is where things are headed. >>So we, I have a bunch more questions, but I want to step back for a second and see if there's anything that you'd like to ask Rob before I go onto my next section. Okay. So I wonder if you could think about, um, maybe both of you, the, the, when you think back on, on 2020 and all the, you know, what's transpired, what, what transitions did you guys have to make? Uh, maybe as a team together IBM and Alaska. Um, and, and, and what do you see as sort of permanent or semi-permanent is work from home? We're gonna going to continue at a higher rate, uh, are there new practice? I mean, I know just today I made an online appointment it's for a remote visit with my doctor, which never could have happened before the pandemic. Right. But are there things specific to your business and your relationship that you see as a transition that could be permanent or semi-permanent? >>Well, I, I think it's there, there's definitely a shift that's happened that will is here to stay, but I don't know if it's full, it's going to be a combination in the future. I think that in-person interactions, especially what Rena mentioned about having that face-to-face interaction is still going to be one things are in the right place and safe they're going to happen again. But I think the ability to show that work can happen in a virtual or a full remote workplace, that's going to just allow that to continue and really give the flex of people. The flexibility I know for myself, flexibility is key. Like I mentioned, with two small children, um, that, that, that becomes such a valuable addition to your work, your life and your work life in general, that I think that's here to stay. >>Okay. Um, so let me ask you this, uh, w one of the themes of this event is relentless re-invention. So what I'm hearing from you Rob, is that it kind of a hybrid model going forward, if you will, uh, maybe the option to work from home, but that face to face interaction, especially when you're creating things like you are in the pharmaceutical business and the deep R and D that collaborative aspect, you know, you, it's harder when you're, when, when, when you're remote. Um, but maybe you could talk about, you know, some of those key areas that you're, you're going to be focused on in 2021 and, and really where you would look for IBM to help. >>I think in 2021, the team I'm part of it, part of is, is growing. So I think there's going to be additional demand for internal research, uh, uh, capabilities for analysis done within the company. So I think I'm going to be looking to Rena to, uh, see what new data offerings are available and all what new products are going to be available. But beyond that, um, I think it's the potential that, you know, there's so much, uh, projects, um, that are going to be coming to the table. We may need to outsource some of that projects and IBM could be potentially be a partner there to do some of the analysis on to help out there. >>Anything you'd add. >>Uh, no, I think that, that sounds good. >>How would you grade IBM and your relationship with IBM Rob? >>Well, I have to be nice to Rina cause she's been very nice to me. I would say an a, an a plus >>My kids, I got kids in college. Several, they get A's, I'm happy. Oh, that's good. You know, you should be proud. So, congratulations. Um, anything else Reno, you give you, I'll give you a last word here before we wrap, >>You know, 2020 was, was a challenging. And, you know, we talked a little bit about, you know, what time in 2020, you know, Rob and I have always had a really good relationship. I think 2020, we got closer, um, with just both professionally and really diving in to key business challenges that they have, and really working with him to understand what the customer needs are and how we can help, not only from, you know, an HR perspective, but also how can we help Otsuka, um, as a company in, in totality. So, you know, we've been able to do that, but personally, I would say that I really appreciated the relationship. I mean, we can go from talking about work to talking about children, to talking about family, um, all in the same five minute conversation or 10 minute conversation, sometimes our conversation. So, you know, thank you, Rob 2020 was definitely super challenging. >>I know for you on so many levels. Um, but I have to say you've been really great at just showing up every time picked up the phone, asked questions. If I needed something I can call you, I knew you were going to pick up, I had an offering and be like, do you have 10 minutes? Can I share this with you? And you would pick up the phone, no problem, and entertain a call or set up a call with all your internal colleagues. And I, I appreciate that so much. And, you know, I appreciate our relationship. I appreciate the business and I, I do hope that we can continue on in 2021, we will continue on in 2021. Uh, but, um, but yeah, I thank you so much. >>Rain has been extremely helpful. I don't want to thank you for all the help. Um, just to add to that one point there, you know, we have, uh, also another product, which I forgot to mention that we licensed in from IBM, it's the treatment pathways, um, tool, which is an online tool. Um, and we have users throughout the globe. So there's been times where I've needed a new user added very quickly for someone in the home office in Japan. And Rena has been extremely helpful in getting things done quickly and very proactively. >>Well, guys, it's really clear that the depth of your relationship I'm interested that you actually got closer in 2020. Uh, the fact that you communicate, you know, several times a day is I think Testament to that relationship. Uh, I'm really pleased to hear what you're doing and the potential with the EMR data for patient outcomes. Uh, as I say in the early days, I used to hear all about how well you have to do that to get paid. And it's really great to see a partnership that's, that's really focused on, on, on patient health and, and changing our lives. So, and mental health is such an important area that for so many years was so misunderstood and the, and the data that we now have, and of course, IBM's heritage and data is key. Uh, the relationship and the follow-up and also the flexibility is, is something I think we all learned in 2020, we have to, we've kind of redefined, you know, resilience in our organizations and, uh, glad to see you guys are growing. Congratulations on the relationship. And thanks so much for spending some time with me. >>Thank you. Thank you, Dave. Thank you, Raina >>For watching this client conversation with IBM Watson health.

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Yeah, welcome back to the cubes. Ongoing coverage of AWS reinvent virtual Cuba's Gone Virtual along with most events these days are all events and continues to bring our digital coverage of reinvent With me is Rahul Pathak, who is the vice president of analytics at AWS A Ro. It's great to see you again. Welcome. And thanks for joining the program. >>They have Great co two and always a pleasure. Thanks for having me on. >>You're very welcome. Before we get into your leadership discussion, I want to talk about some of the things that AWS has announced. Uh, in the early parts of reinvent, I want to start with a glue elastic views. Very notable announcement allowing people to, you know, essentially share data across different data stores. Maybe tell us a little bit more about glue. Elastic view is kind of where the name came from and what the implication is, >>Uh, sure. So, yeah, we're really excited about blue elastic views and, you know, as you mentioned, the idea is to make it easy for customers to combine and use data from a variety of different sources and pull them together into one or many targets. And the reason for it is that you know we're really seeing customers adopt what we're calling a lake house architectural, which is, uh, at its core Data Lake for making sense of data and integrating it across different silos, uh, typically integrated with the data warehouse, and not just that, but also a range of other purpose. Both stores like Aurora, Relation of Workloads or dynamodb for non relational ones. And while customers typically get a lot of benefit from using purpose built stores because you get the best possible functionality, performance and scale forgiven use case, you often want to combine data across them to get a holistic view of what's happening in your business or with your customers. And before glue elastic views, customers would have to either use E. T. L or data integration software, or they have to write custom code that could be complex to manage, and I could be are prone and tough to change. And so, with elastic views, you can now use sequel to define a view across multiple data sources pick one or many targets. And then the system will actually monitor the sources for changes and propagate them into the targets in near real time. And it manages the anti pipeline and can notify operators if if anything, changes. And so the you know the components of the name are pretty straightforward. Blues are survivalists E T Elling data integration service on blue elastic views about our about data integration their views because you could define these virtual tables using sequel and then elastic because it's several lists and will scale up and down to deal with the propagation of changes. So we're really excited about it, and customers are as well. >>Okay, great. So my understanding is I'm gonna be able to take what's called what the parlance of materialized views, which in my laypersons terms assumes I'm gonna run a query on the database and take that subset. And then I'm gonna be ableto thio. Copy that and move it to another data store. And then you're gonna automatically keep track of the changes and keep everything up to date. Is that right? >>Yes. That's exactly right. So you can imagine. So you had a product catalog for example, that's being updated in dynamodb, and you can create a view that will move that to Amazon Elasticsearch service. You could search through a current version of your catalog, and we will monitor your dynamodb tables for any changes and make sure those air all propagated in the real time. And all of that is is taken care of for our customers as soon as they defined the view on. But they don't be just kept in sync a za long as the views in effect. >>Let's see, this is being really valuable for a person who's building Looks like I like to think in terms of data services or data products that are gonna help me, you know, monetize my business. Maybe, you know, maybe it's a simple as a dashboard, but maybe it's actually a product. You know, it might be some content that I want to develop, and I've got transaction systems. I've got unstructured data, may be in a no sequel database, and I wanna actually combine those build new products, and I want to do that quickly. So So take me through what I would have to do. You you sort of alluded to it with, you know, a lot of e t l and but take me through in a little bit more detail how I would do that, you know, before this innovation. And maybe you could give us a sense as to what the possibilities are with glue. Elastic views? >>Sure. So, you know, before we announced elastic views, a customer would typically have toe think about using a T l software, so they'd have to write a neat L pipeline that would extract data periodically from a range of sources. They then have to write transformation code that would do things like matchup types. Make sure you didn't have any invalid values, and then you would combine it on periodically, Write that into a target. And so once you've got that pipeline set up, you've got to monitor it. If you see an unusual spike in data volume, you might have to add more. Resource is to the pipeline to make a complete on time. And then, if anything changed in either the source of the destination that prevented that data from flowing in the way you would expect it, you'd have toe manually, figure that out and have data, quality checks and all of that in place to make sure everything kept working but with elastic views just gets much simpler. So instead of having to write custom transformation code, you right view using sequel and um, sequel is, uh, you know, widely popular with data analysts and folks that work with data, as you well know. And so you can define that view and sequel. The view will look across multiple sources, and then you pick your destination and then glue. Elastic views essentially monitors both the source for changes as well as the source and the destination for any any issues like, for example, did the schema changed. The shape of the data change is something briefly unavailable, and it can monitor. All of that can handle any errors, but it can recover from automatically. Or if it can't say someone dropped an important table in the source. That was part of your view. You can actually get alerted and notified to take some action to prevent bad data from getting through your system or to prevent your pipeline from breaking without your knowledge and then the final pieces, the elasticity of it. It will automatically deal with adding more resource is if, for example, say you had a spiky day, Um, in the markets, maybe you're building a financial services application and you needed to add more resource is to process those changes into your targets more quickly. The system would handle that for you. And then, if you're monetizing data services on the back end, you've got a range of options for folks subscribing to those targets. So we've got capabilities like our, uh, Amazon data exchange, where people can exchange and monetize data set. So it allows this and to end flow in a much more straightforward way. It was possible before >>awesome. So a lot of automation, especially if something goes wrong. So something goes wrong. You can automatically recover. And if for whatever reason, you can't what happens? You quite ask the system and and let the operator No. Hey, there's an issue. You gotta go fix it. How does that work? >>Yes, exactly. Right. So if we can recover, say, for example, you can you know that for a short period of time, you can't read the target database. The system will keep trying until it can get through. But say someone dropped a column from your source. That was a key part of your ultimate view and destination. You just can't proceed at that point. So the pipeline stops and then we notify using a PS or an SMS alert eso that programmatic action can be taken. So this effectively provides a really great way to enforce the integrity of data that's going between the sources and the targets. >>All right, make it kindergarten proof of it. So let's talk about another innovation. You guys announced quicksight que, uh, kind of speaking to the machine in my natural language, but but give us some more detail there. What is quicksight Q and and how doe I interact with it. What What kind of questions can I ask it >>so quick? Like you is essentially a deep, learning based semantic model of your data that allows you to ask natural language questions in your dashboard so you'll get a search bar in your quick side dashboard and quick site is our service B I service. That makes it really easy to provide rich dashboards. Whoever needs them in the organization on what Q does is it's automatically developing relationships between the entities in your data, and it's able to actually reason about the questions you ask. So unlike earlier natural language systems, where you have to pre define your models, you have to pre define all the calculations that you might ask the system to do on your behalf. Q can actually figure it out. So you can say Show me the top five categories for sales in California and it'll look in your data and figure out what that is and will prevent. It will present you with how it parse that question, and there will, in line in seconds, pop up a dashboard of what you asked and actually automatically try and take a chart or visualization for that data. That makes sense, and you could then start to refine it further and say, How does this compare to what happened in New York? And we'll be able to figure out that you're tryingto overlay those two data sets and it'll add them. And unlike other systems, it doesn't need to have all of those things pre defined. It's able to reason about it because it's building a model of what your data means on the flight and we pre trained it across a variety of different domains So you can ask a question about sales or HR or any of that on another great part accused that when it presents to you what it's parsed, you're actually able toe correct it if it needs it and provide feedback to the system. So, for example, if it got something slightly off you could actually select from a drop down and then it will remember your selection for the next time on it will get better as you use it. >>I saw a demo on in Swamis Keynote on December 8. That was basically you were able to ask Quick psych you the same question, but in different ways, you know, like compare California in New York or and then the data comes up or give me the top, you know, five. And then the California, New York, the same exact data. So so is that how I kind of can can check and see if the answer that I'm getting back is correct is ask different questions. I don't have to know. The schema is what you're saying. I have to have knowledge of that is the user I can. I can triangulate from different angles and then look and see if that's correct. Is that is that how you verify or there are other ways? >>Eso That's one way to verify. You could definitely ask the same question a couple of different ways and ensure you're seeing the same results. I think the third option would be toe, uh, you know, potentially click and drill and filter down into that data through the dash one on, then the you know, the other step would be at data ingestion Time. Typically, data pipelines will have some quality controls, but when you're interacting with Q, I think the ability to ask the question multiple ways and make sure that you're getting the same result is a perfectly reasonable way to validate. >>You know what I like about that answer that you just gave, and I wonder if I could get your opinion on this because you're you've been in this business for a while? You work with a lot of customers is if you think about our operational systems, you know things like sales or E r. P systems. We've contextualized them. In other words, the business lines have inject context into the system. I mean, they kind of own it, if you will. They own the data when I put in quotes, but they do. They feel like they're responsible for it. There's not this constant argument because it's their data. It seems to me that if you look back in the last 10 years, ah, lot of the the data architecture has been sort of generis ized. In other words, the experts. Whether it's the data engineer, the quality engineer, they don't really have the business context. But the example that you just gave it the drill down to verify that the answer is correct. It seems to me, just in listening again to Swamis Keynote the other day is that you're really trying to put data in the hands of business users who have the context on the domain knowledge. And that seems to me to be a change in mindset that we're gonna see evolve over the next decade. I wonder if you could give me your thoughts on that change in the data architecture data mindset. >>David, I think you're absolutely right. I mean, we see this across all the customers that we speak with there's there's an increasing desire to get data broadly distributed into the hands of the organization in a well governed and controlled way. But customers want to give data to the folks that know what it means and know how they can take action on it to do something for the business, whether that's finding a new opportunity or looking for efficiencies. And I think, you know, we're seeing that increasingly, especially given the unpredictability that we've all gone through in 2020 customers are realizing that they need to get a lot more agile, and they need to get a lot more data about their business, their customers, because you've got to find ways to adapt quickly. And you know, that's not gonna change anytime in the future. >>And I've said many times in the The Cube, you know, there are industry. The technology industry used to be all about the products, and in the last decade it was really platforms, whether it's SAS platforms or AWS cloud platforms, and it seems like innovation in the coming years, in many respects is coming is gonna come from the ecosystem and the ability toe share data we've We've had some examples today and then But you hit on. You know, one of the key challenges, of course, is security and governance. And can you automate that if you will and protect? You know the users from doing things that you know, whether it's data access of corporate edicts for governance and compliance. How are you handling that challenge? >>That's a great question, and it's something that really emphasized in my leadership session. But the you know, the notion of what customers are doing and what we're seeing is that there's, uh, the Lake House architectural concept. So you've got a day late. Purpose build stores and customers are looking for easy data movement across those. And so we have things like blue elastic views or some of the other blue features we announced. But they're also looking for unified governance, and that's why we built it ws late formation. And the idea here is that it can quickly discover and catalog customer data assets and then allows customers to define granular access policies centrally around that data. And once you have defined that, it then sets customers free to give broader access to the data because they put the guardrails in place. They put the protections in place. So you know you can tag columns as being private so nobody can see them on gun were announced. We announced a couple of new capabilities where you can provide row based control. So only a certain set of users can see certain rose in the data, whereas a different set of users might only be able to see, you know, a different step. And so, by creating this fine grained but unified governance model, this actually sets customers free to give broader access to the data because they know that they're policies and compliance requirements are being met on it gets them out of the way of the analyst. For someone who can actually use the data to drive some value for the business, >>right? They could really focus on driving value. And I always talk about monetization. However monetization could be, you know, a generic term, for it could be saving lives, admission of the business or the or the organization I meant to ask you about acute customers in bed. Uh, looks like you into their own APs. >>Yes, absolutely so one of quick sites key strengths is its embed ability. And on then it's also serverless, so you could embed it at a really massive scale. And so we see customers, for example, like blackboard that's embedding quick side dashboards into information. It's providing the thousands of educators to provide data on the effectiveness of online learning. For example, on you could embed Q into that capability. So it's a really cool way to give a broad set of people the ability to ask questions of data without requiring them to be fluent in things like Sequel. >>If I ask you a question, we've talked a little bit about data movement. I think last year reinvent you guys announced our A three. I think it made general availability this year. And remember Andy speaking about it, talking about you know, the importance of having big enough pipes when you're moving, you know, data around. Of course you do. Doing tearing. You also announced Aqua Advanced Query accelerator, which kind of reduces bringing the computer. The data, I guess, is how I would think about that reducing that movement. But then we're talking about, you know, glue, elastic views you're copying and moving data. How are you ensuring you know, maintaining that that maximum performance for your customers. I mean, I know it's an architectural question, but as an analytics professional, you have toe be comfortable that that infrastructure is there. So how does what's A. W s general philosophy in that regard? >>So there's a few ways that we think about this, and you're absolutely right. I think there's data volumes were going up, and we're seeing customers going from terabytes, two petabytes and even people heading into the exabyte range. Uh, there's really a need to deliver performance at scale. And you know, the reality of customer architectures is that customers will use purpose built systems for different best in class use cases. And, you know, if you're trying to do a one size fits all thing, you're inevitably going to end up compromising somewhere. And so the reality is, is that customers will have more data. We're gonna want to get it to more people on. They're gonna want their analytics to be fast and cost effective. And so we look at strategies to enable all of this. So, for example, glue elastic views. It's about moving data, but it's about moving data efficiently. So What we do is we allow customers to define a view that represents the subset of their data they care about, and then we only look to move changes as efficiently as possible. So you're reducing the amount of data that needs to get moved and making sure it's focused on the essential. Similarly, with Aqua, what we've done, as you mentioned, is we've taken the compute down to the storage layer, and we're using our nitro chips to help with things like compression and encryption. And then we have F. P. J s in line to allow filtering an aggregation operation. So again, you're tryingto quickly and effectively get through as much data as you can so that you're only sending back what's relevant to the query that's being processed. And that again leads to more performance. If you can avoid reading a bite, you're going to speed up your queries. And that Awkward is trying to do. It's trying to push those operations down so that you're really reducing data as close to its origin as possible on focusing on what's essential. And that's what we're applying across our analytics portfolio. I would say one other piece we're focused on with performance is really about innovating across the stack. So you mentioned network performance. You know, we've got 100 gigabits per second throughout now, with the next 10 instances and then with things like Grab it on to your able to drive better price performance for customers, for general purpose workloads. So it's really innovating at all layers. >>It's amazing to watch it. I mean, you guys, it's a It's an incredible engineering challenge as you built this hyper distributed system. That's now, of course, going to the edge. I wanna come back to something you mentioned on do wanna hit on your leadership session as well. But you mentioned the one size fits all, uh, system. And I've asked Andy Jassy about this. I've had a discussion with many folks that because you're full and and of course, you mentioned the challenges you're gonna have to make tradeoffs if it's one size fits all. The flip side of that is okay. It's simple is you know, 11 of the Swiss Army knife of database, for example. But your philosophy is Amazon is you wanna have fine grained access and to the primitives in case the market changes you, you wanna be able to move quickly. So that puts more pressure on you to then simplify. You're not gonna build this big hairball abstraction layer. That's not what he gonna dio. Uh, you know, I think about, you know, layers and layers of paint. I live in a very old house. Eso your That's not your approach. So it puts greater pressure on on you to constantly listen to your customers, and and they're always saying, Hey, I want to simplify, simplify, simplify. We certainly again heard that in swamis presentation the other day, all about, you know, minimizing complexity. So that really is your trade office. It puts pressure on Amazon Engineering to continue to raise the bar on simplification. Isn't Is that a fair statement? >>Yeah, I think so. I mean, you know, I think any time we can do work, so our customers don't have to. I think that's a win for both of us. Um, you know, because I think we're delivering more value, and it makes it easier for our customers to get value from their data way. Absolutely believe in using the right tool for the right job. And you know you talked about an old house. You're not gonna build or renovate a house of the Swiss Army knife. It's just the wrong tool. It might work for small projects, but you're going to need something more specialized. The handle things that matter. It's and that is, uh, that's really what we see with that, you know, with that set of capabilities. So we want to provide customers with the best of both worlds. We want to give them purpose built tools so they don't have to compromise on performance or scale of functionality. And then we want to make it easy to use these together. Whether it's about data movement or things like Federated Queries, you can reach into each of them and through a single query and through a unified governance model. So it's all about stitching those together. >>Yeah, so far you've been on the right side of history. I think it serves you well on your customers. Well, I wanna come back to your leadership discussion, your your leadership session. What else could you tell us about? You know, what you covered there? >>So we we've actually had a bunch of innovations on the analytics tax. So some of the highlights are in m r, which is our managed spark. And to do service, we've been able to achieve 1.7 x better performance and open source with our spark runtime. So we've invested heavily in performance on now. EMR is also available for customers who are running and containerized environment. So we announced you Marnie chaos on then eh an integrated development environment and studio for you Marco D M R studio. So making it easier both for people at the infrastructure layer to run em are on their eks environments and make it available within their organizations but also simplifying life for data analysts and folks working with data so they can operate in that studio and not have toe mess with the details of the clusters underneath and then a bunch of innovation in red shift. We talked about Aqua already, but then we also announced data sharing for red Shift. So this makes it easy for red shift clusters to share data with other clusters without putting any load on the central producer cluster. And this also speaks to the theme of simplifying getting data from point A to point B so you could have central producer environments publishing data, which represents the source of truth, say into other departments within the organization or departments. And they can query the data, use it. It's always up to date, but it doesn't put any load on the producers that enables these really powerful data sharing on downstream data monetization capabilities like you've mentioned. In addition, like Swami mentioned in his keynote Red Shift ML, so you can now essentially train and run models that were built in sage maker and optimized from within your red shift clusters. And then we've also automated all of the performance tuning that's possible in red ships. So we really invested heavily in price performance, and now we've automated all of the things that make Red Shift the best in class data warehouse service from a price performance perspective up to three X better than others. But customers can just set red shift auto, and it'll handle workload management, data compression and data distribution. Eso making it easier to access all about performance and then the other big one was in Lake Formacion. We announced three new capabilities. One is transactions, so enabling consistent acid transactions on data lakes so you can do things like inserts and updates and deletes. We announced row based filtering for fine grained access control and that unified governance model and then automated storage optimization for Data Lake. So customers are dealing with an optimized small files that air coming off streaming systems, for example, like Formacion can auto compact those under the covers, and you can get a 78 x performance boost. It's been a busy year for prime lyrics. >>I'll say that, z that it no great great job, bro. Thanks so much for coming back in the Cube and, you know, sharing the innovations and, uh, great to see you again. And good luck in the coming here. Well, >>thank you very much. Great to be here. Great to see you. And hope we get Thio see each other in person against >>I hope so. All right. And thank you for watching everybody says Dave Volonte for the Cube will be right back right after this short break