>>Okay, welcome back everyone to the cubes coverage here in Las Vegas for AWS re Mars, Remar stands for machine learning, automation, robotics, and space. Part of thehow is reinforces security. And the big show reinvent at the end of the year is the marquee event. Of course, the queues at all three and more coverage here. We've got a great guest here. Ryan re practice lead data analytics, machine learning at mission cloud. Ryan. Thanks for joining me. Absolutely >>Glad. >>So we were talking before he came on camera about mission cloud. It's not a mission as in a space mission. That's just the name of the company to help people with their mission to move to the cloud. And we're a space show to make that it's almost like plausible. I can see a mission cloud coming someday. >>Yeah, absolutely. >>You got >>The name. We got it. We're ready. >>You guys help customers get to the cloud. So you're working with all the technologies on AWS stack and people who are either lifting and shifting or cloud native born in the cloud, right? Absolutely. >>Yeah. I mean, we often see some companies talk about lift and shift, but you know, we try to get them past that because often a lift and shift means like, say you're on Oracle, you're bringing your Oracle licensing, but a lot of companies want to, you know, innovate and migrate more than they want to lift and shift. So that's really what we're seeing in market. >>You see more migration. Yeah. Less lift and shift. >>Yeah, exactly. Because they, they're trying to get out of an Oracle license. Right. They're seeing if that's super expensive and you know, you can get a much cheaper product on AWS. >>Yeah. What's the cutting up areas right now that you're seeing with cloud Amazon. Cause you know, Amazon, you know, is at their, their birthday, you know, dynamo you to sell with their 10th birthday. Where are they in your mind relative to the enterprise in terms of the services and where this goes next in terms of the on-prem you got the hybrid model. Everyone sees that, but like you got outpost. Mm. Not doing so as good as say EKS or other cool serverless stuff. >>Yeah. I mean, that's a great question. One of the things that's you see from AWS is really innovation, right? They're out there, they have over 400 microservices. So they're looking at all the different areas you have on the cloud and that people are trying to use. And they're creating these microservices that you string together, you architect them all up so that you can create what you're looking for. One of the big things we're seeing, right, is with SageMaker. A lot of people are coming in, looking for ML projects, trying to use all the hype that you see around that doing prediction, NLP and computer vision are super hot right now we've helped a lot of companies, you know, start to build out these NLP models where they're doing, you know, all kinds of stuff you use. 'em in gene research, you know, they're trying to do improvements in drugs and therapeutics. It's really awesome. And then we do some eCommerce stuff where people are just looking at, you know, how do I figure out what are similar things on similar websites, right. For, for search companies. So >>Awesome. Take me through the profile of your customer. You have the mix of business. Can you break down the, the target of the small, medium size enterprise, large all the above. >>Yeah. So mission started working with a lot of startups and SMBs and then as we've grown and become, you know, a much larger company that has all the different focus areas, we started to get into enterprise as well and help a lot of pretty well known enterprises out there that are, you know, not able to find the staff that they need and really want to get into >>The cloud. I wanted to dig into the staffing issues and also to the digital transformation journey. Okay. It okay. We all kind of know what's turning into the more dashboards, more automation, DevOps, cloud, native applications. All good. Yeah. And I can see that journey path. Now the reality is how do you get people who are gonna be capable of doing the ML, doing the DevOps dev sec ops. But what about cyber security? I mean is a ton of range of issues that you gotta be competent on to kind of survive in this multi-disciplined world, just to the old days of I'm the top of rack switch guy is over. >>Absolutely. Yeah. You know, it's a really good question. It's really hard. And that's why, you know, AWS has built out that partner ecosystem because they know companies can't hire enough people to do that. You know, if you look at just a migration into a data lake, you know, on-prem often you had one guy doing it, but if you want to go to the cloud, it's like you said, right, you need a security guy. You need to have a data architect. You need to have a cloud architect. You need to have a data engineer. So, you know, in the old days maybe you needed one guy. Now you have to have five. And so that's really why partners are valuable to customers is we're able to come in, bring those resources, get everything done quickly, and then, you know, turn >>It over. Yeah. We were talking again before we came on camera here live, you, you guys have a service led business, but the rise of MSPs managed service providers is huge. We're seeing it everywhere mainly because the cloud actually enables that you're seeing it for things like Kubernetes, serverless, certain microservices have certain domain expertise and people are making a living, providing great managed services. You guys have managed services. What's that phenomenon. Do you agree with it? And how do you, why did that come about and what, how does it keep going? Is it a trend or is it a one trick pony? >>I think it's a trend. I mean, what you have, it's the same skills gap, right? Is companies no longer want that single point of failure? You know, we have a pool model with our managed services where your team's working with a group of people. And so, you know, we have that knowledge and it's spread out. And so if you're coming in and you need help with Kubernetes, we got a Kubernetes guy in that pool to help you, right. If you need, you know, data, we got a data guy. And so it just makes it a lot easier where, Hey, I can pay the same as one guy and get a whole team of like 12 people that can be interchangeable onto my project. So, you know, I think you're gonna see managed services continue to rise and companies, you know, just working in that space. >>Do you see a new skill set coming? That's kind of got visibility right now, but not full visibility. That's going to be needed. I asked this because the environment's changing for the better obviously, but you're seeing companies that are highly valued, like data bricks, snowflake, they're getting killed on valuation. So they gotta have a hard time retaining talent. In my opinion, my opinion probably be true, but you know, you can't, you know, if you're data breach, you can't raise that 45 billion valuation try to hire senior people. They're gonna be underwater from day one. So there's gonna be a real slow down in these unicorns, these mega unicorns, deck, unicorns, whatever they're called because they gotta refactor the company, stock equity package. They attract people. So they gotta put them on a flat foot. And the next question is, do they actually have the juice, the goods to go to the new market? That's another question. So what I mean, what's your take on you're in the trenches. You're in the front lines. >>Yeah, that's a great question. I mean, and it's hard for me to think about whether they have the juice. I think snowflake and data bricks have been great for the market. They've come in. They've innovated, you know, snowflake was cloud native first. So they were built for the cloud. And what that's done is push all the hyperscalers to improve their products, right. AWS has gone through and you know, drastically over the last three years, improved Redshift. Like, I mean it's night and day from three years ago. Did, >>And you think snowflake put that pressure on them? >>Snowflake. Absolutely. Put that pressure on them. You know, I don't know whether they would've gotten to that same level if snowflake wasn't out there stealing market share. But now when you look at it, Redshift is much cheaper than snowflake. So how long are people gonna pay that tax to have snowflake versus switching over snowflakes? >>Got a nice data. Clean room, had some nice lock in features. Only on snowflake. The question is, will that last clean room? I see you smiling. Go ahead. >>Clean. Room's a concept that was actually made by Google. I know Snowflake's trying to capture it as their own, but, but Google's the one that actually launched the clean room concept because of marketing and, and all of that. >>Google also launches semantic layer, which Snowflake's trying to copy that. Does that, what does that mean to you when you hear the word semantic layer? What does that mean? >>And semantic layer just is really all about meta tags, right? How am I going through to figure out what data do I actually have in my data lake so that I can pull it for whatever I'm trying to do, whether it's dashboarding or whether it's machine learning. You're just trying to organize your data better. >>Ryan, you should be a cue post. You're like a masterclass here in, in it and cloud native. I gotta ask you since you're here, since we're having the masterclass being put in a clinic here, lot of clients are confused between how to handle the control plane and the data plane cause machine learning right now is at an all time high. You're seeing deep racer. You're seeing robotic space, all driving by machine learning. SW. He said it today, the, the companion coder, right? The, the code whisperer, that's only gonna get stronger. So machine learning needs data. It feeds on data. So everyone right now is trying to put data in silos. Okay? Cause they think, oh, compliance, you gotta create a data plane and a control plane that makes it highly available. So that can be shared >>Right >>Now. A lot of people are trying to own the data plane and some are trying to own the control plane or both. Right? What's your view on that? Because I see customers say, look, I want to own my own data cause I can control it. Control plane. I can maybe do other things. And some are saying, I don't know what to do. And they're getting forced to take both to control plane and a data plane from a vendor, right? What's your, what's your reaction to that? >>So it's pretty interesting. I actually was presenting at a tech target conference this week on exactly this concept, right, where we're seeing more and more words out there, right? It was data warehouse and it was data lake and it's lake house. And it's a data mesh and it's a data fabric. And some of the concepts you're talking about really come into that data, match data fabric space. And you know, what you're seeing is data's gonna become a product right, where you're gonna be buying a product and the silos yes. Silos exist. But what, what companies have to start doing is, and this is the whole data mesh concept is, Hey yes, you finance department. You can own your silo, but now you have to have an output product. That's a data product that every other part of your company can subscribe to that data product and use it in their algorithms or their dashboard so that they can get that 360 degree view of the customer. So it's really, you know, key that, you know, you work within your business. Some business are gonna have that silo where the data mesh works. Great. Others are gonna go. >>And what do you think about that? Because I mean, my thesis would be, Hey, more data, better machine learning. Right. Is that the concept? >>So, or that's a misconception or, >>Okay. So what's the, what's the rationale to share the data like that and data mission. >>So having more of the right data here, it is improves. Just having more data in general, doesn't improve, right? And often the problem is in the silos you're getting to is you don't have all the data you want. Right. I was doing a big project about shipping and there's PII data. When you talk about shipping, right? Person's addresses, that's owned by one department and you can't get there. Right. But how am I supposed to estimate the cost of shipping if I can't get, you know, data from where a person lives. Right. It's just >>Not. So none of the wrinkle in the equation is latency. Okay. The right data at the right time is another factor is that factored into data mesh versus these other approaches. Because I mean, you can, people are streaming data. I get that. We're seeing a lot of that. But talking about getting data fast enough before the decisions are made, is that an issue or is this just BS? >>I'm going with BS. Okay. So people talk about real time real. Time's great if you need it, but it's really expensive to do. Most people don't need real time. Right. They're really looking for, I need an hourly dashboard or I need a daily dashboard. And so pushing into real time, just gonna be an added expense that you don't >>Really need. Like cyber maybe is that not maybe need real time. >>Well, cyber security add. I mean, there's definitely certain applications that you need real time, >>But don't over invest in fantasy if you don't need an an hour's fine. Right, >>Right. Yeah. If you're, if you're a business and you're looking at your financials, do you need your financials every second? Is that gonna do anything for you? Got >>It. Yeah. Yeah. And so this comes back down to data architecture. So the next question I asked, cause I had a great country with the Fiddler AI CEO, CEO earlier, and he was at Facebook and then Pinterest, he was a data, you know, an architect and built everything. He said themselves. We were talking about all the stuff that's available now are all the platforms and tools available to essentially build the next Facebook if someone wanted to from scratch. I mean, hypothetically thought exercise. So the ability to actually ramp up and code a complete throwaway and rebuild from the ground up is possible. >>Absolutely. >>And so the question is, okay, how do you do it? How long would it take? I mean, in an ideal scenario, not, you know, make some assumptions here, you got the budget, you got the people, how long to completely roll out a brand new platform. >>Now it's funny, you asked that because about a year ago I was asked that exact same question by a customer that was in the religious space that basically wanted to build a combination of Facebook, Netflix, and Amazon altogether for the religious space, for religious goods and you know, church sermons, we estimated for him about a year and about $9 million to do it. >>I mean, that's a, that's a, a round these days. Yeah. Series a. So it's possible. Absolutely. So enterprises, what's holding them back, just dogma process, old school legacy, or are people taking the bold move to take more aggressive, swiping out old stuff and just completely rebuilding? Or is it a talent issue? What's the, what's the enterprise current mode of reset, >>You know, I think it really depends on the enterprise and their aversion to risk. Right. You know, some enterprises and companies are really out there wanting to innovate, you know, I mean there's companies, you know, an air conditioning company that we worked with, that's totally, you know, nest was eaten all their business. So they came in and created a whole T division, you know, to, to chase that business, that nest stole from them. So I think it, I think often a company's not necessarily gonna innovate until somebody comes in and starts stealing their >>Lunch. You know, Ryan, Andy, Jess, we talked about this two reinvents ago. And then Adam Eski said the same thing this year on a different vector, but kind of building on what Andy Jessey said. And it's like, you could actually take new territory down faster. You don't have to kill the old, no I'm paraphrasing. You don't have to kill the old to bring in the new, you can actually move on new ideas with a clean sheet of paper if you have that builder mindset. And I think that to me is where I'm seeing. And I'd love to get your reaction because if you see an opportunity to take advantage and take territory and you have the right budget time and people, you can get it. Oh absolutely. It's gettable. So a lot of people have this fear of, oh, we're, that's not our core competency. And, and they they're the frog and boiling water. >>You know, my answer to that is I think part of it's VCs, right? Yeah. VCs have come in and they see the value of a company often by how many people you hire, right. Hire more people. And the value is gonna go up. But often as a startup, you can't hire good people. So I'm like, well, why are you gonna go hire a bunch of random people? You should go to a firm like ours that knows AWS and can build it quickly for you, cuz then you're gonna get to the market faster versus just trying to hire a bunch of people in >>Someone. Right. I really appreciate you coming on. I'd love to have you back on the cube again, sometime your expertise and your insights are awesome. Give a commercial for the company, what you guys are doing, who you're looking for, what you want to do, hiring or whatever your goals are. Take a minute to explain what you guys are doing and give a quick plug. >>Awesome. Yeah. So mission cloud, you know, we're a premier AWS consulting firm. You know, if you're looking to go to AWS or you're in AWS and you need help and support, we have a full team, we do everything. Resell, MSP professional services. We can get you into the cloud optimize. You make everything run as fast as possible. I also have a full machine learning team. Since we're here at re Mars, we can build you models. We can get 'em into production, can make sure everything's smooth. The company's hiring. We're looking to double in size this year. So, you know, look me up on LinkedIn, wherever happy to, to take, >>You mentioned the cube, you get a 20% discount. He's like, no, I don't approve that. Thanks for coming on the key. Really appreciate it. Again. Machine learning swaping said on stage this, you can be a full time job just tracking just the open source projects. Never mind all the different tools and like platform. So I think you're gonna have a good, good tailwind for your business. Thanks for coming on the queue. Appreciate it. Ryan Reese here on the queue. I'm John furry more live coverage here at re Mars 2022. After this short break, stay with us.

(upbeat music) >> Welcome back to Boston, everybody. This is the birthplace of theCUBE. In 2010, May of 2010 at EMC World, right in this very venue, John Furrier called it the chowder and lobster post. I'm Dave Vellante. We're here at RE:INFORCE 2022, Ed Walsh, CEO of ChaosSearch. Doing a drive by Ed. Thanks so much for stopping in. You're going to help me wrap up in our final editorial segment. >> Looking forward to it. >> I really appreciate it. >> Thank you for including me. >> How about that? 2010. >> That's amazing. It was really in this-- >> Really in this building. Yeah, we had to sort of bury our way in, tunnel our way into the Blogger Lounge. We did four days. >> Weekends, yeah. >> It was epic. It was really epic. But I'm glad they're back in Boston. AWS was going to do June in Houston. >> Okay. >> Which would've been awful. >> Yeah, yeah. No, this is perfect. >> Yeah. Thank God they came back. You saw Boston in summer is great. I know it's been hot, And of course you and I are from this area. >> Yeah. >> So how you been? What's going on? I mean, it's a little crazy out there. The stock market's going crazy. >> Sure. >> Having the tech lash, what are you seeing? >> So it's an interesting time. So I ran a company in 2008. So we've been through this before. By the way, the world's not ending, we'll get through this. But it is an interesting conversation as an investor, but also even the customers. There's some hesitation but you have to basically have the right value prop, otherwise things are going to get sold. So we are seeing longer sales cycles. But it's nothing that you can't overcome. But it has to be something not nice to have, has to be a need to have. But I think we all get through it. And then there is some, on the VC side, it's now buckle down, let's figure out what to do which is always a challenge for startup plans. >> In pre 2000 you, maybe you weren't a CEO but you were definitely an executive. And so now it's different and a lot of younger people haven't seen this. You've got interest rates now rising. Okay, we've seen that before but it looks like you've got inflation, you got interest rates rising. >> Yep. >> The consumer spending patterns are changing. You had 6$, $7 gas at one point. So you have these weird crosscurrents, >> Yup. >> And people are thinking, "Okay post-September now, maybe because of the recession, the Fed won't have to keep raising interest rates and tightening. But I don't know what to root for. It's like half full, half empty. (Ed laughing) >> But we haven't been in an environment with high inflation. At least not in my career. >> Right. Right. >> I mean, I got into 92, like that was long gone, right?. >> Yeah. >> So it is a interesting regime change that we're going to have to deal with, but there's a lot of analogies between 2008 and now that you still have to work through too, right?. So, anyway, I don't think the world's ending. I do think you have to run a tight shop. So I think the grow all costs is gone. I do think discipline's back in which, for most of us, discipline never left, right?. So, to me that's the name of the game. >> What do you tell just generally, I mean you've been the CEO of a lot of private companies. And of course one of the things that you do to retain people and attract people is you give 'em stock and it's great and everybody's excited. >> Yeah. >> I'm sure they're excited cause you guys are a rocket ship. But so what's the message now that, Okay the market's down, valuations are down, the trees don't grow to the moon, we all know that. But what are you telling your people? What's their reaction? How do you keep 'em motivated? >> So like anything, you want over communicate during these times. So I actually over communicate, you get all these you know, the Sequoia decks, 2008 and the recent... >> (chuckles) Rest in peace good times, that one right? >> I literally share it. Why? It's like, Hey, this is what's going on in the real world. It's going to affect us. It has almost nothing to do with us specifically, but it will affect us. Now we can't not pay attention to it. It does change how you're going to raise money, so you got to make sure you have the right runway to be there. So it does change what you do, but I think you over communicate. So that's what I've been doing and I think it's more like a student of the game, so I try to share it, and I say some appreciate it others, I'm just saying, this is normal, we'll get through this and this is what happened in 2008 and trust me, once the market hits bottom, give it another month afterwards. Then everyone says, oh, the bottom's in and we're back to business. Valuations don't go immediately back up, but right now, no one knows where the bottom is and that's where kind of the world's ending type of things. >> Well, it's interesting because you talked about, I said rest in peace good times >> Yeah >> that was the Sequoia deck, and the message was tighten up. Okay, and I'm not saying you shouldn't tighten up now, but the difference is, there was this period of two years of easy money and even before that, it was pretty easy money. >> Yeah. >> And so companies are well capitalized, they have runway so it's like, okay, I was talking to Frank Slootman about this now of course there are public companies, like we're not taking the foot off the gas. We're inherently profitable, >> Yeah. >> we're growing like crazy, we're going for it. You know? So that's a little bit of a different dynamic. There's a lot of good runway out there, isn't there? >> But also you look at the different companies that were either born or were able to power through those environments are actually better off. You come out stronger in a more dominant position. So Frank, listen, if you see what Frank's done, it's been unbelievable to watch his career, right?. In fact, he was at Data Domain, I was Avamar so, but look at what he's done since, he's crushed it. Right? >> Yeah. >> So for him to say, Hey, I'm going to literally hit the gas and keep going. I think that's the right thing for Snowflake and a right thing for a lot of people. But for people in different roles, I literally say that you have to take it seriously. What you can't be is, well, Frank's in a different situation. What is it...? How many billion does he have in the bank? So it's... >> He's over a billion, you know, over a billion. Well, you're on your way Ed. >> No, no, no, it's good. (Dave chuckles) Okay, I want to ask you about this concept that we've sort of we coined this term called Supercloud. >> Sure. >> You could think of it as the next generation of multi-cloud. The basic premises that multi-cloud was largely a symptom of multi-vendor. Okay. I've done some M&A, I've got some Shadow IT, spinning up, you know, Shadow clouds, projects. But it really wasn't a strategy to have a continuum across clouds. And now we're starting to see ecosystems really build, you know, you've used the term before, standing on the shoulders of giants, you've used that a lot. >> Yep. >> And so we're seeing that. Jerry Chen wrote a seminal piece on Castles in The Cloud, so we coined this term SuperCloud to connote this abstraction layer that hides the underlying complexities and primitives of the individual clouds and then adds value on top of it and can adjudicate and manage, irrespective of physical location, Supercloud. >> Yeah. >> Okay. What do you think about that concept?. How does it maybe relate to some of the things that you're seeing in the industry? >> So, standing on shoulders of giants, right? So I always like to do hard tech either at big company, small companies. So we're probably your definition of a Supercloud. We had a big vision, how to literally solve the core challenge of analytics at scale. How are you going to do that? You're not going to build on your own. So literally we're leveraging the primitives, everything you can get out of the Amazon cloud, everything get out of Google cloud. In fact, we're even looking at what it can get out of this Snowflake cloud, and how do we abstract that out, add value to it? That's where all our patents are. But it becomes a simplified approach. The customers don't care. Well, they care where their data is. But they don't care how you got there, they just want to know the end result. So you simplify, but you gain the advantages. One thing's interesting is, in this particular company, ChaosSearch, people try to always say, at some point the sales cycle they say, no way, hold on, no way that can be fast no way, or whatever the different issue. And initially we used to try to explain our technology, and I would say 60% was explaining the public, cloud capabilities and then how we, harvest those I guess, make them better add value on top and what you're able to get is something you couldn't get from the public clouds themselves and then how we did that across public clouds and then extracted it. So if you think about that like, it's the Shoulders of giants. But what we now do, literally to avoid that conversation because it became a lengthy conversation. So, how do you have a platform for analytics that you can't possibly overwhelm for ingest. All your messy data, no pipelines. Well, you leverage things like S3 and EC2, and you do the different security things. You can go to environments say, you can't possibly overrun me, I could not say that. If I didn't literally build on the shoulders giants of all these public clouds. But the value. So if you're going to do hard tech as a startup, you're going to build, you're going to be the principles of Supercloud. Maybe they're not the same size of Supercloud just looking at Snowflake, but basically, you're going to leverage all that, you abstract it out and that's where you're able to have a lot of values at that. >> So let me ask you, so I don't know if there's a strict definition of Supercloud, We sort of put it out to the community and said, help us define it. So you got to span multiple clouds. It's not just running in each cloud. There's a metadata layer that kind of understands where you're pulling data from. Like you said you can pull data from Snowflake, it sounds like we're not running on Snowflake, correct? >> No, complimentary to them in their different customers. >> Yeah. Okay. >> They want to build on top of a data platform, data apps. >> Right. And of course they're going cross cloud. >> Right. >> Is there a PaaS layer in there? We've said there's probably a Super PaaS layer. You're probably not doing that, but you're allowing people to bring their own, bring your own PaaS sort of thing maybe. >> So we're a little bit different but basically we publish open APIs. We don't have a user interface. We say, keep the user interface. Again, we're solving the challenge of analytics at scale, we're not trying to retrain your analytics, either analysts or your DevOps or your SOV or your Secop team. They use the tools they already use. Elastic search APIs, SQL APIs. So really they program, they build applications on top of us, Equifax is a good example. Case said it coming out later on this week, after 18 months in production but, basically they're building, we provide the abstraction layer, the quote, I'm going to kill it, Jeff Tincher, who owns all of SREs worldwide, said to the effect of, Hey I'm able to rethink what I do for my data pipelines. But then he also talked about how, that he really doesn't have to worry about the data he puts in it. We deal with that. And he just has to, just query on the other side. That simplicity. We couldn't have done that without that. So anyway, what I like about the definition is, if you were going to do something harder in the world, why would you try to rebuild what Amazon, Google and Azure or Snowflake did? You're going to add things on top. We can still do intellectual property. We're still doing patents. So five grand patents all in this. But literally the abstraction layer is the simplification. The end users do not want to know that complexity, even though they ask the questions. >> And I think too, the other attribute is it's ecosystem enablement. Whereas I think, >> Absolutely >> in general, in the Multicloud 1.0 era, the ecosystem wasn't thinking about, okay, how do I build on top and abstract that. So maybe it is Multicloud 2.0, We chose to use Supercloud. So I'm wondering, we're at the security conference, >> RE: INFORCE is there a security Supercloud? Maybe Snyk has the developer Supercloud or maybe Okta has the identity Supercloud. I think CrowdStrike maybe not. Cause CrowdStrike competes with Microsoft. So maybe, because Microsoft, what's interesting, Merritt Bear was just saying, look, we don't show up in the spending data for security because we're not charging for most of our security. We're not trying to make a big business. So that's kind of interesting, but is there a potential for the security Supercloud? >> So, I think so. But also, I'll give you one thing I talked to, just today, at least three different conversations where everyone wants to log data. It's a little bit specific to us, but basically they want to do the security data lake. The idea of, and Snowflake talks about this too. But the idea of putting all the data in one repository and then how do you abstract out and get value from it? Maybe not the perfect, but it becomes simple to do but hard to get value out. So the different players are going to do that. That's what we do. We're able to, once you land it in your S3 or it doesn't matter, cloud of choice, simple storage, we allow you to get after that data, but we take the primitives and hide them from you. And all you do is query the data and we're spinning up stateless computer to go after it. So then if I look around the floor. There's going to be a bunch of these players. I don't think, why would someone in this floor try to recreate what Amazon or Google or Azure had. They're going to build on top of it. And now the key thing is, do you leave it in standard? And now we're open APIs. People are building on top of my open APIs or do you try to put 'em in a walled garden? And they're in, now your Supercloud. Our belief is, part of it is, it needs to be open access and let you go after it. >> Well. And build your applications on top of it openly. >> They come back to snowflake. That's what Snowflake's doing. And they're basically saying, Hey come into our proprietary environment. And the benefit is, and I think both can win. There's a big market. >> I agree. But I think the benefit of Snowflake's is, okay, we're going to have federated governance, we're going to have data sharing, you're going to have access to all the ecosystem players. >> Yep. >> And as everything's going to be controlled and you know what you're getting. The flip side of that is, Databricks is the other end >> Yeah. >> of that spectrum, which is no, no, you got to be open. >> Yeah. >> So what's going to happen, well what's happening clearly, is Snowflake's saying, okay we've got Snowpark. we're going to allow Python, we're going to have an Apache Iceberg. We're going to have open source tooling that you can access. By the way, it's not going to be as good as our waled garden where the flip side of that is you get Databricks coming at it from a data science and data engineering perspective. And there's a lot of gaps in between, aren't there? >> And I think they both win. Like for instance, so we didn't do Snowpark integration. But we work with people building data apps on top of Snowflake or data bricks. And what we do is, we can add value to that, or what we've done, again, using all the Supercloud stuff we're done. But we deal with the unstructured data, the four V's coming at you. You can't pipeline that to save. So we actually could be additive. As they're trying to do like a security data cloud inside of Snowflake or do the same thing in Databricks. That's where we can play. Now, we play with them at the application level that they get some data from them and some data for us. But I believe there's a partnership there that will do it inside their environment. To us they're just another large scaler environment that my customers want to get after data. And they want me to abstract it out and give value. >> So it's another repository to you. >> Yeah. >> Okay. So I think Snowflake recently added support for unstructured data. You chose not to do Snowpark because why? >> Well, so the way they're doing the unstructured data is not bad. It's JSON data. Basically, This is the dilemma. Everyone wants their application developers to be flexible, move fast, securely but just productivity. So you get, give 'em flexibility. The problem with that is analytics on the end want to be structured to be performant. And this is where Snowflake, they have to somehow get that raw data. And it's changing every day because you just let the developers do what they want now, in some structured base, but do what you need to do your business fast and securely. So it completely destroys. So they have large customers trying to do big integrations for this messy data. And it doesn't quite work, cause you literally just can't make the pipelines work. So that's where we're complimentary do it. So now, the particular integration wasn't, we need a little bit deeper integration to do that. So we're integrating, actually, at the data app layer. But we could, see us and I don't, listen. I think Snowflake's a good actor. They're trying to figure out what's best for the customers. And I think we just participate in that. >> Yeah. And I think they're trying to figure out >> Yeah. >> how to grow their ecosystem. Because they know they can't do it all, in fact, >> And we solve the key thing, they just can't do certain things. And we do that well. Yeah, I have SQL but that's where it ends. >> Yeah. >> I do the messy data and how to play with them. >> And when you talk to one of their founders, anyway, Benoit, he comes on the cube and he's like, we start with simple. >> Yeah. >> It reminds me of the guy's some Pure Storage, that guy Coz, he's always like, no, if it starts to get too complicated. So that's why they said all right, we're not going to start out trying to figure out how to do complex joins and workload management. And they turn that into a feature. So like you say, I think both can win. It's a big market. >> I think it's a good model. And I love to see Frank, you know, move. >> Yeah. I forgot So you AVMAR... >> In the day. >> You guys used to hate each other, right? >> No, no, no >> No. I mean, it's all good. >> But the thing is, look what he's done. Like I wouldn't bet against Frank. I think it's a good message. You can see clients trying to do it. Same thing with Databricks, same thing with BigQuery. We get a lot of same dynamic in BigQuery. It's good for a lot of things, but it's not everything you need to do. And there's ways for the ecosystem to play together. >> Well, what's interesting about BigQuery is, it is truly cloud native, as is Snowflake. You know, whereas Amazon Redshift was sort of Parexel, it's cobbled together now. It's great engineering, but BigQuery gets a lot of high marks. But again, there's limitations to everything. That's why companies like yours can exist. >> And that's why.. so back to the Supercloud. It allows me as a company to participate in that because I'm leveraging all the underlying pieces. Which we couldn't be doing what we're doing now, without leveraging the Supercloud concepts right, so... >> Ed, I really appreciate you coming by, help me wrap up today in RE:INFORCE. Always a pleasure seeing you, my friend. >> Thank you. >> All right. Okay, this is a wrap on day one. We'll be back tomorrow. I'll be solo. John Furrier had to fly out but we'll be following what he's doing. This is RE:INFORCE 2022. You're watching theCUBE. I'll see you tomorrow.

(upbeat music) >> Welcome back to re:Invent 2021. You're watching theCUBE. My name is Dave Vellante. We're really excited to have Anthony Lye here. He's the Executive Vice President and General Manager of Public Cloud at NetApp. And Jonsi Stefansson as the CTO and VP of cloud at NetApp. Guys, good to see you. >> Same to you. >> Likewise. >> It's great to be back. >> You know, Anthony. Well so, we saw each other virtually at the AWS Storage Day, the big announcement, we're going to talk about that. But I go back and I said this to you several years ago, we were sitting, you know, some after party and you said "We are going to transform NetApp. We are going all in on cloud." We've seen NetApp transform many, many times. This is probably the biggest in history. >> No, I think you're absolutely right. I think, you know, I can't believe it, but you know, it will be five years for me in February. And in those five years, I think we really have done things that nobody expected. And I think we've proven to our existing customers, to our competitors, and now with Amazon, to a whole new set of customers that our intellectual property that we build and the acquisitions that we've done have made a lot of sense. I think we've demonstrated this wonderful concept of symmetry. Customers now understand and believe that a dollar invested in an App, wherever it is on premise or in the cloud is a dollar that moves wherever they want it to move and progresses as their own businesses progress. >> So Jonsi, for the latest announcement that you guys made to integrate ONTAP into the AWS cloud, you had to do some deeper integration, right? It wasn't just wrap your stack and Kubernetes and shove it into the cloud. But can you just talk about what you had to do? What the collaboration was like? >> The collaboration with AWS has been fantastic. It literally took two and a half years, you know, from the point where we decided to agree on the design principles, how we were actually going to deliver this as a service, the integration into every single aspect of AWS, you know, whether it's the console, the FSx, API, the integrations, to all the additional services that AWS has, like RDS, like Aurora, like the SageMaker, like EKS and ECS. And I mean, we are just getting started with the integration points and the collaboration and the teamwork. I would call it teamwork more than a collaboration. The teamwork with all these teams and maybe especially at name who was the leader of the storage sort of a unit in AWS has been fantastic. >> Dave: Yeah. Well so, this is the 10th re:Invent. This is the 9th year we've been here. We've seen a dramatically different cloud than 10 years ago, 15 years ago, and a different storage business. I'm not even sure. I mean, I don't know. I didn't even think about it as the old storage business anymore. Essentially, you're building a cloud on top of clouds. A super cloud if you will. >> Anthony: Yeah, I mean. I think, look, the strategy was, as I said, very, very simple to us, which was, you know, fundamentally companies, you know, run their applications on the basic primitives of compute storage and networking. And the gold standard for file was always ONTAP. And I think what we did, which I think was unique was we didn't just, as you said, throw it onto a cloud, stick it in a virtual machine and tell you, the customer "There. It's ONTAP just as you remember it." We reimagined it. And we architected it to be a cloud service. So it's elastic, it goes up and down. You can change the performance at runtime. And what we really did with Amazon was we wanted to make it a fully managed service. We didn't want people to think about versioning and patching. We wanted to remove all of that and we wanted people to take as much or as little as they needed. And we, and Amazon, we chose that we should own the responsibility for the availability of the service. And we should maintain the service ourselves so that customers of ONTAP can benefit from the solution. But in many ways, customers who've never been ONTAP customers can now take advantage of an enterprise grade file system and all the great things that it does without having to understand how it works. >> And explain why that's important for customers because people, they go, "Wow, you got S3." but it's very simple. Get, put, right? You don't have the full stack of a mature ONTAP. Please explain what that means to customers a little bit. >> You know, file systems are very important things. You know, we basically use them in our work environments every single day, you know. Within your sort of, you know, your Mac book, you have a home directory and sub-directories and files, very elegantly layout applications and layout infrastructures in ways that object repositories cannot. You know, aside from block and file. Sorry, from file and object, you of course, have block storage. And so, file plays a very important role. IDC has file growing at almost twice the pace of object now on the public cloud systems and, you know, file has about 13% of the overall storage market and it's growing. And I don't see any reason why file won't be as big on the Amazon cloud as the S3 has been. >> Dave: So you guys, go ahead, please. >> Yeah. I mean, you also have to take into account that the S3 object storage offerings of AWS is an integrated PaaS in our solution. So that's how we are actually doing automatic tiering. So you actually reap the best of both worlds, where you get the cost management of putting it in object storage, but you get the performance and the data management capabilities that is pretty unprecedented. You know, we are the first store that's offering that can actually do cross-region replication seamlessly by retaining deduplication and compression. But we also play a lot with, you know, block and object storage. So when Anthony was talking about how we've actually delivered this as a service, and this is sort of from our design principles, we are basically delivering this as a software, as a service, because more than an infrastructure as a service, because the stock that we are actually deploying, or the secret sauce of ONTAP, it's a very vast software stack that we are delivering, on top of AWS infrastructure. So I would always call it or categorize it a little bit more than software as a service, rather than infrastructure as a service. >> But it's even more than that, if I'm right, because it's cloud pricing, right? >> Jonsi: Yes. >> So it's not, you're not preying. I mean, when I buy Salesforce, I got to sign up for three-year deal. That's not a consumption-based model. >> Yeah. >> Oh, I think Amazon, you know what Amazon did uniquely and brilliantly was, it retailed technology and it's what makes Amazon so good, is that they choose to sort of simplify things. And when they find benefits as a retailer, they pass them on to the customer and, you know, there's this sort of pay-as-you-go business model, it's really good for the customer. It makes us work harder because, you know, you have to retain your customer sort of every 10 minutes. And that's something that, you know, as you said, with enterprise software and even some of the early SaaS vendors, that's not how it works. And so Amazon has forced us all to be very, very attentive to our customers. >> Dave: And I'd love to talk about what that means for the on-prem business, but if we have time. But you guys won Design Partner of the Year, what's that all about? First of all, congratulations. >> Anthony: Thank you. There's a lot of ISV design partners. You guys came out number one so congratulations on that. What's that all about? Explain what that entailed and how you got that. >> Yeah, I'll say a few words. Maybe Jonsi can add. I mean, the first thing of course is, you know, I S V stands for Independent Software Vendor. So, you know, it's always great because most people would say, "Well, NetApp is on-premise storage hardware." >> Dave: Of course, yeah. >> Which really, we've not really ever been an increasingly with demonstrating that we are a software company and we operate at cloud speed. You know, I can't really take the credit. I would give it to Jonsi and the engineering team. Maybe Jonsi, you can explain, you know, what moral about the award and why I think we were selected. >> So, I mean, I think it says a lot that this is the first time AWS has ever allowed a third party company to be this integrated into their console, into a support ability systems. You know, we make fun of this, me and Anthony all the time, because when we started this, down this path, everybody at NetApp said, "Guys, you're wasting your time." This is why AWS has the marketplace, but we didn't want to go. We already had the marketplace and we wanted to be able to connect to all these associated services and do it in the manner that, you know, this was a true collaboration of engineering teams for a long time to actually deliver the service on both sides so the credit, of course, will always go to the engineers on both sides, even though I designed it, I didn't code it. So, I think that, that alone, being the first to do it in AWS ever. I think we deserve that award. >> So just for our audience, to be clear, we're talking about FSx, ONTAP in the cloud, in the AWS cloud and kind of dance around that. But so that was announced, I guess, in September? >> Anthony: Yes. >> Right? >> Anthony: September, 2nd. >> What's the uptake been like? What's the reaction? >> Unbelievable. >> I'll bet. (laughing) >> No, no, I mean. >> No, I believe it. >> Better than we ever dreamed of. >> Yeah. >> The number of customers, I'm sure I'm not allowed to say the number of customers, but we asked and the fact that, you know, 60% of those customers have never been NetApp customers before, but they see the value in the data management capabilities that we are bringing to the market. >> Dave: So it exceeded expectations and your expectations were probably pretty enthusiastic. >> They were high. >> Yeah. >> I mean, Amazon is on the record. I was with Ed earlier on today, recording a piece and Ed, you know, was very clear that it's one of the fastest growing services now on AWS. You know, it turns out that, you know, the customer base, I think recognizes the, not just the need for a file system, but the uniqueness and capabilities that ONTAP provides, you know, to those customers in how they manage their business and transformations. And so, you know, to be sort of behind the console, to be sort of behind the Amazon CLI and the Amazon API, you see the world very, very differently, you know. I think the Amazon marketplace is a fantastic capability, but I'll tell you, you know, being a core part of the AWS service itself that they sell, that they support, that they bill for. It's a nice place to be. >> So, SaaS company. You're talking to the language of application development, Kubernetes, right? What do you think this means for the future of NetApp specifically, but also generally the on-prem storage business and the storage business in general? >> Well, we just announced our second quarter earnings today and what's happening is our cloud business is growing like crazy. We generated $388 million of ARR and the growth rates are, you know, astronomically high. That is increasingly helping our on-premise business to grow. You know, the nice thing about being in primarily, in the storage and data business is people aren't deleting many things. And the rate at which they're generating information is just accelerating. So, actually the confidence that we give the customer by demonstrating a sort of a cloud first, a sort of principles of all the cloud is actually giving customers to buy more on premise. So, we really don't mind. We are, our job much like Amazon's, is to have this customer obsession and you can't really go wrong, if you just keep asking them what they want. >> Yeah, if you can do so profitably, you're going to be reinvest in your business. Guys, we've got to go. >> Yeah. >> Love to have you back. >> Thank you. >> And you been quite a transformation. You said you're going to do it. You're doing it. So, well done to you. Five years in the making. Okay. This is Dave Vellante for theCUBE, the leader in high-tech coverage. Keep it right there. We'll be right back from AWS re:Invent 21. (upbeat music)

(upbeat music) >> Welcome back to re:Invent 2021. You're watching theCUBE. My name is Dave Vellante. We're really excited to have Anthony Lye here. He's the Executive Vice President and General Manager of Public Cloud at NetApp. And Jonsi Stefansson as the CTO and VP of cloud at NetApp. Guys, good to see you. >> Same to you. >> Likewise. >> It's great to be back. >> You know, Anthony. Well so, we saw each other virtually at the AWS Storage Day, the big announcement, we're going to talk about that. But I go back and I said this to you several years ago, we were sitting, you know, some after party and you said "We are going to transform NetApp. We are going all in on cloud." We've seen NetApp transform many, many times. This is probably the biggest in history. >> No, I think you're absolutely right. I think, you know, I can't believe it, but you know, it will be five years for me in February. And in those five years, I think we really have done things that nobody expected. And I think we've proven to our existing customers, to our competitors, and now with Amazon, to a whole new set of customers that our intellectual property that we build and the acquisitions that we've done have made a lot of sense. I think we've demonstrated this wonderful concept of symmetry. Customers now understand and believe that a dollar invested in an App, wherever it is on premise or in the cloud is a dollar that moves wherever they want it to move and progresses as their own businesses progress. >> So Jonsi, for the latest announcement that you guys made to integrate ONTAP into the AWS cloud, you had to do some deeper integration, right? It wasn't just wrap your stack and Kubernetes and shove it into the cloud. But can you just talk about what you had to do? What the collaboration was like? >> The collaboration with AWS has been fantastic. It literally took two and a half years, you know, from the point where we decided to agree on the design principles, how we were actually going to deliver this as a service, the integration into every single aspect of AWS, you know, whether it's the console, the FSx, API, the integrations, to all the additional services that AWS has, like RDS, like Aurora, like the SageMaker, like EKS and ECS. And I mean, we are just getting started with the integration points and the collaboration and the teamwork. I would call it teamwork more than a collaboration. The teamwork with all these teams and maybe especially at name who was the leader of the storage sort of a unit in AWS has been fantastic. >> Dave: Yeah. Well so, this is the 10th re:Invent. This is the 9th year we've been here. We've seen a dramatically different cloud than 10 years ago, 15 years ago, and a different storage business. I'm not even sure. I mean, I don't know. I didn't even think about it as the old storage business anymore. Essentially, you're building a cloud on top of clouds. A super cloud if you will. >> Anthony: Yeah, I mean. I think, look, the strategy was, as I said, very, very simple to us, which was, you know, fundamentally companies, you know, run their applications on the basic primitives of compute storage and networking. And the gold standard for file was always ONTAP. And I think what we did, which I think was unique was we didn't just, as you said, throw it onto a cloud, stick it in a virtual machine and tell you, the customer "There. It's ONTAP just as you remember it." We reimagined it. And we architected it to be a cloud service. So it's elastic, it goes up and down. You can change the performance at runtime. And what we really did with Amazon was we wanted to make it a fully managed service. We didn't want people to think about versioning and patching. We wanted to remove all of that and we wanted people to take as much or as little as they needed. And we, and Amazon, we chose that we should own the responsibility for the availability of the service. And we should maintain the service ourselves so that customers of ONTAP can benefit from the solution. But in many ways, customers who've never been ONTAP customers can now take advantage of an enterprise grade file system and all the great things that it does without having to understand how it works. >> And explain why that's important for customers because people, they go, "Wow, you got S3." but it's very simple. Get, put, right? You don't have the full stack of a mature ONTAP. Please explain what that means to customers a little bit. >> You know, file systems are very important things. You know, we basically use them in our work environments every single day, you know. Within your sort of, you know, your Mac book, you have a home directory and sub-directories and files, very elegantly layout applications and layout infrastructures in ways that object repositories cannot. You know, aside from block and file. Sorry, from file and object, you of course, have block storage. And so, file plays a very important role. IDC has file growing at almost twice the pace of object now on the public cloud systems and, you know, file has about 13% of the overall storage market and it's growing. And I don't see any reason why file won't be as big on the Amazon cloud as the S3 has been. >> Dave: So you guys, go ahead, please. >> Yeah. I mean, you also have to take into account that the S3 object storage offerings of AWS is an integrated PaaS in our solution. So that's how we are actually doing automatic tiering. So you actually reap the best of both worlds, where you get the cost management of putting it in object storage, but you get the performance and the data management capabilities that is pretty unprecedented. You know, we are the first store that's offering that can actually do cross-region replication seamlessly by retaining deduplication and compression. But we also play a lot with, you know, block and object storage. So when Anthony was talking about how we've actually delivered this as a service, and this is sort of from our design principles, we are basically delivering this as a software, as a service, because more than an infrastructure as a service, because the stock that we are actually deploying, or the secret sauce of ONTAP, it's a very vast software stack that we are delivering, on top of AWS infrastructure. So I would always call it or categorize it a little bit more than software as a service, rather than infrastructure as a service. >> But it's even more than that, if I'm right, because it's cloud pricing, right? >> Jonsi: Yes. >> So it's not, you're not preying. I mean, when I buy Salesforce, I got to sign up for three-year deal. That's not a consumption-based model. >> Yeah. >> Oh, I think Amazon, you know what Amazon did uniquely and brilliantly was, it retailed technology and it's what makes Amazon so good, is that they choose to sort of simplify things. And when they find benefits as a retailer, they pass them on to the customer and, you know, there's this sort of pay-as-you-go business model, it's really good for the customer. It makes us work harder because, you know, you have to retain your customer sort of every 10 minutes. And that's something that, you know, as you said, with enterprise software and even some of the early SaaS vendors, that's not how it works. And so Amazon has forced us all to be very, very attentive to our customers. >> Dave: And I'd love to talk about what that means for the on-prem business, but if we have time. But you guys won Design Partner of the Year, what's that all about? First of all, congratulations. >> Anthony: Thank you. There's a lot of ISV design partners. You guys came out number one so congratulations on that. What's that all about? Explain what that entailed and how you got that. >> Yeah, I'll say a few words. Maybe Jonsi can add. I mean, the first thing of course is, you know, I S V stands for Independent Software Vendor. So, you know, it's always great because most people would say, "Well, NetApp is on-premise storage hardware." >> Dave: Of course, yeah. >> Which really, we've not really ever been an increasingly with demonstrating that we are a software company and we operate at cloud speed. You know, I can't really take the credit. I would give it to Jonsi and the engineering team. Maybe Jonsi, you can explain, you know, what moral about the award and why I think we were selected. >> So, I mean, I think it says a lot that this is the first time AWS has ever allowed a third party company to be this integrated into their console, into a support ability systems. You know, we make fun of this, me and Anthony all the time, because when we started this, down this path, everybody at NetApp said, "Guys, you're wasting your time." This is why AWS has the marketplace, but we didn't want to go. We already had the marketplace and we wanted to be able to connect to all these associated services and do within the manner that, you know, this was a true collaboration of engineering teams for a long time to actually deliver the service on both sides so the credit, of course, will always go to the engineers on both sides, even though I designed it, I didn't coat it. So, I think that, that alone, being the first to do it in AWS ever. I think we deserve that award. >> So just for our audience, to be clear, we're talking about FSx, ONTAP in the cloud, in the AWS cloud and kind of dance around that. But so that was announced, I guess, in September? >> Anthony: Yes. >> Right? >> Anthony: September, 2nd. >> What's the uptake been like? What's the reaction? >> Unbelievable. >> I'll bet. (laughing) >> No, no, I mean. >> No, I believe it. >> Better than we ever dreamed of. >> Yeah. >> The number of customers, I'm sure I'm not allowed to say the number of customers, but we asked and the fact that, you know, 60% of those customers have never been NetApp customers before, but they see the value in the data management capabilities that we are bringing to the market. >> Dave: So it exceeded expectations and your expectations were probably pretty enthusiastic. >> They were high. >> Yeah. >> I mean, Amazon is on the record. I was with Ed earlier on today, recording a piece and Ed, you know, was very clear that it's one of the fastest growing services now on AWS. You know, it turns out that, you know, the customer base, I think recognizes the, not just the need for a file system, but the uniqueness and capabilities that ONTAP provides, you know, to those customers in how they manage their business and transformations. And so, you know, to be sort of behind the console, to be sort of behind the Amazon CLI and the Amazon API, you see the world very, very differently, you know. I think the Amazon marketplace is a fantastic capability, but I'll tell you, you know, being a core part of the AWS service itself that they sell, that they support, that they bill for. It's a nice place to be. >> So, SaaS company. You're talking to the language of application development, Kubernetes, right? What do you think this means for the future of NetApp specifically, but also generally the on-prem storage business and the storage business in general? >> Well, we just announced our second quarter earnings today and what's happening is our cloud business is growing like crazy. We generated $388 million of ARR and the growth rates are, you know, astronomically high. That is increasingly helping our on-premise business to grow. You know, the nice thing about being in primarily, in the storage and data business is people aren't deleting many things. And the rate at which they're generating information is just accelerating. So, actually the confidence that we give the customer by demonstrating a sort of a cloud first, a sort of principles of all the cloud is actually giving customers to buy more on premise. So, we really don't mind. We are, our job much like Amazon's, is to have this customer obsession and you can't really go wrong, if you just keep asking them what they want. >> Yeah, if you can do so profitably, you're going to be reinvest in your business. Guys, we've got to go. >> Yeah. >> Love to have you back. >> Thank you. >> And you been quite a transformation. You said you're going to do it. You're doing it. So, well done to you. Five years in the making. Okay. This is Dave Vellante for theCUBE, the leader in high-tech coverage. Keep it right there. We'll be right back from AWS re:Invent 21. (upbeat music)

(upbeat music) >> Hello and welcome back to theCUBE's coverage of AWS Executive Summit at re:Invent 2021. I'm John Furrier, your host of theCUBE. This segment is about surviving and thriving with the digital revolution that's happening in the digital transformation that's turning into and changing businesses. We've got two great guests here with Guardian Life, Nick Volpe, CIO of Individual Markets at Guardian Life and Kim Gully, CTO of Life and Annuities at Accenture. Accenture obviously doing a lot of cutting-edge work, Guardian changing the game. Nick, thanks for coming on. Kim, thanks for coming on. >> Thanks John, good to be here. >> So, well, before I get into the question, I want to just set the table a little bit. The pandemic has given everyone a mandate. The good projects are exposed. The bad projects are exposed. Everyone can see what's happening because the pandemic forced everyone to identify what's working, what's not working, what the double-down on. Innovation for customers is a big focus, but now with the pandemic relieving and coming out of it, the world's changed. This is an opportunity for businesses. Nick, this is something that you guys are focused on. Can you take us through what Guardian Life's doing in this post pandemic changeover as cloud goes next level? >> Yeah, thanks John. So the immediate need in the pandemic situation was about the new business capability. So those familiar with insurance, traditionally life insurance underwriting, disability underwriting is very in-person, fluids, labs, attending physician statements. And when March of 2020 broke, that all came to an abrupt halt. Doctor's office were either closed. Testing centers were either closed or inundated with COVID testing. So we had to come up with some creative ways to digitize our new business, adopt the application, and adopt our medical questionnaires, and also get creative on some of our underwriting standards that put us at certain limits and certain levels and when we needed the fluids. So we are pretty quickly, we're agile about decisions there. And we moved from about 40 to 50% adoption rate of our electronic applications to the north of 98% across the board. In addition, we saw some opportunities for products and more capabilities beyond new business. So after we weathered the storm, we started to take a step back. And like you said, look at what we were doing, that have a start, stop, continue conversation internally to say, this digitization is a new norm. How do we meet it from every angle, not just a new business. And that's where we started to look at our policy administration systems, moving more to the cloud and leveraging the cloud to its fullest extent versus just a lifted shift. >> Kim, I want to get your perspective at Accenture. I've done a lot of interviews with the past, I think 18 months. A lot of use cases with Accenture, almost in every vertical where you guys are almost like the firefighters, get called in to like help out 'cause the cloud actually now is an enabler. How do you see the impact of the pandemic reverbing through? I mean, obviously you guys come to the table, you guys bring in, I mean, what's your perspective on this? >> So, yeah, it's really interesting. I think the most interesting fact is we talk about, Nick raise such a strong area in our business of underwriting and how can we expedite that, is being talked on the table for a number of years, but the industry has been very slow or reluctant to embrace. And the pandemic became an enforcer in it to be honest. And a lot of the companies were thinking about it prior, but that's it, they'll think about it. I mean, even Accenture, we launched a huge three-year investment to get clients into cloud and digital transformation, but the pandemic just expedited everything. Now the upside is clients that were in a well-advanced stage of planning, they were easily able to adopt, but clients that weren't, were really left behind. So we became very, very busy just supporting the clients that didn't have as much forethought as likes of Guardian, et cetera. >> Nick, it brings up a good point. I want to get your reaction to see if you agree. I mean, people who didn't put their toe in the cloud or just jump in the deep end, really got flat-footed when the pandemic hit, because they weren't prepared. People who were either ingratiated in with the cloud or having active projects or even being full deployments in there did well. What's your take on that? >> Yeah, the enablement we had and the gift we were given by starting our cloud journey, in I want to say 2016, 17 was we really started moving to the cloud. And I think we were the only insurer that moved production load to the cloud. At that point, most of insurers were putting their development environments, maybe even their SIT environments, but Guardian had the strategy of getting out of the data center or moving to a much more flexible, scalable environment architecture using the AWS cloud. So we completed our journey into the cloud by 2018, 19, and we were at the point of really capitalizing versus moving. So we were able to move very quickly, very nimbly. When the pandemic hit or in any digital situation, we have that flexibility and capacity that AWS provides us to really respond to our customers, our customers need. So we were one of the more fortunate insurers that were well into our cloud journey. And at the point of optimization versus the point of moving. >> Let's talk about the connection with Accenture's life insurance and annuity platform also known ALIP, I think the acronym is. What was that? Why was that relevant? What was that all about? >> Yeah, so I'll go first and then Kim, you can jump in and see if you agree with me. >> He essentially help that, love it. (laughs) >> Yeah, you would suspect you would, right John? >> Yeah. (laughs) >> Like I said, our new business focus was the original, like the emergency situation when the pandemic hit. But as we went further into it and realized the mortality and morbidity and the needs and wants of our customers, which is a major focus of Guardian, really being, having the client at the center of every conversation we have, we realized that there was a real opportunity for product and it's product continues to change and you had regulations like 7702 coming out where you had to reprice the entire portfolio to be able to sell it by January 1, 2022. We realized our current systems are for policy admin. We're not matching our digital capabilities that we had moved to the cloud. So we embarked on a very extensive RFP to Accenture and a few other vendors that would come to the table and work with us. And we just really got to a place where combination of our desire to be on the cloud, be flexible, and be capable for our customers, married really well with the knowledge, the industry knowledge and the capabilities that Accenture brought to the table with the ALIP platform. Their book of business, their current infrastructure, their configuration versus development, really all aligned with our need for flexible, fast time to market. We're looking to cut development times significantly. We're looking to cut test in times significantly. And as of right now, it's all proving true between the cloud capability and the ALIP capability. We are reaping the benefits of having this new platform coming up in live very soon here. >> Before I get to Accenture's perspective, I want to just ask you a quick follow-up on that, Nick, if you don't mind. You basically talk us through, okay, I can see what's happening here. You get with Accenture, take advantage of what they got going on. You get into the cloud, you start getting the efficiencies, get the cultural change. What refactoring have you seen? What's your vision, I should say. What's your vision around what's next? Because clearly there's a playbook. You get in the cloud, re-platform, you get the cultural fit, you understand the personnel issues, how to tap the resources, then you've got to look for innovation where you can start changing, how you do things to refactor the business model. >> Yeah, so I think that, specifically to this conversation, that's around the product capability. So for all too long, the insurance companies have had three specific sleeves of insurance products. We've had individual life. We have an individual disability and we'd have individual annuities. Each of them serving a specific purpose in the customer's lives. What this platform and this cloud platform allows us to do is start to think about, can we create the concept of a single wrapper? Can we bring some of these products together? Can we centralize the buying process? And with ALIP behind the scenes, you don't have that, I kind of equate it to building a Ferrari and attaching a trailer to it, and that's what we were doing today. Our digital front-ends, our new business capabilities are all being anchored down or slowed down by our traditional mainframe back-ends. By introducing Accenture on the cloud in AWS, we now have our Ferrari fully free to run as fast as it can versus anchoring this massive trailer to it. So it really was a matter of bringing our product innovation to our digital front-end innovation that we've been working on for two or three years prior. >> I mean, this is the kind of the Amazon way. You decouple things, you decompose, you don't want to have a drag. And with containers, we're seeing companies look at existing legacy in a way that's different. Could you talk about how you guys look at that Nick internally because a lot of CIO's are saying, Hey, you know what? I can have the best of both worlds. I don't have to kill the old to bring in the new, but I can certainly modernize everything. What's your reaction to that? >> Yeah. And I think that's our exact path forward. We don't feel like we need to blow the ocean. We're going after this surgically for the things that we think are going to be most impactful to our customers. So legacy blocks of business that are sitting out there, that are for completely closed, they're not our concern. It's really hitching this new ALIP capability to the next generation of products, the next generation of customer needs, understanding data. Data capture is very important. So if you look at the mainframes and what we're living on now, it's all about the owner of the policy. You lose connection with the beneficiary or the insured. What these new platforms allowed us to do is really understand the household around the products that they're buying. I know it sounds simple, but that data architecture, that data infrastructure on these newer platforms and in the cloud, you can churn it faster, you have scale to do more analysis, but you're also able to capture in a much cleaner way. On the traditional systems, you're talking about what we call intimately the blob on the mainframe that has your name, your first name, your last name, your address, all in one free form field sitting in some database. It's very hard to discern. On these new platforms, given our need and our desire to be deeper into the client's lives, understanding their needs, ALIP coupled with AWS, with our new business capabilities on the front-end really puts together that true customer value chain. That's going to differentiate us. >> Kim, okay, CTO of ALIP as he calls it, the acronym for the service you have. This is a great example. I hate to use the word on-ramp cause that sounds so old. But in a way, in vertical markets, you're seeing the power of the cloud because the data and the AI could be freed up and you can take advantage of all the heavy lifting by providing some platform or some support with Amazon, your expertise. This is a great use case of that, I think. And this is I think a future trend where the developments can be faster, that value can be faster, and your customers don't have to build all the lower level abstractions, if you will. Can you describe the essential relationship to your customers as you guys? Because this is a real great use case. >> Yeah, it is. Our philosophy is simple. Let's not reinvent the wheel. And with cloud and native services that AWS provide, we want to focus on the business of what the system needs to do and not all the little side bits. We can get a great service that's fully managed, that has security patches updates. We want to focus on the real deal. Like Nick wants to focus on the business and not so much what's underneath it. That's my problem, I'm focusing on that. And we will work together in a nice little gel. You've had the relatively new term, no code/low code. It's strange. A modern system like ALIP has been that way for a number of years. Basically it means, I don't want to make code changes. I just want to be able to configure it. So now more people can have access to make change, and we can even get it to the point where it's the people that are sitting there, dealing with the clients. That would be the ultimate, where they can innovate and come up with ideas and try things because we've got it so simple. We're not there yet, let's be realistic, but that's the ultimate goal. So ALIP, the no code/low code has been around for quite some time. And maybe we should take advantage of that, but I think we're missing one thing. So as good as the platform is, the cloud moving in, calculating native services using the built-in security that comes with all that and extending the function and then be able to tap into the InsurTech, FinTech, internet of things, and quickly adapt. I think the partnership is big. Okay, it's very strong part of the exercise. So you can add the product, but without the people that work well together, I think it's also a big challenge. All programs have their idiosyncrasies and there's a lot of challenges along the way. There's one really small simple example I can use. I'd say Guardian is one of our industries market leaders when they approach the security. They really do lead the way out there. They're very strict, very responsible, which is such a pleasure to say, but at the end of the day, you still need to run a business. So, 'cause we're a partnership because we all have the same challenges, we want to get to success. We were able to work together quite quickly. We planned out the right approach that maximize the security, but it also progressed the business and we applied that into the overall program. So I think it is a product definitely. I think it is everything Nick said, you actually elaborated on, but I'd like to point out, there's a big part of the partnership to make it a success as well. >> Yeah, great, great call out there. Nick, let's get your reaction on that because I want to get it to the customer side of it. This enablement platform is the new, I mean, platform has been around for awhile, but the notion of buying tools and having platforms are now interesting 'cause you have to take this low code/no code capability. I mean, you still got a code. I mean, there's some coding going on, but what it means is ease of use composing and being fast. Platforms are super important. That requires real architecture and partnership. What's your reaction? >> Yeah, so I think I'll tie it all together between AWS and ALIP, and here's the beauty of it. So we have something called LaunchPad where we're able to quickly stand up in ALIP instance for development capabilities because of our Amazon relationship. And then to Kim's point, we have been successful with 85% or more, of all the work we've done with an ALIP is configuration versus code and I'd actually I'd venture to say 90%. So that's extremely powerful when you think about the speed to market and our need to be product innovative. So if our developers and even our analysts that sit on the business side could come in and quickly stand up a development environment, start to play with actuarial calculations, new product features and function and then spin that to a more higher-end development environment. You now have the perfect coupling of a new policy administration system that has a flexibility and configuration with a cloud provider like Amazon and AWS that allows us to move quickly with environments, whereas in days past, you'd have to have an architecture team come in and stand up the servers. And I'm going way back, but like buy the boxes, put the boxes in place and wire them down. This combination of ALIP and AWS has really brought a new capability to Guardian and we're really excited about. >> I love that little comparison. Let me just quickly ask you, compared to the old way, give us an order of magnitude of pain and timing involved versus what you just described as standing up something very quickly and getting value and having people shift their intellectual capital into value activities versus undifferentiated heavy lifting. >> Yes, I'll give you real dates. So we really engaged with Accenture on the ALIP program right before Thanksgiving of last year. We had our environment stood up and running, all of our DEV, SIT, UAT up by February, March timeframe on AWS and we are about to launch our first product configuration into the ALIP platform coming November. So within a year, we've taken arguably decades of product innovation from our mainframes and built it onto the ALIP platform on the Amazon cloud. So I don't know that you can do that in any other type of environment or partnership. >> That's amazing. That's just great example to me where cloud scale and real refactoring and business agility is plays out. So congratulations. I got to ask you now, on the customer side you mentioned, you guys love providing value to the customers. What is the impact to the customer? Okay, now you're a customer, Guardian Life's customer. What's the impact to them? Can you share how you see that rendering itself in the marketplace? >> Yeah, so clearly AWS has rendered tons of value to the customer across the value stream whether it be our new business capability, our underwriting capability, our ability to process data and use their scale. I mean, it just goes on and on about the AWS, but specifically around ALIP, the new API environment that we have, the connectivity that we can now make with the new back-end policy admin systems has really brought us to a new level, whether it be repricing, product innovation, responding to claims capabilities, responding to servicing capabilities that the customer might need. We're able to introduce more self-service. So if you think about it from the back-end policy admin going forward to our client portal, we're able to expose more transactions to self-serve. So minimize calls to the call center, minimize frustration of hold times and allow them to come onto the portal and do more and interact more with their policies because we're on this new, more modern cloud environment and a new more modern policy admin. So we're delivering new capabilities to the customer from beginning to end being on the cloud with ALIP. >> Okay, final question. What's next for Guardian Life's journey year with Accenture? What's your plans? What do you want to knock down for the next year? What's on your mind? What's next? >> So that's an easy question. We've had this roadmap plan since we first started talking to Accenture, at least I've had it in my head. We want off all of our policy admin systems for new business come end of 2025. So we've got about four policy admin systems maintaining our different lines of business, our individual disability, our life insurance, and our annuities, for systems that are weighing us down a little bit. We have a glide path and a roadmap with Accenture as a partner to get off of all of these for new business capability by end of 2024. And I'm being gracious to my teams when I say that I'd like to go a little bit sooner. And then we begin to migrate the most important blocks of business that caused the most angst and most concerned with the executive leadership team and then complete the product. But along the way, given regulation, given new customer needs, meeting the needs of the customer's changing life, we're going to have parallel tracks. So I envision we continue to have this flywheel turning of moving, but then we begin another flywheel right next to it that says we're going to innovate now on the new platform as well. So ultimately John, next year, if I could have my entire whole life block, as it stands today on the new admin platform, and one or two new product innovations on the platform as well by the 3rd quarter, 4th quarter of next year, that would be a success as far as I'm concerned. >> Awesome, you guys had all planned out. I love, and I have such a passion for how technology powers business. And this is such a great story for next gen where the modernization trend is today and where it's going. So Nick appreciate it. Kim, thanks for coming out with Accenture. Nick, so just an easy question for you. I have to ask you another one. This is I got you here. You guys are doing a lot of great work. For other CIOs out there that are going through this right now, whatever they are on the spectrum, missed the CloudWave, getting in now, this notion of refactoring and then re-platforming and then refactoring business is a playbook we're seeing emerge. People can get the benefits of going to the cloud, certainly for efficiency, but now it opens up the aperture for different kinds of business models. With more data access, with machine learning. This refactoring seems to be the new hot thing where the best minds are saying, wow, we could do more, even more. What's your vision? How would you share those folks out there of the CIOs? What should they be thinking? What's their approach? What advice would you give? >> Yeah, so a lot of the mistakes we make as CIOs, we go for the white hot core first. We went the other way. We went for the newer digital assets. We went for the stuff that wasn't as concerning to the business. Should we fall over? Should there be an outage? Should there be anything? So if you avoid the white hot core, improve it with your peripherals, easier moves to the cloud portals, broker portals, beneficiary portals, simple AIX frames, moving to the cloud and making them cloud native, new builds. So we started with all those peripheral pieces of the architecture and we avoided the white hot core because that's where you start to get those very difficult conversations about, I don't know if I'm ready to move. And I don't see the obvious benefit of moving a dividend generating policy admin system to the cloud, like why? When you prove it in the pudding and you put the other things out there and prove you can be successful, the conversation to move your core and your white hot core out to the platform out to leverage the cloud and to leverage new admin platforms, it becomes a much easier conversation because you've kind of cut your teeth on something much less detrimental to the business should it go alright. >> What's the old expression, put water through the pipes, get some reps in and get the team ready to bring training, whatever your metaphor you use, that's what you're essentially saying there. Get some, your sea legs, get practice. >> Exactly. >> Then go for the hard stuff. >> It's such a valid point, John. We see a lot of different approaches across a lot of different companies and the biggest challenges, the core is the biggest part. And if you start with that, it can be the scariest part. And I've seen companies trip up big time and it becomes such a bubble spend, which really knocks you on for years, lose confidence in your strategy and everything else. And you're only as strong as your weakest link. So whether you do the outside first or the inside first, from a weakest link until the journey is complete, you never going to maximize. So it was a very different and new and great approach that they took by doing a learning curve around the easiest stuff and then hit in the core. >> Yeah, well, that's a great point. One quick, quick followup on that is that, talk about the impact to the personnel, Kim and Nick, because there's a morale issue going on too. There's a training. I won't say training, but there's a not re-skilling, but there's the rigor, if you're refactoring, you are re-skilling, you're doing new things. The impact of morale and confidence you get certainly. you don't want to be in the white core unconfident. >> Maybe I should get first 'cause it's Nick's stuff. So he probably might want to say a lot, yeah. What we see with a lot of insurance companies, they grow through acquisition. Okay, they're very large companies, grown over time, buying companies with businesses and systems and bringing it in. They usually bring a tenure staff. So getting the staff to the next generation, that staff is extremely important because they know everything that you've got today and then not so aware with what's coming up in the future. And there is a transition and people shouldn't feel threatened, but there is change and people do need to adopt and evolve and it should be fun and interesting, but it is a challenge at that turnover point on who controlling what, and then you get the concerns and get paranoid. So it is a true HR issue that you need to manage through. >> Nick you're the final word here. Go for it. >> Yeah, John. I'll give you a story that I think will sum the whole thing up about the excitement versus contention we see here at Guardian. I have a 50-year veteran on my legacy platform team and this person is so excited, got themselves certified in Amazon and is now leading the charge to bring our mainframes onto ALIP and is one of the most essential, and I've actually had Accenture tell me, if I had a person like this on every one of my engagements who is not only knowledgeable of the legacy, but is so excited to move to the new, I don't think I'd have a failed implementation. So that's the kind of Guardian, the kind of backing Guardian's putting behind this. We are absolutely focusing on rescaling. We are not going to the market. We're giving everyone the opportunity and we have an amazing take-up rate. And again, like I said, 50-year veteran who probably could have retired 10 years ago is so excited, reeducated themselves and is now a key part of this implementation. >> And who wouldn't want to drive a Ferrari when you see it come in. I mean, back in the trailer. Great story, Nick. Thank you for coming on, great insight. Kim, great stuff for the Accenture, as always a great story here. We're here at the heart of the real focus where all companies are feeling right now. We're surviving and thriving and coming out of the pandemic with a growth strategy and a business model powered by technology. So thanks for sharing the story, appreciate it. >> Thanks John, appreciate it. >> Okay, it's CUBE coverage of AWS Executive Summit at re:Invent 2021. I'm John Furrier, your host of theCUBE. Thanks for watching. (bright music)

>>no real filter and that kind of stuff. But you're also an entrepreneur, right? And you know the business, you've been in software, you detect business. I'm instructing you get a lot of pictures, this entertainment business on our show, we're a bubble. We don't do a lot of tech deals that were talking because it's boring tv tech people love tech consumers love the benefit of text. No consumer opens up their iphone and says, oh my gosh, I love the technology behind my, what's it been like being on the shark tank? You know, filming is fun and hang out just fun and it's fun to be a celebrity at first your head gets really big and you get a really good tables at restaurants and who says texas has got a little possessed more skin in the game today in charge of his destiny. Great robert Herjavec. No, these two stars cube alumni >>welcome back to the cubes coverage of A W. S. Public sector seven. I'm john for your host of the cube got a great segment here on healthcare startup accelerators of course. Sandy carter is co hosting media. This one Vice President Aws. She's awesome on the cuBA and jennifer Blumenthal co founder and C of one record entrepreneur, very successful. Thanks for coming on jennifer. Thank good to see you. Sandy thanks for joining me again. You >>are most welcome, >>jennifer. Before we get into the whole accelerated dynamic, just take a minute to explain what you guys do. One record. >>Sure. So one record is a digital health company that enables users to access aggregate and share their healthcare information. So what that means is we help you as a person get your data and then we also help companies who would like to have workflows were consumers in the loop to get their data. So whether they're sharing it with a provider, researcher payer. >>So, Sandy, we've talked about this amazon web services, healthcare accelerator cohort batches. What do you call cohort batches? Cohorts explain what's going on with the healthcare accelerator? >>Yeah. So, um, we decided that we would launch and partner an accelerator program and accelerator program just provides to a start up a little bit extra technical help. A little bit extra subject matter expertise and introductions to funders. And so we decided we were going to start one for health care. It's one of the biggest disruptive industries in public sector. Um, and so we weren't sure how it's gonna go. We partnered with Kids X. Kids X is part of the Los Angeles system for medical. And so we put out a call for startups and we had 427 startups, we were told on average and accelerating it's 50-100. So we were blown away 31 different countries. So it was really amazing. And then what we've been doing is down selecting and selecting that Top 10 for our first cohort. So we're going from 427 down to 10. And so obviously we looked at the founders themselves to see the quality of the leadership of the company, um the strength of their technology and the fit of the technology into the broader overall healthcare and healthcare ecosystem. And so we were thrilled that jennifer and one record was one of the top 10 start ups in this space that we chose to be in the, in the cohort. And so now we're going to take it to the six weeks intensive where we'll do training, helping them with AWS, provide them A W. S. Credits and then Kid X will also provide some of the health care uh subject matter >>expertise as well. Can I get some of those credits over here to maybe? >>Yes, you can actually, you can talk to me don you can't >>Talk to me, Jennifer, I gotta ask you. So you're an entrepreneur. So doing start doing cos it's like a roller coaster. So now to make the top 10 but also be in the area of his accelerator, it's a partnership, right? You're making a bet. What's your take on all this? >>Well, we've always been partners with a W. S. We started building on AWS in the very beginning. So when I was setting up the company a huge decision early on with infrastructure and when I saw the launch of the accelerator, I had to apply because we're at the point in the company that we're growing and part of growing is growing with the VW. So I was really excited to take advantage of that opportunity and now in the accelerator, it's more of thinking about things that we weren't thinking about the services that we can leverage to fill in the gaps within our platform so we can meet our customers where they are >>using award winning MSP cloud status city, your partners, great relationship with the ecosystem. So congratulations Sandi. What's the disruption for the healthcare? Because right now education and health care, the two top areas we're seeing and we're reporting on where cloud scale developed two point or whatever buzzword digital transformation you want to use is impacting heavily healthcare industry. There's some new realities. What's your, what's your vision, what's your view? >>Hey john before she does that, I have to give a plug to Claudius city because they just made premier partner as well, which is a huge deal. Uh and they're also serving public sector. So I just wanted to make sure that you knew that too. So you can congratulate. Go ahead, jennifer >>Well, so if I zoom in, I think about a P. I. S. Every day, that's what I think about and I think about microservices. So for me and for one record, what we think about is legislation. So 21st century Cures act says that you as a consumer have to be able to access your healthcare data from both your providers and from your players and not just your providers, but also the underlying technology vendors and H. I. E. S. H. I am and it's probably gonna extend to really anyone who plays within the healthcare ecosystem. So you're just going to see this explosion of A. P. I. S. And we're just your one of that. I mean for the payers that we went into effect on july 1st. So I mean when you think about the decentralization of healthcare where healthcare is being delivered plus an api economy, you're just going to have a whole new model developing and then throwing price transparency and you've got a whole new cake. >>I'm smiling because I love the peacocks. In fact, last night I shouldn't have tweeted this but there's a little tweet flames going on around A. P. Is being brittle and all this stuff and I said, hey developer experience about building great software apps are there for you. It's not a glue layer by itself. You got to build software around the so kind of a little preaching to the younger generation. But this health care thing is huge because think about like old school health care, it was anti ap I was also siloed. So what's your take on has the culture is changing health care because the user experience, I want my records, I want my privacy, I want to maintain everything confidential but access. That's hard. >>I think well health care to be used to just be paper was forget about a. P. I. Is it was just paper records. I think uh to me you think about uh patient journey, like a patient journey starts with booking an appointment and then everything after that is essentially an api call. So that's how I think about it is to all these micro transactions that are happening all the time and you want your data to go to your health care provider so they can give you the proper care, you want your data to go to your pair so they can pay for your care and then those two stakeholders want your data so that they can provide the right services at the right time to the right channel. And that is just a series of api calls that literally sits on a platform. >>What's interesting, I'd love to get your take on the where you think the progress bar is in the industry because Fintech has shown the way you got defy now behind a decentralized finance, health care seems to be moving on in a very accelerated rate towards that kind of concept of cloud, scale, decentralization, privacy. >>Yeah, I mean, that's a big question, what's interesting to me around that is how healthcare stakeholders are thinking about where they're providing care. So as they're buying up practices primary care specialty care and they're moving more and more outside of the brick and mortar of the health care system or partnering with your startups. That's really where I think you're going to see a larger ecosystem development, you could just look at CVS and walmart or the dollar store if they're going to be moving into health care, what does that look like? And then if you're seeking care in those settings, but then you're going to Mayo clinic or Kaiser permanente, there's so many new relationships that are part of your hair circle >>delivery is just what does that even mean now, delivery of health >>care. It's wherever you it's like the app economy you want to ride right now, you want a doctor right now, that's where we're heading its ease of use. >>This is this exciting startups, changing the game. Yes, I love it. I mean, this is what it's all about this health >>Care, this is what it's all about. And if you look at the funding right now from VCS, we're seeing so much funding pour into health care, we were just looking at some numbers and in the second quarter alone, the funding went up almost 700%. And the amount of funding that is pouring into companies like jennifer's company to really transform healthcare, 30% of it is going into telehealth. So when you talked about, you know, kind of ai at the edge, getting the right doctor the right expert at the right time, we're seeing that as a big trend in healthcare to >>well jennifer, I think the funding dynamics aside the opportunity for market total addressable market is massive when the application is being decomposed, you got front end, whether it's telemedicine, you got the different building blocks of healthcare being radically reconfigured. It's a re factoring of healthcare. Yeah, >>I think if you just think about where we're sitting today, you had to use an app to prove proof of vaccination. So this is not just national, this is a global thing to have that covid wallet. We at one record have a covid wallet. But just a couple years from now, I need more than just by covid vaccination. I need all my vaccinations. I need all my lab results. I need all my beds. It's opening the door for a new consumer behavior pattern, which is the first step to adoption for any technology. >>So somebody else covid wallet. So I need >>that was California. Did the, did a version of we just have a pen and it's pretty cool. Very handy. I should save it to my drive. But my phone, but I don't jennifer, what's the coolest thing you're working on right now because you're in the middle of all the action. >>I get very excited about the payer app is that we're working on. So I think by the end of the month we will be connected to almost to all the blues in the United States. So I'm very excited when a user comes into the one record and they're able to get their clinical data from the provider organization and then their clinical financial and formulary data from their payers because then you're getting a complete view, You're getting the records for someone who gave you care and you're getting the records from someone who paid for your care. And that's an interesting thing that's really moving towards a complete picture. So from a personal perspective that gets exciting. And then from a professional perspective, it's really working with our partners as they're using our API s to build out workflows and their applications. >>It's an api economy. I'd like to ask you to on the impact side to the patient. I hear a lot of people complaining that hey, I want to bring my records to the doctor and I want to have my own control of my own stuff. A lot of times, some doctors don't even know other historical data points about a patient that could open up a diagnosis and, or care >>or they can't even refer you to a doctor. Most doctors really only refer within a network of people that they know having a provider directory that allows doctors refer, having the data from different doctors outside of their, you know, I didn't really allows people to start thinking beyond just their little box. >>Cool. Well, great to have you on and congratulations on being in the top 10 saying this is a wonderful example of how the ecosystem where you got cloud city, your MSP. You mentioned the shout out to them jerry Miller and his team by working together the cloud gives you advantages. So I have to ask, we look at amazon cloud as an entrepreneur. It's kind of a loaded question, but I'm going to ask it. I love it. >>You always do it >>when you look at amazon, what do you see as opportunities as an entrepreneur? Because I'll see the easy ones. They have computing everything else. But like what's the, what does cloud do for you as an entrepreneur? What does it, what does it make you do? >>Yeah. So for been working with jerry since the beginning for me when I think about it, it's really the growth of our company. So when we start building, we really just thinking about it from a monolithic build and we move to microservices and amazon has been there every step of the way to support us as that. And now, you know, the things that I'm interested in are specifically health lake and anything that's NLP related that we could plug into our solution for when we get data from different sources that are coming in really unstructured formats and making it structured so that it's searchable for people and amazon does that for us with their services that we can add into the applications. >>Yeah, we announced that data health like and july it has a whole set of templates for analytics, focused on health care as well as hip hop compliance out of the box as well. >>The I think I think that's what's important is people used to think application first. Now it's creating essentially a data lake, then analytics and then what applications you build on top of that. And that's how our partners think about it and that's how we try and service them using amazon as our problem. So >>you're honing in on the value of the data and how that conflicts and then work within the whatever application requests might come >>in. Yes, >>it's interesting. You know, we had an event last month and jerry Chen from Greylock partners came on and gave a talk called castles in the cloud. He's gonna be cute before. He's a, he's a veces, they talk about moats and competitive manage so having a moat, The old school perimeter moz how cloud destroyed that. He's like, no, now the castles are in the cloud, he pointed snowflake basically data warehouse in the cloud red shifts there too. But they can be successful. And that's how the cloud, you could actually build value, sustainable value in the cloud. If you think that way of re factoring not just hosting a huge, huge, huge thing. >>I think the only thing he, this was customer service because health care is still very personal. So it's always about how you interact with the end user and how you can help me get to where they need to be going >>and what do you see that going? Because that's, that's a good point. >>I think that is a huge opportunity for any new company that wants to enter healthcare, customer service as a service in health care for all the different places that health care is going to be delivered. Maybe there's a company that I don't know about, but when they come out, I'd like to meet them. >>Yeah, I mean, I can't think of one cover that can think of right now. This is what I would say is great customer service for health care. >>And if there is one out there contacted me because I want to talk to you about AWS. >>Yeah. And you need the app from one record that make it all >>happen. That's where Omni channel customer service across all health care entities. Yeah, that's >>a great billion dollar idea for someone listening to our show right now. >>Right, alright. So saying they had to give you the opportunity to talk more because this is a great example of how the world's very agile. What's the next step for the AWS Healthcare accelerator? Are there more accelerators? Do you do it by vertical? >>What happens next? So, with the healthcare accelerator, this was our first go at the accelerator. So, this is our first set of cohorts, Of course, all 427 companies are going to get some help from a W. S. as well. We also you'll love this john We also did a space accelerator. Make sure you ask Clint about that. So we have startups that are synthesizing oxygen on mars to sending an outpost box to the moon. I mean, it's crazy what these startups are doing. Um, and then the third accelerator we started was around clean energy. So sustainability, we sold that one out to, we had folks from 66 different countries participate in that one. So these have been really successful for us. So it reinvent. When we talk again, we'll be announcing a couple of others. So right now we've got healthcare, space, clean energy and we'll be announcing a couple other accelerators moving forward. >>You know, it's interesting, jennifer the pandemic has changed even our ability to get stories. Just more stories out there now. So you're seeing kind of remote hybrid connections, ap ideas, whether it's software or remote interviews or remote connections. There's more stories being told out there with digital transformation. I mean there wasn't that many before pandemic has changed the landscape because let's face it, people were hiding some really bad projects behind metrics. But when you pull the pandemic back and you go, hey, everyone's kind of emperors got no clothes on. Those are bad projects. Those are good projects that cloud investment worked or I didn't have a cloud investment. They were pretty much screwed at that point. So this is now a new reality of like value, you can't show me value. >>It's crazy to me when I meet people who tell me like we want to move to the cloud of like, why are you not on the cloud? Like this really just blows my life. Like I don't understand why you have on prem or while you did start on the cloud, this is more for larger organizations, but younger organizations, you know, the first thing you have to do, it's set up that environment. >>Yeah. And then now with the migration plans and seeing here, uh whereas education or health care or other verticals, you've got, now you've got containers to give you that compatibility and then you've got kubernetes and you've got microservices, you've got land. Uh I mean, come on, that's the perfect storm innovation. There's no excuses in my opinion. So, you know, if you're out there and you're not leveraging it, then you're probably gonna be out of business. That's my philosophy. Thank you for coming up. Okay. Sandy, thank you. Thank you, john Okay. Any of his coverage here, summit here in D. C. I'm john ferrier. Thanks for watching. Mm >>mm mm mhm. I have been in the software and technology industry for over 12 years now, so I've had >>the opportunity

(upbeat music) >> Welcome back to AWS storage day. This is the Cubes continuous coverage. My name is Dave Vellante, and we're going to talk about file storage. 80% of the world's data is in unstructured storage. And most of that is in file format. Devs want infrastructure as code. They want to be able to provision and manage storage through an API, and they want that cloud agility. They want to be able to scale up, scale down, pay by the drink. And the big news of storage day was really the partnership, deep partnership between AWS and NetApp. And with me to talk about that as Ed Naim, who's the general manager of Amazon FSX and Anthony Lye, executive vice president and GM of public cloud at NetApp. Two Cube alums. Great to see you guys again. Thanks for coming on. >> Thanks for having us. >> So Ed, let me start with you. You launched FSX 2018 at re-invent. How has it being used today? >> Well, we've talked about MSX on the Cube before Dave, but let me start by recapping that FSX makes it easy to, to launch and run fully managed feature rich high performance file storage in the cloud. And we built MSX from the ground up really to have the reliability, the scalability you were talking about. The simplicity to support, a really wide range of workloads and applications. And with FSX customers choose the file system that powers their file storage with full access to the file systems feature sets, the performance profiles and the data management capabilities. And so since reinvent 2018, when we launched this service, we've offered two file system choices for customers. So the first was a Windows file server, and that's really storage built on top of Windows server designed as a really simple solution for Windows applications that require shared storage. And then Lustre, which is an open source file system that's the world's most popular high-performance file system. And the Amazon FSX model has really resonated strongly with customers for a few reasons. So first, for customers who currently managed network attached storage or NAS on premises, it's such an easy path to move their applications and their application data to the cloud. FSX works and feels like the NAZA appliances that they're used to, but added to all of that are the benefits of a fully managed cloud service. And second, for builders developing modern new apps, it helps them deliver fast, consistent experiences for Windows and Linux in a simple and an agile way. And then third, for research scientists, its storage performance and its capabilities for dealing with data at scale really make it a no-brainer storage solution. And so as a result, the service is being used for a pretty wide spectrum of applications and workloads across industries. So I'll give you a couple of examples. So there's this class of what we call common enterprise IT use cases. So think of things like end user file shares the corporate IT applications, content management systems, highly available database deployments. And then there's a variety of common line of business and vertical workloads that are running on FSX as well. So financial services, there's a lot of modeling and analytics, workloads, life sciences, a lot of genomics analysis, media and entertainment rendering and transcoding and visual effects, automotive. We have a lot of electronic control units, simulations, and object detection, semiconductor, a lot of EDA, electronic design automation. And then oil and gas, seismic data processing, pretty common workload in FSX. And then there's a class of, of really ultra high performance workloads that are running on FSX as well. Think of things like big data analytics. So SAS grid is a, is a common application. A lot of machine learning model training, and then a lot of what people would consider traditional or classic high performance computing or HPC. >> Great. Thank you for that. Just quick follow-up if I may, and I want to bring Anthony into the conversation. So why NetApp? This is not a Barney deal, this was not elbow grease going into a Barney deal. You know, I love you. You love me. We do a press release. But, but why NetApp? Why ONTAP? Why now? (momentary silence) Ed, that was to you. >> Was that a question for Anthony? >> No, for you Ed. And then I want to bring Anthony in. >> Oh, Sure. Sorry. Okay. Sure. Yeah, I mean it, uh, Dave, it really stemmed from both companies realizing a combined offering would be highly valuable to and impactful for customers. In reality, we started collaborating in Amazon and NetApp on the service probably about two years ago. And we really had a joint vision that we wanted to provide AWS customers with the full power of ONTAP. The complete ONTAP with every capability and with ONTAP's full performance, but fully managed an offer as a full-blown AWS native service. So what that would mean is that customers get all of ONTAP's benefits along with the simplicity and the agility, the scalability, the security, and the reliability of an AWS service. >> Great. Thank you. So Anthony, I have watched NetApp reinvent itself started in workstations, saw you go into the enterprise, I saw you lean into virtualization, you told me at least two years, it might've been three years ago, Dave, we are going all in on the cloud. We're going to lead this next, next chapter. And so, I want you to bring in your perspective. You're re-inventing NetApp yet again, you know, what are your thoughts? >> Well, you know, NetApp and AWS have had a very long relationship. I think it probably dates now about nine years. And what we really wanted to do in NetApp was give the most important constituent of all an experience that helped them progress their business. So ONTAP, you know, the industry's leading shared storage platform, we wanted to make sure that in AWS, it was as good as it was on premise. We love the idea of giving customers this wonderful concept of symmetry. You know, ONTAP runs the biggest applications in the largest enterprises on the planet. And we wanted to give not just those customers an opportunity to embrace the Amazon cloud, but we wanted to also extend the capabilities of ONTAP through FSX to a new customer audience. Maybe those smaller companies that didn't really purchase on premise infrastructure, people that were born in the cloud. And of course, this gives us a great opportunity to present a fully managed ONTAP within the FSX platform, to a lot of non NetApp customers, to our competitors customers, Dave, that frankly, haven't done the same as we've done. And I think we are the benefactors of it, and we're in turn passing that innovation, that, that transformation onto the, to the customers and the partners. >> You know, one is the, the key aspect here is that it's a managed service. I don't think that could be, you know, overstated. And the other is that the cloud nativeness of this Anthony, you mentioned here, our marketplace is great, but this is some serious engineering going on here. So Ed maybe, maybe start with the perspective of a managed service. I mean, what does that mean? The whole ball of wax? >> Yeah. I mean, what it means to a customer is they go into the AWS console or they go to the AWS SDK or the, the AWS CLI and they are easily able to provision a resource provision, a file system, and it automatically will get built for them. And if there's nothing that they need to do at that point, they get an endpoint that they have access to the file system from and that's it. We handle patching, we handle all of the provisioning, we handle any hardware replacements that might need to happen along the way. Everything is fully managed. So the customer really can focus not on managing their file system, but on doing all of the other things that they, that they want to do and that they need to do. >> So. So Anthony, in a way you're disrupting yourself, which is kind of what you told me a couple of years ago. You're not afraid to do that because if we don't do it, somebody else is going to do it because you're, you're used to the old days, you're selling a box and you say, we'll see you next time, you know, three or four years. So from, from your customer's standpoint, what's their reaction to this notion of a managed service and what does it mean to NetApp? >> Well, so I think the most important thing it does is it gives them investment protection. The wonderful thing about what we've built with Amazon in the FSX profile is it's a complete ONTAP. And so one ONTAP cluster on premise can immediately see and connect to an ONTAP environment under FSX. We can then establish various different connectivities. We can use snap mirror technologies for disaster recovery. We can use efficient data transfer for things like dev test and backup. Of course, the wonderful thing that we've done, that we've gone beyond, above and beyond, what anybody else has done is we want to make sure that the actual primary application itself, one that was sort of built using NAS built in an on-premise environment an SAP and Oracle, et cetera, as Ed said, that we can move those over and have the confidence to run the application with no changes on an Amazon environment. So, so what we've really done, I think for customers, the NetApp customers, the non NetApp customers, is we've given them an enterprise grade shared storage platform that's as good in an Amazon cloud as it was in an on-premise data center. And that's something that's very unique to us. >> Can we talk a little bit more about those, those use cases? You know, both, both of you. What are you seeing as some of the more interesting ones that you can share? Ed, maybe you can start. >> Yeah, happy to. The customer discussions that we've, we've been in have really highlighted four cases, four use cases the customers are telling us they'll use a service for. So maybe I'll cover two and maybe Anthony can cover the other two. So, the first is application migrations. And customers are increasingly looking to move their applications to AWS. And a lot of those are applications work with file storage today. And so we're talking about applications like SAP. We're talking about relational databases like SQL server and Oracle. We're talking about vertical applications like Epic and the healthcare space. As another example, lots of media entertainment, rendering, and transcoding, and visual effects workload. workflows require Windows, Linux, and Mac iOS access to the same set of data. And what application administrators really want is they want the easy button. They want fully featured file storage that has the same capabilities, the same performance that their applications are used to. Has extremely high availability and durability, and it can easily enable them to meet compliance and security needs with a robust set of data protection and security capabilities. And I'll give you an example, Accenture, for example, has told us that a key obstacle their clients face when migrating to the cloud is potentially re-architecting their applications to adopt new technologies. And they expect that Amazon FSX for NetApp ONTAP will significantly accelerate their customers migrations to the cloud. Then a second one is storage migrations. So storage admins are increasingly looking to extend their on-premise storage to the cloud. And why they want to do that is they want to be more agile and they want to be responsive to growing data sets and growing workload needs. They want to last to capacity. They want the ability to spin up and spin down. They want easy disaster recovery across geographically isolated regions. They want the ability to change performance levels at any time. So all of this goodness that they get from the cloud is what they want. And more and more of them also are looking to make their company's data accessible to cloud services for analytics and processing. So services like ECS and EKS and workspaces and App Stream and VMware cloud and SageMaker and orchestration services like parallel cluster and AWS batch. But at the same time, they want all these cloud benefits, but at the same time, they have established data management workflows, and they build processes and they've built automation, leveraging APIs and capabilities of on-prem NAS appliances. It's really tough for them to just start from scratch with that stuff. So this offering provides them the best of both worlds. They get the benefits of the cloud with the NAS data management capabilities that they're used to. >> Right. >> Ed: So Anthony, maybe, do you want to talk about the other two? >> Well, so, you know, first and foremost, you heard from Ed earlier on the, the, the FSX sort of construct and how successful it's been. And one of the real reasons it's been so successful is, it takes advantage of all of the latest storage technologies, compute technologies, networking technologies. What's great is all of that's hidden from the user. What FSX does is it delivers a service. And what that means for an ONTAP customer is you're going to have ONTAP with an SLA and an SLM. You're going to have hundreds of thousands of IOPS available to you and sub-millisecond latencies. What's also really important is the design for FSX and app ONTAP was really to provide consistency on the NetApp API and to provide full access to ONTAP from the Amazon console, the Amazon SDK, or the Amazon CLI. So in this case, you've got this wonderful benefit of all of the, sort of the 29 years of innovation of NetApp combined with all the innovation AWS, all presented consistently to a customer. What Ed said, which I'm particularly excited about, is customers will see this just as they see any other AWS service. So if they want to use ONTAP in combination with some incremental compute resources, maybe with their own encryption keys, maybe with directory services, they may want to use it with other services like SageMaker. All of those things are immediately exposed to Amazon FSX for the app ONTAP. We do some really intelligent things just in the storage layer. So, for example, we do intelligent tiering. So the customer is constantly getting the, sort of the best TCO. So what that means is we're using Amazon's S3 storage as a tiered service, so that we can back off code data off of the primary file system to give the customer the optimal capacity, the optimal throughput, while maintaining the integrity of the file system. It's the same with backup. It's the same with disaster recovery, whether we're operating in a hybrid AWS cloud, or we're operating in an AWS region or across regions. >> Well, thank you. I think this, this announcement is a big deal for a number of reasons. First of all, it's the largest market. Like you said, you're the gold standard. I'll give you that, Anthony, because you guys earned it. And so it's a large market, but you always had to make previously, you have to make trade-offs. Either I could do file in the cloud, but I didn't get the rich functionality that, you know, NetApp's mature stack brings, or, you know, you could have wrapped your stack in Kubernete's container and thrown it into the cloud and hosted it there. But now that it's a managed service and presumably you're underneath, you're taking advantage. As I say, my inference is there's some serious engineering going on here. You're taking advantage of some of the cloud native capabilities. Yeah, maybe it's the different, you know, ECE two types, but also being able to bring in, we're, we're entering a new data era with machine intelligence and other capabilities that we really didn't have access to last decade. So I want to, I want to close with, you know, give you guys the last word. Maybe each of you could give me your thoughts on how you see this partnership of, for the, in the future. Particularly from a customer standpoint. Ed, maybe you could start. And then Anthony, you can bring us home. >> Yeah, well, Anthony and I and our teams have gotten to know each other really well in, in ideating around what this experience will be and then building the product. And, and we have this, this common vision that it is something that's going to really move the needle for customers. Providing the full ONTAP experience with the power of a, of a native AWS service. So we're really excited. We're, we're in this for the long haul together. We have, we've partnered on everything from engineering, to product management, to support. Like the, the full thing. This is a co-owned effort, a joint effort backed by both companies. And we have, I think a pretty remarkable product on day one, one that I think is going to delight customers. And we have a really rich roadmap that we're going to be building together over, over the years. So I'm excited about getting this in customer's hands. >> Great, thank you. Anthony, bring us home. >> Well, you know, it's one of those sorts of rare chances where you get to do something with Amazon that no one's ever done. You know, we're sort of sitting on the inside, we are a peer of theirs, and we're able to develop at very high speeds in combination with them to release continuously to the customer base. So what you're going to see here is rapid innovation. You're going to see a whole host of new services. Services that NetApp develops, services that Amazon develops. And then the whole ecosystem is going to have access to this, whether they're historically built on the NetApp APIs or increasingly built on the AWS APIs. I think you're going to see orchestrations. I think you're going to see the capabilities expand the overall opportunity for AWS to bring enterprise applications over. For me personally, Dave, you know, I've demonstrated yet again to the NetApp customer base, how much we care about them and their future. Selfishly, you know, I'm looking forward to telling the story to my competitors, customer base, because they haven't done it. So, you know, I think we've been bold. I think we've been committed as you said, three and a half years ago, I promised you that we were going to do everything we possibly could. You know, people always say, you know, what's, what's the real benefit of this. And at the end of the day, customers and partners will be the real winners. This, this innovation, this sort of, as a service I think is going to expand our market, allow our customers to do more with Amazon than they could before. It's one of those rare cases, Dave, where I think one plus one equals about seven, really. >> I love the vision and excited to see the execution Ed and Anthony, thanks so much for coming back in the Cube. Congratulations on getting to this point and good luck. >> Anthony and Ed: Thank you. >> All right. And thank you for watching everybody. This is Dave Vellante for the Cube's continuous coverage of AWS storage day. Keep it right there. (upbeat music)

>>Mhm Hello, I'm jennifer with the cube. We're here at Rogers vice president of EC two Product Manager, NWS raj. Thanks for coming off its quick cube conversation. Um Congratulations on your 15th birthday of E C two. You get the keys to the kingdom of one of the hottest products. The most important product you look at. I look at our billets. Ec two is the highest, it's always the best everyone focuses on. It's the compute a lot of other goodness with amazon cloud. Thanks for coming on. >>Thank you. Thanks for having me. >>So, can you break down the graviton two processor overview? Why is custom Silicon important and why should architects and developers understand the opportunity with graviton to these are the other opportunities within 80 bucks. What's the, what's the magic do it we should that they think about as the architect their cloud. >>Yeah. So, I mean, I think why it's important is what you said like so much uh the workloads that they're running at the end of the day is running on EC two, whether it's running on Ec two directly or running on one of the other AWS services that's built on a C two and when you have, when you're able to, when we're able to innovate and deliver a very significant price performance advantage, not just lowers their costs. So like there, It's hardly a day of industry where you're able to go and do a pretty simple migration and get a 40% price performance improvement and that's huge and I think that's why this is, you know, raising a lot of interest. Is that um, customers, I found it relatively easy to go and do this migration and get that benefit. >>That's awesome mirage. I gotta ask you ec two offers more than 400 instant types with different combinations of compute memory, networking and storage, which is obviously the backbone of the cloud. A lot of people that are coming in learning about clouds, what does it mean that there's all these instances that because it's just more combinations, different workloads, why 400 instance types? What does that mean for someone learning about clouds? Does it mean anything to you actually? Would you explain the difference of instance types of 400 of them? >>Yeah. So, I mean when you think about an instance type, it's essentially configuration of a virtual machine, there's a certain amount of memory, there's a certain amount of processing power. Uh there could be a certain amount of disk and workloads, uh, the different ratios of these uh, dimensions, these characteristics. So by offering selection across a wide variety of instances were really able to optimize the compute that particular workload needs. The customers could essentially uh, increase their performance and have a more optimized price for what they want to get done. So ultimately, that's what that's what it's about having the right form factor for a given workload and the more configurations that we have, the more we're able to tune for those workloads. >>It's like having a driver riding a car you want the driver type to match the road, match the engine. So the instance has to match the profile of the app, the workload and kind of, and is that kind of where you're getting at getting met? You can do that. >>Yeah. And you know, and one of the things that we're also investing in at the same time as tools to enable customers to realize and learn what the right instance is. So, you know, we launched about a year ago uh capability called compute optimizer that lets customers look at their workloads, you know, in flight essentially and make recommendations saying, hey, instead of this instance, you know, you could Move to um this other instance type and save 50% or you know, as an example. So, um, you know, part of it, creating the selection and the other part of it is creating the tools. So customers, do you know what the right fit is for them so that they can really optimize their thin >>Well Roger, I really preach this is going to ask me anything guru question, but here's the simple one. What is gravitas to, at the end of the day when someone asks you what is graviton too? >>Yeah. So I mean grandma can do is a processor, it's a chip, it's a CPU um and so what that means essentially is and it's an arm. Basic. So um, you know, with, with are just like you have intel and AMG processors, these are the, the circuitry and the computer that does the work. Right. And um with, with Gravitas on we support arm which is a different architecture set but one that has been around long enough and it's pretty ubiquitous across mobile devices and servers now. So the operating systems that you know, you know all the Linux operating system, the tools that you know, they all work and are able to run on Graviton too. So this means that when you have applications, you can very easily take it from the same AMG or intel X 86 platform and move it over and just get the efficiencies that gravity to offers with lower power envelope and higher performance >>there it is many master class here at raj. Pie Vice President Ec two product management laying down the graviton to knowledge and for folks learning about cloud and architects really want to know the difference. It's a 40% performance improvement, lower power envelope, 20% less than cost. I believe something those range about right about in the same territory there. So basically high performance, lower costs, better power. So for workloads that demanded you got the option raj. Thank you for sharing. Thank you. All right. I'm john for, with the cube Thanks for watching. Mhm mm

>>from around the >>globe. It's the Cube with digital coverage of AWS reinvent 2020. Special coverage sponsored by AWS Worldwide Public sector. >>Right. Hello and welcome to the Cube. Virtual our coverage of aws reinvent 2020 with special coverage of the public sector experience. This is the day when we go through all the great conversations around public sector in context to reinvent great guest will for Justin, head of A W s ai and machine learning enablement and partnership with AWS Wilfred. Thanks for joining us. >>Thanks, John. Thanks for having me on. I'm pretty excited to be part of this cube interview. >>Well, I wish we could be in person, but with the pandemic, we gotta do the remote. But I want to get into some of the things you're working on. The A I m l Rapid Adoption Assistance Initiative eyes a big story. What is? What is it described what it is. >>So we launched this artificial intelligence slash machine learning rapid adoption assistance for all public sector partners who are part of the AP in network in September 2020. Onda. We launched this in response to the president's Executive water called the American Year Initiative. So the rapid adoption assistant what it provides us. It provides a direct scalable on automated mechanism for all the public sector partners to reach out to AWS experts within our team for assistance in building and deploying machine learning workloads on behalf of the agencies. So for all all the partners who are part off, this rapid adoption assistance will go through a journey with AWS with my team and they will go through three different faces. The first face will be the envisioning face. The second phase would be the enablement face on the third would be the bill face, as you know, in the envisioning face will dive deeply The use case, the problem that they're trying to solve. This is where we will talk about the algorithms and framework on. We will solidify the architecture er on validate the architecture er on following that will be an enablement face where we engage with the partners trained their technical team, meaning that it will be a hands on approach hands on on keyboard kind of approach where we trained them on machine learning stack On the third phase would be the bill face on the partners leverage the knowledge that they have gained through the enablement and envisioning face, and they start building on rolling out workloads on behalf of the agencies. So we will stay with them throughout the journey on We will doom or any kind of blockers be technical or business, so that's a quick overview off a more rapid adoption assistance program. >>It's funny talking to Swami over the years and watching every year at reinvent the A I. M L Portfolio. Dr Matt Wood is always doing something new. This year is no exception. Even Mawr Machine Learning and AI in the In the News on this rapid adoption assistant initiative sounds like it's an accelerant. Um, so I get all that, But I want to ask you, what problem does it solve for the customer? Or Amazon is because there's demand. There's too much demand. People wanna go faster. What problem does this initiative this rapid adoption of a I machine learning initiative solved? >>So as you know, John, artificial intelligence and related technologies like deep learning and machine learning can literally transform the way agencies operate. They can enable them to provide better services, quicker services and more secure services to the citizens of this country. And that's the reason the president released an executive water called American Initiative on it drives all the government agencies, specifically federal agencies, to promote artificial intelligence to protect and improve the security and economy of the nation. So if you think about it, the best way to achieve the goal is to enable the partners toe build workloads on behalf of agencies, because when it comes to public sector, most of the workloads are delivered by partners. So the problem that we face based on our interaction with the partners is that though the partners have been building a lot off applications with AWS for more than a decade, when it comes to artificial intelligence, they have very limited resources when it comes to deep learning and machine learning, right, like speech recognition, cognitive computing, national language frosting. So we wanted exactly address that. And that's the problem you're trying to solve by launching this rapid adoption assistance, which is nothing but a dry direct mechanism for partners to reach our creative, these experts to help them to build those kind of solutions for the government. >>You know, it's interesting because AI and machine learning it's a secret sauce for workload, especially modern workloads. You mentioned agencies and also public sector. You know, we've seen Certainly there's been pandemic a ton of focus on moving faster, right? So getting those APS out quickly ai drives a lot of that, so totally get it. Um, I think it's an accelerant great program. It just makes a lot of sense. And I know you guys have been going in tow by vertical and kind of having stage making all these other tools kind of be specialized within those verticals. So it makes a ton of sense. I get it, and it is a great, great initiative and solve the problem. The question I have is who gets access to this, right? Is it just agencies you mentioned? Is it all public sector? Could you just clarify who can apply to this program? >>Yes, it is a partner focused program. So all the existing partners, though it is going to affect the end agencies, were trying to help the agency's through the partners. So all the existing AP in partners who are part of the PSP program, we call it the public sector partner program can apply for this rapid adoption assistance. So you have been following John, you have been following AWS and AWS partners on a lot of partners have different kind of expertise on they. They show that by achieving a lot of competencies, right, it could be technical competencies like big data storage and security. Or it could be domain specific competencies like public safety education on government competency. But for a playing this program, the partners don't need to have any kind of competency, and all they have to have is they have to be part of the Amazon Partner Network on they have to be part of the public sector partner program. That is number one Second. It is open toe all partners, meaning that it is open toe. Both technology partners, as well as consulting partners Number three are playing is pretty simple, John, right? You can quickly search for a I M or rapid adoption assistance on a little pop up a page on a P network, the partners have to go on Phil pretty basic information about the workload, the problem that they're trying to solve the machine learning services that they're planning to use on a couple of other information, like contact information, and then our team reaches out to the partner on help them with the journey. >>So real. No other requirements are prerequisites. Just part of the partner program. >>Absolutely. It is meant for partners. And all you have to do is you have to be a part off 18 network, and you have to be a public sector apartment. >>Public sector partner makes sense. I mean, how you're gonna handle the demand. I'm sure the it's gonna be a tsunami of interest, because, I mean, why wouldn't someone take advantage of this? >>Yep. It is open to all kinds of partners because they have some kind of prerequisites, right? So that's what I'm trying to explain. It is open to all partners, but we have since it is open to existing partners, we kind of expect the partners toe understand the best practices off deploying a machine, learning workloads, or for that case, any kind of workload which should be scalable, land secure and resilient. So we're not going to touch? Yeah, >>Well, I wanna ask you what's what's the response been on this launch? Because, you know, I mean to me, it just makes it's just common sense. Why wouldn't someone take advantage of it? E. Whether responses partner or you have domain expertise or in a vertical just makes a lot of sense. You get access to the experts. >>The response has been great. As I said, the once you apply the journey takes six weeks, but already we just launched it. Probably close toe. Two months back in September 2nd week of September, it is almost, uh, almost two months, and we have more than 15 partners as part of this program on dykan name couple of partners say, for example, we worked with delight on We Are. We will be working on number of work clothes for the Indy agencies through delight. And there are other couple of number of other partners were making significant progress using this rapid adoption assistance that includes after associates attained ardent emcee on infinitive. So to answer your question, the response has been great so far. >>So what's the I So I gotta ask, you know, one of things I thought that Teresa Carlson about all the time in Sandy Carter is, you know, trying to get the accelerant get whether it's Fed ramp and getting certifications. I mean, you guys have done a great job of getting partners on board. Is there any kind of paperwork? What's the process? What should a partner expect to take advantage of that? I'm sure they'll be interest beyond just the launch. What's what's involved? What zit Web bases it check a form? Is that a lot of hoops to jump through? Explain what? What? The process >>is. Very interesting question. And it probably is a very important question from a part of perspective, right? So since it is offered for a peon partners, absolutely, they should have already gone through the AP in terms and conditions they should have. Already, a customer agreement or advanced partners might have enterprise agreement. So for utilizing this for leveraging this rapid adoption assistance program, absolutely. There's no paperwork involved. All they have to do is log into the Web form, fill up the basic information. It comes to us way, take it from there. So there is no hard requirements as long as you're part of the AP network. And as long as you're part of the PSP program, >>well, for great insight, congratulations on a great program. I think it's gonna be a smash hit. Who wouldn't wanna take? I know you guys a lot of goodness there with Amazon Cloud higher level services with a I machine learning people could bring it into the table. I know from a cybersecurity standpoint to just education the range of, um, workloads is gonna be phenomenal. Obviously military as well. Eso totally cool. Love it. Congratulations. Like my final question is, um, one about the partner. So I'm a partner. I like this. Say I'm a partner. I jump in Easy to get in. Walk me through What happens? I mean, I signed some paperwork. You check the boxes, I get involved, I get, like, a rep. Do I do things? Do I? What happens to me? Walk me down the path of execution. What's expectation of what will happen? >>I'll explain that in two parts, John. Right? One is from a partner journey perspective and then from AWS perspective. What? What we expect out off partners, right? So, from a experience perspective, as long as they fill out, fill out the web form on, fill out the basic information about the project that they're trying to work. It comes to us. The workflow is automated. All the information is captured on the information comes to my team on. We get back to the partners within three days, but the journey itself can take from 6 to 8 weeks because, as I mentioned during the envisioning case, we try to map the problem to the solution. But the enablement phases the second phase is where it can take anywhere from 2 to 3 weeks because, as I mentioned, we focused on the three layers of the machine learning stack for certain kind of partners. They might be interested in sage maker because they might want to build a custom machine learning model. But for some of the partners, they want the argument that existing applications using S. R or NLP or nL you so we can focus on the high level services. Or we can train them on stage makers so it can take anywhere between 2 to 3 weeks or 3 to 4 weeks. And finally, the build phase varies from partner to partner on the complexity of the work. Lord at that point were still involved with a partner, but the partner will be taking the lead on will be with them to remove any kid of Glaucus being technical or, uh, business couple of Yeah, well, I just >>want to say the word enablement in your title kind of speaks volumes. This isn't about enabling customers. >>It is all about enabling the in customers through partners. So we focus on enabling partners. They could be business big system integrators like Lockheed's or Raytheon's or Delight. Or it could be nimble in small partners. Or it could be a technology partner building an entire pass or SAS service on behalf of the government agencies. Right or that could help the comment agencies in different verticals. So we just enabled the in the agency's through the partners. And the focus of this program is all about partner enablement. >>Well, for just ahead of a does a i machine learning enablement in partnership, part of public sector with a W. S. This is our special coverage. Well, for thanks for coming on being a cube virtual guest. I wish we could be in person, but this year it's remote. This is the cube virtual. I'm John for a year. Host of the Cube. Thanks for watching. >>Thanks a lot, John.

(upbeat music) >> Narrator: From around the globe. It's the cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >> Hi, welcome to the Q virtual. You're watching our coverage or AWS free event 2020. We are the Q virtual and let me hope you in skevent . I'm joined with Steve Mcmilla CEO, president of teradata Stephen, welcome to the show. >> Hey Keith, great to be here today. Glad to be joining you. So teradata, this is a big, exciting market analytics in the public cloud, but let's start with a little history. I remember teradata as being the thing that I do as a data says that my big data on premises and asking questions of teradata, how's the public cloud changed teradata's business. >> I think Teradata has got a fantastic heritage. We've, you know, being in the cloud, the data analytics business for over 40 years. So in fact, you could say that teradata invented data analytics. The cloud for us` is just a really exciting opportunity. It gives our customers another deployment option, and we are looking at how we can take our capabilities from on-prem and extend those into the cloud. And that's really what a lot of teradata's existing customers are looking for. But we also see tremendous opportunity as customers are responding to their market and their environments. They want to use the cloud as a platform, an agile platform, and we're finding that they can see the benefits of using teradata in terms of performance in scale and given a level of insight and to the data that they've got in the cloud, that other platforms can't touch. >> So we're talking about real time, current issues that's going on in customer environments. Talk to me about the teradata top de sure the pandemic. How's the pandemic impacting your customer environments or working the need for this type of analytics capabilities? >> I think the pandemic has just been an accelerant for a lot of transformation for companies. And you know, that the situation with COVID-19 globally has really resulted in a need for companies to be able to respond very harshly, to an uncertain environment. And an environment is changing all of the time. You know, AWS as a cloud provider can provide that level of agility. What teredata does set it on top of AWS has provided a level of business insight that enables companies to use their data, to dynamically respond to the situations that are in front of them today, even as that changes day by day or hour by hour or minute to minute. >> So I've talked to a lot of customer who have looked at the public cloud as a way to respond, celebrate their businesses in the era of the pandemic. But let's talk about long term vision. How are customers going to use teradata moving forward in a post pandemic. >> Okay I think that just from a data strategy perspective, cloud is one aspect of it. Really what our customers want to get from the data, Is real insights, that help them transform how their businesses work, especially in these changing times. So businesses we find are overwhelmed by the amount of data that they've got. There's never a day in the world where there's less data than there was the day before and coping with that explosion of data, getting real insights so they can work what they going to do that is we believe forms the basis of a long term data strategy. >> So help me paint a picture for customers as they look at their multi-cloud or hybrid cloud environments, which you know, I have my systems of record on premises feel, I have my next generation customer facing complications, Back far diverse is transactional. customer experience data. How does Teradata help bridge those worlds? >> That's where I think Teradata is uniquely placed. You know we bring that 40 years of heritage and investment and data analytics and we help our customers take that end to the cloud. We see most of our customers now have a cloud strategy. I was reading an industry report the other day that said that, on average organizations will have seven clouds that they have to deal with. Many customers are deploying on AWS because they see it as a great cloud platform where they can extend their on-prem data capabilities into the cloud use the facilities and features of AWS convened web teradata to really transform the data fabric and the analytics capabilities of their organization. So it's really that combination, that is provide some unique opportunities for our customers. And again, like using teradata in AWS quote, probates, unprecedented a scale, a scale that we've been able to develop in our technology over the last few decades. And we take that know-how and deploy it in the Amazon cloud so that customers have a great degree of control. They can optimize how their queries run inside the environment. They can get degrees of cost certainty that they don't otherwise have they can govern their data and ways that gives them complete control and security over the analytics, the insights that they make available so that they can really change how their companies operate. >> So obviously you run a sizable business, a mature business, that's finding this incredible growth mechanism, but at the end of the day, when your employees come to you with a new idea, you want to know what's the return on investment, you know money, isn't free resources, aren't free. You have limited staff just like everyone else. Talk to me about the return on investment from teradata. >> So I think teradata really offers the ability to get that cost per query and the sweet spot for our customers. So we've done a number of things we've made a cost calculator available on our website so that our, our customers can look at and compare how much it costs to run and say a data environment or an, an AWS quote, and how that compares to all of the other options that may be available to them. And what we see is often an order of magnitude difference in terms of the cost profile for running teradata and getting true business level insights from the data that they have compared to some of the competitive solutions out there. And that might really surprise some of your viewers said, Keith, in terms of that, that's not usually what you'd associate teradata West, or you associate teradata as, an absolutely robust system that's completely meshing critical. But David, we get those features and a really controlled environment, where the cost per query is optimized. we've got consumption-based pricing models that enables that return and investment curve that you're talking about to be either really early on in their process or using our technologies. >> So I've been part of these big, massive projects within enterprises, where we look at these, whether it's data leakes, unstructured data etc. We want to to next big questions of them. The big problem with that has always been cost or runs these projects always, always in my experience go over budget. How does the combination of AWS, which has the potential to have only limited budget and teradata, which falls basically unlimited budget issue or dresses, unlimited budget problem, how do you help control that risk and avoid cost? >> Yeah, so you know working in an environment like AWS, which is completely elastic can really does give tremendous value to our conveying customer set. But as you said, that elasticity comes at a cost. So in order to make sure that our customers run, the most important queries that they get the most value from, we utilize technologies that we've taken from our own prem deployments, things like query optimization and workload management, and that lets us give our customers a degree of control, and that environment that they wouldn't otherwise have. So we're really excited about the future of teradata and the AWS cloud. >> Now we spent a lot of time talking about the AWS cloud, but a lot of customers simply aren't there. A lot of them are just react to the pandemic, as a need for today. Do I have to be all in and AWS and public cloud in general to take advantage of all of these advantages of all of these capabilities? >> What we are, what we want to do from a teradata vantage perspective is really promote it as a platform and a platform that can be used across all of the cloud environments, and into the on-prem environment. If you have teradata vantage deployed in your on-prem So we're all about opening up choice and flexibility. You know, the teradata technology really enables our customers, not just to have a data Mart view of things where, you know, you're, no simple queries on, you know, the rear view mirror of what happened, but the analytics technology lets you get into questions like, well, why did that event happen? What's going to happen next? And what should we do to proactively plan that, you know we see use cases like the internet of things, where, there's a preventative and predictive maintenance on laws that the bases over there, and you can imagine the amount and volume of data that's getting consumed. And we analyze that data real time, get real answeres to make recommendations, to really enable an organization that's servicing these machines the the right level of end state to optimize how they're working on a day-to-day business. is really exciting. >> So again, we're now shipping the conversation back over to public health in consumption. How do I consume Cherokee advantage in AWS? >> We've got a number of different deployment models in terms of consuming teradata vantage , so you can have a pay as you go model, which means, you can start at nothing and work out overtaking or consumption model is really unique because we actually, we Bel on the basis of what we call logical IO, which means that it's only been queries work, inside the environment that our customer gets billed for it. So you don't just get charged by walking into the room and having the light switch on you only get charged when that late is doing something meaningful, for you and your organization, and actually result in an end state for use the company also the blended priests and models. So you can work out what the optimum deployment model as for teradata vantage and save quote. So loss of choice, we're all about giving that flexibility and choice in terms of how we operate. >> So you hit on the topic of IOT, but let's hit that dead on and talk about another hot part of not just the it conversation, but the cloud conversation and especially data analytics, the edge how does a solution like vantage play with datasets, that live at the edge and have to be carried at the edge? >> You know, one of the great things of a teradata vantage and how we're looking at it just now, If we think about, or you may recall as teradata, the desire was to try and get everything into a teradata and have all the data captured and say that ecosystem, that doesn't work as well in the cloud world. What we're all about is opening up that platform. So some of your viewers might be surprised. We now integrate with, 18 of AWS services to really start opening the platform up. We give access to from teradata and to native object stores and cloud environments so that, customers don't have to duplicate data. They don't have to copy it into teradata, and have that data locked in there. We can access a whole plethora of data capture mechanisms that the cloud providers AWS make available, in terms of those APO eyes and those calls. so that we can integrate it all together, and get the best possible set of data sources, for teradata VANTAGE to work on. So really exciting team in terms of opening up that platform being really modern in terms of looking at the data fabric, that our customers have and how they're using these cloud services on a day-to-day basis. And integrating that with the power advantage. >> Steve McMillan, president CEO of teradata. We really appreciate it. 40 years of analytics history. We're seeing the movement in public cloud where we're going from these companies that we put our, all our data into centralized, adapting to the reality of edge data center, public cloud, meeting us where the data's at. We're super excited to now promote you into an alum of the queue, make sure to join us for additional coverage of AWS reinvent 2020 on ducky. (upbeat music)

>>from around the globe. It's the Cube with digital coverage of enterprise data automation, an event Siri's brought to you by Iot. Tahoe, >>my buddy, We're back. And this is Dave Volante, and we're covering the whole notion of automating data in the Enterprise. And I'm really excited to have Paul Damico here. She's a senior vice president of enterprise data Architecture at Webster Bank. Good to see you. Thanks for coming on. >>Hi. Nice to see you, too. Yes. >>So let's let's start with Let's start with Webster Bank. You guys are kind of a regional. I think New York, New England, uh, leave headquartered out of Connecticut, but tell us a little bit about the bank. >>Yeah, Um, Webster Bank >>is regional Boston And that again, and New York, Um, very focused on in Westchester and Fairfield County. Um, they're a really highly rated saying regional bank for this area. They, um, hold, um, quite a few awards for the area for being supportive for the community and, um, are really moving forward. Technology lives. They really want to be a data driven bank, and they want to move into a more robust Bruce. >>Well, we got a lot to talk about. So data driven that is an interesting topic. And your role as data architect. The architecture is really senior vice president data architecture. So you got a big responsibility as it relates to It's kind of transitioning to this digital data driven bank. But tell us a little bit about your role in your organization, >>right? Um, currently, >>today we have, ah, a small group that is just working toward moving into a more futuristic, more data driven data warehouse. That's our first item. And then the other item is to drive new revenue by anticipating what customers do when they go to the bank or when they log into there to be able to give them the best offer. The only way to do that is you >>have uh huh. >>Timely, accurate, complete data on the customer and what's really a great value on off something to offer that or a new product or to help them continue to grow their savings or do and grow their investment. >>Okay. And I really want to get into that. But before we do and I know you're sort of part way through your journey, you got a lot of what they do. But I want to ask you about Cove. It how you guys you're handling that? I mean, you had the government coming down and small business loans and P p p. And huge volume of business and sort of data was at the heart of that. How did you manage through that? >>But we were extremely successful because we have a big, dedicated team that understands where their data is and was able to switch much faster than a larger bank to be able to offer. The TPP longs at to our customers within lightning speeds. And part of that was is we adapted to Salesforce very, for we've had salesforce in house for over 15 years. Um, you know, pretty much, uh, that was the driving vehicle to get our CPP is loans in on and then developing logic quickly. But it was a 24 7 development role in get the data moving, helping our customers fill out the forms. And a lot of that was manual. But it was a It was a large community effort. >>Well, think about that. Think about that too. Is the volume was probably much, much higher the volume of loans to small businesses that you're used to granting. But and then also, the initial guidelines were very opaque. You really didn't know what the rules were, but you were expected to enforce them. And then finally, you got more clarity. So you had to essentially code that logic into the system in real time, right? >>I wasn't >>directly involved, but part of my data movement Team Waas, and we had to change the logic overnight. So it was on a Friday night was released. We've pushed our first set of loans through and then the logic change, Um, from, you know, coming from the government and changed. And we had to re develop our our data movement piece is again and we design them and send them back. So it was It was definitely kind of scary, but we were completely successful. We hit a very high peak and I don't know the exact number, but it was in the thousands of loans from, you know, little loans to very large loans, and not one customer who buy it's not yet what they needed for. Um, you know, that was the right process and filled out the rate and pace. >>That's an amazing story and really great support for the region. New York, Connecticut, the Boston area. So that's that's fantastic. I want to get into the rest of your story. Now let's start with some of the business drivers in banking. I mean, obviously online. I mean, a lot of people have sort of joked that many of the older people who kind of shunned online banking would love to go into the branch and see their friendly teller had no choice, You know, during this pandemic to go to online. So that's obviously a big trend you mentioned. So you know the data driven data warehouse? I wanna understand that. But well, at the top level, what were some of what are some of the key business drivers there catalyzing your desire for change? >>Um, the ability to give the customer what they need at the time when they need it. And what I mean by that is that we have, um, customer interactions in multiple ways, right? >>And I want >>to be able for the customer, too. Walk into a bank, um, or online and see the same the same format and being able to have the same feel, the same look, and also to be able to offer them the next best offer for them. But they're you know, if they want looking for a new a mortgage or looking to refinance or look, you know, whatever it iss, um, that they have that data, we have the data and that they feel comfortable using it. And that's a untethered banker. Um, attitude is, you know, whatever my banker is holding and whatever the person is holding in their phone, that that is the same. And it's comfortable, so they don't feel that they've, you know, walked into the bank and they have to do a lot of different paperwork comparative filling out paperwork on, you know, just doing it on their phone. >>So you actually want the experience to be better. I mean, and it is in many cases now, you weren't able to do this with your existing against mainframe based Enterprise data warehouse. Is is that right? Maybe talk about that a little bit. >>Yeah, we were >>definitely able to do it with what we have today. The technology we're using, but one of the issues is that it's not timely, Um, and and you need a timely process to be able to get the customers to understand what's happening. Um, you want you need a timely process so we can enhance our risk management. We can apply for fraud issues and things like that. >>Yeah, so you're trying to get more real time in the traditional e g W. It's it's sort of a science project. There's a few experts that know how to get it. You consider line up. The demand is tremendous, and often times by the time you get the answer, you know it's outdated. So you're trying to address that problem. So So part of it is really the cycle time, the end end cycle, time that you're pressing. And then there's if I understand it, residual benefits that are pretty substantial from a revenue opportunity. Other other offers that you can you can make to the right customer, Um, that that you, you maybe know through your data. Is that right? >>Exactly. It's drive new customers, Teoh new opportunities. It's enhanced the risk, and it's to optimize the banking process and then obviously, to create new business. Um, and the only way we're going to be able to do that is that we have the ability to look at the data right when the customer walks in the door or right when they open up their app. And, um, by doing, creating more to New York time near real time data for the data warehouse team that's giving the lines of business the ability to to work on the next best offer for that customer. >>Paulo, we're inundated with data sources these days. Are there their data sources that you maybe maybe had access to before? But perhaps the backlog of ingesting and cleaning and cataloging and you know of analyzing. Maybe the backlog was so great that you couldn't perhaps tap some of those data sources. You see the potential to increase the data sources and hence the quality of the data, Or is that sort of premature? >>Oh, no. Um, >>exactly. Right. So right now we ingest a lot of flat files and from our mainframe type of Brennan system that we've had for quite a few years. But now that we're moving to the cloud and off Prem and on France, you know, moving off Prem into like an s three bucket. Where That data king, We can process that data and get that data faster by using real time tools to move that data into a place where, like, snowflake could utilize that data or we can give it out to our market. >>Okay, so we're >>about the way we do. We're in batch mode. Still, so we're doing 24 hours. >>Okay, So when I think about the data pipeline and the people involved, I mean, maybe you could talk a little bit about the organization. I mean, you've got I know you have data. Scientists or statisticians? I'm sure you do. Ah, you got data architects, data engineers, quality engineers, you know, developers, etcetera, etcetera. And oftentimes, practitioners like yourself will will stress about pay. The data's in silos of the data quality is not where we want it to be. We have to manually categorize the data. These are all sort of common data pipeline problems, if you will. Sometimes we use the term data ops, which is kind of a play on Dev Ops applied to the data pipeline. I did. You just sort of described your situation in that context. >>Yeah. Yes. So we have a very large data ops team and everyone that who is working on the data part of Webster's Bay has been there 13 14 years. So they get the data, they understand that they understand the lines of business. Um, so it's right now, um, we could we have data quality issues, just like everybody else does. We have. We have places in him where that gets clans, Um, and we're moving toward. And there was very much silo data. The data scientists are out in the lines of business right now, which is great, cause I think that's where data science belongs. We should give them on. And that's what we're working towards now is giving them more self service, giving them the ability to access the data, um, in a more robust way. And it's a single source of truth. So they're not pulling the data down into their own like tableau dashboards and then pushing the data back out. Um, so they're going to more not, I don't want to say a central repository, but a more of a robust repository that's controlled across multiple avenues where multiple lines of business can access. That said, how >>got it? Yes, and I think that one of the key things that I'm taking away from your last comment is the cultural aspects of this bite having the data. Scientists in the line of business, the line of lines of business, will feel ownership of that data as opposed to pointing fingers, criticizing the data quality they really own that that problem, as opposed to saying, Well, it's it's It's Paulus problem, >>right? Well, I have. My problem >>is, I have a date. Engineers, data architects, they database administrators, right, Um, and then data traditional data forwarding people. Um, and because some customers that I have that our business customers lines of business, they want to just subscribe to a report. They don't want to go out and do any data science work. Um, and we still have to provide that. So we still want to provide them some kind of regimen that they wake up in the morning and they open up their email. And there's the report that they just drive, um, which is great. And it works out really well. And one of the things is why we purchase I o waas. I would have the ability to give the lines of business the ability to do search within the data. And we read the data flows and data redundancy and things like that help me cleanup the data and also, um, to give it to the data. Analysts who say All right, they just asked me. They want this certain report, and it used to take Okay, well, we're gonna four weeks, we're going to go. We're gonna look at the data, and then we'll come back and tell you what we dio. But now with Iot Tahoe, they're able to look at the data and then, in one or two days of being able to go back and say, yes, we have data. This is where it is. This is where we found that this is the data flows that we've found also, which is that what I call it is the birth of a column. It's where the calm was created and where it went live as a teenager. And then it went to, you know, die very archive. Yeah, it's this, you know, cycle of life for a column. And Iot Tahoe helps us do that, and we do. Data lineage has done all the time. Um, and it's just takes a very long time. And that's why we're using something that has AI and machine learning. Um, it's it's accurate. It does it the same way over and over again. If an analyst leads, you're able to utilize talked something like, Oh, to be able to do that work for you. I get that. >>Yes. Oh, got it. So So a couple things there is in in, In researching Iot Tahoe, it seems like one of the strengths of their platform is the ability to visualize data the data structure and actually dig into it. But also see it, um, and that speeds things up and gives everybody additional confidence. And then the other pieces essentially infusing AI or machine intelligence into the data pipeline is really how you're attacking automation, right? And you're saying it's repeatable and and then that helps the data quality, and you have this virtuous cycle. Is there a firm that and add some color? Perhaps >>Exactly. Um, so you're able to let's say that I have I have seven cause lines of business that are asking me questions and one of the questions I'll ask me is. We want to know if this customer is okay to contact, right? And you know, there's different avenues, so you can go online to go. Do not contact me. You can go to the bank and you can say I don't want, um, email, but I'll take tests and I want, you know, phone calls. Um, all that information. So seven different lines of business asked me that question in different ways once said okay to contact the other one says, you know, customer one to pray All these, You know, um, and each project before I got there used to be siloed. So one customer would be 100 hours for them to do that and analytical work, and then another cut. Another analysts would do another 100 hours on the other project. Well, now I can do that all at once, and I can do those type of searches and say, Yes, we already have that documentation. Here it is. And this is where you can find where the customer has said, you know, you don't want I don't want to get access from you by email, or I've subscribed to get emails from you. >>Got it. Okay? Yeah. Okay. And then I want to come back to the cloud a little bit. So you you mentioned those three buckets? So you're moving to the Amazon cloud. At least I'm sure you're gonna get a hybrid situation there. You mentioned Snowflake. Um, you know what was sort of the decision to move to the cloud? Obviously, snowflake is cloud only. There's not an on Prem version there. So what precipitated that? >>Alright, So, from, um, I've been in >>the data I t Information field for the last 35 years. I started in the US Air Force and have moved on from since then. And, um, my experience with off brand waas with Snowflake was working with G McGee capital. And that's where I met up with the team from Iot to house as well. And so it's a proven. So there's a couple of things one is symptomatic of is worldwide. Now to move there, right, Two products, they have the on frame in the offering. Um, I've used the on Prem and off Prem. They're both great and it's very stable and I'm comfortable with other people are very comfortable with this. So we picked. That is our batch data movement. Um, we're moving to her, probably HBR. It's not a decision yet, but we're moving to HP are for real time data which has changed capture data, you know, moves it into the cloud. And then So you're envisioning this right now in Petrit, you're in the S three and you have all the data that you could possibly want. And that's Jason. All that everything is sitting in the S three to be able to move it through into snowflake and snowflake has proven cto have a stability. Um, you only need to learn in train your team with one thing. Um, aws has is completely stable at this 10.2. So all these avenues, if you think about it going through from, um, you know, this is your your data lake, which is I would consider your s three. And even though it's not a traditional data leg like you can touch it like a like a progressive or a dupe and into snowflake and then from snowflake into sandboxes. So your lines of business and your data scientists and just dive right in, Um, that makes a big, big win. and then using Iot. Ta ho! With the data automation and also their search engine, um, I have the ability to give the data scientists and eight analysts the the way of they don't need to talk to i t to get, um, accurate information or completely accurate information from the structure. And we'll be right there. >>Yes, so talking about, you know, snowflake and getting up to speed quickly. I know from talking to customers you get from zero to snowflake, you know, very fast. And then it sounds like the i o Ta ho is sort of the automation cloud for your data pipeline within the cloud. This is is that the right way to think about it? >>I think so. Um, right now I have I o ta >>ho attached to my >>on Prem. And, um, I >>want to attach it to my offering and eventually. So I'm using Iot Tahoe's data automation right now to bring in the data and to start analyzing the data close to make sure that I'm not missing anything and that I'm not bringing over redundant data. Um, the data warehouse that I'm working off is not a It's an on Prem. It's an Oracle database and its 15 years old. So it has extra data in it. It has, um, things that we don't need anymore. And Iot. Tahoe's helping me shake out that, um, extra data that does not need to be moved into my S three. So it's saving me money when I'm moving from offering on Prem. >>And so that was a challenge prior because you couldn't get the lines of business to agree what to delete or what was the issue there. >>Oh, it was more than that. Um, each line of business had their own structure within the warehouse, and then they were copying data between each other and duplicating the data and using that, uh so there might be that could be possibly three tables that have the same data in it. But it's used for different lines of business. And so I had we have identified using Iot Tahoe. I've identified over seven terabytes in the last, um, two months on data that is just been repetitive. Um, it just it's the same exact data just sitting in a different scheme. >>And and that's not >>easy to find. If you only understand one schema that's reporting for that line of business so that >>yeah, more bad news for the storage companies out there. Okay to follow. >>It's HCI. That's what that's what we were telling people you >>don't know and it's true, but you still would rather not waste it. You apply it to, you know, drive more revenue. And and so I guess Let's close on where you see this thing going again. I know you're sort of part way through the journey. May be you could sort of describe, you know, where you see the phase is going and really what you want to get out of this thing, You know, down the road Midterm. Longer term. What's your vision or your your data driven organization? >>Um, I want >>for the bankers to be able to walk around with on iPad in their hands and be able to access data for that customer really fast and be able to give them the best deal that they can get. I want Webster to be right there on top, with being able to add new customers and to be able to serve our existing customers who had bank accounts. Since you were 12 years old there and now our, you know, multi. Whatever. Um, I want them to be able to have the best experience with our our bankers, and >>that's awesome. I mean, that's really what I want is a banking customer. I want my bank to know who I am, anticipate my needs and create a great experience for me. And then let me go on with my life. And so that is a great story. Love your experience, your background and your knowledge. Can't thank you enough for coming on the Cube. >>No, thank you very much. And you guys have a great day. >>Alright, Take care. And thank you for watching everybody keep it right there. We'll take a short break and be right back. >>Yeah, yeah, yeah, yeah.

>> Narrator: From around the Globe, it's theCube with digital coverage of Enterprise Data Automation, and event series brought to you by Io-Tahoe. >> Everybody, we're back. And this is Dave Vellante, and we're covering the whole notion of Automated Data in the Enterprise. And I'm really excited to have Paula D'Amico here. Senior Vice President of Enterprise Data Architecture at Webster Bank. Paula, good to see you. Thanks for coming on. >> Hi, nice to see you, too. >> Let's start with Webster bank. You guys are kind of a regional I think New York, New England, believe it's headquartered out of Connecticut. But tell us a little bit about the bank. >> Webster bank is regional Boston, Connecticut, and New York. Very focused on in Westchester and Fairfield County. They are a really highly rated regional bank for this area. They hold quite a few awards for the area for being supportive for the community, and are really moving forward technology wise, they really want to be a data driven bank, and they want to move into a more robust group. >> We got a lot to talk about. So data driven is an interesting topic and your role as Data Architecture, is really Senior Vice President Data Architecture. So you got a big responsibility as it relates to kind of transitioning to this digital data driven bank but tell us a little bit about your role in your Organization. >> Currently, today, we have a small group that is just working toward moving into a more futuristic, more data driven data warehousing. That's our first item. And then the other item is to drive new revenue by anticipating what customers do, when they go to the bank or when they log in to their account, to be able to give them the best offer. And the only way to do that is you have timely, accurate, complete data on the customer and what's really a great value on offer something to offer that, or a new product, or to help them continue to grow their savings, or do and grow their investments. >> Okay, and I really want to get into that. But before we do, and I know you're, sort of partway through your journey, you got a lot to do. But I want to ask you about Covid, how you guys handling that? You had the government coming down and small business loans and PPP, and huge volume of business and sort of data was at the heart of that. How did you manage through that? >> We were extremely successful, because we have a big, dedicated team that understands where their data is and was able to switch much faster than a larger bank, to be able to offer the PPP Long's out to our customers within lightning speed. And part of that was is we adapted to Salesforce very for we've had Salesforce in house for over 15 years. Pretty much that was the driving vehicle to get our PPP loans in, and then developing logic quickly, but it was a 24 seven development role and get the data moving on helping our customers fill out the forms. And a lot of that was manual, but it was a large community effort. >> Think about that too. The volume was probably much higher than the volume of loans to small businesses that you're used to granting and then also the initial guidelines were very opaque. You really didn't know what the rules were, but you were expected to enforce them. And then finally, you got more clarity. So you had to essentially code that logic into the system in real time. >> I wasn't directly involved, but part of my data movement team was, and we had to change the logic overnight. So it was on a Friday night it was released, we pushed our first set of loans through, and then the logic changed from coming from the government, it changed and we had to redevelop our data movement pieces again, and we design them and send them back through. So it was definitely kind of scary, but we were completely successful. We hit a very high peak. Again, I don't know the exact number but it was in the thousands of loans, from little loans to very large loans and not one customer who applied did not get what they needed for, that was the right process and filled out the right amount. >> Well, that is an amazing story and really great support for the region, your Connecticut, the Boston area. So that's fantastic. I want to get into the rest of your story now. Let's start with some of the business drivers in banking. I mean, obviously online. A lot of people have sort of joked that many of the older people, who kind of shunned online banking would love to go into the branch and see their friendly teller had no choice, during this pandemic, to go to online. So that's obviously a big trend you mentioned, the data driven data warehouse, I want to understand that, but what at the top level, what are some of the key business drivers that are catalyzing your desire for change? >> The ability to give a customer, what they need at the time when they need it. And what I mean by that is that we have customer interactions in multiple ways. And I want to be able for the customer to walk into a bank or online and see the same format, and being able to have the same feel the same love, and also to be able to offer them the next best offer for them. But they're if they want looking for a new mortgage or looking to refinance, or whatever it is that they have that data, we have the data and that they feel comfortable using it. And that's an untethered banker. Attitude is, whatever my banker is holding and whatever the person is holding in their phone, that is the same and it's comfortable. So they don't feel that they've walked into the bank and they have to do fill out different paperwork compared to filling out paperwork on just doing it on their phone. >> You actually do want the experience to be better. And it is in many cases. Now you weren't able to do this with your existing I guess mainframe based Enterprise Data Warehouses. Is that right? Maybe talk about that a little bit? >> Yeah, we were definitely able to do it with what we have today the technology we're using. But one of the issues is that it's not timely. And you need a timely process to be able to get the customers to understand what's happening. You need a timely process so we can enhance our risk management. We can apply for fraud issues and things like that. >> Yeah, so you're trying to get more real time. The traditional EDW. It's sort of a science project. There's a few experts that know how to get it. You can so line up, the demand is tremendous. And then oftentimes by the time you get the answer, it's outdated. So you're trying to address that problem. So part of it is really the cycle time the end to end cycle time that you're progressing. And then there's, if I understand it residual benefits that are pretty substantial from a revenue opportunity, other offers that you can make to the right customer, that you maybe know, through your data, is that right? >> Exactly. It's drive new customers to new opportunities. It's enhanced the risk, and it's to optimize the banking process, and then obviously, to create new business. And the only way we're going to be able to do that is if we have the ability to look at the data right when the customer walks in the door or right when they open up their app. And by doing creating more to New York times near real time data, or the data warehouse team that's giving the lines of business the ability to work on the next best offer for that customer as well. >> But Paula, we're inundated with data sources these days. Are there other data sources that maybe had access to before, but perhaps the backlog of ingesting and cleaning in cataloging and analyzing maybe the backlog was so great that you couldn't perhaps tap some of those data sources. Do you see the potential to increase the data sources and hence the quality of the data or is that sort of premature? >> Oh, no. Exactly. Right. So right now, we ingest a lot of flat files and from our mainframe type of front end system, that we've had for quite a few years. But now that we're moving to the cloud and off-prem and on-prem, moving off-prem, into like an S3 Bucket, where that data we can process that data and get that data faster by using real time tools to move that data into a place where, like snowflake could utilize that data, or we can give it out to our market. Right now we're about we do work in batch mode still. So we're doing 24 hours. >> Okay. So when I think about the data pipeline, and the people involved, maybe you could talk a little bit about the organization. You've got, I don't know, if you have data scientists or statisticians, I'm sure you do. You got data architects, data engineers, quality engineers, developers, etc. And oftentimes, practitioners like yourself, will stress about, hey, the data is in silos. The data quality is not where we want it to be. We have to manually categorize the data. These are all sort of common data pipeline problems, if you will. Sometimes we use the term data Ops, which is sort of a play on DevOps applied to the data pipeline. Can you just sort of describe your situation in that context? >> Yeah, so we have a very large data ops team. And everyone that who is working on the data part of Webster's Bank, has been there 13 to 14 years. So they get the data, they understand it, they understand the lines of business. So it's right now. We could the we have data quality issues, just like everybody else does. But we have places in them where that gets cleansed. And we're moving toward and there was very much siloed data. The data scientists are out in the lines of business right now, which is great, because I think that's where data science belongs, we should give them and that's what we're working towards now is giving them more self service, giving them the ability to access the data in a more robust way. And it's a single source of truth. So they're not pulling the data down into their own, like Tableau dashboards, and then pushing the data back out. So they're going to more not, I don't want to say, a central repository, but a more of a robust repository, that's controlled across multiple avenues, where multiple lines of business can access that data. Is that help? >> Got it, Yes. And I think that one of the key things that I'm taking away from your last comment, is the cultural aspects of this by having the data scientists in the line of business, the lines of business will feel ownership of that data as opposed to pointing fingers criticizing the data quality. They really own that that problem, as opposed to saying, well, it's Paula's problem. >> Well, I have my problem is I have data engineers, data architects, database administrators, traditional data reporting people. And because some customers that I have that are business customers lines of business, they want to just subscribe to a report, they don't want to go out and do any data science work. And we still have to provide that. So we still want to provide them some kind of regiment that they wake up in the morning, and they open up their email, and there's the report that they subscribe to, which is great, and it works out really well. And one of the things is why we purchased Io-Tahoe was, I would have the ability to give the lines of business, the ability to do search within the data. And we'll read the data flows and data redundancy and things like that, and help me clean up the data. And also, to give it to the data analysts who say, all right, they just asked me they want this certain report. And it used to take okay, four weeks we're going to go and we're going to look at the data and then we'll come back and tell you what we can do. But now with Io-Tahoe, they're able to look at the data, and then in one or two days, they'll be able to go back and say, Yes, we have the data, this is where it is. This is where we found it. This is the data flows that we found also, which is what I call it, is the break of a column. It's where the column was created, and where it went to live as a teenager. (laughs) And then it went to die, where we archive it. And, yeah, it's this cycle of life for a column. And Io-Tahoe helps us do that. And we do data lineage is done all the time. And it's just takes a very long time and that's why we're using something that has AI in it and machine running. It's accurate, it does it the same way over and over again. If an analyst leaves, you're able to utilize something like Io-Tahoe to be able to do that work for you. Is that help? >> Yeah, so got it. So a couple things there, in researching Io-Tahoe, it seems like one of the strengths of their platform is the ability to visualize data, the data structure and actually dig into it, but also see it. And that speeds things up and gives everybody additional confidence. And then the other piece is essentially infusing AI or machine intelligence into the data pipeline, is really how you're attacking automation. And you're saying it repeatable, and then that helps the data quality and you have this virtual cycle. Maybe you could sort of affirm that and add some color, perhaps. >> Exactly. So you're able to let's say that I have seven cars, lines of business that are asking me questions, and one of the questions they'll ask me is, we want to know, if this customer is okay to contact, and there's different avenues so you can go online, do not contact me, you can go to the bank and you can say, I don't want email, but I'll take texts. And I want no phone calls. All that information. So, seven different lines of business asked me that question in different ways. One said, "No okay to contact" the other one says, "Customer 123." All these. In each project before I got there used to be siloed. So one customer would be 100 hours for them to do that analytical work, and then another analyst would do another 100 hours on the other project. Well, now I can do that all at once. And I can do those types of searches and say, Yes, we already have that documentation. Here it is, and this is where you can find where the customer has said, "No, I don't want to get access from you by email or I've subscribed to get emails from you." >> Got it. Okay. Yeah Okay. And then I want to go back to the cloud a little bit. So you mentioned S3 Buckets. So you're moving to the Amazon cloud, at least, I'm sure you're going to get a hybrid situation there. You mentioned snowflake. What was sort of the decision to move to the cloud? Obviously, snowflake is cloud only. There's not an on-prem, version there. So what precipitated that? >> Alright, so from I've been in the data IT information field for the last 35 years. I started in the US Air Force, and have moved on from since then. And my experience with Bob Graham, was with snowflake with working with GE Capital. And that's where I met up with the team from Io-Tahoe as well. And so it's a proven so there's a couple of things one is Informatica, is worldwide known to move data. They have two products, they have the on-prem and the off-prem. I've used the on-prem and off-prem, they're both great. And it's very stable, and I'm comfortable with it. Other people are very comfortable with it. So we picked that as our batch data movement. We're moving toward probably HVR. It's not a total decision yet. But we're moving to HVR for real time data, which is changed capture data, moves it into the cloud. And then, so you're envisioning this right now. In which is you're in the S3, and you have all the data that you could possibly want. And that's JSON, all that everything is sitting in the S3 to be able to move it through into snowflake. And snowflake has proven to have a stability. You only need to learn and train your team with one thing. AWS as is completely stable at this point too. So all these avenues if you think about it, is going through from, this is your data lake, which is I would consider your S3. And even though it's not a traditional data lake like, you can touch it like a Progressive or Hadoop. And then into snowflake and then from snowflake into sandbox and so your lines of business and your data scientists just dive right in. That makes a big win. And then using Io-Tahoe with the data automation, and also their search engine. I have the ability to give the data scientists and data analysts the way of they don't need to talk to IT to get accurate information or completely accurate information from the structure. And we'll be right back. >> Yeah, so talking about snowflake and getting up to speed quickly. I know from talking to customers you can get from zero to snowflake very fast and then it sounds like the Io-Tahoe is sort of the automation cloud for your data pipeline within the cloud. Is that the right way to think about it? >> I think so. Right now I have Io-Tahoe attached to my on-prem. And I want to attach it to my off-prem eventually. So I'm using Io-Tahoe data automation right now, to bring in the data, and to start analyzing the data flows to make sure that I'm not missing anything, and that I'm not bringing over redundant data. The data warehouse that I'm working of, it's an on-prem. It's an Oracle Database, and it's 15 years old. So it has extra data in it. It has things that we don't need anymore, and Io-Tahoe's helping me shake out that extra data that does not need to be moved into my S3. So it's saving me money, when I'm moving from off-prem to on-prem. >> And so that was a challenge prior, because you couldn't get the lines of business to agree what to delete, or what was the issue there? >> Oh, it was more than that. Each line of business had their own structure within the warehouse. And then they were copying data between each other, and duplicating the data and using that. So there could be possibly three tables that have the same data in it, but it's used for different lines of business. We have identified using Io-Tahoe identified over seven terabytes in the last two months on data that has just been repetitive. It's the same exact data just sitting in a different schema. And that's not easy to find, if you only understand one schema, that's reporting for that line of business. >> More bad news for the storage companies out there. (both laughs) So far. >> It's cheap. That's what we were telling people. >> And it's true, but you still would rather not waste it, you'd like to apply it to drive more revenue. And so, I guess, let's close on where you see this thing going. Again, I know you're sort of partway through the journey, maybe you could sort of describe, where you see the phase is going and really what you want to get out of this thing, down the road, mid-term, longer term, what's your vision or your data driven organization. >> I want for the bankers to be able to walk around with an iPad in their hand, and be able to access data for that customer, really fast and be able to give them the best deal that they can get. I want Webster to be right there on top with being able to add new customers, and to be able to serve our existing customers who had bank accounts since they were 12 years old there and now our multi whatever. I want them to be able to have the best experience with our bankers. >> That's awesome. That's really what I want as a banking customer. I want my bank to know who I am, anticipate my needs, and create a great experience for me. And then let me go on with my life. And so that follow. Great story. Love your experience, your background and your knowledge. I can't thank you enough for coming on theCube. >> Now, thank you very much. And you guys have a great day. >> All right, take care. And thank you for watching everybody. Keep right there. We'll take a short break and be right back. (gentle music)

>> Narrator: From around the Globe, it's theCube with digital coverage of Enterprise Data Automation, and event series brought to you by Io-Tahoe. >> Everybody, we're back. And this is Dave Vellante, and we're covering the whole notion of Automated Data in the Enterprise. And I'm really excited to have Paula D'Amico here. Senior Vice President of Enterprise Data Architecture at Webster Bank. Paula, good to see you. Thanks for coming on. >> Hi, nice to see you, too. >> Let's start with Webster bank. You guys are kind of a regional I think New York, New England, believe it's headquartered out of Connecticut. But tell us a little bit about the bank. >> Webster bank is regional Boston, Connecticut, and New York. Very focused on in Westchester and Fairfield County. They are a really highly rated regional bank for this area. They hold quite a few awards for the area for being supportive for the community, and are really moving forward technology wise, they really want to be a data driven bank, and they want to move into a more robust group. >> We got a lot to talk about. So data driven is an interesting topic and your role as Data Architecture, is really Senior Vice President Data Architecture. So you got a big responsibility as it relates to kind of transitioning to this digital data driven bank but tell us a little bit about your role in your Organization. >> Currently, today, we have a small group that is just working toward moving into a more futuristic, more data driven data warehousing. That's our first item. And then the other item is to drive new revenue by anticipating what customers do, when they go to the bank or when they log in to their account, to be able to give them the best offer. And the only way to do that is you have timely, accurate, complete data on the customer and what's really a great value on offer something to offer that, or a new product, or to help them continue to grow their savings, or do and grow their investments. >> Okay, and I really want to get into that. But before we do, and I know you're, sort of partway through your journey, you got a lot to do. But I want to ask you about Covid, how you guys handling that? You had the government coming down and small business loans and PPP, and huge volume of business and sort of data was at the heart of that. How did you manage through that? >> We were extremely successful, because we have a big, dedicated team that understands where their data is and was able to switch much faster than a larger bank, to be able to offer the PPP Long's out to our customers within lightning speed. And part of that was is we adapted to Salesforce very for we've had Salesforce in house for over 15 years. Pretty much that was the driving vehicle to get our PPP loans in, and then developing logic quickly, but it was a 24 seven development role and get the data moving on helping our customers fill out the forms. And a lot of that was manual, but it was a large community effort. >> Think about that too. The volume was probably much higher than the volume of loans to small businesses that you're used to granting and then also the initial guidelines were very opaque. You really didn't know what the rules were, but you were expected to enforce them. And then finally, you got more clarity. So you had to essentially code that logic into the system in real time. >> I wasn't directly involved, but part of my data movement team was, and we had to change the logic overnight. So it was on a Friday night it was released, we pushed our first set of loans through, and then the logic changed from coming from the government, it changed and we had to redevelop our data movement pieces again, and we design them and send them back through. So it was definitely kind of scary, but we were completely successful. We hit a very high peak. Again, I don't know the exact number but it was in the thousands of loans, from little loans to very large loans and not one customer who applied did not get what they needed for, that was the right process and filled out the right amount. >> Well, that is an amazing story and really great support for the region, your Connecticut, the Boston area. So that's fantastic. I want to get into the rest of your story now. Let's start with some of the business drivers in banking. I mean, obviously online. A lot of people have sort of joked that many of the older people, who kind of shunned online banking would love to go into the branch and see their friendly teller had no choice, during this pandemic, to go to online. So that's obviously a big trend you mentioned, the data driven data warehouse, I want to understand that, but what at the top level, what are some of the key business drivers that are catalyzing your desire for change? >> The ability to give a customer, what they need at the time when they need it. And what I mean by that is that we have customer interactions in multiple ways. And I want to be able for the customer to walk into a bank or online and see the same format, and being able to have the same feel the same love, and also to be able to offer them the next best offer for them. But they're if they want looking for a new mortgage or looking to refinance, or whatever it is that they have that data, we have the data and that they feel comfortable using it. And that's an untethered banker. Attitude is, whatever my banker is holding and whatever the person is holding in their phone, that is the same and it's comfortable. So they don't feel that they've walked into the bank and they have to do fill out different paperwork compared to filling out paperwork on just doing it on their phone. >> You actually do want the experience to be better. And it is in many cases. Now you weren't able to do this with your existing I guess mainframe based Enterprise Data Warehouses. Is that right? Maybe talk about that a little bit? >> Yeah, we were definitely able to do it with what we have today the technology we're using. But one of the issues is that it's not timely. And you need a timely process to be able to get the customers to understand what's happening. You need a timely process so we can enhance our risk management. We can apply for fraud issues and things like that. >> Yeah, so you're trying to get more real time. The traditional EDW. It's sort of a science project. There's a few experts that know how to get it. You can so line up, the demand is tremendous. And then oftentimes by the time you get the answer, it's outdated. So you're trying to address that problem. So part of it is really the cycle time the end to end cycle time that you're progressing. And then there's, if I understand it residual benefits that are pretty substantial from a revenue opportunity, other offers that you can make to the right customer, that you maybe know, through your data, is that right? >> Exactly. It's drive new customers to new opportunities. It's enhanced the risk, and it's to optimize the banking process, and then obviously, to create new business. And the only way we're going to be able to do that is if we have the ability to look at the data right when the customer walks in the door or right when they open up their app. And by doing creating more to New York times near real time data, or the data warehouse team that's giving the lines of business the ability to work on the next best offer for that customer as well. >> But Paula, we're inundated with data sources these days. Are there other data sources that maybe had access to before, but perhaps the backlog of ingesting and cleaning in cataloging and analyzing maybe the backlog was so great that you couldn't perhaps tap some of those data sources. Do you see the potential to increase the data sources and hence the quality of the data or is that sort of premature? >> Oh, no. Exactly. Right. So right now, we ingest a lot of flat files and from our mainframe type of front end system, that we've had for quite a few years. But now that we're moving to the cloud and off-prem and on-prem, moving off-prem, into like an S3 Bucket, where that data we can process that data and get that data faster by using real time tools to move that data into a place where, like snowflake could utilize that data, or we can give it out to our market. Right now we're about we do work in batch mode still. So we're doing 24 hours. >> Okay. So when I think about the data pipeline, and the people involved, maybe you could talk a little bit about the organization. You've got, I don't know, if you have data scientists or statisticians, I'm sure you do. You got data architects, data engineers, quality engineers, developers, etc. And oftentimes, practitioners like yourself, will stress about, hey, the data is in silos. The data quality is not where we want it to be. We have to manually categorize the data. These are all sort of common data pipeline problems, if you will. Sometimes we use the term data Ops, which is sort of a play on DevOps applied to the data pipeline. Can you just sort of describe your situation in that context? >> Yeah, so we have a very large data ops team. And everyone that who is working on the data part of Webster's Bank, has been there 13 to 14 years. So they get the data, they understand it, they understand the lines of business. So it's right now. We could the we have data quality issues, just like everybody else does. But we have places in them where that gets cleansed. And we're moving toward and there was very much siloed data. The data scientists are out in the lines of business right now, which is great, because I think that's where data science belongs, we should give them and that's what we're working towards now is giving them more self service, giving them the ability to access the data in a more robust way. And it's a single source of truth. So they're not pulling the data down into their own, like Tableau dashboards, and then pushing the data back out. So they're going to more not, I don't want to say, a central repository, but a more of a robust repository, that's controlled across multiple avenues, where multiple lines of business can access that data. Is that help? >> Got it, Yes. And I think that one of the key things that I'm taking away from your last comment, is the cultural aspects of this by having the data scientists in the line of business, the lines of business will feel ownership of that data as opposed to pointing fingers criticizing the data quality. They really own that that problem, as opposed to saying, well, it's Paula's problem. >> Well, I have my problem is I have data engineers, data architects, database administrators, traditional data reporting people. And because some customers that I have that are business customers lines of business, they want to just subscribe to a report, they don't want to go out and do any data science work. And we still have to provide that. So we still want to provide them some kind of regiment that they wake up in the morning, and they open up their email, and there's the report that they subscribe to, which is great, and it works out really well. And one of the things is why we purchased Io-Tahoe was, I would have the ability to give the lines of business, the ability to do search within the data. And we'll read the data flows and data redundancy and things like that, and help me clean up the data. And also, to give it to the data analysts who say, all right, they just asked me they want this certain report. And it used to take okay, four weeks we're going to go and we're going to look at the data and then we'll come back and tell you what we can do. But now with Io-Tahoe, they're able to look at the data, and then in one or two days, they'll be able to go back and say, Yes, we have the data, this is where it is. This is where we found it. This is the data flows that we found also, which is what I call it, is the break of a column. It's where the column was created, and where it went to live as a teenager. (laughs) And then it went to die, where we archive it. And, yeah, it's this cycle of life for a column. And Io-Tahoe helps us do that. And we do data lineage is done all the time. And it's just takes a very long time and that's why we're using something that has AI in it and machine running. It's accurate, it does it the same way over and over again. If an analyst leaves, you're able to utilize something like Io-Tahoe to be able to do that work for you. Is that help? >> Yeah, so got it. So a couple things there, in researching Io-Tahoe, it seems like one of the strengths of their platform is the ability to visualize data, the data structure and actually dig into it, but also see it. And that speeds things up and gives everybody additional confidence. And then the other piece is essentially infusing AI or machine intelligence into the data pipeline, is really how you're attacking automation. And you're saying it repeatable, and then that helps the data quality and you have this virtual cycle. Maybe you could sort of affirm that and add some color, perhaps. >> Exactly. So you're able to let's say that I have seven cars, lines of business that are asking me questions, and one of the questions they'll ask me is, we want to know, if this customer is okay to contact, and there's different avenues so you can go online, do not contact me, you can go to the bank and you can say, I don't want email, but I'll take texts. And I want no phone calls. All that information. So, seven different lines of business asked me that question in different ways. One said, "No okay to contact" the other one says, "Customer 123." All these. In each project before I got there used to be siloed. So one customer would be 100 hours for them to do that analytical work, and then another analyst would do another 100 hours on the other project. Well, now I can do that all at once. And I can do those types of searches and say, Yes, we already have that documentation. Here it is, and this is where you can find where the customer has said, "No, I don't want to get access from you by email or I've subscribed to get emails from you." >> Got it. Okay. Yeah Okay. And then I want to go back to the cloud a little bit. So you mentioned S3 Buckets. So you're moving to the Amazon cloud, at least, I'm sure you're going to get a hybrid situation there. You mentioned snowflake. What was sort of the decision to move to the cloud? Obviously, snowflake is cloud only. There's not an on-prem, version there. So what precipitated that? >> Alright, so from I've been in the data IT information field for the last 35 years. I started in the US Air Force, and have moved on from since then. And my experience with Bob Graham, was with snowflake with working with GE Capital. And that's where I met up with the team from Io-Tahoe as well. And so it's a proven so there's a couple of things one is Informatica, is worldwide known to move data. They have two products, they have the on-prem and the off-prem. I've used the on-prem and off-prem, they're both great. And it's very stable, and I'm comfortable with it. Other people are very comfortable with it. So we picked that as our batch data movement. We're moving toward probably HVR. It's not a total decision yet. But we're moving to HVR for real time data, which is changed capture data, moves it into the cloud. And then, so you're envisioning this right now. In which is you're in the S3, and you have all the data that you could possibly want. And that's JSON, all that everything is sitting in the S3 to be able to move it through into snowflake. And snowflake has proven to have a stability. You only need to learn and train your team with one thing. AWS as is completely stable at this point too. So all these avenues if you think about it, is going through from, this is your data lake, which is I would consider your S3. And even though it's not a traditional data lake like, you can touch it like a Progressive or Hadoop. And then into snowflake and then from snowflake into sandbox and so your lines of business and your data scientists just dive right in. That makes a big win. And then using Io-Tahoe with the data automation, and also their search engine. I have the ability to give the data scientists and data analysts the way of they don't need to talk to IT to get accurate information or completely accurate information from the structure. And we'll be right back. >> Yeah, so talking about snowflake and getting up to speed quickly. I know from talking to customers you can get from zero to snowflake very fast and then it sounds like the Io-Tahoe is sort of the automation cloud for your data pipeline within the cloud. Is that the right way to think about it? >> I think so. Right now I have Io-Tahoe attached to my on-prem. And I want to attach it to my off-prem eventually. So I'm using Io-Tahoe data automation right now, to bring in the data, and to start analyzing the data flows to make sure that I'm not missing anything, and that I'm not bringing over redundant data. The data warehouse that I'm working of, it's an on-prem. It's an Oracle Database, and it's 15 years old. So it has extra data in it. It has things that we don't need anymore, and Io-Tahoe's helping me shake out that extra data that does not need to be moved into my S3. So it's saving me money, when I'm moving from off-prem to on-prem. >> And so that was a challenge prior, because you couldn't get the lines of business to agree what to delete, or what was the issue there? >> Oh, it was more than that. Each line of business had their own structure within the warehouse. And then they were copying data between each other, and duplicating the data and using that. So there could be possibly three tables that have the same data in it, but it's used for different lines of business. We have identified using Io-Tahoe identified over seven terabytes in the last two months on data that has just been repetitive. It's the same exact data just sitting in a different schema. And that's not easy to find, if you only understand one schema, that's reporting for that line of business. >> More bad news for the storage companies out there. (both laughs) So far. >> It's cheap. That's what we were telling people. >> And it's true, but you still would rather not waste it, you'd like to apply it to drive more revenue. And so, I guess, let's close on where you see this thing going. Again, I know you're sort of partway through the journey, maybe you could sort of describe, where you see the phase is going and really what you want to get out of this thing, down the road, mid-term, longer term, what's your vision or your data driven organization. >> I want for the bankers to be able to walk around with an iPad in their hand, and be able to access data for that customer, really fast and be able to give them the best deal that they can get. I want Webster to be right there on top with being able to add new customers, and to be able to serve our existing customers who had bank accounts since they were 12 years old there and now our multi whatever. I want them to be able to have the best experience with our bankers. >> That's awesome. That's really what I want as a banking customer. I want my bank to know who I am, anticipate my needs, and create a great experience for me. And then let me go on with my life. And so that follow. Great story. Love your experience, your background and your knowledge. I can't thank you enough for coming on theCube. >> Now, thank you very much. And you guys have a great day. >> All right, take care. And thank you for watching everybody. Keep right there. We'll take a short break and be right back. (gentle music)

>>from the Cube Studios in Palo Alto and Boston connecting with thought leaders all around the world. This is a cube conversation. >>Welcome back to the Cube's coverage of AWS Summit 2020. It's virtual online, and we're the Cube virtual here in our Palo Alto studios with our covert 19 crew. We're in place here, getting all the content remotely and also digitally. We're gonna bring that in the virtual. Got a great guest here as part of the program at AWS, but more importantly, part of the community doing its part both on building applications but also around covert 19 Dean, great CEO of Skylab APS ink. And they got an app that's being featured called Do your Part Hashtag Do your part, Dean, Thanks for spending the time to come in and talk with me. >>Excited to be here. >>You got to love this virtual ization going on, and I think you know the sad news around what's going on is really an indication of a New World order that we're seeing a new expectation of virtual izing the world that we live in. Obviously, we've been doing content at events. Now it's virtual or digital, but Still, people are online there. They're converging their lives with digital technologies. You guys are in that business. You have an app that's pretty compelling and relevant for the covert. 19. Take a minute to tell us about yourself and Skylab Appsync and do it. Do your part. Uh huh. >>Sure. Thank you. Thank you for having us on first fall. Well, what we do is kind of acts as we launch rapid response platforms. That entire platform in about a week's worth. The times If you have your on Facebook or INSTAGRAM, we'll be doing for causes tribes organizations or some sort of situation that requires there was something to get it quickly. Where you can shave were warning and track behaviors of that community to hit a certain goal. So since we've been doing this for years with all kinds of communities, we code it. We started hearing all these things on the news about companies coming forward and making face faster hand sanitizers, which were great products. But there's nothing out there that was tracking and helping the people that would be in quarantine. Hi, my little heroes inside all of us. So we knew that every night on the news. We were being told to stay home, but how do we track that stuff? So we just had the ability to do it, and we stepped forward and said Amazon aws But you help us and they said, Absolutely give you credits on servers will handle the server stuff. You have a platform and look for war. All these people at home kids and parents >>talk about the app itself. You guys are doing your part and flattening the curve. Tracing has become a topic that they were digitally connected. Why not use the technology for good? You guys have an effort to flatten the curve and track, and people are opting in its not like its surveillance government surveillance. This is actually an opt in. Do your part, you mentioned heroes. It's a hero journey, if you will. But people are doing Their part here is that we talk about the app. What's it's what's it all about? >>So when you go in that it's a one stop shop to learn about leaks to the CDC information. First of all, you want to know making sure you have real news getting quality information, so resource for education. But the unique thing about it is there's tons of those out there is that you have all the action's listed where you can now. Why should you? Why in your hands reaching out to here saying Thank you for spending time with pets, unplugging all the things that just not psychological but actually coded actions that are saving lives? People voluntarily going there report that they're doing that by clicking on it instantly shows up on the wall like Instagram feed, but it's private, and everyone now can see what people are doing. Their high fiving change each other on their badges, and major companies are jumping on board one wiser or a all kinds of companies outside of Amazon. But only when people are doing these things. We'd love the highlight report that these actions state. >>It's really also, I think it's well, first, it's awesome that you're doing in your agile enough with AWS. I want to get to that in a second. But I think the trend with code 19 that I'd like to get your thoughts on this. I think this has a lot of head room is not so much the feel good nature of it that I'm doing my part. But you're starting to see the user experience. People are tired, tired of sheltering in place. We're pushing now 23 months now into this and is gonna go on for more and more. Universities want to open. People want open up their jobs, and it's almost a new norm developing where the tribes, if you will, or groups of people. My daughter lives in San Francisco. She's got some roommates. They're sheltering in place. They're watching their actions. They also want to socialize. So it's almost like a badge collected license to get into a bar. It's like, Hey, I'm doing my part So it's It's almost a signaling kind of tribal thing that you're seeing. And I think this might be part of a future that we're gonna live in, because if I'm aware of my responsibilities and I'm doing my part, I want to communicate with people who are doing their part, and there >>are people who >>aren't doing their part by the way, that's well documented. And then there's a trust element in all this. >>Bring this >>together for us. What does this all means? That tribalism communalism, norms or developing interactions, and expectations are emerging. New roles and new responsibilities are emerging from this. Your thoughts >>well, you're hitting me on the head. Everything's troubling. That's what Sky was focused around. Is, for example, well, we started to help the cheerleading industry because it was a bunch of young athletes from ages 6 to 22. And we have over 40,000 kids, for example, that are tracking behaviors and wannabe recognized for doing the things that really matter in life, not just taking a selfie be rewarded for >>being cheat. >>So how do you compete with all the concepts of being famous for the wrong reasons? So, for example, let's cheer up. We work people for being better athletes, taking the actions that advanced. They're still being a better human beings doing their homework, getting Obama complement, doing the dishes and then making the world a better place. We were already doing that. Now I'm making the world a better place. Is in addition to stopping a bully. Reaching out don't mean girl. Now we have the corporate actions of making the world a better place. Track it, and what was shocking is they can now show that we've got kids that have had 200 days streaks over the last year, and they were addicted to the positive things, not just being cute anymore, also perfectly for covert actions in there. And people are just loving it. So we've got Bruce. Whether navy seals of whether it's with cheer or whether it's with any type of affinity group is out there. >>It's interesting because, you know, people love to see the lights on their selfies on their posts. This >>is a >>new kind of social signaling, but it's got again social responsibility. Kind of built in with the Gamification is in the right way. That's what you're saying. Is that what's happening? >>Yes, and you're sitting on a white paper they wrote recently. It's called Beyond. Gamification is via rest value reinforcement systems, and it's highly. It's much more addictive and sustained engaging for long term, because Gamification is what's done to you without really knowing via Rest is, you are the organization grabbing the steering wheel of deciding what other behaviors that you should be reinforcing. So the RS is the next evolution of Gamification. >>I think that's a huge point. I'd love to do a follow up segment on that because I think this is exactly what I call the Facebook blowback, which is the users, the product that's been kind of the Silicon Valley kind of vibe, and that's really true. Facebook has been, you know, not exploiting that. Using the free service in exchange for leveraging you and being game. Gamification applied to people here. The script is flipped. The users, they're telegraphing their data into a system that's rewarding them for positive things. And it could be on anything >>well and reward them in. Our system is when you're gonna grow a tribe. If you want to take something and grow bigger, you have to have the basics. Talk to me. Follow me. Here's all the resources of channels. Here's the behaviors I want you to do consistently, and then maybe here's some certification course you go. So it's like five little absent, one that are geared for growing the community because learning something I know is not proving that I am and I am is a huge gap between just know, and so everyone was teaching out there Today needs to start backing up their incredible keynotes with an incredible continuity program to create sustained trip transparent change. And you mentioned the GDP. Our rules the world has written, has wised up, realized. I don't mind telling me what I'm doing is long is I get to see what I'm doing. I'm in volunteering. Data don't go straight behind my back when I've been a part of that. Really, Where? On whether I'm general social media, they feel like they're part of the track and will mission. That's totally different than going to a specific apt to tell you when I do. >>This is innovation. I think this is a great, innovative trend. I think this is going to be around much longer on and have a lot, a lot, a lot of headroom to it, because I mean, every wants to be an influencer and have influence. But what you're getting at is interesting. It's reputation, it's who you are, and your actions are contributing to that. You can control that. That's a really great trend. Awesome stuff, great stuff. >>Well, you said very key work. We call them. Everyone likes to be influencers, but they don't feel they can compete with the beautiful, super powerful influencers on social media, where you've got 10 million followers or a 1,000,000 you have to just be the ultimate look, the ultimate fan. People are now realizing they could be micro influencers, and they're attitude. Will it? As long as you recognize us the same way, we want you to know that we're not just customer, not just a fan. I'm a micro influencers long. You'll recognize me and I'll tear the door down. >>Well, you know what? That's something that's near and dear to our hearts. After the Cube, we have a Cube alumni network. We don't try to monetize it. It's just really smart people we share content with. And no network is too small in our mind. We think that is ultimately where it's gonna go. Really appreciate that with Covert 19 as it evolves, you guys had this rapid app. Amazon's helping out. I'll see they're involved in giving you some credits. What's going on with Amazon? What's the relationship? Free credits? Are you an Amazon customer using Amazon Cloud? What's your relationship with AWS? >>Well, first, we wouldn't be able to do what we do about them. So all of our APs for communities are powered by Amazon in AWS. So in addition to that by the given its Cremins, they didn't just want to do your partner. They have all of the other existing communities rapidly deploy these actions, like the cheerleading young athletes like the ones for personal development. So we suddenly were able to track over a 1,000,000 actions taken in people's households of people have shown funny moments and give these with what they're doing is basically making off color. So Amazon really stepped up and help them not just the general public, but on the existing ones, with their leveraging technology that we run off of, as well as providing credits for all of those people. >>Well, congratulations for being featured on the Amazon Summit Virtual Appliances Cube online here is, well, virtual great stuff. Love to follow the progress quickly get a plug in for the company where you guys are at and share the length of that white paper. I think that's something that's worth promoting the white paper you mentioned. >>So the people get all this information sky dot world, so that's kind of the world that we're basically a platform that people have access to this white label. So you have a community organization that you want to be able to train, track to reward people, own your data, and we allow you own a copy of your of your source code. So we truly are empowered people. If you have a tribe, man, right, get your world. You know, this is where the science of engagement business we like to help you get that sustaining and, you know, what >>are you fast forward of? What's the pricing model? >>Yeah, so we started to set up a VM on a monthly fee unless they end up buying out the code and then typically just face to maintain it. So we were I was a customer, was someone was a young person who had developed a large tribe with decent sized multiple countries, and they realized I sold my company. All my people were on Facebook and Instagram, so I was only valued a certain value. Had I had all that community on a platform that I owned. Oh my gosh, I was like a younger rock star realized >>that you're rolling out the rock star and >>again having social >>graph and having that interest graph really creates a lot of value and congratulations. And I >>think you >>look forward to seeing the success. And thanks for doing your part. Literally, Figuratively with the march, check it out online bringing social responsibility and Gamification in the hands of the users where they can control it. The reputation and thank you for coming on the Cube. Really appreciate it. I'm John Furrier. Thanks for watching this Cube. Virtual covering AWS Summit Online. Their virtual event as we are in our quarantine crew studio here in Palo Alto doing all the remote interviews. I'm John Ferrier. Thanks for watching. Yeah, yeah, yeah, yeah.

la from Las Vegas it's the cube covering AWS reinvent 2019 brought to you by Amazon Web Services and in care along with its ecosystem partners hey welcome back everyone cubes live coverage of eight of us reinvent 2019 this is the cube seventh year covering Amazon reinvent it's their eighth year of the conference and want to just shout out to Intel for their sponsorship for these two amazing sets without their support we would be able to bring our mission of great content to you I'm John Force to many men we're here with the chief of AWS the chief executive officer Andy chassis tech athlete and himself three our keynotes welcome to the cube again great to see you great to be here thanks for having me guys congratulations on a great show a lot of great buzz thank you a lot of good stuff your keynote was phenomenal you get right into you giddy up right into as you say three hours 30 announcements you guys do a lot but what I liked the new addition in the last year and this year is the band house man yeah they're pretty good they hit the Queen note so that keeps it balanced so we're going to work on getting a band for the cube awesome so if I have to ask you what's your walk-up song what would it be there's so many choices depends what kind of mood I'm in but maybe times like these by the Foo Fighters these are unusual times right now Foo Fighters playing at the Amazon intersect show they are Gandy well congratulations on the intersect you got a lot going on intersect is the music festival I'll get that in a second but I think the big news for me is two things obviously we had a one-on-one exclusive interview and you laid out essentially what looks like was gonna be your keynote it was transformation key for the practice I'm glad to practice use me anytime yeah and I like to appreciate the comments on Jedi on the record that was great but I think the transformation story is a very real one but the NFL news you guys just announced to me was so much fun and relevant you had the Commissioner of NFL on stage with you talking about a strategic partnership that is as top-down aggressive goals you could get yeah I have Roger Goodell fly to a tech conference to sit with you and then bring his team talk about the deal well you know we've been partners with the NFL for a while with the next-gen stats are they using all their telecasts and one of the things I really like about Roger is that he's very curious and very interested in technology in the first couple times I spoke with him he asked me so many questions about ways the NFL might be able to use the cloud and digital transformation to transform their various experiences and he's always said if you have a creative idea or something you think that could change the world for us just call me is it or text me or email me and I'll call you back within 24 hours and so we've spent the better part of the last year talking about a lot of really interesting strategic ways that they can evolve their experience both for fans as well as their players and the player health and safe safety initiative it's so important in sports and particularly important with the NFL given the nature of the sport and they've always had a focus on it but what you can do with computer vision and machine learning algorithms and then building a digital athlete which is really like a digital twin of each athlete so you understand what does it look like when they're healthy what and compare that when it looks like they may not be healthy and be able to simulate all kinds of different combinations of player hits and angles and different plays so that you can try to predict injuries and predict the right equipment you need before there's a problem can be really transformational so it was super excited about it did you guys come up with the idea it was the collaboration between there's really a collaboration I mean they look they are very focused on player's safety and health and it's it's a big deal for their you know they have two main constituents that the players and fans and they care deeply about the players and it's a it's a hard problem in a sport like football but you watch it yeah I gotta say it does point out the use cases of what you guys are promoting heavily at the show here of the stage maker studio which is a big part of your keynote where they have all this data right and they're dated hoarders they've the hoard data but they're the manual process of going through the data it was a killer problem this is consistent with a lot of the enterprises that are out there they have more data than they even know so this seems to be a big part of the strategy how do you get the customers to actually a wake up to the fact that they got data and how do you tie that together I think in almost every company they know they have a lot of data and there are always pockets of people who want to do something with it but when you're gonna make these really big leaps forward these transformations so things like Volkswagen is doing with they're reinventing their factories in their manufacturing process or the NFL where they're gonna radically transform how they do players health and safety it starts top-down and if they if the senior leader isn't convicted about wanting to take that leap forward and trying something different and organizing the data differently and organizing the team differently and using machine learning and getting help from us and building algorithms and building some muscle inside the company it just doesn't happen because it's not in the normal machinery of what most companies do and so it all wait almost always starts top-down sometimes it can be the commissioner or the CEO sometimes it can be the CIO but it has to be senior level conviction or it does get off the ground and the business model impact has to be real for NFL they know concussions hurting their youth pipelining this is a huge issue for them is their business model they they lose even more players to lower extremity injuries and so just the notion of trying to be able to predict injuries and you know the impact it can have on rules the impact it can have on the equipment they use it's a huge game changer when they look at the next 10 to 20 years all right love geeking out on the NFL but no more do you know off camera a 10 man is here defeated season so everybody's a Patriots fan now it's fascinating to watch you and your three-hour keynote Vernor in his you know architectural discussion really showed how AWS is really extending its reach you know it's not just a place for a few years people have been talking about you know cloud as an operation operational model it's not a destination or a location but I felt that really was laid out is you talked about breadth and depth and Verna really talked about you know architectural differentiation people talk about cloud but there are very there are a lot of differences between the vision for where things are going help us understand and why I mean Amazon's vision is still a bit different from what other people talk about where this whole cloud expansion journey but put over what tagger label you want on it but you know the control plane and the technology that you're building and where you see that going well I think that we've talked about this a couple times we we have two macro types of customers we have those that really want to get at the load level building blocks and stitch them together creatively and however they see fit to create whatever is in there in their heads and then we have this second segment of customers who say look I'm willing to give up some of that flexibility in exchange for getting 80% of the way they're much faster in an abstraction that's different from those low level building blocks in both segments of builders we want to serve and serve well and so we built very significant offerings in both areas I think when you look at micro services you know some of it has to do with the fact that we have this very strongly held belief born out of several years at Amazon where you know the first seven or eight years of Amazon's consumer business we basically jumbled together all of the parts of our technology and moving really quickly and when we wanted to move quickly where you had to impact multiple internal development teams it was so long because it was this big ball this big monolithic piece and we got religion about that and trying to move faster in the consumer business and having to tease those pieces apart and it really was a lot of the impetus behind conceiving AWS where it was these low-level very flexible building blocks that don't try and make all the decisions for customers they get to make them themselves and some of the micro services that you saw Verner talking about just you know for instance what we what we did with nitro or even what we do with firecracker those are very much about us relentlessly working to continue to to tease apart the different components and even things that look like low-level building blocks over time you build more and more features and all of a sudden you realize they have a lot of things that are they were combined together that you wished weren't that slowed you down and so nitro was a completely reimagining of our hypervisor and virtualization layer to allow us both to let customers have better performance but also to let us move faster and have a better security story for our customers I got to ask you the question around transformation because I think it all points to that all the data points you got all the references goldman-sachs on stage at the keynote Cerner and the healthcare just an amazing example because I mean this demonstrating real value there there's no excuse I talked to someone who wouldn't be named last night and then around the area said the CIA has a cost bar like this cost up on a budget like this but the demand for mission based apps is going up exponentially so there's need for the cloud and so seeing more and more of that what is your top-down aggressive goals to fill that solution base because you're also very transformational thinker what is your what is your aggressive top-down goals for your organization because you're serving a market with trillions of dollars of span that's shifting that's on the table a lot of competition now sees it too they're gonna go after it but at the end of the day you have customers that have that demand for things apps yeah and not a lot of budget increase at the same time this is a huge dynamic what's your goals you know I think that at a high level are top-down aggressive goals so that we want every single customer who uses our platform to have an outstanding customer experience and we want that outstanding customer experience in part is that their operational performance and their security are outstanding but also that it allows them to build and it build projects and initiatives that change their customer experience and allow them to be a sustainable successful business over a long period of time and then we also really want to be the technology infrastructure platform under all the applications that people build and they were realistic we know that that you know the market segments we address with infrastructure software hardware and data center services globally are trillions of dollars in the long term it won't only be us but we have that goal of wanting to serve every application and that requires not just the security operational performance but also a lot of functionality a lot of capability we have by far the most amount of capability out there and yet I would tell you we have three to five years of items on our roadmap that customers want us to add and that's just what we know today well and any underneath the covers you've been going through some transformation when we talked a couple years ago about how serverless is impacting things I've heard that that's actually in many ways glue behind the two pizza teams to work between organizations talk about how the internal transformations are happening how that impacts your discussions with customers that are going through that transformation well I mean there's a lot of a lot of the technology we build comes from things that we're doing ourselves you know and that we're learning ourselves it's kind of how we started thinking about microservices serverless - we saw the need we know we would have we would build all these functions that when some kind of object came into an object store we would spin up compute all those tasks would take like three or four hundred milliseconds then we spin it back down and yet we'd have to keep a cluster up in multiple availability zones because we needed that fault tolerance and it was we just said this is wasteful and that's part of how we came up with lambda and that you know when we were thinking about lambda people understandably said well if we build lambda and we build the serverless event-driven computing a lot of people who are keeping clusters of instances aren't going to use them anymore it's going to lead to less absolute revenue for us but we we have learned this lesson over the last 20 years at Amazon which is if it's something it's good for customers you're much better off cannibalizing yourself and doing the right thing for customers and being part of shaping something and I think if you look at the history of Technology you always build things and people say well that's gonna cannibalize this and people are gonna spend less money what really ends up happening is they spend spend less money per unit of compute but it allows them to do so much more that the ultimately long-term end up being you know more significant customers I mean you are like beating the drum all the time customers what they say we implement the roadmap I got that you guys have that playbook down that's been really successful for you yeah two years ago you told me machine learning was really important to you because your customers told what's the next tranche of importance for customers what's on top of mine now as you look at this reinvent kind of coming to a close replays tonight you had conversations your your tech a fleet you're running around doing speeches talking to customers what's that next hill from from my fist machine learning today there's so much I mean that's not it's not a soup question you know I think we're still in this in the very early days of machine learning it's not like most companies have mastered yet even though they're using it much more than they did in the past but you know I think machine learning for sure I think the edge for sure I think that we're optimistic about quantum computing even though I think it'll be a few years before it's really broadly useful we're very enthusiastic about robotics I think the amount of functions are going to be done by these robotic applications are much more expansive than people realize it doesn't mean humans won't have jobs they're just going to work on things that are more value-added I thought we're believers in augmented and virtual reality we're big believers and what's going to happen with voice and I'm also I think sometimes people get bored you know I think you're even bored with machine learning maybe already but yet people get bored with the things you've heard about but I think just what we've done with the chips you know in terms of giving people 40% better price performance in the latest generation of x86 processors it's pretty unbelievable and the difference in what people are going to be able to do or just look at big data I mean big date we haven't gotten through big data where people have totally solved it the amount of data that companies want to store process and analyze is exponentially larger than it was a few years ago and it will I think exponentially increase again in the next few years you need different tools the service I think we're not we're not for with machine learning we're excited to get started because we have all this data from the video and you guys got sage maker yeah we call it a stairway to machine learning heaven we start with the data move up what now guys are very sophisticated with what you do with technology and machine learning and there's so much I mean we're just kind of again in this early innings and I think that it was soaked before sage maker was so hard for everyday developers and data scientists to build models but the combination of sage maker and what's happened with thousands of companies standardizing on it the last two years Plus now sage maker studio giant leap forward we hope to use the data to transform our experience with our audience and we're on Amazon Cloud I really appreciate that and appreciate your support if we're with Amazon and Instant get that machine learning going a little faster for us a big that'll be better if you have requests so any I'm you talked about that you've got the customers that are builders and the customers that need simplification traditionally when you get into the you know the heart of the majority of adoption of something you really need to simplify that environment but when I think about the successful enterprise of the future they need to be builders yeah so has the model flipped if you know I normally would said enterprise want to pay for solutions because they don't have the skill set but if they're gonna succeed in this new economy they need to go through that transformation that yeah so I mean are we in just a total new era when we look back will this be different than some of these previous waves it's a it's a really good question Stu and I I don't think there's a simple answer to it I think that a lot of enterprises in some ways I think wish that they could just skip the low level building blocks and and only operate at that higher level abstraction it's why people were so excited by things like sage maker or code guru or Kendra or contact lens these are all services that allow them to just send us data and then run it on our models and get back the answers but I think one of the big trends that we see with enterprises is that they are taking more and more of their development in-house and they are wanting to operate more and more like startups I think that they admire what companies like Airbnb and Pinterest and slack and and you know Robin Hood and a whole bunch of those companies stripe have done and so when you know I think you go through these phases and errors where there are waves of success at different companies and then others want to follow that success and and replicate and so we see more and more enterprises saying we need to take back a lot of that development in-house and as they do that and as they add more developers those developers in most cases like to deal with the building blocks and they have a lot of ideas on how they can create us to creatively stitch them together on that point I want to just quickly ask you on Amazon versus other clouds because you made a comment to me in our interview about how hard it is to provide a service that to other people and it's hard to have a service that you're using yourself and turn that around and the most quoted line in my story was the compression algorithm there's no compression outliving for experience which to me is the diseconomies of scale for taking shortcuts yeah and so I think this is a really interesting point just add some color comments or I think this is a fundamental difference between AWS and others because you guys have a trajectory over the years of serving at scale customers wherever they are whatever they want to do now you got micro services it's even more complex that's hard yeah how about that I think there are a few elements to that notion of there's no compression algorithm I think the first thing to know about AWS which is different is we just come from a different heritage in a different background we sweep ran a business for a long time that was our sole business that was a consumer retail business that was very low margin and so we had to operate a very large scale given how many people were using us but also we had to run infrastructure services deep in the stack compute storage and database in reliable scalable data centers at very low costs and margins and so when you look at our our business it actually today I mean it's it's a higher margin business in our retail business the lower margin business and software companies but at real scale it's a it's a high-volume relatively low margin business and the way that you have to operate to be successful with those businesses and the things you have to think about and that DNA come from the type of operators that we have to be in our consumer retail business and there's nobody else in our space that does that you know the way that we think about cost the way we think about innovation and the data center and and I also think the way that we operate services and how long we've been operating services of the company it's a very different mindset than operating package software then you look at when you think about some of the issues and very large scale cloud you can't learn some of those lessons until you get two different elbows of the curve and scale and so what I was telling you is it's really different to run your own platform for your own users where you get to tell them exactly how it's going to be done but that's nothing really the way the real world works I mean we have millions of external customers who use us from every imaginable country and location whenever they want without any warning for lots of different use cases and they have lots of design patterns and we don't get to tell them what to do and so operating a cloud like that at a scale that's several times larger the next few providers combined is a very different endeavor and a very different operating rigor well you got to keep raising the bar you guys do a great job really impress again another tsunami of announcements in fact you had to spill the beans early with quantum the day before the event tight schedule I gotta ask you about the music festival because I think there's a really cool innovation it's the inaugural intersex conference yeah it's not part of replay which is the concert tonight right it's a whole new thing big music act you're a big music buff your daughter's an artist why did you do this what's the purpose what's your goal yeah it's an experiment I think that what's happened is that reinvent has gotten so big with 65,000 people here that to do the party which we do every year it's like a thirty five forty thousand person concert now which means you have to have a location that has multiple stages and you know we thought about it last year when we were watching it and we said we're kind of throwing like a four hour music festival right now there's multiple stages and it's quite expensive to set up that set for our partying we said well maybe we don't have to spend all that money for four hours in the rip it apart because actually the rent to keep those locations for another two days is much smaller than the cost of actually building multiple stages and so we we would try it this year we're very passionate about music as a business and I think we are I think our customers feel like we throw in a pretty good music party the last few years and we thought we were trying at a larger scale as an experiment and if you look at the economics the headliners real quick the Foo Fighters are headlining on Saturday night Anderson Park and the free Nashville free Nationals Brandi Carlile Shawn Mullins Willie Porter it's a good set Friday night it's back in Kacey Musgraves so it's it's a really great set of about 30 artists and we're hopeful that if we can build a great experience that people want to attend that we can do it it's scale and it might be something that you know both pays for itself and maybe helps pay for reinvent to overtime and you know I think that we're also thinking about it as not just a music concert and festival the reason we named it intersect is that we want an intersection of music genres and people and ethnicities and age groups and art and Technology all there together and this will be the first year we try it it's an experiment and we're really excited about I'm gone congratulations all your success and I want to thank you we've been seven years here at reinvent we've been documenting the history two sets now once-dead upstairs so appreciate a cube is part of reinvent you know you guys really are a part of the event and we really appreciate your coming here and I know people appreciate the content you create as well and we just launched cube 365 on Amazon Marketplace built on AWS so thanks for letting us cool build on the platform appreciate it thanks for having me guys Jesse the CEO of AWS here inside the cube it's our seventh year covering and documenting they're just the thunderous innovation that Amazon is doing they're really doing amazing work building out the new technologies here in the cloud computing world I'm John Force too many men be right back with more after this short break [Music]

>> From San Francisco, it's theCUBE, covering Day2IQ, brought to you by Day2IQ. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're in downtown San Francisco at the Day2IQ headquarters. They used to be called Mesosphere. They rebranded the company. They've got a much bigger focus than just Mesos and supporting Mesos. So we're here to get the story, really talk about enterprise's journey to cloud native, and we're excited to have our first guest. He's Brian Kenyon, the chief strategy officer. Brian, great to see you. >> Thanks for having me. >> Absolutely. So DayQI, Day2IQ. >> Correct. >> I'm going to get it eventually, by the end of the day. Interesting name. What does Day2IQ mean? Why did you guys rebrand the company that? >> Yeah, absolutely. So we were formerly known as Mesosphere, and the technology that we founded the company on was an open source package called Mesos, so the name naturally had a very close tie with Mesos and Mesosphere. So as we looked to rebrand the company and really enter the market with some of the changes we've seen in the evolution of cloud native, we focused on where customers were having trouble, where they were focused on operations, how they were going to take these concepts and these great ideas that were pervasive in the concept of cloud native and make them institutionalized and operationalized inside their companies. And what we found was, you know, day zero is when you played around and tested things, and day one is when you got it installed and stood up, but day two is when you really focused on the operations. How do I make this enterprise-ready? How do I make this fit my business? All of that happened on day two and after. So we saw that as a pretty natural way to focus our energy and focus our market penetration on day two. >> Right. And you also expanded beyond just kind of the Mesos ecosystem into some other areas, in containers, in Kubernetes, also data. So you guys are taking a little broader approach than maybe the company had at the original launch. >> Yeah, absolutely. And you've heard from one of our founders already and you spoke to our head of engineering. So I'm the newest of those, right? I joined in February, so I'm just, you know, almost 10 months in. So when I joined, I spent a lot of time meeting with our customers, talking to partners, talking to other folks and vendors in the space, and what we saw was there was a massive shift happening from where cloud native started maybe three, four, five years ago to where it is today, and one of the biggest changes has been around the emergence of Kubernetes, which has turned into a de facto standard for containers in cloud native. And so as we've evolved and moved into this D2IQ name, as we've started focusing on meeting our customer, we've obviously taken on a bigger stance inside the Kubernetes community and the Kubernetes product lines. >> Right. So what did you see? I mean, you're a long-time security executive. You've been in strategy and security for years and years and years. What did you see in this opportunity with a small start-up to get you to leave kind of the safe, comfortable, pretty standard corporate job into jumping back into this-- >> Nobody's ever said security's safe, so that's awesome. >> Well, safe certainly in terms of job security. (mumbles) my goodness, a big shill out there these days. >> It is, it is. >> But what did you see? >> I saw the future, is really what I saw. When you really took a step back and you looked at where compute was going and how organizations were starting to adopt new application methodologies, new application architectures, it was very clear that cloud had taken on a big portion of that and the concept of cloud native and open source technologies was becoming more and more prominent. And so as we looked at this, not only did we see a unique opportunity with the cloud native space, but if you fast forward a couple years, customers are going to be coming back around and starting to have conversations around security. How do I secure this? What, how do my CISOs and my operational folks in security understand this and how do they really start to apply the same controls and visibility to it? So it was a unique opportunity to get in and focus on where the future of our industry's going. >> Right. So it's an interesting thing with open source, and open source specifically in the enterprise. I think my favorite open source quote is, yeah, it's free like a puppy. You know, it's not free. You need support and you need training and you need a lot of help. So when you guys work with enterprises and they're incorporating more and more open source into their technology stack, what are some of the challenges that you guys are coming in to help them to actually get beyond a simple free download and the latest cool version to actually running in production, heavy duty loads, really important workloads. >> Absolutely. Yeah, one of the biggest shortfalls we see is obviously expertise, right? So there's a massive amount of innovation and capability that can be, can really be captured through open source software. The challenge is, it's all community-based. So folks contribute code, they sign it in, it's available for everybody to use, but how long is that code updated for? How long is it maintained? How do new features get added? What you see is you see a huge spike in interest and enthusiasm, and then just like every other hype cycle, you get to a trough of disillusionment where people move on to the next thing and the next thing in the open source community. And so organizations who want to leverage that innovation, want to focus their operations around open source, either for cost savings or time to market, find themselves a couple years later looking at code that's been abandoned, projects that aren't maintained anymore. We saw this in security with things like OpenSSL, right? One of the largest SSL libraries used across the entire security landscape. There were two people in the world maintaining that code. And so when a massive security vulnerability hit, organizations were scrambling. We want to stop that now for organizations that want to use open source. We, Day2IQ, want to bring our innovation, our expertise, to bring that open source to the customers and make sure that it's enterprise-ready, it's enterprise-supported, and it's enterprise-scalable. >> Right. So you guys have basically three market offerings, if I understand right. You've got a solution set where you're taking the core software and building solutions around it. You've got services, professional services, to get it in, get it up, and probably supported, so I have a 1-800 somebody to call, please, which, you couldn't call those two people in that case. >> Exactly. >> And then training, is that right? So those are how you're basically enterprise-hardening an open source kernel to get to a great solution for the customer. >> Yeah, what I'd also add in there is services. So whether it's advisory services, implementation services, or just kind of more traditional, our focus is really about meeting the customer where they need us. If you look at cloud and cloud native today, almost every customer across the globe is at a different evolution or a different maturity in that journey, and so some are at the very beginning where they're learning. Others are more towards the end where they're focused on operations and how do I streamline this, how do I hire the right folks. So we've taken a product, services, support, and training strategy that allows us to meet our customers where they are in their cloud native journey and assures us that we can provide the right level of expertise regardless of where they are. >> Right. What's been the biggest, of all the challenges that you see when people are getting started, what's some of the biggest challenges that you just see over and over and over again that you know you're going to get walking in the door? >> Over and over, you see training is just a constant, across the entire industry. No matter where a customer is in their evolution or their journey, they're constantly having to train, whether they're hiring and then training folks on the new way of developing or they're taking developers who have been building code and building applications in virtual machines or old monoliths for years that they want to train to this new paradigm. Training is a huge constant. The other piece is people are looking to rationalize their infrastructure. So services, we are in a very services-led industry right now where we can come in and help customers get stock of where are we today and where do we want to go long-term, and then put them on a plan, put them on a program or a path where they can achieve those outcomes, but do it in a way that's not disruptive or adds (mumbles). >> Right, 'cause the complexity just continues to increase. It's funny, you know, both Amazon introduced a piece of Amazon Cloud you can stick in your data center, and Google introduced a piece of Google Cloud that you can stick in your data center, and Microsoft recently introduced a piece of Azure that you can stick in your data center. So kind of this, you know, kind of real aggressive embracing of hybrid and this real embracing of complex setups where you can partition your workload based on where you think that workload should run today is really gaining hold. So the complexity is only going up, not going down. >> It is, you're absolutely right. And I will tell you, what you just brought up is a great example of why the complexity's going up. On-prem is a massively different, materially different environment than the clouds. The clouds are built on a margin, right? They're built on, if I take the same server and do this over and over again, I get repeatability, I get consistency, I get a very finite platform. If you look at how on-prem is, the traditional data center, you buy some servers from Dell, some servers from HP, storage from EMC, storage from HP. You've got all different types of hardware and software in there. So fixing that on-prem cloud is hard, and the clouds are struggling with this because the concept of taking their very clean, vanilla infrastructure and bringing that to the traditional on-premise is failing. That's where we shine. That's where we've built. That's where Mesosphere got their initial start was taking the cloud concept and bring it to the traditional data center. So we're helping clouds extend now by being that on-prem piece that speaks seamlessly with the clouds that our customers choose to use. >> Right. So I think, too, initially, the cloud was seen as a way to save money, and I've seen that evolve over time. It's really much more about speed and agility in your development cycles and getting new products to market. Do customers grok that? Are they still kind of wrestling with the cost savings and this is kind of an alternative way to buy compute and networking and capacity, or are they really moving fast because of the speed and the competitive threats? >> So I think it's interesting, and it varies, but I will tell you just from my lens, I'll say that a lot of customers are confused. They went to the cloud initially because they believe they wanted to be out of the data center game. It was easier for Amazon or Microsoft or Google to manage the data center than it was for their own IT teams. And so they shifted infrastructure up there, and then what they saw was the promises of hyperscaling, the promises of this elasticity. Your application grows as more users show up. They never realized that because those applications were built under a different premise, under a different architecture, and don't leverage the cloud native capabilities. So you're seeing a shift of people who've moved infrastructure or applications to the cloud to get out of the data center are now saying, okay, I'm kind of locked in, but where do I get my operational efficiency? Where do I get my hyperscaling? How do I get that? And now you're staring to see that shift from just using the clouds as infrastructure to more moving towards microservices, containers, and some of the things that Day2IQ helps with. >> Right, right. It's pretty funny, too, right? 'Cause the apps used to have to be built for the infrastructure on which you were going to deploy them. >> That's right. >> That's now flipped upside down, right? Now the app, the infrastructure needs to support the app. The app comes first, the infrastructure second. >> That's right. >> So having an architecture, you got to have the new architecture. As you said, you just can't simply flip the functionality of an old architecture into a new paradigm. >> And then expect you're going to get the same outcomes. >> Right, right. >> Yeah, very true. >> All right, so before I let you go, I want to get your perspective specifically on security, 'cause again, you were in the security space for a long time. Security's a hot space. Everyone says security has to be baked in everywhere. It can't be the castle and moat anymore. So with your security hat on as you kind of see these migrations and you see these new deployments and you see this move to cloud native, what do you think about from security? Are people baking it in enough? Are they thinking about it in the right way? Is it just such a fundamental shift that they need to think about security and really baking it in from the bottom to the top? >> They absolutely do. And I'll tell you what the scariest thing is, if I go through my CISO networks and talk to folks who are on that side of the fence, they're not even educated to this cloud native space yet. They don't really understand how it's happening and how it's evolving and what that means. So there's a huge education that needs to happen in security, but these things need to be bolted on from the beginning. I'll give you an example. Some of the value that comes from operating cloud native is that your ability to push code and push changes is very agile and quick. So it's encouraged in a cloud native type of architecture that a company can make 100 to 200, 300 code changes a day. >> Right. >> Right? When I grew up, you'd make those monthly, quarterly, right? 'Cause you had a whole bunch of testing. And how they push code multiple times a day. If you don't have your security team in lockstep with those developers and operations staff, how quickly can you get out of compliance? How quickly can you erode your security posture? These are all questions that have to be answered, and we're just at the very earliest stages of getting that. >> Right, and we didn't even talk about IoT and edge devices. >> Absolutely. >> Which opens up a whole different kind of threat surface. >> Absolutely. >> Yeah. >> Absolutely. >> All right, Brian, well, thanks for taking a few minutes. Good luck on the journey and hope things go super for you here. >> Thanks for having me. >> All right, he's Brian, I'm Jeff. You're watching theCUBE. We're at Day2 headquarters, Day2IQ headquarters in downtown San Francisco. Thanks for watching. We'll see you next time. (techno music)