>> Announcer: Live from New York, it's theCUBE! Covering Machine Learning Everywhere: Build Your Ladder To AI. Brought to you by IBM. >> Well, good morning! Welcome here on theCUBE. Along with Dave Vellante, I'm John Walls. We're in Midtown New York for IBM's Machine Learning Everywhere: Build Your Ladder To AI. Great lineup of guests we have for you today, looking forward to bringing them to you, including world champion chess master Garry Kasparov a little bit later on. It's going to be fascinating. Dave, glad you're here. Dave, good to see you, sir. >> John, always a pleasure. >> How you been? >> Up from DC, you know, I was in your area last week doing some stuff with John Furrier, but I've been great. >> Stopped by the White House, drop in? >> You know, I didn't this time. No? >> No. >> Dave: My son, as you know, goes to school down there, so when I go by my hotel, I always walk by the White House, I wave. >> Just in case, right? >> No reciprocity. >> Same deal, we're in the same boat. Let's talk about what we have coming up here today. We're talking about this digital transformation that's going on within multiple industries. But you have an interesting take on it that it's a different wave, and it's a bigger wave, and it's an exciting wave right now, that digital is creating. >> Look at me, I've been around for a long time. I think we're entering a new era. You know, the great thing about theCUBE is you go to all these events, you hear the innovations, and we started theCUBE in 2010. The Big Data theme was just coming in, and it appeared, everybody was very excited. Still excited, obviously, about the data-driven concept. But we're now entering a new era. It's like every 10 years, the parlance in our industry changes. It was cloud, Big Data, SaaS, mobile, social. It just feels like, okay, we're here. We're doing that now. That's sort of a daily ritual. We used to talk about how it's early innings. It's not anymore. It's the late innings for those. I think the industry is changing. The describers of what we're entering are autonomous, pervasive, self-healing, intelligent. When you infuse artificial intelligence, I'm not crazy about that name, but when you infuse that throughout the landscape, things start to change. Data is at the center of it, but I think, John, we're going to see the parlance change. IBM, for example, uses cognitive. People use artificial intelligence. I like machine intelligence. We're trying to still figure out the names. To me, it's an indicator that things are changing. It's early innings now. What we're seeing is a whole new set of opportunities emerging, and if you think about it, it's based on this notion of digital services, where data is at the center. That's something that I want to poke at with the folks at IBM and our guests today. How are people going to build new companies? You're certainly seeing it with the likes of Uber, Airbnb, Waze. It's built on these existing cloud and security, off-the-shelf, if you will, horizontal technologies. How are new companies going to be built, what industries are going to be disruptive? Hint, every industry. But really, the key is, how will existing companies keep pace? That's what I really want to understand. >> You said, every industry's going to be disrupted, which is certainly, I think, an exciting prospect in some respects, but a little scary to some, too, right? Because they think, "No, we're fat and happy "and things are going well right now in our space, "and we know our space better than anybody." Some of those leaders might be thinking that. But as you point out, digital technology has transformed to the extent now that there's nobody safe, because you just slap this application in, you put this technology in, and I'm going to change your business overnight. >> That's right. Digital means data, data is at the center of this transformation. A colleague of mine, David Moschella, has come up with this concept of the matrix, and what the matrix is is a set of horizontal technology services. Think about cloud, or SaaS, or security, or mobile, social, all the way up the stack through data services. But when you look at the companies like Airbnb and Uber and, certainly, what Google is doing, and Facebook, and others, they're building services on top of this matrix. The matrix is comprised of vertical slices by industry and horizontal slices of technology. Disruptors are cobbling together through software and data new sets of services that are disrupting industries. The key to this, John, in my view, anyway, is that, historically, within healthcare or financial services, or insurance, or manufacturing, or education, those were very siloed. But digital and data allows companies and disruptors to traverse silos like never before. Think about it. Amazon buying Whole Foods. Apple getting into healthcare and financial services. You're seeing these big giants disrupt all of these different industries, and even smaller guys, there's certainly room for startups. But it's all around the data and the digital transformation. >> You spoke about traditional companies needing to convert, right? Needing to get caught up, perhaps, or to catch up with what's going on in that space. What do you do with your workforce in that case? You've got a bunch of great, hardworking people, embedded legacy. You feel good about where you are. And now you're coming to that workforce and saying, "Here's a new hat." >> I think that's a great question. I think the concern that one would have for traditional companies is, data is not foundational for most companies. It's not at their core. The vast majority of companies, the core are the people. You hear it all the time. "The people are our greatest asset." That, I hate to say it, but it's somewhat changing. If you look at the top five companies by market cap, their greatest asset is their data, and the people are surrounding that data. They're very, very important because they know how to leverage that data. But if you look at most traditional companies, people are at their core. Data is kind of, "Oh, we got this bolt-on," or it's in a bunch of different silos. The big question is, how do they close that gap? You're absolutely right. The key is skillsets, and the skills have to be, you know, we talk about five-tool baseball players. You're a baseball fan, as am I. Well, you need multi-tool players, those that understand not only the domain of whether it's marketing or sales or operational expertise or finance, but they also require digital expertise. They know, for example, if you're a marketing professional, they know how to do hypertargeting. They know how to leverage social. They know how to do SEO, all these digital skills, and they know how to get information that's relevant and messaging out into the marketplace and permeate that. And so, we're entering, again, this whole new world that's highly scalable, highly intelligent, pervasive, autonomous. We're going to talk about that today with a lot of their guests, with a lot of our guests, that really are kind of futurists and have thought through, I think, the changes that are coming. >> You can't have a DH anymore, right, that's what you're saying? You need a guy that can play the field. >> Not only play the field, not only a utility player, but somebody who's a utility player, but great. Best of breed at all these different skillsets. >> Machine learning, we haven't talked much about that, and another term, right, that certainly has different definitions, but certainly real specific applications to what's going on today. We'll talk a lot about ML today. Your thoughts about that, and how that squares into the artificial intelligence picture, and what we're doing with all those machines out there that are churning 24/7. >> Yeah, so, real quick, I know we're tight on time here. Artificial intelligence to me is the umbrella. Machine learning is the application of math and algorithms to solve a particular problem or answer a particular question. And then there's deep learning, which is highly focused neural networks that go deeper and deeper and deeper, and become auto-didactic, self-learning, in a manner. Those are just the very quick and rudimentary description. Machine learning to me is the starting point, and that's really where organizations really want to start to learn and begin to close the gap. >> A lot of ground to cover, and we're going to do that for you right here on theCUBE as we continue our coverage of Machine Learning Everywhere: Your Ladder To AI, coming up here, IBM hosting us in Midtown, New York. Back with more here on theCUBE in just a bit. (fast electronic music)

foreign welcome back to re invent 2022 we're wrapping up four days well one evening and three solid days wall-to-wall of cube coverage I'm Dave vellante John furrier's birthday is today he's on a plane to London to go see his nephew get married his his great Sister Janet awesome family the furriers uh spanning the globe and uh and John I know you wanted to be here you're watching in Newark or you were waiting to uh to get in the plane so all the best to you happy birthday one year the Amazon PR people brought a cake out to celebrate John's birthday because he's always here at AWS re invented his birthday so I'm really pleased to have two really special guests uh former Cube host Cube Alum great wikibon contributor Stu miniman now with red hat still good to see you again great to be here Dave yeah I was here for that cake uh the twitterverse uh was uh really helping to celebrate John's birthday today and uh you know always great to be here with you and then with this you know Awesome event this week and friend of the cube of many time Cube often Cube contributor as here's a cube analyst this week as his own consultancy sarbj johal great to see you thanks for coming on good to see you Dave uh great to see you stu I'm always happy to participate in these discussions and um I enjoy the discussion every time so this is kind of cool because you know usually the last day is a getaway day and this is a getaway day but this place is still packed I mean it's I mean yeah it's definitely lighter you can at least walk and not get slammed but I subjit I'm going to start with you I I wanted to have you as the the tail end here because cause you participated in the analyst sessions you've been watching this event from from the first moment and now you've got four days of the Kool-Aid injection but you're also talking to customers developers Partners the ecosystem where do you want to go what's your big takeaways I think big takeaways that Amazon sort of innovation machine is chugging along they are I was listening to some of the accessions and when I was back to my room at nine so they're filling the holes in some areas but in some areas they're moving forward there's a lot to fix still it doesn't seem like that it seems like we are done with the cloud or The Innovation is done now we are building at the millisecond level so where do you go next there's a lot of room to grow on the storage side on the network side uh the improvements we need and and also making sure that the software which is you know which fits the hardware like there's a specialized software um sorry specialized hardware for certain software you know so there was a lot of talk around that and I attended some of those sessions where I asked the questions around like we have a specialized database for each kind of workload specialized processes processors for each kind of workload yeah the graviton section and actually the the one interesting before I forget that the arbitration was I asked that like why there are so many so many databases and IRS for the egress costs and all that stuff can you are you guys thinking about reducing that you know um the answer was no egress cost is not a big big sort of uh um show stopper for many of the customers but but the from all that sort of little discussion with with the folks sitting who build these products over there was that the plethora of choice is given to the customers to to make them feel that there's no vendor lock-in so if you are using some open source you know um soft software it can be on the you know platform side or can be database side you have database site you have that option at AWS so this is a lot there because I always thought that that AWS is the mother of all lock-ins but it's got an ecosystem and we're going to talk about exactly we'll talk about Stu what's working within AWS when you talk to customers and where are the challenges yeah I I got a comment on open source Dave of course there because I mean look we criticized to Amazon for years about their lack of contribution they've gotten better they're doing more in open source but is Amazon the mother of all lock-ins many times absolutely there's certain people inside Amazon I'm saying you know many of us talk Cloud native they're like well let's do Amazon native which means you're like full stack is things from Amazon and do things the way that we want to do things and you know I talk to a lot of customers they use more than one Cloud Dave and therefore certain things absolutely I want to Leverage The Innovation that Amazon has brought I do think we're past building all the main building blocks in many ways we are like in day two yes Amazon is fanatically customer focused and will always stay that way but you know there wasn't anything that jumped out at me last year or this year that was like Wow new category whole new way of thinking about something we're in a vocals last year Dave said you know we have over 200 services and if we listen to you the customer we'd have over two thousand his session this week actually got some great buzz from my friends in the serverless ecosystem they love some of the things tying together we're using data the next flywheel that we're going to see for the next 10 years Amazon's at the center of the cloud ecosystem in the IT world so you know there's a lot of good things here and to your point Dave the ecosystem one of the things I always look at is you know was there a booth that they're all going to be crying in their beer after Amazon made an announcement there was not a tech vendor that I saw this week that was like oh gosh there was an announcement and all of a sudden our business is gone where I did hear some rumbling is Amazon might be the next GSI to really move forward and we've seen all the gsis pushing really deep into supporting Cloud bringing workloads to the cloud and there's a little bit of rumbling as to that balance between what Amazon will do and their uh their go to market so a couple things so I think I think we all agree that a lot of the the announcements here today were taping seams right I call it and as it relates to the mother of all lock-in the reason why I say that it's it's obviously very much a pejorative compare Oracle company you know really well with Amazon's lock-in for Amazon's lock-in is about bringing this ecosystem together so that you actually have Choice Within the the house so you don't have to leave you know there's a there's a lot to eat at the table yeah you look at oracle's ecosystem it's like yeah you know oracle is oracle's ecosystem so so that is how I think they do lock in customers by incenting them not to leave because there's so much Choice Dave I agree with you a thousand I mean I'm here I'm a I'm a good partner of AWS and all of the partners here want to be successful with Amazon and Amazon is open to that it's not our way or get out which Oracle tries how much do you extract from the overall I.T budget you know are you a YouTube where you give the people that help you create a large sum of the money YouTube hasn't been all that profitable Amazon I think is doing a good balance of the ecosystem makes money you know we used to talk Dave about you know how much dollars does VMware make versus there um I think you know Amazon is a much bigger you know VMware 2.0 we used to think talk about all the time that VMware for every dollar spent on VMware licenses 15 or or 12 or 20 were spent in the ecosystem I would think the ratio is even higher here sarbji and an Oracle I would say it's I don't know yeah actually 1 to 0.5 maybe I don't know but I want to pick on your discussion about the the ecosystem the the partner ecosystem is so it's it's robust strong because it's wider I was I was not saying that there's no lock-in with with Amazon right AWS there's lock-in there's lock-in with everything there's lock-in with open source as well but but the point is that they're they're the the circle is so big you don't feel like locked in but they're playing smart as well they're bringing in the software the the platforms from the open source they're picking up those packages and saying we'll bring it in and cater that to you through AWS make it better perform better and also throw in their custom chips on top of that hey this MySQL runs better here so like what do you do I said oh Oracle because it's oracle's product if you will right so they are I think think they're filing or not slenders from their go to market strategy from their engineering and they listen to they're listening to customers like very closely and that has sort of side effects as well listening to customers creates a sprawl of services they have so many services and I criticized them last year for calling everything a new service I said don't call it a new service it's a feature of a existing service sure a lot of features a lot of features this is egress our egress costs a real problem or is it just the the on-prem guys picking at the the scab I mean what do you hear from customers so I mean Dave you know I I look at what Corey Quinn talks about all the time and Amazon charges on that are more expensive than any other Cloud the cloud providers and partly because Amazon is you know probably not a word they'd use they are dominant when it comes to the infrastructure space and therefore they do want to make it a little bit harder to do that they can get away with it um because um yeah you know we've seen some of the cloud providers have special Partnerships where you can actually you know leave and you're not going to be charged and Amazon they've been a little bit more flexible but absolutely I've heard customers say that they wish some good tunning and tongue-in-cheek stuff what else you got we lay it on us so do our players okay this year I think the focus was on the upside it's shifting gradually this was more focused on offside there were less talk of of developers from the main stage from from all sort of quadrants if you will from all Keynotes right so even Werner this morning he had a little bit for he was talking about he he was talking he he's job is to Rally up the builders right yeah so he talks about the go build right AWS pipes I thought was kind of cool then I said like I'm making glue easier I thought that was good you know I know some folks don't use that I I couldn't attend the whole session but but I heard in between right so it is really adopt or die you know I am Cloud Pro for last you know 10 years and I think it's the best model for a technology consumption right um because of economies of scale but more importantly because of division of labor because of specialization because you can't afford to hire the best security people the best you know the arm chip designers uh you can't you know there's one actually I came up with a bumper sticker you guys talked about bumper sticker I came up with that like last couple of weeks The Innovation favorite scale they have scale they have Innovation so that's where the Innovation is and it's it's not there again they actually say the market sets the price Market you as a customer don't set the price the vendor doesn't set the price Market sets the price so if somebody's complaining about their margins or egress and all that I think that's BS um yeah I I have a few more notes on the the partner if you you concur yeah Dave you know with just coming back to some of this commentary about like can Amazon actually enable something we used to call like Community clouds uh your companies like you know Goldman and NASDAQ and the like where Industries will actually be able to share data uh and you know expand the usage and you know Amazon's going to help drive that API economy forward some so it's good to see those things because you know we all know you know all of us are smarter than just any uh single company together so again some of that's open source but some of that is you know I think Amazon is is you know allowing Innovation to thrive I think the word you're looking for is super cloud there well yeah I mean it it's uh Dave if you want to go there with the super cloud because you know there's a metaphor for exactly what you described NASDAQ Goldman Sachs we you know and and you know a number of other companies that are few weeks at the Berkeley Sky Computing paper yeah you know that's a former supercloud Dave Linthicum calls it metacloud I'm not really careful I mean you know I go back to the the challenge we've been you know working at for a decade is the distributed architecture you know if you talk about AI architectures you know what lives in the cloud what lives at the edge where do we train things where do we do inferences um locations should matter a lot less Amazon you know I I didn't hear a lot about it this show but when they came out with like local zones and oh my gosh out you know all the things that Amazon is building to push out to the edge and also enabling that technology and software and the partner ecosystem helps expand that and Pull It in it's no longer you know Dave it was Hotel California all of the data eventually is going to end up in the public cloud and lock it in it's like I don't think that's going to be the case we know that there will be so much data out at the edge Amazon absolutely is super important um there some of those examples we're giving it's not necessarily multi-cloud but there's collaboration happening like in the healthcare world you know universities and hospitals can all share what they're doing uh regardless of you know where they live well Stephen Armstrong in the analyst session did say that you know we're going to talk about multi-cloud we're not going to lead with it necessarily but we are going to actually talk about it and that's different to your points too than in the fullness of time all the data will be in the cloud that's a new narrative but go ahead yeah actually Amazon is a leader in the cloud so if they push the cloud even if they don't say AWS or Amazon with it they benefit from it right and and the narrative is that way there's the proof is there right so again Innovation favorite scale there are chips which are being made for high scale their software being tweaked for high scale you as a Bank of America or for the Chrysler as a typical Enterprise you cannot afford to do those things in-house what cloud providers can I'm not saying just AWS Google cloud is there Azure guys are there and few others who are behind them and and you guys are there as well so IBM has IBM by the way congratulations to your red hat I know but IBM won the award um right you know very good partner and yeah but yeah people are dragging their feet people usually do on the change and they are in denial denial they they drag their feet and they came in IBM director feed the cave Den Dell drag their feed the cave in yeah you mean by Dragon vs cloud deniers cloud deniers right so server Huggers I call them but they they actually are sitting in Amazon Cloud Marketplace everybody is buying stuff from there the marketplace is the new model OKAY Amazon created the marketplace for b2c they are leading the marketplace of B2B as well on the technology side and other people are copying it so there are multiple marketplaces now so now actually it's like if you're in in a mobile app development there are two main platforms Android and Apple you first write the application for Apple right then for Android hex same here as a technology provider as and I I and and I actually you put your stuff to AWS first then you go anywhere else yeah they are later yeah the Enterprise app store is what we've wanted for a long time the question is is Amazon alone the Enterprise app store or are they partner of a of a larger portfolio because there's a lot of SAS companies out there uh that that play into yeah what we need well and this is what you're talking about the future but I just want to make a point about the past you talking about dragging their feet because the Cube's been following this and Stu you remember this in 2013 IBM actually you know got in a big fight with with Amazon over the CIA deal you know and it all became public judge wheeler eviscerated you know IBM and it ended up IBM ended up buying you know soft layer and then we know what happened there and it Joe Tucci thought the cloud was Mosey right so it's just amazing to see we have booksellers you know VMware called them books I wasn't not all of them are like talking about how great Partnerships they are it's amazing like you said sub GC and IBM uh with the the GSI you know Partnership of the year but what you guys were just talking about was the future and that's what I wanted to get to is because you know Amazon's been leading the way I I was listening to Werner this morning and that just reminded me of back in the days when we used to listen to IBM educate us give us a master class on system design and decoupled systems and and IO and everything else now Amazon is you know the master educator and it got me thinking how long will that last you know will they go the way of you know the other you know incumbents will they be disrupted or will they you know keep innovating maybe it's going to take 10 or 20 years I don't know yeah I mean Dave you actually you did some research I believe it was a year or so ago yeah but what will stop Amazon and the one thing that worries me a little bit um is the two Pizza teams when you have over 202 Pizza teams the amount of things that each one of those groups needs to take care of was more than any human could take care of people burn out they run out of people how many amazonians only last two or three years and then leave because it is tough I bumped into plenty of friends of mine that have been you know six ten years at Amazon and love it but it is a tough culture and they are driving werner's keynote I thought did look to from a product standpoint you could say tape over some of the seams some of those solutions to bring Beyond just a single product and bring them together and leverage data so there are some signs that they might be able to get past some of those limitations but I still worry structurally culturally there could be some challenges for Amazon to keep the momentum going especially with the global economic impact that we are likely to see in the next year bring us home I think the future side like we could talk about the vendors all day right to serve the community out there I think we should talk about how what's the future of technology consumption from the consumer side so from the supplier side just a quick note I think the only danger AWS has has that that you know Fred's going after them you know too big you know like we will break you up and that can cause some disruption there other than that I think they they have some more steam to go for a few more years at least before we start thinking about like oh this thing is falling apart or anything like that so they have a lot more they have momentum and it's continuing so okay from the I think game is on retail by the way is going to get disrupted before AWS yeah go ahead from the buyer's side I think um the the future of the sort of Technology consumption is based on the paper uh use and they actually are turning all their services to uh they are sort of becoming serverless behind the scenes right all analytics service they had one service left they they did that this year so every service is serverless so that means you pay exactly for the amount you use the compute the iops the the storage so all these three layers of course Network we talked about the egress stuff and that's a problem there because of the network design mainly because Google has a flatter design and they have lower cost so so they are actually squeezing the their their designing this their services in a way that you don't waste any resources as a buyer so for example very simple example when early earlier In This Cloud you will get a VM right in Cloud that's how we started so and you can get 20 use 20 percent of the VM 80 is getting wasted that's not happening now that that has been reduced to the most extent so now your VM grows as you grow the usage and if you go higher than the tier you picked they will charge you otherwise they will not charge you extra so that's why there's still a lot of instances like many different types you have to pick one I think the future is that those instances will go away the the instance will be formed for you on the fly so that is the future serverless all right give us bumper sticker Stu and then Serb G I'll give you my quick one and then we'll wrap yeah so just Dave to play off of sharp G and to wrap it up you actually wrote about it on your preview post for here uh serverless we're talking about how developers think about things um and you know Amazon in many ways you know is the new default server uh you know for the cloud um and containerization fits into the whole serverless Paradigm uh it's the space that I live in uh you know every day here and you know I was happy to see the last few years serverless and containers there's a blurring a line and you know subject we're still going to see VMS for a long time yeah yeah we will see that so give us give us your book Instagram my number six is innovation favorite scale that's my bumper sticker and and Amazon has that but also I I want everybody else to like the viewers to take a look at the the Google Cloud as well as well as IBM with others like maybe you have a better price to Performance there for certain workloads and by the way one vendor cannot do it alone we know that for sure the market is so big there's a lot of room for uh Red Hats of the world and and and Microsoft's the world to innovate so keep an eye on them they we need the competition actually and that's why competition Will Keep Us to a place where Market sets the price one vendor doesn't so the only only danger is if if AWS is a monopoly then I will be worried I think ecosystems are the Hallmark of a great Cloud company and Amazon's got the the biggest and baddest ecosystem and I think the other thing to watch for is Industries building on top of the cloud you mentioned the Goldman Sachs NASDAQ Capital One and Warner media these all these industries are building their own clouds and that's where the real money is going to be made in the latter half of the 2020s all right we're a wrap this is Dave Valente I want to first of all thank thanks to our great sponsors AWS for for having us here this is our 10th year at the cube AMD you know sponsoring as well the the the cube here Accenture sponsor to third set upstairs upstairs on the fifth floor all the ecosystem partners that came on the cube this week and supported our mission for free content our content is always free we try to give more to the community and we we take back so go to thecube.net and you'll see all these videos go to siliconangle com for all the news wikibon.com I publish weekly a breaking analysis series I want to thank our amazing crew here you guys we have probably 30 35 people unbelievable our awesome last session John Walls uh Paul Gillen Lisa Martin Savannah Peterson John Furrier who's on a plane we appreciate Andrew and Leonard in our ear and all of our our crew Palo Alto Boston and across the country thank you so much really appreciate it all right we are a wrap AWS re invent 2022 we'll see you in two weeks we'll see you two weeks at Palo Alto ignite back here in Vegas thanks for watching thecube the leader in Enterprise and emerging Tech coverage [Music]

(bright music) >> Well, hey, everybody. John Walls here with theCUBE continuing coverage at AWS re:Invent '22. It has been three really fantastic days here at the Venetian in Las Vegas. And we still have more to come with us to talk about Persistent Systems, the Senior Vice President of Cloud at Persistent Dominique Bastos. Dominique, good to see you. >> Pleasure to see you. >> Thanks for joining us here on the queue. >> Thank you for having me. >> Oh, you bet. You bet. >> Thank you. All right. Tell us about Persistent Systems. So, first off, core focus, what you're up to and then we'll jump in from there. >> Sure, sure. So Persistent Systems is a digital engineering solutions and services provider. They've been around for 32 years doing software engineering, innovating in several areas within different verticals. There's over 22,500 people at Persistent now as of my last count. We're in 18 countries. >> Mm. >> And in October we hit the $1 billion annualized recurring revenue mark. >> Oh, that's a good number right there. >> It's a good number. It's a great company. It's been such an interesting journey. I was with AWS for almost seven years before recently joining Persistent, and it almost felt like a such a logical transition in terms of bringing what I've seen in my entire career of interacting with customers and businesses to what Persistent can provide as people are looking to make their journey to the cloud whatever stage they might be at so. >> Right. And we should point out is that SVP of Cloud, but your focus is AWS. >> My focus AWS. >> Other options, other opportunities. >> Right. >> But you're AWS all the way. >> Right. It's a multicloud company because, you know, we really don't believe in dictating to a customer what they need. I think the benefit, one of the differentiators for Persistent is the amount of legacy history that they have across these industries and customers. I mean, 32 years is a lot, and in terms of like software engineering. So it's like really doing the hard work, the heavy lifting. And then seeing what can actually be commoditized, repeatable building solutions within these verticals to help customers accelerate their transformations. >> Mm hmm. >> So... >> You know, when we talk about cloud, I mean, this has been something that's been on the forefront feel like a long time. Right? But yet there are still many and maybe you can help me out with that percentage, whatever of companies who are either haven't begun yet, are just beginning, they're really in a nascent stage of this transformation. And yeah, I found it curious this week as we've talked with different people about where are you in your journey and so and so forth. A lot of people are way back just starting pass go, and aren't as mature as I would've thought. I mean, do you find that to be the case? >> Absolutely. And there's many reasons for that. I mean, I think what I've started, I mean I've been seeing it over the years, but we all know IT and business back then was very much kept separate. >> Two separate animals. >> Two separate animals. >> Yeah. >> IT made the decisions, not in a vacuum, but almost in a vacuum, right? Now, obviously companies who know it's necessary and have embraced it, bring together the function of looking at the technological solutions that they're adopting to solve a business problem. Right? But that business problem really is dictated by the customer need. >> Mm hmm. >> So I think I have seen, you know, in terms of like the life cycle of a business adopting technology, post cloud, there's a lot of enterprises that are still, they've made such big investments in their legacy infrastructure. >> Mm hmm. >> And in actually, you know, the developers and the people that are maintaining those systems, and the different connections to put it in layman's terms between their systems and their customers systems, right? So, that entire scenario makes it very difficult for them to move. >> Mm hmm. >> It's like moving a mountain. So, I would say there's like three ways of looking at it. You have those that kind of want to revitalize their technology, right? Their backend systems, they want to optimize costs, they want to, and my background in technology is specifically in data, kind of I came up as a DBA and built data models, and I've always loved data before it was a thing to love data. (John chuckles) So... >> You were so far ahead of the curve. >> I was ahead of the curve. I was a trendsetter. >> What a trendsetter? >> I'm a trendsetter. (Dominique chuckles) So I think from that perspective they're looking at, you know, these enormous of amounts of data that they've been capturing in these legacy systems that they're so heavily invested in, but they're not able to derive the insights to better serve their customers or to even innovate new revenue streams from that data. But, they're taking the first step to say, look, you know, we can actually operate more smoothly at a lower cost by moving to the cloud. >> Mm hmm. >> So there's that. Then there are those that are looking to actually innovate and create new revenue streams, monetize their data, look at opportunities to integrate feedback that they've been getting from their customers to provide new services. So they're using the cloud journey, they've probably already moved into the cloud. They're starting to look at analytics, and potentially using AIML to facilitate creating these solutions and services. And then there's those that, you know, want to pioneer, and break into new inventions and ways of solving the big world problems. >> Mm hmm. >> Right? I mean, I think that's one thing I noticed in this re:Invent that I thought was so special is there's like a really big focus on humanity, on humans, on you know, as we were talking earlier everything and I myself have like holding books and I don't like people being on their phone when we're having a conversation. (John chuckles) >> Right. But I think, you know, we are where we are. The reality is the world has evolved in such a way that community is no longer, it takes a small village, all, you know everybody knows each other. You have face to face interactions. You're not doing that with your customers either. There's digitally native businesses that have for a long time cropped up in the FinTech space in you know, you name the space, there's a startup that was born in the cloud that can reach customers immediately, and can provide a service that an enterprise that's kind of like weighed down with their legacy systems. They can't pivot fast enough. So, I think, you know, the pioneers think beyond that. How do we use quantum computing? You know, how do we use 3D simulation to anticipate solving big world problems? Whether it's, you know, people no longer, I don't know what the statistics are, but it's very sad. That elderly people, you know, the amount of human contact that they have is very little. You know, and if you could provide, I don't know, an experience, an immersive experience where their memories are triggered, you know, to help them with dementia, or Alzheimer's. >> Sure. >> I mean, those types of things, those are the things that I think that's what excites me about the launches that I see at re:Invent. And I think the innovation, you know, you have to take that journey. Unless you're born in the cloud, you do have to kind of take that journey. >> You got to get there. >> You have to get there. >> Right. Sure. >> But it's so worth it. >> So how about, let's just say, if I'm a health sciences company, or I'm a pharmaceutical or whatever, and so I've got this desire to create this new opportunity you know, with a human, I say, but yeah, but if you're also Persistent Systems and you're working with you know, somebody in FinTech, or somebody in EEG or whatever, you can't really understand my challenges or my problems. I mean, how do you wear those different hats so you can identify not only what the focus of that client is, but also their technology and how you're going to get them to marry up so they can achieve their goals? >> Well, the beauty of being, you know, in a company with teams of people that you work with, I cut across industries. Right? So we have vertical leaders that have very deep subject matter expertise in any number of those areas. You know, we're working with genomics for example. So, for example, you know, we engage with a customer that we've been helping over the past 32 years use technology to bring services to their customers. And now we are seeing an opportunity to help them innovate to keep up for their business for obvious reasons, but also to supply their customers with the new innovative solutions within that industry, right? 'Cause you need that vehicle to kind of deploy and deliver what customers need. The way we do it is from end to end, right? So, we have in the partnership with AWS, we're a partner of AWS, and as such we are able to collaborate with AWS and their customers or bring our customers to the cloud for all the way from assessment to planning to execution. And even within Persistent, we have ways to main operationalize the maintenance of these solutions. So it's really very easy managed services type framework that we work under. In terms of like migration planning, we have competencies within AWS. For looking at migrations we have AIML, we have DevOps. So we have the various competencies aligned with AWS to be able to execute at whatever stage the customer is. But also in terms of like the accelerators that we provide or the frameworks to look at total cost, that cuts across, right? And then we don't kind of like, here's what you needed and buy, never speak to us again. (John chuckles) I mean, I think the beauty of this company and what I really loved when I was first speaking to them is the depth of the relationships with their customers and the longevity of them. So they've really seen their customers grow. And you can only do that if you're there for the long run. >> You've got to be present. >> You have to be present. >> Sure. So how do you handle if people are making this transformation and they're moving into the cloud, but the people they have on staff might not be familiar with it, right? They have great expertise in what they've been doing on these legacy systems, but now you're moving, you're migrating to a new world, new culture, new environment, and you got to get 'em up to speed. And that's not easy. >> No. >> Right? So what do you do, or what does Persistent suggest or what are you doing and with regard to closing that gap into making that bridge so that they can maintain a little bit on their own. >> Yeah. >> They can execute and implement on their own. >> Yep. >> A little bit. They don't need somebody there to stand over their shoulder the whole time. >> I won't geek out on having joined AWS in professional services way back when to migrate a major company to the cloud, and having lived through painstakingly all those problems and blockers and adoption roadblocks that you speak of. >> Mm hmm. >> You know, I think the way Persistent handles it is what I would've done myself, right? If I were to start a company and say how do we help customers simplify their cloud journey, and remove the complexity? I think that's what Persistent Systems does. We, there's training programs that we are aligned to with AWS. So there's up-skilling of development teams, application developers. We collaborate from the top down with executives to look at the resources that they have available. Obviously mission critical systems that cannot sacrifice having engineers pulled away for a new project. You know, you take that into account. I think, you know, when I spoke earlier about assessments, you're not just assessing what needs to be lifted and shifted or refactored or rearchitected, you're looking at, you know, all these applications that are going to move to the cloud. Who owns them? >> Mm hmm. >> You know, do you have a CI/CD pipeline, or a data pipeline built? Well, we're going to need that, right? So, the continuous integration, continuous development of applications, that type of DevOps, obviously security also DevSecOps, we look at it from end to end as well. We have a very strong security practice. So, all those advisory pieces we have, but we also have the capability to execute on it. Where we're not just coming in and saying well this is what you should do. We're kind of in there saying, this is what you should do, here's how we can get you started. And then, you know, it's a collaborative effort with our customers to see how much they still want us to stay versus how much they want to take over. >> Right. It's nice to have a friend. >> Yeah. (John laughs) Who doesn't need a friend. (Dominique laughs) And Persistent Systems is your friend. Dominique, thanks for the time. >> Oh, my pleasure. >> I appreciate it. >> Thanks again for having me. >> Thanks for being here on theCUBE. You bet. >> Absolutely. >> You are watching theCUBE as you well know the leader in high tech coverage. (soft music)

(gentle music) >> Welcome back to our coverage here on theCUBE of AWS re:Invent 22. We are on day three, starting to wind down, but still a lot of exciting topics to cover here on the AWS Global Showcase, part of the startup program there at AWS. Joining us now, two representatives from LTI Mindtree. You say LTI Mindtree? I thought they were two different companies. Well, they're actually one and the same. Been together just a mere two weeks now. We'll hear more about that from Sid Bohra, who is the Chief Business Officer at LTI Mindtree and Ashish Varerkar, who is the Vice President of Cloud Success at LTI Mindtree. Gentlemen, thanks for being with us here on theCUBE. >> Pleasures all ours. >> Thank you. >> And congratulations. So two weeks in the making in its infancy, still in the honeymoon period, but how's the two weeks been? Everything all right? >> Well, two weeks have been very exciting. >> I'll bet. >> Well, I would say the period prior to that was just as exciting as you can imagine. >> John: Oh, sure. And we are super excited about what the future holds for this company because we truly believe that we have a remarkable opportunity to create value for our clients as one company. >> Well let's talk about LTI Mind tree then a little bit. Ashish, I'll let you carry the ball on this. Tell us about your services, about your core focus, and about those opportunities that Siddharth was just telling us about. >> So I think with the two companies coming together, we have a larger opportunity to like go to market with our end to end business transformation services and leveraging cloud platforms, right? So, and that's what we do. My responsibility particularly is to see to it that what customers are deploying on cloud is aligned to their business outcomes and then take it forward from there. >> Yeah, Vice President of Cloud Success, that gives you a lot of runway, right? Does it not? I mean, how do you define success in the cloud? Because there are a lot of different areas of complexity with which companies are dealing. >> So I think you would agree that in today's scenario, customers are not looking for a platform, right? But they're looking for a platform which can deliver business value. They're looking at business value and resiliency and then at the end, the cost, right? So if you're able to deliver these three things to the customer through the cloud implementation, I think that's success for us. >> Right. We've talked about transformation a lot this week and modernization, right, which is those are two pretty key buzzwords right now we're hearing a lot of. So when you see said, you know, companies come to you and they say, okay, it's time for us to make this commitment. Do they make it generally wholeheartedly? Is there still some trepidation of the unknown? Because there's a lot of, as we've said, complexity to this, it's multidimensional. We can go public, we can go hybrid, we can go multicloud. I mean, we got a lot of flavors. >> Yeah >> Absolutely. >> No, we see a spectrum. There are customers who are very early in the journey of getting onto cloud and are a little uncertain about what value they can get out of it. And on the other end of the spectrum, there are companies who are well into the journey who have understood what are the benefits of truly leveraging cloud who also understand what are the challenges they will face in getting onto the journey. So we get to meet a spectrum of customers, I would say. If you ask me where do bulk of them lie, I would say early in their journey. I would say there are only a handful who have that maturity where they can predict what's exactly going to happen on the cloud journey, what value they will accumulate through the process. So there's a lot of hand holding to be done, a lot of, you know, solving together to be done with our clients. >> You know, it is such a dynamic environment too, right? You have new opportunities that seem to be developed and released on a daily basis, almost, right? There's a large amount of flexibility, I would think, that has to be in place because where you think you're going to go today might not be where you wind up in six months. >> That's true. >> Is that fair? >> Absolutely fair. And I think from that perspective, if you look at the number of services that AWS provides, right? And what customers are looking for is how can they compose their business processes using this multiple services in a very seamless manner. And most of the announcements that we have seen during the re:Invent as well, they're talking about seamless connectivity between their services. They're talking about security, they're talking about creating a data fabric, the data zone that they announced. I think all these things put together, if you're able to kind of connect the dots and drive the business processes, I think that's what we want to do for our customers. >> And the value to AWS, it just can't be underscored enough I would assume, because there's comfort there, there's confidence there. When you bring that to the table as well along with your services, what kind of magnitude are we talking about here? What kind of force do you think? How would you characterize that? >> Well I think, you know, firstly, I would say that most of our engagements are not just services. Ashish and team and the company have invested heavily in building IP that we pair with our services so that we bring non-linearity and more, I would say, certainty to the outcomes that our customers get. And I can share some examples in the course of the conversation, but to answer your question in terms of magnitude, what we are collaborating with AWS on for our clients ranges from helping customers build more resiliency. And I'm talking about life sciences companies build more resiliency in the manufacturing R and D processes. That's so critical. It was even more critical during the pandemic times because we were working with some of the pharma companies who were contributing to the efforts in the pandemic. That's one end of the spectrum. On the other side, we are helping streaming companies and media companies digitize their supply chain, and their supply chains, the media supply chain, so that it is more effective, it's more efficient, it's more real time, again, using the power of the cloud. We are helping pharmaceutical companies drive far greater speed in the R and D processes. We are helping banking companies drive far more compliance in their anti-money laundering efforts and all of those things. So if you look at the magnitude, we judge the magnitude by the business impact that it's creating and we are very excited about what AWS, LTI Mindtree, and the customer are able to create in terms of those business impacts. >> And these are such major decisions. >> That's right. >> For a company, right, to make, and there are a number of factors that come into play here. What are you hearing from the C-Suite with regard to what weighs the most in their mind and is there, is it a matter of, you know, fear missing out? Or is it about trying to stay ahead of your competition, catching up the competition? I mean, generally speaking, you know, where are the, where's the C-Suite weighing in on this? >> I think in the current times, I think there is a certain level of adoption of cloud that's already happened in most enterprises. So most CIOs in the C-suite- >> They already get it. They already get it. >> They kind of get it, but I would say that they're very cagey about a bunch of things. They're very cagey about, am I going to end up spending too much for too little? Am I going to be able to deliver this transformation at the speed that I'm hoping to achieve? What about security? Compliance? What about the cost of running in the cloud? So those are some really important factors that sometimes end up slowing the cloud transformation journeys down because customers end up solving for them or not knowing for them. So while there is a decent amount of awareness about what cloud can do, there are some, a whole bunch of important factors that they continue to solve for as they go down that journey. >> And so what kind of tools do you provide them then? >> Primarily, what we do is, to Siddharth's point, right? So on one end, we want to see to it that we are doing the business transformation and all our cloud journeys start with a business North Star. So we align, we have doubled down on, say, five to six business domains. And for each of these business domains industries, we have created business North Star. For these business North Star, we define the use cases. And these use cases then get lit up through our platform. So what we have done is we have codified everything onto our platform. We call it Infinity. So primarily business processes from level one, level two, level three, level, and then the KPIs which are associated with these business processes, the technical KPIs and the business KPIs, and then tying it back to what you have deployed on cloud. So we have end to end cloud transformation journeys enabled for customers through the business North Star. >> And Infinity is your product. >> Can I add something? >> Please do. Yeah, please. >> Yeah so, you know, Ashish covered the part about demystifying if I were to do this particular cloud initiative, it's not just modernizing the application. This is about demystifying what business benefit will accrue to you. Very rare to find unless you do a very deep dive assessment. But what the platform we built also accelerates, you talked about modernization early in the conversation, accelerates the modernization process by automating a whole bunch of activities that are often manual. It bakes insecurity and compliance into everything it does. It automates a whole bunch of cloud operations including things like finops. So this is a life cycle platform that essentially codifies best practices so that you are not getting success by coincidence, you're getting success by design. So that's really what, that's really how we've approached the topic of realizing the true power of cloud by making sure that it's repeatedly delivered. >> Right. You know, I want to hit on security too because you brought that up just a few moments ago. Obviously, you know, we all, and I'd say we, we can do a better job, right? I mean, there's still problems, there's still challenges, there are a lot of bad actors out there that are staying ahead of the game. So as people come to you, clients come to you, and they raise these security concerns, what's your advice to them in terms of, you know, what kind of environment they're going into and what precautions or protections they can put in place to try to give themselves a little bit of peace of mind about how they're going to operate? >> You want to take it? >> So I think primarily, if you are going to cloud, you are going with an assumption that you are moving out of your firewalls, right? You're putting something out of your network area. So and from that perspective, the parameter security from the cloud perspective is very, very important. And then each and every service or the interactions between the services and what you integrate out of your organization, everything needs to be secured through the right guard rates. And we integrate all those things into our platform so that whatever new apps that get deployed or build or any cost product that gets deployed on cloud, everything is secure from a 360 degree perspective. So primarily, maintaining a good security posture, which on a hybrid cloud, I would not say only cloud, but extending your on-prem security posture to cloud is very, very important to when you go to implementing anything on could. >> If you had a crystal ball and we were sitting down here a year from now, you know, what do you think we'd be talking about with regard to, you know, developing these end-to-end opportunities that you are, what's the, I wouldn't say missing piece, but a piece that you would like to have refined to the point where you come back next year and say, John, guess what we did? Look what we were able to accomplish. Anything that you're looking at that you want to tackle here in 2023? Or is there some fine tuning somewhere that you think could even tighten your game even more than it is already? >> We have a long, long way to go, I would say. I think my core takeaway in terms of where the world of technology is headed because cloud is, you know, is essentially a component of what customers want to achieve. It's a medium through which they want to achieve. I think we live in a highly change oriented economy. Every industry is what I call getting re-platformed, right? New processes, new experiences, new products, new efficiency. So a year from now, and I can tell you even for few years from now, we would be constantly looking at our success in terms of how did cloud move the needle on releasing products faster? How did cloud move the needle on driving better experience and better consumer loyalty, for example. How did cloud move the needle on a more efficient supply chain? So increasingly, the technology metrics like, you know, keeping the lights on, or solving tickets, or releasing code on time, would move towards business metrics because that's really the ultimate goal of technology or cloud. So I would say that my crystal ball says we will increasingly be talking business language and business outcomes. Jeff Bezos is an incredible example, right? One of his annual letters, he connected everything back into how much time did consumers save by using Amazon. And I think that's really where in the world, that's the world we are headed towards. >> Ashish, any thoughts on that? >> I think Siddharth put it quite well. I would say if you are able to make a real business impact for our customers in next one year, helping them in driving some of their newer services on cloud through cloud, that would be a success factor for us. >> Well gentlemen, congratulations on the merger. I said two weeks. Still very much in the honeymoon phase and I'm sure it's going to go very well and I look forward to seeing you back here in a year. We'll sit down, same spot, let's remember, fifth floor, and we'll give it a shot and see how accurate you were on that. >> Absolutely. >> Wonderful. It's been a pleasure. >> Thank you gentlemen. >> Thank you for joining us. >> Thank you. >> Very good. Ashish, good to see you, sir. >> Thank you. >> A pleasure. We'll continue here. We're at the Venetian at AWS re:Invent 22, continue at the AWS Global Showcase startup. I'm John Walls. You're watching theCUBE, the leader in high tech coverage. (gentle music)

(techno music) >> Welcome back to the Cube. I'm John Walls. We continue our coverage here at AWS reInvent 22. We're in the Venetian in Las Vegas, wrapping up our day one coverage here in the executive summit sponsored by Accenture and with me to talk about Accenture, couple of guys who are no strangers at all to the Cube. In fact, I think we got to give you like alumni passes or something. (Chris and Merim laugh) We got to come up with something like that. Um, Merim Becirovic is with us. Uh, Merim's a global IT at Accenture. And Chris Wegmann, who's already been on once today, as a matter of fact. >> Yeah (indistinct) >> So we're going to start charging you rent, Chris. (Chris and Merim laugh) Uh, global technology and practice lead with the AWS business group at Accenture. Good, glad to have you both back and, um, you're welcome to the Cube any time, by the way. >> So don't be scared. >> Thanks, great to be back. Let's talk about >> Sure. >> What, what you folks have been up to. So, um, you are, as we were talking earlier, you are where a lot of your clients would like to be. You, you've begun this transformation. You have fully migrated to the cloud, you've learned, right? >> Yes. You've hit all the bumps along the way. So talk about your journey. >> Yeah. >> And then how you think that experience could be translated to what your clients are going through. >> Yeah, so I'll, I'll hit it from the lessons learned and working together with our business group partners. We, so Accenture's journey to the cloud is complete. We have finished that journey, and as part of that journey, we have migrated all of the services it takes to run Accenture to the public cloud. So now that's done. That was complete. But now we are this, now it is this cloud continuum living in the cloud. And the, now, the thing we talk about, and I'd love to have Chris, you know, shine a little bit more, is we have built our digital core in a cloud, now. We're no longer dependent on data centers. And that has given us tremendous flexibility around how to enable the business as it has grown significantly since we started this journey a few years back. >> Yeah, you know, Merim, like you talk about, right? We talk about our client, we've talked to our clients about building this digital core, right? And, and we've been through that as Accenture, as a global IT organization, you know. Supporting well over 720,000 people. >> Yeah. >> Right? That growth over the last year has been tremendous. Right? So, without the strong digital core built on cloud, right? We couldn't do that, right? We couldn't add that number of people, right? We couldn't make the, the, the changes were needed during, uh, Covid to bring people home, working from home. You know, whether it being uh, the way we changed our business model or things like that, um, you know that was all enabled by cloud. It couldn't be done without that. And, you know, also the variable in our business, right? Is very tied now to our cloud consumption, right? So, you know, it goes up, it goes down, right? We've, you know, Merim and his team have completely built their, their their core with those, with those concepts uh, in mind. >> Yeah, I mean, you're talking about, you know, 700, 800,000 employees and how many countries did you say? >> 130 different countries, at least. >> 130 different countries. So, I mean, no small task, obviously, uh, to get everything done. When did you start? >> So our cloud journey, effectively, we started in 2015. And we were done, kind of right before Covid around 2019. We took a pause for a couple of different things but we could have probably done that faster. And if we were, if I was to do it again now, today we could probably do it in two to three years, flat. With everything that we've learned so far. >> So what's the application, then, to your clients' experiences that, I mean, been there, done that, right? >> You can, exactly right. I mean, you know, we always say that we want to be our best credential, right? And Merim and his team are our best credential in this space. Um, so, you know, a lot of our customers, you know, struggle making that commitment. A lot of 'em are past that struggle, now. They're committed, they're going. Uh, but I talk to a lot of my customers about, you know, do I, do I migrate? Do I modernize? You know, how do I do it? And, and it was interesting with Accenture, right? It, it started out very much as a migration program. >> Yeah. >> Right, so, we made the decision, Merim and his team made the decision to do a migration and now a modernization, right? And, and that's proven very effective. Uh, it, it's, it's, it's proven, you know, uh, we got that core in place, right? We were able to build off of that versus, you know, spending- it would've taken a lot more time just to start with a modernization approach. >> Yeah. Where, where do you draw the line between the two, between migration and modernization, then? Because just by migrating alone, you are modernizing, you know, some of your operations, so you're getting up to speed. But, but how do you draw that line and then how do you get people to jump over it? >> So I, I'll hit it from how our lessons learned. So, when we first started and we did the migrations it was literally lift and shift. And it was a lot of argument about lift and shift isn't worth it. But we found out it was, because it wasn't just about moving the work loads and keeping it like a data center. It was moving the work loads and then optimizing because everything in the cloud was significantly faster. So then I didn't have to consume all the services the same way I did in the data center. I can actually consume them smaller. But also as time went by, what we learned is, hey, now these services are working here. Which ones are actually costing us more money to run? And not that they were costing more than the data center, but it's relative to the cloud which ones cost more in the cloud? Then we looked at that and said, okay how do we want to modernize those? And then we modernized as container capabilities started the evolving, got much more mature. We shifted a lot of workloads to containers. But otherwise, the other principle we push very hard is big consumption of Lambda and uh, serverless capabilities on Amazon. So we have refactored multiple applications to give us that capability to say we no longer need the IAS capabilities, those servers, those VM's, and we run on, on serverless capability. And what's great about that is, now I don't have a server to patch, to scan, to remediate, to upgrade. I've moved away from that capability. And the teams can focus more on building the business capabilities the business wants. Um, like we did to our pricing team. I don't know if you knew this one, Chris, but all the pricing capability has been redone to be cloud native on, on AWS. >> And how, how do you deal with the folks that, that still kind of have a foot in the on-prem world that, um, that they're just not ready to give it up? You know, they, they like the control, they like the self-management. >> Yeah. >> They, they want to be in charge. >> Well, yeah. I mean, a lot of, a lot of our customers, it's, there's a reason why they need on-prem still. And there is on-prem, let's be clear. I mean, it, it is a hybrid cloud world for most of our, our customers, right? Whether they got manufacturing, whether they've got, you know, datas that are, you know, SCADA systems or, or operational IT systems that have to be close to their, their execution or to their, to their factories and things like that. So that's going to happen. I think everyone, and I shouldn't say everyone, but you know, most of our customers know they need to get there, right? And are somewhere on their journey, right? Very few have not started at all. Uh, but it's about acceleration, right? And I, I do think, um, we're going to see more and more acceleration. We saw it with Covid, right? >> Mm-hm. >> And then, you know, obviously I think we're going to see it again, right? With you know, kind of what's going on with the economy and stuff like that. It, it's, you know, it's a great way to push that change through. >> Right. >> And I, I'm really excited, to be honest what I'm really excited about, if I look at what Merim and his team's doing, is they're just leveraging that digital core and truly taking the investments that the hyper scaler's are making, the AWS's are making, and leveraging 'em. So we're not making that investment, right? We're a capital white company, right? So we don't like making good capital investments, right? And we're taking advantage of the capital investments. And we couldn't do that of the, of the hyper scales. We couldn't do that without being there. Right? >> Right. >> We just couldn't do it. >> And maybe, John, if I can build on that. >> Sure. >> Like, one of, one of the things for me when I think about the cloud is, I'm not alone. You know, because when you're in a data center when you're running a data center, you're kind of on an island. And on that island, if you've got security issues, if you got stuff you're dealing with with attackers, you know, you're, you're kind of on an island and you're alone. Whereas in this world, I am where all the investment is, where all the security capabilities are being built, and I have partners that are there with us that help us when these situations come up. So for me, I'm very uh, grateful that we pushed very hard in the beginning to get here. But I wouldn't have it any other way. For us. >> So like, do you- do you want to live outside the fort? >> Yeah. >> No >> No. (laughs) >> You're exactly right. >> Yeah. >> I don't want to live outside the fort. >> Right. >> There are a lot of bad guys out there right now. >> Yeah. >> All right, so, the journey is over. >> Right. You can unpack your bags and get comfortable, right? (Merim laughs) >> No. >> Hardly. >> No. >> So, so what is the, what has this done in terms of setting you up for your future plans? And, and >> So I'll talk about a couple different things and maybe you can build on it, Chris, from what you're seeing, like for us, we, we got very good at, I hate the concept of just FinOps but it's the way of being in the cloud. It's different than running a data center and uh, the way we think about building services, consuming services, allocating services, provisioning services. There's just so much more flexibility there that we can completely fine tune the service that we want to provide. That helps us from when we think about 360 degree value, as we talk to our clients, for ourselves to say it also helps just simply on the sustainability agenda, right, because now, as Amazon builds their capabilities to be more sustainable, those SKUs are available to us, we can naturally consume those SKUs much more effectively. Um, and then uh, the next thing to me, what I'm, what I'm especially excited about is all the stuff we're doing around network. So, you know, pre-Covid, 95% of our traffic was just straight to the internet because we had already finished the journey. So now what do you need a wide area network for anymore? >> Right. >> If you're not routing traffic between data centers what do you need it for? So, we have been working with, with AWS especially, like building these cloud land type capabilities and consuming it. So think of consuming, uh, network same way as you do the cloud. So I'm excited about that one. >> Yeah. That, that, I'm super excited about that, right? Because you know, network's at the core of everything you do, right? And there's always a lot of concern, hey, when I go to the cloud, my network costs are going to go up, right? Um, but I think we've proven, right? >> Yes. >> Being able, that those costs can come down, right? And we can have a better experience, uh, deal with the ebbs and flows of our business whether it's people working from home, people working in the office, you know, or at the client sites. We, we've, you know, we've got that cloud-based backbone that we support. You know, I, I mean Merim, I agree a hundred percent. I think you and your team have done a great job of cost management, cloud cost management, optimization, right? You didn't stop, right? >> No. >> You didn't lo- you didn't just live after the migration on VMs. Right? You know, you went serverless, you went, you know, containerization. >> Yep. >> Uh, and that's kept our cloud bill going down. >> Yes. >> Right. Versus going up, right? >> Yes. >> And I hear from a lot of customers concerned about cloud costs and that type of stuff, but you've proven right, >> Yes. >> That you can keep it flat, if not going down because you're using those last minutes. Sustainability is the other thing that I truly am, I, I love, right? Is, you know, we're all trying to become a more sustainable, sustainable organization. We're trying to help our clients become more sustainable organizations. And you know, you know, your ability to take on Gravitant processors, right? Which use less power. >> Yes. >> Right? Overnight, right? >> Yes. >> Or, hey, I'm using a, you know a, uh, serverless lambda, whatever, right? And I'm not running that server. >> Right. >> You know, so, you're able to show that sustainability gains, um, you know, very quickly. Which you could not do, right? You know, in just doing cloud basic migrations. >> Well, I tell you what I think is impressive, is that you put your money where your mouth is, right? >> Yep. (laughs) >> Is that, that it's, and, and if I'm going to be a client, not to, you know, give you guys a pat on the back, you don't need it. You're doing great without me. But I'd say you've been there, you've done that. And, and so I can learn from you. You understand my pain. >> Yes. >> You understand my reservations, my challenges and uh, you could be my, my headlights here. (Merim laughs) >> So, I think great approach. Kudos to you and certainly wish you both success and to your fourth and fifth appearances on the Cube. (Merim and Chris laugh) Um, we have slots tomorrow if you're arou- available. So, maybe we'll fill it up >> There you go. >> and bring it back again. >> Awesome. >> Guys, thanks for being here. >> Sure. >> It was very nice. >> Appreciate the time. >> All right. >> That's great. >> I've been talking, uh, about Accenture. This is the, of course, executive summit being sponsored by Accenture here at AWS reInvent 22. I'm John Walls. You're watching the Cube, the leader in tech coverage.

(gentle music) >> Now welcome back to theCUBE, everyone. I'm John Walls, and once again, we're glad to have you here for AWS re:Invent 22. Our coverage continues here on Thursday, day three, of what has been a jam-packed week of tech and AWS, of course, has been the great host for this. It's now a pleasure to welcome in Anurag Gupta, who is the founder and CEO of Shoreline, joining us here as part of the AWS Global Showcase Startup Program, and Anurag, good to see you, sir. Thanks for joining us. >> Thank you so much. >> Tell us about Shoreline, about what you're up to. >> So we're a DevOps company. We're really focused on repairing issues. If you think about it, there are a ton DevOps companies and we all went to the cloud in order to gain faster innovation and by and large check. Then all of the things involved in getting things into production, artifact generation, testing, configuration management, deployment, also by and large, automated. Now pity the poor SRE who's getting the deluge of stuff on them, every week, every two days, sometimes multiple times a day, and it's complicated, right? Kubernetes, VMs, lots of services, multiple clouds, sometimes, and you know, they need to know a little bit about everything. And you know what, there are a ton of companies that actually help you with what we call Day-2 Ops. It's just that most of them help you with observability, telling you what's gone wrong, or incident management, routing something to someone. But you know, back when I was at AWS, I never got really that excited about one more dashboard to look at or one more like better ticket routing. What used to really excite me was having some issue extinguished forever. And if you think about it, like the first five minutes of an incident are detecting and routing. The next hour, two hours, is some human being going in and fixing it, so that feels like the big opportunity to reduce, so hopefully we can talk a little bit about different ways that one can do that. >> What about Day-2 Ops? Just tell me about how you define that. >> So I basically define it as once the software goes into a production, just making sure things stay up and are healthy and you're resilient and you don't get errors and all of those sorts of things because everything breaks sooner or later, you know, to a greater or lesser degree. >> Especially that SRE you're talking about, right? >> Yeah. >> So let's go back to that scenario. Yeah, you pity the poor soul because they do have to be a little expert in everything. >> Exactly. >> And that's really challenging and we all know that, that's really hard. So how do you go about trying to lighten that burden, then? >> So when you look at the numbers, about somewhere between 40% to even 95% of the alarms that fire, the alerts that fire, are false positives and that's crazy. Why is someone waking up just to deal with? >> It's a lot of wasted time, isn't it? >> A lot of wasted time. And you know, you're also training someone into what I call ClickOps, just to go in and click the button and resolve it and you don't actually know if it was the false positive or it's the rare real positive, and so that's a challenge, right? And so the first thing to do is to figure out where the false positives are. Like, let's say Datadog tells you that CPU is high and alarms. Is that a good thing or a bad thing? It's hard for them to tell, right? But you have to then introspect it into something precise like, oh, CPU is high, but response times are standard and the request rate is high. Okay, that's a good thing. I'm going to ignore this. Or CPU is high, but it kind of resolves itself, so I'm going to not wake anybody up. Or CPU is high and oh, it's the darn JVM starting to garbage collect again, so let me go and take a heap dump and give that to my dev team and then bounce the JVM and you know, without waking anybody up, or CPU is high, I have no idea what's going on. Now it's time to wake somebody up. You know, what you want to use humans for is the ability to think about novel stuff, not to do repetitive stuff, so that's the first step. The second step is, about 40% of what remains is repetitive and straightforward. So like a disk is full, I'd better clean up the garbage on the disk or maybe grow the disk. People shouldn't wake up to deal to grow a disk. And so for that, what you want to do is just have those sorts of things get automated away. One of the nice things about Shoreline is, is that we take the experience in what we build for one company, and if they're willing, provide it to everybody else. Our belief is, a central tenant is, if someone somewhere fixes something, everyone everywhere should gain the benefit because we all sit on the same three clouds, we all sit on the same set of database infrastructure, et cetera. We should all get the same benefits. Why do we have to scar our own backs rather than benefiting from somebody else's scar tissue, so that's the second thing. The third thing is, okay, let's say it's not straightforward, not something I've seen before, then in that case, what often happens is on average like eight people get involved. You know, it initially goes to L1 support or L1 ops and, but they don't necessarily know because, as you say, the environment's complex. And so, you know, they go into Slack and they say, "At here, can somebody help me with this?" And those things take a much longer time, so wouldn't it be better that if your best SRE is able to say, "Hey, check these 20 things and then run these actions." We could convert that into like a Jupyter Notebook where you could say the incident got fired I pre-populated all the diagnostics, and then I tell people very precisely, "If you see this, run this, et cetera." Like a wiki, but actually something you could run right in this product. And then, you know, last piece of the puzzle, the smaller piece, is sometimes new things happen and when something new happens, what you want is sort of the central tech of Shoreline, which is parallel distributed, real-time debugging. And so the ability to do, you know, execute a command across your fleet rather than individual boxes so that you can say something like, "I'm hearing that my credit card app is slow. For everything tagged as being part of my credit card app, please run for everything that's running over 90% CPU, please run a top command." And so, you know, then you can run in the same time on one host as you can on 30,000 and that helps a lot. So that's the core of what we do. People use us for all sorts of things, also preventative maintenance, you know, just the proactive regular things. You know, like your car, you do an oil change, well, you know, you need to rotate your certs, certificates. You need to make sure that, you know, there isn't drift in your configurations, there isn't drift in your software. There's also security elements to it, right? You want to make sure that you aren't getting weird inbound/outbound traffic across to ports you don't expect to be open. You don't want to have these processes running, you know, maybe something's bad. And so that's all the kind of weird anomaly detection that's easy to do if you run things in a distributed parallel way across everything. That's super hard to do if you have to go and Whac-A-Mole across one box after the next. >> Well, which leads to a question just in terms of setting priorities then, which is what you're talking about helping companies establish priorities, this hierarchy of level one warning, level two, level three, level four. Sounds like that should be a basic, right? But you're saying that's not, that's not really happening in the enterprise. >> Well, you know, I would say that if you hadn't automated deployments, you should do that first. If you haven't automated your testing pipeline, shame on you, you should do that like a year ago. But now it's time to help people in production because you've done that other work and people are suffering. You know, the crazy thing about the cloud is, is that companies spend about three times more on the human beings to operate their cloud infrastructure as on the cloud infrastructure itself. I've yet to hear anybody say that their cloud bill is too low, you know, so, you know, there's a clearer savings also available. And you know, back when I was at AWS, obviously I had to keep the lights on too, but you know, I had to do that, but it's kind of a tax on my engineers and I'd really spend, prefer to spend the head count on innovation, on doing things that delight my customers. You never delight your customers by keeping the lights on, you just avoid irritating them by turning 'em off, right? >> So why are companies so fixed in on spending so much time on manually repairing things and not looking for these kinds of little, much more elegant solution and cost-efficient, time-saving, so on so forth. >> Yeah, I think there just hasn't been very much in this space as yet because it's a hard, hard problem to solve. You know, automation's a little bit scary and that's the reality of it and the way you make it less scary is by proving it out, by doing the simple things first, like reducing the alert fatigue, you know, that's easy. You know, providing notebooks to people so that they can click things and do things in a straightforward way. That's pretty easy. The full automation, that's kind of the North Star, that's what we aspire to do. But you know, people get there over time and one of our customers had 700 instances of this particular incident solved for them last week. You imagine how many human beings would've been doing it otherwise, you know? >> Right. >> That's just one thing, you know? >> How many did it take the build a pyramid? How many decades did that take, right? You had an announcement this week. I don't think we've talked about that. >> No, yeah, so we just announced Incident Insights, which is a free product that lets people plug into initially PagerDuty and pretty soon the Opsgenie ServiceNow, et cetera. And what you can do is, is you give us an API key read-only and we will suck your PagerDuty data out. We apply some lightweight ML unsupervised learning, and in a couple of minutes, we categorize all of your incidents so that you can understand which are the ones that happen most often and are getting resolved really quickly. That's ClickOps, right? Those alarms shouldn't fire. Which are the ones that involve a lot of people? Those are good candidates to build a notebook. Which are the ones that happen again and again and again? Those are good candidates for automation. And so, I think one of the challenges people have is, is that they don't actually know what their teams are doing and so this is intended to provide them that visibility. One of our very first customers was doing the beta test for us on it. He used to tell us he had about 100 tickets, incidents a week. You know, he brought this tool in and he had 2,100 last week and was all, you know, like these false alarms, so while he's giving us- >> That was eye opening for him to see that, sure. >> And why he's, you know, looking at it, you know, he's just like filing Jiras to say, "Oh, change this threshold, cancel this alarm forever." You know, all of that kind of stuff. Before you get to do the fancy work, you got to clean your room before you get to do anything else, right? >> Right, right, dinner before dessert, basically. >> There you go. >> Hey, thanks for the insights on this and again the name of the new product, by the way, is... >> Incident Insights. >> Incident Insights. >> Totally free. >> Free. >> Yeah, it takes a couple of minutes to set up. Go to the website, Shoreline.io/insight and you can be up and running in a couple of minutes. >> Outstanding, again, the company is Shoreline. This is Anurag Gupta, and thank you for being with us. We appreciate it. >> Appreciate it, thank you. >> Glad to have to here on theCUBE. Back with more from AWA re:Invent 22. You're watching theCUBE, the leader in high-tech coverage. (gentle music)

(upbeat music) >> Hey, welcome back everyone, live coverage here. Re:invent 2022. I'm John Furrier, host of theCUBE. Two sets here. We got amazing content flowing. A third set upstairs in the executive briefing area. It's kind of a final review, day three. We got a special guest for do a re:Invent review. Muddu Sudhakar CEO founder of Aisera. Former multi-exit entrepreneur. Kind of a CUBE analyst who's always watching the floor, comes in, reports on our behalf. Thank you, you're seasoned veteran. Good to see you. Thanks for coming. >> Thank you John >> We've only got five minutes. Let's get into it. What's your report? What are you seeing here at re:Invent? What's the most important story? What's happening? What should people pay attention to? >> No, a lot of things. First all, thank you for having me John. But, most important thing what Amazon has announced is AIML. How they're doubling down on AIML. Amazon Connect for Wise. Watch out all the contact center vendors. Third, is in the area of workflow, low-code, no-code, workflow automation. I see these three are three big pillars. And, the fourth is ETL and ELTs. They're offering ETL as included as a part of S3 Redshift. I see those four areas are the big buckets. >> Well, it's not no ETL to S3. It's ETL into S3 or migration. >> That's right. >> Then the other one was Zero ETL Promise. >> Muddu: That's right. >> Which there's a skeptical group out there that think that's not possible. I do. I think ultimately that'll happen, but what's your take? >> I think it's going to happen. So, it's going to happen both within that data store as well as outside the data store, data coming in. I think that area, Amazon is going to slowly encroach into the whole thing will be part offered as a part of Redshift and S3. >> Got it. What else are you seeing? Security. >> Amazon Connect Amazon Connect is a big thing. >> John: Why is that so important? It seems like they already have that. >> They have it, but what they're doing now is to automate AI bots. They want to use AI bot to automate both agent assist, AI assist, and also WiseBot automation. So, all the contact center Wise to text they're doubling down. I think it's a good competition to Microsoft with the Nuance acquisition and what Zoom is doing today. So, I think within Microsoft, Zoom, and Amazon, it's a nice competition there. >> Okay, so we had Adam's keynote, a lot of security and data, that was big. Today, we had Swami, all ML, 13 announcements. Adam did telegraph to me that he was going to to share the love. Jassy would've probably taken most of those announcements, we know that. Adam shared the love. So, Adam, props to you for sharing the love with Swami and some of those announcements. We had 13. So, good for him. >> Yes. >> And then, we had Aruba with the partners. What's your take on the partner network? A revamp? >> No, I think Aruba did a very good job in terms of partners. Look at these, one of the best stores that Amazon does. Even the companies like me, I'm a startup company. They know how to include the partners, drive more revenue with partners, sell through it, more expansion. So, Amazon is still one of the best for startup to mid-market companies to go into enterprise. So, I love their partnership angle. >> One of the things I like that she said that resonated with me 'cause, I've been working with those teams, is it's unified, clear roles, but together. But, scaling the support for partners and making money for partners. >> That's right. >> That is a huge deal. Big road ahead. She's focused on it. She says, no problem. We want to scale up the business model of the channel. >> Muddu: That's right. >> The resources, so that the ecosystem can make money and serve customers or serve customers and make money. >> Muddu: That's right. And, I think one thing that they're always good is Marketplace. Now, they're doing is outside of market with ISV, co-sell, selling through. I think Amazon really understood that adding the value so that we make money as a partners and they make money, incrementally. So, I think Aruba is doing a very good job. I really like it. >> Okay, final question. What's going on with Werner? What do you expect to hear tomorrow from a developer front? Not a lot of developer productivity conversations at this re:Invent. Not a lot of people talking about software supply chain although Snyk was on theCUBE earlier. Developer productivity. Werner's going to speak to that tomorrow we think. Or, I don't know. What do you think? >> I think he's going talk something called generative AI. Rumored the people are talking about the code will be returned by the algorithms now. I think if I'm Werner, I'm going to talk about where the technology is going, where the humans will not be writing code. So, I think AI is going to double down with Amazon more on the generative AI. He's going to try a lot about that. >> Generative AI is hot. We could have generative CUBE, no hosts. >> Muddu: Yes, that would be good. >> No code, no host >> Muddu: Have an answer, John Software. (both laugh) >> We're going to automate everything. Muddu, great to hear from you. Thanks for reporting. Anything else on the ecosystem? Any observations on the ecosystem and their opportunity? >> So, coming from my side, if I'd to provide an answer, today we have like close to thousand leads that are good. Most of them are financial, healthcare. Healthcare is still one of the largest ones I saw in this conference. Financials, and then, I'm started seeing a lot more on the manufacturing. So, I think supply chain, they were not so. I think Amazon is doing fantastic job with financial, healthcare, and supply chain. >> Where is their blind spot if you had to point that one? >> I think media and entertainment. Media and entertainment is not that big on Amazon. So, I think we should see a lot more of those. >> Yeah, I think they need to look at that. Any other observations? Hallway conversations that are notable that you would like to share with folks watching? >> I think what needs to happen is with VMware, and Citrix desktop, and Endpoint Management. That's their blind spot. So far, nobody's really talking about the Endpoints. Your workstation, laptop, desktop. Remember, that was big with VMware. Nope, that's not a thought of conversation in email right now. So, I think that area is left behind by Amazon. Somebody needs to go after that white space. >> John: And, the audience here is over 50,000. Big numbers. >> Huge. One of the best shows, right? I mean after Covid. It's by far the best show I've seen in this year. >> All right, if you'd do a sizzle reel, what would it be? >> Sizzle reel. I think it's going to be a lot more on, as I said, generative to AI is the key word to watch. And, more than that, low-code no-code workflow automation. How do you automate the workflows? Which is where ServiceNow is fairly strong. I think you'll see Amazon and ServiceNow playing in the workflow automation. >> Muddu, thank you so much for coming on theCube sharing. That's a wrap up for day three here in theCUBE. I'm John Furrier, Dave Vellante for Lisa Martin, Savannah Peterson, all working on Paul Gillan and John Walls and the whole team. Thanks for all your support. Wrapping it up to the end of the day. Pulling the plug. We'll see you tomorrow. (upbeat music)

>>Well, hello everybody. John Walls here and continuing our coverage here at AWS Reinvent 22 on the queue. We continue our segments here in the Global Startup program, which of course is sponsored by AWS Startup Showcase, and with us to talk about any scale as the co-founder and CEO of the company, Robert and n, you are Robert. Good to see you. Thanks for joining us. >>Yeah, great. And thank you. >>You bet. Yeah. Glad to have you aboard here. So let's talk about Annie Scale, first off, for those at home and might not be familiar with what you do. Yeah. Because you've only been around for a short period of time, you're telling me >>Company's about >>Three years now. Three >>Years old, >>Yeah. Yeah. So tell us all about it. Yeah, >>Absolutely. So one of the biggest things happening in computing right now is the proliferation of ai. AI is just spreading throughout every industry has the potential to transform every industry. But the thing about doing AI is that it's incredibly computationally intensive. So if you wanna do do ai, you're not, you're probably not just doing it on your laptop, you're doing it across many machines, many gpu, many compute resources, and that's incredibly hard to do. It requires a lot of software engineering expertise, a lot of infrastructure expertise, a lot of cloud computing expertise to build the software infrastructure and distributed systems to really scale AI across all of the, across the cloud. And to do it in a way where you're really getting value out of ai. And so that is the, the problem statement that AI has tremendous potential. It's incredibly hard to do because of the, the scale required. >>And what we are building at any scale is really trying to make that easy. So trying to get to the point where, as a developer, if you know how to program on your laptop, then if you know how to program saying Python on your laptop, then that's enough, right? Then you can do ai, you can get value out of it, you can scale it, you can build the kinds of, you know, incredibly powerful applica AI applications that companies like Google and, and Facebook and others can build. But you don't have to learn about all of the distributed systems and infrastructure. It just, you know, we'll handle that for you. So that's, if we're successful, you know, that's what we're trying to achieve here. >>Yeah. What, what makes AI so hard to work with? I mean, you talk about the complexity. Yeah. A lot of moving parts. I mean, literally moving parts, but, but what is it in, in your mind that, that gets people's eyes spinning a little bit when they, they look at great potential. Yeah. But also they look at the downside of maybe having to work your way through Pike mere of sorts. >>So, so the potential is definitely there, but it's important to remember that a lot of AI initiatives fail. Like a lot of initiative AI initiatives, something like 80 or 90% don't make it out of, you know, the research or prototyping phase and inter production. Hmm. So, some of the things that are hard about AI and the reasons that AI initiatives can fail, one is the scale required, you know, moving. It's one thing to develop something on your laptop, it's another thing to run it across thousands of machines. So that's scale, right? Another is the transition from development and prototyping to production. Those are very different, have very different requirements. Absolutely. A lot of times it's different teams within a company. They have different tech stacks, different software they're using. You know, we hear companies say that when they move from develop, you know, once they prototype and develop a model, it could take six to 12 weeks to get that model in production. >>And that often involves rewriting a lot of code and handing it off to another team. So the transition from development to production is, is a big challenge. So the scale, the development to production handoff. And then lastly, a big challenge is around flexibility. So AI's a fast moving field, you see new developments, new algorithms, new models coming out all the time. And a lot of teams we work with, you know, they've, they've built infrastructure. They're using products out there to do ai, but they've found that it's sort of locking them into rigid workflows or specific tools, and they don't have the flexibility to adopt new algorithms or new strategies or approaches as they're being developed as they come out. And so they, but their developers want the flexibility to use the latest tools, the latest strategies. And so those are some of the main problems we see. It's really like, how do you scale scalability? How do you move easily from development and production and back? And how do you remain flexible? How do you adapt and, and use the best tools that are coming out? And so those are, yeah, just those are and often reasons that people start to use Ray, which is our open source project in any scale, which is our, our product. So tell >>Me about Ray, right? Yeah. Opensource project. I think you said you worked on it >>At Berkeley. That's right. Yeah. So before this company, I did a PhD in machine learning at Berkeley. And one of the challenges that we were running into ourselves, we were trying to do machine learning. We actually weren't infrastructure or distributed systems people, but we found ourselves in order to do machine learning, we found ourselves building all sorts of tools, ad hoc tools and systems to scale the machine learning, to be able to run it in a reasonable amount of time and to be able to leverage the compute that we needed. And it wasn't just us people all across, you know, machine learning researchers, machine learning practitioners were building their own tooling and infrastructure. And that was one of the things that we felt was really holding back progress. And so that's how we slowly and kind of gradually got into saying, Hey, we could build better tools here. >>We could build, we could try to make this easier to do so that all of these people don't have to build their own infrastructure. They can focus on the actual machine learning applications that they're trying to build. And so we started, Ray started this open source project for basically scaling Python applications and scaling machine learning applications. And, well, initially we were running around Berkeley trying to get all of our friends to try it out and, and adopt it and, you know, and give us feedback. And if it didn't work, we would debug it right away. And that slow, you know, that gradually turned into more companies starting to adopt it, bigger teams starting to adopt it, external contributors starting to, to contribute back to the open source project and make it better. And, you know, before you know it, we were hosting meetups, giving to talks, running tutorials, and the project was just taking off. And so that's a big part of what we continue to develop today at any scale, is like really fostering this open source community, growing the open source user base, making sure Ray is just the best way to scale Python applications and, and machine learning applications. >>So, so this was a graduate school project That's right. You say on, on your way to getting your doctorate and now you commercializing now, right? Yeah. I mean, so you're being able to offer it, first off, what a journey that was, right? I mean, who would've thought Absolutely. I guess you probably did think that at some point, but >>No, you know, when we started, when we were working on Ray, we actually didn't anticipate becoming a company, or we at least just weren't looking that far ahead. We were really excited about solving this problem of making distributed computing easy, you know, getting to the point where developers just don't have to learn about infrastructure and distributed systems, but get all the benefits. And of course, it wasn't until, you know, later on as we were graduating from Berkeley and we wanted to continue really taking this project further and, and really solving this problem that it, we realized it made sense to start a company. >>So help me out, like, like what, what, and I might have missed this, so I apologize if I did, but in terms of, of Ray's that building block and essential for your, your ML or AI work down the road, you know, what, what is it doing for me or what, what will it allow me to do in either one of those realms that I, I can't do now? >>Yeah. And so, so like why use Ray versus not using Ray? Yeah, I think the, the answer is that you, you know, if you're doing ai, you need to scale. It's becoming, if you don't find that to be the case today, you probably will tomorrow, you know, or the day after that. And so it's really increasingly, it's a requirement. It's not an option. And so if you're scaling, if you're trying to build these scalable applications you are building, you're either going to use Ray or, or something like Ray or you're going to build the infrastructure yourself and building the infrastructure yourself, that's a long journey. >>So why take that on, right? >>And many of the companies we work with don't want to be in the business of building and managing infrastructure. No. Because, you know, if they, they want their their best engineers to build their product, right? To, to get their product to market faster. >>I want, I want you to do that for me. >>Right? Exactly. And so, you know, we can really accelerate what these teams can do and, you know, and if we can make the infrastructure something they just don't have to think about, that's, that's why you would choose to use Ray. >>Okay. You know, between a and I and ml are, are they different animals in terms of what you're trying to get done or what Ray can do? >>Yeah, and actually I should say like, it's not just, you know, teams that are new teams that are starting out, that are using Ray, many companies that have built, already built their own infrastructure will then switch to using Ray. And to give you a few examples, like Uber runs all their deep learning on Ray, okay. And, you know, open ai, which is really at the frontier of training large models and, and you know, pushing the boundaries of, of ai, they train their largest models using Ray. You know, companies like Shopify rebuilt their entire machine learning platform using Ray, >>But they started somewhere else. >>They had, this is all, you know, like, it's not like the v1, you know, of their, of their machine learning infrastructure. This is like, they did it a different way before, this is like the second version or the third iteration of of, of how they're doing it. And they realize often it's because, you know, I mean in the case of, of Uber, just to give you one example, they built a system called hova for scaling deep learning on a bunch of GPUs. Right Now, as you scale deep learning on GPUs for them, the bottleneck shifted away from, you know, as you scale GPU's training, the bottleneck shifted away from training and to the data ingest and pre-processing. And they wanted to scale data ingest and pre-processing on CPUs. So now Hova, it's a deep learning framework. It doesn't do the data ingest and pre-processing on CPUs, but you can, if you run Hova on top of Ray, you can scale training on GPUs. >>And then Ray has another library called Ray Data you can, that lets you scale the ingest and pre-processing on CPUs. You can pipeline them together. And that allowed them to train larger models on more data before, just to take one example, ETA prediction, if you get in an Uber, it tells you what time you're supposed to arrive. Sure. That uses a deep learning model called d eta. And before they were able to train on about two weeks worth of data. Now, you know, using Ray and for scaling the data, ingestive pre-processing and training, they can train on much more data. You know, you can get more accurate ETA predictions. So that's just one example of the kind of benefit they were able to get. Right. Also, because it's running on top of, of Ray and Ray has this ecosystem of libraries, you know, they can also use Ray's hyper parameter tuning library to do hyper parameter tuning for their deep learning models. >>They can also use it for inference and you know, because these are all built on top of Ray, they inherit the like, elasticity and fault tolerance of running on top of Ray. So really it simplifies things on the infrastructure side cuz there's just, if you have Ray as common infrastructure for your machine learning workloads, there's just one system to, to kind of manage and operate. And if you are, it simplifies things for the end users like the developers because from their perspective, they're just writing a Python application. They don't have to learn how to use three different distributed systems and stitch them together and all of this. >>So aws, before I let you go, how do they come into play here for you? I mean, are you part of the showcase, a startup showcase? So obviously a major partner and major figure in the offering that you're presenting >>People? Yeah, well you can run. So any scale is a managed ray service. Like any scale is just the best way to run Ray and deploy Ray. And we run on top of aws. So many of our customers are, you know, using Ray through any scale on aws. And so we work very closely together and, and you know, we have, we have joint customers and basically, and you know, a lot of the value that any scale is adding on top of Ray is around the production story. So basically, you know, things like high availability, things like failure handling, retry alerting, persistence, reproducibility, these are a lot of the value, the values of, you know, the value that our platform adds on top of the open source project. A lot of stuff as well around collaboration, you know, imagine you are, you, something goes wrong with your application, your production job, you want to debug it, you can just share the URL with your, your coworker. They can click a button, reproduce the exact same thing, look at the same logs, you know, and, and, and figure out what's going on. And also a lot around, one thing that's, that's important for a lot of our customers is efficiency around cost. And so we >>Support every customer. >>Exactly. A lot of people are spending a lot of money on, on aws. Yeah. Right? And so any scale supports running out of the box on cheaper like spot instances, these preempt instances, which, you know, just reduce costs by quite a bit. And so things like that. >>Well, the company is any scale and you're on the show floor, right? So if you're having a chance to watch this during reinvent, go down and check 'em out. Robert Ashihara joining us here, the co-founder and ceo and Robert, thanks for being with us. Yeah. Here on the cube. Really enjoyed it. Me too. Thanks so much. Boy, three years graduate program and boom, here you are, you know, with off to the enterprise you go. Very nicely done. All right, we're gonna continue our coverage here on the Cube with more here from Las Vegas. We're the Venetian, we're AWS Reinvent 22 and you're watching the Cube, the leader in high tech coverage.

>>Good afternoon everybody. I'm John Walls and welcome back to our coverage here on the cube of AWS Reinvent 22. We are bringing you another segment with the Global Startup Program, which is part of the AWS Start Showcase, and it's a pleasure to welcome two new guests here to the showcase. First, immediately to my right Han w lre. Good to see you Han. Good to see you. The leader of the Enterprise Solutions Architecture at aws. And on the far right, Rolin Lee, who is the co-founder and CEO of Heim Doll Data. Roland, good to see you. Great >>To be here. >>All right, good. Thanks for joining us. Well first off, for those at home, I may not be familiar with Heim Doll. What do you do? Why are you here? But I'll let you take it from there. >>Well, we're one of the sponsors here at AWS and great to be here. We offer a data access layer in the form of a proxy, and what it does is it provides complete visibility and the capability to enhance the interaction between the application and one's current database. And as a result, you'll, the customer will improve database scale, database security and availability. And all these features don't require any application changes. So that's sort of our marketing pitch, if you will, all these types of features to improve the experience of managing a database without any application >>Changes. And, and where's the cloud come into play then, for you then, where, where did it come into play for you? >>So we started out actually helping out customers on premise, and a lot of enterprise customers are moving over to the cloud, and it was just a natural progression to do that. And so aws, which is a key part of ours, partners with us to help solve customer problems, especially on the database side, as the application being application performance tends to have issues between the interaction between the application database and we're solving that issue. >>Right. Sohan, I mean, Roan just touched on it about OnPrem, right? There's still some kickers and screamers out there that, that don't, haven't bought in or, or they're about to, but you're about to get 'em. I, I'm sure. But talk about that, that conversion or that transition, if you would, from going OnPrem into a hybrid environment or to into the, the bigger cloud environment and and how difficult that is sometimes. Yes. Maybe to get people to, to make that kind of a leap. >>Well, I would say that a lot of customers are wanting to focus more on product innovation experimentation, and also in terms of having to manage servers and patching, you know, it's to take away from that initiative that they're trying to do. So with aws, we provide undifferentiated heavy lifting so that they can focus on product innovation. And one of the areas talking about Heim is that from the database side, we do provide Amazon rds, which is database and also Aurora, to give them that lift so they don't have to worry about patching servers and setting up provisioning servers as well. >>Right. So Roland, can you get the idea across to people very simply, let us take care of the, the hard stuff and, and that will free you up to do your product innovations, to do your experimentations to, to really free up your team, basically to do the fun stuff and, and let us sweat over the, the, the details basically. Right? >>Exactly. Our, our motto is not only why build when, when you can buy. So a lot of it has to do with offering the, the value in terms of price and the features such as it's gonna benefit a team. Large companies like amazon.com, Google, they have huge teams that can build data access layers and proxies. And what we're trying to do here is commercialize those cuz those are built in house and it's not readily available for customers to use. And you'd need some type of interface between the application and the database. And we provide that sort of why build when you can buy. >>Well, I was gonna say why h right? I mean what's your special sauce? Because everybody's got something, obviously a market differentiator that you're bringing into place here. So you started to touch on a little bit there for me, but, but dive a little deeper there. I mean, what, what is it that, that you're bringing to the table with AWS that you think puts you above the crowd? >>Well, lemme give you a use case here. In typical events like let's say Black Friday where there's a surge traffic that can overwhelm the database, the Heim doll data access layer database proxy provides an auto scaling distributed architecture such that it can absorb those surges and traffic and help scale the database while keeping the data fresh and up to date. And so basically traffic based on season time of day, we can, we can adjust automatically and all these types of features that we offer, most notably automated query caching, ReadWrite split for asset compliance don't require any code changes, which typically requires the application developer to make those changes. So we're saving months, maybe years of development and maintenance. >>Yeah, a lot of gray hairs too, right? Yeah, you're, you're solving a lot of problems there. What about database trends in just in general Hunt, if you will. I mean, this is your space, right? I mean, what we're hearing about from Heindel, you know, in terms of solutions they're providing, but what are you seeing just from the macro level in terms of what people are doing and thinking about the database and how it relates to the cloud? Right. >>And some of the things that we're seeing is that we're seeing an explosion of data, relevant data that customers need to be able to consume and also process as well. So with the explosion of data, there's also, we see customers trying to modernize their application as well through microservices, which does change the design patterns of like the applications we call the access data patterns as well. So again, going back to that, a differentiated heavy lifting, we do have something called purpose built databases, right? It's the right tool for the right purpose. And so it depends on what their like rpo, rto their access to data pattern. Is it a base, is it an acid? So we want to be able to provide them the options to build and also innovate. So with that, that's why we have the Amazon rds, the also the, we also have Redshift, we also have Aurora and et cetera. The Rediff is more of the BI side, but usually when you ingest the data, you have some level of processing to get more insight. So with that, that's why customers are moving more of towards the managed service so that they can give that lift and then focusing on that product and innovation. Yeah. >>Have we kind of caught up or are we catching up to this just the tsunami of data to begin with, right? Because I mean, that was it, you know, what, seven, eight years ago when, when that data became kind of, or becoming king and, and reams and reams and reams and all, you know, can't handle it, right? And, and are we now able to manage that process and manage that flow and get the right data into the right hands at the right time? We're doing better with that. >>I would say that it, it definitely has grown in size of the amount of data that we're ingesting. And so with the scalability and agility of the cloud, we're able to, I would say, adapt to the rapid changes and ingestions of the data. So, so that's why we have things like Aurora servers to have that or auto scale so they can do like MySQL or Postgres and then they can still, like what you know, I'm trying to do is basically don't have to co do like any code changes. It would be a data migration. They still use the same underlying database on also mechanisms, but here we're providing them at scale on the cloud. >>Yeah. Our proxies, they must have for all databases. I mean, is that, is that essential these days? >>Well, good question John. I would say yes. And this is often built in house, as I mentioned, for large companies, they do build some type of data access layer or proxy and, or some utilize some orm, some object relational map to do it. And what again, what we're trying to do is offer this, put this out into the market commercially speaking, such that it can be readily used for, for all the customers to use rather than building it from scratch all the time. >>You know what I didn't ask you was Roy, how does AWS come into play for you then? And, and as in the startup mode, the focus that they've had in startups in general, but in you in particular, I mean, talk about that partnership or that relationship and the value that you're extracting from that. >>The ad AWS partnership has been absolutely wonderful. The collaboration, they have one of the best managed service databases. The value that it that adds in terms of the durability, the manageability, what the Heim doll data does is it compliments Amazon rds, Amazon Redshift very well in the sense that we're not replacing the database. What we're doing is we are allowing the customer to get the most out of the managed service database, whether it be Redshift or Aurora Serverless, rds, all without code changes. And or the analogy that I would give John is a car, a race car may be very fast, but it takes a driver to get to those fast speeds. We're the driver, the Hyundai proxy provides that intelligence so that you can get the most out of that database engine. >>And, and Hfi would then touch on, first off AWS and the emphasis that you have put on startups and are obviously, you know, kind of putting your money where your mouth is, right? With, with the way you've encouraged and nurtured that environment. And they would be about Heim doll in general about where you see this going or what you would like to have, where you want to take this in the next say 12 months, 18 months. >>I think it's more of a better together story of how we can basically coil with our partners, right? And, and basically focusing on helping our customers drive that innovation and be collaboration. So as Heim, as a independent service vendor isv, most customers can leverage that through a marketplace where basically it integrates very nicely with aws. So that gives 'em that lift and it goes back to the undifferentiated heavy lifting on the Hein proxy side, if you will, because then you have this proxy in the middle where then it helps them with their SQL performance. And I've seen use cases where customers were, have some legacy system that they may not have time to modernize the application. So they use this as a lift to keep, keep going as they try to modernize. But also I've seen customers who use are trying to use it as a, a way to give that performance lift because they may have a third party software that they cannot change the code by putting this in there that helps optimize their lines of business or whatever that is, and maybe can be online store or whatever. So I would say it was a better together type of story. >>Yeah. Which is, there's gotta be a song in there somewhere. So peek around the corner and if you wanna be headlights here right now in terms of 12, 18 months, I mean, what, you know, what what next to solve, right? You've already taken, you've slayed a few dragons along the way, but there are others I'm sure is it always happens in innovation in this space. Just when you solve a problem you've just dealt or you have to deal with others that pop up as maybe unintended consequences or at least a new challenge. So what would that be in your world right now? What, what do you see, you know, occupying your sleepless nights here for the next year or so? >>Well, for, for HOMEDALE data, it's all about improving database performance and scale. And those workloads change. We have O ltp, we have OLA with artificial intelligence ml. There's different type of traffic profiles and we're focused on improving those data profiles. It could be unstructured structured. Right now we're focused on structured data, which is relational databases, but there's a lot of opportunity to improve the performance of data. >>Well, you're driving the car, you got a good navigator. I think the GPS is working. So keep up the good work and thank you for sharing the time today. Thank you. Thank you, joy. Do appreciate it. All right, you are watching the cube. We continue our coverage here from AWS Reinvent 22, the Cube, of course, the leader in high tech coverage.

>> Well, welcome back here to the Venetian. We're in Las Vegas. It is Wednesday, Day 2 of our coverage here of AWS re:Invent, 22. I'm your host, John Walls on theCUBE and it's a pleasure to welcome in two more guests as part of our AWS startup showcase, which is again part of the startup program globally at AWS. I've got Anant Verma, who is the Vice President of Engineering at Elation. Anant, good to see you, sir. >> Good to see you too. >> Good to be with us. And Haseeb Budhani, who is the CEO and co-founder of Rafay Systems. Good to see you, sir. >> Good to see you again. >> Thanks for having, yeah. A cuber, right? You've been on theCUBE? >> Once or twice. >> Many occasions. But a first timer here, as a matter of fact, glad to have you aboard. All right, tell us about Elation. First for those whom who might not be familiar with what you're up to these days, just give it a little 30,000 foot level. >> Sure, sure. So, yeah, Elation is a startup and a leader in the enterprise data intelligence space. That really includes a lot of different things including data search, data discovery, metadata management, data cataloging, data governance, data policy management, a lot of different things that companies want to do with the hoards of data that they have and Elation, our product is the answer to solve some of those problems. We've been doing pretty good. Elation is in running for about 10 years now. We are a series A startup now, we just raised around a few, a couple of months ago. We are already a hundred million plus in revenue. So. >> John: Not shabby. >> Yeah, it's a big benchmark for companies to, startup companies, to cross that milestone. So, yeah. >> And what's the relationship? I know Rafay and you have worked together, in fact, the two of you have, which I find interesting, you have a chance, you've been meeting on Zoom for a number of months, as many of us have it meeting here for the first time. But talk about that relationship with Rafay. >> Yeah, so I actually joined Elation in January and this is part of the move of Elation to a more cloud native solution. So, we have been running on AWS since last year and as part of making our solution more cloud native, we have been looking to containerize our services and run them on Kubernetes. So, that's the reason why I joined Elation in the first place to kind of make sure that this migration or move to a cloud native actually works out really well for us. This is a big move for the companies. A lot of companies that have done in the past, including, you know, Confluent or MongoDB, when they did that, they actually really reap great benefits out of that. So to do that, of course, you know, as we were looking at Kubernetes as a solution, I was personally more looking for a way to speed up things and get things out in production as fast as possible. And that's where I think, Janeb introduced us... >> That's right. >> Two of us. I think we share the same investor actually, so that's how we found each other. And yeah, it was a pretty simple decision in terms of, you know, getting the solution, figuring it out if it's useful for us and then of course, putting it out there. >> So you've hit the keyword, Kubernetes, right? And, so if you would to honestly jump in here, there are challenges, right? That you're trying to help them solve and you're working on the Kubernetes platform. So, you know, just talk about that and how that's influenced the work that the two of you are doing together. >> Absolutely. So, the business we're in is to help companies who adopt Kubernetes as an orchestration platform do it easier, faster. It's a simple story, right? Everybody is using Kubernetes, but it turns out that Kubernetes is actually not that easy to to operationalize, playing in a sandbox is one thing. Operationalizing this at a certain level of scale is not easy. Now, we have a lot of enterprise customers who are deploying their own applications on Kubernetes, and we've had many, many of them. But when it comes to a company like Elation, it's a more complicated problem set because they're taking a very complex application, their application, but then they're providing that as a service to their customers. So then we have a chain of customers we have to make happy. Anant's team, the platform organization, his internal customers who are the developers who are deploying applications, and then, the company has customers, we have to make sure that they get a good experience as they consume this application that happens to be running on Kubernetes. So that presented a really interesting challenge, right? How do we make this partnership successful? So I will say that, we've learned a lot from each other, right? And, end of the day, the goal is, my customer, Anant's specifically, right? He has to feel that, this investment, 'cause he has to pay us money, we would like to get paid. >> John: Sure. (John laughs) >> It reduces his internal expenditure because otherwise he'd have to do it himself. And most importantly, it's not the money part, it's that he can get to a certain goalpost significantly faster because the invention time for Kubernetes management, the platform that you have to build to run Kubernetes is a very complex exercise. It took us four and a half years to get here. You want to do that again, as a company, right? Why? Why do you want to do that? We, as Rafay, the way I think about what we deliver, yes, we sell a product, but to what end? The product is the what, the why, is that every enterprise, every ISV is building a Kubernetes platform in house. They shouldn't, they shouldn't need to. They should be able to consume that as a service. They consume the Kubernetes engine the EKS is Amazon's Kubernetes, they consume that as an engine. But the management layer was a gap in the market. How do I operationalize Kubernetes? And what we are doing is we're going to, you know, the Anant said. So the warden saying, "Hey you, your team is technical, you understand the problem set. Would you like to build it or would you rather consume this as a service so you can go faster?" And, resoundingly the answer is, I don't want to do this anymore. I wouldn't allow to buy. >> Well, you know, as Haseeb is saying, speed is again, when we started talking, it only took us like a couple of months to figure out if Rafay is the right solution for us. And so we ended up purchasing Rafay in April. We launched our product based on Rafay in Kubernetes, in EKS in August. >> August. >> So that's about four months. I've done some things like this before. It takes a couple of years just to sort of figure out, how do you really work with Kubernetes, right? In a production at a large scale. Right now, we are running about a 600 node cluster on Rafay and that's serving our customers. Like, one of the biggest thing that's actually happening on December 8th is we are running what we call a virtual hands on lab. >> A virtual? >> Hands on lab. >> Okay. >> For Elation. And they're probably going to be about 500 people is going to be attending it. It's like a webinar style. But what we do in that hands on lab is we will spin up an Elation instance for each attendee, right on the spot. Okay? Now, think about this enterprise software running and people just sign up for it and it's there for you, right on the spot. And that's the beauty of the software that we have been building. There's the beauty of the work that Rafay has helped us to do over the last few months. >> Okay. >> I think we need to charge them more money, I'm getting from this congregation. I'm going to go work on that. >> I'm going to let the two of you work that out later. All right. I don't want to get in the way of a big deal. But you mentioned that, we heard about it earlier that, it's you that would offer to your cert, to your clients, these services. I assume they have their different levels of tolerance and their different challenges, right? They've got their own complexities and their own organizational barriers. So how are you juggling that end of it? Because you're kind of learning as, well, not learning, but you're experiencing some of the thing. >> Right. Same things. And yet you've got this other client base that has a multitude of experiences that they're going through. >> Right. So I think, you know a lot of our customers, they are large enterprise companies. They got a whole bunch of data that they want work with us. So one of the thing that we have learned over the past few years is that we used to actually ship our software to the customers and then they would manage it for their privacy security reasons. But now, since we're running in the cloud, they're really happy about that because they don't need to juggle with the infrastructure and the software management and upgrades and things like that, we do it for them, right? And, that's the speed for them because now they are only interested in solving the problems with the data that they're working with. They don't need to deal with all these software management issues, right? So that frees our customers up to do the thing that they want to do. Of course it makes our job harder and I'm sure in turn it makes his job harder. >> We get a short end of the stick, for sure. >> That's why he is going to get more money. >> Exactly. >> Yeah, this is a great conversation. >> No, no, no. We'll talk about that. >> So, let's talk about the cloud then. How, in terms of being the platform where all this is happening and AWS, about your relationship with them as part of the startup program and what kind of value that brings to you, what does that do for you when you go out and are looking for work and what kind of cache that brings to you >> Talk about the AWS? >> Yes, sir. >> Okay. Well, so, the thing is really like of course AWS, a lot of programs in terms of making sure that as we move our customers into AWS, they can give us some, I wouldn't call it discount, but there's some credits that you can get as you move your workloads onto AWS. So that's a really great program. Our customers love it. They want us to do more things with AWS. It's a pretty seamless way for us to, as we were talking about or thinking about moving into the cloud, AWS was our number one choice and that's the only cloud that we are in, today. We're not going to go to any other place. >> That's it. >> Yeah. >> How would you characterize? I mean, we've already heard, from one side of the fence here, but. >> Absolutely. So for us, AWS is a make or break partner, frankly. As the EKS team knows very well, we support Azure's Kubernetes and Google's Kubernetes and the community Kubernetes as well. But the number of customers on our platform who are AWS native, either a hundred percent or a large percentage is, you know, that's the majority of our customer base. >> John: Yeah. >> And AWS has made it very easy for us in a variety of ways to make us successful and our customers successful. So Anant mentioned the credit program they have which is very useful 'cause we can, you know, readily kind of bring a customer to try things out and they can do that at no cost, right? So they can spin up infrastructure, play with things and AWS will cover the cost, as one example. So that's a really good thing. Beyond that, there are multiple programs at AWS, ISV accelerate, et cetera. That, you know, you got to over time, you kind of keep getting taller and taller. And you keep getting on bigger and bigger. And as you make progress, what I'm finding is that there's a great ecosystem of support that they provide us. They introduce us to customers, they help us, you know, think through architecture issues. We get access to their roadmap. We work very, very closely with the guest team, for example. Like the, the GM for Kubernetes at AWS is a gentleman named Barry Cooks who was my sponsor, right? So, we spend a lot of time together. In fact, right after this, I'm going to be spending time with him because look, they take us seriously as a partner. They spend time with us because end of the day, they understand that if they make their partners, in this case, Rafay successful, at the end of the day helps the customer, right? Anant's customer, my customer, their AWS customers, also. So they benefit because we are collectively helping them solve a problem faster. The goal of the cloud is to help people modernize, right? Reduce operational costs because data centers are expensive, right? But then if these complex solutions this is an enterprise product, Kubernetes, at the enterprise level is a complex problem. If we don't collectively work together to save the customer effort, essentially, right? Reduce their TCO for whatever it is they're doing, right? Then the cost of the cloud is too high. And AWS clearly understands and appreciates that and that's why they are going out of their air, frankly, to make us successful and make other companies successful in the startup program. >> Well. >> I would just add a couple of things there. Yeah, so, you know, cloud is not new. It's been there for a while. You know, people used to build things on their own. And so what AWS has really done is they have advanced technology enough where everything is really simple as just turning on a switch and using it, right? So, just a recent example, and I, by the way, I love managed services, right? So the reason is really because I don't need to put my own people to build and manage those things, right? So, if you want to use a search, they got the open search, if you want to use caching, they got elastic caching and stuff like that. So it's really simple and easy to just pick and choose which services you want to use and they're ready to be consumed right away. And that's the beautiful, and that that's how we can move really fast and get things done. >> Ease of use, right? Efficiency, saving money. It's a winning combination. Thanks for sharing this story, appreciate. Anant, Haseeb thanks for being with us. >> Yeah, thank you so much having us. >> We appreciate it. >> Thank you so much. >> You have been a part of the global startup program at AWS and startup showcase. Proud to feature this great collaboration. I'm John Walls. You're watching theCUBE, which is of course the leader in high tech coverage.

>>And welcome back to the Cube everyone. I'm John Walls to continue our coverage here of AWS Reinvent 22. We're part of the AWS Startup Showcase is the global startup program that AWS so proudly sponsors and with us to talk about what they're doing now in the AWS space. Shaun Knapps, the CEO of AS Send IO and Sean, good to have here with us. We appreciate >>It. Thanks for having me, >>John. Yeah, thanks for the time. First off, gotta show the t-shirt. You caught my attention. Big data is a cluster. I don't think you get a lot of argument from some folks, right? But it's your job to make some sense of it, is it not? Yeah. Tell us about a Send io. >>Sure. As Send IO is a data automation platform. What we do is connect a lot of the, the disparate parts of what data teams do when they create ETL and E o T data pipelines. And we use advanced levels of automation to make it easier and faster for them to build these complex systems and have their world be a little bit less of a, a cluster. >>All right. So let's get into automation a little bit then again, I, your definition of automation and how you're applying it to your business case. >>Absolutely. You know, what we see oftentimes is as spaces mature and evolve, the number of repetitive and repeatable tasks that actually become far less differentiating, but far more taxable if you will, right to the business, start to accumulate as those common patterns emerge. And, and, you know, as we see standardization around tech stacks, like on Amazon and on Snowflake and on data bricks, and as you see those patterns really start to, to formalize and standardize, it opens up the door to basically not have your team have to do all those things anymore and write code or perform the same actions that they used to always have to, and you can lean more on technology to properly automate and remove the, the monotony of those tasks and give your teams greater leverage. >>All right. So, so let's talk about at least maybe your, the journey, say in the past 18 months in terms of automation and, and what have you seen from a trend perspective and how are you trying to address that in order to, to meet that need? >>Yeah, I think the last 18 months have become, you know, really exciting as we've seen both that, you know, a very exciting boom and bust cycle that are driving a lot of other macro behaviors. You know, what we've seen over the last 18 months is far greater adoption of the, the standard, what we call the data planes, the, the architectures around snowflake and data bricks and, and Amazon. And what that's created as a result is the emergence of what I would call is the next problem. You know, as you start to solve that category of how >>You, that's it always works too, isn't >>It? Yeah, exactly. Always >>Works that >>This is the wonderful thing about technology is the job security. There's always the next problem to go solve. And that's what we see is, you know, as we we go into cloud, we get that infinite scale, infinite capacity, capacity, infinite flexibility. And you know, with these modern now data platforms, we get that infinite ability to store and process data incredibly quickly with incredible ease. And so what, what do most organizations do? You take a ton of new bodies, like all the people who wanted to do those like really cool things with data you're like, okay, now you can. And so you start throwing a lot more use cases, you start creating a lot more data products, you start doing a lot more things with data. And this is really where that third category starts to emerge, which is you get this data mess, not mesh, but the data mess. >>You get a cluster cluster, you get a cluster exactly where the complexity skyrockets. And as a result that that rapid innovation that, that you are all looking for and, and promised just comes to a screeching halt as you're just, just like trying to swim through molasses. And as a result, this is where that, that new awareness around automation starts really heightened. You know, we, we did a really interesting survey at the start of this year, did it as a blind survey, independent third party surveyed, 500 chief data officers, data scientists, data architects, and asked them a plethora of questions. But one of the questions we asked them was, do you currently or do you intend on investing in data automation to increase your team's productivity? And what was shocking, and I was very surprised by this, okay, what was shocking was only three and a half percent said they do today. Which is really interesting because it really hones in on this notion of automation is beyond what a lot of a think of, you know, tooling and enhancements today, only three and a half percent today had it, but 88.5% said they intend on making data automation investments in the next 12 months. And that stark contrast of how many people have a thing and how many people want that benefit of automation, right? I think it is incredibly critical as we look to 2023 and beyond. >>I mean, this seems like a no-brainer, does it not? I mean, know it is your business, of course you agree with me, but, but of course, of course what brilliant statement. But it is, it seems like, you know, the more you're, you're able to automate certain processes and then free up your resources and your dollars to be spent elsewhere and your, and your human capital, you know, to be invested elsewhere. That just seems to be a layup. I'm really, I'm very surprised by that three and a half percent figure >>I was too. I actually was expecting it to be higher. I was expecting five to 10%. Yeah. As there's other tools in the, the marketplace around ETL tools or orchestration tools that, that some would argue fit in the automation category. And I think the, what, what the market is telling us based on, on that research is that those themselves are, don't qualify as automation. That, that the market has a, a larger vision for automation. Something that is more metadata driven, more AI back, that takes us a greater leap and of leverage for the teams than than what the, the existing capabilities in the industry today can >>Afford. Okay. So if you got this big leap that you can make, but, but, but maybe, you know, should sites be set a little lower, are you, are you in danger of creating too much of an expectation or too much of a false hope? Because you know, I mean sometimes incremental increases are okay. I >>Agree. I I I think the, you know, I think you wanna do a little bit of both. I think you, you want to have a plan for, for reaching for the stars and you gotta be really pragmatic as well. Even inside of a a suni, we actually have a core value, which is build for 10 x plan for a hundred x and so know where you're going, right? But, but solve the problems that are right in front of you today as, as you get to that next scale. And I think the, the really important part for a lot of companies is how do you think about what that trajectory is and be really smart around where you choose to invest as you, one of the, the scenes that we have is last year's innovation is next year's anchor around your neck. And that's because we, we were in this very fortunately, so this really exciting, rapidly moving innovative space, but the thing that was your advantage not too long ago is everybody can move so quickly now becomes commonplace and a year or two later, if you don't jump on whatever that next innovation is that the industry start to standardize on, you're now on hook paying massive debt and, and paying, you know, you thought you had, you know, home mortgage debt and now you're paying the worst of credit card debt trying to pay that down and maintain your velocity. >>It's >>A whole different kind of fomo, right? I'm fair, miss, I'm gonna miss out. What am I missing out on? What the next big thing exactly been missing out >>On that? And so we encourage a lot of folks, you know, as you think about this as it pertains to automation too, is you solve for some of the problems right in front of you, but really make sure that you're, you're designing the right approach that as you stack on, you know, five times, 10 times as many people building data products and, and you, you're, you're your volume and library of, of data weaving throughout your, your business, make sure you're making those right investments. And that's one of the reasons why we do think automation is so important and, and really this, this next generation of automation, which is a, a metadata and AI back to level of automation that can just achieve and accomplish so much more than, than sort of traditional norms. >>Yeah. On that, like, as far as Dex Gen goes, what do you think is gonna be possible that cloud sets the stage for that maybe, you know, not too long ago seem really outta reach, like, like what's gonna give somebody to work on that 88% in there that's gonna make their spin come your way? >>Ah, good question. So I, I think there's a couple fold. I, you know, I think the, right now we see two things happening. You know, we see large movements going to the, the, the dominant data platforms today. And, and you know, frankly, one of the, the biggest challenges we see people having today is just how do you get data in which is insanity to me because that's not even the value extraction, that is the cost center piece of it. Just get data in so you can start to do something with it. And so I think that becomes a, a huge hurdle, but the access to new technologies, the ability to start to unify more of your data and, and in rapid fashion, I think is, is really important. I think as we start to, to invest more in this metadata backed layer that can connect that those notions of how do you ingest your data, how do you transform it, how do you orchestrate it, how do you observe it? One of the really compelling parts of this is metadata does become the new big data itself. And so to do these really advanced things to give these data teams greater levels of automation and leverage, we actually need cloud capabilities to process large volumes of not the data, but the metadata around the data itself to deliver on these really powerful capabilities. And so I think that's why the, this new world that we see of the, the developer platforms for modern data cloud applications actually benefit from being a cloud native application themselves. >>So before you take off, talk about the AWS relationship part of the startup showcase part of the growth program. And we've talked a lot about the cloud, what it's doing for your business, but let's just talk about again, how integral they have been to your success and, and likewise what you're thinking maybe you bring to their table too. Yeah, >>Well we bring a lot to the table. >>Absolutely. I had no doubt about that. >>I mean, honestly, it, working with with AWS has been truly fantastic. Yep. You know, I think, you know, as a, a startup that's really growing and expanding your footprint, having access to the resources in AWS to drive adoption, drive best practices, drive awareness is incredibly impactful. I think, you know, conversely too, the, the value that Ascend provides to the, the AWS ecosystem is tremendous leverage on onboarding and driving faster use cases, faster adoption of all the really great cool, exciting technologies that we get to hear about by bringing more advanced layers of automation to the existing product stack, we can make it easier for more people to build more powerful things faster and safely. Which I think is what most businesses at reinvent really are looking for. >>It's win-win, win-win. Yeah. That's for sure. Sean, thanks for the time. Thank you John. Good job on the t-shirt and keep up the good work. Thank you very much. I appreciate that. Sean Na, joining us here on the AWS startup program, part of their of the Startup Showcase. We are of course on the Cube, I'm John Walls. We're at the Venetian in Las Vegas, and the cube, as you well know, is the leader in high tech coverage.

(upbeat music) >> Hi everybody. Welcome back to theCUBE as to continue our coverage here at AWS re:Invent '22. We're in the Venetian. Out in Las Vegas, it is Wednesday. And the PaaS is still happening. I can guarantee you that. We continue our series of discussions as part of the "AWS Startup Showcase". This is the "Global Startup Program", a part of that showcase. And I'm joined by two gentlemen today who are going to talk about what CoreStack is up to. One of them is Ez Natarajan, who is the Founder and CEO. Good to have you- (simultaneous chatter) with us today. We appreciate it. Thanks, EZ. >> Nice to meet you, John. >> And Brad Winney who is the area Sales Leader for startups at AWS. Brad, good to see you. >> Good to see you, John. >> Thanks for joining us here on The Showcase. So Ez, first off, let's just talk about CoreStack a little bit for people at home who might not be familiar with what you do. It's all about obviously data, governance, giving people peace of mind, but much deeper than that. I'll let you take it from there. >> So CoreStack is a governance platform that helps customers maximize their cloud usage and get governance at scale. When we talk about governance, we instill confidence through three layers: solving the problems of the CIO, solving the problems of the CTO, solving the problems of the CFO, together with a single pin of class,- >> John: Mm-hmm. >> which helps them achieve continuous holistic automated outcomes at any given time. >> John: Mm-hmm. So, Brad, follow up on that a little bit- >> Yeah. because Ez touched on it there that he's got a lot of stakeholders- >> Right. >> with a lot of different needs and a lot of different demands- >> Mm-hmm. >> but the same overriding emotion, right? >> Yeah. >> They all want confidence. >> They all want confidence. And one of the trickiest parts of confidence is the governance issue, which is policy. It's how do we determine who has access to what, how we do that scale. And across not only start been a process. This is a huge concern, especially as we talked a lot about cutting costs as the overriding driver for 2023. >> John: Mm-hmm. >> The economic compression being what it is, you still have to do this in a secure way and as a riskless way as possible. And so companies like CoreStack really offer core, no pun intended, (Ez laughs) function there where you abstract out a lot of the complexity of governance and you make governance a much more simple process. And that's why we're big fans of what they do. >> So we think governance from a three dimensional standpoint, right? (speaks faintly) How do we help customers be more compliant, secure, achieve the best performance and operations with increased availability? >> Jaohn: Mm-hmm. >> At the same time do the right spend from a cost standpoint. >> Interviewer: Mm-hmm. So when all three dimensions are connected, the business velocity increases and the customer's ability to cater to their customers increase. So our governance tenants come from these three pillars of finance operations, security operations and air operations at cloud operations. >> Yeah. And... Yeah. Please, go ahead. >> Can I (indistinct)? >> Oh, I'm sorry. Just- >> No, that's fine. >> So part of what's going on here, which is critical for AWS, is if you notice a lot of (indistinct) language is at the business value with key stakeholders of the CTO, the CSO and so on. And we're doing a much better job of speaking business value on top of AWS services. But the AWS partners, again, like CoreStack have such great expertise- >> John: Mm-hmm. >> in that level of dialogue. That's why it's such a key part for us, why we're really interested partnering with them. >> How do you wrestle with this, wrestle may not be the right word, but because you do have, as we just went through these litany, these business parts of your business or a business that need access- >> Ez: Mm-hmm. >> and that you need to have policies in place, but they change, right? I mean, and somebody maybe from the financial side should have a window into data and other slices of their business. There's a lot of internal auditing. >> Man: Mm-hmm. >> Obviously, it's got to be done, right? And so just talk about that process a little bit. How you identify the appropriate avenues or the appropriate gateways for people to- >> Sure. >> access data so that you can have that confidence as a CTO or CSO, that it's all right. And we're not going to let too much- >> out to the wrong people. >> Sure. >> Yeah. So there are two dimensions that drive the businesses to look for that kind of confidence building exercise, right? One, there are regulatory external requirements that say that I know if I'm in the financial industry, I maybe need to following NIST, PCI, and sort of compliances. Or if I'm in the healthcare industry, maybe HIPAA and related compliance, I need to follow. >> John: Mm-hmm. >> That's an external pressure. Internally, the organizations based on their geographical presence and the kind of partners and customers they cater to, they may have their own standards. And when they start adopting cloud; A, for each service, how do I make sure the service is secure and it operates at the best level so that we don't violate any of the internal or external requirements. At the same time, we get the outcome that is needed. And that is driven into policies, that is driven into standards which are consumable easily, like AWS offers well-architected framework that helps customers make sure that I know I'm architecting my application workloads in a way that meets the business demands. >> John: Mm-hmm. >> And what CoreStack has done is taken that and automated it in such a way it helps the customers simplify that process to get that outcome measured easily so they get that confidence to consume more of the higher order services. >> John: Okay. And I'm wondering about your relationship as far with AWS goes, because, to me, it's like going deep sea fishing and all of a sudden you get this big 4, 500 pound fish. Like, now what? >> Mm-hmm. >> Now what do we do because we got what we wanted? So, talk about the "Now what?" with AWS in terms of that relationship, what they're helping you with, and the kind of services that you're seeking from them as well. >> Oh, thanks to Brad and the entire Global Startup Ecosystem team at AWS. And we have been part of AWS Ecosystem at various levels, starting from Marketplace to ISV Accelerate to APN Partners, Cloud Management Tools Competency Partner, Co-Sell programs. The team provides different leverages to connect to the entire ecosystem of how AWS gets consumed by the customers. Customers may come through channels and partners. And these channels and partners maybe from WAs to MSPs to SIs to how they really want to use each. >> John: Mm-hmm. >> And the ecosystem that AWS provides helps us feed into all these players and provide this higher order capability which instills confidence to the customers end of the day. >> Man: Absolutely. Right. >> And this can be taken through an MSP. This can be taken through a GSI. This can be taken to the customer through a WA. And that's how our play of expansion into larger AWS customer base. >> Brad: Yeah. >> Brad, from your side of the fence. >> Brad: No, its... This is where the commons of scale come to benefit our partners. And AWS has easily the largest ecosystem. >> John: Mm-hmm. >> Whether or not it's partners, customers, and the like. And so... And then, all the respective teams and programs bring all those resources to bear for startups. Your analogy of of catching a big fish off coast, I actually have a house in Florida. I spend a lot of time there. >> Interviewer: Okay. >> I've yet to catch a big 500 pound fish. But... (interviewer laughs) >> But they're out there. >> But they're definitely out there. >> Yeah. >> And so, in addition to the formalized programs like the Global Partner Network Program, the APN and Marketplace, we really break our activities down with the CoreStacks of the world into two major kind of processes: "Sell to" and "Sell with". And when we say "Sell to", what we're really doing is helping them architect for the future. And so, that plays dividends for their customers. So what do we mean by that? We mean helping them take advantage of all the latest serverless technologies: the latest chip sets like Graviton, thing like that. So that has the added benefit of just lowering the overall cost of deployment and expend. And that's... And we focus on that really extensively. So don't ever want to lose that part of the picture of what we do. >> Mm-hmm. >> And the "Sell with" is what he just mentioned, which is, our teams out in the field compliment these programs like APN and Marketplace with person-to-person in relationship development for core key opportunities in things like FinTech and Retail and so on. >> Interviewer: Mm-hmm. >> We have significant industry groups and business units- >> Interviewer: Mm-hmm. >> in the enterprise level that our teams work with day in and day out to help foster those relationships. And to help CoreStack continue to develop and grow that business. >> Yeah. We've talked a lot about cost, right? >> Yeah. >> But there's a difference between reducing costs or optimizing your spend, right? I mean there- >> Brad: Right. >> Right. There's a... They're very different prism. So in terms of optimizing and what you're doing in the data governance world, what kind of conversations discussions are you having with your clients? And how is that relationship with AWS allowing you to go with confidence into those discussions and be able to sell optimization of how they're going to spend maybe more money than they had planned on originally? >> So today, because of the extra external micro-market conditions, every single customer that we talk to wanting to take a foster status of, "Hey, where are we today? How are we using the cloud? Are we in an optimized state?" >> Interviewer: Mm-hmm. >> And when it comes to optimization, again, the larger customers that we talk to are really bothered about the business outcome and how their services and ability to cater to their customers, right? >> Interviewer: Mm-hmm. >> They don't want to compromise on that just because they want to optimize on the spend. That conversation trickled down to taking a poster assessment first, and then are you using the right set of services within AWS? Are the right set of services being optimized for various requirements? >> Interviewer: Mm-hmm. >> And AWS help in terms of catering to the segment of customers who need that kind of a play through the patent ecosystem. >> John: Mm-hmm. Yeah. We've talked a lot about confidence too, cloud with confidence. >> Brad: Yeah. Yeah. >> What does that mean to different people, you think? I mean, (Brad laughing) because don't you have to feel them out and say "Okay. What's kind of your tolerance level for certain, not risks, but certain measures that you might need to change"? >> I actually think it's flipped the other way around now. I think the risk factor- >> Okay. >> is more on your on-prem environment. And all that goes with that. 'Cause you... Because the development of the cloud in the last 15 years has been profound. It's gone from... That's been the risky proposition now. With all of the infrastructure, all the security and compliance guardrails we have built into the cloud, it's really more about transition and risk of transition. And that's what we see a lot of. And that's why, again, where governance comes into play here, which is how do I move my business from on-prem in a fairly insecure environment relatively speaking to the secure cloud? >> Interviewer: Sure. >> How do I do that without disrupting business? How do I do that without putting my business at risk? And that's a key piece. I want to come back, if I may, something on cost-cutting. >> Interviewer: Sure. >> We were talking about this on the way up here. Cost-cutting, it's the bonfire of the vanities in that in that everybody is talking about cost-cutting. And so we're in doing that perpetuating the very problem that we kind of want to avoid, which is our big cost-cutting. (laughs) So... And I say that because in the venture capital community, what's happening is two things: One is, everybody's being asked to extend their runways as much as possible, but they are not letting them off the hook on growth. And so what we're seeing a lot of is a more nuanced conversation of where you trim your costs, it's not essential, spend, but reinvest. Especially if you've got good strong product market fit, reinvest that for growth. And so that's... So if I think about our playbook for 2023, it's to help good strong startups. Either tune their market fit or now that they good have have good market fit, really run and develop their business. So growth is not off the hook for 2023. >> And then let me just hit on something- >> Yeah. >> before we say goodbye here that you just touched on too, Brad, about. How we see startups, right? AWS, I mean, obviously there's a company focus on nurturing this environment of innovation and of growth. And for people looking at maybe through different prisms and coming. >> Brad: Yeah. >> So if you would maybe from your side of the fence, Ez from CoreStack, about working as a startup with AWS, I mean, how would you characterize that relationship about the kind of partnership that you have? And I want to hear from Brad too about how he sees AWS in general in the startup world. But go ahead. >> It's kind of a mutually enriching relationship, right? The support that comes from AWS because our combined goal is help the customers maximize the potential of cloud. >> Interviewer: Mm-hmm. >> And we talked about confidence. And we talked about all the enablement that we provide. But the partnership helps us get to the reach, right? >> Interviewer: Mm-hmm. >> Reach at scale. >> Interviewer: Mm-hmm. We are talking about customers from different industry verticals having different set of problems. And how do we solve it together so that like the reimbursement that happens, in fact healthcare customers that we repeatedly talk to, even in the current market conditions, they don't want to save. They want to optimize and re-spend their savings using more cloud. >> Interviewer: Mm-hmm. >> So that's the partnership that is mutually enriching. >> Absolutely. >> Yeah. To me, this is easy. I think the reason why a lot of us are here at AWS, especially the startup world, is that our business interests are completely aligned. So I run a pretty significant business unit in a startup neighbor. But a good part of my job and my team's job is to go help cut costs. >> Interviewer: Mm-hmm. >> So tell me... Show me a revenue responsibility position where part of your job is to go cut cost. >> Interviewer: Right. >> It's so unique and we're not a non-profit. We just have a very good long-term view, right? Which is, if we help companies reduce costs and conserve capital and really make sure that that capital is being used the right way, then their long-term viability comes into play. And that's where we have a chance to win more of that business over time. >> Interviewer: Mm-hmm. >> And so because those business interests are very congruent and we come in, we earn so much trust in the process. But I think that... That's why I think we being AWS, are uniquely successful startups. Our business interests are completely aligned and there's a lot of trust for that. >> It's a great success story. It really is. And thank you for sharing your little slice of that and growing slice of that too- >> Yeah. Absolutely. >> from all appearances. Thank you both. >> Thank you, John. >> Thank you very much, John. >> Appreciate your time. >> This is part of the AWS Startup Showcase. And I'm John Walls. You're watching theCUBE here at AWS re:Invent '22. And theCUBE, of course, the leader in high tech coverage.

(steady music) >> Oh, welcome back here on theCUBE. I'm John Walls, we're in The Venetian and day one of a jam-packed three days here at AWS re:Invent '22. This is the Executive Summit sponsored by Accenture, and it is Merck time. And I mean, it is loaded with Merck time. We have quite the panel here, in fact. First threesome of the day, by the way. I see you guys have really loaded up nicely. Ron Kim is with us, the SVP and CTO of Merck. Ron, good to see you, sir. >> Thanks, John. >> Also, Fran Gaetens, who's the VP of Technology Infrastructure, Operations, and Experience, which I want to hear more about. Love that job title, Fran. >> Thanks, John. >> And Sean Finnerty, VP of Cloud and Infrastructure Technology. Again, everybody here from Merck. So fellows, thanks for being with us. >> Thanks, John. >> Appreciate the time. >> Yeah. >> So let's just talk about Merck, first off in general in terms of what's happening with the cloud. And Ron, I'll let you jump onto that first. I realize this talk of journey, right? >> Mm-hm. >> It's different for everybody, different slices depending upon where you are, where you start, where you need to finish. Where are you right now in terms of what you're doing with the cloud? >> Yeah, John, we've been on this journey for about two years, have done some great work and achieve some great results in proving we could move to the cloud, moving to the cloud at scale, achieving really measurable financial and operational results. Where we're focusing now going forward is transforming the business. And as you know, our business is saving and improving lives. And so when we talk about moving things to the cloud, it's much more than just moving servers or things like that. It's really contributing towards our business that saves and improves lives. So for our work that we work on together moving into the cloud, the stakes are high, but we think the opportunity's great. And the way to seize that opportunity is what we're doing now, is our BlueSky program and working with AWS and Accenture on it. >> Yeah, so two years, you're two years in. It's like nascent stage still, right? I mean, and it never ends, (laughs) frankly. >> Yeah. >> But talk about that progression and was it, you know, baby steps, was it diving in? I mean, how do you decide, you know, the batting order basically here about how you're going to get things going? >> The early parts of the the two-year journey so far, we're really starting small, primarily driven by a central team. And we did that consciously to get momentum, build the foundation, prove again we could move things to the cloud with success, we could start to scale. And then as that journey went on, now instead of just relying on the central team, we're starting to get the rest of the company involved. So this is not just this team doing the cloud journey. It's the whole company, and that's an ongoing journey, getting all the different stakeholders involved and things like that. But I think that's where we are on the journey now, is look, let's lock arms with everybody in the company. So it's a Merck-wide cloud transformation, not just the BlueSky team. >> Right, and of course, as you know, the C-suite's got to be behind all this. And we hear about how that it's now being driven in some cases, you know, these kind of transformations, whether it's from CEO level down the CTO and CIO and what have you. Fran, the experience part of your job. I just want to get to that real quick. So you know, how do you define that? >> Yeah. First of all, I'm delighted you asked. >> Okay. (laughs) >> And the focus on experience that my team's accountable for transcends, you know, our cloud journey. We have held for the last three years within my organization a priority that's focused on improving the experience that colleagues in our company have with workplace technology and services. And so I'd come into this role at the time and thought carefully, you know, about how to best title our organization in a way that would draw curiosity or inquisition. >> Sure. >> A very creative colleague that we have an opportunity to work with in our company suggested the term, and I loved it and ran with it. And today, it's, you know, still something that we spend a significant portion of cycles focused on. >> Well, it's a very clear signal, right? And a reminder as well that ultimately the experience whether it's your internal stakeholders or external, your customers, right, that you're delivering a very pleasant and efficient, and hopefully you said life-saving >> Yeah. >> experience as well. And I think that'd be a pretty good reminder for your team, isn't it? >> It is. >> "Hey, we're all part of the experience here." >> Yeah. >> Yeah. Right, so Sean, let's talk about some of the things that we've discussed here, branching out within Merck. >> Yep. >> You know, and making it a company effort, not just an IT effort. Right, now all of a sudden, you're into everybody's business and everybody is sharing this. I mean, is there buying that's necessary here? I mean, how do you bring that bunch along? You've all lived it, you know it. They're experiencing it for the first time. >> Yeah, it's a great question and it's one we get quite a bit walking the halls here at re:Invent. We're very lucky in that we do have, you mentioned earlier, top-down support, right? So when we're talking about moving to the cloud, we're not just running around the halls of the technology, you know, cubes of all the people that are sitting there at computers banging away every day. We're meeting with the CEO and a significant portion of the executive team, talking about how does our cloud journey underpin our business transformation aspirations? How do we speed up scientific research? How do we do clinical trials more effectively? How do we manufacture medicine more effectively, more reliably? Those are all underpinned by this technology transformation that we're embarking on sort of from the bottoms up, and meeting in the middle with the top-down strategic imperative to transform the business by leveraging technology. So that clear and unambiguous support coming from the C-suite at our company allows us to prioritize very aggressively and point at that mission to say, "Hey, we're not just here to talk about moving a server or two. We're here to talk about how we transform scientific research and discovery in the interest of our patients and delivering medicine more effectively, more quickly." So it's really, really interesting. >> Yeah, and so being on one side of that, you know, obviously you're dealing with people, whether chemists, scientists, whomever doing computational chemistry whatever it might be. They know their business and you're trying to integrate these new capabilities into their business, right? How do you do that? I mean, how do you know what they need and how do they tell you what they need when they don't know what you have? (laughs) >> That's quite a question. >> Yeah. I got there. >> Yeah, I mean, my initial thought is, you know, there has to be a compelling value to anybody getting impacted by this. And that's what we all work to do. So whether it's faster, less lead time, reducing cycle times, more reliability, innovation, I mean, there has to be something in it for them, and the work we're doing crosses that whole spectrum. So some of the efforts we have, "Hey, this is a cost-savings effort, this is for agility, this is for speed." So you know, it can't be just we're just doing this for the sake of moving of the cloud. There has some business value in it. And you know, Sean and the team have done a great job on kind of putting the rigor behind how do we describe that value so people then say, "Is that value really there or not? And does it really add up?" And I think that's been one of the keys to our success, is the work that Sean and members of his team have been doing is there's a pretty rigorous way we track our progress. And we've involved finance from day one in that. So having their buy in, you know, gives the whole set of results a lot of credibility. >> But tell me about that, Sean, about in terms of identifying value and quantifying it, in terms that a bottom line can orient to that. >> Yeah, absolutely. I mean, I've been at the cloud migration game myself personally for years, right? I got into this game back in 2011. The challenge of those programs has always been articulating the value associated with migrating stuff. It's easy to say, "I'm going to take a server. I'm going to move it from here to here. Then that difference is X, point at that." That's easy, everyone can understand that. But the labor efficiencies and the business value and the business transformation that comes with moving a capability from on-prem or from another hosting service to the cloud and transforming how we deliver, manage, operate, and scale those solutions, that's really where the power of this comes from, is business value tied to discrete actions, moving systems with a plan from one point to another point. And then being able to clearly articulate the value by implementing, as Ron mentioned, models we've created. So we've created actually financial calculation models to put dollars and cents next to labor efficiencies, time liberated, you know, the ability to deliver with higher velocity, higher quality, higher reliability. Those now have dollar values associated with them, which we're able to take, apply to our portfolio, and look for those opportunities that jump out as, "Hey, you know, that one's worth a million bucks. Let's prioritize that one. The ones that maybe have lower value or less business impact, you know, let's put those to the side and get to those later." So we can constantly demonstrate that not only are we raising our ability to deliver for our patients, but we're also delivering value back to the corporation to invest in other things that need focus and attention. >> Yeah, so talk about AWS and Accenture a little bit about, I mean, obviously big players with this. I'm assuming that interaction, maybe Fran, you know, talk about the partnership and again, how they have helped you get to the point that where you currently reside. >> Yeah, our partnership with both firms has been longstanding. That said, you know, what's changed in a market way happened a couple years ago when we originated this cloud acceleration program that we called BlueSky. We worked directly with Accenture to develop a comprehensive business case that, you know, fundamentally lined out the detail of our intention, how we would prosecute this work, and you know, among other things be crystal clear about the value at stake and how we would capture and realize that over time. So you know, through that lens, it's really taken a village with parties from all three firms, you know, to come together, prosecute this important work, but likewise, as I like to say, keep score, you know, in the context of value because ultimately, it's the one thing that we can talk about unambiguously with the program in the context of measurable results. >> Because of the work you do, obviously, you know, invaluable in many respects. But just the thought about cloud, and I know governance, security, compliance, all these things are critical. You know, how do those weigh in, in terms of considerations you have to make? And especially going forward as you develop new ideas, new things, ideas you're trying to bring to market, >> Yeah. >> I mean, how much does that play and the cloud and what exposures there might be? >> Yeah, it plays in quite a bit. And no matter what type of work we do, cloud or on-premise, I mean, security is of utmost importance. That's how we operate. Now what's interesting is when we think about in AWS, you know, AWS has the ability, they have the the scale and the learnings from multiple clients, right? So rather than a single company like us trying to figure out security on our own, we can benefit from what are all the lessons that they've learned that they bake back into their platform. So that's been a great benefit. But regardless of our partner, we'll always be very, a lot of scrutiny about security no matter what. And that's how we should operate. But the benefits of the platform within AWS, I mean, there's a lot of security intelligence built in from their experience, so that's- >> If I can add to that- >> Sure. >> Yeah. To build on prior remarks that Sean had articulated, this migration to the cloud, right, happens to be a catalyst for a broader transformation. One where we're fundamentally changing our ways of working. Ways that consider, you know, topics like security, compliance, documentation, regulatory requirements. And choosing to bake those in to these solutions from the onset rather than consider them as an appendage or an afterthought. So you know, the cloud is a really important part of this. You know, there's no mistake about it, but it's also a powerful catalyst for something that's broader. >> Tremendously more efficient, right? With our thinking and how we're going to plan and how we're going to execute. >> Yeah, and to build on that even more, we view it as an opportunity to raise the bar on our compliance, security, and regulatory readiness game. As we're touching applications across our portfolio, rearchitecting, leaning in on things like the well-architected framework and other things that AWS and Accenture bring to bear. We set the bar higher when we move things from where they are today to a new destination and introduce automation so that that uplift of control does not come at the cost of additional time or labor. It's simply we're raising the bar in ourselves. We're using this transformational opportunity to implement that change. Our customers are along for the ride and reap the benefits of the fact that, you know, we've raised the bar on ourselves, basically. >> Well, you said two years, so the first steps, and I'm sure the next ones are going to be just as successful. I really appreciate the time. Thanks for sharing that and for bringing so much expertise at the table. >> Thanks, John. >> Appreciate that, good to have you guys with us. >> Thanks. >> Talking about Merck and their cloud transformation. Love that word, we've been talking a lot about it this week. You're watching theCUBE, of course, here at the Executive Summit sponsored by Accenture. And theCUBE being, of course, the leader at tech coverage. (calm music)

>> Well, thanks for joining us here on theCUBE. I'm John Walls. We're at Reinvent AWS's big show going on here in Las Vegas at the Venetian. Going to be here all week, so be sure to tune in here to theCUBE as we continue our executive summit sponsored by Accenture today. Joined now by Steve Steuart, who's the worldwide principal on mainframe migration at Go to Market at AWS. Steve, good to see you, sir. >> Nice to meet you. >> Just found out we're neighbors, as a matter of fact, down in northeastern Florida. >> That's right. >> So we'll exchange addresses later, I'm sure. And Joel Rosenberger, who is a global mainframe monetization lead for the Accenture AWS business group. Joel, good to see you. >> Nice to meet you. >> Thanks for joining us here on theCUBE. >> Absolutely. >> All right, so what's up with the mainframe? We're kind of kidding about 64 Corvette's versus 22 Teslas and making that old Corvette. Dress it up, take it out for the street ride. Make it nice and fun. But let's just set the stage here first off for our viewers about mainframe and kind of the status in terms of modernization and getting it up to 22 standards. >> Right, I mean, I think the big thing is that, you know modernization for mainframes is different for every customer based on their drivers and where they want to go. You know, at AWS we like to say transform with AWS, augmentation pattern, hybrid pattern, working coexisting or transform too. So move some of those workloads into the cloud. And it's not that, you know mainframes are fantastic machines, but they are in dire need of modernization with their applications. And that's really the driving force and the business needs to make a decision based on their drivers, what's best fit for them. And we're here to help. >> So how, Joel, go ahead. >> Oh, I was going to say, and we're saying that too is basically the mainframe is a great technology platform but it's the processes around that that not kept up. So making changes to the mainframe applications can take a couple years, for the simplest changes. And so when Steve talks about modernizing with or on the mainframe it's really how do we improve those processes? And from our perspective and companies are really struggling with that right now. >> Yeah, and how do you go about this, because the mainframe is so center, right? It is so integral, right? >> Oh it's center. >> Oh yeah, absolutely. >> Absolutely essential. And yet you're talking about changes being made over a period of time of years. A lot of sensitivity there, right? >> Oh absolutely. >> Lot of complexity there. So how do you start factoring all that in and selling that to somebody that this journey might take you till 2025 to get it done? >> Well it could be a multi-year process. The selling is really the business drivers. You have to, businesses today need to leverage the cloud to be competitive. >> Absolutely. >> Right, that's just a fact. Right? So, how do you transform with modernize in place, or transform over. But it is a transformational change. If you look at the number one drivers is agility. The CEO say, I want this green next week and well we can't get it to you next week. We can get it to you Q2 of next year. Born in the cop companies... >> That's probably not the answer they want to hear. >> No, they don't want hear that. >> That is not the answer they want to hear. >> Our number one issue is that there are CEOs saying that we can't be agile, but mainframes can't be agile, if you develop, adopt DevOps for your mainframe. >> Yep. >> IBM has an offering, we have an offering as well. And so they need to start looking at that. So what are your drivers? Go to market responsiveness, competitive, what are the drivers? And then you make a decision as to where you want to move the workload. >> Joel: Yep. >> Is it hard though, Joel, just because as you know this environment is so dynamic now, right? >> Yep. >> And change is rapid, and I mean like capital R. >> Yep, absolutely. Yep. >> So all of a sudden you set this two/three year trajectory and yet opportunities, solutions, options can vary in year one or year two and all of a sudden this path you had set is going to have to take a left turn instead of a right turn because of a new development. Right? So it's... >> Absolutely, I mean, and that's one of the biggest struggles that people have is with business agility. Exactly what you're saying is the market is changing faster, like Steve said, it might be a year or so before I can deliver that but the market has already changed from that perspective. >> Right. >> And so I think a lot of people are trying to modernize with that. So they're connecting a lot of web properties to mainframes but that causes additional problems. >> Right. >> And those problems are the mainframe now scales unpredictably, because I don't know, how do I predict web traffic and from that perspective, so a lot of people are struggling do I have enough capacity on the mainframe to do that? Cause it's not elastic like the cloud from that perspective. So there's a lot of patterns that have to be reinvented, or already been invented with the cloud and how do we do that with the mainframe now? >> So you could get benefits not waiting three to four years. >> Absolutely. >> You get benefit pretty much immediately by doing augmentation patterns consuming processing on the mainframe, consuming it maybe certain movements, certain workloads, bringing on down quicker. You know, if you're a large estate it'll take you time but you are able to drive that. Part of our assessments is bottom up what you currently have, and what are your business drivers. >> Yep, absolutely. >> What are the big boulder items you need to do and tackle those. And so it's a process that we work together with our customers to start transforming their mainframe. >> Right. >> Yeah I hear about, I'm sorry, go on Joel. >> Yeah, and a key thing on that is a lot of people look at the mainframe is this big monolith. >> John: Right. >> It's basically the this big thing, I don't know what to do with, I don't want to touch because if I touch it I might break it. I don't have people to fix it. And so there's a lot of concern around that, but one of the things like Steve said is how Accenture and AWS work together is figuring out how do I take that monolith, divide it into smaller pieces either through data augmentation, through an analysis, and figure out a roadmap through that application or that monolithic applications and figure out how to move. >> Well that's, how you get an elephant, right? Leverage is one part at a time. >> Exactly, one part at a time. >> It's just one. >> Right, it's just leverage AI, leverage or AI and our platforms and machine learning. All these things are available and you can coexist with that. >> All right, so tell me about technical debt. I read about technical debt and you know, it kind of comes with the territory, >> Right. >> in terms of mainframe. So how do you, first off, you know, how do you define that and then how do you deal with that? How do you make that go away as far as concerns go? >> Well, you know, you have to look at your, for my definition for technical debts is the same thing when my wife says I have to do something in the backyard and I push it, I'll do it next time. Right? So it starts piling up, right? There's a lot of to-dos at the house. >> Absolutely. >> Right, it's the same thing, it's the IT to-dos that you just put off. >> I'll catch up to that some other time. >> Yep. >> And there you are, they keep on... And so next thing you know, you have this, oh my gosh I got all this work I got to do. >> Right. And that's part of the technical debt. And then so you got to look at how does that resolving that meet my needs for the cloud. So leveraging the cloud, if you're under mainframe you have limited solutions for addressing your technical debt. Leveraging the cloud with the mainframe, now you have multiple options for you. to tackle and eliminate your technical debt. So that's one of the benefits of leveraging the cloud for that. >> And I would add on to what Steve said about technical debt. It's exactly that, it's I haven't done that yet, but one of the things that I've seen is there's multiple ways to solve any problem, any programming problem technical problem from that, there's a shortcut way to get it done quickly, >> John: Right. >> that may not be clean and scalable and that. And what happens is, especially on the mainframe over 40 or 50 years, a lot of those shortcuts have been taken. And so it's not even as easy as, it's basically, you think about it, I didn't do it but now my grass is this high, >> John: Right. >> And now I got to do it, type of thing. So it's really about... >> And you can't use a lawnmower >> You can't use a lawnmower so you have to figure out different ways. >> You can't bag it, >> No, no. >> No, no, a whole nother >> Absolutely. >> Right. >> So understanding technical debt and overcoming it is realizing that those shortcuts need to be re-architected, redesigned, modernized, >> All right. >> from that perspective. And you need to take that perspective on. >> So you guys have to be kind of sometimes the bearer of bad news in a way, right? Because they have these, you said monolithic of systems in place that need revised they got to be modernized. >> Yep. >> And they've been kicking that can down the road. We've talked about some big companies for a long time. So they got a lot of baggage on that side and they have to get up to speed. So if, if you were talking to a prospective client, about understanding why it's time to start doing that necessary housekeeping, how do you convince people that this is the time? >> What are your top three absolutely mission critical applications that you have today, right? What is the staff that maintains it? What is the average age of those resources? And what is your succession strategy? >> Joel: Yep. >> It's as simple as that. >> Oh. >> I would add on to that. A lot of times we don't have to convince the customer right now. >> John: Right. >> The customers are coming to us, because what's happened is this whole digital transformation that's happening in the web and all that kind of stuff. Their competitors are already moving off of that. Or have come up with something else. So the business is coming and saying, why can't I move that fast? >> Right. >> And then, like Steve said is those are the reasons why you can't move that fast. So let's address those reasons. >> All right, the born of the cloud company is coming in, but also another driving force that's happening, If you look at a lot of our new customers. Are the digital natives arriving in the C-suites. So the folks that have always known the internet understand the benefits of the cloud, or where there's a new CIO, new CEO. >> Yep. >> And so we're seeing that changing of the guard type scenario. >> Because a lot of those people grew up with a mainframe. >> Right. Right. >> And of the old guard. >> Sure. >> And they're like, well it's worked for the last 30 years, why don't I just keep it working the same way it is. >> And don't we need it to work? >> Yeah >> Right? The way it has been? >> Yeah, exactly. >> Yeah. >> Well, and that's the other key thing, is the core applications. So what has happened with the cloud is over the last you know, 10, 15 years is a lot of the applications that could move moved. Now we're left with the core applications on the mainframe and those are the ones that a multi-billion dollar company, if they get that wrong, they're out business. So there's a lot of scrutiny and a lot of other things. So a lot of the stuff that we're doing now is to help understand that risk and get over that risk. >> And do companies have the expertise in house, to do this? And where do you find it outside? Because it, you know, might not be the sexiest thing to do. >> That's a great question because, you know Steve and I talk about this all the time which is running the mainframe is different than modernizing the mainframe. >> Steve: Right. And so I might have a lot of skills in house to run the mainframe, but how do I figure out to get, to break up that monolith into pieces. >> Steve: Right. How do I figure out, you know, how the best way to put that on AWS? How do I figure that out? You need to leverage people like AWS and Accenture and others to be able to do that. >> This is, there's a psychology to this and more technical, there's more psychological than technical. So you got to find your unicorns. People should have gas in the tank that want to adopt. >> Joel: Yep, absolutely. >> And the ones that don't, then, you know, they're out. You know, nothing like passive aggressive people showing up to help, to really cause havoc. (all laugh) And that's really what you got to kind of focus on. >> Yes. We see that a lot. >> Right. Right. But that's where the managing service comes in too right? >> Absolutely. >> You can get people there. You can, this is a worry they can check the box and move on and get help in that. >> Yeah. AWS, this is an industry first, where you have a managed service within your console to provision tooling to analyze, develop for the mainframe or deploy onto AWS. But the running of it, specific servers that have been you know, optimized for mainframe workloads with your monitoring and security and all those things it's an industry first. I've been in this business 30 years it's fantastic with what I'm seeing over here. >> And do you have any kind of a guess about what share is still out there to be had, in terms of modernizing mainframes, in terms of businesses? I mean, are there still, well, you know it might be hard to put a, to quantify it with a number, but there's still a lot of folks... >> Oh yeah. >> who haven't made that commitment yet. >> Well, they're beginning to, so if you look at, I think, I'm going to throw a number out, I think it's like 80% of the Fortune 100 companies have mainframes. >> Absolutely. >> Is that right? >> So yeah, if you paid your mortgage today, if you used your cell phone today, if you've done any of those things, core stuff is run on mainframe. >> Financial transactions are huge. >> Oh huge, huge, you've got airlines, manufacturing, >> Insurance. >> healthcare. >> John: Right. >> Pretty much everything runs on a mainframe, if you go deep enough in the organization. >> And so that's all, you know people are making those decisions. And what we've done is what I call an earn trust moment. You know, AWS standing up and saying, 'hey we're here to help our customers to move' we're a large organization, we're doing heavy investments in this. We have R&Dand staff, to help our customers transform with or to AWS. >> And we're seeing that resonated in the marketplace. So last year AWS announced the mainframe modernization service Over the last year, we've seen clients, like I said is they're coming to us now. >> Right. >> Saying we want to go mainframe zero, for lack of a better expression. And so we're just seeing a lot of activity. So what AWS did last year has really resonated within the marketplace and changed that dynamic. >> Well, the mainframe ain't dead yet. >> No. >> It isn't. >> It's not going to die. I think there's going to be a different >> Too big, two powerful and too necessary. >> Absolutely. >> Yeah I think we're going to coexist with it and some will leave, so. >> But you still need that same functionality, just somewhere else. >> All right. >> That's right. Well, appreciate the conversation, neighbor. >> Thank you. (all laugh) >> And have a great show. Look forward to seeing you down the road here. >> Thank you very much. >> Thanks John, appreciate it. >> Thanks for joining us here. You are watching theCUBE here at Reinvent 22. And theCUBE, as I remind you is the leader in high tech coverage. (soothing music)

(bright upbeat music) >> Well, hello everybody. John Walls is here on "the CUBE". Great to have you with us as we continue our series here at the AWS Executive Summit sponsored by Accenture. And today we're talking about public service and not just a little slice of public service but probably the largest public sector offering in the UK and for with us or with us. Now to talk about that is Lianne Anderton, who is in with the Intelligent Automation Garage Delivery Lead at the UK Department of Work and Pension. Lianne, good to see you today. Thanks for joining us here on "the CUBE". >> Hi, thanks for having me. >> And also with this us is Amar Narayan, who is a Manager Director at Accenture the AWS Business Group for the Lead in Health and Public Sector, also UK and Ireland. And Amar, I think, you and Lianne, are in the same location, Newcastle, I believe in the UK, is that right? >> Yeah, absolutely. Yep, yeah, we're, here in the northeast of UK. >> Well, thank you for being with us. I appreciate the time. Lianne, let's talk about what you do, the Department of Work and Pension, the famous DWP in England. You have influence or certainly touchpoints with a huge amount of the British population. In what respects, what are you doing for the working class in England and what does technology have to do with all that? >> Sure, so for the Department for Work and Pensions I think the pensions bit is fairly self explanatory so anybody who is over state pension age within the UK. for the work part of that we also deal with people of working age. So, these are people who are either in employment and need additional help through various benefits we offer in the UK. Those people who are out of work. And we also deal with health related benefits as well. And we are currently serving over 20 million claimants every year at this moment in time. So, we're aware of a huge part of the UK government. >> All right, so say that number again. How many? >> 20 million claimants every year. >> Million with an M, right? >> Yeah. >> So, and that's individuals. And so how many transactions, if you will, how many do you think you process in a month? How, much traffic basically, are you seeing? >> An extraordinary amount? I'm not even, I don't think I even know that number. (Lianne laughing) >> Mind blowing, right? So, it's- >> A huge, huge amount. >> Mind blowing. >> Yeah, so, basically the we kind of keep the country going. So, you know, if the department for Work and Pensions kind of didn't exist anymore then actually it would cause an infinite number of problems in society. We, kind of help and support the people who need that. And, yeah, so we play a really vital role in kind of you know, social care and kind of public service. >> So, what was your journey to Accenture then? What, eventually led you to them? What problem were you having and how have you collaborated to solve that? >> So, in terms of how we work with Accenture. So, we had in around 2017 DWP was looking at a projected number of transactions growing by about 210 million which was, you know, an extraordinary amount. And, you know, I think as we've kind of covered everything that we do is on a massive scale. So, we as DWP as an organization we had absolutely no idea how we were going to be able to handle such a massive increase in the transactions. And actually, you know, after kind of various kind of paths and ideas of how we were going to do that, automation, was actually the answer. But the problem that we have with that is that we have, like many governments around the world, we have really older legacy systems. So, each of these benefits that we deal with are on legacy systems. So, whatever we were going to develop had to, you know, connect to all of these, it had to ingest and then process all of these pieces of data some of which, you know, given the fact that a lot of these systems have a lot of manual input you have data issues there that you have to solve and whatever we did, you know, as we've talked about in terms of volumes has to scale instantly as well. So, it has to be able to scale up and down to meet demand and, you know, and that down scaling is also equally as important. So yeah, you've got to be able to scale up to meet the volumes but also you've got to be able to downscale when when it's not needed. But we had nothing that was like that kind of helped us to meet that demand. So, we built our own automation platform, The Intelligent Automation Garage and we did that with Accenture. >> So Amar, I'd like you to chime in here then. So, you're looking at this client who has this massive footprint and obviously vital services, right? So, that's paramount that you have to keep that in mind and the legacy systems that Lianne was just talking about. So, now you're trying to get 'em in the next gen but also respecting that they have a serious investment already in a lot of technology. How do you approach that kind of problem solving, those dynamics and how in this case did you get them to automation as the solution? >> Sure, so I think I think one of the interesting things, yeah as Lianne has sort of described it, right? It's effectively like, you know the department has to have be running all of the time, right? They can't, you know, they can't effectively stop and then do a bunch of IT transformation, you know it's effectively like, you know, changing the wheels of a jumbo jet whilst it's taking off, right? And you've got to do all of that all in one go. But what I think we really, really liked about the situation that we were in and the client relationship we had was that we knew we had to it wasn't just a technology play, we couldn't just go, "All right, let's just put some new technology in." What we also needed to do was really sort of create a culture, an innovation culture, and go, "Well how do we think about the problems that we currently have and how do we think about solving them differently and in collaboration, right?" So, not just the, "Let's just outsource a bunch of technology for to, you know, to Accenture and build a bunch of stuff." So, we very carefully thought about, well actually, the unique situation that they're in the demands that the citizens have on the services that the department provide. And as Lianne mentioned, that technology didn't exist. So, we fundamentally looked at this in a different way. So, we worked really closely with the department. We said, Look, actually what we ultimately need is the equivalent of a virtual workforce. Something where if you already, you know all of a sudden had a hundred thousand pension claims that needed to be processed in a week that you could click your fingers and, you know in a physical world you'd have another building all of your kits, a whole bunch of trained staff that would be able to process that work. And if in the following week you didn't need that you no longer needed that building that stuff or the machinery. And we wanted to replicate that in the virtual world. So, we started designing a platform we utilized and focused on using AWS because it had the scalability. And we thought about, how were we going to connect something as new as AWS to all of these legacy systems. How are we going to make that work in the modern world? How are we going to integrate it? How we going to make sure it's secure? And frankly, we're really honest with the client we said, "Look, this hasn't been done before. Like, nowhere in Accenture has done it. No one's done it in the industry. We've got some smart people, I think we can do it." And, we've prototyped and we've built and we were able to prove that we can do that. And that in itself just created an environment of solving tricky problems and being innovative but most importantly not doing sort of proof of concepts that didn't go anywhere but building something that actually scaled. And I think that was really the real the start of what was has been the Garage. >> So, And Lianne, you mentioned this and you just referred to it Amar, about The Garage, right? The Intelligent Automation Garage. What exactly is it? I mean, we talked about it, what the needs are all this and that, but Lianne, I'll let you jump in first and Amar, certainly compliment her remarks, but what is the IAG, what's the... >> So, you know, I think exactly what kind of Amar, has said from a from a kind of a development point of view I think it started off, you know, really, really small. And the idea is that this is DWP, intelligent automation center of excellence. So, you know, it's aims are that, you know, it makes sure that it scopes out kind of the problems that DWP are are facing properly. So, we really understand what the crux of the problem is. In large organizations It's very easy, I think to think you understand what the problem is where actually, you know, it is really about kind of delving into what that is. And actually we have a dedicated design team that really kind of get under the bonnet of what these issues really are. It then kind of architects what the solutions need to look like using as Amar said, all the exciting new technology that we kind of have available to us. That kind of sensible solution as to what that should look like. We then build that sensible solution and we then, you know as part of that, we make sure that it scales to demand. So, something that might start out with, I dunno, you know a few hundred claimants or kind of cases going through it can quite often, you know, once that's that's been successful scale really, really quickly because as you know, we have 20 million claimants that come through us every year. So, these types of things can grow and expand but also a really key function of what we do is that we have a fully supported in-house service as well. So, all of those automations that we build are then maintained and you know, so any changes that kind of needed to be need to be made to them, we have all that and we have that control and we have our kind of arms wrapped around all of those. But also what that allows us to do is it allows us to be very kind of self-sufficient in making sure that we are as sufficient, sorry, as efficient as possible. And what I mean by that is looking at, you know as new technologies come around and they can allow us to do things more effectively. So, it allows us to kind of almost do that that kind of continuous improvement ourselves. So, that's a huge part of what we do as well. And you know, I think from a size point of view I said this started off really small as in the idea was this was a kind of center of excellence but actually as automation, I think as Amar alluded to is kind of really started to embed in DWP culture what we've started to kind of see is the a massive expansion in the types of of work that people want us to do and the volume of work that we are doing. So, I think we're currently running at around around a hundred people at the moment and I think, you know we started off with a scrum, a couple of scrum teams under Amar, so yeah, it's really grown. But you know, I think this is here to stay within DWP. >> Yeah, well when we talk about automation, you know virtual and robotics and all this I like to kind of keep the human element in mind here too. And Amar, maybe you can touch on that in certain terms of the human factors in this equation. 'Cause people think about, you know, robots it means different things to different people. In your mind, how does automation intersect with the human element here and in terms of the kinds of things Lianne wants to do down the road, you know, is a road for people basically? >> Oh yeah, absolutely. I think fundamentally what the department does is support people and therefore the solutions that we designed and built had to factor that in mind right? We were trying to best support and provide the best service we possibly can. And not only do we need to support the citizens that it supports. The department itself is a big organization, right? We're up to, we're talking between sort of 70 and 80,000 employees. So, how do we embed automation but also make the lives of the, of the DWP agents better as well? And that's what we thought about. So we said, "Well look, we think we can design solutions that do both." So, a lot of our automations go through a design process and we work closely with our operations team and we go, well actually, you know in processing and benefit, there are some aspects of that processing that benefit that are copy and paste, right? It doesn't require much thought around it, but it just requires capturing data and there's elements of that solution or that process that requires actual thought and understanding and really empathy around going, "Well how do I best support this citizen?" And what we tended to do is we took all of the things that were sort of laborious and took a lot of time and would slow down the overall process and we automated those and then we really focused on making sure that the elements that required the human, the human input was made as user friendly and centric as we possibly could. So, if there's a really complex case that needs to be processed, we were able to present the information in a really digestible and understandable way for the agents so that they could make a informed and sensible decision based around a citizen. And what that enabled us to do is essentially meet the demands of the volumes and the peaks that came in but also maintain the quality and if not improve, you know the accuracy of the claims processing that we had. >> So, how do you know, and maybe Lianne, you can address this. How do you know that it's successful on both sides of that equation? And, 'cause Amar raised a very good point. You have 70 to 80,000 employees that you're trying to make their work life much more efficient, much simpler and hopefully make them better at their jobs at the end of the day. But you're also taking care of 20 million clients on the, your side too. So, how do you, what's your measurement for success and what kind of like raw feedback do you get that says, "Okay, this has worked for both of our client bases, both our citizens and our employees?" >> Yeah, so we can look at this both from a a quantitative and a qualitative point of view as well. So, I think from a let take the kind figures first. So we are really hot on making sure that whatever automations we put in place we are there to measure how that automation is working what it's kind of doing and the impact that it's having from an operational point of view. So I think, you know, I think the proof of the fact that the Intelligent Automation Garage is working is that, you know, in the, in its lifetime, we've processed over 20 million items and cases so far. We have 65 scaled and transitioned automations and we've saved over 2 million operational hours. I was going to say that again that's 2 million operational hours. And what that allows us to do as an organization those 2 million hours have allowed us to rather than people as Amar, said, cutting and pasting and doing work that that is essentially very time consuming and repetitive. That 2 million hours we've been able to use on actual decision making. So, the stuff that you need as sentient human being to make judgment calls on and you know and kind of make those decisions that's what it's allowed us as an organization to do. And then I think from a quality point of view I think the feedback that we have from our operational teams is, you know is equally as as great. So, we have that kind of feedback from, you know all the way up from to the director level about, you know how it's kind of like I said that freeing up that time but actually making the operational, you know they don't have an easy job and it's making that an awful lot easier on a day to day basis. It has a real day to day impact. But also, you know, there are other things that kind of the knock on effects in terms of accuracy. So for example, robot will do is exactly as it's told it doesn't make any mistakes, it doesn't have sick days, you know, it does what it says on the tin and actually that kind of impact. So, it's not necessarily, you know, counting your numbers it's the fact that then doesn't generate a call from a customer that kind of says, "Well you, I think you've got this wrong." So, it's all that kind of, these kind of ripple effects that go out. I think is how we measure the fact that A, the garage is working and b, it's delivering the value that we needed to deliver. >> Robots, probably ask better questions too so yeah... (Lianne laughing) So, real quick, just real quick before you head out. So, the big challenge next, eureka, this works, right? Amar, you put together this fantastic system it's in great practice at the DWP, now what do we do? So, it's just in 30 seconds, Amar, maybe if you can look at, be the headlights down the road here for DWP and say, "This is where I think we can jump to next." >> Yeah, so I think, what we've been able to prove as I say is that is scaled innovation and having the return and the value that it creates is here to stay, right? So, I think the next things for us are a continuous expand the stuff that we're doing. Keeping hold of that culture, right? That culture of constantly solving difficult problems and being able to innovate and scale them. So, we are now doing a lot more automations across the department, you know, across different benefits across the digital agenda. I think we're also now becoming almost a bit of the fabric of enabling some of the digital transformation that big organizations look at, right? So moving to a world where you can have a venture driven architectures and being able to sort of scale that. I also think the natural sort of expansion of the team and the type of work that we're going to do is probably also going to expand into sort of the analytics side of it and understanding and seeing how we can take the data from the cases that we're processing to overall have a smoother journey across for our citizens. But it's looking, you know, the future's looking bright. I think we've got a number of different backlogs of items to work on. >> Well, you've got a great story to tell and thank you for sharing it with us here on "the CUBE", talking about DWP, the Department of Work and Pensions in the UK and the great work that Accenture's doing to make 20 million lives plus, a lot simpler for our friends in England. You've been watching ""the CUBE"" the AWS Executive Summit sponsored by Accenture. (bright upbeat music)

>>Welcome back here on the Cube. I'm John Walls. We are in Las Vegas at the Venetian, and this is Reinvent 22 in the Executive Summit sponsored by Accenture. Glad to have you with us here as we continue our conversations. I'm joined by Paul Puckett, who's the former director of the Enterprise Cloud Management Services at the US Army. Paul, good to see you sir. Hey, you as well, John. Thank you. And Justin, she who is managing director and cloud go to market lead at Accenture Federal Services. Justin, good morning to you. Good morning, John. Yeah, glad to have you both here on the cube. First time too, I believe, right? Yes sir. Well, welcome. I wish we had some kind of baptism or indoctrination, but I'll see what I can come up with in the next 10 minutes for you. Let's talk about the Army, Paul. So enterprise cloud management, US Army. You know, I can't imagine the scale we're talking about here. I can't imagine the solutions we're talking about. I can't imagine the users we're talking about. Just for our folks at home, paint the picture a little bit of what kind of landscape it is that you have to cover with that kind of title. >>Sure. The United States Army, about 1.4 million people. Obviously a global organization responsible for protecting and defending the United States as part of our sister services in the Department of Defense. And scale often comes up a lot, right? And we talk about any capability to your solution for the United States Army scale is the, the number one thing, but oftentimes people overlook quality first. And actually when you think of the partnership between the Army and Accenture Federal, we thought a lot when it came to establishing the enterprise Cloud management agency that we wanted to deliver quality first when it came to adopting cloud computing and then scale that quality and not so much be afraid of the, the scale of the army and the size that forces us to make bad decisions. Cuz we wanted to make sure that we proved that there was opportunity and value in the cloud first, and then we wanted to truly scale that. And so no doubt, an immense challenge. The organization's been around for now three years, but I think that we've established irreversible momentum when it comes to modernization, leveraging cloud computing >>For the army. So let's back up. You kind of threw it in there, the ecma. So this agency was, was your a collaboration, right? To create from the ground up and it's in three years in existence. So let's just talk about that. What went into that thinking? What went into the planning and then how did you actually get it up and run into the extent that it is today? >>Sure. Well, it was once the enterprise cloud management office. It was a directorate within the, the CIO G six of the United States Army. So at the headquarters, the army, the chief information Officer, and the G six, which is essentially the military arm for all IT capability were once a joint's organization and the ECMO was created to catalyze the adoption of cloud computing. The army had actually been on a, a cloud adoption journey for many years, but there wasn't a lot of value that was actually derived. And so they created the ecma, well, the ECMO at the time brought me in as the director. And so we were responsible for establishing the new strategy for the adoption of cloud. One of the components of that strategy was essentially we needed an opportunity to be able to buy cloud services at scale. And this was part of our buy secure and build model that we had in place. And so part of the buy piece, we put an acquisition strategy together around how we wanted to buy cloud at scale. We called it the cloud account management optimization. OTA >>Just rolls right off the >>Tongue, it just rolls right off the tongue. And for those that love acronyms, camo, >>Which I liked it when I was say cama, I loved that. That was, that was, >>You always have to have like a tundra, a little >>Piece of that. Very good. It was good. >>But at the time it was novetta, no, Nevada's been bought up by afs, but Novea won that agreement. And so we've had this partnership in place now for just about a year and a half for buying cloud computing net scale. >>So let's talk about, about what you deal with on, on the federal services side here, Justin, in terms of the army. So obviously governance, a major issue, compliance, a major issue, security, you know, paramount importance and all that STEM leads up to quality that Paul was talking about. So when you were looking at this and keeping all those factors in, in your mind, right? I mean, how many, like, oh my God, what kind of days did you have? Oh, well, because this was a handful. >>Well, it was, but you could see when we were responding to the acquisition that it was really, you know, forward thinking and forward leaning in terms of how they thought about cloud acquisition and cloud governance and cloud management. And it's really kind of a sleepy area like cloud account acquisition. Everyone's like, oh, it's easy to get in the cloud, you know, run your credit card on Amazon and you're in, in 30 seconds or less. That's really not the case inside the federal government, whether it's the army, the Air Force or whoever, right? Those, those are, they're real challenges in procuring and acquiring cloud. And so it was clear from, you know, Paul's office that they understood those challenges and we were excited to really meet them with them. >>And, and how, I guess from an institutional perspective, before this was right, I I assume very protective, very tight cloistered, right? You, you, in terms of being open to or, or a more open environment, there might have been some pushback was they're not. Right? So dealing with that, what did you find that to be the case? Well, so >>There's kind of a few pieces to unpacking that. There's a lot of fear in trepidation around something you don't understand, right? And so part of it is the teaching and training and the, and the capability and the opportunity in the cloud and the ability to be exceptionally secure when it comes to no doubt, the sensitivity of the information of the Department of Defense, but also from an action acquisition strategy perspective, more from a financial perspective, the DOD is accustomed to buying hardware. We make these big bets of these big things to, to live in today's centers. And so when we talk about consuming cloud as a utility, there's a lot of fear there as well, because they don't really understand how to kind of pay for something by the drink, if you will, because it incentivizes them to be more efficient with their utilization of resources. >>But when you look at the budgeting process of the d od, there really is not that much of incentive for efficiency. The p PPE process, the planning program, budgeting, execution, they care about execution, which is spending money and you can spend a lot of money in the cloud, right? But how are you actually utilizing that? And so what we wanted to do is create that feedback loop and so the utilization is actually fed into our financial systems that help us then estimate into the future. And that's the capability that we partnered with AFS on is establishing the closing of that feedback loop. So now we can actually optimize our utilization of the cloud. And that's actually driving better incentives in the PPE >>Process. You know, when you think about these keywords here, modernized, digitized, data driven, so on, so forth, I, I don't think a lot of people might connect that to the US government in general just because of, you know, it's a large intentionally slow moving bureaucratic machine, right? Is that fair to characterize it that way? It >>Is, but not in this case. Right? So what we done, >>You you totally juxtapose that. Yeah. >>Yeah. So what we've done is we've really enabled data driven decision making as it relates to cloud accounts and cloud governance. And so we have a, a tool called Cloud Tracker. We deployed for the army at a number of different classifications, and you get a full 360 view of all of your cloud utilization and cloud spend, you know, really up to date within 24 hours of it occurring, right? And there a lot of folks, you know, they didn't never went into the console, they never looked at what they were spending in cloud previously. And so now you just go to a simple web portal and see the entire entirety of the army cloud spend right there at your fingertips. So that really enables like better decision making in terms of like purchasing savings plans and reserved instances and other sorts of AWS specific tools to help you save money. >>So Paul, tell me about Cloud Tracker then. Yeah, I mean from the client side then, can you just say this dashboard lays it out for you right? In great detail about what kind of usage, what kind of efficiencies I assume Yeah. What's working, what's not? >>Absolutely. Well, and, and I think a few things to unpack that's really important here is listen, any cloud service provider has a concept. You can see what you're actually spending. But when it comes to money in the United States government, there are different colors of money. There's regulations when it comes to how money is identified for different capabilities or incentives. And you've gotta be very explicit in how you track and how you spend that money from an auditability perspective. Beyond that, there is a move when it comes to the technology business management, which is the actual labeling of what we actually spend money on for different services or labor or software. And what Cloud Tracker allows us to do is speak the language of the different colors of money. It allows us to also get very fine grain in the actual analysis of, from a TBM perspective, what we're spending on. >>But then also it has real time hooks into our financial systems for execution. And so what that really does for us is it allows us to complete the picture, not just be able to see our spend in the cloud, but also be able to able to see that spending context of all things in the P P P E process as well as the execution process that then really empowers the government to make better investments. And all we're seeing is either cost avoidance or cost savings simply because we're able to close that loop, like I said. Yep. And then we're able to redirect those funds, retag them, remove them through our actual financial office within the headquarters of the army, and be able to repurpose that to other modernization efforts that Congress is essentially asking us to invest >>In. Right. So you know how much money you have, basically. Exactly. Right. You know how much you've already spent, you know how you're spending it, and now you how much you have left, >>You can provide a reliable forecast for your spend. >>Right. You know, hey, we're, we're halfway through this quarter, we're halfway through the, the fiscal year, whatever the case might be. >>Exactly. And the focus on expenditures, you know, the government rates you on, you know, how much have you spent, right? So you have a clear total transparency into what you're going to spend through the rest of the fiscal. Sure. >>All right. Let's just talk about the relationship quickly then about going forward then in terms of federal services and then what on, on the, the US Army side. I mean, what now you've laid this great groundwork, right? You have a really solid foundation where now what next? >>We wanna be all things cloud to the army. I mean, we think there's tremendous opportunity to really aid the modernization efforts and governance across the holistic part of the army. So, you know, we just, we want to, we wanna do it all with the Army as much as we can. It's, it's, it's a fantastic >>Opportunity. Yeah. AFS is, is in a very kind of a strategic role. So as part of the ecma, we own the greater strategy and execution for adoption of cloud on behalf of the entire army. Now, when it comes to delivery of individual capabilities for mission here and there, that's all specific to system owners and different organizations. AFS plays a different role in this instance where they're able to more facilitate the greater strategy on the financial side of the house. And what we've done is we've proven the ability to adopt cloud as a utility rather than this fixed thing, kind of predict the future, spend a whole bunch of money and never use the resource. We're seeing the efficiency for the actual utilization of cloud as a utility. This actually came out as one of the previous NDAs. And so how we actually address nda, I believe it was 2018 in the adoption of cloud as a utility, really is now cornerstone of modernization across all of the do d and really feeds into the Jo Warfighting cloud capability, major acquisition on behalf of all of the D O D to establish buying cloud as just a common service for everyone. >>And so we've been fortunate to inform that team of some of our lessons learned, but when it comes to the partnership, we just see camo moving into production. We've been live for now a year and a half. And so there's another two and a half years of runway there. And then AFS also plays a strategic role at part of our cloud enablement division, which is essentially back to that teaching part, helping the Army understand the opportunity of cloud computing, align the architectures to actually leverage those resources and then deliver capabilities that save soldier's >>Lives. Well, you know, we've, we've always known that the Army does its best work on the ground, and you've done all this groundwork for the military, so I'm not surprised, right? It's, it's a winning formula. Thanks to both of you for being with us here in the executive summit. Great conversation. Awesome. Thanks for having us. A good deal. All right. Thank you. All right. You are watching the executive summit sponsored by Accenture here at Reinvent 22, and you're catching it all on the cube, the leader in high tech coverage.

well you're watching the cube and I knew that you knew that I'm John Walls we're here in Las Vegas it's re invent 22. Big Show AWS putting it on the Big Show here late in 2022 that's going really well we're at the executive Summit right now sponsored by Accenture and we're going to talk about that relationship between Accenture and AWS um kind of where it is now and where it's going you know even bigger things down the road to help us do that two guests Andy Tay who's a senior managing director and the Accenture AWS business group lead at Accenture Andy thanks for being with us thanks for having me and Sarah whose last name was one of my all-time favorites all good because it is it's all good right okay it's all good Sarah all good worldwide leader of accenture's AWS business group for AWS and thank you both again for being here so let's talk about the relationship just in general high level here 30 000 feet a lot of great things have been happening we know a lot of great things are happening but how's this all you think evolved how did how has this come about that you two are just inextricably linked almost here in the cloud space Sarah why don't you jump on that yeah I'd love to um I think one of the the strongest factors that causes that Synergy for us is we both work backwards from our customer outcomes and so just by consistently doing that taking those customer signals um really obsessing over our customers success we know what we're marching towards and so then we kind of extract those themes and really work together to think about okay when we look at this holistically how do we go bigger better faster together and accomplish and solve those customer problems yeah Andy yeah John let me just maybe add and you know to amplify you know what Sarah just touched on um we both have common to our culture this notion of working from the client's perspective first so really delivering to the clients values or um you know in aws's parlance it's you know customer and so that's at the core and when we keep that at the core everything else becomes really easy where we invest what we build key clients we focus on what our team structure is et cetera Etc that's really easy so that sort of core core pillar number one in terms of our sort of you know success factors the second thing that I think really helps us is our sort of scale geographically you know certainly from an Accenture standpoint as you know John we're north of 800 000 people globally um couple that with aws's strength we really do have you know a field depth and breadth across the board that allows us to sort of see and feel what's happening in the market and allows us really to see around the corners as we like to think and say um and and that helps us be intentional on what we do um and then the third thing is really us we might know what we do but we sort of need to then play to our strengths and as you know we're two very different companies one focus on the technology side the other you know focus on the technology Services although we'll touch on you know some of the changes we're looking at as we go forward but that sort of playing to strength is key as well for us as a third pillar of success and so keeping those three things at the core really helps us move you know day to day and year by year and that's what you see in this continued partnership so what are you hearing from your customers these days we've talked a lot already today and it's kind of the buzzword you know modernization right everybody's talking about this transformation I don't care if you're in Mainframe or where you are everybody wants a modernized right now um you know what are you hearing from customers in that regard and I'm sure everybody's in a different state different yeah frame of mind you know some are embracing some are dragging uh what what's your take on the state of play right now well and I think it's like especially in these macroeconomic moments that we're in um time to value is critical for our customers um and then we have the talent shortage but even with those our customers still need us to solve for sustainability and still focus on inclusion diversity and equity and so we can't lower the bar in anything that we've already been doing we need to just keep doing more and building with them and so I think um for us really getting to the to the meat of what our customers need modernization is a big one but we're still seeing just so many of our customers look at basic transformation right how how do I dip in how do I start to move my environment move my people and get ready for what I need to do next for my business and so that that is a challenge and like we said with with the markets as volatile as they are right now I think a lot of customers are just trying to work with us to figure out how to do that in the most optimized and efficient way I just want to kind of rub people on the head and say it's going to be all right I mean it's so volatile as you pointed out Sarah right yeah I mean the market up and down and we're worried about a recession and companies and their plans they want to be Forward Thinking yeah but they've got to you know keep their powder dry too in some respects and get ready for that rainy day you know John it's funny um because you would think you know you've got the one hand you know rub that you know it's gonna be all right and and then on the other end you'll you know maybe clients should sort of hold temper and you know sort of just pause but I think clients get it they see it they feel it they understand the need to invest and I think you know there's a recent study back in 2008 those clients you know Sarah and I were reading the other day those clients who didn't invest ahead of those you know major if you remember those macroeconomic downturn times they came out really on the bad side um and so clients now are realizing that in these times these are the moments to invest and so they get it but they're faced with a couple of challenges one is time Sarah touched on you just don't have time and the second is Talent so we're working in a very intentional way on what we can do to help them there and and as you'll hear later on from Chris Wegman and Eric Farr um we're launching our velocity platform which really helps to compress that type and and get them faster you know time to Value we're also being very intentional on talent and how we help their talent so you know rotate so that we're not just taking the technology Journey but we're also having the people journey and then the third thing Sarah and I really focus on with our teams is figuring out new ways new sources of value for our clients and that's not just cost that's value the broader set and so we find that in moments like this it's actually an opportunity for us to really bring the best of AWS and Accenture to our clients well you hit value and I always find this one kind of tough because there is a big difference between cost and value my cost is X right whatever I write on my chat that's my cost so but but how do you help clients identify that value so that because it's you know it can be a little nebulous right can it not I mean it's uh but you have to validate you got to quantify at the end of the day because that's what the CEO wants to see it's what the CIO wants to see yeah you've got to identify values so how many how do you do that yeah yeah I mean we we have many different ways right velocity which Andy kind of touched on I think is is really um it's our foundational approach to help customers really kind of enter into their Cloud journey and focus on those key factors for Success right so we've got ISB Solutions built in there We've Got Talent and change built in we've got kind of what we're calling the fabric right that foundational technology layer and giving our customers all of that in a way that they can consume in a way that they can control and you know different modules essentially that they can leverage to move it's going to be tangible right they're going to be able to see I've now got access to all these things that I need I can move as I need to move and I'm not constantly you know looking around figuring out how to lock it all together we've given them that picture and that road map on how to really leverage this because we we need to be able to point to tangible outcomes and so that's critical yeah proof's got to be in the pudding and and you know to Sarah's point I think sort of we're entering into this sort of new dare I say new chapter of cloud and then you know sort of the first chapter was sort of those outcomes were around cost you know I've moved you into the cloud you can shut down your data center but now we've sort of got other sources of value now Beyond costs there's news new sources of revenue how do I become a platform company on top of the AWS cloud and then you know eke out new Revenue sources for myself how do I drive new experiences for my customers yeah um how do I maybe tap into the sustainability angle of things and how do I get greater Innovation from my talent how do I operate better in a Sarah said how do I become more Nimble more agile and more responsive to Market demands and so all those areas all those Dynamics all those outcomes are sources of value that were sort of really laser focused on and just ensuring that as a partnership we we help our clients on that Journey so what do you do about talent I mean you brought it up a couple of times UTP has um in terms of of training retaining recruiting all those key elements right now it's an ultra competitive environment right now yeah and there might be a little bit of a talent Gap in terms of what we're producing right so um you know how do you I guess make the most out of that and and make sure you keep the good people around yeah Talent is an interesting one John um and we were just touching on this uh before we got here um you know sort of from an Accenture standpoint um we're obviously focused on growing our AWS Talent um we've now got I think it's north of 27 000 people in Accenture with AWS certifications north of 34 000 certificates you know which is absolutely fantastic a small City it's just I mean it is very intentional in building that um as AWS rolls out new Services Adam touched on a whole bunch of them today we're at the core of that and ramping and building our talent so that we can drive and get our clients quicker to their value and then the second area of focus is what do we do to help our clients Talent how do we train them how do we enable them how do we you know get them to be more agile and you know being able to sort of operate in what we call that digital core operate in the cloud how do we do that and so we're focused um in in capabilities in fact our Accenture head of talent and people and change Christie Smith John is is here this week just for that and we're exploring ways in which we can get tighter and even more Innovative Around Talent and so I ultimately that that bleeds over to where the partnership goes right because if you can enhance that side of it then then everybody wins on that in terms of what you think you know where this is going yeah yeah it's already you know pretty good setup uh things are working pretty well but as the industry changes so rapidly and and you have to meet those needs how do you see the partnership evolving as well to meet those needs down the road we we have a very fortunate position in that our CEOs are both very engaged in this partnership and they push us think bigger go faster figure it out let's ride and there are definite pros and cons and some days I'm flying this close to the Sun but um it isn't a it's an absolute privilege to work with them the way that we get to and so we're always looking I mean Auntie said it earlier this is the relationship that helps us look around corners we've raised the bar and so we're constantly pushing each other pushing our teams just innovating together thinking it all through on where are we going and like I said reading those tea leaves reading those themes from our customers like hey we've just had five customers with the same similar feeling problem that we're trying to solve or we ran into the same issue in the field and how do we put that together and solve for it because we know it's not just five right we know they're more out there and so um I think you know it's it's leadership principles for us right at Amazon that guiding think big um you know insist on high standards that that'll always be core and Central to who we are and then you know fortunately Accenture has a really similar ethos yeah quick take on that Andy yeah I think as we look out you know I think um we're going to we've already seen but we're going to see this continued blurring of Industries um of um you know sort of clients moving into other Industries and yeah sort of this sort of agitation Market agitation um and so I think disruption you know disruption and and we're being you know focused on what do we need to be to do in order to help our clients on those Journeys and and to continue to you know get them you know faster Solutions is an area that we you know we are um really looking at and these are solutions that are either industry Solutions you'll hear a couple of them this week um you know we've got our insurance solution that we're we've developed as an intelligent underwriting capability leveraging AWS AIML to sort of be intelligent and cognitive um you know we've got other Solutions around the around Industries energy and Life Sciences but then also intelligent applications that might be touching you know areas I think earlier today Adam talked about AWS supply chain and that's an area that we are focused on and and proud to be a part of that and we're working very very closely with with Amazon on that uh to help you know our clients move ahead so I think we're going to see this continued blurring and we're going to obviously you know keep addressing that and just keep iterating well it looks like a relationship of trust and expertise right and it's worked out extremely well and uh if this is any indication where the interview went uh even better things are ahead for the partnership so thank you thank you for chiming in I appreciate your perspectives yeah thank you it's been great we continue our coverage here on thecube we're at re invent 22 we're in Las Vegas and you're watching thecube the leader in technical coverage foreign