(upbeat music) (air whooshing) >> Good afternoon, cloud nerds, and welcome back to beautiful Las Vegas, Nevada. We are at AWS re:invent day four. Afternoon of day four here on theCUBE. I'm Savannah Peterson, joined by my fabulous cohost, Paul Gillin. Paul, you look sharp today. How you doing? >> Oh, you're just as fabulous, Savannah. You always look sharp. >> I appreciate that. They pay you enough to keep me buttered up over here at- (Paul laughing) It's wonderful. >> You're holding up well. >> Yeah, thank you. I am excited about our next conversation. Two fabulous gentlemen. Please welcome Sam and Monty, welcome to the show. >> Thank you. >> And it was great. Of the PR 2%, the most interesting man alive. (Paul and Savannah laughing) >> In person. Yeah, yeah. >> In the flesh. Our favorite guests so far. So how's the show been for you guys? >> Sam: It's been phenomenal. >> Just spending a lot of time with customers and partners and AWS. It's been great. It's been great. >> It is great. It's really about the community. It feels good to be back. >> Monty: Eating good food, getting my steps in above goals. >> I feel like the balance is good. We walk enough of these convention centers that you can enjoy the libations and the delicious food that's in Las Vegas and still not go home feeling like a cow. It is awesome. It's a win-win. >> To Sam's point though, meeting with customers, meeting with other technology providers that we may be able to partner with. And most importantly, in my role especially, meeting with all of our AWS key stakeholders in the partnership. So yeah, it's been great. >> Everyone's here. It's just different having a conversation in person. Even like us right now. So just in case folks aren't familiar, tell me about Talend. >> Yeah. Well, Talend is a data integration company. We've been around for a while. We have tons of different ways to get data from point A to point B, lots of different sources, lots of different connectors, and it's all about creating accessibility to that data. And then on top of that, we also have a number of solutions around governance, data health, data quality, data observability, which I think is really taking off. And so that's kind of how we're changing the business here. >> Casual change, data and governance. I don't know if anyone's talking about that at all on the snow floor. >> Been on big topic here. We've had a lot of conversations with the customers about that. >> So governance, what new dynamics has the cloud introduced into data governance? >> Well, I think historically, customers have been able to have their data on-prem. They put it into things like data lakes. And now having the flexibility to be able to bring that data to the clouds, it opens up a lot of doors, but it also opens up a lot of risks. So if you think about the chief data officer role, where you have, okay, I want to be able to bring my data to the users. I want to be able to do that at scale, operationally. But at the same time you have a tension then between the governance and the rules that really restrict the way that you can do that. Very strong tension between those two things. >> It really is a delicate balance. And especially as people are trying to accelerate and streamline their cloud projects, a lot to consider. How do you all help them do that? Monty, let's go to you. >> Yeah, we keep saying data, data, what is it really? It's ones and zeros. In this day and age, everything we see, we touch, we do, we either use data, or we create data, and then that... >> Savannah: We are data quite literally. >> We literally are data. And so then what you end up with is all these disparate data silos and different applications with different data, and how do you bring all that together? And that's where customers really struggle. And what we do is we bring it all together, and we make it actionable for the customer. We make it very simple for them to take the data, use it for the outcomes that they're looking for in their business initiatives. >> Expand on that. What do you mean make it actionable? Do you tag it? Do you organize it in some way? What's different about your approach? >> I mean, it's a really flexible platform. And I think we're part of a broader ecosystem. Even internally, we are a data driven company. Coming into the company in April, I was able to come in and get this realtime view of like, "Hey, here's where our teams are." And it's all in front of me in a Tableau dashboard that's populated from Talend integration, bringing data out of our different systems, different systems like Workday where we're giving offers out to people. And so everything from managing headcount to where our AWS spend is, all of that stuff. >> Now, we've heard a lot of talk about data and in fact the keynote yesterday that was focused mainly on data and getting data out of silos. How do you play with AWS in that role? Because AWS has other data integration partners. >> Sam: For sure. >> What's different about your relationship? Yeah. >> Go ahead. >> Yeah, we've had a strong relationship with AWS for many years now. We've got more than 80 connectors into the different AWS services. So we're not new to the AWS game. We align with the sales teams, we align with the partner teams, and then of course, we align with all the different business units and verticals so that we can enact that co-sell motion together with AWS. >> Sam: Yeah. And I think from our product standpoint, again, just being a hyper flexible platform, being able to put, again, any different type of source of data, to any type of different destination, so things like Redshift, being able to bring data into those cloud data warehouses is really how we do that. And then I think we have between bringing data from A to B, we're also able to do that along a number of different dimensions. Whether that's just like, "Hey, we just need to do this once a day to batch, all the way down to event driven things, streaming and the like. >> That customization must be really valuable for your customers as well. So one of the big themes of the show has been cost reduction. Obviously with the economic times as we're potentially dipping our toes into as well, is just in general, always wanting to increase margins. How do you help customers cut cost? >> Well, it's cost cutting, but it's also speed to market. The faster you can get a product to market, the faster you can help your customers. Let's say healthcare life sciences, pharmaceutical companies, patient outcomes. >> Great and timely example there. >> Patient outcomes, how do they get drugs to market quicker? Well, AstraZeneca leveraged our platform along with AWS. And they even said >> Cool. >> for every dollar that they spend on data initiatives, they get $40 back. That's a billion dollars >> Wow. >> savings by getting a drug to market one month faster. >> Everybody wins. >> How do you accelerate that process? >> Well, by giving them the right data, taking all the massive data that I mentioned, siloed in everywhere, and making it so that the data scientists can take all of this data and make use of it, makes sense of it, and move their drug production along much quicker. >> Yeah. And I think there's other things too like being very flexible in the way that it's deployed. Again, I think like you have this historical story of like, it takes forever for data to get updated, to get put together. >> Savannah: I need it now. And in context. >> And I think where we're coming from is almost more of a developer focus where your jobs are able to be deployed in any way you want. If you want to containerize those, you want to scale them, you need to schedule them that way. We plug into a lot of different ecosystems. I think that's a differentiation as well. >> I want to hang out on this one just for a second 'cause it's such a great customer success story and so powerful. I mean, in VC land, if you can take a dollar and make two, they'll give you a 10x valuation, 40. That is so compelling. I mean, do you think other customers could expect that kind of savings? A billion dollars is nothing to laugh at especially when we're talking about developing a vaccine. Yeah, go for it, Sam. >> It really depends on the use case. I think what we're trying to do is being able to say, "Hey, it's not just about cost cutting, but it's about tailoring the offerings." We have other customers like major fast food vendors. They have mobile apps and when you pull up that mobile app and you're going to do a delivery, they want to be able to have a customized offering. And it's not like mass market, 20% off. It's like, they want to have a very tailored offer to that customer or to that person that's pulling open that app. And so we're able to help them architect and bring that data together so that it's immediately available and reliable to be able to give those promotions. >> We had ARP on the show yesterday. We're talking about 50 million subscribers and how they customize each one of their experiences. We all want it to be about us. We don't want that generic at... Yeah, go for it, Paul. >> Oh, okay. >> Yeah. >> Well, I don't want to break break the rhythm here, but one area where you have differentiated, about two years ago you introduced something called the trust score. >> Sam: Yeah. >> Can you explain what that is and how that has resonated with your customers? >> Yeah, let's talk about this. >> Yeah, the thing about the trust score is, how many times have you gotten a set of data? And you look at it and you say, "Where did you get this data? Something doesn't look right here." And with the trust score, what we're able to do is quantify and value the different attributes of the data. Whether it's how much this is being used. We can profile the data, and we have a trust score that runs over time where you can actually then look at each of these data sets. You can look at aggregates of data sets to then say... If you're the data engineer, you can say, "Oh my, something has gone wrong with this particular dataset." Go in, quickly pull up the data. You can see if some third party integration has polluted your data source. I mean, this happens all the time. And I think if you sort of compare this to the engineering world, you're always looking to solve those problems sooner, earlier in the chain. You don't want your consumer calling you saying, "Hey, I've got a problem with the data, or I've got a problem- >> You don't want them to know there was ever a problem in theory. >> Yeah, the trust score helps those data engineers and those people that are taking care of the data address those problems sooner. >> How much data does somebody need to be able to get to the point where they can have a trust score? If you know what I'm trying to say. How do we train that? >> I mean, it can be all the way from just like a single data source that's getting updated, all the way to very large complex ones. That's where we've introduced this hierarchy of data sets. So it's not just like, "Hey, you've got a billion data sources here and here are the trust scores." But it's like, you can actually architect this to say like, "Okay, well, I have these data sets that belong to finance." And then finance will actually get, "Here's the trust score for these data sets that they rely on." >> What causes datasets to become untrustworthy? >> Yeah. Yeah. I mean, it happens all the time. >> A of different things, right? >> In my history, in the different companies that I've been at, on the product side, we have seen different integrations that maybe somebody changes something. In upstream, some of those integrations can actually be quite brittle. And as a consumer of that data, it's not necessarily your fault, but that data ends up getting put into your production database. All of a sudden your data engineering team is spending two days unwinding those transactions, fixing the data that's in there. And all the while, that bad data that's in your production system, is causing a problem for somebody that is ultimately relying on that. >> Is that usually a governance problem? >> I think governance is probably a separate set of constraints. This is sort of the tension between wanting to get all of the data available to your consumers versus wanting to have the quality around it as well. >> It's tough balance. And I think that it's really interesting. Everybody wants great data, and you could be making decisions that affect people's wellness, quite frankly. >> For sure. >> Very dramatically if you're ill-informed. So that's very exciting. >> To your point, we are all data. So if the data is bad, we're not going to get the outcomes that we want ultimately, >> I know. We certainly want the best outcomes for ourselves. >> We track that data health for its entire life cycle throughout the process. >> That's cool. And that probably increases your confidence in the trust score as well 'cause you're looking at so much data all the time. You got a smart thing going on over here. I like it. I like it a lot. >> We believe in it and so does AWS because they are a strong partner of ours, and so do customers. I think we mentioned we've had some phenomenal customer conversations along with- >> What a success story and case study. I want to dust your shoulders off right now if I wasn't tethered in. That's super impressive. So what's next for you all? >> Yeah, so I think we're going to continue down this path of data health and data governance. Again, I kind of talked about the... you're talking about data health being this differentiator on top of just moving the data around and being really good at that. I think you're also going to have different things around country level or state level governance, literal laws that you need to comply with. And so like- >> Savannah: CCPA- >> I mean, a long list- >> Oodles. Yeah. Yeah, yeah, yeah. >> I think we're going to be doing some interesting things there. We are continuing to proliferate the sources of data that we connect to. We're always looking for the latest and greatest things to put the data into. I think you're going to see some interesting things come out of that too. >> And we continue to grow our relationship with AWS, our already strong relationship. So you can procure Talend products to the AWS marketplace. We just announced Redshift serverless support for Talend. >> All their age. >> Which sounds amazing, but because we've been doing this for so long with AWS, dirty little secret, that was easy for us to do because we're already doing all this stuff. So we made the announcement and everyone was like, "Congratulations." Like, "Thanks." >> Look at you all. Full of the humble brags. I love it. >> Talend has gone through some twists and turns over the last couple of years. Company went private, was purchased by Thoma Bravo about a year and a half ago. At that time, your CEO said that it was a chance to really refocus the company on some core strategic initiatives and move forward. Both of you joined obviously after that happened. But what did you see about sort of the new Talend that attracted you, made you want to come over here? >> For sure. Yeah. I think, when I got a chance to talk to the board and talk to Chris, our chair, we talked about there being the growth thesis behind it. So I think Thoma been a great partner to Talend. I think we're able to do some things internally that would be I think, fairly challenging for companies that are in the public markets right now. I think especially, just a lot of pressure on different prices and the cost capital and all of that. >> Right now. >> That was a really casual way of stating that. But yeah, just a little pressure. >> Little bit of pressure. And who knows? Who knows how long that's going to last, right? But I think we've got a great board in place. They've been very strong strategic partner for us talking about all the different ways that we can grow. I think it's been a good partner for us- >> One of the strengths of Thoma's strategy is synergy between the companies they've acquired. >> Oh, for sure. >> They've acquired about 40 software companies. Are you seeing synergy? You talk to those other companies a lot? >> Yeah, so I have an operating partner. I talk with him on a weekly, sometimes daily basis. If we have questions or like, "Hey, what are you seeing in this space?" We can get plugged in to advisors very quickly. I think it's been a very helpful thing where... otherwise, you're relying on your personal network or things like that. >> This is why Monty was saying it was easy for you guys to go serverless. >> And we keep talking about trust, but in this case, Thoma Bravo really trusts our senior leadership team to make the right decisions that Sam and I are here making as we move forward. It's a great relationship. >> Sam: A good team. >> It sounds like it. All the love. I can feel the love even from you guys talking about it, it's genuine. You're not just getting paid to show this. That's fantastic. >> Are we getting paid for this or... >> Yeah. (Savannah giggling) (Paul laughing) I mean, some folks in the audience are probably going to want your autograph after this, although you get that a lot- >> Pictures are available after- >> Yeah, selfies are 10 bucks. That's how I get my boos budget. So last question for you. We have a challenge here on the theCUBE re:invent. We're looking for your 32nd hot take. Think of it as your thought leadership sizzle reel. Biggest takeaway, key themes from the show or looking forward into 2023? Sam, you're ready to rock, go. >> Yeah, totally. >> I think you're going to continue to hear the tension between being able to bring the data to the masses versus the simplicity and being able to do that in a way that is compliant with all the different laws, and then clean data. It's like a lot of different challenges that arise when you do this at scale. And so I think if you look at the things that AWS is announcing, I think you look at any sort of vendor in the data space are announcing, you see them sort of coming around to that set of ideas. Gives me a lot of confidence in the direction that we're going that we're doing the right stuff and we're meeting customers and prospects and partners, and everybody is like... We kind of get into this conversation and I'll say, "Yeah, that's it. We want to get involved in that." >> You can really feel the momentum. Yeah, it's true. It's great. What about you, Monty? >> I mean, I don't need 30 seconds. I mentioned it. >> Great. >> Between Talend and AWS, we're aligned from the sales teams to the product teams, the partner teams and the alliances. We're just moving forward and growing this relationship. >> I love it. That was perfect. And on that note, Sam, Monty, thank you so much for joining us. >> Yeah, thanks for having us. >> I'm sure your careers are going to continue to be rad at Talend and I can't wait to continue the conversation. >> Sam: Yeah, it's a great team. >> Yeah, clearly. I mean, look at you two. If you're any representation of the culture over there, they're doing something great. (Monty laughing) I thank all of you for tuning in to our nearly... Well, shoot. I think now over 100 interviews at AWS Reinvent in Sin City. We are hanging out here. Paul and I've got a couple more for you. So we hope to see you tuning in with Paul Gillin. I'm Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (upbeat music)

(upbeat music) >> Hello, brilliant cloud community, and welcome back to AWS re:Invent. We are here in Las Vegas, Nevada. I'm Savannah Peterson, joined by my co-host Dave Vellante. Dave, how you doing? >> I'm doing well, thanks, yeah. >> Yeah, I feel like... >> I'm hanging in there. >> you've got a lot of pep in your step today for the fourth day. >> I think my voice is coming back, actually. >> (laughs) Look at you, resilient. >> I was almost lost yesterday, yeah. >> Yeah. (laughs) >> So, I actually, at a Hitachi event one time almost completely lost my voice. The production guys pulled me off. They said, "You're done." (Savannah laughing) They gave me the hook. >> You got booted? >> Dave: Yeah, yeah. >> Yeah, yeah, you actually (laughs) got the hook, wow. >> So, I have good memories of Hitachi. >> I was going to say (Dave laughing) interesting that you mentioned Hitachi. Our two guests this morning are from Hitachi. Sid and KP, welcome to the show. >> Thank you. >> Savannah: How you guys doing? Looking great for day four. >> Great. Thank you. >> Great. >> Hanging in there. >> Thank you, Dave and Savannah. (Savannah laughing) >> Dave: Yeah, cool. >> Savannah: Yeah. (laughs) >> Yeah, it was actually a Pentaho thing, right? >> Oh, Pentaho? Yeah. >> Which kind of you guys into that software edge. It was right when you announced the name change to Hitachi Vantara, which is very cool. I had Brian Householder on. You remember Brian? >> Yeah, I know. >> He was explaining the vision, and yeah (indistinct). >> Yeah. Well, look at you a little Hitachi (indistinct). >> Yeah, I've been around a long time, yeah. >> Yeah, all right. (Dave laughing) >> Just a casual flex to start us off there, Dave. I love it. I love it. Sid, we've talked a lot on the show about delivering outcomes. It's a hot theme. Everyone wants to actually have tangible business outcomes from all of this. How are customers realizing value from the cloud? What does that mean? >> See, still 2007, 2008, it was either/or kind of architecture. Either I'm going to execute my use cases on cloud or I'm going to keep my use cases and outcomes through edge. But in the last four or five years and specifically we are in re:Invent, I would talk about AWS. Lot of the power of hyperscalers has been brought to edge. If you talk about the snowball family of AWS, if you talk about monitor on edge devices, if you talk about the entire server list being brought into Lambda coupled inside snowball, now the architecture premise, if I talk about logical shift is end. Now the customers are talking about executing the use cases between edge and cloud. So, there is a continuum rather than a binary bullion decision. So, if you are talking about optimizing a factory, earlier I'll do the analytics at cloud, and I'll do machine on edge. Now it is optimization of a factory outcome at scale across my entire manufacturing where edge, private cloud, AWS, hyperscalers, everything is a continuum. And the customer is not worried about where, which part of my data ops, network ops, server ops storage ops is being executed. >> Savannah: It's like (indistinct). >> The customer is enjoying the use cases. And the orchestration is abstracted through an industrial player like Hitachi working very collaboratively with AWS. So, that is how we are working on industrial use cases right now. >> You brought up manufacturing. I don't think there's been a hotter conversation around supply chain and manufacturing than there has been the last few years. I can imagine taking that guessing game out for customers is a huge deal for you guys. >> Big because if you look at the world today, right from a safety pin, to a cell phone jacket, to a cell phone, the entire supply chain is throttled. The supply chain is throttled because there are various choke points. >> Savannah: Yeah. >> And each choke points is surrounded by different kind of supply and geopolitical issues. >> Savannah: 100%. >> Now, if we talk about the wheat crisis happening because of the Ukraine-Russia war, but the wheat crisis actually creates a multiple string of impacts which impact everything. Silicon, now we talk about silicon, but we then forget about nickel. Nickel is also controlled in one part of that geopolitical conflict. So, everything is getting conflagrated into a very big supply issue. So, if your factories are not performing beyond optimum, if they are not performing at real, I'm, we are talking about factory, hyperscale of the factory. The factory needs to perform at hyperscale to provide what the world needs today. So, we are in a very different kind of a scenario. Some of the economists call it earlier the recession was because of a demand constraint. The demand used to go down. Today's recession is because the supply is going down. The demand is there, but the supply is going down. And there is a different kind of recession in the world. The supply is what is getting throttled. >> And the demand is somewhat unpredictable too. People, you know, retailers, they've... >> Especially right now. >> kind of messed up their inventory. And so, the data is still siloed. And that's where, you know, you get to, okay, can I have the same experience across clouds, on-prem, out to the edge? Kind of bust those silos. >> Yep. >> You know, I dunno if it's, it's certainly not entirely a data problem. There's (laughs), like you say, geopolitical and social issues. >> Savannah: There's so much complexity. >> But there's a data problem too. >> Yes. >> Big. >> So, I wonder if you could talk about your sort of view of, point of view on that cross-cloud, hybrid, out to the edge, what I call super cloud? >> Absolutely. So, today, if you look at how enterprises are adopting cloud or how they're leveraging cloud, it's not just a hosting platform, right? It is the platform from where they can draw business capabilities. You heard in the re:Invent that Amazon is coming up with a supply chain service out of the box in the cloud. That's the kind of capabilities that business wants to draw from cloud today. So, the kind of multicloud or like hybrid cloud, public cloud, private cloud, those are the things which are kind of going to be behind the scenes. At the end of the day, the cloud needs to be able to support businesses by providing their services closer to their consumers. So, the challenges are going to be there in terms of like reliability, resilience, cost, security. Those are the ones that, you know, many of the enterprises are grappling with in terms of the challenges. And the way to solve that, the way how we approach our customers and work with them is to be able to bring resilience into the cloud, into the services which are running in cloud, and by driving automation, making autonomous in everything that you do, how you are monitoring your services, how we are making it available, how we are securing it, how we are making it very cost-effective as well. It cannot be manually executed; it has to be automated. So, automation is the key in terms of making the services leveraged from all of this cloud. >> That's your value add. >> Absolutely. >> And how do I consume that value add? Is it sort of embedded into infrastructure? Is it a service layer on top? >> Yeah, so everything that we do today in terms of like how these services have to be provided, how the services have to be consumed, there has to be a modern operating model, right? I think this is where Hitachi has come up with what we are calling as Hitachi Application Reliability Center and Services. That is focusing on modern operating, modern ways of like, you know, how you support these cloud workloads and driving this automation. So, whether we provide a hyper-converged infrastructure that is going to be at the edge location, or we are going to be able to take a customer through the journey of modernization or migrating onto cloud, the operating model that is going to be able to establish the foundation on cloud and then to be able to operate with the right levels of reliability, security, cost is the key. And that's the value added service that we provide. And then the way we do that is essentially by looking at three principles: one, to look at the service in totality. Gone are the days you look at infrastructure separately, applications separately, data and security separately, right? >> Savannah: No more silos. >> No more silos. You look at it as a workload, and you look at it as a service. And number two is to make sure that the DevOps that you bring and what you do at the table is totally integrated and it's end to end. It's not a product team developing a feature and then ops team trying to keep the lights on. It has to be a common backlog with the error budget that looks at you know, product releases, product functionalities, and even what ops needs to do to evolve the product as well. And then the third is to make sure that reliability and resiliency is inbuilt. Cloud offers native durability, native availability. But if your service doesn't take advantage of that, it's kind of going to still be not available. So, how do you kind of ingrain and embed all of these things as a value add that we provide? >> There's a lot of noise. We've got hybrid cloud. We've got multicloud. We've got a lot going on. It adds to the complexity. How do you help customers solve that complexity as they begin their transformation journey? I mean, I'm sure you're working with the biggest companies, making really massive change. How do you guide them through that process? >> So, it is to look at the outcome working backwards, like what AWS does, right? Like, you know, how do you look at the business outcome? What is the value that you're looking to drive? Again, it's not to be pinned through one particular cloud. I know there is lot of technology choices that you can make and lot of deployment models that you can choose from. But at the end of the day, having a common operating model which is kind of like modern, agile, and it is kind of like keeping the outcomes in the mind, that is what we do with our customers to be able to create that operating model, which completes the transformation, by the way. And cloud is just one part of the LEGO blocks which provides that overall scheme and then the view for driving that overall transformation. >> So, let's paint a picture. Let's say you've got this resilient foundation; you've kind of helped the customers build that out. How do they turn that into value for their customers? Do you have any examples that you can share? That'd be great. >> Yeah, I can start with what we're doing for one of the, you know, world's largest facility, infrastructure, power, cooling, security, monitoring company that has their products deployed in 2,000 locations across the globe. For them, and always on business means you are monitoring the temperature. You are monitoring the safety of people who are within the facility, right? A temperature shift of one to two degree can affect even the sustainability goals of NARC, our customer, but also their end consumers. So, how do you monitor these kind of like critical parameters? How do you have a platform? >> Savannah: Great example, yeah. >> How you have cloud resources that are going to be always on, that are going to be reliable, that are going to be cost-effective as well is what we are doing for one of our customers. Sid can talk about another example as well. >> Great. >> Yeah, go for it, Sid. >> So, there are examples: rail. We are working with a group in England; it's called West Coast Partnership. And they had a edge device which was increasing in size. Now, this edge device was becoming big because the parameters which go into the edge device were increasing because of regulation and because the rail is part of national security infrastructure. We have worked with West Coast Partnership and Hitachi Rail, which is a group company, to create a miniaturization of this edge device, because if the size of the edge device is increasing on the train, then the weight of the train increases, and the speed profile, velocity profile, everything goes down. So, we have miniaturized the edge device. Secondly, all the data profiles, signal control, traction control, traction motors, direction control, timetable compliance, everything has been kept uniform. And we have done analytics on cloud. So, what is the behavior of the driver? What is a big breaking parameter of the driver? If the timetable has being missed, is there an erratic behavior being demonstrated by the driver to just meet the timetable? And the timetable is a pretty important criteria in rail because if you miss one, then... So, what we have done is we have created an edge-to-cloud environment where the entire rail analytics is happening. Similarly, in another group company, Hitachi Energy, they had a problem that arguably one of the largest transformer manufacturer in the world. The transformer is a pretty common name now because you're seeing what is happening in Ukraine. Russia went after the transformers and substations before the start of the winter so that their district heating can be meddled with. Now, the transformer, it had a lead time of 17 weeks before COVID. So, if you put me an order of a three-phase transformer, I can deliver it to you in 17 weeks. After and during COVID, the entire lead time increased to 57 to 58 weeks. In cases of a complex transformer, it even went up to something like two years. >> Savannah: Ooh! >> Now, they wanted to increase the productivity of their existing plant because there is only that much sheet metal, that much copper for solenoid, that much microprocessor and silicon. So, they wanted to increase the output of their factory from 95 to 105, 10 more transformers every day, which is 500 and, which is 3,650 every- >> Savannah: Year. >> Year. Now, to do that, we went to a very complex machine; it's called a guard machine. And we increased the productivity of the guard machine by just analyzing all the throttles and all the wastages which are happening there. There are multiple case studies because, see, Hitachi is an industrial giant with 105 years of body of work. KP and I just represent the tip of the digital tip of the arrow. But what we are trying to do through HARC, through industry cloud, through partnership with AWS is basically containerizing and miniaturizing our entire body of work into a democratized environment, an industrial app store, if I may say, where people can come and take their industrial outcomes at ease without worrying about their computational and network orchestration between edge and cloud. That's what we are trying to do. >> I love that analogy of an industrial app cloud. Makes it feel easier in decreasing the complexity of all the different things that everyone's factoring into making their products, whatever they're making. So, we have a new challenge here on theCUBE at AWS re:Invent, where we are looking for your 30-second hot take, your Instagram reel, sound bite. What's the most important story or theme either for you as a team or coming out of the show? You can ponder it for a second. >> It might be different. See, for me, it is industrial security. Industrial OT security should be the theme of the Western world. Western world is on the crosshairs of multiple bad actors. And the industrial security is in the chemical plants, is in the industrial plants, is in the power grids, is in our postal networks and our rail networks. They need to be secured; otherwise, we are geopolitically very weak. Gone are the days when anyone is going to pick up a battle with America or Western world on a field. The battle is going to be pretty clandestine on an cyber world. And that is why industrial security is very important. >> Critical infrastructure and protecting it. >> Absolutely. >> Well said, Sid. KP, what's your hot take? >> My take is going to be a modern operating model, which is going to complete the transformation and to be able to tap into business services from cloud. So, a modern operating model through HARC, that is going to be my take. >> Fantastic. Well, can't wait to see what comes out of Hitachi next. Sid, KP... >> KP: Thank you. >> thank you so much for being here. >> Sid: Thank you. >> Absolutely. >> Dave: Thanks, guys. >> Savannah: This is I could talk to you all about supply chain all day long. And thank all of you for tuning in to our continuous live coverage here from AWS re:Invent in fantastic Sin City. I'm Savannah. Oh, excuse me. With Dave Vellante, I'm Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (digital xylophone music)

(gentle music) >> Good morning, fellow cloud nerds, and welcome back to day four of AWS re:Invent. We are here in fabulous Las Vegas, Nevada. I'm joined by my cohost Paul Gillin. I'm Savannah Peterson. We're on theCUBE. Paul, how you doing? You doing well? >> We're staggering to the conclusion. >> (laughing) It's almost the end then. >> And I say that only talking about my feet. This event is still going strong. The great keynote this morning by Werner Vogels about system architecture and really teaching 70,000 people how to design systems. AWS really taking advantage of this event to educate its customer base and- >> So much education here. >> Yeah, and that was a fantastic sort of cap to the keynotes we've seen this week. >> Yeah, I'm impressed Paul, our first AWS re:Invent. I think we're doing pretty good all things considered. >> Well, we're still alive. >> And our next guest actually looks like he's been sleeping this week, which is remarkable. Please welcome Ayal to the show. Ayal, how you doing today? >> I'm good, I'm good. Thank you for having me. >> It's our pleasure. You're with Anjuna. >> Yes. >> Just in case the audience isn't familiar, what's Anjuna? >> Anjuna is an enterprise security company. We focus in the space of confidential computing. And essentially we enable people to run anything they want in any environment with complete security and privacy. >> Which is a top priority for pretty much every single person here. >> Ayal: That is true. >> Now, confidential computing, I keep hearing that term. >> Yeah, let's go there. >> Is it, I mean, is there a trademark associated with it? Is there a certification? Is the concept or is it actually a set of principles and frameworks? >> Savannah: Give us the scoop. >> Yeah, so confidential computing is essentially a set of technologies that were added to the hardware itself, to the CPU, and now to GPUs by the hardware vendors. So Intel, AMD, Arm, Nvidia AWS with their own hardware solution for this. And essentially what it allows you to do is to run workloads on top of the CPU and the GPU in a way that even if somebody gets full access to the infrastructure, you know, root access, physical access, they're not going to have any access to the data and the code running on top of it. And as you can imagine in cloud environments, this is extremely, extremely (indistinct). >> And this done through encryption? >> It involves encryption. If you go one step deeper, it involves protecting the data while it's running, data and memory, when the application is processing it. Which is always been the missing piece in terms of where you protect data. >> So I got excited when I looked at the show notes because you are serving some of the most notoriously security strict customers in the market. Can you tell us about the Israeli Ministry of Defense? >> Sure. So essentially what we do with the Israel Ministry of Defense and other customers, especially on the on the government side, one of the challenges government has is that they have to, if they want security and privacy in the cloud, they have to use something like a gov cloud. And sometimes that makes sense, but sometimes either the gov cloud is not ready because of legal battles or just it takes time to set it up. In some countries, it's just not going to make financial sense for the clouds to create a gov cloud. So what we do is we enable them to run in the commercial cloud with the security and privacy of a gov cloud. >> Was that, I can imagine, so you took them to the public cloud, correct? >> Ayal: Yes. >> Was that a challenging process? When I think of national security, I can imagine a business transformation like that would be a little nerve-wracking. >> Oh, definitely. It was a long process and they went like, "This is probably one of the best security experts on the planet." And they went extremely deep in making sure that this aligns with what they would be able to do to actually move sensitive data to the commercial cloud. Which, obviously, that the requirements are higher than anything I've ever seen from anybody else. And the fact that they were willing to publicly talk about this and be a public reference for us shows the level of confidence that they have in the underlying technology, in the security and privacy that this allows them to achieve. >> We still hear reservations, particularly from heavily regulated industries, about moving into the cloud. Concerns about security, data ownership, shared responsibility. >> Ayal: Yes. >> Are those real, are those valid? Or is the technology foundation now strong enough that they should not be worried about those things? >> Yeah, this is an excellent question, because the the shared responsibility model, is exactly sort of the core of what this is about. The shared responsibility model essentially means the cloud's, sort of by definition, the cloud is somebody else managing the infrastructure for you, right? And if somebody's managing the infrastructure for you they have full access to what you do on top of that infrastructure. That's almost the definition. And that's always been sort of one of the core security problems that was never solved. Confidential computing solves this. It means that you can use the cloud without the clouds having any access to what you do on top of their infrastructure. And that means that if the clouds get hacked, your data is safe. If an employee of the cloud decides to get access to your data, they can't. They just don't have any access. Or if the government comes to the cloud with a subpoena, the clouds can't give them access to your data, which is obviously very important for European customers and other customers outside of the US. So this is essentially what confidential computing does and it allows to break that shared responsibility model, where you as the customer get full control of your data back. >> Now, do you need the hardware foundation to do that? Or are you solving this problem in software? >> No. So we do need a hardware foundation for this which is now available in every cloud. And it's part of every server CPU that Intel ship, that AMD ship. This is part of almost every data center in AWS. But what we bring to the table at Anjuna, is every time there was a fundamental shift in computer architecture, you needed a software stack on top of it to essentially make it usable. And I think the best last example was VMware, right? But virtualization was extremely powerful technology that nobody was using until VMware built a software stack to make it super simple to virtualize anything. And to some extent that was the birth of the public cloud. We would never have a public cloud without virtualization. We're seeing the same level of shift now with confidential computing on the hardware side. And all the large players are behind this. They're all part of the confidential computing consortium that pushes this. But the challenge customers are running into, is for them to go use this they have to go refactor and rebuild every application. >> Why? >> And nobody's going to go do that. And that's exactly what we help them with. >> Yeah. >> In terms of why, as part of confidential computing, what it essentially means is that the operating system is outside the cross cycle. You, you don't want to cross the operating system because you don't want somebody with root access to have any access to your data. And what this means is every application obviously communicates with the operating system pretty often, right? To send something to the network or some, you know, save something to the file system, which means you have to re-architect your application and break it into two: a confidential piece and a piece that's communicating with the operating system and build some channel for the two sides to communicate. Nobody's going to go do that for every application. We allow you to essentially do something like Anjuna run application and it just runs in a confidential computing environment. No changes. >> Let's talk a little bit more about that. So when we're thinking about, I think we've talked a little bit about it, but I think there's a myth of control when we're talking about on-prem. Everybody thinks that things are more secure. >> Right. >> It's not the case. Tell us how enterprise security changes once when a customer has adopted Anjuna. >> Yeah, so I think you're absolutely right. I think the clouds can put a lot more effort and expertise into bringing security than the data center. But you definitely have this sort of more sense of security in your data center because you own the full stack, right? It's your people, it's your servers, it's your networks in the cloud >> Savannah: It's in your house, so to speak. Yeah. >> Exactly. And the cloud is the third party managing all that for you. And people get very concerned about that, and to some extent for a good reason. Because if a breach happens regardless of whose fault it is, the customer's going to be the one sort of left holding the bag and dealing with the aftermath of the breach. So they're right to be concerned. In terms of what we do, once you run things in confidential computing, you sort of solve the core problem of security. One of the core problems of security has always been when somebody gets access to the infrastructure especially root access to the infrastructure, it's game over. They have access to everything. And a lot of how security's been built is almost like these bandaid solutions to try to solve. Like perimeter security is how do I make sure nobody gets access to the infrastructure if they don't need to, right? All these detection solutions is once they're in the infrastructure, how do I detect that they've done something they shouldn't have? A lot of the vulnerability management is how do I make sure everything is patched? Because if somebody gets access how do I make sure they don't get root access? And then they really get access to everything. And conversation computing solves all of that. It solves the root cause, the root problem. So even if somebody gets root access, even if somebody has full access to the infrastructure, they don't have access to anything, which allows you to one, essentially move anything you want to the public cloud regardless, of the sensitivity of it, but also get rid of a lot of these other sort of bandaid solutions that you use today to try to stop people from getting that access because it doesn't matter anymore. >> Okay. So cyber security is a one and a half trillion dollar industry, growing at over 10% a year. Are you saying that if organizations were to adopt confidential computing universally that industry would not be necessary? >> No, I think a lot of it will have to change with confidential computing. Exactly, like the computer industry changed with virtualization. If you had asked when VMware just got started if the data centers are going to like, "Oh, this is going to happen," I don't think anybody could have foreseen this. But this is exactly what virtualization did. Confidential computing will change the the security industry in a massive way, but it doesn't solve every security problem. What it essentially does is it moves the perimeter from the machine itself, which used to be sort of the smallest atom, to be around the workload. And what happens in the machine doesn't matter anymore. You still need to make sure that your workload is protected. So companies that make sure that you write secure code are still going to be needed. Plus you're going to need security for things like denial of service. Because if somebody runs, you know, gets access to their infrastructure, they can stop you from running but your data is going to be protected. You're not going to need any of these data protection solutions around the box anymore. >> Let's hang out there for a second. Where do you see, I mean what an exciting time to be you, quite frankly, and congratulations on all of your success so far. Where are we going in the next two to five years? >> Yeah, I think with confidential computing the first thing that this is going to enable is essentially moving everything to the public cloud. I think the number one concern with the cloud kind of like you mentioned, is security and privacy. >> Savannah: Right. >> And this essentially eliminates that need. And that's why the clouds are so excited about this. That's why AWS talks about it. And I think Steve Schmidt, the of CISO of Amazon, used to be the CISO of AWS, talks about confidential computing as the future of data security and privacy. And there's a reason why he does that. We've seen other clouds talk about this and push this. That's why the clouds are so excited about this. But even more so again, I think over time this will allow you to essentially remove a lot of the security tools that exist there, kind of reimagine security in a better way. >> Savannah: Clean it up a little bit. Yeah. >> Exactly. And over time, I think it's going to change the world of compute even more because one of the things this allows you to do is the closer you get to the edge, the more security and privacy problems you have. >> Savannah: Right. And so many variables. >> Exactly. And it's basically out there in the wild, and people can get physical access. >> Quite literally a lot of the time, yeah. >> Exactly. And what confidential computing does, it provides that complete security and privacy regardless of even if somebody has physical access, which will allow you to move workloads much closer to the edge or to the edge itself instead of sending everything back to your backend to process things. >> We have interviewed a number of security companies here during this event, and I have to say, confidential computing has never come up. They don't talk about it. Why is that? Is there an awareness problem? >> Savannah: Are they threatened? >> Yeah, so I think the biggest, and to some extent, this is exactly like I kept bringing up VMware. Like VMware's, you can think of Salesforce, when they talked about SaaS, they sort of embedded the concept of SaaS. No other company on the planet was talking about SaaS. They created a new category and now almost everything is SaaS. VMware with virtualization, right? Nobody was using it, and now, almost everything is virtualized. Confidential computing is a new way of doing things. It's basically a kind have to shift the way of how you think about security and how you think about privacy. And this is exactly what we're seeing. I don't expect other security companies to talk about this. And to some extent, one of the things I've realized that we're almost more of an infrastructure company than a security company, because we bake security to be part of the infrastructure. But we're seeing more and more the clouds talk about this. The CPU vendors talk about this. We talk to customers more and more. Like almost every large bank I talk to now has a confidential computing strategy for 2023. This is now becoming part of the mainstream. And yeah, security companies will have to adopt or die if they don't fit into that new world that it is going to create >> This is the new world order, baby, get on the train or get left behind. >> Ayal: Exactly. >> I love it. This is a really fascinating conversation and honestly what you're doing makes so much sense. Yeah, you don't need me to validate your business model, but I will, just for the sake of that. >> Thank you. >> We have a new challenge here at re:Invent on theCUBE where we are looking for your 30 second Instagram reel hot take, thought leadership. What's the biggest theme, key takeaway from the show or experience this year for you? >> Yeah, so for me, obviously focusing on confidential computing. I think this is just going to be similar to how no network was encrypted 10 years ago and today every network is encrypted with TLS and HTTPS. And how five years ago no disc was encrypted, and today every disc is encrypted with disc encryption. The one missing piece is memory. Memory is where data is exposed now. I think within a few years all memory is going to be encrypted and it's just going to change two industries: the security industry as well as the computer industry. >> Paul: Does that include cache memory? >> What's that? >> Does that include cache memory? >> That is encrypting the RAM essentially. So everything, this is the one last place where data is not encrypted, and that's exactly what confidential computing brings to the table. >> Are there any performance concerns with encrypting memory? >> That's a phenomenal question. One of the really nice things about confidential computing is that the heavy lifting is done by the hardware vendors themselves as part of the hardware and not part of the critical path in the CPU. It's very similar to the TLS acceleration cards, if you remember those, which allows us to be extremely, extremely performant. And that's why I think this is going to be for everything. Because every time we had a security solution that had no performance impact and was super simple to use it just became the default, because why wouldn't you use it for everything? >> Ayal, this has been absolutely fascinating. We could talk to you all day. Unfortunately, we're out of time. But really thank you so much for coming on the show. Now, we feel more confident in terms of our confidential computing knowledge and definitely learned a lot. Thank all of you for tuning in to our fantastic four day live stream at AWS re:Invent here in Sin City with Paul Gillin. I'm Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (gentle music)

>>Good Morning Cloud community and welcome back to Fabulous Las Vegas, Nevada, where we are at AWS Reinvent. It is day four here on the Cube. I'm Savannah Peterson with Lisa Martin. You are looking fantastic. Day four, we've done 45 interviews. How are you feeling? Oh, >>Great. I can't believe it's day four. The cube will be producing over 100 interviews. >>Impressive. Right >>On this stage where there are two sets, and of course we have the set upstairs as well. It's amazing how much content we've created, how many great conversations we've had, right? And the excitement around AWS and the, and the community. >>Yeah. I feel like we've learned so much together. Love co-hosting with you, and so excited for our first conversation this morning with Wira. Welcome, Tim and Kashmira, welcome to the show. How you doing? You both look great for day four. Thank >>You. Yeah, we're doing good. Great. We're doing good. Ready to go. Day four, let's go. >>That's the spirit. That's exactly the energy we need here on the cube. So just in case someone in the audience is not familiar, tell us about Wipro. >>So Wipro is a global consulting company and we help transform our customers and their businesses. >>Transformation's been a super hot topic here at the show, quite frankly a big priority, especially with cost cutting and everything else that's going on. How, how do you do that? How do you help customers do that? Has >>Me run? So we, we, so we have our A strategy, which we call our full stride cloud strategy. So particularly from a cloud perspective here, obviously with aws, we have end to end client services. So from high end strategic consulting through customer journeys, technology implementation, all the way through to our managed services. So we help customers with the end to end journey, particularly as here we're talking about cloud, but also business transformation as well. And we have, you know, a whole host of technologies. So about a few years ago we made an announcement around a billion investment in cloud casual and that Yeah, absolutely. A cool billion and just a cool billion. Yeah. And that pocket >>Change. Exactly. >>Right. And that investment. Over the last few years, we've acquired a number of really exciting companies like Capco, which is a consulting company in the financial services space. We've acquired design companies, a company called Design it, looking at customer journeys and user experience, and then also technology companies called Rising, which looks after the whole SAP space. So we've kind of got the end to end solutions and technologies. And then we also invest in what we call Wipro Ventures. These are really innovative, exciting startups. We invest in those companies to really drive transformation. And the final thing that really brings the whole thing together is that we have decades of experience in engineering. That's kind of the heart of where we come from. So that experience all of that together really helps our clients to transform their business. And particularly as we're talking about cloud helps us to transform the cloud. Now what we are really hoping is that we can help our clients become what we call intelligent enterprises, and we are focusing more and more on customer outcomes and really helping them with those business outcomes. >>Yeah. It doesn't matter what we do if there isn't that business outcome. >>Yeah. That's what it's all about. I'm curious, Tim, to get your, as the America's cloud leader, one of the things that, that our boss, John Furrier, who is the co CEO of the Cube, was able to do every year, he gets to sit down with the head of AWS for a preview of reinvent, right? He's been doing this for 10 years now, and one of the things that Adam Olitsky said to him, this is something about a week or so ago, is CIOs and CEOs are not coming to me to talk about technology. They wanna talk about transformation. Sure, yeah. Business transformation, not an amorphous topic of digital transformation. Are you hearing the same? >>Absolutely. Right. So I think this is my seventh reinvent, right? And I think six, seven years ago, the majority of the conversations you would've had are about technology, right? Great technology, but kind of technology for it to solve it problems. You know, how do I, how do I migrate, how do I modernize, how do I use data? How do I make all this stuff happen? Right now it's about how do I drive new business opportunities, new revenue streams, how do I drive more efficiencies through the manufacturing 2.0 or what have you, right? Yeah. One really good example, like take, take medical devices, right? So like a connected defibrillator, right? Anytime you're building a, what they call an IOT device or a connected device, right? You have four competing an edge device in the space, an edge device, yeah. Right? You have four competing elements, right? >>You've got form factor, power, connectivity and intelligence, and all those things compete, right? I can have all the power if I want, if I can have something as biggest as a tape, right? You know, I can have satellite if I, it gets right off if I can plug it in somewhere. But when you're talking about an implanted defibrillator, right? That, that all competes. So you have an engineering problem, an engineering challenge that's based on a device, right? And then it's gotta connect to the cloud, right? So you have a lot of AWS services, I ot, core device shadowing, all sorts of things. That individual patient then, so, so there's the engineering challenge of, okay, I wanna build a device, I gotta prototype it, I gotta design it, I gotta build it at scale, I have to support it. Then you have a patient, right? Which is the end goal of the business is the patient care. >>They have a console at home that connects to that defibrillator via Bluetooth, let's say. And that's where you get your device updates, just like your laptop, right? You know, now push from where updates to your chest. Yes. Device, ot. It's like, okay, I'm just gonna do this every Thursday, right? So now you've very quickly move to a patient experience and that patient experience will very greatly, right? You know, based on age and exposure to technology and all other sorts of things, how diligent they are. Do they do the update every week Right. To their primary care provider? And then what we're, we're also hearing, okay, so like Kashmira mentioned, we, we can, we can have that design discussion, right? Yeah. We can have the engineering device discussion with our device, device lab. Then we can have our, you know, what's the, what's the patient experience, but then broader, what's the patient experience as they move, as we all do through a healthcare, that's a healthcare network, it's a provider network, it's a series of hospitals and providers. So what does that big picture and ecosystem look like? And it's, you haven't heard me mention server or data center or any of that stuff? No. Right? This is >>The most human anecdote we've had on >>Show. Fantastic. This >>Sidebar. Okay. I mean it great. Keep going. It's wonderful. And it's, and it's, it's fascinating because none of this happens or is possible without cloud and, and the type of services that AWS is, is releasing out into their, into their, into their, into the world, right? But it very quickly moves from technology to human. It very quickly moves from individual to ecosystem to to, to partner and culture and, you know, society, right? So, so these are the types of conversations we're having. I mean, this is kind of stuff that gets me outta bed in the morning. So it's great, right? It's great that, I love that. It's great that we've moved, we moved into that space. >>Well, it's, I mean the human element is so important. Every, every company has to be a data company. Hospitals, absolutely. Grocery stores, retailers, you name it. And what we're seeing is this, and we talk about data democratization all the time. Well, another thing that Adam Slosky told John Furrier is that the role of, of data analysts is gonna, is going to change, maybe go away or the, or the term because data needs to be everywhere. The doctors need the data. Absolutely. Every person in the organization needs to be able to analyze data to deliver outcomes. >>Yeah, absolutely. Yeah. And it's fundamental part of our strategies. And when we are looking at, you know, data is everywhere, you need to really think about how do you align to it. But we are looking at it from an industry perspective. So when we're looking at solutions for our clients, we're looking at how do we deliver data solutions for our bank? How do we deliver data solutions in healthcare? How do we deliver data solutions in various different industry? So >>Many different verticals that you're >>Touching. Yeah, all the different verticals. So that's, you know, we have like a four point strategy industry is the first one. So we have been really worked with a lot of clients around migrations and modernizations. What we're moving to now is really this industry play. So this week we've spent a lot of time with our energy and utilities clients and the AWS practice at banking and financial services, which is a very significant part of our business. Also cloud automotive. This is a really, really, you know, the fascinat, this is so exciting, but the fundamental part of that, it's very, is data, right? It's all hits on data. So it was really great to hear some of the announcements this week around the data piece announcements just for me, that's really exciting. Yeah. A couple of other things that when we're thinking about our overall focus and strategy is, you know, looking at business transformation is, as you mentioned, is the ecosystem. >>So how do we bring all this together? And it's really, we see ourselves as an ecosystem orchestrator, and we are really here to look at leveraging our relationship with the best partners. We've actually met 17 partners here this week and had client sessions with them. And that's, you know, working with the license of Snowflake and Data Break in the, in the data space, our long term partners like sap, ibm, VMware, and you know, and new partners like Con. And we are looking at how do we bring the best of this ecosystem orchestration so that to support those client business outcome. Sure. And then one final sort of pillar, sorry, is talent, right? So the biggest thing that everyone is thinking about and we all think about every single day is talent. So we've done two really exciting things this year. One has been around our own talent. >>So we've really looked at our own internal influences, people who are speaking to our clients every single day. Not so much the technology people, but the client people speaking to the client. And we've really raised the level of cloud fluency with these people so that they can really start to have that discussion. You know, and our clients, you know, they know this technology way better than us, you most of the time. And then secondly, we actually announced last week and, and you initiative, which we are calling skill skills, which is very well known to our AWS clients because AWS provide this skill, skill concept to their clients. But we are the first partner to do the skills. Skills Yeah. From a partnering perspective. And this is really gonna transform. So it's not just about training and enablement, it's actually about creating a journey for you to, you know, do your best work. >>Tim, what, how do you define cloud fluency? We were actually talking about it yesterday. Sure, sure. Yeah. And, and really kind of bringing that across an organization, but what, what does it take for an individual who may not be a technologist to become cloud fluent? >>Sure. Well, there's a couple, there's a couple angles to that, right? One is, one is how do you create cloud fluency for people who might already be technical, right? And that's, and that's, you know, I've spent over a decade with, you know, boutique disruptive consulting companies who live and die by whether they can attract and retain talent. And there's sort of four elements to that. It's, can you, can you show people they're gonna work on interesting stuff, right? Are they gonna be excited about what they do? Can you show that they're gonna expand their skill sets? Yep. Can you show them a career path? And you can, can you surround all of that with a supportive engineering first culture, right? That, you know, rewards for outcomes, but also creates this sort of community, right? Yeah. That's, that's one thing that sort of, you know, that that will be a natural entropy, people will be attracted to that. On the other side of it, as you create fluency, you kind of do it with the conversation that I just had, like around something like medical devices or something like the cloud car. When you just say, look, you start with something everybody already knows, right? We all know what patient care is like. We all know what autonomous vehicles is kind of like, right? And you work backwards from that and say, now here's, here's how all the pieces stitch together to create this end outcome for, for us and for our customers, for >>The, you know, I'm speaking my language, Tim. So I run a boutique consultancy, my talent go, I live and die on that. Quite frankly. It's everything, right? And, and it's so, wow, it's so important. I mean, in eliminating that churn at scale, how big is your team? Now I'm just thinking about this cause I'm sure you're, your talent retention has to be a challenge as well. Sure. >>So, so we have 25,000 woo professionals on aws trained on, you know, tech cloud technologies globally. Impressive. Yeah. And then we have, in terms of our go to market team, we've got 50 strong as well. Well, so we, these are people who are live and breathe aws, right? And speaking and working with the cloud. >>Let's hang out there a little bit. Tell us a little bit more about the partnership with aws. Cast me, >>Let's go to you. Yeah, so our partnership is, you know, it's 11 years strong. It's been an and a really, really great partnership's. >>How longs >>That's true. Yeah. >>No, is you, were, you're, you're like day ones there. That's Yeah. Real legacy it. >>Awesome. You know, this year excitingly, we actually won the APJ partner of dsi, partner of the year. Congratulations. >>Really casual. >>Yeah. Just like >>Married the lead there. Congratulations. >>Yeah. So that really is testament to how we're really knuckling down and working proactively to, to really support our clients. And, you know, the, the partnership is a really, really strong partnership. It's been there for many years with, you know, great solutions and engagement and many of the things I talked about in terms of our industry plays that we're driving. We've got a whole new set of competencies that we've launched, like a new energy competency this year. So we're focusing on industry and then also security, two new security competencies. And you know, what's really exciting on the security side, you saw the announcements around the security data lake, but we've been working over the last few months with Gary, me and his team, and actually are one of the first partners that are driving that initiative. So we're really proud to be part of that. So yeah. You know, and then there's a client engagement as well. So we have a dedicated team at AWS that works with our dedicated team. So we're supporting the client's needs day to day. >>Are you as customer obsessed as AWS is? Absolutely. I >>Figured so. Absolutely. Everything's about the customer. Nothing happens about >>That. Right? Well, you talked about outcomes, it's all about outcomes. >>Well, and I mean, quite literally going for the heart with the defibrillator analogy. No, I mean, you tell the customers at the heart of what you're doing, part of everything. Can't resist a good pun there. So as I warned you, we have a little challenge for you here on the cube. We're looking for your hot take your 32nd sound bite thought leadership. What's the biggest takeaway from the event and moving forward, looking into 2023? Tim, you're giving me that eye contact. I'm going to you first, >>Right? Okay, sure. Love to. So I don't know how hot a take it is, but I kind of see this transition as cloud, as the operating system, right? So, so let's take the, the what we call the cloud car project. We have the connected car. You know, a car is a durable good, and we all know, or there's been a lot of talk about the electric cars or the autonomous vehicles being like more of a computer than a vehicle, right? But a vehicle's supposed to last 10, 15, 20 years. Our laptops don't last 10, 15, 20 years. So there's this cell, there's this major challenge to say, how can I, how can I change the way the technology operates within the vehicle? So you see this transition to where instead of it being a car that, that has a computer, then it, the, the, the latest transition is to more of a computer that, that operates like a car. >>This new vehicle that's going to emerge is gonna be much like a cell phone, right? Where it, it traverses the world and depending on where it is, different things might be available, right? And, and how and how, how the actual technology, the software that is running will, will be, you know, sort of amorphous and move between different resources in the network on the car, everywhere else. And so that's a really different way of thinking about if, if we think about how quickly the Overton window, like what becomes normal, it changes over time. We're really getting to like a very fast movement of that into something like this vehicle's still gonna be something that we don't even maybe think of as a car anymore. Just the way that an iPhone isn't what we used to think of a phone at our >>Pocket computer. Yeah. What's in the mirror part? Great. >>That's kind my >>Take. Awesome. Right? Catch me man. >>Yeah, and I mean I, if I was to suggest that, you know, summarize it by simply, for me it's really focusing on industry solutions, delivering client outcomes, fundamentally underpinned by data security and sustainability. You know, I think Nailed it. >>Yeah. Knock it outta the park. Perfect little sound bite. That was fantastic. You both were a wonderful start to the day. Thank you so much for being here. Tim and Kashmir, absolute >>Pleasure. >>This is, this is a joy. We're gonna keep learning here on the cube. And thank all of you for tuning in to our fabulous AWS reinvent coverage here from Sin City with Lisa Martin. I'm Savannah Peterson and you are watching The Cube, the leader in high tech coverage.

(soft music) >> Welcome back to Sin City, guys and girls we're glad you're with us. You've been watching theCUBE all week, we know that. This is theCUBE's live coverage of AWS re:Invent 22, from the Venetian Expo Center where there are tens of thousands of people, and this event if you know it, covers the entire strip. There are over 55,000 people here, hundreds of thousands online. Dave, this has been a fantastic show. It is clear everyone's back. We're hearing phenomenal stories from AWS and it's ecosystem. We got a great customer story coming up next, featured on the main stage. >> Yeah, I mean, you know, post pandemic, you start to think about, okay, how are things changing? And one of the things that we heard from Adam Selipsky, was, we're going beyond digital transformation into business transformation. Okay. That can mean a lot of things to a lot of people. I have a sense of what it means. And I think this next interview really talks to business transformation beyond digital transformation, beyond the IT. >> Excellent. We've got two guests. One of them is an alumni, Scott Mullins joins us, GM, AWS Worldwide Financial Services, and Brad Peterson is here, the EVP, CIO and CTO of NASDAQ. Welcome guys. Great to have you. >> Hey guys. >> Hey guys. Thanks for having us. >> Yeah >> Brad, talk a little bit, there was an announcement with NASDAQ and AWS last year, a year ago, about how they're partnering to transform capital markets. It was a highlight of last year. Remind us what you talked about and what's gone on since then. >> Yeah, so, we are very excited. I work with Adena Friedman, she's my boss, CEO of NASDAQ, and she was on stage with Adam for his first Keynote as CEO of AWS. And we made the commitment that we were going to move our markets to the Cloud. And we've been a long time customer of AWS and everyone said, you know the last piece, the last frontier to be moved was the actual matching where all the messages, the quotes get matched together to become confirmed orders. So that was what we committed to less than a year ago. And we said we were going to move one of our options markets. In the US, we have six of them. And options markets are the most challenging, they're the most high volume and high performance. So we said, let's start with something really challenging and prove we can do it together with AWS. So we committed to that. >> And? Results so far? >> So, I can sit here and say that November 7th so we are live, we're in production and the MRX Exchange is called Mercury, so we shorten it for MRX, we like acronyms in technology. And so, we started with a phased launch of symbols, so you kind of allow yourself to make sure you have all the functionality working then you add some volume on it, and we are going to complete the conversion on Monday. So we are all good so far. And I have some results I can share, but maybe Scott, if you want to talk about why we did that together. >> Yeah. >> And what we've done together over many years. >> Right. You know, Brian, I think it's a natural extension of our relationship, right? You know, you look at the 12 year relationship that AWS and NASDAQ have had together, it's just the next step, in the way that we're going to help the industry transform itself. And so not just NASDAQ's business transformation for itself, but really a blueprint and a template for the entire capital markets industry. And so many times people will ask me, who's using Cloud well? Who's doing well in the Cloud? And NASDAQ is an easy example to point to, of somebody who's truly taking advantage of these capabilities because the Cloud isn't a place, it's a set of capabilities. And so, this is a shining example of how to use these capabilities to actually deliver real business benefit, not just to to your organization, but I think the really exciting part is the market technology piece of how you're serving other exchanges. >> So last year before re:Invent, we said, and it's obvious within the tech ecosystem, that technology companies are building on top of the Cloud. We said, the big trend that we see in the 2020s is that, you know, consumers of IT, historically, your customers are going to start taking their stacks, their software, their data, their services and sassifying, putting it on the Cloud and delivering new services to customers. So when we saw Adena on stage last year, we called it by the way, we called it Super Cloud. >> Yeah. >> Okay. Some people liked the term but I love it. And so yeah, Super Cloud. So when we saw Adena on stage, we said that's a great example. We've seen Capital One doing some similar things, we've had some conversations with US West, it's happening, right? So talk about how you actually do that. I mean, because you've got a lot, you've got a big on-premises stay, are you connecting to that? Is it all in the Cloud? Paint a picture of what the architecture looks like? >> Yeah. And there's, so you started with the business transformation, so I like that. >> Yeah. >> And the Super Cloud designation, what we are is, we own and operate exchanges in the United States and in Europe and in Canada. So we have our own markets that we're looking at modernizing. So we look at this, as a modernization of the capital market infrastructure, but we happen to be the leading technology provider for other markets around the world. So you either build your own or you source from us. And we're by far the leading provider. So a lot of our customers said, how about if you go first? It's kind of like Mikey, you know, give it to Mikey, let him try it. >> See if Mikey likes it. >> Yeah. >> Penguin off the iceberg thing. >> Yeah. And so what we did is we said, to make this easy for our customers, so you want to ask your customers, you want to figure out how you can do it so that you don't disrupt their business. So we took the Edge Compute that was announced a few years ago, Amazon Outposts, and we were one of their early customers. So we started immediately to innovate with, jointly innovate with Amazon. And we said, this looks interesting for us. So we extended the region into our Carteret data center in Northern New Jersey, which gave us all the services that we know and love from Amazon. So our technical operations team has the same tools and services but then, we're able to connect because in the markets what we're doing is we need to connect fairly. So we need to ensure that you still have that fairness element. So by bringing it into our building and extending the Edge Compute platform, the AWS Outpost into Carteret, that allowed us to also talk very succinctly with our regulators. It's a familiar territory, it's all buttoned up. And that simplified the conversion conversation with the regulators. It simplified it with our customers. And then it was up to us to then deliver time and performance >> Because you had alternatives. You could have taken a more mature kind of on-prem legacy stack, figured out how to bolt that in, you know, less cloudy. So why did you choose Outposts? I am curious. >> Well, Outposts looked like when it was announced, that it was really about extending territory, so we had our customers in mind, our global customers, and they don't always have an AWS region in country. So a lot of you think about a regulator, they're going to say, well where is this region located? So finally we saw this ability to grow the Cloud geographically. And of course we're in Sweden, so we we work with the AWS region in Stockholm, but not every country has a region yet. >> And we're working as fast as we can. - Yes, you are. >> Building in every single location around the planet. >> You're doing a good job. >> So, we saw it as an investment that Amazon had to grow the geographic footprint and we have customers in many smaller countries that don't have a region today. So maybe talk a little bit about what you guys had in mind and it's a multi-industry trend that the Edge Compute has four or five industries that you can say, this really makes a lot of sense to extend the Cloud. >> And David, you said it earlier, there's a trend of ecosystems that are coming onto the Cloud. This is our opportunity to bring the Cloud to an ecosystem, to an existing ecosystem. And if you think about NASDAQ's data center in Carteret, there's an ecosystem of NASDAQ's clients there that are there to be with NASDAQ. And so, it was actually much easier for us as we worked together over a really a four year period, thinking about this and how to make this technological transition, to actually bring the capabilities to that ecosystem, rather than trying to bring the ecosystem to AWS in one of our public regions. And so, that's been our philosophy with Outpost all along. It's actually extending our capabilities that our customers know and love into any environment that they need to be able to use that in. And so to Brad's point about servicing other markets in different countries around the world, it actually gives us that ability to do that very quickly, very nimbly and very succinctly and successfully. >> Did you guys write a working backwards document for this initiative? >> We did. >> Yeah, we actually did. So to be, this is one of the fully exercised. We have a couple of... So by the way, Scott used to work at NASDAQ and we have a number of people who have gone from NASDAQ data to AWS, and from AWS to NASDAQ. So we have adopted, that's one of the things that we think is an effective way to really clarify what you're trying to accomplish with a project. So I know you're a little bit kidding on that, but we did. >> No, I was close. Because I want to go to the like, where are we in the milestone? And take us through kind of what we can expect going forward now that we've worked backwards. >> Yep, we did. >> We did. And look, I think from a milestone perspective, as you heard Brad say, we're very excited that we've stood up MRX in production. Having worked at NASDAQ myself, when you make a change and when you stand up a market that's always a moment where you're working with your community, with your clients and you've got a market-wide call that you're working and you're wanting to make sure that everything goes smoothly. And so, when that call went smoothly and that transition went smoothly I know you were very happy, and in AWS, we were also very happy as well that we hit that milestone within the timeframe that Adena set. And that was very important I know to you. >> Yeah. >> And for us as well. >> Yeah. And our commitment, so the time base of this one was by the end of 2022. So November 7th, checked. We got that one done. >> That's awesome. >> The other one is we said, we wanted the performance to be as good or better than our current platform that we have. And we were putting a new version of our derivative or options software onto this platform. We had confidence because we already rolled it to one market in the US then we rolled it earlier this year and that was last year. And we rolled it to our nordic derivatives market. And we saw really good customer feedback. So we had confidence in our software was going to run. Now we had to marry that up with the Outpost platform and we said we really want to achieve as good or better performance and we achieved better performance, so that's noticeable by our customers. And that one was the biggest question. I think our customers understand when we set a date, we test them with them. We have our national test facility that they can test in. But really the big question was how is it going to perform? And that was, I think one of the biggest proof points that we're really proud about, jointly together. And it took both, it took both of us to really innovate and get the platform right, and we did a number of iterations. We're never done. >> Right. >> But we have a final result that says it is better. >> Well, congratulations. - Thank you. >> It sounds like you guys have done a tremendous job. What can we expect in 2023? From NASDAQ and AWS? Any little nuggets you can share? >> Well, we just came from the partner, the partner Keynote with Adam and Ruba and we had another colleague on stage, so Nick Ciubotariu, so he is actually someone who brought digital assets and cryptocurrencies onto the Venmo, PayPal platform. He joined NASDAQ about a year ago and we announced that in our marketplace, the Amazon marketplace, we are going to offer digital custody, digital assets custody solution. So that is certainly going to be something we're excited about in 2023. >> I know we got to go, but I love this story because it fits so great at the Super cloud but we've learned so much from Amazon over the years. Two pieces of teams, we talked about working backwards, customer obsession, but this is a story of NASDAQ pointing its internal capabilities externally. We're already on that journey and then, bringing that to the Cloud. Very powerful story. I wonder what's next in this, because we learn a lot and we, it's like the NFL, we copy it. I think about product market fit. You think about scientific, you know, go to market and seeing that applied to the financial services industry and obviously other industries, it's really exciting to see. So congratulations. >> No, thank you. And look, I think it's an example of Invent and Simplify, that's another Amazon principle. And this is, I think a great example of inventing on behalf of an industry and then continually working to simplify the way that the industry works with all of us. >> Last question and we've got only 30 seconds left. Brad, I'm going to direct it to you. If you had the opportunity to take over the NASDAQ sign in Times Square and say a phrase that summarizes what NASDAQ and AWS are doing together, what would it say? >> Oh, and I think I'm going to put that up on Monday. So we're going to close the market together and it's going to say, "Modernizing the capital market's infrastructure together." >> Very cool. >> Excellent. Drop the mic. Guys, this was fantastic. Thank you so much for joining us. We appreciate you joining us on the show, sharing your insights and what NASDAQ and AWS are doing. We're going to have to keep watching this. You're going to have to come back next year. >> All right. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (soft music)

>>Hey guys and girls, welcome back to The Cube's Live coverage of AWS Reinvent 22 from Sin City. We've been here, this is our third day of coverage. We started Monday night first. Full day of the show was yesterday. Big news yesterday. Big news. Today we're hearing north of 50,000 people, and I'm hearing hundreds of thousands online. We've been having great conversations with AWS folks in the ecosystem, AWS customers, partners, ISVs, you name it. We're pleased to welcome back one of our alumni to the program, talking about partner ecosystem. Dominic Rav Vida joins us, the VP of Developer relations at single store. It's so great to have you on the program. Dominic. Thanks for coming. >>Thanks. Great. Great to see you >>Again. Great to see you too. We go way back. >>We do, yeah. >>So let's talk about reinvent 22. This is the 11th reinvent. Yeah. What are some of the things that you've heard this week that are exciting that are newsworthy from single stores perspective? >>I think in particular what we heard AWS announce on the zero ETL between Aurora and Redshift, I think it's, it's significant in that AWS has provided lots of services for building blocks for applications for a long time. And that's a great amount of flexibility for developers. But there are cases where, you know, it's a common thing to need to move data from transactional systems to analytics systems and making that easy with zero etl, I think it's a significant thing and in general we see in the market and especially in the data management market in the cloud, a unification of different types of workloads. So I think that's a step in the right direction for aws. And I think for the market as a whole, why it's significant for single store is, that's our specialty in particular, is to unify transactions and analytics for realtime applications and analytics. When you've got customer facing analytic applications and you need low latency data from realtime streaming data sources and you've gotta crunch and compute that. Those are diverse types of workloads over document transactional workloads as well as, you know, analytical workloads of various shapes and the data types could be diverse from geospatial time series. And then you've gotta serve that because we're all living in this digital service first world and you need that relevant, consistent, fresh data. And so that unification is what we think is like the big thing in data right >>Now. So validation for single store, >>It does feel like that. I mean, I'd say in the recent like six months, you've seen announcements from Google with Alloy db basically adding the complement to their workload types. You see it with Snowflake adding the complement to their traditional analytical workload site. You see it with Mongo and others. And yeah, we do feel it was validation cuz at single store we completed the functionality for what we call universal storage, which is, is the industry's first third type of storage after row store and column store, single store dbs, universal storage, unifies those. So on a single copy of data you can form these diverse workloads. And that was completed three years ago. So we sort of see like, you know, we're onto something >>Here. Welcome to the game guys. >>That's right. >>What's the value in that universal storage for customers, whether it's a healthcare organization, a financial institution, what's the value in it in those business outcomes that you guys are really helping to fuel? >>I think in short, if there were like a, a bumper sticker for that message, it's like, are you ready for the next interaction? The next interaction with your customer, the next interaction with your supply chain partner, the next interaction with your internal stakeholders, your operational managers being ready for that interaction means you've gotta have the historical data at the ready, accessible, efficiently accessible, and and, and queryable along with the most recent fresh data. And that's the context that's expected and be able to serve that instantaneously. So being ready for that next interaction is what single store helps companies do. >>Talk about single store helping customers. You know, every company these days has to be a data company. I always think, whether it's my grocery store that has all my information and helps keep me fed or a gas station or a car dealer or my bank. And we've also here, one of the things that John Furrier got to do, and he does this every year before aws, he gets to sit down with the CEO and gets really kind of a preview of what's gonna happen at at the show, right? And Adams Lisky said to him some interesting very poignant things. One is that that data, we talk about data democratization, but he says the role of the data analyst is gonna go away. Or that maybe that term in, in that every person within an organization, whether you're marketing, sales, ops, finance, is going to be analyzing data for their jobs to become data driven. Right? How does single store help customers really become data companies, especially powering data intensive apps like I know you do. >>Yeah, that's, there's a lot of talk about that and, and I think there's a lot of work that's been done with companies to make that easier to analyze data in all these different job functions. While we do that, it's not really our starting point because, and our starting point is like operationalizing that analytics as part of the business. So you can think of it in terms of database terms. Like is it batch analysis? Batch analytics after the fact, what happened last week? What happened last month? That's a lot of what those data teams are doing and those analysts are doing. What single store focuses more is in putting those insights into action for the business operations, which typically is more on the application side, it's the API side, you might call it a data product. If you're monetizing your data and you're transacting with that providing as an api, or you're delivering it as software as a service, and you're providing an end-to-end function for, you know, our marketing marketer, then we help power those kinds of real time data applications that have the interactivity and have that customer touchpoint or that partner touchpoint. So you can say we sort of, we put the data in action in that way. >>And that's the most, one of the most important things is putting data in action. If it's, it can be gold, it can be whatever you wanna call it, but if you can't actually put it into action, act on insights in real time, right? The value goes way down or there's liability, >>Right? And I think you have to do that with privacy in mind as well, right? And so you have to take control of that data and use it for your business strategy And the way that you can do that, there's technology like single store makes that possible in ways that weren't possible before. And I'll give you an example. So we have a, a customer named Fathom Analytics. They provide web analytics for marketers, right? So if you're in marketing, you understand this use case. Any demand gen marketer knows that they want to see what the traffic that hits their site is. What are the page views, what are the click streams, what are the sequences? Have these visitors to my website hit certain goals? So the big name in that for years of course has been Google Analytics and that's a free service. And you interact with that and you can see how your website's performing. >>So what Fathom does is a privacy first alternative to Google Analytics. And when you think about, well, how is that possible that they, and as a paid service, it's as software, as a service, how, first of all, how can you keep up with that real time deluge of clickstream data at the rate that Google Analytics can do it? That's the technical problem. But also at the data layer, how could you keep up with Google has, you know, in terms of databases And Fathom's answer to that is to use single store. Their, their prior architecture had four different types of database technologies under the hood. They were using Redis to have fast read time cash. They were using MySEQ database as the application database they were using. They were looking at last search to do full tech search. And they were using DynamoDB as part of a another kind of fast look up fast cash. They replaced all four of those with single store. And, and again, what they're doing is like sort of battling defacto giant in Google Analytics and having a great success at doing that for posting tens of thousands of websites. Some big names that you've heard of as well. >>I can imagine that's a big reduction from four to one, four x reduction in databases. The complexities that go away, the simplification that happens, I can imagine is quite huge for them. >>And we've done a study, an independent study with Giga Home Research. We published this back in June looking at total cost of ownership with benchmarks and the relevant benchmarks for transactions and analytics and databases are tpcc for transactions, TPC H for analytics, TPC DS for analytics. And we did a TCO study using those benchmark datas on a combination of transactional and analytical databases together and saw some pretty big improvements. 60% improvement over Myse Snowflake, for >>Instance. Awesome. Big business outcomes. We only have a few seconds left, so you've already given me a bumper sticker. Yeah. And I know I live in Silicon Valley, I've seen those billboards. I know single store has done some cheeky billboard marketing campaigns. But if you had a new billboard to create from your perspective about single store, what does it say? >>I, I think it's that, are you, are you ready for the next interaction? Because business is won and lost in every moment, in every location, in every digital moment passing by. And if you're not ready to, to interact and transact rather your systems on your behalf, then you're behind the curve. It's easy to be displaced people swipe left and pick your competitor. So I think that's the next bumper sticker. I may, I would say our, my favorite billboard so far of what we've run is cover your SaaS, which is what is how, what is the data layer to, to manage the next level of SaaS applications, the next generation. And we think single store is a big part >>Of that. Cover your SaaS. Love it. Dominic, thank you so much for joining me, giving us an update on single store from your perspective, what's going on there, kind of really where you are in the market. We appreciate that. We'll have to >>Have you back. Thank you. Glad to >>Be here. All right. For Dominic rta, I'm Lisa Martin. You're watching The Cube, the leader in live, emerging and enterprise tech coverage.

(soft electronic music) >> Good afternoon guys and gals. Welcome back to theCube's Live coverage of AWS re:Invent 2022. We've been in Sin City since Monday night, giving you a load of content. I'm sure you've been watching the whole time, so you already know. Lisa Martin here with John Furrier. John, we love having these conversations at AWS re:Invent. So many different topics of conversation. We also love talking to AWS's partner ecosystem. There's so much emphasis on it, so much growth and innovation. >> Yeah, and the thing is we got two great leaders from a very popular company that's doing very well. Security, security's a big part of the story. Data and security. Taking up all the keynote time, you're hearing a lot of it. This company's a company we've been following from the beginning. Doing really good stuff in open source, cloud native, security, shifting-left. Snyk's just a great company. With the CTO and the head of the product organization, these guys have the keys to the kingdom in security. We're going to have a great conversation. >> Yeah, we are. Both from Snyk, Manoj Nair joins us, rejoins us, for your, I believe, 11th visit. Chief Product Officer of Snyk. Adi Sharabani, Chief Technology Officer. Welcome guys. Great to have you. >> Yeah, thank you. >> Great to be back. >> So what's going on at Snyk? I know we get to talk to you often, but Manoj, give us the lowdown on what are some of the things that are new since we last connected with Snyk. >> A lot of innovation going on. We just had a major launch last month and you know when we talked to our customers three big themes are happening in parallel. One is the shift to going from traditional development to, really, DevOps, but we need to make that DevSecOps and Snyk was ahead of, that was the genesis of Snyk, but we're still, you know, maybe 15, 20% of organizations have realized that. So that one big theme. Supply chain security, top of mind for everyone. And then really, cloud and, you know, how do you really take advantage of cloud. Cloud is code. So our innovation map to those three big themes, we have done a lot in terms of that shift-left. And Adi will talk about, kind of, some of our original, like, you know, thinking behind that. But we flipped the security paradigm on its head. Was to make sure developers loved what they were, you know, experiencing with Snyk. And oh, by the way, they're fixing security issues. The second one, supply chain. So you know, SBOMs and everyone hears about this and executive orders, what do you do? Who does what with that? So we launched a few things in terms of simplifying that. You can go to our website and, you know, just upload your SBOM. It'll tell you using the best security intelligence data. In fact, the same data is used by AWS inside their products, inside Inspector. So we use that data from Snyk's intelligence to light up and tell you what vulnerabilities do your third party code have. Even things that you might not be scanning. And then the last one is really code to cloud. Cloud is code. So we have brought the ability to monitor your cloud environments all the way into your platform and the security engineering teams, rather than later on and after the fact. Those are some of the big ones that we're working on. >> Lisa: Lots going on. >> Yeah. >> Lisa: Wow. >> Lots going on there. I mean, SBOMs, Software Bill of Materials. I mean, who would've thought in the developer community, going back a decade, that we'd be talking about bill of materials, open source becomes so popular. You guys are cloud native. Developer productivity's a hot trend. Not much going on here, talking about developer productivity. Maybe Werner, keynote tomorrow will talk about it. Software supply chain, huge security risk. You guys are in the front lines. I want to understand, if you can share, why is Snyk successful? Everyone is hearing about you guys. Your business is doing great. What's the secret sauce of your success? Why are you guys so successful? >> I think that, you know, I've been doing application security for more than two decades now and in the past we always saw the potential associated with transferring, shifting-left in a sense, before the term, right? Taking those security solutions out of the hands of the security people and putting it in the hands of developers. It's speeds up the process. It's very, very clear to anyone. The problem was that we always looked at it the wrong way. We did shift-left, and shift-left is not enough because in my terminology shift-left, meaning let's take those security solution put it earlier in the cycle, but that's not enough because the developer is not speaking those terms. The developer is not a security persona. The security persona is thinking in terms of risk. What are the risks that a specific issue creates? The developer is thinking in terms of the application. What would be the impact on application of a change I would might make into it. And so the root cause of Snyk success, in my opinion, is the fact that from the get-go we scratch that, we build a solution for the developer that is based on how the workflows of the developer, whether it's the ID, whether it's the change management, the pull request. Whether it's integration with the Gits and so on. And whether it's with integration with the cloud and the interaction with the cloud providers. And doing that properly, addressing the developers how they want to context, to get, with the context they want to get as part of the issues, with the workflows they want to get. That's kind of the secret sauce, in a sense. And very easy maybe to say, but very, very hard to implement properly. >> This is huge. I want to unpack that. I want to just, great call out, great description. This is huge. This is a, we're seeing the past three years in particular, maybe three with the pandemic. Okay, maybe go a couple years earlier, then. The developers' behavior is driving the change. And you know, if you look at the past three DockerCons we've covered, we've been powering that site, been following that community very closely since the beginning, as well. It just seems in the past three to four years that the developers choices at scale, not what they're buying or who's pushing tools to them, has been one big trend. >> Yeah. >> They're setting the pace. >> Developer is the king. >> If it's self-service, we've seen self-service. Whether it's freemium to paid, that works. This is the new equation. Developer, developer choice is critical. So self-service they want. And two, the language barrier or jargon between or mindsets between security and developers. Okay, so DevOps brings IT into the workflow. Check. DevSecOps brings in there. You guys crack the code on that, is that what you're saying? >> Yes, and it's both the product, like how do you use the solution, as well as the go to market. How do you consume the solution? And you alluded to that with the PLG motion, that I think Synk has done the superb job at and that really helped our businesses. >> Okay, so Manoj, product, you got the keys to the kingdom, you got the product roadmap. I could imagine, and what I'd love to get your reaction too Adi, if you don't mind. If you do that, what you've done, the consequence of that is now security teams and the data teams can build guardrails. We're reporting a lot of that in the queue. We're hearing that we can provide guardrails. So the velocity of the developer seems to be increasing. Do you see that? Is that a consequence? >> That's something that we actually measure in the product. Right, so Snyk's focus is not finding issues, it's fixing issues. So one of the things we have been able to heuristically look at our thousands of customers and say, they're fixing issues 27 days faster than they were prior to Snyk. So, you know, I'm a Formula one fan. Guardrails, you say. I say there's a speed circuit. Developers love speed. We give them the speed. We give the security teams the ability to sit on those towers and, you know, put the right policies and guardrails in place to make sure that it's not speed without safety. >> And then I'm sure you guys are in the luxury box now, partying while the developers are (Lisa laughing) no more friction, no more fighting, right? >> The culture is changing. I had a discussion with a Fortune 50 CISO a month ago, and they told me, "Adi, it's the first time in my life where the development teams are coming to me, asking me, hey I want you to buy us this security solution." And for, that was mind blowing for him, right? Because it really changes the discussion with the security teams and the development teams >> Before Lisa jumps in, well how long, okay, let me ask you that question on that point. When did that tipping point change, culturally? Was it just the past few years? Has there, has DevOps kind of brought that in, can you? >> Yeah, I think it's a journey that happened together with Snyk's, kind of, growth. So if three years ago it was the very early adopters that were starting to consume that. So companies that are very, you know, modern in the way they developed and so on. And we saw it in our business. In the early days, most of our business came from the high tech industry. And now it's like everywhere. You have manufacturing, you have banks, you have like every segment whatsoever. >> Talk about that cultural shift. That's really challenging for organizations to achieve. Are you seeing, so that, that CISO was quite surprised that the developer came and said, this is what I want. Are you seeing more of that cultural changes? Is that becoming pervasive? >> Yeah, so I think that the root cause of that is that, you mentioned the growth, like the increased speed of velocity in applications. We have 30 million developers in the world today. 30 millions. By the end of the decade it's going to be 45 millions and all of them are using open source, third party code. Look at what's going on here in the event, right? This accelerates the speed for which they develop. So with that, what happened in the digital transformation world, the organizations are facing that huge growth, exponential growth in the amount of technology and products that are being built by their teams. But the way they manage that before, from a security perspective, just doesn't scale. And it breaks and it breaks and it breaks. This is why you need a different approach. A solution that is based on the developers, who are the ones that created the problems and the ones that will be responsible of fixing the issues. This is why we are kind of centering ourselves around them. >> And the world has changed, right? What is cloud? It's code, it's not infrastructure. Old infrastructure, hosted infrastructure. So if cloud is code and cloud native applications are all code and they're being deployed with Terraform packages and cloud formations, that's code. Why take an old school approach of scanning it outside-in. I talked to CISO today who said, I feel bad that, you know, our policy makes it such that a terraform change takes six months. What did I do? I made cloud look like infrastructure. >> Yeah, it's too slow. >> So that, you know, so both sides, you know, CISOs want something that the business, you know, accepts and adopts and it's, culture changes happen because the power is with the developers because all of this is code, and we enabled that whole seamless journey, all the way from code to cloud. So it's kind, you know, I think that this is a part of it. It's by direction, it's a bridge and both sides are meeting in the middle here. >> It's a bridge. I'm curious, how are you facilitating that bridge? You, we talk about the developers being the kings and queens and really so influential in business decisions these days. And you're talking about the developers now embracing Snyk. But you're also talking to CISOs. Is your customer conversation level changing as a result of security folks understanding why it needs to shift-left. >> We had a breakfast meeting with customers, prospects and everyone, I think this morning. It was interesting, we were remarking. There are CTOs, VPs of engineering, CISOs, VPs of AppSec. And it was such a rich conversation on both sides, right? So just the joy of facilitating that conversation and dialogue. CISOs, and so the levels are changing. It started for us in CTOs and VPs of engineering and now it's both because, you know, one of the things Adi talks about is, like, that security has to become development aware. And that's starting to be like the reality. Me getting another solution, with maybe a better acronym than the old acronym, but it's still outside-in, it's scan based. I light up up the Christmas tree, who is going to fix it? And with the speed of cloud, now I got throw in more lights. Those lights are no longer valid. >> The automation. >> The automation without prioritization and actual empowerment is useless. >> All right, I know we got a couple minutes left, but I want to get into that point about automation because inside-out, you've made me think about this. I want to get your thought Adi, if you don't mind. The integration challenges now are much more part of the ecosystem, more joint engineering. You mentioned these meetings are not just salesperson and customer buyer, it's teams are talking to each other. There's a lot of that going on. How do you guys look at that? Because now the worst things that I hear and when I talk to customers is, I hate the word PenTest and AppSec review. It slows things down. People want to go faster. So how do you guys look at that? What's Snyk doing around making the AppSec review process, integration across companies, work better? >> So I'll give you an example from the cloud and then I will relate to the AppSec. And this relates to what you mentioned before. We had a discussion yesterday with a CISO that said, we are scanning the cloud, we are opening the lights, we see this issue. Now what do I do? Who needs to fix this? So they have this long process of finding the actual team that is required to fix it. Now they get to the team and they say, why didn't you tell me about it when I developed it? The same goes for AppSec, right? The audit is a very late stage of the game. You want to make sure that the testing, that the policies, everything is under the same structure, the same policies. So when you do the same thing, it's part of the first time of code that you create, it's part of the change management, it's part of the build, it's part of the deployment and it's part of the audit. And you have everything together being done under the same platform. And this is, kind of, one of the strengths that we bring to the table. The discussion changes because now you have an aligned strategy, rather than kind of blocks that we have, kind of, mashed up together. >> So the new workflow, it's a new workflow, basically, in the mindset of the customer. They got to get their arms around that thing. If we don't design it in, the wheels could come off the bus at the 11th hour. >> Adi: Yeah. >> And everything slows down. >> I had a discussion with Amazon today, actually, that they had an internal discussion and they said, like, some of the teams were like, why have you blocked my app from being released? And they said, have you ever scanned your app? Have you ever looked at your, like, and, and they're like, if you haven't, then you're not really onboard with the platform and it just breaks. This is what happens. >> Great conversation. I know we don't, I wish we had more time. We'll do a follow up on theCube for sure. Should we get into the new twist? >> I've got one final question for you guys. We're making some Instagram reels, so think about your elevator pitch in 30 seconds. And I want to ask you about Snyk's evolution. Manoj, I want to start with you. What is that elevator pitch about Snyk's evolution to the end user customer? >> Empower developers, help them go faster, more productive and do it in a way that security is really built in, not bolted on. And that's really, you know, from a, the evolution and the power that we are giving is make the organization more productive because security is just happening as a part of making the developer more productive. >> Awesome. And Adi, question for you, how, your elevator pitch on how Snyk is really an enabler for CISOs these days? >> Yeah, so I always ask the CISO first of all, are you excited about the way your environment looks like today? Do you need to have a cultural change? Because if you need to have a cultural change, if you want to get those two teams working closely together, we are here to enable that. And it goes from the product, it goes from our education pieces that we can talk about in another section, and it works around the language that we build to allow and enable that discussion. >> Awesome. Guys, that was a double mic drop for both of you. >> Manoj: Thank you. >> Adi: Thank you, Lisa. >> Thank you so much for joining John and me, talking about what's happening with Snyk, what you're enabling customers to do and how, really, you're enabling cultural change. That's hard to do. That's awesome stuff guys. And congratulations on your 11th and your first Cube. >> Second, second, >> Second. >> Adi: I will be here more, but (laughs) >> You got it, you got it. You have to come back because we have too much to talk about. >> Adi: Exactly. (laughs) >> Thanks guys, we appreciate it. >> If we can without Manoj, so I can catch up. (Manoj laughs) >> Okay. We'll work on that. >> Bring you in the studio. (everyone laughing) >> Exactly. >> Eight straight interviews. (John and Lisa laughing) >> We hope you've enjoyed this conversation. We want to thank our guests. For John Furrier, I'm Lisa Martin. You're watching theCUBE, the leader in emerging and enterprise tech coverage. (soft electronic music)

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

(upbeat music) >> Good morning and welcome back to fabulous Las Vegas, Nevada. We're here at AWS re:Invent with wall-to-wall coverage all day long on theCUBE. My name is Savannah Peterson and I am joined this morning by the beautiful Lisa Martin. Lisa, good morning. >> Good morning. Good. >> How you feeling day three? >> Day three is we are going to be shot out of a cannon today. The amount of content coming at you from theCUBE today- >> Get ready, you all. >> Us two gals, is a lot. We're going to have some great conversations. >> And we're starting with a really great one with a Cube Alumni to the max. You've been on the show multiple times. >> John: Yeah. >> Very excited to welcome John, the CMO of Couchbase. Welcome. How you doing this morning? >> Thanks. I'm doing great. Great to be here with you. >> How do you feel about the show so far? What's your pulse? >> The show has been great. I say the energy is great. The traffic at our booth, the conversations that we're having, both with prospective customers and even just partners, right? They're all here. The ecosystem is here >> And everyone's finally back in person and it feels so good. >> John: It does. >> So, we're going to dig in a little bit but just in case the audience isn't familiar, tell us about Couchbase. >> Sure. Couchbase is a publicly traded database company. We have a cloud database platform called Capella which is hosted on AWS and GCP. It is used for building mission-critical applications. So, we have great customers, we're building apps that really matter and are using to drive their business. So, we're very excited about that. 30% of the Fortune 100 are Couchbase customers. >> Nice. Talk a little bit about the AWS relationship. >> Mm-hm. Yeah, so we have a great AWS relationship. In fact, yesterday we announced a deepening of that relationship, a strategic collaboration agreement. We're very excited. It's a multi-year agreement. It's focused on go-to market, from a sales and marketing standpoint. We're going to target, you know, various verticals and, you know, really generate joint business between the two of us. So, it's a deepening of a already strong relationship and we're really excited about that. >> Savannah: Yeah. Go ahead. >> What are some of the industry verticals that you're going to be tackling together? >> Well, gaming for one, right? Manufacturing, the workloads that Couchbase is good for are these mission-critical workloads are ones that are really suited for us to be used with AWS. So, we've done some work with them already in those areas and I'm sure we'll be digging in even deeper. >> That's exciting. Speaking of digging in deeper, tell us a little bit more about Capella. >> Capella. It's a cloud databases services I mentioned. We launched it last October and we are super excited by the uptake, the interest that we're seeing. We have a free 30 day trial, so, you know, people can come and try it and get their hands dirty just getting experience with the product and then, you know, become a customer after that. And we're seeing very strong interest from our existing customer base as well. So, we're really excited about how things are going. >> Talk about Capella and the latest release and how it's really enabling Couchbase to invest deeper into the developer experience. >> Yeah, so, at the end of October, we announced a revamp of our user interface, our user experience for Capella really focused on developers. And what we've done is make it so that it's familiar to developers, right? It's a GitHub-like experience. So, developer comes in, they're very familiar, of course, with GitHub, they are familiar with how the Couchbase Capella interface will work. And so that's something that, you know, we've really invested, in fact, we've invested in developers quite a bit. We announced a Couchbase community hub and a Couchbase ambassadors program, both focused on developers and getting out there and building our community. >> A community is a big topic that we've been talking about at all the conferences this year. We're all back in person, in community. How often are you communicating with your community to get feedback on what that experience should be like? >> Yeah, I mean, we actually have a Discord server, so we're in constant communication. (Savannah laughing) >> Savannah: Yes. (John laughing) 24/7. (laughing) >> Basically, you know, we have staff who's dedicated to making sure that the users on there are getting their answers and giving us feedback on the experience. The ambassadors are somebody who have a really strong relationship, who get early insight and give us feedback before we even release a product. So, it gives us a chance to really test-drive it with core developers and get the insight we need before we get it in the market. >> Yeah. It matters so much. You can build it, but they won't come if it's not fantastic. >> John: Exactly. >> Lisa: Right. >> Let's shift a little bit and talk about customers. How, and price, how do you guys compare? >> Customers and? >> And price, your price performance? >> Price, oh. So, customers, we also announced this week a joint customer Arthrex with AWS. Arthrex is a orthopedics medical devices company and they use our Edge capabilities along with running Couchbase on AWS. So, you think of the kinds of surgeries that orthopedic surgeons do, it's scopes and they are often inside. So, what it does is it collects the data, the video data and all of that on a medical devices and then brings it back to a centralized app for the doctors to use sort of in post when they're actually doing further medical recommendations. >> Savannah: It's so cool. >> So, it's cool, the thing about it is it can work whether it's online or offline, it's one of the reasons that Arthrex selected us because the fact that it can, you know, often sometimes there's not connectivity in the operating room, I'd say deep inside of a hospital. So, these devices work regardless and then when they get connectivity, it sinks back to that centralized service. So, it's one of the main reasons that they selected us. >> That's outstanding. You know, one of the things that John Furrier, you know, John, well, you guys go way back. >> John: Way back. >> He had a sit down with Adam Selensky, oh, about 10 days or so ago. He gets an exclusive with the CEO of AWS every pre re:Invent. And one of the things that Adam said is that the role or the title, data analyst, is going to go away, in that every role will have responsibilities of analyzing data. And I always think of that in terms of operations, marketing, finance, sales, but you just brought up physicians as data analysts in their jobs, right? Probably not, we're thinking about it in that way. >> Yeah. >> But it's so interesting how data is really being democratized. >> John: Yeah. >> And how Couchbase is an enabler of that in an operating room. >> John: Yeah, yeah, yeah. >> That's amazing. >> It's a great story. There's many others and I think, you know, we have embedded operational analytics in Couchbase Capella, and, you know, in our offerings in general. So, what that does is allows us to do real-time, highly personalized applications based on that analytics that are coming in real-time from the data from the applications. And so that's something that's actually driving a highly interactive user experience, one that's very personalized and customized. And that's one of the things that our customers really like about what we do. >> It's fascinating. I never thought about it from a medical device perspective. >> Lisa: No, no. >> John: No. >> My gosh is if doctors don't have enough cognitive burden load. >> John: I know. >> You know, right? Like, they don't need to be a data analyst. I would much rather they were just good at the surgery part. That's a piece of the puzzle I need them to do. Yeah, for sure. That's a fascinating customer example. Can you share any other joint AWS examples with us? >> Joint AW- I mean, there's many in the gaming area where, because Couchbase is memory-first architecture, we deliver very, very interactive user experiences and we're used a lot for session management, user ID management in the gaming space, specifically with AWS. It's an area we've done some joint work already and had a lot of success, you know, with small and large gaming companies. >> Yeah. It looks like you also, according to my notes here, we've got things in travel and hospitality as well. >> Yes. Also Carnival Cruises is a great example. We enable their on-ship, on-board experience, highly customized, everybody wears a device called a medallion, and as they move around the ship, it knows where they are and it's able to provide customized services. You walk up to a bar, you have your favorite drink, it can be hit the bar when you land there. >> I'll take that. >> How about that? (laugh) >> That's outstanding. >> Isn't that great? >> Can we carry that onto the AWS show floor? >> Exactly. >> Or Starbucks order? >> Yeah, yeah. Yes, please. Yes, please. Well, another thing that's so interesting these days, is that every company has to be a data company. Say they have to be a software company. They have to be a data company. You just gave some great examples. Hospitality, gaming, healthcare, where that data democratization has to happen. >> John: Yeah. >> Businesses has to transform. But one of the things that Adam also told John is that CIOs, CEOs are coming to him not wanting to talk about technology but about transformation. >> Yeah. >> Huge topic. >> And that's a journey where every customer is at different levels. >> Yeah. >> How is Couchbase helping businesses transform and where are your customer conversations these days? >> Yeah, yeah, yeah. So, I mean, the transformation of the business is a major topic of conversation. So, we completely agree with that. How Couchbase helps is, you know, in our database, one of the things we have is the SQL engine. And so as people are looking to move and modernize their infrastructure, if they're moving off of, or from like a technology that's principally based on SQL but doesn't give all the flexibility of a JSON database or document database like we do, we actually enable them to get more easily onto our platform so that they can start that transformation. And then it's a, you know, it's a journey of how they want to transform their business and it's really focused on how do they better serve their customers and clients, whether it's internal or external? >> It really matters. I mean, and that ease of use as well as the transformation journey. It takes a long time for people to adapt. So, every piece of that puzzle, every Lego being quicker or easier, more intuitive, like you said, with the user experience, we can tell you're very thoughtful. How does this improve the total cost of ownership for your customers? >> That's one of the things that we announced along with that developer changes, was a new storage engine underneath Couchbase Capella. And it's 10 X more dense storage. And what that means is fewer servers. So, fewer servers is a much better cost of ownership story. That plus just the performance of the platform itself, we find, you know, against competition, we can do things on say six nodes that take 18 nodes for others. >> Lisa: Oh wow. >> And we have a great consolidation story as well because we have, it's a multi-modal database, meaning that it has SQL engine, document database, full tech search, eventing and analytics, all these pieces on one common data layer. So, you can actually consolidate off of other technologies onto one, onto Couchbase, and that actually saves you money. So, that's a great story for us. >> There's got to be a sustainability element to that as well? >> Yeah, I mean it's, obviously, if you're using less, using fewer servers, there's a kind of power consumption aspect of it as well. Absolutely. >> Are you finding that a lot of customers and companies we talk to these days have in their RFPs, they must only work with vendors who have an actual ESG program? Are you finding more customers coming to you saying, how can you help us dial down our carbon emissions? >> John: Yeah. >> Savannah: Great question. >> We've got a sustainability program that we've got to meet, we've got commitments to our customers. >> John: Yeah. >> Is that something that's really now kind of a hard and fast requirement? >> We're hearing it, we're definitely hearing it. I wouldn't say it's, you know, massively pervasive but I would say it's a growing component of, as you said, RFPs. And it's something that we feel like we have a great story for. And so, you know, it's something that helps when we get into those conversations, we can clearly articulate how we can provide that value and how we meet some of those needs that they have. >> Yeah, that's awesome. So, we have a bit of a challenge, new to the show at re:Invent. >> John: Mm-hm. >> Where we are prompting you to give us your 30 second Instagram Reel sizzle highlight. Don't worry, I'm not actually timing you, but your thought leadership hot-take on the most important theme or takeaway from this year's show. >> From the conference here. I would say that, and I think this was talked about a little bit by AWS as well, but the convergence of analytics and operational data, you know, through the applications is one that we're certainly seeing as well. It's the reason we have analytics in our database. But as I walk around and look at it, I see that very much as a common theme as well, in terms of what other vendors are saying and just the conversations we're having. So for me, that's one of the things I think would be a takeaway from this show. >> Yeah. Embedded analytics, real-time, everybody wants to know what's going on, in context. >> Yeah. That's right. >> Right now, not last week, not what we're processing from last month. >> Exactly. >> I mean, right? (cross-talking) >> So, I can react and take advantage or take an action if I have to. >> Exactly. And then deliver that personalized experience that we all expect these days. >> Oh, yes. >> I'll take that medallion- >> It's about the medallion. I was like, okay. >> You up with that, John? >> We'll get right on it. >> Lisa: All right. (laughs) >> About this. So, what's next for Couchbase? >> John: Well- >> I know you got the partnership, you've got all this exciting momentum. >> So, we're excited heading into next year. We're going to continue to innovate on Capella, right? Continue to deliver more value, lean into our developer community that we have. We're investing heavily, not just from a product standpoint but from a company standpoint in terms of, you know, our community meetups and some of those things. We have a big community-focused event coming up in March called Connect, Couchbase Connect. So, that's something that we'll, you know, continue to drive. That'll be a major theme for us next year. Cloud and developers and, you know, continuing to enable that ecosystem. >> Lisa: Excellent. >> I just had a Microsoft moment where I saw you saying, "Cloud developers," on stage. (Lisa and Savannah laughing) >> I'm not going Steve Ballmer on you. (all laughing) >> Pardon. I was trying to get someone to sing yesterday. I was hoping you were my Ballmer dance. Oh, man. Well, this has been a really great way to start the day. John, thank you so much for being on the show with us, seriously. And it's great that you keep coming back. I'm glad we haven't scared you off. (John laughing) >> Never. >> Savannah: We will have you anytime. >> Thank you. >> And thank you all for tuning in for yet another fantastic day of all day live coverage here from AWS re:Invent. We are in Sin City, having a fabulous time with Lisa Martin. I'm Savannah Peterson. This is theCUBE and we are the leader in high-tech technology coverage. (upbeat music) (upbeat music fades)

(calming music) >> Hello and welcome back to fabulous Las Vegas, Nevada. We're here at AWS re:Invent day three of our scintillating coverage here on theCUBE. I'm Savannah Peterson, joined by John Furrier. John Day three energy's high. How you feeling? >> I dunno, it's day two, day three, day four. It feels like day four, but again, we're back. >> Who's counting? >> Three pandemic levels in terms of 50,000 plus people? Hallways are packed. I got pictures. People don't believe it. It's actually happening. Then people are back. So, you know, and then the economy is a big question too and it's still, people are here, they're still building on the cloud and cost is a big thing. This next segment's going to be really important. I'm looking forward to this next segment. >> Yeah, me too. Without further ado let's welcome our guests for this segment. We have Brad from AMD and we have Rahul from you are, well you do a variety of different things. We'll start with CloudFix for this segment, but we could we could talk about your multiple hats all day long. Welcome to the show, gentlemen. How you doing? Brad how does it feel? We love seeing your logo above our stage here. >> Oh look, we love this. And talking about re:Invent last year, the energy this year compared to last year is so much bigger. We love it. We're excited to be here. >> Yeah, that's awesome. Rahul, how are you feeling? >> Excellent, I mean, I think this is my eighth or ninth re:Invent at this point and it's been fabulous. I think the, the crowd, the engagement, it's awesome. >> You wouldn't know there's a looming recession if you look at the activity but yet still the reality is here we had an analyst on yesterday, we were talking about spend more in the cloud, save more. So that you can still use the cloud and there's a lot of right sizing, I call you got to turn the lights off before you go to bed. Kind of be more efficient with your infrastructure as a theme. This re:Invent is a lot more about that now. Before it's about the glory days. Oh yeah, keep building, now with a little bit of pressure. This is the conversation. >> Exactly and I think most companies are looking to figure out how to innovate their way out of this uncertainty that's kind of on everyone's head. And the only way to do it is to be able to be more efficient with whatever your existing spend is, take those savings and then apply them to innovating on new stuff. And that's the way to go about it at this point. >> I think it's such a hot topic, for everyone that we're talking about. I mean, total cost optimization figuring out ways to be more efficient. I know that that's a big part of your mission at CloudFix. So just in case the audience isn't versed, give us the pitch. >> Okay, so a little bit of background on this. So the other hat I wear is CTO of ESW Capital. We have over 150 enterprise software companies within the portfolio. And one of my jobs is also to manage and run about 40 to 45,000 AWS accounts of our own. >> Casual number, just a few, just a couple pocket change, no big deal. >> And like everyone else here in the audience, yeah we had a problem with our costs, just going out of control and as we were looking at a lot of the tools to help us kind of get more efficient one of the biggest issues was that while people give you a lot of recommendations recommendations are way too far from realized savings. And we were running through the challenge of how do you take recommendation and turn them into real savings and multiple different hurdles. The short story being, we had to create CloudFix to actually realize those savings. So we took AWS recommendations around cost, filtered them down to the ones that are completely non-disruptive in nature, implemented those as simple automations that everyone could just run and realize those savings right away. We then took those savings and then started applying them to innovating and doing new interesting things with that money. >> Is there a best practice in your mind that you see merging in this time? People start more focused on it. Is there a method or a purpose kind of best practice of how to approach cost optimization? >> I think one of the things that most people don't realize is that cost optimization is not a one and done thing. It is literally nonstop. Which means that, on one hand AWS is constantly creating new services. There are over a hundred thousand API at this point of time How to use them right, how to use them efficiently You also have a problem of choice. Developers are constantly discovering new services discovering new ways to utilize them. And they are behaving in ways that you had not anticipated before. So you have to stay on top of things all the time. And really the only way to kind of stay on top is to have automation that helps you stay on top of all of these things. So yeah, finding efficiencies, standardizing your practices about how you leverage these AWS services and then automating the governance and hygiene around how you utilize them is really the key >> Brad tell me what this means for AMD and what working with CloudFix and Rahul does for your customers. >> Well, the idea of efficiency and cost optimization is near and dear to our heart. We have the leading. >> It's near and dear to everyone's heart, right now. (group laughs) >> But we are the leaders in x86 price performance and density and power efficiency. So this is something that's actually part of our core culture. We've been doing this a long time and what's interesting is most companies don't understand how much more efficiency they can get out of their applications aside from just the choices they make in cloud. but that's the one thing, the message we're giving to everybody is choice matters very much when it comes to your cloud solutions and just deciding what type of instance types you choose can have a massive impact on your bottom line. And so we are excited to partner with CloudFix, they've got a great model for this and they make it very easier for our customers to help identify those areas. And then AMD can come in as well and then help provide additional insight into those applications what else they can squeeze out of it. So it's a great relationship. >> If I hear you correctly, then there's more choice for the customers, faster selection, so no bad choices means bad performance if they have a workload or an app that needs to run, is that where you you kind of get into the, is that where it is or more? >> Well, I mean from the AMD side right now, one of the things they do very quickly is they identify where the low hanging fruit is. So it's the thing about x86 compatibility, you can shift instance types instantly in most cases without any change to your environment at all. And CloudFix has an automated tool to do that. And that's one thing you can immediately have an impact on your cost without having to do any work at all. And customers love that. >> What's the alternative if this doesn't exist they have to go manually figure it out or it gets them in the face or they see the numbers don't work or what's the, if you don't have the tool to automate what's the customer's experience >> The alternative is that you actually have people look at every single instance of usage of resources and try and figure out how to do this. At cloud scale, that just doesn't make sense. You just can't. >> It's too many different options. >> Correct The reality is that your resources your human resources are literally your most expensive part of your budget. You want to leverage all the amazing people you have to do the amazing work. This is not amazing work. This is mundane. >> So you free up all the people time. >> Correct, you free up wasting their time and resources on doing something that's mundane, simple and should be automated, because that's the only way you scale. >> I think of you is like a little helper in the background helping me save money while I'm not thinking about it. It's like a good financial planner making you money since we're talking about the economy >> Pretty much, the other analogy that I give to all the technologists is this is like garbage collection. Like for most languages when you are coding, you have these new languages that do garbage collection for you. You don't do memory management and stuff where developers back in the day used to do that. Why do that when you can have technology do that in an automated manner for you in an optimal way. So just kind of freeing up your developer's time from doing this stuff that's mundane and it's a standard best practice. One of the things that we leverage AMD for, is they've helped us define the process of seamlessly migrating folks over to AMD based instances without any major disruptions or trying to minimize every aspect of disruption. So all the best practices are kind of borrowed from them, borrowed from AWS in most other cases. And we basically put them in the automation so that you don't ever have to worry about that stuff. >> Well you're getting so much data you have the opportunity to really streamline, I mean I love this, because you can look across industry, across verticals and behavior of what other folks are doing. Learn from that and apply that in the background to all your different customers. >> So how big is the company? How big is the team? >> So we have people in about 130 different countries. So we've completely been remote and global and actually the cloud has been one of the big enablers of that. >> That's awesome, 130 countries. >> And that's the best part of it. I was just telling Brad a short while ago that's allowed us to hire the best talent from across the world and they spend their time building new amazing products and new solutions instead of doing all this other mundane stuff. So we are big believers in automation not only for our world. And once our customers started asking us about or telling us about the same problem that they were having that's when we actually took what we had internally for our own purpose. We packaged it up as CloudFix and launched it last year at re:Invent. >> If the customers aren't thinking about automation then they're going to probably have struggle. They're going to probably struggle. I mean with more data coming in you see the data story here more data's coming in, more automation. And this year Brad price performance, I've heard the word price performance more this year at re:Invent than any other year I've heard it before, but this year, price performance not performance, price performance. So you're starting to hear that dialogue of squeeze, understand the use cases use the right specialized processor instance starting to see that evolve. >> Yeah and and there's so much to it. I mean, AMD right out of the box is any instance is 10% less expensive than the equivalent in the market right now on AWS. They do a great job of maximizing those products. We've got our Zen four core general processor family just released in November and it's going to be a beast. Yeah, we're very excited about it and AWS announced support for it so we're excited to see what they deliver there too. But price performance is so critical and again it's going back to the complexity of these environments. Giving some of these enterprises some help, to help them understand where they can get additional value. It goes well beyond the retail price. There's a lot more money to be shaved off the top just by spending time thinking about those applications. >> Yeah, absolutely. I love that you talked about collaboration we've been talking about community. I want to acknowledge the AWS super fans here, standing behind the stage. Rahul, I know that you are an AWS super fan. Can you tell us about that community and the program? >> Yeah, so I have been involved with AWS and building products with AWS since 2007. So it's kind of 15 years back when literally there were just a handful of API for launching EC2 instances and S3. >> Not the a hundred thousand that you mentioned earlier, my goodness, the scale. >> So I think I feel very privileged and honored that I have been part of that journey and have had to learn or have had the opportunity to learn both from successes and failures. And it's just my way of contributing back to that community. So we are part of the FinOps foundation as well, contributing through that. I run a podcast called AWS Insiders and a livestream called AWS Made Easy. So we are trying to make sure that people out there are able to understand how to leverage AWS in the best possible way. And yeah, we are there to help and hold their hand through it. >> Talk about the community, take a minute to explain to the audience watching the community around this cost optimization area. It's evolving, you mentioned FinOps. There's a whole large community developing, of practitioners and technologists coming together to look at this. What does this all mean? Talk about this community. >> So cost management within organizations is has evolved so drastically that organizations haven't really coped with it. Historically, you've had finance teams basically buy a lot of infrastructure, which is CapEx and the engineering teams had kind of an upper bound on what they would spend and where they would spend. Suddenly with cloud, that's kind of enabled so much innovation all of a sudden, everyone's realized it, five years was spent figuring out whether people should be on the cloud or not. That's no longer a question, right. Everyone needs to be in the cloud and I think that's a no-brainer. The problem there is that suddenly your operating model has moved from CapEx to OpEx. And organizations haven't really figured out how to deal with it. Finance now no longer has the controls to control and manage and forecast costs. Engineering has never had to deal with it in the past and suddenly now they have to figure out how to do all this finance stuff. And procurement finds itself in a very awkward way position because they are no longer doing these negotiations like they were doing in the past where it was okay right up front before you engage, you do these negotiations. Now it's kind of an ongoing thing and it's constantly changing. Like every day is different. >> And you got marketplace >> And you got marketplace. So it's a very complex situation and I think what we are trying to do with the FinOps foundation is try and take a lot of the best practices across organizations that have been doing this at least for the last 10, 15 years. Take all the learnings and failures and turn them into hopefully opinionated approaches that people can take organizations can take to navigate through this faster rather than kind of falter and then decide that oh, this is not for us. >> Yeah. It's a great model, it's a great model. >> I know it's time John, go ahead. >> All right so, we got a little bumper sticker exercise we used to say what's the bumper sticker for the show? We used to say that, now we're modernizing, we're saying if you had to do an Instagram reel right now, short hot take of what's going on at re:Invent this year with AMD or CloudFix or just in general what would be the sizzle reel, that would be on Instagram or TikTok, go. >> Look, I think when you're at re:Invent right now and number one the energy is fantastic. 23 is going to be a building year. We've got a lot of difficult times ahead financially but it's the time, the ones that come out of 23 stronger and more efficient, and cost optimize are going to survive the long run. So now's the time to build. >> Well done, Rahul let's go for it. >> Yeah, so like Brad said, cost and efficiencies at the top of everyone's mind. Stuff that's the low hanging fruit, easy, use automation. Apply your sources to do most of the innovation. Take the easiest part to realizing savings and operate as efficiently as you possibly can. I think that's got to be key. >> I think they nailed it. They both nailed it. Wow, well it was really good. >> I put you on our talent list of >> And alright, so we repeat them. Are you part of our host team? I love this, I absolutely love this Rahul we wish you the best at CloudFix and your 17 other jobs. And I am genuinely impressed. Do you sleep actually? Last question. >> I do, I do. I have an amazing team that really helps me with all of this. So yeah, thanks to them and thank you for having us here. >> It's been fantastic. >> It's our pleasure. And Brad, I'm delighted we get you both now and again on our next segment. Thank you for being here with us. >> Thank you very much. >> And thank you all for tuning in to our live coverage here at AWS re:Invent, in fabulous Sin City with John Furrier, my name's Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (calm music)

(bright upbeat music) >> Hey, friends. Welcome back to theCUBE's Live coverage of AWS re:Invent 2022 in Sin City. We are so excited to be here with tens of thousands of people. This is our third day of coverage, really the second full day of the show, but we started Monday night. You're going to get wall-to-wall coverage on theCUBE. You probably know that because you've been watching. I'm Lisa Martin and I'm here with Paul Gill. Paul, this is great. We have had such great conversations. We've been talking a lot about data. Every company is a data company, has to be a data company. We've been talking about developers, the developer experience, and how that's so influential in business decisions for businesses in every industry. >> And it's a key element of what's going on here on the floor at re:Invent is developers, the theme of developers just permeates the show. Lots and lots of boots here devoted to DevOps and Agile approaches. And certainly that is one of the things that the Cloud enables is your team to rethink the way they develop software, and that's what we're going to talk about next. >> That is what we're going to talk about next. We have two guests from Split. split.io is the URL if you want to check it out. Chris Demars joins us Developer advocate. Chris, great to have you and PaaS, VP of Engineering guys thank you so much for joining us on the program. >> Thank you for having us. >> Thank you for having us. >> Talk to us Pierre, we'll start with you. For the audience that might not know Split what does the company do? What's the value in it for customers? What are you all about? >> Sure. So in very simple terms, for those who are familiar, we do feature flags, feature management and experimentation. And essentially that two essential feature of the Agile transformation as you were mentioning and elements that really helps getting as much art we can from the team in term of productivity and in term of impact. And we basically help with those elements. And so that's a very short... >> 'Excellent, very nice. Chris, you were saying before we went live you do a lot of speaking at conferences, you're often in front of large audiences. As the developer advocate, what are some of the key requirements you're hearing from the developer community that organizations need to be encompassing? >> I think community is key. Like community is at the forefront of developer advocacy and developer relations. Like you want to go where the developers are and developers want to hear those stories in those personalized pieces of the puzzle. And when you're able to talk about modern Web and software technology and loop in product with that and still keep talking about those things and bring that to them, like that is on top of the list when it comes to developer advocacy and being embedded within the developer community. >> Lisa: Yeah. >> Tell us about feature flags, because I would assume that for our viewers who are not developers, who are not familiar with Agile technologies, the Agile approaches that might be, may be a new term, what are feature flags? How do you use them? >> Sure, I can start with that. So feature flag is a tool that you embed in your code that allows you to control the activation of your code essentially. And that's allows you to really validate things in a much better and solve way and also attach measurement to it. So, when you're writing your new feature, you just put essentially an if statement around it, if my feature flag is on, then I actually do all those things with soft, then I don't do any of those things and then within our platform, then you can control the activation. Do you want to turn it on for yourself just to try it out? Do you want your QA team to start validating it? Do you want 5% of your users 10%? And start seeing how they interacting with the product. That's what feature flag is. >> It's an amazing piece of any part of the stack, right? 'Cause I'm a Web accessibility and an UI specialist and being able to control the UI with a feature flag and being able to turn on and off those features based on percentage, locale, all of those things. It's very, very powerful. >> What are some of the scenarios which you would use feature flags? You have been testing? >> Yeah, yeah. We actually, you can imagine we use it for pretty much everything. So, as Chris was saying, in the front-end, everything you want to change, you basically can validate and attach measurements. So you can do AB testing, so you can see the impact, you can see if there is a change in performance. We use it also for a lot of backend services and changes and a lot of even infrastructure changes where we can control the traffic and where it goes. So we can validate that things are operating the way that they should before we fully done the market I think. >> 'It can be as small as, you know having a checkout button here and then writing an AB test and running an experiment and moving that checkout button somewhere else because then you can get conversion rates and see which one performed better to a certain amount of people and whatever performed better, that's the feature you would go with. >> Chris, talk about the value of the impact in feature flags for the developer from a developer experience perspective, a productivity perspective. >> So I think that having that feature and being able to write that UI, let's say that you have a checkout button, right? And there's specific content there's verbiage on that checkout button. And then let's say that another team within the organization wants to change that because the conversion is different. You can make those changes, still have it in production and then have it tested. So you don't have to cut specific branches or like test URLs to give to QA, you can do all of that behind that flag. And then once everything is good to go, push it out there and then based on those metrics and that data, see which one performs better and then that's the one that you would go with. >> One of the things with feature flag and it goes to like our main theme of 'What a Release, What a Relief' is that it gives autonomy to the teams and to the developers, enable them to move independently from others. So the deployment can go but their code is not activated until they decide to. And so, they are not impeding anybody else. It makes releases a lot safer, a lot simpler and it gives a lot more speed to everybody because when you do releases with five teams, 10 teams, pushing the code at the same time, you have such a high-risk of breaking something that it's you know... So it's a huge effort and it requires a lot of attention from a lot of people. If anything happens, all those teams needs to investigate. When you decouple all those things, the deployments are essentially not doing anything per se until every individual team activate those things independently. So if anything goes wrong, only them are affected and they don't have to depend on anybody else to get their thing out. So it really helps them making their life a lot safer and gives them a lot more speed because they have autonomy. >> So, why come to re:Invent? What do you get with this audience that you don't get elsewhere? >> Why to re:Invent? I think like re:Invent in the Cloud and AWS is a lot about getting speed to companies to build better product and faster. And essentially like the tool we provide and the technology and the platform we provide is really at the heart of that in itself. And so that's why we feel we have really great conversation with all the people on the floor. >> 'the people who have the right mindset for adopting... >> For me, it's very much community and networking, I love developer community and just community in general is my lifeblood. That's why I travel so much and I talk about these things and I'm with people and if it's not about the products, the story and the story is what gets people. That's why I love being here and being with my team and it's amazing. >> And what is that story? If you had an elevator pitch to give, what would you tell me? >> Hoo, if you were in a late release or deploy at night. I've been there, I'm sure you've been there, it doesn't matter what you're doing. We don't want be up until two, three in the morning doing those things, right? Our product helps alleviate those stresses. And you talking about accessibility, what I do, you know, a big piece of that are hidden impairments like anxiety will stress and anxiety go hand in hand and you want to alleviate that all across the board for everybody involved. >> As you see organizations shift Agile technologies and to parallel development and continuous release cycles, what are some of the biggest barriers they encounter in changing that mindset? >> Ooh, what do you think? >> It depends on where they are in the organization. The Agile transformation is a journey and it's also a change of mindset, it's a change of process. So depending on where they are then they might have some areas where they need a little bit more effort in those directions. What we see is that feature flag just the control of the layout. It's usually something that's fairly easily adopted. Thinking about measurement and attaching measurement to it is often something that requires a little bit more thinking. Like engineers are not really used to thinking about AB testing. It feels like more of a product management thing but AB testing is important also for performance informations like errors and all those things. There is a lot of risk management to be done. We do that through monitoring with APMs, but with feature flag and with Split, you can do that at a feature level and it really gives a great insight. And that's usually something that takes a little bit more digestion from the developers to really get their mind around it and get to it. But there's a lot of value to it. >> I'm looking at the split I/O website and I like the tagline shorten time from code to customer. As customers in any industry, as consumers, we have this expectation that we can get whatever we want anytime 24 by 7 and it's going to be a relevant experience. So it sounds to me like from a speed perspective, there's a lot of business impact that Split can help organizations make from getting releases faster, getting cut faster time-to-market, delivering what customers expect because we all expect real-time these days. Nobody wants to wait. >> Yeah, that's right. Yeah, I think that has to do with the going back to the decoupling of things that, you know... Not having to go through so many teams to have it tested and getting away from all the meetings about meetings to review the metrics, right? We all love meetings about meetings. >> No. (laughs loudly) >> Right, exactly, exactly. So being able to take that away and being able to push all of that stuff into production, getting it tested while it's in production and then being able to turn those features on, it's already there without having to do another deployment. And I think, like that's really powerful to me at least. >> Does your solution have value at the security level as well? >> Yes. So that's one of the particularity on the way we do things is like the way you control the feature flag, you have kind of two ways of doing it. Either the piece of code, the SDKs that we provide, the library we provide, you that you put in your code could come back to our platform and check. The way we do it is we send the rules back to the SDK so the whole evaluation is local. The evaluation is extremely fast and it's very secure because it's all happening within your environment. You never have to share any information, no PI whatsoever, contrary it to some of the other tools that you might find on the market. >> So the theme of the booth is 'What a Release, What a Relief'. What are some of the things that you're hearing as you're engaging folks on the show floor this week? >> Oh, what is Aura Photography and can I take a picture of. (everyone laughs loudly) I think just a lot of the stresses of... They're like the release cycle and you know, having to go through so many teams. I feel like that's a common theme that I've heard of. >> Yeah, we see a number of teams organization that still have like really big deployments with like a lot of teams basically coming together, pushing the code together, and there's a lot of pain in it. It's like, it's a huge effort by huge teams. You get 10, 20 people that have to have watch over it at always weird hours, and I think there is a lot of pain to that and that resonate a lot with people. And when we talk about monitoring at the future level, that also helps a lot. Like I was part of organizations before where we had a dedicated staff engineer to just monitor and fix performance on a daily basis because it's such a huge problem and it affects so much the performance of the company. And so essentially, you have this person that tries to look at is a performance being degraded today with the deployment of yesterday and what went out yesterday and you have so many things that went out. It's so hard to control. With what we provide, we tell you exactly which feature flag is responsible for the degradation. And so, you don't need that person to focus on that anymore. And you can focus on delivering value a lot better. >> I think it also might take away the need for extensive release notebooks and playbooks, right? 'Cause when you do bring all those teams together, it's certain people that are in that meeting and there's a PDF saying, all right, we check this off the list, we check this off the list. I think that might alleviate some of that overhead as well. >> Streamlining processes, process efficiencies, workforce productivity improvements, big impact. >> And that gets code quicker to the user. >> You talk about decoupling deploy from release. What do you mean by that? What's the value? >> So the deployment in my definition is essentially getting the code out to production. The release is activating the code in production. And often people do both of those things at the same time, right? But there's a huge risk when you do that because if anything goes wrong, now you need to revert everything which is not a short operation often and takes a lot of effort. And so now, if you can basically push your code to production but separate the activation of it, the release of it, then it goes a lot faster. It's a lot. You have a lot of autonomy and decoupling and if anything goes wrong, it's the click of a button and it's off. So like there's a lot of safety that comes with it and we know that any outages as a high cost for all the companies. So it's like, if you can reduce the outage to like five seconds... >> Right. >> It's a lot better than basically several hours. >> Can you talk about the value out of Split versus DIY and where are most of your customers in this process? Do they have a bunch of tools, a bunch of processes, a bunch of teams, and you're really helping them consolidate streamline? >> The one thing I hear a lot is we rolled our own AB testing and feature flagging system, but some of the issues I've seen and I've heard are that they don't have all those metrics or they have to work with a specific data team to get those metrics. And then you go back to having those meetings about meetings... >> Lisa: Dependencies. >> Right, you have a data team that's putting together a report that is then presented to you and then that's got to be presented to a stakeholder and then that stakeholder makes a decision whether to turn on feature A or feature B, right? Our product from my understanding is we have those metrics already built in and you can have that at your disposal. >> Yeah, the other thing I would add to that is like we see a number of people, they start on the feature flag journey just because they have a high risk thing that they need to put out. So they do the minimal thing to basically control it somehow, but it works only in one part of the stacks. They can't basically leverage it anywhere else and it's very limited in capability so that it just serve the purpose that was needed at that time. They don't have a dedicated team to manage it. So it just there, but it's very constrained and it's not supported effectively. The other thing is like for those companies is like they have a question to ask themselves. It's like do they want to invest resources in managing that kind of tool or is it not so core to their business that they want essentially to have vendor deal with it at a much lower price and they would have to invest resources for them to support it, and... >> Sounds like feature flags are kind of a team building. Have you have a team building dimension to them? >> Yeah. >> Yeah. >> It takes a team for sure. >> Yeah, and then once you add like AB testing and the feature flag, it's the collaboration between product management and engineering. It can go even further. Like two executives like to basically, you know, view the impact, understand the impact. So it goes from the control to the risk management to the product and to the impact and measuring the flow of delivery and the communication around it. >> Here we are at re:Invent, so many thousands of people as I mentioned, we're on the second full-day of the event. What have you heard from AWS that really excites you about being in their ecosystem? Any news in particular that jumps out at you that really speaks to improving that developer experience as if we've heard a lot of focus on the developer? >> Chris: Yeah, I haven't heard much, have you? >> So, I arrived yesterday, I haven't followed yet all the announcement, I'm just like, >> there's so many- >> on the news, yeah, yeah. >> So I'm on the booth at the same time. >> I stopped counting at 15 during the Keynote this morning. >> Many of them just can't keep up, there's so much happening at one time's so much. >> This event is a can of content, can of news re:Invent. It is hard. But yesterday they were spent so much time talking about data and how... And I always think every company today has to be a data company, have to be a software company, we were just talking with Capital One and they think of themselves as a technology company that does banking. And sometimes, I'll talk with retailers that think of themselves as technology companies that do retail and they love that but that's what companies like Split have to enable these days. It's companies to become technology companies, deliver code faster to customer because the customer's demanding it. We're not going to want less stuff slower. >> Yeah, I mean it's so essential I think for me like I joined Split because of that premises. Like every company now is a software company and every company has really to compete in innovation. You know all those banks, Capital One like we see it a lot in the financial industry where our message resonates extremely strongly is really in a high-competitive environment and they have to be innovative and innovation comes when people have speed and autonomy. And if you basically provide that to teams and the tools to basically get some signals and some quick feedback loop, that's how you get innovation. Like you can't decide what to build but you can basically provide the tools to enable them to think about. >> Right, you can experiment more flexibly right, faster. >> And developers have to be empowered, right? >> Yes. >> I think that's the probably one of the number one messages I've heard at all the shows we've done this year. How influential the developer is in the direction of the business. >> Autonomy and empowerment are two main factors 'cause I'm a front end developer at heart and I want to work on cool stuff and we're doing cool stuff. Like we are doing cool stuff. We can't talk about all of it, right? But I think we're doing a lot of cool things at Split and I'm really stoked to be a part of the team and grow developer relations, grow developer advocacy and be along for the journey. >> Yeah, I love that. Last question for both of you, same question. If you had a bumper sticker and you were going to put it on a fancy shiny new car, car of your choice about Split, what would it say? Pierre I'll start with you then Chris. >> Bumper sticker. >> On the spot question. >> On the question, (everyone laughs happily) I mean the easy answer is probably written on my t-shirt. Like, you know, 'What a Release, What a Relief'. I think that the first step for teams is like, you can have a message that's very like even further, you know, the Agile transformation is a journey and I basically tell people, you need to first crawl, walk and run and I think the 'What a Release, What a Relief' is a good step to like getting to the working. And I think like that would be the first bumper sticker before I get to the further one about AP testing and innovative. >> Love it. Chris, what would your bumper sticker say? >> It would say Split software, feature flags for the masses. Hard stop. >> Mic drop. >> Done. >> Awesome guys, thank you so much for joining Paul and me on the program. It's been outstanding introducing Split to our audience, what you do, how you're impacting the developer experience and ultimately, the business and the end customer on the backend who just wants things to work. We appreciate your insights, we appreciate your time. >> Thanks so much for having us. >> Appreciate it. >> Our pleasure. For our guests and Paul Gillin, I'm Lisa Martin. You're watching theCUBE, which you know is the leader in live enterprise and emerging tech coverage. (bright upbeat music)

>>Good afternoon and welcome back to the Classiest Show in Technology. This is the Cube we are at AWS Reinvent 2022 in Fabulous Sin City. That's why I've got my sequence on. We love a little Vegas, don't we? I'm joined by John Farer, another, another Vegas >>Fan. I don't have my sequence, I left it in my room. We're >>Gonna have to figure out how to get us 20 as soon as possible. What's been your biggest shock for you at the show so far? >>Well, I think the data story and security is so awesome. I love how that's front and center. If you look at the minutes of the keynote of Adamski, the CEO on day one, it's all bulked into data and security. All worked hand in hand. That's on top of already the innovation of their infrastructure. So I think you're gonna see a lot of interplay going on in this next segment. It's gonna tell a lot of that innovation story that's coming next. It's pretty awesome. >>It is pretty awesome, and I'm super excited. It's not only what we do here on the Cube, it's also in my show notes. We are gonna be geeking out for the next segment. Please welcome Paul and Puja. Wonderful to have you both here. Paul from Amazon, s3, glacier, and Pujan, CEO of kuo. I wanna turn to you Pujan, to start us off, just in case the audience isn't familiar, give us the Kuo pitch. >>Yeah, so basically Kuo is a, a backup as a service offering, right? Built in AWS four aws, right? And effectively going after, you know, any service that a customer uses on top of aws, right? And so a lot of the data sitting on s3, right? So that's been like our, our big use case going and basically building backup and air gap protection for, for s3. But we basically go to every other service, e c two, ebs, dynamo, you know, you name it, right? So basically do the whole thing >>And the relationship with aws. Can you guys share, I mean, you got you here together. You guys are a great partnership. Born in the cloud, operation in the cloud. Absolutely. I think talk about the partnership with aws. >>Absolutely. I think the last five years of building on AWS has been phenomenal, right? And I love the platform. It's, it's a very pure platform for us. You know, the APIs and, and the access you get and access you get to the service teams like Paul sitting here and the other teams you have gotten access to, I think has been phenomenal. But we also have, I would say, pushed the envelope in terms of how innovative we have been and how aggressive we have been in utilizing all the innovation that AWS has built in over the last few years. But it would not have happened without the fantastic partnership with the service teams. >>Paul, talk about the, AM the S3 part of this. What's the story there? >>Well, it's been great working with the CUO team over the course of the last few years. We were just upstairs diving deep into the, to the features that they're taking advantage of. They really push us hard on behalf of customers, and it's been a, it's just been a great relationship over the last years. >>That's awesome. And the ecosystem at such a, we're gonna hear tomorrow, the keynote on the, from Aruba who's gonna tend over the ecosystem. You guys are working together. There's a lot of strategic partnerships, so much collaboration between you guys that makes it very, this is the next gen cloud of cloud environment we're seeing. And you heard the, the economies around the corner. It's still gonna be challenging, but still there's more growth in the cloud. This is not stopping. This is impacts the customers. What are the customers saying to you guys when you work backwards from their needs? They want it faster, easier, cheaper. They want it more integrated. What are some of the things, all those you guys hearing from customers? >>So for us, you know, if you think about it, like, you know, as people are moving to the cloud, especially like take a use case like s3, right? So much of critical data sitting on top of S3 today. And so what folks have realized that as they're, you know, putting all of those, you know, what, over two 50 trillion objects, you know, sitting on s3, a lot of them need backup and data protection because there could be accidental deletions, there could be software bugs, there could be a ransomware type event due to which you need a second copy of the data that is outside of your security domain, right? But again, that needs to get be done at the, at the right price point, right? And that's where like a technology like Columbia comes in because since we've been built on the cloud, we've optimized it correctly. So especially for folks who are very cost conscious, given the macroeconomic conditions, we are heading into a technology that's built correctly so that, you know, you get the right architecture and the right solution at the right price point and the scale, right? Talking about trillions of objects, billions of objects within a single customer, within a single bucket sometimes. And that's where Columbia comes in. Cause we basically do that at scale without, again, impacting the, the customer's wallet more than it needs to. >>The porridge has to be the right temperature and the right size bowl. With the right spoon. You've got a lot of complexity when it comes to solving those customer challenges. You have a couple customer story examples you're allowed to share with us. Correct? Paul, do you want to kick one off? Go ahead. Oh, puja. All right. >>No, absolutely. I think there's a ton of them. I, I'll talk about, you know, want to begin with like Cox Automotive, right? A phenomenal customer that we, all of us have worked together with them. And again, looking for a solution to backup S3 to essentially go air gap protection outside of their account, right? They looked at doing it themselves, right? They thought they'll go and basically do it themselves. And then they fortunately bumped into Columbia, they looked at our architecture, looked at what it would really go and take to build it. And guess what, sitting in 2022, getting 23 right now, nobody wants to go and build this themselves. They actually want a turnkey solution that just does it, right? And so, again, we are a phenomenal joint customer of ours doing this at a pretty massive scale, right? And there are many more like that. There's Warner Brothers that are essentially going into the cloud from on premises, right? And they're going really fast accelerating the usage on aws again, looking at, you know, backup and data protection and using clum because of our extreme simplicity that we provide. >>Yeah, I think it's, you've got a, a lot of different people solving different problems that you're working with all the time. Millions of customers. Well, how do you prioritize? >>Well, for us, it really all comes down to fundamentals, right? So Amazon, s3 s unique distributed architecture delivers industry leading durability, availability, performance and security at virtually unlimited scale, right? And it's really been delivering on the fundamentals that has earned the trust of so many customers of all sizes and industries over the course of over 16 years. Now, in terms of how we prioritize on behalf of those customers, we always say that 90% of our roadmap comes directly from what customers are telling us is important. And a large number of our customers now are using S3 through lumino, which is why the relationship is so important. We're here talking about customer use cases here at the show, and we do that regularly throughout the year as well. And that's, that's how we land on a road. >>And what are the, what are the top stories from customers? What, what are they telling you? What's the number one top three things you're hearing? >>I tell you, like, again, it just comes down to the fundamentals, right? Of security, availability, durability and performance at virtually unlimited scale. Like that is the first customer first discussions that we have with customers talking about durable storage, for >>Sure. What I find interesting in, you mentioned scale, right? That comes up a lot scale with data. Yeah. That we heard data. The big theme here, security, what's in my S3 bucket? Can you find out what's in there? Is it backed up properly? How do I get it back? Where's the ransomware? Why not just target the ransomware? So how do you navigate the, the security challenges, the, the need to store all that scale data? What's the secret sauce? >>Yeah, so I think the, the big thing is we'll start with the, you know, how we have architected the product, right? If you think about it, this, you're dealing with a lot of scale, right? You get to a hundred million, a billion and billions very fast on S3 few, especially on a cloud native application. So it starts with the visibility, right? It's basically about, like we have things where you do, where you create a subset of your buckets called protection groups that you can essentially, you know, do it based on prefixes. So now you can essentially figure out what prefix you want to back up and what you don't want to back up. Maybe there's log data that you don't care about, so you don't back that up, right? And it all starts with that visibility that you give. And the prefix level data protection then comes the scale, which is where I was telling you, right? We have basically built an orchestration engine, right? It's like we call the ES for Lambdas, right? So we have a internal orchestration engine and essentially what what we have done is we have our own language internally that spawns off these lambdas, right? And they go after these S3 partitions do the right things and then you basically reel them back. So things like that that we do that are not possible if you're not built on the >>Clock. Well also, I mean, just mind blowing and go back 10 years. Yeah. I mean you got Lambda. What you're talking about here is the gift of the cloud innovation. Yeah. So the benefit of S3 is now accelerated. This is the story this year. Yeah. I mean they're highlighting it at scale, not just in the data, but like what we knew when Lambda came out and what S3 could do. But now mainstream solutions are coming in. Does that change your backup plans? Because we're gonna see a lot more end to end, lot more solutions. We heard that on the keynote. Some are saying it's more complexity. Of course it might, but you can abstract another way with the cloud that's the best part of the cloud. So these abstraction leads. So what's your view on that? But I wanna get your thoughts because you guys are perfectly positioned for this scale, but there's more coming. Yes. Yes. Exactly. What, how are you looking at that? >>So again, I think the, you know, obviously the, the S3 teams and every team in AWS is basically pushing the envelope in terms of innovation. But the key for a partner like us is to go and take that innovation. A lot of complex architectures behind the scene. But what you deliver to the customer is simple. I'll give you one more example. One of the things we launched that, you know, Paul and others are very excited about, is this ability to do instant access on the backup, right? So you could have billions of objects that you backed up. Maybe you need just 10,000 of them for a DR test. And we can basically create like an instant virtual bucket on top of that backup that you can instantly restore >>Spinning up a sandbox of temporary data to go check it >>Out. Exactly. Offer an inte application. >>Think we're geeking out right now. >>Yeah, I know. Brought that part of the segment, John. Don't worry, we're safely there. But, >>But that's the thing, right? That all that is possible because of all the, the scale and innovation and all the APIs and everything that, you know, Paul and the team gives us that we go and build on top of >>Paul, geek out on with us on this. We >>Are super excited for instant restore >>For store. I mean, automation programmability. >>It is, I mean it's the logical next step for backup in the cloud. Exactly. Yeah. But it's a super hard engineering problem to go solve for customers. I mean, the RTO benefits alone are super compelling, but then there's a cost element as well of not having to bring back all that stuff for a test restore, for example. And so it's, it's been really great to, to work with the team on that. We have some ideas on how we may help solve it from our side, and we're looking forward to collaborating on it. >>This is a great illustration of what I was writing about this week around the classic cloud, which is great. And as Adam said, and used like to use the word and, and you got this new functionality we're seeing emerge from the growth. Yes. From the companies that are built on Amazon web services that are growing. You're a partner, they have a lot of other partners and people are taking over restaurant here off action. I mean, there's real growth and new functionality on top of aws. You guys are no different. What's, are you prepared for that? Are you ready to go? >>Yeah, no, absolutely. And I think if you think about, if you think about it, right, I think it's also about doing this without impacting the primary application. Like if the customer is running a primary application at scale on s3, a backup application like ours can't come in and really mess with that. So I think being able to do things where, and this is where you solve really hard computer science problems, right? Where you're bottling yourself. If you are essentially seeing any kind of, you know, interfering with the primary, you're going to cut yourself down. You're gonna go after a different partition. So there are a lot of things you need to do behind the scenes, which is again, all the complexity, all of that, but deliver the, to the customer a very, very simple thing. >>You know, Paul, I wanna get your thoughts and I want you to chime in. Yeah. In 2014, I interviewed Steven Schmidt, my first interview with the, he was the CISO then, and now he's a CSO and, and former ciso, he's back at that time, the word was the cloud's not secure. Now we're talking about security. Just in the complexity of how you're partitioning and managing your sub portions, how you explained it, it's harder for the attackers. The cloud in its in its architecture has become a more secure environment. Yeah. Well, and getting more secure as you have laying out this, this is a new dynamic. This is good. Can you explain the, >>I mean, I, I can just tell you that at AWS security is job zero and that it will always be our number one priority, right? We have a, an infrastructure with under AWS that is vetted and approved to run even top secret workloads, which benefits all customers in all regions. >>And your, your security posture is embedded on top of that. And you got your own stuff. >>Yeah. And if you think of it as a shared responsibility model, so security of the cloud is the responsibility of the cloud provider, but then security of the data on top of it. Like you, you go and delete stuff, your software goes and does something that resiliency, the integrity of the data is your responsibility as a customer. And that's where, you know, we come in. Who >>Shared responsibility has been such a hot topic all week. Yeah. >>I gotta ask him one more question. Cause this is fascinating. And we are talking about on the cube all day today after we saw the announcement and Adam's comment on the cube, Adams LE's comment on the keynote. I mean, he said, if you're gonna tighten your belt, meaning economic cost recovery, re right sizing. If you want to tighten your belt, come to the cloud. So I have to ask you guys, Puja, if you can comment, that'd be great. There's a lot of other competitors out there that aren't born on aws. What is the customer gonna do when they tighten the build? What does that mean? They're gonna go to, to the individual contracts. They're gonna work in the marketplace. I mean this, there's a new dynamic in town. It's called AWS 2022. They weren't really around much in the recession of 2008. They were just starting to grow. Now they're an economic force. People like yourselves have embedded in there. There's a lot of competition. What's gonna happen? >>I think people are gonna just go to a place like, you know, AWS marketplace. You're going to essentially look for solutions and essentially like, and, and the right solutions built in are going to be self-service like aws. It's a very self-service thing. A hundred percent. So you go and do self-service, you figure out what's working, what's not working. Also, the model has to be consumption oriented. No longer can you expect the customer to go and pay a bunch of money for shelfware, right? It's like, like how we charge how AWS charges, which is you pay for what you consume. That and all has to be front and center, >>Right? I think that's a really, I think that's a really important >>Point. It's time >>And I think it's time. So we have a new challenge on the cube. We give you 30 seconds roughly to give us your extraordinarily hot take your shining thought leadership moment and, and highlight what you think is the most important takeaway from the show. The biggest soundbite, the juiciest announcement. Paul, I'll >>Start with an Instagram. Real basically. Yeah. Okay. >>Yeah. Hi. Go. I would just say from an S3 perspective, over the course of the last several years, we've really seen workloads shift from just backup and recovery and static images on websites to data lake analytics applications. And you continue to see that here. And I can tell you that some of these scaled applications are running at enormous mind blowing scale, right? And so, so every year we come here, we talk to customers, and it's just every year it sort of blows me away. And I've been in the storage industry for a long time and it's just is, it blows me away. Just the scale at customers are running in >>And >>Blowing scale. And when it comes to backup, let me just say that it's easy to back up and recover a single object, but doing an easy thing, a billion or 10 billion times over, that's actually quite hard. >>And just to, just to bold that a little bit, just pull out my highlighter. S3 now has over 280 trillion objects. That's a lot. >>That's a lot of objects. >>Yeah. You are not, you are not kidding. When you talk about scale, I mean, this is the most scalable. >>That's not solution's not there. Yeah. That, that's right. And we wake up every, we have a culture of durability and we wake up every single day to raise the bar on the fundamentals and make sure that every single one of those objects is protected and safe. >>Okay. You, I, >>I can't imagine worrying about two, two 80 trillion different things. >>Let's go. You're Instagram real >>For me again, you know, between S3 and us, we are two players out there that are really, you know, processing the data at the end of the day, right? And so I'm very excited about, you know, what we are going to do more and more with the instant restore capability where we can integrate third party services on top of it that can do more things with the data that is not, not passively sitting, but now becomes active data that you can analyze and do things with. So that's something where we take this to the next level is something that I'm super excited about. >>There's a lot to be excited about and, and we're excited to have you. We're excited to hear what happens next. Excited to see more collaboration like this. Paul Pon, thank you so much for joining us here on the show. Thank all of you from for tuning into our continuous wall to wall super thrilling live coverage of AWS reinvent here in fabulous Las Vegas, Nevada, with John Furrier. I'm Savannah Peterson. We're the cube, the leading source for high tech coverage.

>>Good evening everyone and welcome back to Sparkly Sin City, Las Vegas, Nevada, where we are here with the cube covering AWS Reinvent for the 10th year in a row. John Furrier has been here for all 10. John, we are in our last session of day one. How does it compare? >>I just graduated high school 10 years ago. It's exciting to be, here's been a long time. We've gotten a lot older. My >>Got your brain is complex. You've been a lot in there. So fast. >>Graduated eight in high school. You know how it's No. All good. This is what's going on. This next segment, wrapping up day one, which is like the the kickoff. The Mondays great year. I mean Tuesdays coming tomorrow big days. The announcements are all around the kind of next gen and you're starting to see partnering and integration is a huge part of this next wave cuz API's at the cloud, next gen cloud's gonna be deep engineering integration and you're gonna start to see business relationships and business transformation scale a horizontally, not only across applications but companies. This has been going on for a while, covering it. This next segment is gonna be one of those things that we're gonna look at as something that's gonna happen more and more on >>Yeah, I think so. It's what we've been talking about all day. Without further ado, I would like to welcome our very exciting guest for this final segment, trust from single store. Thank you for being here. And we also have him on from IBM Data and ai. Y'all are partners. Been partners for about a year. I'm gonna go out on a limb only because their legacy and suspect that a few people, a few more people might know what IBM does versus what a single store does. So why don't you just give us a little bit of background so everybody knows what's going on. >>Yeah, so single store is a relational database. It's a foundational relational systems, but the thing that we do the best is what we call us realtime analytics. So we have these systems that are legacy, which which do operations or analytics. And if you wanted to bring them together, like most of the applications want to, it's really a big hassle. You have to build an ETL pipeline, you'd have to duplicate the data. It's really faulty systems all over the place and you won't get the insights really quickly. Single store is trying to solve that problem elegantly by having an architecture that brings both operational and analytics in one place. >>Brilliant. >>You guys had a big funding now expanding men. Sequel, single store databases, 46 billion again, databases. We've been saying this in the queue for 12 years have been great and recently not one database will rule the world. We know that. That's, everyone knows that databases, data code, cloud scale, this is the convergence now of all that coming together where data, this reinvent is the theme. Everyone will be talking about end to end data, new kinds of specialized services, faster performance, new kinds of application development. This is the big part of why you guys are working together. Explain the relationship, how you guys are partnering and engineering together. >>Yeah, absolutely. I think so ibm, right? I think we are mainly into hybrid cloud and ai and one of the things we are looking at is expanding our ecosystem, right? Because we have gaps and as opposed to building everything organically, we want to partner with the likes of single store, which have unique capabilities that complement what we have. Because at the end of the day, customers are looking for an end to end solution that's also business problems. And they are very good at real time data analytics and hit staff, right? Because we have transactional databases, analytical databases, data lakes, but head staff is a gap that we currently have. And by partnering with them we can essentially address the needs of our customers and also what we plan to do is try to integrate our products and solutions with that so that when we can deliver a solution to our customers, >>This is why I was saying earlier, I think this is a a tell sign of what's coming from a lot of use cases where people are partnering right now you got the clouds, a bunch of building blocks. If you put it together yourself, you can build a durable system, very stable if you want out of the box solution, you can get that pre-built, but you really can't optimize. It breaks, you gotta replace it. High level engineering systems together is a little bit different, not just buying something out of the box. You guys are working together. This is kind of an end to end dynamic that we're gonna hear a lot more about at reinvent from the CEO ofs. But you guys are doing it across companies, not just with aws. Can you guys share this new engineering business model use case? Do you agree with what I'm saying? Do you think that's No, exactly. Do you think John's crazy, crazy? I mean I all discourse, you got out of the box, engineer it yourself, but then now you're, when people do joint engineering project, right? They're different. Yeah, >>Yeah. No, I mean, you know, I think our partnership is a, is a testament to what you just said, right? When you think about how to achieve realtime insights, the data comes into the system and, and the customers and new applications want insights as soon as the data comes into the system. So what we have done is basically build an architecture that enables that we have our own storage and query engine indexing, et cetera. And so we've innovated in our indexing in our database engine, but we wanna go further than that. We wanna be able to exploit the innovation that's happening at ibm. A very good example is, for instance, we have a native connector with Cognos, their BI dashboards right? To reason data very natively. So we build a hyper efficient system that moves the data very efficiently. A very other good example is embedded ai. >>So IBM of course has built AI chip and they have basically advanced quite a bit into the embedded ai, custom ai. So what we have done is, is as a true marriage between the engineering teams here, we make sure that the data in single store can natively exploit that kind of goodness. So we have taken their libraries. So if you have have data in single store, like let's imagine if you have Twitter data, if you wanna do sentiment analysis, you don't have to move the data out model, drain the model outside, et cetera. We just have the pre-built embedded AI libraries already. So it's a, it's a pure engineering manage there that kind of opens up a lot more insights than just simple analytics and >>Cost by the way too. Moving data around >>Another big theme. Yeah. >>And latency and speed is everything about single store and you know, it couldn't have happened without this kind of a partnership. >>So you've been at IBM for almost two decades, don't look it, but at nearly 17 years in how has, and maybe it hasn't, so feel free to educate us. How has, how has IBM's approach to AI and ML evolved as well as looking to involve partnerships in the ecosystem as a, as a collaborative raise the water level together force? >>Yeah, absolutely. So I think when we initially started ai, right? I think we are, if you recollect Watson was the forefront of ai. We started the whole journey. I think our focus was more on end solutions, both horizontal and vertical. Watson Health, which is more vertically focused. We were also looking at Watson Assistant and Watson Discovery, which were more horizontally focused. I think it it, that whole strategy of the world period of time. Now we are trying to be more open. For example, this whole embedable AI that CICE was talking about. Yeah, it's essentially making the guts of our AI libraries, making them available for partners and ISVs to build their own applications and solutions. We've been using it historically within our own products the past few years, but now we are making it available. So that, how >>Big of a shift is that? Do, do you think we're seeing a more open and collaborative ecosystem in the space in general? >>Absolutely. Because I mean if you think about it, in my opinion, everybody is moving towards AI and that's the future. And you have two option. Either you build it on your own, which is gonna require significant amount of time, effort, investment, research, or you partner with the likes of ibm, which has been doing it for a while, right? And it has the ability to scale to the requirements of all the enterprises and partners. So you have that option and some companies are picking to do it on their own, but I believe that there's a huge amount of opportunity where people are looking to partner and source what's already available as opposed to investing from the scratch >>Classic buy versus build analysis for them to figure out, yeah, to get into the game >>And, and, and why reinvent the wheel when we're all trying to do things at, at not just scale but orders of magnitude faster and and more efficiently than we were before. It, it makes sense to share, but it's, it is, it does feel like a bit of a shift almost paradigm shift in, in the culture of competition versus how we're gonna creatively solve these problems. There's room for a lot of players here, I think. And yeah, it's, I don't >>Know, it's really, I wanted to ask if you don't mind me jumping in on that. So, okay, I get that people buy a bill I'm gonna use existing or build my own. The decision point on that is, to your point about the path of getting the path of AI is do I have the core competency skills, gap's a big issue. So, okay, the cube, if you had ai, we'd take it cuz we don't have any AI engineers around yet to build out on all the linguistic data we have. So we might use your ai but I might say this to then and we want to have a core competency. How do companies get that core competency going while using and partnering with, with ai? What you guys, what do you guys see as a way for them to get going? Because I think some people probably want to have core competency of >>Ai. Yeah, so I think, again, I think I, I wanna distinguish between a solution which requires core competency. You need expertise on the use case and you need expertise on your industry vertical and your customers versus the foundational components of ai, which are like, which are agnostic to the core competency, right? Because you take the foundational piece and then you further train it and define it for your specific use case. So we are not saying that we are experts in all the industry verticals. What we are good at is like foundational components, which is what we wanna provide. Got it. >>Yeah, that's the hard deep yes. Heavy lift. >>Yeah. And I can, I can give a color to that question from our perspective, right? When we think about what is our core competency, it's about databases, right? But there's a, some biotic relationship between data and ai, you know, they sort of like really move each other, right? You >>Need, they kind of can't have one without the other. You can, >>Right? And so the, the question is how do we make sure that we expand that, that that relationship where our customers can operationalize their AI applications closer to the data, not move the data somewhere else and do the modeling and then training somewhere else and dealing with multiple systems, et cetera. And this is where this kind of a cross engineering relationship helps. >>Awesome. Awesome. Great. And then I think companies are gonna want to have that baseline foundation and then start hiring in learning. It's like driving the car. You get the keys when you're ready to go. >>Yeah, >>Yeah. Think I'll give you a simple example, right? >>I want that turnkey lifestyle. We all do. Yeah, >>Yeah. Let me, let me just give you a quick analogy, right? For example, you can, you can basically make the engines and the car on your own or you can source the engine and you can make the car. So it's, it's basically an option that you can decide. The same thing with airplanes as well, right? Whether you wanna make the whole thing or whether you wanna source from someone who is already good at doing that piece, right? So that's, >>Or even create a new alloy for that matter. I mean you can take it all the way down in that analogy, >>Right? Is there a structural change and how companies are laying out their architecture in this modern era as we start to see this next let gen cloud emerge, teams, security teams becoming much more focused data teams. Its building into the DevOps into the developer pipeline, seeing that trend. What do you guys see in the modern data stack kind of evolution? Is there a data solutions architect coming? Do they exist yet? Is that what we're gonna see? Is it data as code automation? How do you guys see this landscape of the evolving persona? >>I mean if you look at the modern data stack as it is defined today, it is too detailed, it's too OSes and there are way too many layers, right? There are at least five different layers. You gotta have like a storage you replicate to do real time insights and then there's a query layer, visualization and then ai, right? So you have too many ETL pipelines in between, too many services, too many choke points, too many failures, >>Right? Etl, that's the dirty three letter word. >>Say no to ETL >>Adam Celeste, that's his quote, not mine. We hear that. >>Yeah. I mean there are different names to it. They don't call it etl, we call it replication, whatnot. But the point is hassle >>Data is getting more hassle. More >>Hassle. Yeah. The data is ultimately getting replicated in the modern data stack, right? And that's kind of one of our thesis at single store, which is that you'd have to converge not hyper specialize and conversation and convergence is possible in certain areas, right? When you think about operational analytics as two different aspects of the data pipeline, it is possible to bring them together. And we have done it, we have a lot of proof points to it, our customer stories speak to it and that is one area of convergence. We need to see more of it. The relationship with IBM is sort of another step of convergence wherein the, the final phases, the operation analytics is coming together and can we take analytics visualization with reports and dashboards and AI together. This is where Cognos and embedded AI comes into together, right? So we believe in single store, which is really conversions >>One single path. >>A shocking, a shocking tie >>Back there. So, so obviously, you know one of the things we love to joke about in the cube cuz we like to goof on the old enterprise is they solve complexity by adding more complexity. That's old. Old thinking. The new thinking is put it under the covers, abstract the way the complexities and make it easier. That's right. So how do you guys see that? Because this end to end story is not getting less complicated. It's actually, I believe increasing and complication complexity. However there's opportunities doing >>It >>More faster to put it under the covers or put it under the hood. What do you guys think about the how, how this new complexity gets managed or in this new data world we're gonna be coming in? >>Yeah, so I think you're absolutely right. It's the world is becoming more complex, technology is becoming more complex and I think there is a real need and it's not just from coming from us, it's also coming from the customers to simplify things. So our approach around AI is exactly that because we are essentially providing libraries, just like you have Python libraries, there are libraries now you have AI libraries that you can go infuse and embed deeply within applications and solutions. So it becomes integrated and simplistic for the customer point of view. From a user point of view, it's, it's very simple to consume, right? So that's what we are doing and I think single store is doing that with data, simplifying data and we are trying to do that with the rest of the portfolio, specifically ai. >>It's no wonder there's a lot of synergy between the two companies. John, do you think they're ready for the Instagram >>Challenge? Yes, they're ready. Uhoh >>Think they're ready. So we're doing a bit of a challenge. A little 32nd off the cuff. What's the most important takeaway? This could be your, think of it as your thought leadership sound bite from AWS >>2023 on Instagram reel. I'm scrolling. That's the Instagram, it's >>Your moment to stand out. Yeah, exactly. Stress. You look like you're ready to rock. Let's go for it. You've got that smile, I'm gonna let you go. Oh >>Goodness. You know, there is, there's this quote from astrophysics, space moves matter, a matter tells space how to curve. They have that kind of a relationship. I see the same between AI and data, right? They need to move together. And so AI is possible only with right data and, and data is meaningless without good insights through ai. They really have that kind of relationship and you would see a lot more of that happening in the future. The future of data and AI are combined and that's gonna happen. Accelerate a lot faster. >>Sures, well done. Wow. Thank you. I am very impressed. It's tough hacks to follow. You ready for it though? Let's go. Absolutely. >>Yeah. So just, just to add what is said, right, I think there's a quote from Rob Thomas, one of our leaders at ibm. There's no AI without ia. Essentially there's no AI without information architecture, which essentially data. But I wanna add one more thing. There's a lot of buzz around ai. I mean we are talking about simplicity here. AI in my opinion is three things and three things only. Either you use AI to predict future for forecasting, use AI to automate things. It could be simple, mundane task, it would be complex tasks depending on how exactly you want to use it. And third is to optimize. So predict, automate, optimize. Anything else is buzz. >>Okay. >>Brilliantly said. Honestly, I think you both probably hit the 32nd time mark that we gave you there. And the enthusiasm loved your hunger on that. You were born ready for that kind of pitch. I think they both nailed it for the, >>They nailed it. Nailed it. Well done. >>I I think that about sums it up for us. One last closing note and opportunity for you. You have a V 8.0 product coming out soon, December 13th if I'm not mistaken. You wanna give us a quick 15 second preview of that? >>Super excited about this. This is one of the, one of our major releases. So we are evolving the system on multiple dimensions on enterprise and governance and programmability. So there are certain features that some of our customers are aware of. We have made huge performance gains in our JSON access. We made it easy for people to consume, blossom on OnPrem and hybrid architectures. There are multiple other things that we're gonna put out on, on our site. So it's coming out on December 13th. It's, it's a major next phase of our >>System. And real quick, wasm is the web assembly moment. Correct. And the new >>About, we have pioneers in that we, we be wasm inside the engine. So you could run complex modules that are written in, could be C, could be rushed, could be Python. Instead of writing the the sequel and SQL as a store procedure, you could now run those modules inside. I >>Wanted to get that out there because at coupon we covered that >>Savannah Bay hot topic. Like, >>Like a blanket. We covered it like a blanket. >>Wow. >>On that glowing note, Dre, thank you so much for being here with us on the show. We hope to have both single store and IBM back on plenty more times in the future. Thank all of you for tuning in to our coverage here from Las Vegas in Nevada at AWS Reinvent 2022 with John Furrier. My name is Savannah Peterson. You're watching the Cube, the leader in high tech coverage. We'll see you tomorrow.

(upbeat music) >> Good afternoon, fellow cloud nerds, and welcome back to theCUBE's live coverage of AWS re:Invent, here in a fabulous Sin City, Las Vegas, Nevada. My name is Savannah Peterson, joined by my fabulous co-host, John Furrier. John, how you feeling? >> Great, feeling good Just getting going. Day one of four more, three more days after today. >> Woo! Yeah. >> So much conversation. Talking about business transformation as cloud goes next level- >> Hot topic here for sure. >> Next generation. Data's classic is still around, but the next gen cloud's here, it's changing the game. Lot more AI, machine learning, a lot more business value. I think it's going to be exciting. Next segment's going to be awesome. >> It feels like one of those years where there's just a ton of momentum. I don't think it's just because we're back in person at scale, you can see the literally thousands of people behind us while we're here on set conducting these interviews. Our bold and brave guests, just like the two we have here, combating the noise, the libations, and everything else going on on the show floor. Please help me welcome Mike from Science Logic and Ajay from Zebrium. Gentlemen, welcome to the show floor. >> Thank you. >> Thank you Savannah. It's great to be here. >> How you feeling? Are you feeling the buzz, Mike? Feeling the energy? >> It's tough to not feel and hear the buzz, Savannah >> Savannah: Yeah. (all laughing) >> John: Can you hear me? >> Savannah: Yeah, yeah, yeah. Can you hear me now? What about you, Ajay? How's it feel to be here? >> Yeah, this is high energy. I'm really happy it's bounced back from COVID. I was a little concerned about attendance. This is hopping. >> Yeah, I feel it. It just, you can definitely feel the energy, the sense of community. We're all here for the right reasons. So I know that, I want to set the stage for everyone watching, Zebrium was recently acquired by Science Logic. Mike, can you tell us a little bit about that and what it means for the company? >> Mike: Sure, sure. Well, first of all, science logic, as you may know, has been in the monitoring space for a long time now, and what- >> Savannah: 20 years I believe. >> Yeah. >> Savannah: Just about. >> And what we've seen is a shift from kind of monitoring infrastructure, to monitoring these increasingly complex modern cloud native applications, right? And so this is part of a journey that we've been on at Science Logic to really modernize how enterprises of all sizes manage their IT estate. Okay? So, managing, now workloads that are increasingly in the public cloud, outside the four walls of the enterprise, workloads that are increasingly complex. They're microservices based, they're container based. >> Mhmm. >> Mike: And the rate of change, just because of things like CICD, and agile development has also increased the complexity in the typical IT environment. So all these things have conspired to make the traditional tools and processes of managing IT and IT applications much more difficult. They just don't scale. One of the things that we've seen recently, Savannah is this shift in sort of moving to cloud native applications, right? >> Huge shift. >> Mike: Today it only incorporates about roughly 25% of the typical IT portfolio, but most of the projections we've seen indicate that that's going to invert in about three years. 75% of applications will be what I call cloud native. And so this really requires different technologies to understand what's going on with those applications. And so Zebrium interested us when we were looking at partners at the beginning of this year as they have a super innovative approach to understanding really what's going on with any cloud native application. And they really distill, they separate the complexity out of the equation and they used machine learning to tremendous effect to rapidly understand the root cause of an application failure. And so I was introduced to Ajay, beginning of this year, actually. It feels like it's been a long time now. But we've been on this journey together throughout 2022, and we're thrilled to have Zebrium now, part of the Science Logic family. >> Ajay, Zebrium saves people a lot of time. Obviously, I've worked with developers and seen that struggle when things break, shortening that time to recovery and understanding is so critical. Can you tell us a little bit about what's under the hood and how the ML works to make that happen? >> Ajay: Yeah. So the goal is to figure out not just that something went wrong, but what went wrong. >> Savannah: Right. >> And we took, you know, based on a couple of decades of experience from my co-founders- >> Savannah: Casual couple of decades, came into went into this product just to call that out. Yeah, great. >> Exactly. It took some general learnings about the nature of software and when software breaks, what tends to happen, you tend to see unusual things happen, and they lead to bad things happening. It's very simple. >> Yes. >> It turns out- >> Savannah: Mutations lead to bad things happening, generally speaking. >> So what Zebrium's really good at is identifying those rare things accurately and then figuring out how they connect, or correlate to the bad things, the errors, the warnings, the alerts. So the machine learning has many stages to it, but at its heart it's classifying the event, catalog of any application stack, figuring out what's rare, and when things start to break it's telling you this cluster of events is both unusual, and unlikely to be random, and it's very likely the root cause report for the problem you're trying to solve. We then added some nice enhancements, such as correlation with knowledge spaces in, on the public internet. If someone's ever solved that problem before, we're able to find a match, and pull that back into our platform. But the at the heart, it was a technology that can find rare events and find the connections with other events. >> John: Yeah, and this is the theme of re:Invent this year, data, the role of data, solving end-to-end complexities. One, you mentioned that. Two, I think the Mike, your point about developers and the CICD pipeline is where DevOps is. That is what IT now is. So, if you take digital transformation to its conclusion, or its path and continue it, IT is DevOps. So the developers are actually doing the IT in their coding, hence the shift to autonomous IT. >> Mike: Right, right. Now, those other functions at IT used to be a department, not anymore, or they still are, so, but they'll go away, is security and data teams. You're starting to see the formation of- >> Mike: Yep. >> New replacements to IT as a function to support the developers who are building the applications that will be the company. >> That's right. Yeah. >> John: I mean that's, and do you agree with that statement? >> Yeah, I really do. And you know, collectively independent of whether it's like traditional IT, or it's DevOps, or whatever it is, the enterprise as a whole needs to understand how the infrastructure is deployed, the health of that infrastructure, and more importantly the applications that are hosted in the infrastructure. How are they doing? What's the health? And what we are seeing, and what we're trying to facilitate at Science Logic is really changed the lens of IT, from being low level compute, storage, and networking, to looking at everything through a services lens, looking at the services being delivered by IT, back to the business, and understanding things through a services lens. And Zebrium really compliments that mission that we've been on, by providing, cause a lot of cases, service equal equal application, and they can provide that kind of very real time view of service health in, you know, kind of the IT- >> And automation is beautiful there too, because, as you get into some of the scale- >> Yeah >> Ajay's. understanding how to do this fast is a key component. >> Yeah. So scale, you, you've pinpointed one of the dimensions that makes AI really important when it comes to troubleshooting. The humans just can't scale as fast as data, nor can they keep up with complexity of modern applications. And the third element that we feel is really important is the velocity with which people are now rolling out changes. People develop new features within hours, push them out to production. And in a world like that, the human has just no ability or time to understand what's normal, what's bad, to update their alert rules. And you need a machine, or an AI technology, to go help you with that. And that's basically what we're about. >> So this is where AI Ops comes in, right? Perfectly. Yeah. >> Yeah. You know, and John started to allude to it earlier, but having the insight on what's going on, we believe is only half of the equation, right? Once you understand what's going on, you naturally want to take action to remediate it or optimize it. And we believe automation should not be an exercise that's left to the reader. >> Yeah. >> As a lot of traditional platforms have done. Instead, we have a very robust, no-code, low-code automation built into our platform that allows you to take action in context with what you're seeing right then and there with the service. >> John: Yeah. Essentially monitoring, a term you use observability, some used as a fancy word today, is critical in all operating environments. So if we, if we kind of holistically, hey we're a distributed computing system, aka cloud, you got to track stuff at scale and you got to understand what it, what the impact is from a systems perspective. There's consequences to understanding what goes wrong. So as you look at that, what's the challenge for customers to do that? Because that seems to be the hard part as they lift and shift to the cloud, run their apps on the cloud, now they got to go take it to the next level, which is more developer velocity, faster productivity, and secure. >> Yeah. >> I mean, that seems to be the table stakes now. >> Yeah. >> How are companies forming around that? Are they there yet? Are they halfway there? Are they, where are they in the progression of, one, are they changing? And if so- >> Yeah that's a great question. I mean, I think whether it's an IT use case or a security use case, you can't manage what you don't know about. So visibility, discoverability, understanding what's going on, in a lot of ways that's the really hard problem to solve. And traditionally, we've approached that by like, harvesting data off of all these machines and devices in the infrastructure. But as we've seen with Zebrium and with related machine learning technologies, there's multiple ways of gaining insight as to what's going on. Once you have the insight be it an IT issue, like a service outage, or a security vulnerability, then you can take action. And the idea is you want to make that action as seamless as possible. But I think to answer your question, John, enterprises are still kind of getting their heads around how can we break down all the silos that have built up over the last decade or two, internally, and get visibility across the estate that really matters. And I think that's the real challenge. >> And I mean, and, at the velocity that applications are growing, just looking at our notes here, number of applications scaling from 64 million in 2017 to 147 million in 2021. That goes to what you were talking about, even with those other metrics earlier, 582 million by 2026 is what Morgan Stanley predicts. So, not only do we need to get out of silos we need to be able to see everything all the time, all at once, from the past legacy, as well as as we extend at scale. How are you thinking about that, Ajay? You're now with a big partner as an umbrella. What's next for you all? How, how are you going to help people solve problems faster? >> Yeah, so one of the attractions to the Zebrium team about Science Logic, aside from the team, and the culture, was the product portfolio was so complimentary. As Mike mentioned, you need visibility, you need mapping from low level building blocks to business services. And the end, at the end of the spectrum, once you know something's wrong you need to be able to take action automatically. And again, Science Logic has a very strong product, set of product capabilities and automated actions. What we bring to the table is the middle layer, which is from visibility, understanding what went wrong, figuring out the root cause. So to us, it was really exciting to be a very nice tuck in into this broader platform where we helped complete the story. >> Savannah: Yeah, that's, that's exciting. >> John: Should we do the Insta challenge? >> I was just getting ready to do that. You go for it John. You go ahead and kick it off. >> So we have this little tradition now, Instagram real, short and sweet. If you were going to see yourself on Instagram, what would be the Instagram reel of why this year's re:Invent is so important, and why people should pay attention to what's going on right now in the industry, or your company? >> Well, I think partly what Ajay was saying it's good to be back, right? So seeing just the energy and being back in 3D, you know en mass, is awesome again. It really is. >> Yeah. >> Mike: But, you know, I think this is where it's happening. We are at an inflection point of our industry and we're seeing a sea change in the way that applications and software delivered to businesses, to enterprises. And it's happening right here. This is the nexus of it. And so we're thrilled to be here as a part of all this, and excited about the future. >> All right, Ajay- >> Well done. He passes >> Your Instagram reel. >> Knowing what's happening in the broader economy, in the business context, it's, it feels even more important that companies like us are working on technologies that empower the same number of people to do more. Because it may not be realistic to just add on more headcount given what's going on in the world. But your deliverables and your roadmaps aren't slowing down. So, still the same amount of complexity, the same growth rates, but you're going to have to deal with all of that with fewer resources and be smarter about it. So, the approaches we're taking feel very much off the moment, you know, given what's going on in the real world. >> I love it. I love it. I've got, I've got kind of a finger to the wind, potentially hardball question for you here to close it out. But, given that you both have your finger really on the pulse right here, what percentage of current IT operations do you think will eventually be automated by AI and ML? Or AI ops? >> Well, I think a large percentage of traditional IT operations, and I'm talking about, you know, network operating center type of, you know, checking heartbeat monitors of compute storage and networking health. I think a lot of those things are going to be automated, right? Machine learning, just because of the scale. You can't scale, you can't hire enough NOC engineers to scale that kind of complexity. But I think IT talents, and what they're going to be focusing on is going shift, and they're going to be focusing on different parts. And I believe a lot of IT is going to be a much more of an enabler for the business, versus just managing things when they go wrong. So that's- >> All right. >> That's what I believe is part of the change. >> That's your, all right Ajay what about your hot take? >> Knowing how error-prone predictions are, (all laughing) I'll caveat my with- >> Savannah: We're allowing for human error here. >> I could be wildly wrong, but if I had to guess, you know, in 10 years you know, as much as 50% of the tasks will be automated. >> Mike: Oh, you- >> I love it. >> Mike: You threw a number out there. >> I love it. I love that he put his finger out- >> You got to see, you got to say the matrix. We're all going to be part of the matrix. >> Well, you know- >> And Star Trek- >> Skynet >> We can only turn back to this footage in a few years and quote you exactly when you have the, you know Mackenzie Research or the Morgan Stanley research that we've been mentioning here tonight and say that you've called it accurately. So I appreciate that. Ajay, it was wonderful to have you here. Congratulations on the acquisition. Thank you. Mike, thank you so much for being here on the Science Logic side, and congratulations to the team on 20 years. That's very exciting. John. Thank you. >> I try, I tried. Thank you. >> You try, you succeed. And thank you to all of our fabulous viewers out there at home. Be sure and tweet us at theCUBE. Say hello, Furrier, Sav is savvy. Let us know what you're thinking of AWS re:Invent where we are live from Las Vegas all week. You're watching theCUBE, the leader in high tech coverage. My name's Savannah Peterson, and we'll see you soon. (upbeat music)

(upbeat music) >> Announcer: Live from Las Vegas, it's theCUBE! Covering UIPath FORWARD America's 2019. Brought to you by UIPath. >> Welcome back, everyone, to theCUBE's live coverage of UIPath FORWARD, here in Sin City, Las Vegas Nevada. I'm your host, Rebecca Knight, co-hosting alongside Dave Velante. We have two guests for this segment. We have Kurt Carlson, Associate Dean for faculty and academic affairs of the Mason School of Business at the college of William and Mary. Thanks for coming on the show. >> Thanks you for having me. >> Rebecca: And we have Tom Clancy, the SVP of learning at UIPath, thank you so much. >> Great to be here. >> You're a Cube alum, so thank you for coming back. >> I've been here a few times. >> A Cube veteran, I should say. >> I think 10 years or so >> So we're talking today about a robot for every student, this was just announced in August, William and Mary is the first university in the US to provide automation software to every undergraduate student, thanks to a four million dollar investment from UIPath. Tell us a little bit about this program, Kurt, how it works and what you're trying to do here. >> Yeah, so first of all, to Tom and the people at UIPath for making this happen. This is a bold and incredible initiative, one that, frankly, when we had it initially, we thought that maybe we could get a robot for every student, we weren't sure that other people would be willing to go along with that, but UIPath was, they see the vision, and so it was really a meeting of the minds on a common purpose. The idea was pretty simple, this technology is transforming the world in a way that students, we think it's going to transform the way that students actually are students. But it's certainly transforming the world that our students are going into. And so, we want to give them exposure to it. We wanted to try and be the first business school on the planet that actually prepares students not just for the way RPA's being used today, but the way that it's going to be used when AI starts to take hold, when it becomes the gateway to AI three, four, five years down the road. So, we talked to UIPath, they thought it was a really good idea, we went all in on it. Yeah, all of our starting juniors in the business school have robots right now, they've all been trained through the academy live session putting together a course, it's very exciting. >> So, Tom, you've always been an innovator when it comes to learning, here's my question. How come we didn't learn this school stuff when we were in college? We learned Fortran. >> I don't know, I only learned BASIC, so I can't speak to that. >> So you know last year we talked about how you're scaling, learning some of the open, sort of philosophy that you have. So, give us the update on how you're pushing learning FORWARD, and why the College of William and Mary. >> Okay, so if you buy into a bot for every worker, or a bot for every desktop, that's a lot of bots, that's a lot of desktops, right? There's studies out there from the research companies that say that there's somewhere a hundred and 200 million people that need to be educated on RPA, RPA/AI. So if you buy into that, which we do, then traditional learning isn't going to do it. We're going to miss the boat. So we have a multi-pronged approach. The first thing is to democratize RPA learning. Two and a half years ago we made, we created RPA Academy, UIPath academy, and 100% free. After two and a half years, we have 451,000 people go through the academy courses, that's huge. But we think there's a lot more. Over the next next three years we think we'll train at least two million people. But the challenge still is, if we train five million people, there's still a hundred million that need to know about it. So, the second biggest thing we're doing is, we went out, last year at this event, we announced our academic alliance program. We had one university, now we're approaching 400 universities. But what we're doing with William and Mary is a lot more than just providing a course, and I'll let Kurt talk to that, but there is so much more that we could be doing to educate our students, our youth, upscaling, rescaling the existing workforce. When you break down that hundred million people, they come from a lot of different backgrounds, and we're trying to touch as many people as we can. >> You guys are really out ahead of the curve. Oftentimes, I mean, you saw this a little bit with data science, saw some colleges leaning in. So what lead you guys to the decision to actually invest and prioritize RPA? >> Yeah, I think what we're trying to accomplish requires incredibly smart students. It requires students that can sit at the interface between what we would think of today as sort of an RPA developer and a decision maker who would be stroking the check or signing the contract. There's got to be somebody that sits in that space that understands enough about how you would actually execute this implementation. What's the right buildout of that, how we're going to build a portfolio of bots, how we're going to prioritize the different processes that we might automate, How we're going to balance some processes that might have a nice ROI but be harder for the individual who's process is being automated to absorb against processes that the individual would love to have automated, but might not have as great of an ROI. How do you balance that whole set of things? So what we've done is worked with UIPath to bring together the ideas of automation with the ideas of being a strategic thinker in process automation, and we're designing a course in collaboration to help train our students to hit the ground running. >> Rebecca, it's really visionary, isn't it? I mean it's not just about using the tooling, it's about how to apply the tooling to create competitive advantage or change lives. >> I used to cover business education for the Financial Times, so I completely agree that this really is a game changer for the students to have this kind of access to technology and ability to explore this leading edge of software robotics and really be, and graduate from college. This isn't even graduate school, they're graduating from college already having these skills. So tell me, Kurt, what are they doing? What is the course, what does it look like, how are they using this in the classroom? >> The course is called a one credit. It's 14 hours but it actually turns into about 42 when you add this stuff that's going on outside of class. They're learning about these large conceptual issues around how do you prioritize which processes, what's the process you should go through to make sure that you measure in advance of implementation so that you can do an audit on the backend to have proof points on the effectiveness, so you got to measure in advance, creating a portfolio of perspective processes and then scoring them, how do you do that, so they're learning all that sort of conceptual straight business slash strategy implementation stuff, so that's on the first half, and to keep them engaged with this software, we're giving them small skills, we're calling them skillets. Small skills in every one of those sessions that add up to having a fully automated and programmed robot. Then they're going to go into a series of days where every one of those days they're going to learn a big skill. And the big skills are ones that are going to be useful for the students in their lives as people, useful in lives as students, and useful in their lives as entrepreneurs using RPA to create new ventures, or in the organizations they go to. We've worked with UIPath and with our alums who've implement this, folks at EY, Booz. In fact, we went up to DC, we had a three hour meeting with these folks. So what are the skills students need to learn, and they told us, and so we build these three big classes, each around each one of those skills so that our students are going to come out with the ability to be business translators, not necessarily the hardcore programmers. We're not going to prevent them from doing that, but to be these business translators that sit between the programming and the decision makers. >> That's huge because, you know, like, my son's a senior in college. He and his friends, they all either want to work for Amazon, Google, an investment bank, or one of the big SIs, right? So this is a perfect role for a consultant to go in and advise. Tom, I wanted to ask you, and you and I have known each other for a long time, but one of the reasons I think you were successful at your previous company is because you weren't just focused on a narrow vendor, how to make metrics work, for instance. I presume you're taking the same philosophy here. It transcends UIPath and is really more about, you know, the category if you will, the potential. Can you talk about that? >> So we listen to our customers and now we listen to the universities too, and they're going to help guide us to where we need to go. Most companies in tech, you work with marketing, and you work with engineering, and you build product courses. And you also try to sell those courses, because it's a really good PNL when you sell training. We don't think that's right for the industry, for UIPath, or for our customers, or our partners. So when we democratize learning, everything else falls into place. So, as we go forward, we have a bunch of ideas. You know, as we get more into AI, you'll see more AI type courses. We'll team with 400 universities now, by end of next year, we'll probably have a thousand universities signed up. And so, there's a lot of subject matter expertise, and if they come to us with ideas, you mentioned a 14 hour course, we have a four hour course, and we also have a 60 hour course. So we want to be as flexible as possible, because different universities want to apply it in different ways. So we also heard about Lean Six Sigma. I mean, sorry, Lean RPA, so we might build a course on Lean RPA, because that's really important. Solution architect is one of the biggest gaps in the industry right now so, so we look to where these gaps are, we listen to everybody, and then we just execute. >> Well, it's interesting you said Six Sigma, we have Jean Younger coming on, she's a Six Sigma expert. I don't know if she's a black belt, but she's pretty sure. She talks about how to apply RPA to make business processes in Six Sigma, but you would never spend the time and money, I mean, if it's an airplane engine, for sure, but now, so that's kind of transformative. Kurt, I'm curious as to how you, as a college, market this. You know, you're very competitive industry, if you will. So how do you see this attracting students and separating you guys from the pack? >> Well, it's a two separate things. How do we actively try to take advantage of this, and what effects is it having already? Enrollments to the business school, well. Students at William and Mary get admitted to William and Mary, and they're fantastic, amazingly good undergraduate students. The best students at William and Mary come to the Raymond A. Mason school of business. If you take our undergraduate GPA of students in the business school, they're top five in the country. So what we've seen since we've announced this is that our applications to the business school are up. I don't know that it's a one to one correlation. >> Tom: I think it is. >> I believe it's a strong predictor, right? And part because it's such an easy sell. And so, when we talk to those alums and friends in DC and said, tell us why this is, why our students should do this, they said, well, if for no other reason, we are hiring students that have these skills into data science lines in the mid 90s. When I said that to my students, they fell out of their chairs. So there's incredible opportunity here for them, that's the easy way to market it internally, it aligns with things that are happening at William and Mary, trying to be innovative, nimble, and entrepreneurial. We've been talking about being innovative, nimble, and entrepreneurial for longer than we've been doing it, we believe we're getting there, we believe this is the type of activity that would fit for that. As far as promoting it, we're telling everybody that will listen that this is interesting, and people are listening. You know, the standard sort of marketing strategy that goes around, and we are coordinating with UIPath on that. But internally, this sells actually pretty easy. This is something people are looking for, we're going to make it ready for the world the way that it's going to be now and in the future. >> Well, I imagine the big consultants are hovering as well. You know, you mentioned DC, Booz Allen, Hughes and DC, and Excensior, EY, Deloitte, PWC, IBM itself. I mean it's just, they all want the best and the brightest, and now you're going to have this skill set that is a sweet spot for their businesses. >> Kurt: That's the plan. >> I'm just thinking back to remembering who these people are, these are 19 and 20 year olds. They've never experienced the dreariness of work and the drudge tasks that we all know well. So, what are you, in terms of this whole business translator idea, that they're going to be the be people that sit in the middle and can sort of be these people who can speak both languages. What kind of skills are you trying to impart to them, because it is a whole different skill set. >> Our vision is that in two or three years, the nodes and the processes that are currently... That currently make implementing RPA complex and require significant programmer skills, these places where, right now, there's a human making a relatively mundane decision, but it's sill a model. There's a decision node there. We think AI is going to take over that. The simple, AI's going to simply put models into those decision nodes. We also think a lot of the programming that takes place, you're seeing it now with studio X, a lot of the programming is going to go away. And what that's going to do is it's going to elevate the business process from the mundane to the more human intelligent, what would currently be considered human intelligence process. When we get into that space, people skills are going to be really important, prioritizing is going to be really important, identifying organizations that are ripe for this, at this moment in time, which processes to automate. Those are the kind of skills we're trying to get students to develop, and what we're selling it partly as, this is going to make you ready of the world the way we think it's going to be, a bit of a guess. But we're also saying if you don't want to automate mundane processes, then come with us on a different magic carpet ride. And that magic carpet ride is, imagine all the processes that don't exist right now because nobody would ever conceive of them because they couldn't possibly be sustained, or they would be too mundane. Now think about those processes through a business lens, so take a business student and think about all the potential when you look at it that way. So this course that we're building has that, everything in the course is wrapped in that, and so, at the end of the course, they're going to be doing a project, and the project is to bring a new process to the world that doesn't currently exist. Don't program it, don't worry about whether or not you have a team that could actually execute it. Just conceive of a process that doesn't currently exist and let's imagine, with the potential of RPA, how we would make that happen. That's going to be, we think we're going to be able to bring a lot of students along through that innovative lens even though they are 19 and 20, because 19 and 20 year olds love innovation, while they've never submitted a procurement report. >> Exactly! >> A innovation presentation. >> We'll need to do a Cube follow up with that. >> What Kurt just said, is the reason why, Tom, I think this market is being way undercounted. I think it's hard for the IDCs and the forces, because they look back they say how big was it last year, how fast are these companies growing, but, to your point, there's so much unknown processes that could be attacked. The TAM on this could be enormous. >> We agree. >> Yeah, I know you do, but I think that it's a point worth mentioning because it touches so many different parts of every organization that I think people perhaps don't realize the impact that it could have. >> You know, when listening to you, Kurt, when you look at these young kids, at least compared to me, all the coding and setting up a robot, that's the easy part, they'll pick that up right away. It's really the thought process that goes into identifying new opportunities, and that's, I think, you're challenging them to do that. But learning how to do robots, I think, is going to be pretty easy for this new digital generation. >> Piece of cake. Tom and Kurt, thank you so much for coming on theCUBE with a really fascinating conversation. >> Thank you. >> Thanks, you guys >> I'm Rebecca Knight, for Dave Velante, stay tuned for more of theCUBEs live coverage of UIPath FORWARD. (upbeat music)