>>Hey everyone. Welcome back to Las Vegas. It's the Cube live at AWS Reinvent 2022. This is our fourth day of coverage. Lisa Martin here with Paul Gillen. Paul, we started Monday night, we filmed and streamed for about three hours. We have had shammed pack days, Tuesday, Wednesday, Thursday. What's your takeaway? >>We're routed final turn as we, as we head into the home stretch. Yeah. This is as it has been since the beginning, this show with a lot of energy. I'm amazed for the fourth day of a conference, how many people are still here I am too. And how, and how active they are and how full the sessions are. Huge. Proud for the keynote this morning. You don't see that at most of the day four conferences. Everyone's on their way home. So, so people come here to learn and they're, and they're still >>Learning. They are still learning. And we're gonna help continue that learning path. We have an alumni back with us, Toron joins us, the CPO and co-founder of Dremeo. Tomer, it's great to have you back on the program. >>Yeah, thanks for, for having me here. And thanks for keeping the, the best session for the fourth day. >>Yeah, you're right. I like that. That's a good mojo to come into this interview with Tomer. So last year, last time I saw you was a year ago here in Vegas at Reinvent 21. We talked about the growth of data lakes and the data lake houses. We talked about the need for open data architectures as opposed to data warehouses. And the headline of the Silicon Angle's article on the interview we did with you was, Dremio Predicts 2022 will be the year open data architectures replace the data warehouse. We're almost done with 2022. Has that prediction come true? >>Yeah, I think, I think we're seeing almost every company out there, certainly in the enterprise, adopting data lake, data lakehouse technology, embracing open source kind of file and table formats. And, and so I think that's definitely happening. Of course, nothing goes away. So, you know, data warehouses don't go away in, in a year and actually don't go away ever. We still have mainframes around, but certainly the trends are, are all pointing in that direction. >>Describe the data lakehouse for anybody who may not be really familiar with that and, and what it's, what it really means for organizations. >>Yeah. I think you could think of the data lakehouse as the evolution of the data lake, right? And so, you know, for, for, you know, the last decade we've had kind of these two options, data lakes and data warehouses and, you know, warehouses, you know, having good SQL support, but, and good performance. But you had to spend a lot of time and effort getting data into the warehouse. You got locked into them, very, very expensive. That's a big problem now. And data lakes, you know, more open, more scalable, but had all sorts of kind of limitations. And what we've done now as an industry with the Lake House, and especially with, you know, technologies like Apache Iceberg, is we've unlocked all the capabilities of the warehouse directly on object storage like s3. So you can insert and update and delete individual records. You can do transactions, you can do all the things you could do with a, a database directly in kind of open formats without getting locked in at a much lower cost. >>But you're still dealing with semi-structured data as opposed to structured data. And there's, there's work that has to be done to get that into a usable form. That's where Drio excels. What, what has been happening in that area to, to make, I mean, is it formats like j s o that are, are enabling this to happen? How, how we advancing the cause of making semi-structured data usable? Yeah, >>Well, I think first of all, you know, I think that's all changed. I think that was maybe true for the original data lakes, but now with the Lake house, you know, our bread and butter is actually structured data. It's all, it's all tables with the schema. And, you know, you can, you know, create table insert records. You know, it's, it's, it's really everything you can do with a data warehouse you can now do in the lakehouse. Now, that's not to say that there aren't like very advanced capabilities when it comes to, you know, j s O and nested data and kind of sparse data. You know, we excel in that as well. But we're really seeing kind of the lakehouse take over the, the bread and butter data warehouse use cases. >>You mentioned open a minute ago. Talk about why it's, why open is important and the value that it can deliver for customers. >>Yeah, well, I think if you look back in time and you see all the challenges that companies have had with kind of traditional data architectures, right? The, the, the, a lot of that comes from the, the, the problems with data warehouses. The fact that they are, you know, they're very expensive. The data is, you have to ingest it into the data warehouse in order to query it. And then it's almost impossible to get off of these systems, right? It takes an enormous effort, tremendous cost to get off of them. And so you're kinda locked in and that's a big problem, right? You also, you're dependent on that one data warehouse vendor, right? You can only do things with that data that the warehouse vendor supports. And if you contrast that to data lakehouse and open architectures where the data is stored in entirely open formats. >>So things like par files and Apache iceberg tables, that means you can use any engine on that data. You can use s SQL Query Engine, you can use Spark, you can use flin. You know, there's a dozen different engines that you can use on that, both at the same time. But also in the future, if you ever wanted to try something new that comes out, some new open source innovation, some new startup, you just take it and point out the same data. So that data's now at the core, at the center of the architecture as opposed to some, you know, vendors logo. Yeah. >>Amazon seems to be bought into the Lakehouse concept. It has big announcements on day two about eliminating the ETL stage between RDS and Redshift. Do you see the cloud vendors as pushing this concept forward? >>Yeah, a hundred percent. I mean, I'm, I'm Amazon's a great, great partner of ours. We work with, you know, probably 10 different teams there. Everything from, you know, the S3 team, the, the glue team, the click site team, you know, everything in between. And, you know, their embracement of the, the, the lake house architecture, the fact that they adopted Iceberg as their primary table format. I think that's exciting as an industry. We're all coming together around standard, standard ways to represent data so that at the end of the day, companies have this benefit of being able to, you know, have their own data in their own S3 account in open formats and be able to use all these different engines without losing any of the functionality that they need, right? The ability to do all these interactions with data that maybe in the past you would have to move the data into a database or, or warehouse in order to do, you just don't have to do that anymore. Speaking >>Of functionality, talk about what's new this year with drio since we've seen you last. >>Yeah, there's a lot of, a lot of new things with, with Drio. So yeah, we now have full Apache iceberg support, you know, with DML commands, you can do inserts, updates, deletes, you know, copy into all, all that kind of stuff is now, you know, fully supported native part of the platform. We, we now offer kind of two flavors of dr. We have, you know, Dr. Cloud, which is our SaaS version fully hosted. You sign up with your Google or, you know, Azure account and, and, and you're up in, you're up and running in, in, in a minute. And then dral software, which you can self host usually in the cloud, but even, even even outside of the cloud. And then we're also very excited about this new idea of data as code. And so we've introduced a new product that's now in preview called Dr. >>Arctic. And the idea there is to bring the concepts of GI or GitHub to the world of data. So things like being able to create a branch and work in isolation. If you're a data scientist, you wanna experiment on your own without impacting other people, or you're a data engineer and you're ingesting data, you want to transform it and test it before you expose it to others. You can do that in a branch. So all these ideas that, you know, we take for granted now in the world of source code and software development, we're bringing to the world of data with Jamar. And when you think about data mesh, a lot of people talking about data mesh now and wanting to kind of take advantage of, of those concepts and ideas, you know, thinking of data as a product. Well, when you think about data as a product, we think you have to manage it like code, right? You have to, and that's why we call it data as code, right? The, all those reasons that we use things like GI have to build products, you know, if we wanna think of data as a product, we need all those capabilities also with data. You know, also the ability to go back in time. The ability to undo mistakes, to see who changed my data and when did they change that table. All of those are, are part of this, this new catalog that we've created. >>Are you talk about data as a product that's sort of intrinsic to the data mesh concept. Are you, what's your opinion of data mesh? Is the, is the world ready for that radically different approach to data ownership? >>You know, we are now in dozens of, dozens of our customers that are using drio for to implement enterprise-wide kind of data mesh solutions. And at the end of the day, I think it's just, you know, what most people would consider common sense, right? In a large organization, it is very hard for a centralized single team to understand every piece of data, to manage all the data themselves, to, you know, make sure the quality is correct to make it accessible. And so what data mesh is first and foremost about is being able to kind of federate the, or distribute the, the ownership of data, the governance of the data still has to happen, right? And so that is, I think at the heart of the data mesh, but thinking of data as kind of allowing different teams, different domains to own their own data to really manage it like a product with all the best practices that that we have with that super important. >>So we we're doing a lot with data mesh, you know, the way that cloud has multiple projects and the way that Jamar allows you to have multiple catalogs and different groups can kind of interact and share data among each other. You know, the fact that we can connect to all these different data sources, even outside your data lake, you know, with Redshift, Oracle SQL Server, you know, all the different databases that are out there and join across different databases in addition to your data lake, that that's all stuff that companies want with their data mesh. >>What are some of your favorite customer stories that where you've really helped them accelerate that data mesh and drive business value from it so that more people in the organization kind of access to data so they can really make those data driven decisions that everybody wants to make? >>I mean, there's, there's so many of them, but, you know, one of the largest tech companies in the world creating a, a data mesh where you have all the different departments in the company that, you know, they, they, they were a big data warehouse user and it kinda hit the wall, right? The costs were so high and the ability for people to kind of use it for just experimentation, to try new things out to collaborate, they couldn't do it because it was so prohibitively expensive and difficult to use. And so what they said, well, we need a platform that different people can, they can collaborate, they can ex, they can experiment with the data, they can share data with others. And so at a big organization like that, the, their ability to kind of have a centralized platform but allow different groups to manage their own data, you know, several of the largest banks in the world are, are also doing data meshes with Dr you know, one of them has over over a dozen different business units that are using, using Dremio and that ability to have thousands of people on a platform and to be able to collaborate and share among each other that, that's super important to these >>Guys. Can you contrast your approach to the market, the snowflakes? Cause they have some of those same concepts. >>Snowflake's >>A very closed system at the end of the day, right? Closed and very expensive. Right? I think they, if I remember seeing, you know, a quarter ago in, in, in one of their earnings reports that the average customer spends 70% more every year, right? Well that's not sustainable. If you think about that in a decade, that's your cost is gonna increase 200 x, most companies not gonna be able to swallow that, right? So companies need, first of all, they need more cost efficient solutions that are, you know, just more approachable, right? And the second thing is, you know, you know, we talked about the open data architecture. I think most companies now realize that the, if you want to build a platform for the future, you need to have the data and open formats and not be locked into one vendor, right? And so that's kind of another important aspect beyond that's ability to connect to all your data, even outside the lake to your different databases, no sequel databases, relational databases, and drs semantic layer where we can accelerate queries. And so typically what you have, what happens with data warehouses and other data lake query engines is that because you can't get the performance that you want, you end up creating lots and lots of copies of data. You, for every use case, you're creating a, you know, a pre-joy copy of that data, a pre aggregated version of that data. And you know, then you have to redirect all your data. >>You've got a >>Governance problem, individual things. It's expensive. It's expensive, it's hard to secure that cuz permissions don't travel with the data. So you have all sorts of problems with that, right? And so what we've done because of our semantic layer that makes it easy to kind of expose data in a logical way. And then our query acceleration technology, which we call reflections, which transparently accelerates queries and gives you subsecond response times without data copies and also without extracts into the BI tools. Cause if you start doing bi extracts or imports, again, you have lots of copies of data in the organization, all sorts of refresh problems, security problems, it's, it's a nightmare, right? And that just collapsing all those copies and having a, a simple solution where data's stored in open formats and we can give you fast access to any of that data that's very different from what you get with like a snowflake or, or any of these other >>Companies. Right. That, that's a great explanation. I wanna ask you, early this year you announced that your Dr. Cloud service would be a free forever, the basic DR. Cloud service. How has that offer gone over? What's been the uptake on that offer? >>Yeah, it, I mean it is, and thousands of people have signed up and, and it's, I think it's a great service. It's, you know, it's very, very simple. People can go on the website, try it out. We now have a test drive as well. If, if you want to get started with just some sample public sample data sets and like a tutorial, we've made that increasingly easy as well. But yeah, we continue to, you know, take that approach of, you know, making it, you know, making it easy, democratizing these kind of cloud data platforms and, and kinda lowering the barriers to >>Adoption. How, how effective has it been in driving sales of the enterprise version? >>Yeah, a lot of, a lot of, a lot of business with, you know, that, that we do like when it comes to, to selling is, you know, folks that, you know, have educated themselves, right? They've started off, they've followed some tutorials. I think generally developers, they prefer the first interaction to be with a product, not with a salesperson. And so that's, that's basically the reason we did that. >>Before we ask you the last question, I wanna just, can you give us a speak peek into the product roadmap as we enter 2023? What can you share with us that we should be paying attention to where Drum is concerned? >>Yeah. You know, actually a couple, couple days ago here at the conference, we, we had a press release with all sorts of new capabilities that we, we we just released. And there's a lot more for, for the coming year. You know, we will shortly be releasing a variety of different performance enhancements. So we'll be in the next quarter or two. We'll be, you know, probably twice as fast just in terms of rock qu speed, you know, that's in addition to our reflections and our career acceleration, you know, support for all the major clouds is coming. You know, just a lot of capabilities in Inre that make it easier and easier to use the platform. >>Awesome. Tomer, thank you so much for joining us. My last question to you is, if you had a billboard in your desired location and it was going to really just be like a mic drop about why customers should be looking at Drio, what would that billboard say? >>Well, DRIO is the easy and open data lake house and, you know, open architectures. It's just a lot, a lot better, a lot more f a lot more future proof, a lot easier and a lot just a much safer choice for the future for, for companies. And so hard to argue with those people to take a look. Exactly. That wasn't the best. That wasn't the best, you know, billboards. >>Okay. I think it's a great billboard. Awesome. And thank you so much for joining Poly Me on the program, sharing with us what's new, what some of the exciting things are that are coming down the pipe. Quite soon we're gonna be keeping our eye Ono. >>Awesome. Always happy to be here. >>Thank you. Right. For our guest and for Paul Gillin, I'm Lisa Martin. You're watching The Cube, the leader in live and emerging tech coverage.

>> Announcer: Live from San Francisco, it's theCUBE. Covering Google Cloud Next '19. Brought to you by Google Cloud and its ecosystem partners. >> Hey welcome back everyone. It's theCUBE's live coverage here in San Francisco in Moscone South. We're on the ground floor here at Google Next, Google's Cloud conference. I'm chatting with Stu Miniman; Dave Vellante's also hosting. He's out there getting stories. Our next two guests: Dana Berg, Chief Operating Officer of SADA and Chris Lehman, Head of Engineering for SADA. Guys, welcome to theCUBE. Thanks for joining us. We're here on the ground floor. >> Thank you. >> Thank you. >> This is exciting. I feel like a movie star right here. >> It's game day here. All the tech athletes are out, Dave. If you look at the show, look at the demographics, hardcore developers, lot of IT, leaders also here, cloud architects, a lot of people trying to figure it out. We heard the keynote. Google is bringing a lot to the table. So what's new with you guys? You guys recently sold your Microsoft business, going all-in on Google. Talk about that relationship. >> We are. This is a brand new day for SADA. The energy around this place, where we are in the market, and where we are with the expanded attendance here has actually reaffirmed our business strategy to go all-in with Google. I don't know if you are aware but SADA has been around for almost 20 years. Historically have always been leaders in bringing people to the cloud even before there was really much of a cloud. We were a you know a pilot partner within Microsoft and Google and had a great thriving Microsoft business but an even bigger Google business and you know, we looked at the tea leaves, we looked at where we wanted to be, and aligned with a company that shared our mission and values and it was a clear choice. We chose Google. We made a very specific and deliberate act to sell off our Microsoft business so that we could take the horsepower of all of our engineering staff and apply them to Google. >> It's interesting you know, we've been around for 10 years doing theCUBE, go to a lot of events, I mean Dave Vellante, Stu, and I have been around for 30 years covering the IT, you guys 20 years. You guys have seen many ways of innovation come and go. Now you're going all in on Google. What is it about this wave right now that made that decision? What do you guys see? You're seeing something early here. Expand on that. Give us some color commentary because there's a wave here, right? A lot of people try. It's a combination of things. I mean, we saw the client-server thing. We saw that movement. Also the internet, we saw the web, mobile, now it's cloud. What's the big wave? What are you guys riding? >> I think there's a couple of things and I think it's unique to, philosophically, how we think of our real special relationship with Google. There is a momentum, right, and not to quote like a Bernie Sanders, but, seems like there's a revolution going on here, right, and, you know, I think, you know, what we see when we look around and we hear conversations and even with our customers, the way that we're all winning together is because we're winning the hearts and minds of the people inside of our customer base that are actually the ones responsible for inventing and the ones responsible for building, so when we're in board rooms and we're selling and along with Google, we're talking with developers, we're talking with designers, we're talking about people that are actually driving the vision for these business applications. We're not always talking to the CIO down like some of our other competitors seems to have only been able to sell that way. We're talking about the people responsible for not only constructing it but maintaining it. So that revolution is there. These folks are bubbling that up and they're seeing the real value inside of Google and what is that value from our point of view, and why did we make such a bold statement just to stick with Google is, and we saw Thomas today echo this, I think there's very few cloud providers that are bold enough to actually lead with the fact that we want our customers to have full choice whether you're using GCP or not. We want to build, architect, and manufacture a product offering that allows you to keep your stuff in your data centers, move your stuff to AWS. That power of choice is really not like what we've never heard anywhere else. >> And then on top of that, too, you got an application renaissance, right? A whole new way of coding, infrastructure that's programmable and going away, I mean if you think about what that does to the existing infrastructures, they can now mix and match and rearchitect everything from scratch and accelerate the app movement. >> Well, that's absolutely true, and a lot of that has to do with the fact that there are managed services in the cloud which makes it dramatically easier to build applications of course, so there's no question about that. Some of the offerings on GCP are particularly attractive for our clients, particularly the managed Kubernetes service. That's where we're seeing perhaps most of the interest that we're seeing, like that's a very common theme. Also the ML stack is an area that our customers are very interested in. >> Chris, can you bring us in some of those customer environments, you know, one of the things you hear, you know, most customers, it's, "I've got my application portfolio." Modernizing that is pretty challenging. There are some things that are kind of easy, some things that take a lot more work, but, you know, migration is one of those things that makes most people that have been in IT a while cringe because there's always the devil in the details and something goes wrong once you've got 95 percent done. What are you seeing, what's working, what's not working, how's the role of data changing, and all of that? >> I think migrations are usually more complex than they at first appear and so even with best intentions thinking that customers can just move their workloads seamlessly to the cloud have actually in practice been more challenging. So some of the areas that we find challenges are around data migration, especially in the context of zero downtime. That's always more difficult than with applications. So that's definitely an area that were we're spending a lot of time working with our customers to deliver. >> Just to add to that, I have to keep reminding myself of the name, but obviously the Anthos announcement today sounds incredibly intriguing as a lower barrier of effort to actually migrate. Our customers have been trying to really absorb and take a hold of Kubernetes and can it containerize methods for a long time. Some are having a harder time doing it than others. I think Anthos promises to make that endeavor much, much easier, and I think about as we leave here this week and we go back and we reeducate our own engineering teams as well as our customers, I think we might see some highly accelerated project timelines go from here down to here. >> And the demo that Jennifer Lynn did was pretty impressive. I mean, running inside of containers, whether it's VMs, and then having service patches on the horizon coming to the table is going to change the implementation delivery piece too in a massive way. I mean, you've got-- >> Oh, absolutely. >> Code, build, run on the cloud side, but this this kind of changes the equation on your end. Can you guys share the insight into that equation, because Google's clearly posturing to be partner friendly. You guys are a big partner now. You're going all-in. This is an interesting dynamic because you can focus on solving customers' problems. All this heavy lifting kind of goes away. Talk about the impact to you as a partner when you look at Anthem, Anthem migrate in particular, some of these migration challenges with containers and Kubernetes seems like it's a perfect storm right now to kind of jump in and do more, faster. >> Yeah. >> Well, it's certainly very interesting. Well, we'll want to take a really hard look at it. I mean, a very, very cool announcement. Moving to containers in the source prior to the migration obviously solves a lot of challenges so for that reason, it's definitely a move forward. >> And I think... You know, we always talk about, in this industry, the acceleration for consumption, but really that's a poor way of saying... Probably what we should be saying is an acceleration of value. So we're constantly in this battle to try and deliver value to our customers faster. That's what our customers want, right, and in essence we see Anthos as being potentially a big game-changer there so that, you know, our CIOs that we're talking with can show to their various stakeholders that they are making very good proactive moves into the cloud at lower-caught barriers of entry, right? >> Yeah. So, you brought up the the ML piece of Google. Wondering if you could help share a little bit on that. When I think back two years ago, you know, data was really at the core of what a lot of what Google was talking about. I was actually surprised not to hear a lot of it on the main stage this morning, but you know, AI, ML, what are you doing, what are your customers doing, does Google have leadership in the space? >> Google certainly has leadership in the space. Our customers, I think, relatively universally, think that their ML stack is the strongest among the competitors, but I think in practice what we're finding is there's a lot more urgency as far as just literal data migrations off of their data centers into the cloud, and I foresee a lot more AI and ML work as more move in. >> John: Yeah. >> So you might, in our booth here, not to give a plug, but we've got a booth down at the end with a full-fledged racing car, just to talk about the art of the possible with AI and ML. Our engineering teams in the race teams that we sponsor, they're there, the driver's there, you should go down and talk to 'em. We've taken all the race telemetry data for the last six months and all of his races and practices, we've aggregated that data all into GCP, run AI and ML algorithms on it to provide his racing team some very predictive ways that he can get better and that team can get better, and so I'd invite just anybody that wants to go there and take a look at, even if you're in banking, or if you're in retail, or if you're in health care, take a look at some of how that was done, because it's a very, very powerful way, to answer your question, head and shoulders down why Google is actually accelerating and exceeding in AI. >> And one of the things that Thomas Kurian showed onstage was the recent Hack-a-Thon they had with the college students with the NCAA data of the game that just finished, and throughout that experience, this is a core theme of GCP, and now Anthos, which is getting data in and using it easily, and scaling at a scale level that seems unprecedented. So this team seems to be the application... The new differentiator. >> I think it is. I think that announcement, obviously the big three takeaways for us, certainly, scale, unmatched. Certainly speed and migration with Anthos. If I could highlight one other, I was incredibly pleased with, well I've been pleased since Thomas' arrival in general by bringing an enterprise class strategy within sight of Google that I think are going to respond well to our enterprise customers, and part of enterprise class is also making sure that their partner community has amazing enhancement programs that really incentivize those partners that are actually in the full managed services space from cradle to grave, lifetime customer value. So we're very excited about even further announcements this week that no doubt have been inspired by Thomas to try and really take advantage of their partner community that are in the business of cradle to grave support of customers. >> You feel comfortable with Thomas. He's taught a lot of customers, he knows the enterprise. >> We've had an opportunity to meet with him. We've had some shared customers that have had a great privilege of getting to know him and support us and collectively them. >> John: He knows the partner equation pretty well, and the enterprise. >> Without a doubt. >> It's about partnering, because there's a monetization, the shared go to markets together. Talk about the importance of that and what's it like to be a partner. >> Yeah, without a doubt, again, you know, his embrace of the open-source community that you saw today, really taking advantage of highlighting partner value is wonderful, but I think Thomas, above anything else, knows that Google needs to scale. They need to scale, and then they have to have breadth and they have to have depth, and, you know, to get to where Google needs to be over the course of the next two, three years, it's wonderful, it's refreshing, it's 100% accurate that Google knows and Thomas knows that the path to do that is via partners; partners that share in Google's vision, that are 100% aligned to the same things that Google is aligned with, and I think that's why I'm so thankful to be at SADA, large in part, because all of the things that we care about in terms of our customer success as well as Google's success, we all share that, so it's a great trifecta. >> It's a ground-floor opportunity. Congratulations. Guys, talk about your business. What's going on? You've got some new offices I heard you opened up. What's going on in the state of the business? Obviously the Google focus you're excited about obviously. >> Yeah, yeah, yeah. >> There, at the beginning, I called Google the dark horse. I think with the tech that they have and the renewed focus on the enterprise, building on what Diane Greene had put foundationally, Thomas is meeting with hundreds of customers. He's so busy he doesn't have time to come on theCUBE, but he'll come on soon, but he's focused. This is now a great opportunity. Talk about your business. What's the state of the union there? Give an update. >> I can take that one if you don't mind. >> Go ahead. >> You can add poetic color if you want. (laughing) Yeah, so as I said, we're entering a new journey for SADA in light of renewed focus, renewed conviction to Google. We are investing more than we ever have into the common belief that Google is the one to beat in terms of momentum, drive, and ultimately winning the hearts and the minds of who we've talked about. So, over the last four months, we've opened five new offices in New York, Austin, Chicago, Denver. Our headquarters is in Los Angeles, and just recently, we just opened a brand new office in Toronto, so we can really help our Canadian customers really see the the same type of white-glove treatment we provide those customers in the States and so that's why, well, I wasn't earlier, but I'm walking around with a Canadian flag. We're very excited about the presence that we're going to have in Canada >> Its "Toronno." I always blow and I call it "Toron-to," being the American that I am. It's "Toronno." >> Dana: Glad you said it right. Good. >> Now, on the engineering side, so you guys are on the front lines as also a sales, development, there's also customer relationship, engineering side, so I'm sure you guys are hiring. There's some hard problems to solve out there. Can you guys share some color commentary on the type of solutions you guys are doing? What's the heavy? What solutions are you solving, problems that you're solving for customers, what are the key things that you got going on? >> Yeah. >> Well, a lot of cloud migrations, a lot of web and application development, custom development, and data pipelines. I'd say those are really the three key focus areas that we're working on at the moment. >> One other thing, too: so... we believe that we want 100% customer retention, always, and that goes above and beyond an implementation. So the other big area of investments that we're making is in a whole revamped technical account management team, so for those of our GCP customers that have had the privilege, we've had the privilege of working with and for, we are building out a team of individuals that will, well beyond the project, stay with that customer, work with them weekly, monthly, quarterly, and try to always find ways to expand and move workloads into the cloud. We think that provides stickiness. We think that provides ultimate value to try and help our customers identify where else they can take full advantage of the cloud, and it's a fairly new program, and large in part I just want to thank Thomas and the partner team for new programs that are coming out to help us so that we can actually reinvest in things that go you know throughout the lifecycle of the customer. So, very, very good stuff. >> Dana, Chris, thanks for coming on. Appreciate it. We'll check out your booth, the car's there, with the data. Bring that data exhaust to the table, pun intended. >> Yes. >> Analyzing with Google Cloud, Anthos. Good commentary. Thanks for sharing. >> Really appreciate being on board. Thanks for having us. >> Alright, great. CUBE coverage here live on the floor in San Francisco. Google Next 2019. This is Google's cloud conference. Customers are here. A lot of developers. More action, live on the day one of three days of coverage after this short break. Stay with us. (theCUBE Theme)