(bright, upbeat music playing) >> Hello, Brilliant Cloud community and welcome back to AWS re:Invent, where we are live all day everyday from the show floor, here in Las Vegas, Nevada. I'm Savannah Peterson joined by my beautiful co-host, Lisa Martin here on theCUBE. Lisa, you're smiling, you're radiating, day three, you would think it was day one. How you doing? >> Amazing. I can't believe the energy that has been maintained >> It's been a theme. on this show floor, since Monday night at 4:00 pm. >> I know, and I kind of thought today we might see some folks trickling out. It is packed, as our guests and I were, we were all just talking about, right before the segment, almost too packed which is a really great sign for AWS. >> It is. We're hearing north of 55,000 people here. And of course, we only get a little snapshot of what's at the Venetian. >> Literally this corner, yeah. We don't get to see anything else around The Strip, that's going on, so it's massive. >> Yeah, it is very massive. I'm super excited. We've got two guests from Infosys with us on this last segment from this stage today. David and Anant, welcome to the show. How you doing? >> Awesome. >> You're both smiling and I am really excited. We have our first prop of the show, (David and Anant laughing) and it's a pretty flashy, sexy prop. Anant, what's going on here? >> Oh, so this is something that we are very proud of. Last year we won one award, which was very special for us because it was our first award with AWS, and that was, "The Industry Partner of The Year Award." And on the back of that, this year we won three awards and this is super awesome for us, because all of them are very special. One was in collaboration, second was in design, and third was in sustainability. So we are very proud, and we thank AWS, and it's a fantastic partnership. >> Yeah, congratulations. >> Anant: Yes. I mean that's huge. >> Yes, it's absolutely huge. And the second one is, we are the Launch Partner for MSK, which again is a very proud thing for us. So I think those are the two things that we wanted to talk about. >> How many awards are you going to win next year then? (all laughing) >> We want to target more than three. (Savannah chuckles) >> Keep it going up. >> Probably five, right? >> So it's the odd numbers, one, three, five, seven, ten. Yeah. Yeah. Yeah. >> Savannah: There you go. >> I think we got that question last year and we said we'd get two, and we ended up over-delivering with three, so who knows? >> Hey, nothing wrong with setting the bar low and clearing it. And I mean, not setting it low, setting it with one and clearing it with three is pretty fantastic. We talk about it as an ego thing sometimes with awards and it feels great for internal culture, but David, what does it mean on the partnership side to win awards like that? >> So what's really important for us with our partners is to make sure that we're achieving their goals, and when their goals are achieved in our partnership it's just the byproduct that we're achieving our own with our clients. The awards are a great representation of that to see, you know, again, being recognized in three different categories really shows that we've had success with AWS, and in turn, you know, Anant and I can attest to it. We've been very successful at the partnership on our side. >> Yeah, and I bet it's really exciting for the team. Just speaking for Energy (indistinct) >> And there's celebration, you know, there's been a few cocktails being raised... >> Has there? In Las Vegas? >> David: I know. Cocktails? >> Lisa Martin: Shocking! I'm shocked! >> Lisa Martin: I know! (all laughing) I wouldn't mind one right now to be really, really honest. Let's dig into the product a little bit. Infosys Cobalt. What's the scoop, Anant? >> Yeah, so first of all, we were the first ones to actually launch a Cloud brand called Cobalt, right? We were the first ones in the world. In fact, one of our competitor followed us soon after. So essentially what we did was we brought all our Cloud offerings into one brand called Cobalt. It becomes very clear to our customers on what our proposition is. It is very consistent to the market in terms of what our narrative is. And it's a little easy for our customers to understand what we bring to the table. So Cobalt is not one product or what one platform it's a set of services, solutions and platforms that we bring to accelerate customer's journey where they're leveraging Cloud. So that's what Cobalt is. >> Awesome, everyone wants to do everything faster. >> Yes. >> Lisa Martin: Yeah. >> And the booth was packed. I walked by earlier, it was absolutely buzzing. >> Yes. >> Yeah. Nobody wants to do, you know, wants less data slower. >> Anant: Yes. (Savannah laughs) >> It's always more faster. >> Anant: More faster. And we're living in this explosion unlike anything this swarm of data unlike anything that we've ever seen before. Every company, regardless of industry has to be a data company. >> Anant: Yes. But they have to be able to work with the right partners to extract, to first of all harness all that data, extract insights in real time, because of course on the consumer side we're not patient anymore. >> Anant: Yes. We expect a personalized, realtime, custom experience. >> Anant: Absolutely. >> How do you work with AWS to help deliver that and how do the partners help deliver that as well? >> Well I'll start with on the partner side of it. You walk through the hallways here or down the aisles you see partners like MongoDB, Snowflake, Databricks and such, they're all attesting their commitment and their strong partnership with AWS, and coincidentally they're also very good partners of our own. And as a result... >> Savannah: One big happy family here at AWS when you met. >> And this is something that I'm calling, coining the phrase sub-ecosystems. These are partnerships where one is successful with each other, and then the three come together, and we go together with an integrated solution. And it's really taking off. It's something that's really powerful. The fun thing about re:Invent here is isn't just that we're having amazing discussions with our clients and AWS, but we're also having with the other partners here about how we can all work together so... And data analytics is a big one, security is another hot one-- >> Lisa Martin: Security is huge. >> Savannah: Yeah. Cost optimization from the start. >> Absolutely. And Ruba was saying this, right? Ruba said, like she was giving example of a marathoner. Marathon is not a single man or a single woman sport, right? So similarly Cloud journey is a team's, sort of you know, team journey, so that's why partners play a big role in that and that's exactly what we are trying to do. >> So you guys get to see a lot of different companies across a lot of different industries. We're living in very interesting times, how do you see the Cloud evolving? >> Oh, yeah. So what we did when we launched Cobalt in 2020 we have now evolved our story. We call it Cobalt 2.0. And essentially what we wanted to do was to focus on industry Clouds. So it's not just about taking a workload and moving it from point A to point B or moving data to Cloud or getting out of data centers, but it's also being very specific to the industry that this specific customer belongs to, right? So for example, if we go to banking they would say we want to better our security posture. If we go to a retailer they want to basically have smart stores. If we go to a manufacturing customer they want to have a smart factory. So we want to make sure that there are specific industry blueprints and specific reference architectures that we bring and start delivering outcomes. So we call it something called... >> Savannah: I know you're hot on business outcomes. >> Yes. >> Savannah: Yes. So we call it something called the link of life forces. So there are six technologies; Cloud, Data, Edge, IOT, 5G, and AI. They will come together to deliver business outcomes. So that's where we are heading with Cobalt 2.0, And that's essentially what we want to do with our customers. >> Savannah: It's a lot to think about. >> Yes. >> David: Yes. >> And, yeah, go for it David. >> I was just saying from a partnering perspective, you know prior to Cloud, we were talking about transactional type businesses where if you ask a technology company who their partner is its generally a reseller where they're just basically taking one product and selling it to their client. What's happened with cloud now it's not about the transaction upfront it's about the actual, you know, the consumption of the technology and the bringing together all of these to form an outcome, it changes the model dramatically, and quite honestly, the global system integrators like Infosys are in great position because we can pull that together to the benefit of our partners, put our own secret sauce around it and take these solutions to market and drive consumption because that's what the Cloud's all about. >> Right. Well, how are you helping customers really treat Cloud as a strategic focus? You know we often hear companies talk about we're Cloud first. Well not everything belongs in the Cloud. So then we hear companies start talking about being Cloud smart. >> Anant: Yes. How are you helping, and so we'll go with that. How are you helping enterprises really become Cloud smart and where is the partner angle? So we'll start with you and then we'll bring the partner angle in. >> Oh yeah, big time. I think one of the things that we have been educating our customers is Cloud is not about cost takeout. So Cloud is about innovation, Cloud is about growth. And I'll give two examples. One of the beauty products companies they wanted to set up their shop in US and they said that, you know, "we don't have time to basically buy the infrastructure, implement an ERP platform, and you know, or roll it out, test it and go into production. We don't have so much time. Time to market is very important for us." And they embarked on the Cloud journey. So expanding into new market, Cloud can play a big role. That is one of the ways to expand and you know, grow your business. Similarly, there is another company that they wanted to go into retail banking, right? And they didn't have years to launch a product. So they actually use AWS and it's a joint Infosys and AWS customer. A pretty big bank. They launched retail banking and they did it in less than six months. So I think these are some of the examples of cloud not being cost takeout but it's about innovation and growth. So that's what we are trying to tell customers. >> Savannah: Big impacts. >> Big impact. Yes, absolutely. >> And that's where the Cobalt assets come into play as well. You know, as Anant mentioned, we have literally thousands of these industries specific and they're derived in a lot of cases in partnership with the companies you see down the aisles here, and AWS. And it accelerates the deployments and ensures a successful adoption, more so than before. You know, we have clients that are coming to us now that used to buy, run their own procurement. You know they would have... Literally there was one bank that came to us with a over a hundred products >> The amount of work. I'm just seeing it... >> A list of a hundred products. Some they bought directly from a vendor, some they went through a distributor, some they went through a reseller and such, >> Savannah: It's so ad-hoc. And they're looking at this in a completely different way and they're looking to rationalize those technologies, again, look for companies that will contract for a business outcome and leverage the cloud and get to that next era, and it's a fun time. We're really excited. >> I can imagine you're really a part of the transformation process for a lot of these companies. >> Anant: Absolutely. Anant when we were chatting before we went live you talked about your passion for business outcomes. Can you give us a couple examples of customers or business outcomes that really get you and the team excited? Same thing to you David, after. >> Well, absolutely. Even our contractual structures are now moving into business outcomes. So we are getting paid by the outcomes that we are delivering, right? So, one of the insurance customers that we have we actually get paid by the number of claims that we process, right? Similarly there is a healthcare customer where we actually get paid by the number of customers that we cater to from a Medicare and Medicaid standpoint, right? >> Savannah: Tangible results processed and projected-- >> Successful process of claims. >> Interesting. >> Anant: Exactly. >> Yeah. (indistinct) reality. >> Yeah, reality, (chuckles) What a novel idea. >> Yeah. (Savannah and Lisa chuckle) >> One of the great examples you hear about airplane engines now that the model is you don't buy the engine, you basically pay for the hours that it's used, and the maintenance and the downtime, so that you take the risk away. You know, you put that in the context of the traditional business. You're taking away the risk of owning the individual asset, the maintenance, any of the issues, the bug fixes. And again, you're partnering with a company like Infosys, we'll take on that based upon our knowledge and based upon our vast experience we can confidently contract in that way that, you know, years ago that wasn't possible. >> Savannah: It's kind of a sharing economy at scale style. >> David: Exactly. >> Anant: Absolutely. >> Yeah, which is really exciting. So we have a new challenge here on theCUBE this year at re:Invent. We are looking for your 32nd Instagram real sizzle soundbite. Your hot take, your thought leadership on the biggest theme or most important thing coming out of this year's show. David, we'll start with you. We've been starting with Anant, so I'm going to go to you. We're making eye contact right now so you're in the hot seat. (all laugh) >> Well, I think there was a lot of time given to sustainability on the stage this week, and I think that, you know, every CEO that we talk to is bringing that up as a major priority and that's a very important element for us as a company and as a service provider. >> Savannah: I mean, you're obviously award winning in the sustainability department. >> Exactly. Nice little plug there. >> Yeah. >> You know, and I think the other things that have come up we saw a lot about data analytics this week. You know, I think new offerings from AWS but also new partnerships that we're going to take advantage of. And again, security has been a hot topic. >> Absolutely. Anant, what's your hot take? >> Yeah. I think one very exciting thing for partners like us is the re-imagining that is being done by Ruba for the partners, right? The AWS marketplace. I think that is a big, big thing that I took out. Of course, sustainability is huge. Like Adam said, the fastest way to become sustainable is to move to Cloud, right? So rather than overthinking and over-engineering this whole topic just take your workloads and move it to Cloud and you'll be sustainable, right? So I think that's the second one. And third is of course cybersecurity. Zscaler, Palo Alto, CrowdStrike, these are some of the big companies that are at the event here, and we have been partnering with them. Many more. I'm just calling out three names, but many more. I think cybersecurity is the next one. So I think these are three on top of my mind. >> Just a few things you casually think about. That was great. Great responses from both of you Anant, David, such a pleasure to have you both with us. We hope to have you back again. You're doing such exciting things. I'm sure that everything we talked about is going to be a hot topic for many years to come as people navigate the future as well as continue their business transformations. It is always a joy to sit next to you on stage my dear. >> Likewise. And thank all of you, wherever you're tuning in from, for joining us here at AWS re:Invent live from Las Vegas, Nevada. With Lisa Martin, I'm Savannah Peterson, and for the last time today, this is theCUBE, the leader in high tech coverage. (bright, upbeat music playing)

>>Hello, brilliant cloud community and welcome back to AWS Reinvent, where we are live all day every day. From the show floor here in Las Vegas, Nevada. I'm Savannah Peterson, joined by my beautiful cohost Lisa Martin here on the cube. Lisa, you're smiling. You're radiating Day three. You would think it was day one. How you doing? >>Amazing. I can't believe the energy that has been maintained omni show floor since Monday night at 4:00 PM >>I know. And I, I kind of thought today we might see some folks trickling out. It is packed as our, as our guests and I were, we were all just talking about right before the segment, almost two packed, which is a really great sign for aws. It is. We're >>Hearing worth of 55,000 people here. And of course we only get a, a little snapshot of which literally >>This corner, >>We don't get to see anything else around the strip that's going on. So it's massive. Yeah, >>It is a very massive, I'm super excited. We've got two guests from Infosys with us on this last segment from this stage today. David and Anant, welcome to the show. How you doing? >>Awesome. >>You're both smiling and I am really excited. We have our first prop of the show and it's a pretty flashy, sexy prop. Anant, what's going on here? >>Oh, so this is something that we are very proud of. Last year we won one award, which was very special for us because it was our first award with aws and that was the industry partner of the year award. And on the back of that, this year we won three awards. And this is super awesome for us because all of them are very special. One was in collaboration, second was in design, and third was in sustainability. So we are very proud and we thank AWS and it's a fantastic partnership. Yeah. And >>Congratulations. Yes. I mean that's >>Huge. Yes, it's absolutely huge. And the second one is we are the launch partner for msk, which again is a very proud thing for us. So I think those are the two things that we wanted to talk about. >>How many awards are you gonna win next year then? >>Do you want to target more than three? >>So we keep going up probably fine, >>Right? I >>Love, >>That's the odd numbers. 1, 3, 5, 7, 10. There you go. >>Yeah, >>I think you, we got that question last year and we said we get two and we ended up overdelivering with three. So who >>Knows? Hey, nothing. Nothing wrong with the setting the bar low and clearing it and I mean, not setting it low, setting it with one and clearing it with three is pretty fantastic. Yes, yes. We talk about it as an ego thing sometimes with awards and it feels great for internal culture. But David, what does it mean on the partnership side to win awards like that? So >>What's really important for us with our partners is to make sure that we're achieving their goals and when, when their goals are achieved in our partnership, it's just the byproduct that we're achieving our own with our clients. The awards are a great representation of that to see, you know, again, being recognized three in three different categories really shows that we've had success with AWS and in turn, you know, know and not, I can attest to it, we've been very successful with the partnership on our side. >>Yeah. And I bet it's really exciting for the team. Just speaking for energy, are your >>Team sponsor? Absolutely. There's celebration, you know, there's been a few cocktails being raised >>In Las Vegas >>Cocktail. Oh, >>I wouldn't mind one right now to be really be really honest. Let's dig into the, into the product a little bit. Infosys Cobalt, what's the scooping on? >>Yeah, so first of all, we were the first ones to actually launch a cloud brand called Cobalt. Right? We are the first ones in the world. In fact, one of our competitor followed us soon after. So essentially what we did was we brought all our cloud offerings into one brand called Cobalt. It becomes very clear to our customers on what our proposition is. It is very consistent to the market in terms of what our narrative is. And it's little easy for our customers to understand what we bring to the table. So is not one product or one platform. It's a set of services, solutions and platforms that we bring to accelerate customers journey where they're leveraging cloud. So that's what Cobalt is. >>Awesome. Everyone wants to do everything faster. Yes. And Booth was packed. I walked by earlier, it was absolutely buzzing. Yes. >>Yeah. Nobody wants to do it, you know, wants less data slower. Yes. Always more faster. More faster. And we're living in this explosion unlike anything, this swarm of data, unlike anything that we've ever seen before. Yes. Every company, regardless of industry, has to be a data company. Yes. But they have to be able to work with the right partners. Absolutely. To extract, to first of all, harness all that data. Yes. Extract insights in real time. Yes. Because of course, on the consumer side, we're not patient anymore. Yes. We expect a personalized, real time custom experience. Absolutely. How do you work with AWS to help deliver that and how do the partners help deliver that as well? >>Well, I'll start with on the partner side of it. You walk through the hallways here or down the aisles, you see partners like MongoDB, snowflake, data Bricks and and such. They're all attest their commitment and their strong partnership with aws. And coincidentally, they're also very good partners of our own. And as a result, what >>Big happy family here at AWS when you >>Met? Yes, and this, this is something that I'm, I'm calling coining the phrase sub ecosystems. These are partnerships where one is successful with each other and then the three come together and we go together with an integrated solution. And it's really taking off. It's something that's really powerful. The, the fun thing about, you know, reinvent here is it's just that we're having amazing discussions with our clients and aws, but we're also having it with the other partners here about how we can all work together. So, and data analytics is a big one. Security is another hot one. This is huge. >>Yeah. Optimization. >>The absolutely. And I, and Ruba was saying this, right? Ruba said like she was giving example of a marathon or Marathon is not a single man or a single woman sport. Right? So similarly cloud journey is a team's sort of, you know, team journey. Yeah. So that's why partners play a big role in that and that's exactly what we are trying to do. >>So you guys get to see a lot of different companies across a lot of different industries. We've, we're living in very interesting times. How do you see the cloud evolving? >>Oh yeah. So, so what we did when we launched Cobalt in 2020, we have now evolved our story, we call it Cobalt 2.0. And essentially what we want to do was to focus on industry clouds. So it's not just about taking a workload and doing it from point A to point B or moving data to cloud or getting out of data centers, but also being very specific to the industry that this specific customer belongs to. Right? So for example, if you go to banking, they would say, we want to better our security posture. If you go to a retailer, they want to basically have smart stores. If we go to a manufacturing customer, they want to have a smart factory. So we want to make sure that there are specific industry blueprints and specific reference architectures that we bring and start delivering outcomes. So we have, we call it something called, >>I know you're hot on business outcomes. Yes, yes. >>So we call it something called the link of life forces. So there are six technologies, cloud, data Edge, iot, 5g, and ai. They will come together to deliver business outcomes. So that's where we are heading with Cobalt 2.0. And that's essentially what we want to do with our customers. >>That's a lot to think about. Yes. And yeah, go for it. >>David. I just say from a partnering perspective, you know, prior to cloud we were talking about transactional type businesses where if you ask a technology company who their partner is, is generally a reseller where they're just basically taking one product and selling it to their, their client. What's happened with cloud now, it's not about the transaction up front, it's about the, the actual, you know, the consumption of the technology and the bringing together all of these to form an outcome. It changes the model dramatically. And, and quite honestly, you know, the global system integrators like emphasis are in a great position cuz we can pull that together to the benefit our of our partners put our own secret sauce around it and take these solutions to market and drive consumption. Cuz that's what the cloud's all about. >>Absolutely. Right. How are you helping customers really treat cloud as a strategic focus? You know, we, we often hear companies talk about we're we're cloud first. Well, not everything belongs in the cloud. So then we hear companies start talking about being cloud smart. Yes. How are you helping? And so we'll go with that. How are you helping enterprises really become cloud smart and where is the partner angle? So we'll start with you and then we'll bring the partner angle in. >>Sure. Oh yeah, big time. I think one of the things that we have been educating our customers is cloud is not about cost takeout. So cloud is about innovation, cloud is about growth. And I'll give two examples. One of one of the beauty products companies, they wanted to set up their shop in us and they said that, you know, we don't have time to basically buy the infrastructure, implement an er p platform and you know, or roll it out, test it, and go into production. We don't have so much time, time to market is very important for us. And they embarked on the cloud journey. So expanding into new market cloud can play a big role. That is one of the ways to expand and, you know, grow your business. Similarly, there is another company that they, they wanted to get into retail banking, right? And they didn't have years to launch a product. So they actually use AWS and it's a joint infos and AWS customer, a pretty big bank. They launched into, they launched retail banking and they did it in less than six months. So I think these are some of the examples of, wow, it's Snap Cloud not being cost takeout, but it's about innovation and growth. So that's what we are trying to tell >>Customers. Big impacts, big impact. >>Absolutely. And that's where the, the Cobalt assets come into play as well. We, you know, as as not mentioned, we have literally thousand of these industries specific, and they're derived in, in a lot of cases in, in, in partnership with the, the companies you see down the, the aisles here and, and aws. And it accelerates the, the, the deployments and ensures a accessible adoption more so than before. You know, we, we have clients that are coming to us now that used to buy, run their own procurement. You know, they, they would have literally, there was one bank that came to us with a over a hundred, >>The amount of work. Yeah. >>A list of a hundred products. Some they bought directly from a, a vendor, some they went through a distributor, something went through a, a seller and such. And they're, they're, now they're looking at this in a completely different way. And they're looking to rationalize those, those technologies, again, look for companies that will contract for a business outcome and leverage the cloud and get to that next era. And it's, it's a, it's a fun time. We're really excited. >>I can imagine you, you're really a part of the transformation process for a lot of these companies. Absolutely. And when we were chatting before we went live, you talked about your passion for business outcomes. Can you give us a couple examples of customers or business outcomes that really get you and the team excited? Same thing to you, David, after. Yeah, >>Well, absolutely. Even our contractual structures are now moving into business outcomes. So we are getting paid by the outcomes that we are delivering, right? So one of the insurance customers that we have, we actually get paid by the number of claims that we process, right? Similarly, there is a healthcare customer where we actually get paid by the number of customers that we cater to from a Medicare and Medicaid standpoint, right? >>Tangible results versus >>Projected forecast. Successful process of >>Claims. That's interesting. Exactly. Yeah. I love reality. Yeah, reality. What a novel idea. Yeah. >>One of the great examples you hear about airplane engines now that the model is you don't buy the engine. You basically pay for the hours that it's used and the maintenance and the downtime so that they, you take the risk away. You know, you put that in the context of a traditional business, you're taking away the risk of owning the individual asset, the maintenance, any, any of the issues, the bug fixes. And again, you're, you're partnering with a company like Emphasis will take on that based upon our knowledge and based upon our vast experience, we can confidently contract in that way that, you know, years ago that wasn't possible. >>It's kind of a sharing economy at scale style. >>Exactly. Absolutely. >>Yeah. Which is really exciting. So we have a new challenge here on the cube this year at ve We are looking for your 32nd Instagram real sizzle sound bite, your hot take your thought leadership on the, the biggest theme or most important thing coming out of this year's show. David, we'll start with you. We've been starting with it on, I'm to go to you. We're making eye contact right now, so you're in the hot seat. >>Well, let's, I I think there's a lot of time given to sustainability on the stage this week, and I think that, you know, every, every CEO that we talk to is bringing that up as a major priority and that's a very important element for us as a company and as a service >>Provider. I mean, you're obviously award-winning and the sustainability department. Exactly. >>Yes. Nice little plug there. You know, and I, I think the other things that have come up, we saw a lot about data analytics this week. You know, I think new offerings from aws, but also new partnerships that we're gonna take advantage of. And, and again, security has been a hot topic. >>Absolutely. And not, what's your hot take? >>Yeah. I think one, one very exciting thing for partners like us is the, the reimagining that is being done by rhu for the partners, right? The AWS marketplace. I think that is a big, big thing that I took out. Of course, sustainability is huge. Like Adam said, the fastest way to become sustainable is to move to cloud, right? So rather than overthinking and over-engineering this whole topic, just take your workloads and move it to cloud and you'll be sustainable. Right. So I think that's the second one. And third is of course cyber security. Zscaler, Palo Alto, CrowdStrike. These are some of the big companies that are at the event here. And we have been partnering with them many more. I'm just calling out three names, but many more. I think cyber security is the next one. So I think these are three on top of my mind. >>Just, just a few things you casually think about. That was great, great responses from both of you and David, such a pleasure to have you both with us. We hope to have you back again. You're doing such exciting things. I'm sure that everything we talked about is gonna be a hot topic for many years to come as, as people navigate the future, as well as continue their business transformations. It is always a joy to sit next to you on stage. Likewise. Thank you. And thank all of you wherever you're tuning in from. For joining us here at AWS Reinvent Live from Las Vegas, Nevada, with Lisa Martin. I'm Savannah Peterson. And for the last time today, this is the cube, the leader in high tech coverage.

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

>>the Cube presents H p E discover 2022. Brought to you by H P E. >>Okay, we're back at HPD. Discovered 2022 This is Day Three. We're kind of in the mid point of day three. John Furry and Dave Volonte Wall to wall coverage. I think there are 14th hp slash hp Discover we've sort of documented the history of the company over the last decade. Plus, I'm not a is here is executive vice president at Infosys and Cejudo. Sankaran Kutty is the CEO and vice president of Infosys. Infosys doing some amazing work in the field with clients. Guys, Thanks for coming on the Cube. Thank >>you for the opportunity. >>Yeah, absolutely so. Digital transformation. It's all the buzz word kind of pre pandemic. It was sort of Yeah, you know, we'll get there a lot of lip service to it. Some Some started the journey and then, of course, pandemic. If you weren't digital business, you are out of business. What are the trends that you're seeing now that we're exiting the isolation economy? >>Yeah, um, again, as you rightly called out pre pandemic, it was all about using sort of you know innovation at scale as one of the levers for digital transformation. But if you look at now, post Pandemic, one of the things that we see it's a big trend is at a broad level, right? Digital transformation is not about cost. Take out. Uh, it's all about growth, right? So essentially, uh, like, uh, what we hear from most of the CEO s and most of the customers and most of the executives in the tech company, Digital transformation should be used for business growth. And essentially, it means three things that we see three trends in that space. One is how can you build better products and solutions as part of your transformation strategy? How can you basically use digital transformation to expand into new markets and new new territories and new regions? And the third is, how can you better the experience for your customers? Right. So I think that is broadly what we see as, uh, some other things. And essentially, if you have better customer experience, they will buy more. If you expand into new markets, your revenue will increase. If you actually build better products and solutions, consumers will buy it right, so It's basically like a sort of an economy that goes hand in hand. So I would say the trend is clearly going towards business growth than anything else when it comes to the, >>you know, follow up on that. We had I d. C on yesterday and they were sharing with some of their high level numbers. We've looked at this and and and it seems like I t spending is pretty consistent despite the fact that, for example, you know, the to see the consumer businesses sort of tanking right now. Are you seeing any pullback or any evidence that people are pulling the reins back on the digital transformation Or they just going because if they don't keep keep moving fast, they're gonna fall behind. What are you seeing there? Absolutely. >>In fact, you know what? What we call them as the secular headwinds, right? I mean, if you look at the headwinds here, we see digital transformation is in the minds of everybody, every customer, right. So while there are budget constraints, where are all these macro tailwinds as we call with respect to inflation, with respect to what's happening with Russia and Ukraine with respect to everything that's happening with respect to supply chain right. I think we see some of those tail headwinds. But essentially, digital transformation is not stopping. Everybody is going after that because essentially they want to be relevant in the market. And if they want to be relevant in the market, they have to transform. And if they have to transform, they have to adopt digital transformation. >>Basically, there's no hiding anymore. You know, hiding and you can't hide the projects and give lip service because there's evidence of what the consequences are. And it can be quantified. Yes, you go out of business, you lose money. You mentioned some of the the cost takeouts growth is yes. So I got given the trends and the headwinds and the tail winds. What are you guys seeing as the pattern of companies that came out of the pandemic with growth? And what's going on with that growth driver? What are the elements that are powering companies to grow? Is that machine learning? Is that cloud scales and integration? What are some of the key areas that's given that extra up into the right? >>Yes, I I would say there are six technologies that are defining how growth is being enabled, right? So I think we call it as cloud ai edge five g, Iot and of course, everything to do with a And so these are six technologies that are powering digital transformation. And, uh, one of the things that we are saying is more and more customers are now coming and saying that we want to use these six technologies to drive business outcomes. Uh, for example, uh, we have a very large oil and gas customer of ours who says that, you know, we want to basically use cloud as a lever to Dr Decarbonization. E S G is such a big initiative for everybody in the SGS in the minds of everybody. So their outcome of using technology is to drive decarbonization. And they don't make sure that, you know, they achieve the goals of E. S G. Right There is another customer of ours in the retail space. They are saying we want to use cloud to drive experience for our employees. So I would say that you know, there is pretty much, you know, all these drivers which are helping not just growing their business, but also bettering the experience and meeting some of the organisation goals that they have set up with respect to cloud. So I would say Cloud is playing a big role in every digital transformation initiative of the company. >>How do you spend your time? What's the role of the CEO inside of a large organisation like Infosys? >>So, um, one is in terms of bringing in an outside in view of how technology is making an impact to our customers. And I'm looking at How do we actually start liberating some of these technologies in building solutions, you know, which can actually drive value for our customers? That's one of the focus areas. You know what I do? Um, And if you look at some of the trends, you know what we have seen in the past years as well as what we're seeing now? Uh, there's been a huge spend around cloud which is happening with our customers and predominantly around the cloud Native application development, leveraging some of the services. What's available from the cloud providers like eh? I am l in Hyoty. Um, and and there's also a new trend. You know what we are seeing off late now, which is, um, in terms of improving the experience overall experience liberating some of the technologies, like technologies like block, block, chain as well as we are, we are right, and and this is actually creating new set of solutions. Um, new demands, you know, for our customers in terms of leveraging technologies like matadors leveraging technologies like factory photo. Um, and these are all opportunities for us to build solutions, you know, which can, you know, improve the time to market for our customers in terms of adopting some of these things. Because there has been a huge focus on the improved end user experience or improve experience improved, uh, productivity of, uh, employees, you know, which is which has been a focus. Uh, post pandemic. Right? You know, it has been something which is happening pre pandemic, but it's been accelerated Post pandemic. So this is giving an opportunity for for my role right now in terms of liberating these technologies, building solutions, building value propositions, taking it to our customers, working with partners and then trying to see how we can have this tightly integrated with partners like HP E in this case, and then take it jointly to the market and and find out you know, what's what's the best we can actually give back to our customers? >>You know, you guys have been we've been following you guys for for a long, long time. You've seen many cycles, uh, in the industry. Um, and what's interesting to get your reaction to what we're seeing? A lot of acceleration points, whether it's cloud needed applications. But one is the software business is no longer there. It's open source now, but cloud scale integrations, new hybrid environment kind of brings and changes the game, so there's definitely software plentiful. You guys are doing a lot of stuff with the software. How are customers integrated? Because seeing more and more customers participating in the open source community uh, so what? Red hat's done. They're transforming the open shift. So as cloud native applications come in and get scale and open source software, cloud scale performance and integrations are big. You guys agree with that? >>Absolutely. Absolutely. So if you if you look at it, um, right from the way we can't socialise those solutions, um, open source is something What we have embedded big way right into the solution. Footprint. What we have one is, uh, the ability for us to scale the second is the ability for us to bring in a level of portability, right? And the third is, uh, ensuring that there is absolutely no locking into something. What we're building. We're seeing this this being resonated by our customers to because one is they want to build a child and scalable applications. Uh, it's something where the whole, I would say, the whole dependency on the large software stacks. Uh, you know, the large software providers is likely diminishing now, right? Uh, it's all about how can I simplify my application portfolio Liberating some of the open source technologies. Um, how can I deploy them on a multi cloud world liberating open standards so that I'm not locked into any of these providers? Um, how can I build cloud native applications, which can actually enable portability? And how can I work with providers who doesn't have a lock in, you know, into their solutions, >>And security is gonna be embedded in everything. Absolutely. >>So security is, uh, emperor, right from, uh, design phase. Right? You know, we call it a secure by design And that's something What? We drive for our customers right from our solutions as well as for developing their own solutions >>as opposed to secure by bolt on after the fact. What is the cobalt go to market strategy? How does that affect or how you do business within the HP ecosystem? Absolutely. >>I think you know what we did in, uh, in 2000 and 20. We were the first ones, uh, to come out with an integrated cloud brand called Cobalt. So essentially, our thought process was to make sure that, you know, we talk one consistent language with the customer. There is a consistent narrative. There is a consistent value proposition that we take right. So, essentially, if you look at the Cobalt gold market, it is based on three pillars. The first pillar is all about technology solutions. Getting out of data centres migrating were close to cloud E r. P on Cloud Cloud, Native Development, legacy modernisation. So we'll continue to do that because that's the most important pillar. And that's where our bread and butter businesses right. The second pillar is, uh, more and more customers are asking industry cloud. So what are you specifically doing for my industry. So, for example, if you look at banking, uh, they would say we are focused on Modernising our payment systems. We want to reduce the financial risk that we have because of anti money laundering and those kind of solutions that they're expecting. They want to better the security portion. And of course, they want to improve the experience, right? So they are asking for each of these imperatives that we have in banking. What are some of those specific industry solutions that you are bringing to the table? Right. So that's the second pillar of our global go to market. And the third pillar of our go to market as soon as I was saying is looking at what we call us Horizon three offerings, whether it is metal wars, whether it is 13.0, whether it is looking at something else that will come in the future. And how do we build those solutions which can become mainstream the next 18 to 24 months? So that's essentially the global >>market. That's interesting. Okay, so take the banking example where you've got a core app, it's probably on Prem, and it's not gonna have somebody shoved into the cloud necessarily. But they have to do things like anti money, money laundering and know your ky. See? How are they handling that? Are they building micro services? Are you building for them microservices layers around that that actually might be in the cloud or cloud Native on Prem and Greenway. How is that? How are customers Modernising? >>Absolutely brilliant question. In fact, what we have done is, uh, as part of cobalt, we have something called a reference. Architecture are basically a blueprint. So if you go to a bank and you're engaging a banking executive, uh, the language that we speak with them is not about, uh, private cloud or public cloud or AWS or HP or zero, right? I mean, we talk the language that they understand, which is the banking language. So we take this reference architecture, and we say here is what your core architecture should look like. And, as you rightly called out, there is K. I see there is retail banking. There is anti money laundering. There is security experience. Uh, there are some kpi s and those kind of things banking a PSR open banking as we call, How do we actually bring our solutions, which we have built on open source and something that are specific to cloud and something that our cloud neutral and that's what we take them. So we built this array of solutions around each of those reference architectures that we take to our customers. >>Final question for you guys. How are you guys leveraging the H, P E and new Green Lake and all the new stuff they got here to accelerate the customers journey to edge the cloud? >>So I would say it on three areas right now. This is one is Obviously we are working very closely with HP in terms of taking out solutions jointly to the market and, um, leveraging the whole green late model and providing what I call it as a hyper scale of like experience for our customers in a hybrid, multi cloud world. That's the first thing. The second thing is Onion talked about the cobalt, right? It's an important, I would say, an offering from, uh, you know and offering around cloud from our side. So what we've done is we've closely integrated the assets. You know what I was referring to what we have in our cobalt, uh, under other Kobold umbrella very closely with the HP ecosystem, right? You know, it can be tools like the Emphasis Polly Cloud Platform or the Emphasis pollinate platform very tightly integrated with the HP stack, so that we could actually offer the value proposition right across the value chain. The thought of you know we have actually taken the industry period, like what again mentioned right in terms of rather than talking about a public cloud or a private cloud solution or an edge computing solution. We actually talk about what exactly are the problem statements? What is there in manufacturing today? Or it's there in financial industries today? Or or it's in a bank today or whatever it's relevant to the industry. That's an industry people. So we talk right from an industry problem and and and and and and build that industry, industry people solutions, leveraging the assets, what we have in the and the framework that we have within the couple, plus the integrated solutions. What we bring along with HB. That's that's Those are the three things, what we do along with >>it and that that industry pieces do. There's a whole data layer emerging those industries learning cos they're building their own clouds. Look, working with companies like you because they want to monetise. That's a big part of their digital strategy, guys. Thanks so much for coming on the cue. Thank you. Appreciate your time. Thank >>you. Thank you very much. Really appreciate. >>Thank you. Thank you for watching John and I will be back. John Ferrier, Development at HPD Discovered 2022. You're watching the queue? >>Yeah. >>Mm.

>>Hello, and welcome to the cubes. Continuous coverage of AWS reinvent 2021. I'm Dave Nicholson, and we're running an incredible event this year. One of the most important technology events. It's a hybrid event with two live stages. Two sets here in Las Vegas. Two studios we've interviewed more than a hundred guests and two distinguished guests that I have here from emphasis today have joined us. Thank you very much. Uh, Mr., who's the executive vice president of Infosys cobalt. And we'll talk about what that is exactly in a moment along with David Wilson, Wilson, I'm sorry, senior vice president and head of global alliances in the partner ecosystem for Infosys gentlemen. Welcome. Thank you. Thank you very much. So let's cut right to the chase cobalt. And when you tell your family that you're executive vice-president of cobalt, do they just smile and immediately nod? Like they know what it is? Absolutely. >>In fact, uh, in fact it is so exciting for us, uh, what we did at Infosys, just to define cobalt in one sentence, it is a set of services, solutions, and products that we are bringing together to solve, you know, accelerate our customer's journey or what we call as the customer's digital journey. So in slough, everybody talking about Kala cloud in a different way, with different narratives, different value proposition we had in forces. And by the way, we were the first ones in the world to combine all of this and the one brand called cobalt. So that's essentially what cobalt is. So anything and everything that we do in cloud, it's all under this brand called cobalt and that's Infosys cobalt. >>So does, does Infosys cobalt include a combination of bespoke solutions, cheering for people as well as packaged standardized things? How do you, how do you strike a balance because you can't have a one size fits all? Uh, what does that look like? How do you segregate those? >>Yes. Great question. So, so essentially what you are done with a cobalt is a delicate cobalt. In two ways. One is there are customers who want a solutions to solve technology problems. It could be getting out of data centers, it could be migrating workloads to cloud. It could be analytics on cloud ERP on cloud daddy's mainframe modernization, and, you know, getting off mainframes. And at the same time, there are industry verticals like financial services, retail manufacturing, and of course, life sciences, and many more who want to understand what are the business solutions and what are the solutions that we have for solving their business problems. So essentially cobalt is a bespoke solutions. It has products, it has platforms, and we have brought all of this together and we take it to our customers. So essentially these are industry blueprints. These are reference architectures. So we have 250 industry blueprints and around 25,000, that's it that we can actually take to our customers to help their digital journey. >>So, David, I imagine that key to the success of cobalt is, uh, uh, the idea of partnerships, talk about the alliances, uh, uh, that, uh, that you're involved with specifically the way that cobalt interacts with the AWS yes. >>Universe. Absolutely. So the, you know, as we designed our cobalt strategy, the partners are a major component of this. They contribute to it. They're part of the design. And ultimately when we go to the clients with these solutions, these assets, uh, our partners, components are baked right into the solution. In the case of AWS, we've been so successful with it that we recognize this week, uh, as their industry solutions partner of the year. Congratulations. Yeah. So I was joking. We should bring our trophy and put it in between, but we emphasis is invested heavily in developing the, the partner ecosystem, you know, gone are the days where our clients are, uh, putting out an RFP and purchasing individual piece parts, and then, you know, searching at NSI. They're looking for a business outcomes and, uh, uh, emphasis along with our cobalt strategy is able to work with partners like AWS and go there and sell an outcome and accelerate the whole. >>Well, you mentioned RFPs. Uh, what is your, uh, what is your go-to market strategy look like in terms of engaging with those end user clients? Um, is it in partnership with AWS? Is it led by Infosys bringing in AWS where appropriate some mix of the two? What does that look like in this world of cooperation and petition that we're in, >>It's actually a mix of two. So essentially the way we go to market is that there are solutions that Infosys has built on AWS that we will take to our customers. There are solutions that you have built, which are cloud neutral, and those are some things that we take to the customers. And the third one, which is very important is co-creating solutions for our customers along with AWS. So our go to market is a combination of all of them, and that's what makes it exciting. >>So a non-test running cobalt, you're, you're responsible for alliances. You guys are probably in contact a lot with one another. All of these crazy new things are announced at AWS. I'm sure you get a little bit of a preview of it. It's not a complete, it's not a complete surprise when you arrive, but you've gotta be screaming for teams and solutions to leverage some of the coolest stuff within cobalt. How does that, how does that conversation go? >>Yeah, so David David and I work very closely, right? In fact, uh, uh, the way, the way we do things is our go to market cannot be complete without partners. So similarly my strategy and our strategy and global cannot be complete without David. So we actually worked together to identify, in fact, we have been visiting a lot of boots. We got to create, we've gone to a lot of great ideas. We want to see how we can bring them into the cobalt framework and bundle some of that as part of our solutions. So we keep looking at those, we'll look at the announcements that were made and we'll solve, you know, identify many more sales motions that we can take to the, >>So David talk about some of the things you've seen here at re-invent this week that are specifically relevant for cobalt and emphasis customer. >>Well, what's some of the most exciting discussions we've been having is with, uh, not only, uh, AWS themselves about the, the announcements and the way in which we can leverage them, leverage them and go to market. But, uh, AWS has built out their own partner ecosystem, uh, that we then interact with. So we've had some exciting conversations with AWS's ISV partners, their, uh, their other solution providers about how we can bring this together and go to market together. You know, when, when an example, we had a lot of discussions this week was about, uh, how we're doing it, right? The mainframe services, uh, that were announced and how we can support them in building out our industry specific assets. So, you know, taking a kernel of what AWS provides and then wrapping our secret sauce around it, in partnership with other companies and then take into our clients, you know, that's what we're, I, it, the good part is we can quickly go from a discussion to a, go to market, a dialogue with our direct clients who are also here, which have been in real-time having those discussions. >>So emphasis a non has been a trusted advisor for clients predating the Dawn of cloud, if you will. Uh, and I'm sure that certain slices of your revenue don't wanna make this too uncomfortable. A question certain slices of your revenue are still dependent upon all of that. 80% of it. That's still on prem. How do you manage that? You're, you're laser focused on cobalt and you've got alliances. Um, everybody's looking towards the cloud. How do you balance that with the very real needs of Infosys as a business? Aren't you in the same boat as your customers, in terms of transformation? >>Well, you know, I, I would, I'm sorry, >>My eyes go back and forth. See, I told you it was gonna be easy for us to have a conversation. Yeah. Jump into >>W when you, when you look at the different partners out there, we have a discussion about being asset heavy asset light emphasis. Um, we, we grew up through application management, uh, and now as we're seeing these transformations go forward, the last thing we wanted to be is a server huggers. Uh, we're ready to accelerate these transformations as fast as possible. And, uh, you know, partners like AWS are recognizing that, uh, a non steam can go in there and be the disruptor to actually accelerate those transformation. >>Absolutely. In fact, involved when we spoke to some of the AWS executives, uh, we want to be the challenger, right? Because we don't carry any baggage. Uh, we clearly believe, as Gartner says that a cloud is going to be the, for business innovation, and we want to drive innovation and transformation for our customers. So essentially we want to make this relationship with AWS much bigger and better. We want to be the partners with our clients to drive business innovation with industry segments, industry clouds, solutions that drive opening, new markets, building better products and solutions, helping get better customer intimacy and those kinds of things. And so that's essentially what our thought processes with, uh, what we want to do. >>It's been mentioned a few times here that, uh, somewhere around 80 to 85% of it spend is still on premises. It's not in the cloud yet. So despite how large, we all think the AWS AWS universe has become so far, we're really just at the beginning stages. But what are you seeing in terms of clients hesitancy towards cloud at this point, has that changed over the last couple of years? Uh, what are the inhibiting factors that you see? What are the accelerants that you see at this stage of the game? >>Well, in fact, in fact, COVID unfortunately Colbert, uh, while it was all a very bad thing, but it actually helped accelerate customer's journey to cloud. Uh, in fact, uh, the, we have several customers who used to say that, you know, everybody has to come to office to work. Nobody can work remotely because there are security constraints that is, there will be impacted the security posture, but to when we hit March, 2020, and everybody had to work remote, it's the same set of customers who decided to go to cloud and started limited him to part of cloud. So I would say COVID in short has accelerated customers knowledge about cloud. They are no longer worried about security. They're no longer worried about, uh, latency and bandwidth. I think I don't see any major hesitancy at this point of time. Uh, but the trend that we're seeing towards cloud is cloud is going to be used more for innovation. And it's not just going to be about, take my data center and moving to cloud, right? So it's not going to be just those tactical reasons. Uh, and that's exactly what we did. We actually came out with a report, which says, moving from cloud chaos to cloud clarity, and it talks about all these facets of what are those strengths that customer should look for. So that's essentially what we use. >>So I imagine cobalt one of the kind of main ideas behind it is to remove friction associated with that move to cloud, to the extent that you can not be reinventing the wheel every single time you're engaging a customer. Is that, is that a fair statement? >>In fact, you know, many customers of ours, in fact, almost all of them are saying, we do not want to reinvent the wheel. So how can you help us? So what we have done as part of cobalt is to bring these reference architectures, right? So for example, if a financial services customer wants to fight fraud, fraud analytics is a reference architecture that we have. Uh, if the telco customer wants to implement 5g, we have a framework and a reference architecture for OSS BSS on cloud. Uh, if there is licenses customer who wants to basically look at drug discovery, we have an architecture for that. So we want to make it more and more in a inference architecture based without reinventing the wheel and bring the best practices from other customers to drive those scenarios. So that's essentially what we do. >>So cobalt underway, you've been recognized for a performance to this point. It's a lot of pressure for 2022. So what are you going to, what do you, what, what, what are you going to slap on the desk in 2022? When we get back together, >>We do plan to up bookends by this time next year, to, to able to pre >>It is perfectly acceptable by the way, to share both the 20, 21 and 2022 award on stage, because we have to make up for 2019 when we weren't here physically. >>But to build off of, with a, knotless saying about the, uh, you know, what's going on in the last 18 to 24 months, you know, we're seeing clients now that we have one that, uh, came to us with a 114 list of products that they bought from various partners, either directly through distributors and such and saying, listen, we no longer want to be in the procurement function. You know, we want to take these hundred and 14 products. We recognize we're going to get it down to 30 or 40 of the key ones, obviously a shifting a lot of that to cloud. And we were able to leverage emphasis cobalt to actually accelerate that and incorporate our partner components to help that shift. So I think next year, I think that will be a major theme that you're seeing clients recognize that the, the way in which they procure and they develop their it platform will be much different. And emphasis with the design we put in place will be in a key position to, to support them at that. Well, >>We recorded this. I'm not sure if you realized we were actually recording this, so we're going to go, we can go back and review this tape next year and we'll see. And I hope to see you then, David, thank you so much for joining us here at the cube and for the cube here in our continuous coverage at AWS reinvent 2021 live in Las Vegas. I'm Dave Nicholson saying stay tuned because there's always more on the cube. And I'd like to remind you that we are your leader in hybrid tech event coverage.

(upbeat music) >> From our studios in the heart of Silicon Valley, Palo Alto, California, this is a Cube Conversation. >> Hi and welcome to The Cube Studios for another Cube Conversation where we go in depth with thought leaders driving innovation across the tech industry. I'm your host, Peter Burris. One of the most interesting trends in the technology industry today is the application of AI, machine learning, deep learning, and other classes of advanced technology, to solving the types of business problems that could not be addressed before. And the outcomes that are being generated by these new toolings are significant and impressive, but they are not evenly distributed across the industry. Some companies are doing it really well, most companies are not. So, the promise is there, we just have to turn that promise into something that's more reliable, more repeatable, and more certain. Now, to have that conversation about how we're going to do that, we've got Anant Chintamaneni who's the vice president and general manager at HP, for their BlueData group. Anant, welcome to The Cube. >> It's great to be here, Peter, thank you. >> So, Anant, let's start with this notion of successful applications of AI and ML technology. What are you seeing in the industry? Am I wrong in characterizing that we're seeing some success, but just uneven success? >> Yeah, I completely agree with you. As a trusted partner for a large number of enterprises out there, and we work with hundreds of customers, and we intersect with them at various phases of their journey, we're seeing a tremendous growth in the interest for AI, machine learning, and even, in some cases, deep learning. I mean we're talking about enterprises across financial services, retail, health care, manufacturing, in the auto industry especially, with autonomous cars. The evolution from collecting all that big data, unstructured data, doing analytics on it, the logical next step for them is to exploit that data further and get prescriptive and predictive analytics. So, absolutely, it's the next frontier for a lot of these organizations, and it's a boardroom mandate. >> And we're seeing it turn into specific operational capabilities that are absolutely essential to how the business makes money and how the business serves its customers, but I can tell you, and I want to test this with you: I hear, all the time, customers telling me that it's just too complex that all these use cases are driving off in bespoke workflows to actually achieve the use cases in a variety of different roles and responsibilities. That seems like it's a prescription that's going to only lead to periodic success. Have I got that right? >> Absolutely. I mean, if you look at what you can do with data and analytics, there's obviously different types of business users and business use cases. We're talking about in financial services or even retail, any of these large enterprises that have customer-facing operations, there's value to be generated at the time you intersect with the customer. There's value to be generated in identifying opportunities to upsell, cross-sell. There's also opportunities around just revenue generation, coming up with new business models. Let's face it: all these industries are being disrupted, and they're trying to come up with ways by which they can be more data-driven and create these new business models. The problem is that, when you have these different groups, there's a number of use cases, and there's a number of different ways to solve it. You have human beings involved there who have their tools of choice, who have their specific methodologies in trying to go after a specific problem, so there's no uniformity and no uniform platform either, so each of these silos of environment that are being created, so you have this trend where you have exponentially going instead of use cases, but then the workflows are not there for them to kind of scale these use cases in a consistent, repeatable fashion even if you're using different tools. >> And I think, what really, we're trying to suggest that enterprises do is allow problems to suggest their own sets of solutions using data science and related technologies, but come up with a way to ensure a uniformity of success. Now, to do that, it seems as though we need to start thinking about how we're going to operationalize those workflows that tie the data science work to the actual implementation and run times that lead to the business getting the outcomes that they want. >> Absolutely. I think, for the last several years, everybody was fascinated by creating the best Python-based machine learning model or now, more recently, doing modeling with autonomous machine learning type of techniques. And there's a lot of different ways to create these models that demonstrates some success in the lab, but ultimately, if you want to get business value from those models and all the hard work that you've done, it has to be injected into the business process, whether that's, like we talked about, the use cases, whether it's doing scoring at the edge to find a defect in a manufacturing process that is a multimillion-dollar cost, or if you are trying to run something on a nightly basis or on an hourly basis to identify fraud or security breaches. So, you're absolutely right that operationalization of machine learning is ultimately the key, and I think that's the progression that enterprises have to make, which is they made lots of investments in talent, in tools to create these models, but they have to figure out how to operationalize them, and so that's absolutely the next frontier. And I think, if you look at the New Age companies, they've got unified platforms where it's easy for their data scientists to come up with an idea, try out different tools, access the data, and then operationalize that model, so you have a feature or a capability in these New Age Internet properties available within days, sometimes even hours, and that's a capability that's missing in the enterprises. So, I think that discipline of operationalization, allowing users to work with their tools of choice, access their datasets, but all in the context of security and governance and trying to operationalize it, is absolutely where these enterprises need to go in order to get success and real business value. >> Well, you mentioned the edge. It seems as though another element must be that it also can target to the infrastructure where it naturally can run so that we're not trying to force-fit everything up into a cloud where we move all the data around. There are going to be circumstances where the nature of the data, the nature of the model, requires that it run proximate to some activity. Have I got that right? >> Absolutely. I think, if you look at when you operationalize a model and when you're talking about a manufacturing facility or even like a car, which is practically the edge, then you need to be able to take your model and operationalize it at the edge so you can do inferencing. You could give the signals that need to happen at that point in time. And, similarly, there are other more mundane type of operations that will happen where the data is actually present or being generated whether that's in the cloud or in the data center. >> So, Anant, we've talked about the need to operationalize. Just give us a very, very quick view of how that need translates into actual offers and services. >> Yeah, so we've been working with our customers to essentially give them a set of capabilities that allows them to have the necessary tools to capture the data, process the data. I mean this has been happening for the last several years with the whole big data management space, fast data management space. So, we give a set of tools to allow customers to do data engineering, we allow the data scientist which is the persona that is interested in creating the model, the right set of visual interfaces, and/or the ability to onboard their product of choice so that they can be more productive, they can share their models, they can version them, and then, eventually, a set of tools for the devops and the operations team to take those models and deploy them. And that comprehensive, end-to-end capability which is to build, which is to then deploy, monitor, and then have that closed-loop process, so again, being able to monitor that model, see how it's deviating, and go through that closed-loop cycle, is the set of capabilities that we're providing in an integrated product. >> Anant Chintamaneni, vice president at HPE, working with the BlueData team, thanks very much for being on The Cube. >> Thank you, Peter, thanks for the opportunity. >> And, once again, thanks for joining us for another Cube Conversation. I'm Peter Burris, see you next time. (upbeat music)

>> Live from New York. It's theCUBE. Covering theCUBE New York City, 2018. Brought to you by SiliconANGLE Media, and it's ecosystem partners. >> I'm John Furrier with Peter Burris, our next two guests are Jim Franklin with Dell EMC Director of Product Management Anant Chintamaneni, who is the Vice President of Products at BlueData. Welcome to theCUBE, good to see you. >> Thanks, John. >> Thank you. >> Thanks for coming on. >> I've been following BlueData since the founding. Great company, and the founders are great. Great teams, so thanks for coming on and sharing what's going on, I appreciate it. >> It's a pleasure, thanks for the opportunity. >> So Jim, talk about the Dell relationship with BlueData. What are you guys doing? You have the Dell-ready solutions. How is that related now, because you've seen this industry with us over the years morph. It's really now about, the set-up days are over, it's about proof points. >> That's right. >> AI and machine learning are driving the signal, which is saying, 'We need results'. There's action on the developer's side, there's action on the deployment, people want ROI, that's the main focus. >> That's right. That's right, and we've seen this journey happen from the new batch processing days, and we're seeing that customer base mature and come along, so the reason why we partnered with BlueData is, you have to have those softwares, you have to have the contenders. They have to have the algorithms, and things like that, in order to make this real. So it's been a great partnership with BlueData, it's dated back actually a little farther back than some may realize, all the way to 2015, believe it or not, when we used to incorporate BlueData with Isilon. So it's been actually a pretty positive partnership. >> Now we've talked with you guys in the past, you guys were on the cutting edge, this was back when Docker containers were fashionable, but now containers have become so proliferated out there, it's not just Docker, containerization has been the wave. Now, Kubernetes on top of it is really bringing in the orchestration. This is really making the storage and the network so much more valuable with workloads, whether respective workloads, and AI is a part of that. How do you guys navigate those waters now? What's the BlueData update, how are you guys taking advantage of that big wave? >> I think, great observation, re-embrace Docker containers, even before actually Docker was even formed as a company by that time, and Kubernetes was just getting launched, so we saw the value of Docker containers very early on, in terms of being able to obviously provide the agility, elasticity, but also, from a packaging of applications perspective, as we all know it's a very dynamic environment, and today, I think we are very happy to know that, with Kubernetes being a household name now, especially a tech company, so the way we're navigating this is, we have a turnkey product, which has containerization, and then now we are taking our value proposition of big data and AI and lifecycle management and bringing it to Kubernetes with an open source project that we launched called Cube Director under our umbrella. So, we're all about bringing stateful applications like Hadoop, AI, ML to the community and to our customer base, which is some of the largest financial services in health care customers. >> So the container revolution has certainly groped developers, and developers have always had a history of chasing after the next cool technology, and for good reason, it's not like just chasing after... Developers tend not to just chase after the shiny thing, they chased after the most productive thing, and they start using it, and they start learning about it, and they make themselves valuable, and they build more valuable applications as a result. But there's this interesting meshing of creators, makers, in the software world, between the development community and the data science community. How are data scientists, who you must be spending a fair amount of time with, starting to adopt containers, what are they looking at? Are they even aware of this, as you try to help these communities come together? >> We absolutely talk to the data scientists and they're the drivers of determining what applications they want to consume for the different news cases. But, at the end of the day, the person who has to deliver these applications, you know data scientists care about time to value, getting the environment quickly all prepared so they can access the right data sets. So, in many ways, most of our customers, many of them are unaware that there's actually containers under the hood. >> So this is the data scientists. >> The data scientists, but the actual administrators and the system administrators were making these tools available, are using containers as a way to accelerate the way they package the software, which has a whole bunch of dependent libraries, and there's a lot of complexity our there. So they're simplifying all that and providing the environment as quickly as possible. >> And in so doing, making sure that whatever workloads are put together, can scaled, can be combined differently and recombined differently, based on requirements of the data scientists. So the data scientist sees the tool... >> Yeah. >> The tool is manifest as, in concert with some of these new container related technologies, and then the whole CICD process supports the data scientist >> The other thing to think about though, is that this also allows freedom of choice, and we were discussing off camera before, these developers want to pick out what they want to pick out what they want to work with, they don't want to have to be locked in. So with containers, you can also speed that deployment but give them freedom to choose the tools that make them best productive. That'll make them much happier, and probably much more efficient. >> So there's a separation under the data science tools, and the developer tools, but they end up all supporting the same basic objective. So how does the infrastructure play in this, because the challenge of big data for the last five years as John and I both know, is that a lot of people conflated. The outcome of data science, the outcome of big data, with the process of standing up clusters, and lining up Hadoop, and if they failed on the infrastructure, they said it was a failure overall. So how you making the infrastructure really simple, and line up with this time of value? >> Well, the reality is, we all need food and water. IT still needs server and storage in order to work. But at the end of the day, the abstraction has to be there just like VMware in the early days, clouds, containers with BlueData is just another way to create a layer of abstraction. But this one is in the context of what the data scientist is trying to get done, and that's the key to why we partnered with BlueData and why we delivered big data as a service. >> So at that point, what's the update from Dell EMC and Dell, in particular, Analytics? Obviously you guys work with a lot of customers, have challenges, how are you solving those problems? What are those problems? Because we know there's some AI rumors, big Dell event coming up, there's rumors of a lot of AI involved, I'm speculating there's going to be probably a new kind of hardware device and software. What's the state of the analytics today? >> I think a lot of the customers we talked about, they were born in that batch processing, that Hadoop space we just talked about. I think they largely got that right, they've largely got that figured out, but now we're seeing proliferation of AI tools, proliferation of sandbox environments, and you're psyched to see a little bit of silo behavior happening, so what we're trying to do is that IT shop is trying to dispatch those environments, dispatch with some speed, with some agility. They want to have it at the right economic model as well, so we're trying to strike a better balance, say 'Hey, I've invested in all this infrastructure already, I need to modernize it, and that I also need to offer it up in a way that data scientists can consume it'. Oh, by the way, we're starting to see them start to hire more and more of these data scientists. Well, you don't want your data scientists, this very expensive, intelligent resource, sitting there doing data mining, data cleansing, detail offloads, we want them actually doing modeling and analytics. So we find that a lot of times right now as you're doing an operational change, the operational mindset as you're starting to hire these very expensive people to do this very good work, at the corest of the data, but they need to get productive in the way that you hired them to be productive. >> So what is this ready solution, can you just explain what that is? Is it a program, is it a hardware, is it a solution? What is the ready solution? >> Generally speaking, what we do as a division is we look for value workloads, just generally speaking, not necessarily in batch processing, or AI, or applications, and we try and create an environment that solves that customer challenge, typically they're very complex, SAP, Oracle Database, it's AI, my goodness. Very difficult. >> Variety of tools, using hives, no sequel, all this stuff's going on. >> Cassandra, you've got Tensorflow, so we try fit together a set of knowledge experts, that's the key, the intellectual property of our engineers, and their deep knowledge expertise in a certain area. So for AI, we have a sight of them back at the shop, they're in the lab, and this is what they do, and they're serving up these models, they're putting data through its paces, they're doing the work of a data scientist. They are data scientists. >> And so this is where BlueData comes in. You guys are part of this abstraction layer in the ready solutions. Offering? Is that how it works? >> Yeah, we are the software that enables the self-service experience, the multitenancy, that the consumers of the ready solution would want in terms of being able to onboard multiple different groups of users, lines of business, so you could have a user that wants to run basic spark, cluster, spark jobs, or you could have another user group that's using Tensorflow, or accelerated by a special type of CPU or GPU, and so you can have them all on the same infrastructure. >> One of the things Peter and I were talking about, Dave Vellante, who was here, he's at another event right now getting some content but, one of the things we observed was, we saw this awhile ago so it's not new to us but certainly we're seeing the impact at this event. Hadoop World, there's now called Strata Data NYC, is that we hear words like Kubernetes, and Multi Cloud, and Istio for the first time. At this event. This is the impact of the Cloud. The Cloud has essentially leveled the Hadoop World, certainly there's some Hadoop activity going on there, people have clusters, there's standing up infrastructure for analytical infrastructures that do analytics, obviously AI drives that, but now you have the Cloud being a power base. Changing that analytics infrastructure. How has it impacted you guys? BlueData, how are you guys impacted by the Cloud? Tailwind for you guys? Helpful? Good? >> You described it well, it is a tailwind. This space is about the data, not where the data lives necessarily, but the robustness of the data. So whether that's in the Cloud, whether that's on Premise, whether that's on Premise in your own private Cloud, I think anywhere where there's data that can be gathered, modeled, and new insights being pulled out of, this is wonderful, so as we ditched data, whether it's born in the Cloud or born on Premise, this is actually an accelerant to the solutions that we built together. >> As BlueData, we're all in on the Cloud, we support all the three major Cloud providers that was the big announcement that we made this week, we're generally available for AWS, GCP, and Azure, and, in particular, we start with customers who weren't born in the Cloud, so we're talking about some of the large financial services >> We had Barclays UK here who we nominated, they won the Cloud Era Data Impact Award, and what they're actually going through right now, is they started on Prem, they have these really packaged certified technology stacks, whether they are Cloud Era Hadoop, whether they are Anaconda for data science, and what they're trying to do right now is, they're obviously getting value from that on Premise with BlueData, and now they want to leverage the Cloud. They want to be able to extend into the Cloud. So, we as a company have made our product a hybrid Cloud-ready platform, so it can span on Prem as well as multiple Clouds, and you have the ability to move the workloads from one to the other, depending on data gravity, SLA considerations. >> Compliancy. >> I think it's one more thing, I want to test this with you guys, John, and that is, analytics is, I don't want to call it inert, or passive, but analytics has always been about getting the right data to human beings so they can make decisions, and now we're seeing, because of AI, the distinction that we draw between analytics and AI is, AI is about taking action on the data, it's about having a consequential action, as a result of the data, so in many respects, NCL, Kubernetes, a lot of these are not only do some interesting things for the infrastructure associated with big data, but they also facilitate the incorporation of new causes of applications, that act on behalf of the brand. >> Here's the other thing I'll add to it, there's a time element here. It used to be we were passive, and it was in the past, and you're trying to project forward, that's no longer the case. You can do it right now. Exactly. >> In many respects, the history of the computing industry can be drawn in this way, you focused on the past, and then with spreadsheets in the 80s and personal computing, you focused on getting everybody to agree on the future, and now, it's about getting action to happen right now. >> At the moment it happens. >> And that's why there's so much action. We're passed the set-up phase, and I think this is why we're hearing, seeing machine learning being so popular because it's like, people want to take action there's a demand, that's a signal that it's time to show where the ROI is and get action done. Clearly we see that. >> We're capitalists, right? We're all trying to figure out how to make money in these spaces. >> Certainly there's a lot of movement, and Cloud has proven that spinning up an instance concept has been a great thing, and certainly analytics. It's okay to have these workloads, but how do you tie it together? So, I want to ask you, because you guys have been involved in containers, Cloud has certainly been a tailwind, we agree with you 100 percent on that. What is the relevance of Kubernetes and Istio? You're starting to see these new trends. Kubernetes, Istio, Cupflow. Higher level microservices with all kinds of stateful and stateless dynamics. I call it API 2.0, it's a whole other generation of abstractions that are going on, that are creating some goodness for people. What is the impact, in your opinion, of Kubernetes and this new revolution? >> I think the impact of Kubernetes is, I just gave a talk here yesterday, called Hadoop-la About Kubernetes. We were thinking very deeply about this. We're thinking deeply about this. So I think Kubernetes, if you look at the genesis, it's all about stateless applications, and I think as new applications are being written folks are thinking about writing them in a manner that are decomposed, stateless, microservices, things like Cupflow. When you write it like that, Kubernetes fits in very well, and you get all the benefits of auto-scaling, and so control a pattern, and ultimately Kubernetes is this finite state machine-type model where you describe what the state should be, and it will work and crank towards making it towards that state. I think it's a little bit harder for stateful applications, and I think that's where we believe that the Kubernetes community has to do a lot more work, and folks like BlueData are going to contribute to that work which is, how do you bring stateful applications like Hadoop where there's a lot of interdependent services, they're not necessarily microservices, they're actually almost close to monolithic applications. So I think new applications, new AI ML tooling that's going to come out, they're going to be very conscious of how they're running in a Cloud world today that folks weren't aware of seven or eight years ago, so it's really going to make a huge difference. And I think things like Istio are going to make a huge difference because you can start in the cloud and maybe now expand on to Prem. So there's going to be some interesting dynamics. >> Without hopping management frameworks, absolutely. >> And this is really critical, you just nailed it. Stateful is where ML will shine, if you can then cross the chasma to the on Premise where the workloads can have state sharing. >> Right. >> Scales beautifully. It's a whole other level. >> Right. You're going to the data into the action, or the activity, you're going to have to move the processing to the data, and you want to have nonetheless, a common, seamless management development framework so that you have the choices about where you do those things. >> Absolutely. >> Great stuff. We can do a whole Cube segment just on that. We love talking about these new dynamics going on. We'll see you in CF CupCon coming up in Seattle. Great to have you guys on. Thanks, and congratulations on the relationship between BlueData and Dell EMC and Ready Solutions. This is Cube, with the Ready Solutions here. New York City, talking about big data and the impact, the future of AI, all things stateful, stateless, Cloud and all. It's theCUBE bringing you all the action. Stay with us for more after this short break.

(orchestral music) >> Hi, I'm Peter Burris and welcome to another digital community event. As we do with all digital community events, we're gonna start off by having a series of conversations with real thought leaders about a topic that's pressing to today's enterprises as they try to achieve new classes of business outcomes with technology. At the end of that series of conversations, we're gonna go into a crowd chat and give you an opportunity to voice your opinions and ask your questions. So stay with us throughout. So, what are we going to be talking about today? We're going to be talking about the challenge that businesses face as they try to apply AI, ML, and new classes of analytics to their very challenging, very difficult, but nonetheless very value-producing outcomes associated with data. The challenge that all these businesses have is that often, you spend too much time in the infrastructure and not enough time solving the problem. And so what's required is new classes of technology and new classes of partnerships and business arrangements that allow for us to mask the underlying infrastructure complexity from data science practitioners, so that they can focus more time and attention on building out the outcomes that the business wants and a sustained business capability so that we can continue to do so. Once again, at the end of this series of conversations, stay with us, so that we can have that crowd chat and you can, again, ask your questions, provide your insights, and participate with the community to help all of us move faster in this crucial direction for better AI, better ML and better analytics. So, the first conversation we're going to have is with Anant Chintamaneni. Anant's the Vice President of Products at BlueData. Anant, welcome to theCUBE. >> Hi Peter, it's great to be here. I think the topic that you just outlined is a very fascinating and interesting one. Over the last 10 years, data and analytics have been used to create transformative experiences and drive a lot of business growth. You look at companies like Uber, AirBnB, and you know, Spotify, practically, every industry's being disrupted. And the reason why they're able to do this is because data is in their DNA; it's their key asset and they've leveraged it in every aspect of their product development to deliver amazing experiences and drive business growth. And the reason why they're able to do this is they've been able to leverage open-source technologies, data science techniques, and big data, fast data, all types of data to extract that business value and inject analytics into every part of their business process. Enterprises of all sizes want to take advantage of that same assets that the new digital companies are taking and drive digital transformation and innovation, in their organizations. But there's a number of challenges. First and foremost, if you look at the enterprises where data was not necessarily in their DNA and to inject that into their DNA, it is a big challenge. The executives, the executive branch, definitely wants to understand where they want to apply AI, how to kind of identify which huge cases to go after. There is some recognition coming in. They want faster time-to-value and they're willing to invest in that. >> And they want to focus more on the actual outcomes they seek as opposed to the technology selection that's required to achieve those outcomes. >> Absolutely. I think it's, you know, a boardroom mandate for them to drive new business outcomes, new business models, but I think there is still some level of misalignment between the executive branch and the data worker community which they're trying to upgrade with the new-age data scientists, the AI developer and then you have IT in the middle who has to basically bridge the gap and enable the digital transformation journey and provide the infrastructure, provide the capabilities. >> So we've got a situation where people readily acknowledge the potential of some of these new AI, ML, big data related technologies, but we've got a mismatch between the executives that are trying to do evidence-based management, drive new models, the IT organization who's struggling to deal with data-first technologies, and data scientists who are few and far between, and leave quickly if they don't get the tooling that they need. So, what's the way forward, that's the problem. How do we move forward? >> Yeah, so I think, you know, I think we have to double-click into some of the problems. So the data scientists, they want to build a tool chain that leverages the best in-class, open source technologies to solve the problem at hand and they don't want, they want to be able to compile these tool chains, they want to be able to apply and create new algorithms and operationalize and do it in a very iterative cycle. It's a continuous development, continuous improvement process which is at odds with what IT can deliver, which is they have to deliver data that is dispersed all over the place to these data scientists. They need to be able to provide infrastructure, which today, they're not, there's an impotence mismatch. It takes them months, if not years, to be able to make those available, make that infrastructure available. And last but not the least, security and control. It's just fundamentally not the way they've worked where they can make data and new tool chains available very quickly to the data scientists. And the executives, it's all about faster time-to-value so there's a little bit of an expectation mismatch as well there and so those are some of the fundamental problems. There's also reproducibility, like, once you've created an analytics model, to be able to reproduce that at scale, to be then able to govern that and make sure that it's producing the right results is fundamentally a challenge. >> Audibility of that process. >> Absolutely, audibility. And, in general, being able to apply this sort of model for many different business problems so you can drive outcomes in different parts of your business. So there's a huge number of problems here. And so what I believe, and what we've seen with some of these larger companies, the new digital companies that are driving business valley ways, they have invested in a unified platform where they've made the infrastructure invisible by leveraging cloud technologies or containers and essentially, made it such that the data scientists don't have to worry about the infrastructure, they can be a lot more agile, they can quickly create the tool chains that work for the specific business problem at hand, scale it up and down as needed, be able to access data where it lies, whether it's on-prem, whether it's in the cloud or whether it's a hybrid model. And so that's something that's required from a unified platform where you can do your rapid prototyping, you can do your development and ultimately, the business outcome and the value comes when you operationalize it and inject it into your business processes. So, I think fundamentally, this start, this kind of a unified platform, is critical. Which, I think, a lot of the new age companies have, but is missing with a lot of the enterprises. >> So, a big challenge for the enterprise over the next few years is to bring these three groups together; the business, data science world and infrastructure world or others to help with those problems and apply it successfully to some of the new business challenges that we have. >> Yeah, and I would add one last point is that we are on this continuous journey, as I mentioned, this is a world of open source technologies that are coming out from a lot of the large organizations out there. Whether it's your Googles and your Facebooks. And so there is an evolution in these technologies much like we've evolved from big data and data management to capture the data. The next sort of phase is around data exploitation with artificial intelligence and machine learning type techniques. And so, it's extremely important that this platform enables these organizations to future proof themselves. So as new technologies come in, they can leverage them >> Great point. >> for delivering exponential business value. >> Deliver value now, but show a path to delivery value in the future as all of these technologies and practices evolve. >> Absolutely. >> Excellent, all right, Anant Chintamaneni, thanks very much for giving us some insight into the nature of the problems that enterprises face and some of the way forward. We're gonna be right back, and we're gonna talk about how to actually do this in a second. (light techno music) >> Introducing, BlueData EPIC. The leading container-based software platform for distributed AI, machine learning, deep learning and analytics environments. Whether on-prem, in the cloud or in a hybrid model. Data scientists need to build models utilizing various stacks of AI, ML and DL applications and libraries. However, installing and validating these environments is time consuming and prone to errors. BlueData provides the ability to spin up these environments on demand. The BlueData EPIC app store includes, best of breed, ready to run docker based application images. Like TensorFlow and H2O driverless AI. Teams can also add their own images, to provide the latest tools that data scientists prefer. And ensure compliance with enterprise standards. They can use the quick launch button. which provides pre configured templates with the appropriate application image and resources. For example, they can instantly launch a new Sandbox environment using the template for TensorFlow with a Jupyter Notebook. Within just a few minutes, it'll be automatically configured with GPUs and easy access to their data. Users can launch experiments and make GPUs automatically available for analysis. In this case, the H2O environment was set up with one GPU. With BlueData EPIC, users can also deploy end points with the appropriate run time. And the inference run times can use CPUs or GPUs. With a container based BlueData Platform, you can deploy fully configured distributed environments within a matter of minutes. Whether on-prem, in the public cloud, or in a hybrid a architecture. BlueData was recently acquired by Hewlett Packward Enterprise. And now, HPE and BlueData are joining forces to help you on your AI journey. (light techno music) To learn more, visit www.BlueData.com >> And we're back. I'm Peter Burris and we're continuing to have this conversation about how businesses are turning experience with the problems of advance analytics and the solutions that they seek into actual systems that deliver continuous on going value and achieve the business capabilities required to make possible these advanced outcomes associated with analytics, AI and ML. And to do that, we've got two great guests with us. We've got Kumar Sreekanti, who is the co-founder and CEO of BlueData. Kumar, welcome back to theCUBE. >> Thank you, it is nice to be here, back again. >> And Kumar, you're being joined by a customer. Ramesh Thyagarajan, is the executive director of the Advisory Board Company which is part of Optum now. Ramesh, welcome to theCUBE. >> Great to be here. >> Alright, so Kumar let's start with you. I mentioned up front, this notion of turning technology and understanding into actual business capabilities to deliver outcomes. What has been BlueData's journey along, to make that happen? >> Yeah, it all started six years ago, Peter. It was a bold vision and a big idea and no pun intended on big data which was an emerging market then. And as everybody knows, the data was enormous and there was a lot of innovation around the periphery. but nobody was paying attention to how to make the big data consumable in enterprise. And I saw an enormous opportunity to make this data more consumable in the enterprise and to give a cloud-like experience with the agility and elasticity. So, our vision was to build a software infrastructure platform like VMware, specially focused on data intensity distributed applications and this platform will allow enterprises to build cloud like experiences both on enterprise as well as on hybrid clouds. So that it pays the journey for their cloud experience. So I was very fortunate to put together a team and I found good partners like Intel. So that actually is the genesis for the BlueData. So, if you look back into the last six years, big data itself has went through a lot of evolution and so the marketplace and the enterprises have gone from offline analytics to AI, ML based work loads that are actually giving them predictive and descriptive analytics. What BlueData has done is by making the infrastructure invisible, by making the tool set completely available as the tool set itself is evolving and in the process, we actually created so many game changing software technologies. For example, we are the first end-to-end content-arised enterprise solution that gives you distributed applications. And we built a technology called DataTap, that provides computed data operation so that you don't have to actually copy the data, which is a boom for enterprises. We also actually built multitenancy so those enterprises can run multiple work loads on the same data and Ramesh will tell you in a second here, in the healthcare enterprise, the multitenancy is such a very important element. And finally, we also actually contributed to many open source technologies including, we have a project called KubeDirector which is actually is our own Kubernetes and how to run stateful workloads on Kubernetes. which we have actually very happy to see that people like, customers like Ramesh are using the BlueData. >> Sounds like quite a journey and obviously you've intercepted companies like the advisory board company. So Ramesh, a lot of enterprises have mastered or you know, gotten, understood how to create data lakes with a dupe but then found that they still weren't able to connect to some of the outcomes that they saw. Is that the experience that you had. >> Right, to be precise, that is one of the kind of problems we have. It's not just the data lake that we need to be able to do the workflows or other things, but we also, being a traditional company, being in the business for a long time, we have a lot of data assets that are not part of this data lake. We're finding it hard to, how do we get the data, getting them and putting them in a data lake is a duplication of work. We were looking for some kind of solutions that will help us to gather the benefits of leaving the data alone but still be able to get into it. >> This is where (mumbles). >> This is where we were looking for things and then I was lucky and fortunate to run into Kumar and his crew in one of the Hadoop conferences and then they demonstrated the way it can be done so immediately hit upon, it's a big hit with us and then we went back and then did a POC, very quickly adapt to the technology and that is also one of the benefits of corrupting this technology is the level of contrary memorization they are doing, it is helping me to address many needs. My data analyst, the data engineers and the data scientists so I'm able to serve all of them which otherwise wouldn't be possible for me with just this plain very (mumbles). >> So it sounds as though the partnership with BlueData has allowed you to focus on activities and problems and challenges above the technology so that you can actually start bringing data science, business objectives and infrastructure people together. Have I got that right? >> Absolutely. So BlueData is helping me to tie them all together and provide an excess value to my business. We being in the healthcare, the importance is we need to be able to look at the large data sets for a period of time in order to figure out how a patient's health journey is happening. That is very important so that we can figure out the ways and means in which we can lower the cost of health care and also provide insights to the physician, they can help get people better at health. >> So we're getting great outcomes today especially around, as you said that patient journey where all the constituents can get access to those insights without necessarily having to learn a whole bunch of new infrastructure stuff but presumably you need more. We're talking about a new world that you mentioned before upfront, talking about a new world, AI, ML, a lot of changes. A lot of our enterprise customers are telling us it's especially important that they find companies that not only deliver something today but demonstrate a commitment to sustain that value delivery process especially as the whole analytics world evolves. Are you experiencing that as well? >> Yes, we are experiencing and one of the great advantage of the platform, BlueData platform that gave me this ability to, I had the new functionality, be it the TensorFlow, be it the H2O, be it the heart studio, anything that I needed, I call them, they give me the images that are plug-and-play, just put them and all the prompting is practically transparent to nobody need to know how it is achieved. Now, in order to get to the next level of the predictive and prescriptive analytics, it is not just you having the data, you need to be able to have your curated data asset set process on top of a platform that will help you to get the data scientists to make you. One of the biggest challenges that are scientist is not able to get their hands on data. BlueData platform gives me the ability to do it and ensure all the security meets and all the compliances with the various other regulated compliances we need to make. >> Kamar, congratulations. >> Thank you. >> Sounds like you have a happy customer. >> Thank you. >> One of the challenges that every entrepreneur faces is how did you scale the business. So talk to us about where you are in the decisions that you made recently to achieve that. >> As an entrepreneur, when you start a company, odds are against you, right? You're always worried about it, right. You make so many sacrifices, yourself and your team and all that but the the customer is the king. The most important thing for us to find satisfied customers like Rameshan so we were very happy and BlueData was very successful in finding that customer because i think as you pointed out, as Ramesh pointed out, we provide that clean solution for the customer but as you go through this journey as a co-founder and CEO, you always worry about how do you scale to the next level. So we had partnerships with many companies including HPE and we found when this opportunity came in front of me with myself and my board, we saw this opportunity of combining the forces of BlueData satisfied customers and innovative technology and the team with the HPs brand name, their world-class service, their investment in R&D and they have a very long, large list of enterprise customers. We think putting these two things together provides that next journey in the BlueData's innovation and BlueData's customers. >> Excellent, so once again Kumar Sreekanti, co-founder and CEO of BlueData and Ramesh Thyagarajan who is the executive director of the advisory board company and part of Optum, I want to thank both of you for being on theCUBE. >> Thank you >> Thank you, great to be here. >> Now let's hear a little bit more about how this notion of bringing BlueData and HPE together is generating new classes of value that are making things happen today but are also gonna make things happen for customers in the future and to do that we've got Dave Velante who's with Silicon Angle Wiki Bond joined by Patrick Osbourne who's with HPE in our Marlborough studio so Dave over to you. >> Thanks Peter. We're here with Patrick Osbourne, the vice president and general manager of big data and analytics at Hewlett Packard Enterprise. Patrick, thanks for coming on. >> Thanks for having us. >> So we heard from Kumar, let's hear from you. Why did HPE purchase, acquire BlueData? >> So if you think about it from three angles. Platform, people and customers, right. Great platform, built for scale addressing a number of these new workloads and big data analytics and certainly AI, the people that they have are amazing, right, great engineering team, awesome customer success team, team of data scientists, right. So you know, all the folks that have some really, really great knowledge in this space so they're gonna be a great addition to HPE and also on the customer side, great logos, major fortune five customers in the financial services vertical, healthcare, pharma, manufacturing so a huge opportunity for us to scale that within HP context. >> Okay, so talk about how it fits into your strategy, specifically what are you gonna do with it? What are the priorities, can you share some roadmap? >> Yeah, so you take a look at HPE strategy. We talk about hybrid cloud and specifically edge to core to cloud and the common theme that runs through that is data, data-driven enterprises. So for us we see BlueData, Epic platform as a way to you know, help our customers quickly deploy these new mode to applications that are fueling their digital transformation. So we have some great plans. We're gonna certainly invest in all the functions, right. So we're gonna do a force multiplier on not only on product engineering and product delivery but also go to market and customer success. We're gonna come out in our business day one with some really good reference architectures, with some of our partners like Cloud Era, H2O, we've got some very scalable building block architectures to marry up the BlueData platform with our Apollo systems for those of you have seen that in the market, we've got our Elastic platform for analytics for customers who run these workloads, now you'd be able to virtualize those in containers and we'll have you know, we're gonna be building out a big services practice in this area. So a lot of customers often talk to us about, we don't have the people to do this, right. So we're gonna bring those people to you as HPE through Point Next, advisory services, implementation, ongoing help with customers. So it's going to be a really fantastic start. >> Apollo, as you mentioned Apollo. I think of Apollo sometimes as HPC high performance computing and we've had a lot of discussion about how that's sort of seeping in to mainstream, is that what you're seeing? >> Yeah absolutely, I mean we know that a lot of our customers have traditional workloads, you know, they're on the path to almost completely virtualizing those, right, but where a lot of the innovation is going on right now is in this mode two world, right. So your big data and analytics pipeline is getting longer, you're introducing new experiences on top of your product and that's fueling you know, essentially commercial HPC and now that folks are using techniques like AI and modeling inference to make those services more scalable, more automated, we're starting to bringing these more of these platforms, these scalable architectures like Apollo. >> So it sounds like your roadmap has a lot of integration plans across the HPE portfolio. We certainly saw that with Nimble, but BlueData was working with a lot of different companies, its software, is the plan to remain open or is this an HPE thing? >> Yeah, we absolutely want to be open. So we know that we have lots of customers that choose, so the HP is all about hybrid cloud, right and that has a couple different implications. We want to talk about your choice of on-prem versus off-prem so BlueData has a great capability to run some of these workloads. It essentially allows you to do separation of compute and storage, right in the world of AI and analytics we can run it off-prem as well in the public cloud but then we also have choice for customers, you know, any customer's private cloud. So that means they want to run on other infrastructure besides HPE, we're gonna support that, we have existing customers that do that. We're also gonna provide infrastructure that marries the software and the hardware together with frameworks like Info Site that we feel will be a you know, much better experience for the customers but we'll absolutely be open and absolutely have choice. >> All right, what about the business impact to take the customer perspective, what can they expect? >> So I think from a customer perspective, we're really just looking to accelerate deployment of AI in the enterprise, right and that has a lot of implications for us. We're gonna have very scalable infrastructure for them, we're gonna be really focused on this very dynamic AI and ML application ecosystems through partnerships and support within the BlueData platform. We want to provide a SAS experience, right. So whether that's GPUs or accelerators as a service, analytics as a service, we really want to fuel innovation as a service. We want to empower those data scientists there, those are they're really hard to find you know, they're really hard to retain within your organization so we want to unlock all that capability and really just we want to focus on innovation of the customers. >> Yeah, and they spend a lot of time wrangling data so you're really going to simplify that with the cloud (mumbles). Patrick thank you, I appreciate it. >> Thank you very much. >> Alright Peter, back to you in Palo Alto. >> And welcome back, I'm Peter Burris and we've been talking a lot in the industry about how new tooling, new processes can achieve new classes of analytics, AI and ML outcomes within a business but if you don't get the people side of that right, you're not going to achieve the full range of benefits that you might get out of your investments. Now to talk a little bit about how important the data science practitioner is in this equation, we've got two great guests with us. Nanda Vijaydev is the chief data scientists of BlueData. Welcome to theCUBE. >> Thank you Peter, happy to be here. >> Ingrid Burton is the CMO and business leader at H2O.AI, Ingrid, welcome to the CUBE. >> Thank you so much for having us. >> So Nanda Vijaydev, let's start with you. Again, having a nice platform, very, very important but how does that turn into making the data science practitioner's life easier so they can deliver more business value. >> Yeah thank you, it's a great question. I think end of the day for a data scientist, what's most important is, did you understand the question that somebody asked you and what is expected of you when you deliver something and then you go about finding, what do I need for them, I need data, I need systems and you know, I need to work with people, the experts in the process to make sure that the hypothesis I'm doing is structured in a nice way where it is testable, it's modular and I have you know, a way for them to go back to show my results and keep doing this in an iterative manner. That's the biggest thing because the satisfaction for a data scientist is when you actually take this and make use of it, put it in production, right. To make this whole thing easier, we definitely need some way of bringing it all together. That's really where, especially compared to the traditional data science where everything was monolithic, it was one system, there was a very set way of doing things but now it is not so you know, with the growing types of data, with the growing types of computation algorithms that's available, there's a lot of opportunity and at the same time there is a lot of uncertainty. So it's really about putting that structure and it's really making sure you get the best of everything and still deliver the results, that is the focus that all data scientists strive for. >> And especially you wanted, the data scientists wants to operate in the world of uncertainty related to the business question and reducing uncertainty and not deal with the underlying some uncertainty associated with the infrastructure. >> Absolutely, absolutely you know, as a data scientist a lot of time used to spend in the past about where is the data, then the question was, what data do you want and give it to you because the data always came in a nice structured, row-column format, it had already lost a lot of context of what we had to look for. So it is really not about you know, getting the you know, it's really not about going back to systems that are pre-built or pre-processed, it's getting access to that real, raw data. It's getting access to the information as it came so you can actually make the best judgment of how to go forward with it. >> So you describe the world with business, technology and data science practitioners are working together but let's face it, there's an enormous amount of change in the industry and quite frankly, a deficit of expertise and I think that requires new types of partnerships, new types of collaboration, a real (mumbles) approach and Ingrid, I want to talk about what H2O.AI is doing as a partner of BlueData, HPE to ensure that you're complementing these skills in pursuit or in service to the customer's objectives. >> Absolutely, thank you for that. So as Nanda described, you know, data scientists want to get to answers and what we do at H2O.AI is we provide the algorithms, the platforms for data scientist to be successful. So when they want to try and solve a problem, they need to work with their business leaders, they need to work with IT and they actually don't want to do all the heavy lifting, they want to solve that problem. So what we do is we do automatic machine learning platforms, we do that with optimizing algorithms and doing all the kind of, a lot of the heavy lifting that novice data scientists need and help expert data scientists as well. I talk about it as algorithms to answers and actually solving business problems with predictions and that's what machine learning is really all about but really what we're seeing in the industry right now and BlueData is a great example of kind of taking away some of the hard stuff away from a data scientist and making them successful. So working with BlueData and HPE, making us together really solve the problems that businesses are looking for, it's really transformative and we've been through like the digital transformation journey, all of us have been through that. We are now what I would term an AI transformation of sorts and businesses are going to the next step. They had their data, they got their data, infrastructure is kind of seamlessly working together, the clusters and containerization that's very important. Now what we're trying to do is get to the answers and using automatic machine learning platforms is probably the best way forward. >> That's still hard stuff but we're trying to get rid of data science practitioners, focusing on hard stuff that doesn't directly deliver value. >> It doesn't deliver anything for them, right. They shouldn't have to worry about the infrastructure, they should worry about getting the answers to the business problems they've been asked to solve. >> So let's talk a little bit about some of the new business problems that are going to be able to be solved by these kinds of partnerships between BlueData and H2O.AI. Start, Nanda, what do you, what gets you excited when we think about the new types of business problems that customers are gonna be able to solve. >> Yeah, I think it is really you know, the question that comes to you is not filtered through someone else's lens, right. Someone is trying an optimization problem, someone is trying to do a new product discovery so all this is based on a combination of both data-driven and evidence-based, right. For us as a data scientist, what excites me is that I have the flexibility now that I can choose the best of the breed technologies. I should not be restricted to what is given to me by an IT organization or something like that but at the same time, in an organization, for things to work, there has to be some level of control. So it is really having this type of environments or having some platforms where some, there is a team that can work on the control aspect but as a data scientist, I don't have to worry about it. I have my flexibility of tools of choice that I can use. At the same time, when you talk about data, security is a big deal in companies and a lot of times data scientists don't get access to data because of the layers and layers of security that they have to go through, right. So the excitement of the opportunity for me is if someone else takes care of the problem you know, just tell me where is the source of data that I can go to, don't filter the data for me you know, don't already structure the data for me but just tell me it's an approved source, right then it gives me more flexibility to actually go and take that information and build. So the having those controls taken care of well before I get into the picture as a data scientist, it makes it extremely easy for us to focus on you know, to her point, focus on the problem, right, focus on accessing the best of the breed technology and you know, give back and have that interaction with the business users on an ongoing basis. >> So especially focus on, so speed to value so that you're not messing around with a bunch of underlying infrastructure, governance remaining in place so that you know what are the appropriate limits of using the data with security that is embedded within that entire model without removing fidelity out of the quality of data. >> Absolutely. >> Would you agree with those? >> I totally agree with all the points that she brought up and we have joint customers in the market today, they're solving very complex problems. We have customers in financial services, joint customers there. We have customers in healthcare that are really trying to solve today's business problems and these are everything from, how do I give new credit to somebody? How do I know what next product to give them? How do I know what customer recommendations can I make next? Why did that customer churn? How do I reach new people? How do I do drug discovery? How do I give a patient a better prescription? How do I pinpoint disease than when I couldn't have seen it before? Now we have all that data that's available and it's very rich and data is a team sport. It takes data scientists, it takes business leaders and it takes IT to make it all work together and together the two companies are really working to solve problems that our customers are facing, working with our customers because they have the intellectual knowledge of what their problems are. We are providing the tools to help them solve those problems. >> Fantastic conversation about what is necessary to ensure that the data science practitioner remains at the center and is the ultimate test of whether or not these systems and these capabilities are working for business. Nanda Vijaydev, chief data scientist of BlueData, Ingrid Burton CMO and business leader, H2O.AI, thank you very much for being on theCUBE. >> Thank you. >> Thank you so much. >> So let's now spend some time talking about how ultimately, all of this comes together and what you're going to do as you participate in the crowd chat. To do that let me throw it back to Dave Velante in our Marlborough studios. >> We're back with Patrick Osbourne, alright Patrick, let's wrap up here and summarize. We heard how you're gonna help data science teams, right. >> Yup, speed, agility, time to value. >> Alright and I know a bunch of folks at BlueData, the engineering team is very, very strong so you picked up a good asset there. >> Yeah, it means amazing technology, the founders have a long lineage of software development and adoption in the market so we're just gonna, we're gonna invested them and let them loose. >> And then we heard they're sort of better together story from you, you got a roadmap, you're making some investments here, as I heard. >> Yeah, I mean so if we're really focused on hybrid cloud and we want to have all these as a services experience, whether it's through Green Lake or providing innovation, AI, GPUs as a service is something that we're gonna be you know, continuing to provide our customers as we move along. >> Okay and then we heard the data science angle and the data science community and the partner angle, that's exciting. >> Yeah, I mean, I think it's two approaches as well too. We have data scientists, right. So we're gonna bring that capability to bear whether it's through the product experience or through a professional services organization and then number two, you know, this is a very dynamic ecosystem from an application standpoint. There's commercial applications, there's certainly open source and we're gonna bring a fully vetted, full stack experience for our customers that they can feel confident in this you know, it's a very dynamic space. >> Excellent, well thank you very much. >> Thank you. Alright, now it's your turn. Go into the crowd chat and start talking. Ask questions, we're gonna have polls, we've got experts in there so let's crouch chat.