[Music] we're here with steve melanie the president and ceo of aviatrix steve john and i started this whole super cloud narrative as a way to describe that something different is happening specifically within the aws ecosystem but more broadly across the cloud landscape at re invent last year you and i spoke on the cube and you said one of your investors guy named nick sterile said to you at the show it's happening steve welcome to the cube what's happening what did nick mean by that yeah we were we were just getting ready to go on and i leaned over and he looked at me and he whispered in my ear and said it's happening he said it just like that and and you're right it was it was kind of funny and we talked about that and what he means is enterprises you know this is why i went to aviatrix three and a half years ago is the the the flip switch for enterprises and they said now we mean it we've been talking about cloud for 12 years or 15 years now we mean it we are digitally transforming we are the movement to cloud is going to make that happen and oh by the way of course it's multi-cloud because enterprises put workloads where they run best where they have the best security the best performance the best cost and the business is driving this transformation and they decide that i'm going to use that azure and another business unit decides i'm using google and another one says i'm using aws and so of course it's going to be multi-cloud and i think we're going to start seeing actual multi-cloud applications once that infrastructure and you know you call it the super cloud once that starts getting built developers are going to go wait a minute so i can pick this feature from google and and that service from azure and that service from aws easily without any hesitation once that happens they're going to start really developing today there aren't multi-cloud applications but but but the what's happening is the enterprise embracing public cloud they're using multiple clouds many of them call it four plus one right they're four different public clouds plus what they have on prem that to me is what's happening i am now re-architecting my enterprise infrastructure from applications all the way down to the network and i am embracing uh uh public clouds in that in that process so i mean you nailed us so many things in there i mean digitally transforming to me this is the digital transformation it's leveraging embracing the capex from the hyperscalers now you know people in the industry we're not trying to do what gartner does and create a new category per se but we do use super cloud as a metaphor so i don't expect necessarily vendors to use it or not but but i and i get that but when you talk about multi-cloud what specifically is new in other words what you touched on some of this stuff what constitutes a modern multi-cloud or what we would call a super cloud you know network architecture what are the salient attributes yeah i would say today so two years ago there was no such thing even as multiple clouds it was aws let's be clear everything was aws and for people to even back then two three years ago to even envision that there would be anything else other than aws people couldn't even envision now people kind of go yeah that was done we now see that we're going to use multiple clouds we're going to use azure we're going to use gcp and we're going to use this and we'll guess we're going to use oracle and even ollie cloud we're going to use five or four or five different public clouds what's but that would be i think of as multiple clouds but from an i.t perspective they need to be able to support all those clouds in these shared services and what they're going to do i actually think we're starting and you may have hit on something in the super cloud or i know you've talked about metacloud that that's got bad connotations for facebook i know everybody's like no please not another meta thing but there is that concept of this abstracted layer above you know writing we call it you know altitude you know aviatrix everything's you know riding above the clouds right that that that common abstracted layer this application infrastructure that runs the application that rides above all the different public clouds and i think once we do that you know dave what's going to happen is i think really what's going to happen is you're going to start seeing these these multi-cloud applications which to my knowledge really doesn't exist today i i think that might be the next phase and in order for that to happen you have to have all of the infrastructure be multi-cloud meaning not just networking and network security from from from aviation but you need snowflake you need hashtag you need datadog you need all the new horsemen of the new multi-cloud which isn't the old guys right this is all new people aviatrix dashie snowflake datadonk you name it that are going to be able to deliver all this multi-cloud cross-cloud wherever you want to talk about it such that application development and deployment can happen seamlessly and frictionlessly across multi-cloud once that happens the entire stack then you're going to start seeing and that to me starts enabling this what you guys call you know the super cloud the meta cloud the whatever cloud but that then rides above all the individual clouds that that's going to start getting a whole new realm of application development in my mind so we've got some work to do to basic do some basic blocking and tackling then the application developers can really build on top of that so so some of the skeptics on on this topic would ask how do you envision this changing networking versus it just being a bolt-on to existing fossilized network infrastructure in other words yeah how do we get from point a where we are today to point b you know so-called networking so we can actually build those uh super cloud applications yeah so you know what it is it's interesting because it goes back to my background at nasira and what we used to talk about then it isn't about managing complexity it's about creating simplicity it's very different and when you put the intelligence into the software right this is what computer science is all about we're turning networking into computer science when you create an abstraction layer we are not just an overlay day we dave we actually integrate in with the native services of the cloud we are not managing the complexity of these multi-clouds we are using it you know controlling the native constructs adding our own intelligence to this and then creating what is basically simplification for the people above it so we're simplifying things not just managing the complexity that's how you get the agility for cloud that's how you get to be able to do this because if all you are is a veneer on top of complexity you're just hiding complexity you're not creating simplicity and what happens is it actually probably gets more complex because if all you're doing is hiding the bad stuff you're not getting rid of it i love that i love that we're doing that at the networking and network security layer you're going to see snowflake and datadog and other people do it at their layers you know i reminds of a conversation i had with cause the one of the founders of pure storage who they're all about simplicity this idea of of creating simplicity versus like you said just creating you know a way to handle the complexity compare you know pure storage with the sort of old legacy emc storage devices and that's what you had you had you you had emc managing the complexity at pure storage disrupting by creating simplicity so what are the challenges of creating that simplicity and delivering that seamless experience that continuous experience across cloud is it engineering is it mindset is it culture is it technology what is it well i mean look at look you see the recession that we're we're hitting you see there is a significant problem that we have in the general it industry right now and it's called skills gap skills shortage it's two problems we don't have enough people and we don't have enough people that know cloud and the reason is everybody on the same tuesday three and a half years ago all said now i mean i'm moving the cloud we're a technology company we don't make sneakers anymore we don't make beer we're a technology company and we're going to digitally transform and we're going to move the cloud guess what three years ago there were probably seven people that understood cloud now everyone on the same tuesday morning all decides to try to hire those same seven people there's just not enough people around so you're going to need software and you're going to have to put the intelligence into the software because you're not going to be able to a hire those people and b even if you hire them you can't keep them as soon as they learn cloud guess what happens dave they're off they're on to the next job at the next highest bidder so how are you going to handle that you have to have software that intelligent software that is going to simplify things for you we have people managing massive multi-cloud network and network security people with two people on-prem they got hundreds right you it's not about taking that complex model that it had on-prem and jam it into the cloud you don't have the people to do it and you're not going to get the people to do it you know i want to ask you yeah so i want to ask you about the go to market challenges because we our industry gets a bad rap for for selling we're really good at selling and then but but actually delivering what we sell sometimes we fall down there so so i love tom sweet as cfo of of dell he talks about the the say do ratio uh how that's actually got to be low but you know but you know what i mean uh the math the fraction guy right so but do do what you say you're going to do are there specific go to market challenges related to this type of cross cloud selling where you can set you have to set the customer's expectations because what you're describing is not going to happen overnight it's a journey but how do you handle that go to market challenge in terms of setting those customer expectations and actually delivering what you say you can sell and selling enough to actually have a successful business um so i think everything's outside in so so i think the the what really is exciting to me about this cloud computing model that with the transformation that we're going through is it is business-led and it is led by the ceo and it is led by the business units they run the business it is all about agility is about enabling my developers and it's all about driving the business market share revenue all these kind of things you know the last transformation of mainframe to on to pc client server was led by technologists it wasn't led by the business and it was it was really hard to tie that to the business so then so this is great because we can look at the initiatives you can look at the the the initiatives of the ceo in your company and now as an i.t person you can tie to that and they're going to have two or three or four initiatives and you can actually map it to that so that's where we start is let's look at what the c your ceo cares about he cares about this he cares about that he cares about driving revenue he cares about agility of getting new applications out to the market sooner to get more revenue there's this and oh by the way transfer made transforming your infrastructure to the cloud is the number one thing so it's all about agility so guess what you need to be able to respond to that immediately because tomorrow the business is going to go to you and say great news dave we're moving to gcp wait what no one told me about that well we're telling you now and uh you need to be ready tomorrow and if you're sitting there and you're tied to the low-level constructs and all you know is aws well i don't have those people and even if i have even if i could hire them i'm not allowed to because i can't hire anybody how am i going to respond to the business and the needs of the business now all of a sudden i'm in the way as the infrastructure team of the ceo's goals because we decided we need to we need to get the ai capabilities of gcp and we're moving to gcp or i just did a big deal with gcp and uh miraculously they said i need to run on gcp right i did a big deal with google right guess what comes along with that oh you're moving to gcp great the business says we're moving to gcp and the i.t guys are sitting there going well no one told me well sorry so it's all about agility it's all about that and the and and complexity is the killer to agility this is all about business they're going to come to you and say we just acquired a company we need to integrate them oh but they got they use the same ip address range as we do there's overlapping ips and oh by the way they're in a different cloud how do i do that no one cares the business doesn't care they're like me they're very impatient get it done or we'll find someone who will yeah so you've got to get ahead of that and so when we in terms of when we talk to customers that's what we do this isn't just about defenses this is about making you get promoted making you do good for your company such that you can respond to that and maybe even enable the company to go do that like we're going to enable people to do true multi-cloud applications because the infrastructure has to come first right you you put the foundation in your big skyscraper like the crew behind me and the plumbing before you start building the floors right so infrastructure comes first then comes then comes the applications yeah so you know again some people call it super cloud like us multi-cloud 2.0 but the the real mega trend that i see steve and i'd love you to bottom line this and bring us home is you know andreessen's all companies are software companies it's like version 2.0 of that and the applications that are going to be built on that top this tie into the digital transformations it was goldman it's jpmc it's walmart it's capital one b of a oracle's acquisition of cerner is going to be really interesting to see these super clouds form within industries bringing their data their tooling and their specific software expertise built on top of that hyperscale infrastructure and infrastructure for companies like yours so bottom line is stephen steve what's the future of cloud how do you see it the future is n plus one so two years ago people had one plus one i had what i had on prem and then what i had in aws they today if you talk to an enterprise they'll have what they call four plus one right which is four public clouds plus what i have on prem it's going to n plus one right and what's going to happen is exactly what you said you're going to have industry clouds you're going to the the multi-cloud aspect of it is going to end it's not going to go from four to one some people think oh it's not going to be four it's going down to one or two bs it's going to end it's going to a lot as they start extending to the edge and they start integrating out to the to the branch offices it's not going to be about that branch offer so that edge iot or edge computing or data centers or campus connecting into the cloud it's going to be the other way around the cloud is going to extend to those areas and you're going to have ai clouds you know whether it's you know ultra beauty who's a customer of ours who's starting to roll out ar and vr out to their retail stores to show you know makeup and this and the other thing these are new applications transformations are always driven by new applications that don't exist this isn't about lift and shift of the existing applications the 10x tam in this market is going to becomes all the new things that's where the explosion is going to happen and you're going to see end level those those branch offices are going to look like clouds and they're going to need to be stitched together and treated like one infrastructure so it's going to go from four plus one to n plus one and that's what you're gonna want as an enterprise i'm gonna want n clouds so we're gonna see an explosion it's not going to be four it's going to be end now at the end underneath all of that will be leveraging and effectively commoditizing the existing csps yeah and but you're going to have an explosion of people commoditizing them and just like the goldmans and the industry clubs are going to do they're going to build their own eye as well right no way no way it's that's what's going to happen it's going to be a 10x on what we saw last decade with sas it's all going to happen around clouds and supercloud steve malini thanks so much for coming back in the cube and helping us sort of formulate this thinking i mean it really started with with with you and myself and john and nick and really trying to think this through and watching this unfold before our eyes so great to have you back thank you yeah it's fun thanks for having me are you welcome but keep it right there for more action from super cloud 22 be right back [Music] you

>>Okay, welcome back everyone to San Francisco, live coverage here with the cube 80, be summit 2022. We're back in person. I'm John furry host of the cube. We'll be at the 80 us summit in New York city. This summer, check us out then. But right now, two days in San Francisco, getting all the coverage what's going on in the cloud, we got a cube, alumni and friend of the cube. I dos car CEO, investor, a Sierra, and also an investor and a bunch of startups, angel investor. I'm gonna do great to see you. Thanks for coming on the cube. Good to see you. Good to see. See you, sir. Chris pump. Cool. How are you? >>Good. How are you? >>So congratulations on all your investments. Uh, you've made a lot of great successes over the past couple years and your company raising some good cash as Sarah. So give us the update. How much cash have you guys raised? What's the status of the company product what's going on? >>First of all, thank you for having me. We're back to be business with you never while after. Great to see you. Um, so I, as the company started around four years back, I invested with a few of the investors and now I'm the CEO. Um, we have raised close to a hundred million there. The investors are people like nor west Menlo, true ventures, coast, lo ventures, Ram Shera, and all those people all well known guys, Andy Beel chime Paul Mo Mayard web. So a whole bunch of operating people and, uh, Silicon valley vs are involved >>And has it gone? >>It's going well. We are doing really well. We are going almost 300% year over year. Uh, for last three years, the space ISRA is going after is what I call the applying AI for customer service. It operations, it help desk, uh, the same place I used to work at ServiceNow. We are partners with ServiceNow to take, how can we argument for employees and customers, Salesforce, and service now to take it the next stage? Well >>Of having you on the cube, Dave and I, David ante as well loves having you on too, because you not only bring the entrepreneurial CEO experience, you're an investor. You're like a, you're like a guest analyst. <laugh> >>You know who done? You >>Get the comment, this fun to talk to you though, you >>Get the commentary, you you're your finger on the pulse. Um, so I gotta ask you obviously, AI and machine learning, machine learning AI, or you want to phrase isn't every application. Now, AI first, uh, you're seeing a lot of that going on. You're starting to see companies build the modern applications at the top of the stack. So the cloud scale has hit. We're seeing cloud scale. You predicted that we talked about in the cube many times. Now you have that past layer with a lot more services and cloud native becoming a standard layer. Containerizations growing Docker just raised a hundred million on a 2 billion valuation back from the debt after they pivoted from an enterprise services. So open source developers are booming. Um, where's the action. I mean, is there data control, plane emerging, AI needs data. There's a lot of challenges around this. There's a lot of discussions and a lot of companies being funded, observability there's 10 million observability companies. Data is the key. What's your angle on this? What's your take? Yeah, >>No, look, I think I'll give you the view that I see right from my side. Obviously data is very clear. So the things that system of recorded you and me talked about the next layer is called system of intelligence. That's where the AI will play. Like we talk cloud native, it'll be called AI. Native NATO is a new buzzword and using the AI for customer service it operations. We talk about observability. I call it AI ops, applying ops for good old it operations management, cloud management. So you'll see the AOPs applied for whole list of, uh, application from observability doing the CMDB, predicting the events incidents. So I see a lot of work clicking for AIOps and AI service desk. What used to be help desk with ServiceNow BMC <inaudible> you see a new, a layer emerging as a system of intelligence. Uh, the next would be is applying AI with workflow automation. So that's where you'll see a lot of things called customer workflows, employee workflows. So think of what UI path automation, anywhere ServiceNow are doing, that area will be driven with AI workflows. So you'll see AI going off >>Is RPA a company is AI, is RPA a feed of something bigger? Or can someone have a company on RPA UI pass? One will be at their event this summer? Um, is it a product company? I mean, I mean, RPA is almost, should be embedded in everything. It's a feature. >>It is very good point. Very, very good thing. So one is, it's the category for sure. Like it's a category, it's an area where RPA maybe change the name. I call it much more about automation, workflow automation, but RPA and automation is a category. Um, it's a company also, but that automation should be ed in every area. Yeah. Like we call cloud NATO and AI NATO. It'll become automation. NATO. Yeah. And that's your thinking? So >>It's most interesting me. I think about the, what you're talking about. What's coming to my is I'm kinda having flashbacks to the old software model of middleware. Remember at middleware, it was very easy to understand it was middleware. It sat between two things and then the middle and it was software abstraction. Now you have all kinds of workflows abstractions everywhere. So multiple databases, it's not a monolithic thing. Right? Right. So as you break that down, is this the new modern middleware? Because what you're talking about is data workflows, but they might be siloed. Are they integrated? I mean, these are the challenges. This is crazy. What's the, >>So don't put the database became called polyglot databases. Yeah. I call this one polyglot automation. So you need automation as a layer, as a category, but you also need to put automation in every area like you you're talking about. It should be part of service. Now it should be part of ISRA, like every company, every Salesforce. So that's why you see it. MuleSoft and Salesforce buying RPA companies. So you'll see all the SaaS companies, cloud companies having an automation as a core. So it's like how you have a database and compute and sales and networking. You'll also have an automation as a layer <inaudible> inside every stack. >>All right. So I wanna shift gears a little bit and get your perspective on what's going on behind us. You can see, uh, behind us, you got the expo hall, got, um, we're back to vents, but you got, you know, AMD, Clum, Ove, uh, Dynatrace data, dog, innovative all the companies out here that we know. And we interview them all. They're trying to be suppliers to this growing enterprise market. Right. Okay. But now you also got the entrepreneurial equation. Okay. We're gonna have John Sado on from Deibel later today. He's a former NEA guy and we always talk to Jerry, Jen. We know all the, the VCs. What does the startups look like? What does the, to of the, in your mind, cuz you, I know you invest the entrepreneurial founder situation. Cloud's bigger. Mm-hmm <affirmative> global, right? Data's part of it. You mentioned data's code. Yes. Basically. Data's everything. What's it like for a first an entrepreneur right now who's starting a company. What's the white space. What's the attack plan. How do they get in the market? How do they engineer everything? >>Very good. So I'll give it to two things that I'm seeing out there. Remember days of Amazon created the startups 15 years back, everybody built on Amazon now Azure and GCP. The next layer would be is people don't just build on Amazon. They're going build it on top of snowflake. Companies are snowflake becomes the data platform, right? People will build on snowflake. Right? So I, my old boss Blankman trying to build companies on snowflake. So you don't build it just on Amazon. You build it on Amazon and snowflake. Snowflake will become your data store. Snowflake will become your data layer. Right? So I think that's the next level of <inaudible> trying to do that. So if I'm doing observability AI ops, if I'm doing next level of Splunk SIM, I'm gonna build it on snowflake, on Salesforce, on Amazon, on Azure, et cetera. >>It's interesting. You know, Jerry Chan has it put out a thesis a couple months ago called castles in the cloud where your moat is, what you do in the cloud. Not necessarily in the, in the IP. Um, Dave LAN and I had last reinvent, coined the term super cloud. Right's got a lot of traction and a lot of people throwing, throwing mud at us, but we were, our thesis was, is that what Snowflake's doing? What Goldmans Sachs is doing. You're starting to see these clouds on top of clouds. So Amazon's got this huge CapEx advantage. And guys like Charles Fitzgerald out there who we like was kind of shitting on us saying, Hey, you guys terrible, they didn't get him. Like, yeah, I don't think he gets it, but that's a whole, can't wait to debate him publicly on this. He's cool. Um, but snowflake is on Amazon. Yes. Now they say they're on Azure now. Cause they've got a bigger market and they're public, but ultimately without a AWS snowflake doesn't exist and, and they're reimagining the data warehouse with the cloud, right? That's the billion dollar opportunity. >>It is. It is. They both are very tight. So imagine what Frank has done at snowflake and Amazon. So if I'm a startup today, I want to everything on Amazon where possible whatever is, I cannot build, I'll make the pass layer. Remember the middle layer pass will be snowflake so I can build it on snowflake. I can use them for data layer. If I really need do size, I'll build it on force.com Salesforce. Yeah. Right. So I think that's where you'll. >>So basically the, the, if you're an entrepreneur, the, the north star in terms of the, the outcome is be a super cloud. It is, That's the application on another big CapEx ride, the CapEx of AWS or >>Cloud, and that reduce your product development, your go to market and you get use the snowflake marketplace to drive your engagement. >>Yeah. Yeah. How are, how is Amazon and the clouds dealing with these big whales, the snowflakes of the world? I mean, I know they got a great relationship, uh, but snowflake now has to run a company they're public. Yeah. So, I mean, I'll say, I think they had Redshift. Amazon has got Redshift, um, but snowflakes, a big customer and the they're probably paying AWS, I think bills too. So >>John video it's like whole Netflix is, and Amazon prime Netflix runs on Amazon, but Amazon has Amazon prime that co-optation will be there. So Amazon will have Redshift, but Amazon is also partnering with, uh, snowflake to have native snowflake data warehouses, a data layer. So I think depending on the applic use case, you have to use each of the above. I think snowflake is here for a long term. So if I'm building an application, I want to use snowflake then, right. Think from stats. >>Well, I think that it comes back down to entrepreneurial hustle. Do you have a better product? Right. Product value will ultimately determine it as long as the cloud doesn't, You know, foreclose your value. That's right. With some sort of internal hack. But I think, I think the general question that I have is that I, I think it's okay to have a super cloud like that because the rising tide is still happening. Some point, when does the rising tide stop >>And >>The people shopping up their knives, it gets more competitive or is it just an infinite growth cycle? >>I think it's growth. You call it cloud scale. You invented the word cloud scale. So I think, look, cloud will continually agree, increase. I think there's, as long as there are more movement from on, uh, on-prem to the classical data center, I think there's no reason at this point, the rumor, the old lift and shift that's happening in like my business. I see people lift and shifting from the it operations, it helpless, even the customer service service now and, uh, ticket data from BMCs CAS like Microfocus, all those workloads are shifted to the cloud, right? So ticketing system is happening. Cloud system of record is happening. So I think this train has still a long way to go >>Made. I wanna get your thoughts for the folks watching that are, uh, enterprise buyers or practitioners, not suppliers to the market, feel free to text me or DMing next. Question's really about the buying side, which is if I'm a customer, what's the current, um, appetite for startup products, cuz you know, the big enterprises now and you know, small, medium, large, and large enterprise, they're all buying new companies cuz a startup can go from zero to relevant very quickly. So that means now enterprises are engaging heavily with startups. What's it like what's is there a change in order of magnitude of the relationship between startup selling to, or growing startup selling to an enterprise? Um, have you seen changes there? I mean I'm seeing some stuff, but why don't we get your thoughts on that? What, no, it >>Is. If I remember going back to our 2007 or eight, when I used to talk to you back then and Amazon started very small, right? We an Amazon summit here. So I think enterprises on the average used to spend nothing with startups. It's almost like 0% or one person today. Most companies are already spending 20, 30% with startups. Like if I look at a CIO, a line of business it's gone. Yeah. Can it go more? I think it can double in the next four, five years. Yeah. Spending on the startups. >>Yeah. And check our, uh, AWS startups.com. That's a site that we built for the startup community for buyers and startups. And I want get your reaction because I, I reference the URL cause it's like, there's like a bunch of companies we've been promoting because the solutions that startups have actually are new stuff. Yes. It's bending, it's shifting left for security or using data differently or are um, building tools and platforms for data engineering. Right. Which is a new persona that's emerging. So you know, a lot of good resources there. Um, and goes back now to the data question. Now, getting back to your, what you're working on now is what's your thoughts around this new, um, data engineering persona. You mentioned a AIOps we've been seeing AOPs IOPS blue booming and that's creating a new developer paradigm that's right. Which we call and coin data as code data as code is like infrastructure as code, but it's for data, right? It's developing with data, right? Retraining machine learnings, going back to the data lake, getting data to make, to do analysis, to make the machine learning better post event or post action. So this, this to engineers like an SRE for data, it's a new, scalable role we're seeing. Do you see the same things? Do you agree? Um, do you disagree or can you share >>Yourself? I, no, I have a lot of thoughts that first is I see the AOP solutions in the future should be not looking back. I need to be like we are in San Francisco bay. That means earthquake prediction. Right? I want AOPs to predict when the outages are gonna happen. When there's a performance issue. I don't think most AOPs vendors have not gone through it. Like I spend a lot of time with data dog, Cisco app dynamic, right? Dynatrace, all this solution will go future towards predict to proactive solution with AOPs. But what you bring of a very good point on the data side, I think like we have a Amazon marketplace and for startup, there should be data exchange where you want to create for AOPs and AI service desk customers that give the data, share the data because we thought the data algorithms are useless. I can come the best algorithm, but I gotta train them, modify them, tweak them, make >>Them >>Better, make them better. Yeah. And I think there are a whole data exchange is the industry has not thought through something you and me talk many times. Yeah. Yeah. I think the whole, that data is very important. >>You've always been on, on the Vanguard of data because, uh, it's been really fun. Yeah. >>Going back to big data days back in 2009, you know, >>Look at, look how much data bricks has grown. >>It is double, the >>Key cloud air kinda went private, so good stuff. But what are you working on right now? Give a, give a, um, plug for what you're working on. You'll still invest strength. >>I do still invest, but look, I'm a hundred percent on ISRA right now. I'm the CEO there. Yeah. Okay. >>So >>Right. ISRA is my number one baby right now. So I'm looking at that growing customers and my customers. Some of them you like it's zoom auto desk, MacAfee, uh, grantor. So all the top customers, um, mainly for it help desk customer service ops. Those are three product lines and going after enterprise and commercial deals. >>And when should someone buy your product? What what's their need? What category is it? >>I think the look whenever somebody needs to buy the product is if you need AOP solution to predict, keep your lights on, predict ours one area. If you want to improve employee experience, you are using a slack teams and you want to automate all your workflows. That's another value. Prop. Third is customer service. You don't want to hire more people to do it. Some of the areas where you want to scale your company, grow your company, eliminate the cost customer service. >>Great stuff, man. Great to see you. Thanks for coming on. Congratulations on the success of your company and your investments. Thanks for coming on the key. Okay. I'm John fur here at the cube live in San Francisco for day one of two days of coverage of Aish summit 2022. And we're gonna be at a summit in San, uh, in New York in the summer. So look for that on this calendar, of course, go to Aish startups.com and mention that it's ay for all the hot startups and of course the cube.net and Silicon angle.com. Thanks for watching. We'll be back more coverage after this short break.

>>Hey, welcome back everyone. We're live here in the cube in Las Vegas Raiders reinvent 2021. I'm Jeffrey hosted the key we're in person this year. It's a hybrid event online. Great action. Going on. I'm rolling. Vice-president of ADF analytics. David is great to see you. Thanks for coming on. >>It's great to be here, John. Thanks for having me again. >>Um, so you've got a really awesome job. You've got serverless, you've got analytics. You're in the middle of all the action for AWS. What's the big news. What are you guys announcing? What's going on? >>Yeah, well, it's been an awesome reinvent for us. Uh, we've had a number of several us analytics launches. So red shift, our petabyte scale data warehouse, EMR for open source analytics. Uh, and then we've also had, uh, managed streaming for Kafka go serverless and then on demand for Kinesis. And then a couple of other big ones. We've got RO and cell based security for AWS lake formation. So you can get really fine grain controls over your data lakes and then asset transactions. You can actually have a inserts, updates and deletes on data lakes, which is a big step forward. >>Uh, so Swami on stage and the keynote he's actually finishing up now. But even last night I saw him in the hallway. We were talking about as much as about AI. Of course, he's got the AI title, but AI is the outcome. It's the application of all the data and this and a new architecture. He said on stage just now like, Hey, it's not about the old databases from the nineties, right? There's multiple data stores now available. And there's the unification is the big trend. And he said something interesting. Governance can be an advantage, not an inhibitor. This is kind of this new horizontally scalable, um, kind of idea that enables the vertical specialization around machine learning to be effective. It's not a new architecture, but it's now becoming more popular. People are realizing it. It's sort of share your thoughts on this whole not shift, but the acceleration of horizontally scalable and vertically integrated. Yeah, >>No, I think the way Swami put it is exactly right. What you want is the right tool for the right job. And you want to be able to deliver that to customers. So you're not compromising on performance or functionality of scale, but then you wanted all of these to be interconnected. So they're, well-integrated, you can stay in your favorite interface and take advantage of other technologies. So you can have things like Redshift integrated with Sage makers, you get analytics and machine learning. And then in Swami's absolutely right. Governance is actually an enabler of velocity. Once you've got the right guardrails in place, you can actually set people free because they can innovate. You don't have to be in the way, but you know that your data is protected. It's being used in the way that you expect by the people that you are allowing to use that data. And so it becomes a very powerful way for customers to set data free. And then, because things are elastic and serverless, uh, you can really just match capacity with demand. And so as you see spikes in usage, the system can scale out as those dwindle, they can scale back down, and it just becomes a very efficient way for customers to operate with data at scale >>Every year it reinvented. So it was kind of like a pinch me moment. It's like, well, more that's really good technology. Oh my God, it's getting easier and easier. As the infrastructure as code becomes more programmable, it's becoming easier, more Lambda, more serverless action. Uh, you got new offerings. How are customers benefiting for instance, from the three new offerings that you guys announced here? What specifically is the value proposition that you guys are putting out there? Yeah, so the, >>Um, you know, as we've tried to do with AWS over the years, customers get to focus on the things that really differentiate them and differentiate their businesses. So we take away in Redshift serverless, for example, all of the work that's needed to manage clusters, provision them, scale them, optimize them. Uh, and that's all been automated and made invisible to customers, the customers to think about data, what they want to do with it, what insights they can derive from it. And they know they're getting the most efficient infrastructure possible to make that a reality for them with high performance and low costs. So, uh, better results, more ability to focus on what differentiates their business and lower cost structure over time. >>Yeah. I had the essential guys on it's interesting. They had part of the soul cloud. Continuous is their word for what Adam was saying is clouds everywhere. And they're saying it's faster to match what you want to do with the outcomes, but the capabilities and outcomes kind of merging together where it's easy to say, this is what we want to do. And here's the outcome it supports that's right with that. What are some of the key trends on those outcomes that you see with the data analytics that's most popular right now? And kind of where's that, where's that going? >>Yeah. I mean, I think what we've seen is that data's just becoming more and more critical and top of mind for customers and, uh, you know, the pandemic has also accelerated that we found that customers are really looking to data and analytics and machine learning to find new opportunities. How can they, uh, really expand their business, take advantage of what's happening? And then the other part is how can they find efficiencies? And so, um, really everything that we're trying to do is we're trying to connect it to business outcomes for customers. How can you deepen your relationship with your customers? How can you create new customer experiences and how can you do that more efficiently, uh, with more agility and take advantage of, uh, the ability to be flexible. And you know, what is a very unpredictable world, as we've seen, >>I noticed a lot of purpose-built discussion going on in the keynote with Swami as well. How are you creating this next layer of what I call purpose-built platform like features? I mean, tools are great. You see a lot of tools in the data market tools are tools of your hammer. You want to look for a nail. We see people over by too many tools and you have ultimately a platform, but this seems to be a new trend where there's this connect phenomenon was showing me that you've got these platform capabilities that people can build on top of it, because there's a huge ecosystem of data tools out there that you guys have as partners that want to snap together. So the trend is things are starting to snap together, less primitive, roll your own, which you can do, but there's now more easier ways. Take me through that. Explain that, unpack that that phenomenon role rolling your own firm is, which has been the way now to here. Here's, here's some prefabricated software go. >>Yeah. Um, so it's a great observation and you're absolutely right. I mean, I think there's some customers that want to roll their own and they'll start with instances, they'll install software, they'll write their own code, build their own bespoke systems. And, uh, and we provide what the customers need to do that. But I think increasingly you're starting to see these higher level abstractions that take away all of that detail. And mark has Adam put it and allow customers to compose these. And we think it's important when you do that, uh, to be modular. So customers don't have to have these big bang all or nothing approaches you can pick what's appropriate, uh, but you're never on a dead end. You can always evolve and scale as you need to. And then you want to bring these ideas of unified governance and cohesive interfaces across so that customers find it easy to adopt the next thing. And so you can start off say with batch analytics, you can expand into real time. You can bring in machine learning and predictive capabilities. You can add natural language, and it's a big ecosystem of managed services as well as third parties and partners. >>And what's interesting. I want to get your thoughts while I got you here, because I think this is such an important trend and historic moment in time, Jerry chin, who one of the smartest VCs that we know from Greylock and coin castles in the cloud, which kind of came out of a cube conversation here in the queue years ago, where we saw the movement of that someone's going to build real value on AWS, not just an app. And you see the rise of the snowflakes and Databricks and other companies. And he was pointing out that you can get a very narrow wedge and get a position with these platforms, build on top of them and then build value. And I think that's, uh, the number one question people ask me, it's like, okay, how do I build value on top of these analytic packages? So if I'm a startup or I'm a big company, I also want to leverage these high level abstractions and build on top of it. How do you talk about that? How do you explain that? Because that's what people kind of want to know is like, okay, is it enabling me or do I have to fend for myself later? This is kind of, it comes up a lot. >>That's a great question. And, um, you know, if you saw, uh, Goldman's announcement this week, which is about bringing, building their cloud on top of AWS, it's a great example of using our capabilities in terms of infrastructure and analytics and machine learning to really allow them to take what's value added about Goldman and their position to financial markets, to build something value, add, and create a ton of value for Goldman, uh, by leveraging the things that we offer. And to us, that's an ideal outcome because it's a win-win for us in Goldman, but it's also a win for Goldman and their customers. >>That's what we call the Supercloud that's the opportunity. So is there a lot of Goldmans opportunities out there? Is that just a, these unicorns, are these sites? I mean, how do you, I mean, that's Goldman Sachs, they're huge. Is there, is this open to everybody? >>Absolutely. I mean, that's been one of the, uh, you know, one of the core ideas behind AWS was we wanted to give anybody any developer access to the same technology that the world's largest corporations had. And, uh, that's what you have today. The things that Goldman uses to build that cloud are available to anybody. And you can start for a few pennies scale up, uh, you know, into the petabytes and beyond >>When I was talking to Adams, Lipski when I met with him prior to re-invent, I noticed that he was definitely had an affinity towards the data, obviously he's Amazonia, but he spent time at Tableau. So, so as he's running that company, so you see that kind of mindset of the data advantage. So I have to ask you, because it's something that I've been talking about for a while and I'm waiting for it to emerge, but I'm not sure it's going to happen yet. But what infrastructure is code was for dev ops and then dev sec ops, there's almost like a data ops developing where data as code or programmable data. If I can connect the dots of what Swami's saying, what you're doing is this is like a new horizontal layer of data of freely available data with some government governance built in that's right. So it's, data's being baked into everything. So data is any ingredient, not a query to some database, it's gotta be baked into the apps, that's data as code that's. Right. So it's almost a data DevOps kind of vibe. >>Yeah, no, you're absolutely right. And you know, you've seen it with things like ML ops and so on. It's all the special case of dev ops. But what you're really trying to do is to get programmatic and systematic about how you deal with data. And it's not just data that you have. It's also publicly available data sets and it's customers sharing with each other. So building the ecosystem, our data, and we've got things like our open data program where we've got publicly hosted data sets or things like the AWS data exchange where customers can actually monetize data. So it's not just data as code, but now data as a monetizeable asset. So it's a really exciting time to be in the data business. >>Yeah. And I think it's so many too. So I've got to ask you while I got you here since you're an expert. Um, okay. Here's my problem. I have a lot of data. I'm nervous about it. I want to secure it. So if I try to secure it, I'm not making it available. So I want to feed the machine learning. How do I create an architecture where I can make it freely available, but yet maintain the control and the comfort that this is going to be secure. So what products do I buy? >>Yeah. So, uh, you know, a great place to start at as three. Um, you know, it's one of the best places for data lakes, uh, for all the reasons. That's why we talked about your ability scale costs. You can then use lake formation to really protect and govern that data so you can decide who's allowed to see it and what they're allowed to see, and you don't have to create multiple copies. So you can define that, you know, this group of partners can see a, B and C. This group can see D E and F and the system enforces that. And you have a central point of control where you can monitor what's happening. And if you want to change your mind, you can do that instantly. And all access can be locked down that you've got a variety of encryption capabilities with things like KMS. And so you can really lock down your data, but yet keep it open to the parties that you want and give them specifically the access that you want to give them. And then once you've done that, they're free to use that data, according to the rules that you defined with the analytics tools that we offer to go drive value, create insight, and do something >>That's lake formation. And then you got a Thena querying. Yes, we got all kinds of tooling on top of it. >>It's all right. You can have, uh, Athena query and your data in S3 lake formation, protecting it. And then SageMaker is integrated with Athena. So you can pull that data into SageMaker for machine learning, interrogate that data, using natural language with things like QuickSight Q a like we demoed. So just a ton of power without having to really think too deeply about, uh, developing expert skill sets in this. >>So the next question I want to ask you is because that first part of the great, great, great description, thank you very much. Now, 5g in the edges here, outpost, how was the analytics going on that as edge becomes more pervasive in the architecture? >>Yeah, it's going to be a key part of this ecosystem and it's really a continuum. So, uh, you know, we find customers are collecting data at the edge. They might be making local ML or inference type decisions on edge devices, or, you know, automobiles, for example. Uh, but typically that data with some point will come back into the cloud, into S3 will be used to do heavy duty training, and then those models get pushed back out to the edge. And then some of the things that we've done in Athena, for example, with federated query, as long as you have a network path, and you can understand what the data format or the database is, you can actually run a query on that data. So you can run real-time queries on data, wherever it lives, whether it's on an edge device, on an outpost, in a local zone or in your cloud region and combine all of that together in one place. >>Yeah. And I think having that data copies everywhere is a big thing deal. I've got to ask you now that we're here at reinvent, what's your take we're back in person last year was all virtual. Finally, not 60,000 people, like a couple of years ago, it's still 27,000 people here, all lining up for the sessions, all having a great time. Um, all good. What's the most important story from your, your area that people should pay attention to? What's the headline, what's the top news? What should people pay attention to? >>Yeah, so I think first off it is awesome to be back in person. It's just so fun to see customers and to see, I mean, you, like, we've been meeting here over the years and it's, it's great to so much energy in person. It's been really nice. Uh, you know, I think from an analytics perspective, there's just been a ton of innovation. I think the core idea for us is we want to make it easy for customers to use the right tool for the right job to get insight from all of their data as cost effectively as possible. And I think, uh, you know, I think if customers walk away and think about it as being, it's now easier than ever for me to take advantage of everything that AWS has to offer, uh, to make sense of all the data that I'm generating and use it to drive business value, but I think we'll have done our jobs. Right. >>What's the coolest thing that you're seeing here is that the serverless innovation, is it, um, the new abstraction layer with data high level services in your mind? What's the coolest thing. Got it. >>It's hard to pick the coolest that sticks like kicking the candies. I mean, I think the, uh, you know, the continued innovation in terms of, uh, performance and functionality in each of our services is a big deal. I think serverless is a game changer for customers. Uh, and then I think really the infusion of machine learning throughout all of these systems. So things like Redshift ML, Athena ML, Pixar, Q a just really enabling new experiences for customers, uh, in a way that's easier than it ever has been. And I think that's a, that's a big deal and I'm really excited to see what customers do with it. >>Yeah. And I think the performance thing to me, the coolest thing that I'm seeing is the graviton three and the gravitron progression with the custom stacks with all this ease of use, it's just going to be just a real performance advantage and the costs are getting lowered. So I think the ECE two instances around the compute is phenomenal. No, >>Absolutely. I mean, I think the hardware and Silicon innovation is huge and it's not just performance. It's also the energy efficiency. It's a big deal for the future reality. >>We're at an inflection point where this modern applications are being built. And in my history, I'm old, my birthday is today. I'm in my fifties. So I remember back in the eighties, every major inflection point when there was a shift in how things were developed from mainframe client server, PC inter network, you name it every time the apps change, the app owners, app developers all went to the best platform processing. And so I think, you know, that idea of system software applications being bundled together, um, is a losing formula. I think you got to have that decoupling large-scale was seeing that with cloud. And I think now if I'm an app developer, whether whether I'm in a large ISV in your ecosystem or in the APN partner or a startup, I'm going to go with my software runs the best period and where I can create value. That's right. I get distribution, I create value and it runs fast. I mean, that's, I mean, it's pretty simple. So I think the ecosystem is going to be a big action for the next couple of years. >>Absolutely. Right. And I mean, the ecosystem's huge and I think, um, and we're also grateful to have all these partners here. It's a huge deal for us. And I think it really matters for customers >>What's on your roadmap this year, what you got going on. What can you share a little bit of a trajectory without kind of, uh, breaking the rules of the Amazonian, uh, confidentiality. Um, what's, what's the focus for the year? What do you what's next? >>Well, you know, as you know, we're always talking to customers and, uh, I think we're going to make things better, faster, cheaper, easier to use. And, um, I think you've seen some of the things that we're doing with integration now, you'll see more of that. And, uh, really the goal is how can customers get value as quickly as possible for as low cost as possible? That's how we went to >>Yeah. They're in the longterm. Yeah. We've always say every time we see each other data is at the center of the value proposition. I've been saying that for 10 years now, it's actually the value proposition, powering AI. And you're seeing because of it, the rise of superclouds and then the superclouds are emerging. I think you guys are the under innings of these emerging superclouds. And so it's a huge treading, the Goldman Sachs things of validation. So again, more data, the better, sorry, cool things happening. >>It is just it's everywhere. And the, uh, the diversity of use cases is amazing. I mean, I think from, you know, the Australia swimming team to, uh, to formula one to NASDAQ, it's just incredible to see what our >>Customers do. We see the great route. Good to see you. Thanks for coming on the cube. >>Pleasure to be here as always John. Great to see you. Thank you. Yeah. >>Thanks for, thanks for sharing. All of the data is the key to the success. Data is the value proposition. You've seen the rise of superclouds because of the data advantage. If you can expose it, protect it and govern it, unleashes creativity and opportunities for entrepreneurs and businesses. Of course, you got to have the scale and the price performance. That's what doing this is the cube coverage. You're watching the leader in worldwide tech coverage here in person for any of us reinvent 2021 I'm John ferry. Thanks for watching.

(upbeat music) >> Announcer: Live from Boston, Massachusetts, it's theCUBE, covering your Red Hat Summit 2019. Brought to you by Red Hat. >> And welcome back to Boston, we continue our coverage here in theCUBE of the Red Hat Summit and welcoming now to theCUBE stage for the first time, I believe, David Gledhill. Who is the group chief information officer and head of group technology and operations at DBS Bank. David, good morning to you. >> Morning, hi, it's great to be here. >> All the way from Singapore, and he was early for the segment this morning. So you get extra points for that, congratulations. >> Put that up to jet lag. (men laughing) >> Thanks for being with us. David, anymore we talk about companies in general, everybody says everybody's a tech company now, right? Not the way it used to be. How is that playing out in your world in financial services as far as how deeply ingrained you have to be with the technology? >> Yeah, so very much, we are. Tech transformation started about 10 years ago. Been CIO of the company about 10 years. And frankly, the first five years were just fixing the basics. So getting in place what we'd call world-class systems. Doing a bunch of stuff on resilience and security and all of that kind of stuff. And the other thing, and this is the dramatic change, you know 10 years ago when I joined the company, we were 85% outsourced to managed service vendors. So I had technology people that basically were signing contractors and managing service agreements. We didn't have technology DNA. Over those five years and a full 10 years actually. We've been doing a lot about just insourcing and rebuilding our technical muscle if you like. So now we're, we've gone from 85% outsourced to 90% insourced. So we run, build and manage our own. We're now a technology company. >> And five years ago, we had a real big shift and we were closest to what was going on in China and so probably saw this before many, many of the other banks saw this around the world. Of what Alibaba was doing with Ant Financial and Tencent and this whole, just complete disruption of how customers interact with the banking industry. So we got an early lead on this digital transformation and really for the last five, six years have been doubling down on building a pure digital offering and we see ourselves as a technology company providing banking services, not as a bank with some technology department in the backend. >> Yeah, I'd love if you can, a little bit, to help us dig into that because, I think back it was okay, what does digitization mean 10 years ago, it was like oh, okay, I need to make sure I have a good website and maybe a good mobile app. Which is a fine starting piece, and also the piece you talked about is when it was outsourced, I'm managing pieces but I sign up for what I need today and when the business needs something, those outsources aren't necessarily tied to them, so you're playing telephone with them. Most the companies I've talked to that have brought skills back inside, it's because the needs of the business are constantly asking for more and it can't be well, it's not part of our contract with what we have. We'll get to that in a year or two. >> Yeah, yeah, so that's a very interesting shift. It plays out in a number of different dimensions. First of all, let me go into that question of business and tech and that separation. When we were managed service, it was literally writing contracts and the specs and handing to vendors. It was just a horrible process. And how can you be a modern technology firm like that? So insourcing, for us, was one big thing to owe those people, but when you insource, then you end up with a business unit and a technology unit. And you still have got silos, so how do you break that? Because that really is a problem. If you look at the way technology companies work, they don't work like that. Five years ago when we said, okay, how do you make that flip to being the digital company? We went very deep into how some of the great technology companies operate. We wanted to understand, what is it? How does that DNA work? How does that culture work? How do they organize themselves? How do they build technology? How do they become agile, speed to market? And so we looked at, we studied Google, Amazon, Netflix Apple, LinkedIn, Facebook and we call them the Gandalf companies. And we said, how can we be more like them? Well, a Gandalf is missing a D. And fortunately at DBS, we happen to have a D. (laughing) So our goal became how do we become the D in Gandalf? And that was just like a lightening rod through the organization because all of the sudden it said to our people, forget about biz and tech and things. You need to think about how these technology comp operates and be more like them. Which means there's no separation, there are no silos we are together building great technical products for our customers so we need to re-think the organization to make sure that happens. >> There's magic. (laughing) You've got a saying, making banking joyful. >> Yep. >> All right, which is not exactly the emotion that I associate with having to deal with my bank. It's fine, but joyful? A very unusual adjective there. What's that all about? And again, at the end of the day, how does technology enhance that? How does that compliment that and really boosted that? >> Yeah, so it was quite a radical moment for us. That came up, we were at a leadership meeting and talking about what is our purpose and how do we. Lots of people talk about customer journey, thinking and stuff like that but how do you bring that to life and one of the execs there said, well what about making banking joyful? And the rest of us just looked at him like he was from a different planet. Saying, are you kidding, what do you mean by that? But as we thought about it more, it has a great meaning and a great purpose to it, that we're not there just to do transactions but we're there to enrich lives, create new businesses, to make customers feel great in their financial stability, in the way they deal with us. And it applies on so many levels. So if you're a bank teller, you understand how to make banking joyful by just that, going the extra mile, in terms of service. If you're in infrastructure, and you're dealing with data centers and servers, you understand that making banking joyful, you must be there all the time. You must have sub-second responses, you must feel great in the customers hands, so it's something that you can apply to all aspects of banking and everybody plays a part in making banking joyful for our customers. >> All right, so David, bring us inside a little bit your organization, you said transforming to a technology company. What's that mean, what technology are you using? We're here at the Red Hat Show. Open-source, not the first thing that people think about when they they think about banking. So how does that fit into the culture that you're building? >> Yeah, yeah, okay, so, this Gandalf thing that I talked about, that's great as a logo and a mindset shift, but it doesn't get you very far. And so what we came up with is five key elements that have to change. And we had to work on to become more like a technology company. And one was a shift from projects to running technology like a series of platforms. That enables you to do agile at scale, but for that you need to organize very differently, which is the third thing. And then the fourth thing is that you need to build for modern systems. The legacy way of building technology just wasn't going to get us to where we needed to be as a technology company. And then the last bit is alternate everything. So, if you want speed to market and agility, you have to alternate. That modern technology stat, it was very obvious to us that the legacy, corporate technologies that we used to build systems, were just not going to win it for us. And so that's our move to open-source. Red Hat was a fabulous partner in that and we used Red Hat extensively throughout our entire infrastructure. And so we went through this rapid modernization of moving to open-source, moving to open-source database we used Merare DD quite extensively, but also, picking up pieces of the open-source from the Gandalf companies. We've seen the way they use open-source to scale. Plus also, to provide just amazing services. So for example, Netflix. We run a bunch of banking platforms on Netflix, believe it or not. It's kind of cool, banking on Netflix is a kinda crazy concept, but we brought that do life. What is is that Netflix we loved? We loved their engineering discipline around chaos engineering and the use of chaos to really build resilient platforms. So in our whole test and deployment framework, we have a lot of Netflix chaos elements built into that to make sure that when we actually are testing, we're testing for chaos and random failures which we inject into those platforms. We don't do it in production like Netflix do quite yet. This whole concept of site reliability and chaos and excellence of service is again something we learned from the Gandalf companies. So Gandalf was not just a, oh yeah, let's pester in the heart of the business article. It was really, let's use their engineering disciplines and design principles to build our own systems. Our network, Facebook, which is, you think of it as a network company. We think of network and the infrastructure layer. And our infrastructure and our networking is designed on a bunch of concepts that Facebook have about how they build their network within their data centers. >> Can you help connect the dots, you talk about a phenomenal technologies, chaos engineering, networking like these global companies. How does that lead to the outcome that you talked about? You know, joy to your end users? >> So if you want to make banking joyful, you have to be super-reliable. You have to be on the edge of the innovation curve all the time. Which means you need to be test and learn, which means you'll be very agile. You need to be able to scale very well and the open-source technologies enable us to scale superbly. You need to be able to to perform as well, superbly well. When I joined the company, our measure of how well our applications were performing is are they up or down? And then we advanced that to, well, are they up and maybe 80% of the time they responded within four seconds. Those are terrible measures because they're not joyful. That means 20% of the time we're awful. That doesn't bring joy to a customer. So what brings joy is we've now scrapped all those things and we're starting to look at performance, for example at the 99th percentile, so anything below that is just noise and the signal is what is our worst performing 99%, because if you wanna be joyful every single time that a customer opens your application you wanna be there and respond well, et cetera, et cetera. Same thing goes for customer science. Where do you get customer drop offs and how do you fix problems? So customer science and the engineering disciplines around observing and instrumenting a platform all the time become very , very important. So it goes very, very deep. You know it's a simple concept. But totally changes the way we engineer. >> Your line of work, or your industry obviously is very security oriented, right? >> Yeah. >> I think of healthcare being another with health information what have you. But certainly financial services, so in the open-source community, how do you address this, I would say it's not a clash by any means, but it's a concern, I would think, still that you have to be micro-observant of security practices and yet this is an open-community and exchange of ideas and could be an exchange of vulnerabilities or problems, too. >> So, sure, and we absolutely do. There are certain things that we, certain places that we won't go, or we will go but only for experimentation reasons because of that question. But you know arguably, we think that open-source company can more secure over time than non-open source, because you're also getting a bunch of people fixing it the whole time. And we've seen some of the issues with some of the open-source and the heart bleed and those other bits and pieces. But they were shut down pretty quickly and found pretty quickly. So we move with caution, we're very cognoscente. We move with our eyes open and it's really the zero day vulnerabilities that we are exposed to. But equally, if you're in a proprietary state. The whole thing that came up with the X86 platform in terms of the vulnerabilities there that apply open-source or not. So yeah, security issues exist everywhere. >> Right, all right, so, David, bring us in. You talked about some of the open-sourced technologies. Where does Red Hat fit into this? What's it like, how have they advanced that journey that DBS has been on? >> So for the heavy lifting, for the big applications that we want to run, and the majority of our workload going with open-source is fine, but you want to have open-source that also you think isn't going to break or have big security vulnerabilities to your question. And that's really where a partner like Red Hat comes in because it gives us access to all the wonderful benefits of open-source with a trusted partner that's putting industrial strength quality releases out that we can really rely on and bank on. So, in awhile we used open-source, at the periphery and true open-source that we just plug it off the internet. The really very, very high demanding workloads and very secure workloads we will always work with a partner that can wrap that into an enterprise-quality offering for us. So Red Hat has gone from zero to running way over 50%, 60% of our workload. And we'll continue to put it even more on that because it's a platform we can trust. >> That's great, so, when you look at your journey overall, how far are you along that journey? Anything when you look out, what are some of the things that are exciting you looking forward? >> So while we believe we're ahead of most banks. There are some that are in the mix, Goldmans are pretty far advance, Duetsche, a couple of the others, Capital One, a few. But it's a sort of rare breed. We're about 80%, 90% done on our transformation journey to get stuff to what we'd call cloud ready or optimized. But we think we're just scratching the surface because if you think about plugging ourselves into customers lives, making banking joyful, our external brand promise for that is live more, bank less. And nobody wakes up in the morning and says, oh, I can't wait to go to my local bank branch and go and do some banking. >> (laughing) I heard Steve talking about it yesterday. >> Actually there is one place. My wife loves going there because we do some great free cookies at DBS. >> John: Oh, excellent. >> But other that my wife, the rest of the planet doesn't really do that. >> John: Fair enough. >> If you want to live more, bank less, it's how do we get the toil of banking away from customers yet embed ourselves in their journeys. And for that we believe that this whole play on ecosystems is very important. So being a creator of an ecosystem or participating so that we take the banking toil out, and yet we inject ourselves, be that leisure or travel or insurance or whatever. And you don't see the bank, the bank is invisible. Then you're live more, bank less. To do that, you need great ecosystems. And we think three things help us to plug into ecosystems. Number one is you have to be able to scale very easily. And all the work we've done on the Gandalf stack means that were no longer afraid of scale, just bring it on. The second thing you need a lot of connectivity, and DBS two years ago, we launched the world's largest banking API platform. We went live with 150 different APIs and 60 live partners at the time. That's now grown to over 350 APIs and 100s of corporates and SME partners that wanna partner with us to pug us into their offering. So the more we do that, the more we disappear and let people live more, bank less. >> Well, next time, if you wanna bring some cookies with you, by all means, okay. (David laughs) We're always up for that, David, thanks for the time. >> Sure. >> We appreciate that and good luck on the mission and the journey there at DBS. >> Sure, thanks very much and great to be here, thank you. >> David Gledhill joining us this morning here, as we continue our coverage of the Red Hat Summit. We're in Boston. You're watching theCUBE. (upbeat music)