(light music) >> Hi everybody. Welcome to this Cube Conversation. I'm really pleased to announce a collaboration with Rob Strechay. He's a guest cube analyst, and we'll be working together to extract the signal from the noise. Rob is a long-time product pro, working at a number of firms including AWS, HP, HPE, NetApp, Snowplow. I did a stint as an analyst at Enterprise Strategy Group. Rob, good to see you. Thanks for coming into our Marlboro Studios. >> Well, thank you for having me. It's always great to be here. >> I'm really excited about working with you. We've known each other for a long time. You've been in the Cube a bunch. You know, you're in between gigs, and I think we can have a lot of fun together. Covering events, covering trends. So. let's get into it. What's happening out there? We're sort of exited the isolation economy. Things were booming. Now, everybody's tapping the brakes. From your standpoint, what are you seeing out there? >> Yeah. I'm seeing that people are really looking how to get more out of their data. How they're bringing things together, how they're looking at the costs of Cloud, and understanding how are they building out their SaaS applications. And understanding that when they go in and actually start to use Cloud, it's not only just using the base services anymore. They're looking at, how do I use these platforms as a service? Some are easier than others, and they're trying to understand, how do I get more value out of that relationship with the Cloud? They're also consolidating the number of Clouds that they have, I would say to try to better optimize their spend, and getting better pricing for that matter. >> Are you seeing people unhook Clouds, or just reduce maybe certain Cloud activities and going maybe instead of 60/40 going 90/10? >> Correct. It's more like the 90/10 type of rule where they're starting to say, Hey I'm not going to get rid of Azure or AWS or Google. I'm going to move a portion of this over that I was using on this one service. Maybe I got a great two-year contract to start with on this platform as a service or a database as a service. I'm going to unhook from that and maybe go with an independent. Maybe with something like a Snowflake or a Databricks on top of another Cloud, so that I can consolidate down. But it also gives them more flexibility as well. >> In our last breaking analysis, Rob, we identified six factors that were reducing Cloud consumption. There were factors and customer tactics. And I want to get your take on this. So, some of the factors really, you got fewer mortgage originations. FinTech, obviously big Cloud user. Crypto, not as much activity there. Lower ad spending means less Cloud. And then one of 'em, which you kind of disagreed with was less, less analytics, you know, fewer... Less frequency of calculations. I'll come back to that. But then optimizing compute using Graviton or AMD instances moving to cheaper storage tiers. That of course makes sense. And then optimize pricing plans. Maybe going from On Demand, you know, to, you know, instead of pay by the drink, buy in volume. Okay. So, first of all, do those make sense to you with the exception? We'll come back and talk about the analytics piece. Is that what you're seeing from customers? >> Yeah, I think so. I think that was pretty much dead on with what I'm seeing from customers and the ones that I go out and talk to. A lot of times they're trying to really monetize their, you know, understand how their business utilizes these Clouds. And, where their spend is going in those Clouds. Can they use, you know, lower tiers of storage? Do they really need the best processors? Do they need to be using Intel or can they get away with AMD or Graviton 2 or 3? Or do they need to move in? And, I think when you look at all of these Clouds, they always have pricing curves that are arcs from the newest to the oldest stuff. And you can play games with that. And understanding how you can actually lower your costs by looking at maybe some of the older generation. Maybe your application was written 10 years ago. You don't necessarily have to be on the best, newest processor for that application per se. >> So last, I want to come back to this whole analytics piece. Last June, I think it was June, Dev Ittycheria, who's the-- I call him Dev. Spelled Dev, pronounced Dave. (chuckles softly) Same pronunciation, different spelling. Dev Ittycheria, CEO of Mongo, on the earnings call. He was getting, you know, hit. Things were starting to get a little less visible in terms of, you know, the outlook. And people were pushing him like... Because you're in the Cloud, is it easier to dial down? And he said, because we're the document database, we support transaction applications. We're less discretionary than say, analytics. Well on the Snowflake earnings call, that same month or the month after, they were all over Slootman and Scarpelli. Oh, the Mongo CEO said that they're less discretionary than analytics. And Snowflake was an interesting comment. They basically said, look, we're the Cloud. You can dial it up, you can dial it down, but the area under the curve over a period of time is going to be the same, because they get their customers to commit. What do you say? You disagreed with the notion that people are running their calculations less frequently. Is that because they're trying to do a better job of targeting customers in near real time? What are you seeing out there? >> Yeah, I think they're moving away from using people and more expensive marketing. Or, they're trying to figure out what's my Google ad spend, what's my Meta ad spend? And what they're trying to do is optimize that spend. So, what is the return on advertising, or the ROAS as they would say. And what they're looking to do is understand, okay, I have to collect these analytics that better understand where are these people coming from? How do they get to my site, to my store, to my whatever? And when they're using it, how do they they better move through that? What you're also seeing is that analytics is not only just for kind of the retail or financial services or things like that, but then they're also, you know, using that to make offers in those categories. When you move back to more, you know, take other companies that are building products and SaaS delivered products. They may actually go and use this analytics for making the product better. And one of the big reasons for that is maybe they're dialing back how many product managers they have. And they're looking to be more data driven about how they actually go and build the product out or enhance the product. So maybe they're, you know, an online video service and they want to understand why people are either using or not using the whiteboard inside the product. And they're collecting a lot of that product analytics in a big way so that they can go through that. And they're doing it in a constant manner. This first party type tracking within applications is growing rapidly by customers. >> So, let's talk about who wins in that. So, obviously the Cloud guys, AWS, Google and Azure. I want to come back and unpack that a little bit. Databricks and Snowflake, we reported on our last breaking analysis, it kind of on a collision course. You know, a couple years ago we were thinking, okay, AWS, Snowflake and Databricks, like perfect sandwich. And then of course they started to become more competitive. My sense is they still, you know, compliment each other in the field, right? But, you know, publicly, they've got bigger aspirations, they get big TAMs that they're going after. But it's interesting, the data shows that-- So, Snowflake was off the charts in terms of spending momentum and our EPR surveys. Our partner down in New York, they kind of came into line. They're both growing in terms of market presence. Databricks couldn't get to IPO. So, we don't have as much, you know, visibility on their financials. You know, Snowflake obviously highly transparent cause they're a public company. And then you got AWS, Google and Azure. And it seems like AWS appears to be more partner friendly. Microsoft, you know, depends on what market you're in. And Google wants to sell BigQuery. >> Yeah. >> So, what are you seeing in the public Cloud from a data platform perspective? >> Yeah. I think that was pretty astute in what you were talking about there, because I think of the three, Google is definitely I think a little bit behind in how they go to market with their partners. Azure's done a fantastic job of partnering with these companies to understand and even though they may have Synapse as their go-to and where they want people to go to do AI and ML. What they're looking at is, Hey, we're going to also be friendly with Snowflake. We're also going to be friendly with a Databricks. And I think that, Amazon has always been there because that's where the market has been for these developers. So, many, like Databricks' and the Snowflake's have gone there first because, you know, Databricks' case, they built out on top of S3 first. And going and using somebody's object layer other than AWS, was not as simple as you would think it would be. Moving between those. >> So, one of the financial meetups I said meetup, but the... It was either the CEO or the CFO. It was either Slootman or Scarpelli talking at, I don't know, Merrill Lynch or one of the other financial conferences said, I think it was probably their Q3 call. Snowflake said 80% of our business goes through Amazon. And he said to this audience, the next day we got a call from Microsoft. Hey, we got to do more. And, we know just from reading the financial statements that Snowflake is getting concessions from Amazon, they're buying in volume, they're renegotiating their contracts. Amazon gets it. You know, lower the price, people buy more. Long term, we're all going to make more money. Microsoft obviously wants to get into that game with Snowflake. They understand the momentum. They said Google, not so much. And I've had customers tell me that they wanted to use Google's AI with Snowflake, but they can't, they got to go to to BigQuery. So, honestly, I haven't like vetted that so. But, I think it's true. But nonetheless, it seems like Google's a little less friendly with the data platform providers. What do you think? >> Yeah, I would say so. I think this is a place that Google looks and wants to own. Is that now, are they doing the right things long term? I mean again, you know, you look at Google Analytics being you know, basically outlawed in five countries in the EU because of GDPR concerns, and compliance and governance of data. And I think people are looking at Google and BigQuery in general and saying, is it the best place for me to go? Is it going to be in the right places where I need it? Still, it's still one of the largest used databases out there just because it underpins a number of the Google services. So you almost get, like you were saying, forced into BigQuery sometimes, if you want to use the tech on top. >> You do strategy. >> Yeah. >> Right? You do strategy, you do messaging. Is it the right call by Google? I mean, it's not a-- I criticize Google sometimes. But, I'm not sure it's the wrong call to say, Hey, this is our ace in the hole. >> Yeah. >> We got to get people into BigQuery. Cause, first of all, BigQuery is a solid product. I mean it's Cloud native and it's, you know, by all, it gets high marks. So, why give the competition an advantage? Let's try to force people essentially into what is we think a great product and it is a great product. The flip side of that is, they're giving up some potential partner TAM and not treating the ecosystem as well as one of their major competitors. What do you do if you're in that position? >> Yeah, I think that that's a fantastic question. And the question I pose back to the companies I've worked with and worked for is, are you really looking to have vendor lock-in as your key differentiator to your service? And I think when you start to look at these companies that are moving away from BigQuery, moving to even, Databricks on top of GCS in Google, they're looking to say, okay, I can go there if I have to evacuate from GCP and go to another Cloud, I can stay on Databricks as a platform, for instance. So I think it's, people are looking at what platform as a service, database as a service they go and use. Because from a strategic perspective, they don't want that vendor locking. >> That's where Supercloud becomes interesting, right? Because, if I can run on Snowflake or Databricks, you know, across Clouds. Even Oracle, you know, they're getting into business with Microsoft. Let's talk about some of the Cloud players. So, the big three have reported. >> Right. >> We saw AWSs Cloud growth decelerated down to 20%, which is I think the lowest growth rate since they started to disclose public numbers. And they said they exited, sorry, they said January they grew at 15%. >> Yeah. >> Year on year. Now, they had some pretty tough compares. But nonetheless, 15%, wow. Azure, kind of mid thirties, and then Google, we had kind of low thirties. But, well behind in terms of size. And Google's losing probably almost $3 billion annually. But, that's not necessarily a bad thing by advocating and investing. What's happening with the Cloud? Is AWS just running into the law, large numbers? Do you think we can actually see a re-acceleration like we have in the past with AWS Cloud? Azure, we predicted is going to be 75% of AWS IAS revenues. You know, we try to estimate IAS. >> Yeah. >> Even though they don't share that with us. That's a huge milestone. You'd think-- There's some people who have, I think, Bob Evans predicted a while ago that Microsoft would surpass AWS in terms of size. You know, what do you think? >> Yeah, I think that Azure's going to keep to-- Keep growing at a pretty good clip. I think that for Azure, they still have really great account control, even though people like to hate Microsoft. The Microsoft sellers that are out there making those companies successful day after day have really done a good job of being in those accounts and helping people. I was recently over in the UK. And the UK market between AWS and Azure is pretty amazing, how much Azure there is. And it's growing within Europe in general. In the states, it's, you know, I think it's growing well. I think it's still growing, probably not as fast as it is outside the U.S. But, you go down to someplace like Australia, it's also Azure. You hear about Azure all the time. >> Why? Is that just because of the Microsoft's software state? It's just so convenient. >> I think it has to do with, you know, and you can go with the reasoning they don't break out, you know, Office 365 and all of that out of their numbers is because they have-- They're in all of these accounts because the office suite is so pervasive in there. So, they always have reasons to go back in and, oh by the way, you're on these old SQL licenses. Let us move you up here and we'll be able to-- We'll support you on the old version, you know, with security and all of these things. And be able to move you forward. So, they have a lot of, I guess you could say, levers to stay in those accounts and be interesting. At least as part of the Cloud estate. I think Amazon, you know, is hitting, you know, the large number. Laws of large numbers. But I think that they're also going through, and I think this was seen in the layoffs that they were making, that they're looking to understand and have profitability in more of those services that they have. You know, over 350 odd services that they have. And you know, as somebody who went there and helped to start yet a new one, while I was there. And finally, it went to beta back in September, you start to look at the fact that, that number of services, people, their own sellers don't even know all of their services. It's impossible to comprehend and sell that many things. So, I think what they're going through is really looking to rationalize a lot of what they're doing from a services perspective going forward. They're looking to focus on more profitable services and bringing those in. Because right now it's built like a layer cake where you have, you know, S3 EBS and EC2 on the bottom of the layer cake. And then maybe you have, you're using IAM, the authorization and authentication in there and you have all these different services. And then they call it EMR on top. And so, EMR has to pay for that entire layer cake just to go and compete against somebody like Mongo or something like that. So, you start to unwind the costs of that. Whereas Azure, went and they build basically ground up services for the most part. And Google kind of falls somewhere in between in how they build their-- They're a sort of layer cake type effect, but not as many layers I guess you could say. >> I feel like, you know, Amazon's trying to be a platform for the ecosystem. Yes, they have their own products and they're going to sell. And that's going to drive their profitability cause they don't have to split the pie. But, they're taking a piece of-- They're spinning the meter, as Ziyas Caravalo likes to say on every time Snowflake or Databricks or Mongo or Atlas is, you know, running on their system. They take a piece of the action. Now, Microsoft does that as well. But, you look at Microsoft and security, head-to-head competitors, for example, with a CrowdStrike or an Okta in identity. Whereas, it seems like at least for now, AWS is a more friendly place for the ecosystem. At the same time, you do a lot of business in Microsoft. >> Yeah. And I think that a lot of companies have always feared that Amazon would just throw, you know, bodies at it. And I think that people have come to the realization that a two pizza team, as Amazon would call it, is eight people. I think that's, you know, two slices per person. I'm a little bit fat, so I don't know if that's enough. But, you start to look at it and go, okay, if they're going to start out with eight engineers, if I'm a startup and they're part of my ecosystem, do I really fear them or should I really embrace them and try to partner closer with them? And I think the smart people and the smart companies are partnering with them because they're realizing, Amazon, unless they can see it to, you know, a hundred million, $500 million market, they're not going to throw eight to 16 people at a problem. I think when, you know, you could say, you could look at the elastic with OpenSearch and what they did there. And the licensing terms and the battle they went through. But they knew that Elastic had a huge market. Also, you had a number of ecosystem companies building on top of now OpenSearch, that are now domain on top of Amazon as well. So, I think Amazon's being pretty strategic in how they're doing it. I think some of the-- It'll be interesting. I think this year is a payout year for the cuts that they're making to some of the services internally to kind of, you know, how do we take the fat off some of those services that-- You know, you look at Alexa. I don't know how much revenue Alexa really generates for them. But it's a means to an end for a number of different other services and partners. >> What do you make of this ChatGPT? I mean, Microsoft obviously is playing that card. You want to, you want ChatGPT in the Cloud, come to Azure. Seems like AWS has to respond. And we know Google is, you know, sharpening its knives to come up with its response. >> Yeah, I mean Google just went and talked about Bard for the first time this week and they're in private preview or I guess they call it beta, but. Right at the moment to select, select AI users, which I have no idea what that means. But that's a very interesting way that they're marketing it out there. But, I think that Amazon will have to respond. I think they'll be more measured than say, what Google's doing with Bard and just throwing it out there to, hey, we're going into beta now. I think they'll look at it and see where do we go and how do we actually integrate this in? Because they do have a lot of components of AI and ML underneath the hood that other services use. And I think that, you know, they've learned from that. And I think that they've already done a good job. Especially for media and entertainment when you start to look at some of the ways that they use it for helping do graphics and helping to do drones. I think part of their buy of iRobot was the fact that iRobot was a big user of RoboMaker, which is using different models to train those robots to go around objects and things like that, so. >> Quick touch on Kubernetes, the whole DevOps World we just covered. The Cloud Native Foundation Security, CNCF. The security conference up in Seattle last week. First time they spun that out kind of like reinforced, you know, AWS spins out, reinforced from reinvent. Amsterdam's coming up soon, the CubeCon. What should we expect? What's hot in Cubeland? >> Yeah, I think, you know, Kubes, you're going to be looking at how OpenShift keeps growing and I think to that respect you get to see the momentum with people like Red Hat. You see others coming up and realizing how OpenShift has gone to market as being, like you were saying, partnering with those Clouds and really making it simple. I think the simplicity and the manageability of Kubernetes is going to be at the forefront. I think a lot of the investment is still going into, how do I bring observability and DevOps and AIOps and MLOps all together. And I think that's going to be a big place where people are going to be looking to see what comes out of CubeCon in Amsterdam. I think it's that manageability ease of use. >> Well Rob, I look forward to working with you on behalf of the whole Cube team. We're going to do more of these and go out to some shows extract the signal from the noise. Really appreciate you coming into our studio. >> Well, thank you for having me on. Really appreciate it. >> You're really welcome. All right, keep it right there, or thanks for watching. This is Dave Vellante for the Cube. And we'll see you next time. (light music)

>> Announcer: Live from New Orleans, Louisiana, it's the Cube, covering .NEXT Conference 2018. Brought to you by Nutanix. >> Welcome back to the Cube, I'm here with Keith Townsend and I'm Stu Miniman. Happy to have on the program first-time guest Joe Zarb, who's with SAP Labs. He's the Vice President of Global Technology Partners. And welcome back to the Cube, long-time guest, Venugopal Pai, Vice President of Customer Success with Nutanix. Gentlemen, thanks so much for joining us. >> Great to be here, Stu, great to be here, Keith. >> All right, so Venugopal, our audience has seen him a few times. Joe, let's start, your role and inside SAP Labs what your organization does. >> Sure, happy to do that. So Joe Zarb, I head up our global technology partners within our global business development and ecosystems team. Basically helping our customers to respond to their needs and their wants for solutions that span not only SAP, but their whole digital transformation agenda. So we do that with the partners, and we do it with global service providers, we do it with software technology partners, and hardware technology partners. >> And Pai, we talked to Inder earlier today about customer success, but from an application standpoint, tell us why you're here. >> Of course, no thank you, Stu, thank you, Keith. Very good to be here again. So the reason that I'm here with Joe from SAP is we've had a long-standing relationship with SAP. Spanning almost four years. And the reason it's important is as Nutanix becomes the platform that customers start to depend on for the infrastructure, the key elements of what value we provide the customer is to mitigate a lot of the complexity that comes from infrastructure and allow them to focus on the business value of the application. And the predominant application as you start to global enterprises, large customers, SAP tends to be the lifeblood of that company. And the business value of how they drive value. So our partnership with SAP is to really make sure that as we start looking at transforming the data center and moving them to a digital platform that makes it very easy to consume, the ability for transcending the value to an SAP application, making sure that customers have that trust of, if I run SAP on Nutanix, the trust of availability, performance, capability, all the things that they need enterprise vendors to stand up to, we wanted to make sure that our journey with SAP started up early. Our journey with SAP in making sure they understand the concept of hyper-convergence and the impact of what it does for them has been a very fulfilling one and has been a journey that will continue on for a long ways to come. So that's why we're here. >> So, Joe, let's talk about digital transformation and the drivers. You know SAP, rich set of data is, I've heard it called a cash register of the world. So many transactions go through that. With that said, it's also one of those areas that we say, oh thoust dare not touch SAP. It is the system of record. However, it's a rich, rich area for digital transformation. The go fast, break things, part of the IT team, wants access to SAP, they want to get the data from there, they want to update transactions. Talk about that conflicting role that SAP has of, we're steady, rock solid versus go fast and break stuff. >> Right, so that's a great question. And what we're facing at SAP are demands that are coming from our customers around what people term as bimodal IT. They got to run their business, but they also have to innovate. So a big part of our strategy going forward is centered around HANA as you know, which is our real-time database, and it's a translytics database, right? So you could do transactions in it, you could also do analytics with the database within the same data set. So it provides a very powerful platform so that you could do your transactional operations and the analytics in a way where you could innovate. So that bimodal IT, and the relationship with Nutanix and the other hyper-convergent infrastructure players that we work with is really to focus on driving down the total cost of ownership in those operational areas, get to market quicker with those, and free up a technical center of excellence and functional center of excellence resources so that they can help the enterprise innovate. We have an entire platform that's dedicated just to innovation. It's our SAP Leonardo platform with our SAP Cloud platform, with Nutanix, and other hyper-converged players, and our transactional system. So that whole digital transformation really needs to take into account, hey, you got to protect the base, you got to run those core applications, but you can't take your eye off of innovation 'cause digital transformation's all about innovations. Business model reinvention as well as business process reinvention. So I think that's a big part of what we're focused on. >> So talk about Nutanix's role. How do you help customers with that goal of saying, the things that we do before are critically important, you need to keep doin' 'em, we need to do it cheaper, we need to do it faster, and we need to do it more reliably while we look to innovation. >> Absolutely. And I think that's a great story in terms of what Joe talked about in terms of SAP's lead into making sure that the ship is steady as it goes while making sure that the innovation engine is not forgotten, right? Where we start seeing is that the amalgamation between the two saying, I've got the traditional applications running as is, but I got to embrace innovation. And if we look at what Nutanix has done, and continues to do as you saw in some of the announcements at this event, is bringing the innovation in, but making sure that that innovation is brought with the respect of applications running in the data center, and still giving the customer the flexibility of hey, I want to embrace Cloud. I want to embrace the concept of what Cloud means to me, not just taking my data and moving it into the public Cloud, but giving me the way to get the Cloud-like heuristics, the Cloud-like management, Cloud-like flexibility, Cloud-like agility, the consumption of Cloud DevOps capabilities, so the combination of what we delivered in infrastructure layer, become where hardware to software, and tie it to what SAP is doing to drive that innovation from an application level is a very good partnership conversation to have, is hey, how do we now blend this software base in terms of what we're doing in the data center, and tie that to the innovation that SAP's driving at the application level, and together that's when true innovation for customers starts bringing to light. Because they focus the applications, we got the infrastructure, but this partnership then brings the two together. >> So, Pai, let's put some meat on the bone. It takes nine months, 12 months, to deploy SAP infrastructure period. Nutanix rack and stack, I can get a whole cluster up in less than an hour. However, there's still that SAP layer that basis layer that has to be laid out. How are you helping customers get more agile in that so that they wow the business? >> Absolutely. And just to put things in context, our SAP partner who has been around for four years, right? We've been SAP certified for 2 1/2 years, right? Both for SAP NetWeaver running on VMware hypervisors, and then as of a year and a half ago, running on our AHV hypervisor. So we're bringing that hypervisor innovation into the SAP world. Right, so that's one side. When you start looking at our software stack that start disseminating the focus on why things take so long for deploying an application is because the application layer is complex and the infrastructure layer is complex. So what we're doing is with the 40 to 50 customers you already have running on SAP is what we bring is if we can reduce the complexity of the infrastructure layer, the speed to value of deploying an application becomes much, much faster. So that's why customers are gravitating to Nutanix is because the infrastructure complexity has been eliminated as hey, it takes me six months to spin up a infrastructure that's meet variety of where they apply the amount of VM, which server, which storage, and you figure we're networking, and then I spin up the application. When we bring in Nutanix, the ability for us to disaggregate all that layered complexity that comes into play, speeds up the deployment of the application, therefore better time to value for customers saying, hey, I got to spin up the application a few months. I can't wait for nine months because the infrastructure's slowing me down. We start eliminating that complexity. >> Joe, one of the more interesting things to watch in the industry is the change in how customers are purchasing. Especially from software. The days of everything fully shrink-wrapped are long behind us. It's the subscription economy now. Nutanix is going along that journey from buying to software to fully subscription model. Can you touch on what you're seeing in maybe either you or Pai'll connect how that comes together with Nutanix. >> Yeah, I'd be happy to do that. So what we are seeing, and this is implemented in our strategy and our go-to market approach, is really that we live in a hybrid world. And I thought that that was a wonderful quote that I heard here at the conference or driven home in the keynote. So we do. We live in a hybrid world. SAP's strategy recognizes that. That's what our customers want. So we work very closely with Cloud partners like Microsoft Azure and Google, and of course Amazon and others. And of course we have an on-premise suite of solutions. So when we start to look at these business models, it's oftentimes about right-sizing the business model for the workload and the need of that particular customer sometimes for a particular industry. Now where Nutanix comes into play in this hyper-converged infrastructure is, there's some really difficult things that need to get done to make this world a reality. Right if you're going to move workloads and have them run in the Cloud, you might have them run at the edge if it's an IoT solution leveraging our Leonardo platform you might have them running in the core or you might have it running in a branch office. Every time you start adding those layers, you're adding complexity, you're adding cost, and you're adding a requirement for skills. So when we can work with close partners to downgrade the skills, downgrade some of the number of people you might need, create simplicity and create an environment where really it's a Nutanix statement but where our customers have that freedom to move their workload to the right environment to take advantage of it. Those are the partners who we want to work with. >> So SAP Labs, you can't get out of a Labs conversation without talking, well no we can't get out of a SAP Labs conversation without talking mobile and Fiori and all of the great stuff that's happening on just taking advantage of the deep data. Data's the biggest accessor, and mobile and giving that data to mobile, let's talk a little bit about the itch. What's the story between Nutanix, SAP, when it comes to stuff that CIOs care about today and that's Fiori. >> Yeah, so a great question. So if we look at Satyam presented yesterday in terms of our direction around IoT and looking at the edge as a very critical component of the entire operating system, enterprise called operating system model. One of the key things that we are spending a lot of time on is understanding the use cases for verticals and understanding okay when you look at a specific vertical, let's say it's oil and gas, or energy, or manufacturing, right? All of those verticals have a unique perspective on what IoT means to them. So IoT is a good buzzword and a good catchword, but when it comes to use cases and verticals, there's a very specific nomenclature on what they mean by IoT for them, right? So spending a lot of steam and Nutanix making a lot of time in deciphering what IoT means for customers, defining what use cases mean for that vertical and then working with SAP in determining okay, what does Leonardo mean for them because Leonardo is again, is a platform. Within the verticals, we're working with SAP and okay within the Leonardo platform, within the vertical, how do we define what our value prop within the IoT landscape is when it comes to the edge? And so you can see more coming from us, but we truly understand the importance of data like you said, and the creation of data at the edge, and the importance of analyzing the data, maybe in the Cloud. And that transformation of where the edge of data's created and where it needs to be analyzed, that journey is very complex. And if we can make that journey simple, then SAP customers win, SAP application, deployment wins, and we're able to therefore mitigate some of the complexity that comes with making that journey simple. >> You know I might add to that is again, what Pai said is spot on, but if you look at it from a manufacturing point of view, moving to the edge, customers are confronted with the reality of the networking complexity and they're either going to take the processing and move it to the problem or bring the problem to the processing. And so to do that takes hard work. And servers, and so there's a whole new genre of high-performance gateways and hardware that's emerging on the market from players like Fujitsu and Hewlett-Packard Enterprise and Dell, what have you. And you end up having a plethora of these devices at every well head, on every AMI, AMR meter-reading infrastructure in the utility system or in every single plant floor. So how do you take that level of innovation that's happening now at the plant floor and make it part, not only of your operational system, but of your IT and your data center so you could manage it with all the ilities that IT people do. And I think Nutanix and SAP are working to solve that problem. And our Leonardo platform is what we have to drive that edge and with Nutanix it's a very manageable environment. >> Great well, Joe and Pai, really appreciate the update on where you are today, where some of the direction are, we're going to the future. Getting towards the end of two days of live coverage here at Nutanix .NEXT 2018. For Keith Townsend, I'm Stu Miniman. Thanks for watching the Cube. >> Thank you. (upbeat music)

>> Narrator: Live, from Las Vegas, it's theCUBE, covering InterConnect 2017, brought to you by IBM. >> Okay, welcome back, everyone. We are live in Las Vegas, at the Mandalay Bay, for IBM's InterConnect 2017. It's the cloud and big-data Watson show that's all kind of coming together. This is theCUBE's three-day coverage, wall-to-wall day two, coming to an end here. I'm John Furrier, with my co-host Dave Vellante. Our next guest is Dave Lindquist who's an IBM Fellow, vice-president of Cloud DevOps and Analytics, at IBM. Great to have you on theCUBE, thanks for joining us. >> Thank you, John, thank you, Dave. >> So, love to have the IBM Fellows on, because we can then, like, get down and dirty, right? Get down and talk about the tech. I don't see if Ginnie's on stage today, I love the bumper sticker she has, 'cause she's, she nails it; enterprise strong, data first, cognitive to the core. So, enterprise strong means, there's a cloud-readiness equation going on right now, and we just came back from Google Next, and, hey, we've got great technology, buy us. Well, SLAs matter. You know, being enterprise ready isn't always about the best tech. >> No, no. >> It's about everything; it's the data, it's the machine-learning, it's the software, and also, those table stakes going on in the enterprise. Unpack that for us. >> Sure. Well, I think a lot of what you just went through, is at least part of the driving force between bringing ops into the dev space, this DevOps thing, and we'll expand on that in a little bit. But one of the big pushes going on is really around site reliability engineering, and how do you appropriately bring the skills together with the development teams to really set systems up in elastic scale, recovery-oriented compute models, so that you can scale that with the demand, you can recover from situations, you can recover from failures, you have a lot of redundancy built in the system. It takes a lot of time for teams to mature, to understand that, that aspect of delivering cloud services and delivering applications into, into a continuous available environment. >> What's IBM's formula for that right now, is you guys ramp-up and scale-up the cloud, IBM Cloud, you have the soft layer, and that's now Bluemix. So you have, on the lower end of the stack, you got to get that hardened infrastructure, if it's a service, and the platforms and service stuff. Then you start to bleed into the Bluemix. It's all one Bluemix now, but, you've got app developers, they want infrastructure as code, they want data as code, but then you got to have an uncoupling of set of services that look like one set of services. How hard is that, and what are you guys doing specifically to talk to customers about the value you're bringing on both sides of that camp? You know, the hard workload focused hybrid, to the creative sizzle of an app. >> Yeah, well, lot in that question, there's a lot of parts, lot of parts there. One of the things that's clearly going on, is, taking that next step in loose coupling systems, creating more independent services that can scale, elastically, independently of each other, the recovery-oriented models, and then presenting those services, up at the layers you mentioned; at the infrastructural areas, compute-storage networking, into the paths and container layers, so that the application developers can very rapidly get the environment they need, compose the services that they need, like the runtimes, data, messaging, et cetera, as a loosely-coupled system, and then build their applications to be deployed into that environment. >> How much innovation is going on? You're starting to see now, a new trend where there's more hardware engineering going into some chips, and hardware configurations, that's essentially software-driven, to offload, maybe machine-learning, some other, cooler things, that can assist some of the hard stuff that frees up more creativity on the software side. Say, machine-learning is a great example, you're starting to see Intel and others start thinking, okay, let's put some stuff on a chip. You have 5G wireless, you've got autonomous vehicles coming, a whole new hardware paradigm is kind of emerging with the cloud; how do you see that playing out, from an innovation standpoint? How does that strategy play out from a cloud, and IoT? >> To me, a lot of the things that are so exciting that's going on in the cloud, probably the big driver in the cloud is this whole acceleration of innovation. How quickly can you get from, instantiate an idea, in-field, iterate in-field with your users, towards a business outcome, and as you hit those outcomes, start scaling and expanding that out. And a lot of that innovation is building on some of the things that you mentioned: big data, cognitive, IoT, social, how do you start bringing these things together? And so, as you bring this together, real-time, you clearly need just exponential growth occurring, in compute capacity, which is probably creating, not probably, it's creating all kinds of opportunities for breakthroughs in algorithms, and breakthroughs in the hardware to support that. >> The other thing that we're seeing, I want to get your thoughts and commentary on is, how analytics is so compatible with the cloud, because, you're seeing that sweet spot developing nicely, and also with cloud-native trend is booming. You're seeing cloud-native compute foundations got big traction, and then the analytics is, people have no problem putting that in the public could, but yet they want the hybrid over here for some other stuff. So the workloads are starting to settle into their swim lanes. Your thoughts on the DevOps equation, as analytics moves to the cloud, not exclusively, but you know, for the majority of cases, and this cloud-native trend that's coming down the pike. >> Yeah, so, break that down in a couple pieces, the cloud-native trend, as well as the analytics trend. The cloud-native trend, what you see is a lot of development with micro services, and part of what makes that so exciting, is the culture of the teams and how they come together. You're basically seeing small teams, small, integrated teams, often called two-pizza teams, or squads, where you pull together designers with developers, with tests, with data science, with business, insights business strategy, into a team that then works together through the whole life-cycle, iterating incrementally and delivering in-field, to, as they move towards that business outcome that they're trying to achieve. So, what cloud-native is doing, is allowing, where that micro service model is really allowing many of these teams to work with relative autonomy, but accountability for their service, as it comes together to bring the full system together. What we're learning is that, one, you get a lot of speed like that, but then you start to, you need a level of analytics to help understand how that's coming together through that whole life-cycle, and what I mean by that is, you know, how is the testing coming along? So that everybody needs to start adopting more continuous testing, from unit tests, right, performance testing, availability, right into security testing. So you start running basic, simple analytics, where you start gathering on how the teams are doing in the continuous testing, and you can start setting soft and hard gates. An example of a soft gate might be, code coverage is dropping, so send an alert to the team to say, you've got to step up the code coverage. A hard gate might be, a security scan failed, so stop the deploy. And so, that's a basic set of analytics, but, the fun areas, to me, the exciting areas, we're starting to apply much more sophisticated models, are in understanding code health, and how the teams are actually working together. So you start developing models-- >> It's almost like team chemistry and coding working together. It's like, hey, you guys are good. You know, you're in the zone, you know? You're in the coding zone. Yeah, but this is a good point, I want to highlight just, let's just stop on that one point, I want to just drill down. I think that you nailed something that's, we've been kind of teasing out, and you put into words, the cloud-native trend around micro services, you mentioned teams working together, maybe some shared analytics, and kind of, code health, team, you know, scoreboard, or whatever. This is way beyond agile. I mean, agile has been a term that's been talked about inside companies, hey, let's be agile. You're talking about a fundamental industry reconfiguration of the players, so this is like a whole 'nother ballgame. >> To me, it builds on agile, what's going on, it does build on-- >> It goes beyond, it's-- >> But it goes way beyond, and even, you know, the early thinking, in DevOps, I think we're really pushing the envelope when we still call it DevOps, because we're thinking of the broad life-cycle of, you know, design practices. How do you begin to understand your users and what you're trying to accomplish with your users? Then you get into, you know, continuous integration, delivery, and testing, but then where it gets real interesting, is you start instrumenting everything, including, you know, getting direct LAN to site insight into how your users are using what you're deploying, and that causes the ability to pivot very rapidly, daily, weekly, into, you know, guiding where you're going to take your next iterations. To me, that's what's really taking this way past what you typically saw in an agile-- >> So what's happening to this traditional IT function? How is it adapting? You know, is it bi-modal, is there subtraction layer coming in, is there an equilibrium being reached between old and new? How would you describe what's going on? >> Fascinating question. What I often see in most of the enterprises I work in, is, they have a couple of investments going on. They're on a journey, a dev transformation journey, and a lot of that is, you know, really at the core of it, embracing DevOps. But what you'll see is, there's groups really pushing the envelope in these teams with cloud-native, micro service development, really all about speed, how quickly can they take small teams, get the idea into market? But then what you also see going on is, large sets of very valuable assets that data transactional systems, and how do you start embracing more, and more automation, to really reduce the cycle times, improve the service levels, and to effectively, start taking cost out of that full equation, that full life-cycle. So, what you're seeing, is a lot of automation coming into the existing IT environment. You're seeing a lot more of taking down of the silos of ops, and development teams, and that's going on in the core areas, and in the more cloud-native area, you're seeing, there's actually a common team put together, and they basically own the whole spectrum. They build it, they run it, the whole piece. >> You would think the competitive implications of this are huge. Without naming names, are you, at this point, able to discern patterns where organizations that are implementing this type of approach, are becoming more competitive, becoming more profitable, gaining share. Do we have enough evidence of that yet? >> Yes. Well, Gene, we were talking about Gene Kim earlier, and you can see, from a lot of the studies he has, that you'll see how much more effective and high-performance you're getting out of teams that are really embracing the best practices DevOps, and it is translating into financial results. So, you are seeing that bridge occur, but, part of what got me thinking about, is, what we were talking about earlier, the analytics that we've been exploring in the, in the team insights, and how the patterns you see, in how teams are interacting, and their code, and, you know, where are the core committers, the extended community, and extended community, the extended ring outside of that. You can begin to see patterns that are working well, patterns that are starting to have problems. It might actually be an architecture issue-- >> A self-healing concept too, if you think about it. This is actually taking it to like, social media has the same problem, on Twitter, runs with the same voice. You could have a zillion followers, and not have any influence, or have, you know, 100 followers and have a lot of influence, based on, that's no measure for that. You're getting at something that's more scoring-oriented, and analytical. That's interesting to me, I'm going to follow up on that, maybe another time. The question I want to ask you, 'cause I want to, I can't get it out of my mind, 'cause you mentioned the cloud-native, it's got me, kind of really, you know, riffing on this. We believe it's a multi-cloud world, right? And there's going to be a variety of clouds, not a winner take all, and they're all going to have differentiation, but having the traverse clouds is going to be really, really important. So, Kubernetes is kind of interesting to me, because you're looking at Kubernetes really kind of coming in and saying, hey, we could actually be a factor in orchestrating, and managing the sets of containers and micro services. And so, it's almost like a whole 'nother land-grab is going on around Kubernetes, because, it's so delicate. Can you share thoughts on that? Because, it's kind of nuanced, Kubernetes is, has got great traction in containers and micro services, but it's super-important. Why is it important, and why is it fragile, or is it fragile? In the sense of its importance, and not to be forked or tweaked. >> First, it's growing very rapidly. The use of containers for development and building, largely cloud-native micro service applications, is growing at a very rapid rate. And then, the ability to set-up these Kube clusters in different clouds, to be able to take advantage of the characteristics or services that are, are in those different clouds, including, you know, maybe you want to set-up a cluster near where your data is so you can have the processing local to that data, maybe you want to set-up clusters around certain security, or privacy, or regulatory policies. So, Kube is really providing, almost a platform-like layer for the containers, that is very robust. I wouldn't say it's fragile, but, with that flexibility, to setting that up, and where you want to setup that-- >> It allows customers to really figure out where to put workloads that matter. So, IoT would be a great use case for this. IoT, say, hey, you know what? This cloud is awesome at this and, put that app over there, and this one goes over here, 'cause it's got something over there that I like, but now, you need to have, I mean, is that kind of where, this is like, interoperability of networking in like, the 80s, in 90s, when that whole trend started booming is really its importance. >> Yes, yes-- >> Its openness. >> Well, the openness is critical. A lot of what we saw in distributed computing and the connectivity between clusters will be critical, but I do want to get to that point you mentioned on the openness; to me, openness is critical from a number of dimensions. One, certainly for inter-operability, and portability, but probably the most important is the rallying point for innovation, that you get these ecosystems, and with open technologies, which really is an open governance with open standards, you find a lot of creativity and innovation occurring within that base, and that, to me, is what really causes these environments to explode and take off. >> And if they can take that openness into the data level, then you're going to have a perfect storm of innovation, because now, you've got open source, which is thriving, and continues to be great, tier one by the way. >> And you're choosing to invest so much, and give back so much to the community. Not everybody does that, but you've made a business case for that. Why that strategy? I mean, it's IBM, you would think, you know, historically, IBM, very closed. But, you are almost overly-aggressive about your open source investments. >> Yeah. Not even sure it's historical, it dates back a long time, quite a while ago-- >> Yeah, that's true. >> Dave: You can go back, all the way to Linux. >> Yeah, Linux was the, they were the main player in Linux. >> You go back, obviously, the internet itself, TCP/IP, Linux, Java, Eclipse-- >> Track record's amazing. >> To me, all these industry breakthroughs, things that shape the industry are often, at its core, there were, at critical places, there was an open ecosystem, an open governance, open technology that really enabled it to just expand and grow at a tremendous rate. >> I think blockchain is perfect for you guys right now. A great example of, and in, might, people might be saying, oh, a little bit early, I think that bet is going to be playing out well. If you take the open source, and this whole digital value thing, very interesting. Well, I mean, final thought: what are you excited about right now? I mean, as an IBM Fellow, you get the canvas within the tech space, obviously, a lot to pull, it's kind of intoxicating these days. We kind of went down memory lane with some old ways, but, there's a ton of great new things happening. What are you excited about? I mean, what's getting you buzzed up about the current tech scene? >> The things that are really, I find fascinating and exciting now, is the different ways we're learning to apply AI, cognitive machine-learning into the different systems. We just, sort of, covering it just a little bit, in the DevOps space itself, but we're learning to apply it from the end of test, to understanding how we can predict where we have problematic code files, and how you would improve your test or skills, to the other spectrum of how is the community actually operating? Is the community healthy, is it growing? How are my projects and my teams working together? How healthy is that, are there issues that I have to start looking at? Do I have a design issue, an architecture issue, a squad issue? So, I can start doing that. This is all, we're learning how to take in big data and apply machine learning to this to get these types of insights. And to me, you know, that's just one spectrum of how we're applying it, but that's, to me, what's so exciting, is how we're applying it. You know, some of the examples that were shown with blockchain and cognitive, and in IoT, and AI. >> Dave is changing the game. The algorithms are coming out as more like libraries, not as custom stuff, and you've got the compute over the top. It's like, I wish I was 15 again, you know? What a great time to be in the tech industries, a computer scientist or any kind of science field right now. >> It is a great time. >> It's just a super time. Appreciate it, Dave, thanks for coming on theCUBE. Dave Lindquist, IBM Fellow, vice president of DevOps and the cloud at IBM, sharing his insight, great job. IBM's coverage continues here at day two, here on theCUBE, I'm John Furrier with Dave Vellante. Stay with us for our wrap after this short break. (percussive tones)