>> From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE in ETR. This is "Breaking Analysis" with Dave Vellante. >> Despite all the talk about repatriation, hybrid and multi-Cloud opportunities, and Cloud is an increasingly expensive option for customers, the data continues to show the importance of public Cloud to the digital economy. Moreover, the two leaders, AWS and Azure, are showing signs of accelerated momentum that point to those two giants pulling away from the pack in the years ahead, with each firm's showing broad based momentum across their respective product lines. It's unclear if anything, other than government intervention or self-inflicted wounds will slow these two companies down this decade. Despite their commanding lead, a winning strategy for companies that don't run their own Cloud continues to be innovating on top of their massive CapEx investments. The most notable example here being Snowflake. Hello, everyone. Welcome to this week's Wikibon CUBE insights powered by ETR. In this breaking analysis, we provide our quarterly market share update for the big four hyperscale Cloud providers. And we'll share some new ETR data from their most recent survey. And we'll drill into some of the reasons for the momentum of these two companies and drill further into the database and data warehouse sector to see what, if anything, has changed in that space. First, let's look at some of the noteworthy comments from AWS and Microsoft in their recent earnings updates. We heard from Amazon, the following, "AWS has seen a reacceleration of revenue growth as customers have expanded their commitment to the Cloud and selected AWS as their Cloud partner." Notably, AWS revenues increased 39% in Q3 2021. That's a thousand basis point increase in growth relative to Q3 2020. That's an astounding milestone for a company that we expect to surpass $60 billion in revenue this year. Further, AWS touted the adoption of its custom silicon, and specifically its Graviton2 processors. AWS is fond of emphasizing Graviton's 40% price performance improvements relative to x86 processors, something we've reported on quite extensively. AWS is investing in custom silicon, encouraging ISVs to port their code to the platform so that customers will experience little or no code changes when they migrate. Again, we believe this is a secret weapon for AWS as its cost structure will continue to improve at a rate faster than competitors that don't have the resources or the skills or the stomach to develop such capabilities. Microsoft, for its part, also saw astoundingly good growth of 48% this past quarter for Azure. This is a company that we forecast will approach $40 billion in IaaS and PaaS public Cloud revenue this year. Microsoft's CEO, Satya Nadella, on its earnings call, emphasized the changing nature of Cloud expanding in a distributed fashion to the edge. He referenced Azure as the world's computer. Building on his statements last year that Microsoft is building out a powerful, ubiquitous, intelligent, sensing and predictive Cloud. Yes, folks, it does feel like we're entering the so-called Metaverse, doesn't it? Okay, to underscore the momentum of these two companies, let's take a look at the ETR breakdown of Net score, which measures spending momentum. This chart will be familiar to our listeners. It shows the breakdown of net score for AWS, with the lime green showing new adoptions. That's 11%. The forest green is spending more than 6% relative to the first half of this year. That's a very robust 53%. The gray is flat spending. That's 30% on a very, very large base. And the pink is spending declines of minus 6% or worse. That's 4%. And the bright red is defections i.e those leaving AWS. That's 1%. That's virtually non-existent. You subtract the reds from the greens and you get a net score of 59. Remember, anything over 40, we can still consider to be elevated. Let's look at that same data for Microsoft again. You have some new ads that lime green, that's 7%. The forest green is at 46% of customers spending more, which is an incredible figure for a company with revenues that will in the near term surpass $200 billion. And the red is in the low single digits. Buffered by its enormous PC software profits over the years, Microsoft is powered through its Window's Dogma and transitioned into a Cloud powerhouse. Let's now share some of our latest numbers for the big four hyperscale players, AWS, Azure, Alibaba and Google. Here, we show data for these companies from 2018 and our estimates for 2021. This data includes our final figures for AWS, Azure and GCP for Q3 with Alibaba yet to report. Remember, only AWS and Alibaba report IaaS revenue cleanly with Microsoft and Google, they give us a little breadcrumb nuggets that allow us to triangulate with our survey data and other intelligence. But it's our attempt to do an apples to apples comparison for those four companies using AWS and it's reporting as a baseline. In Q3, AWS reported more than $16 billion in revenue. We estimate Azure at 10 billion, Alibaba, we expect to come in at just under 3 billion, and GCP at 2.5 billion for the quarter. With three quarters of data in, with the exception of Alibaba, we're forecasting AWS to capture 51% of the big four revenue, the hyperscale revenue. And really we believe these are the only four hyperscalers. AWS will surpass 60 billion with Azure just under 40 billion, Alibaba approaching 11 billion, and Google coming in just under 10 billion for the year is our expectation. We forecast these four will account for $120 billion this year. That's a 41% increase over 2020 and the same collective growth rate as 2020 relative to 2019. We expect Azure to be 63% of the size of AWS revenue. So it is gaining share. Both of those companies, however, saw accelerated growth this past quarter with Alibaba and GCP's growth rates decelerating relative to last year. Now, let's take a closer look at those growth rates. This chart shows the quarterly growth rates for each of the four going back to the beginning of 2019. Both GCP and Alibaba are showing dramatic declines in growth rates, whereas, this past quarter Azure saw accelerated growth and AWS has now seen an increased rate of growth for the past two quarters. In fact, AWS' growth is about where it was in 2019 when it was around half of its current revenue size. And in 2019 growth was decelerating through the quarters as you can see where today that trend has reversed. It's quite amazing. All right, let's take a look at the broader Cloud landscape and bring back some ETR data. This chart that we're showing here, it shows net score or spending momentum on the vertical axis and market share or presence in the dataset on the horizontal axis. Note that red dotted line, anything above that we can still consider elevated and impressive. As when we've previously shared this data, AWS and Microsoft Azure are up and to the right. Now remember, this chart is not just counting IaaS and PaaS as we showed you earlier, it's however the customers views whatever they think Cloud is. And so they're likely including Microsoft SaaS in this picture. Which is why Microsoft shows larger than AWS despite what we showed you earlier. Nonetheless, these two are well ahead of the pack and the growth rates indicate that they're pulling away. But we've added some of the other players, most notably VMware Cloud on AWS. It's showing momentum as is VMware Cloud, which is VMware Cloud foundation and other on-prem Cloud offerings, even though it's below the red line for the on-prem piece, it's very respectable. The VMware Cloud on AWS has been consistently up above that red line. Has popped beneath it in some quarters, but it's very, very strong. As is, you know, Red Hat OpenShift, it's a little bit below the line, but it is respectable. We've superimposed this by the way. Red Hat OpenShift in the ETR platform is under the container orchestration taxonomy, but we'd like to put it in next to the Cloud players for context. That's how Red Hat sort of thinks about this as well. They think about OpenShift as Cloud. And then you can see the other players. Alibaba has got a small sample in the ETR dataset. Just does not enough presence in China. But Dell and HPE have started to show up in the Cloud taxonomy. So buyers are associating their private Clouds with Cloud. So Dell's Apex, HPE's GreenLake. So that's a positive. And you can see Oracle, which of course is OCI, Oracle Cloud infrastructure. And then IBM with its public Cloud. So, it's a positive that these on-prem players are showing up in this data, but the reality is the hyperscalers are growing collectively at 40% annually and the on-prem players are growing in the low single digits. So, and if you carve out the IaaS business of AWS and Azure, they're larger than most of the on-premises infrastructure players. And all the on-prem players are moving toward an as a service model, as I just alluded to. So, undoubtedly, hybrid multicloud edge are going to present opportunities for the likes of Dell, HPE, Cisco, VMware, IBM, Red Hat, et cetera. But they also present opportunities for the public Cloud players who have vibrant ecosystems and marketplaces much more diverse and deep than the traditional vendors. You know, we have a clearer picture of Microsoft's sort of hybrid and edge strategy because the company has such an enormous legacy business, it really had to think about that much more deeply. It wasn't a blank sheet of paper like AWS. It's going to be interesting at reinvent this year if new CEO, Adam Selipsky, will talk about this. And it will be good to hear how he's thinking about the next decade, how AWS thinks about hybrid and edge, I guarantee that with their developer affinity and custom Silicon capabilities, they're thinking about it differently than traditional enterprise players. And as we've stressed in this segment, they have across the board momentum. Now to quantify that, let's take a look at AWS as portfolio in the spending momentum within its product segments. This chart shows AWS's net scores or spending momentum in the areas where AWS participates in the ETR taxonomy. Again, note that red line. Anything above 40% is considered an elevated watermark. We're showing data from last October, this past July and the latest October 21 survey. That yellow line or a bar. What's notable is the yellow versus the gray bars up across the board for the most part, other than chime... And by the way, other than chime, everything is above the 40% mark as well. Now, we've highlighted database because we feel it's one of the most strategic sectors in a real battleground. So we want to drill into that a bit. Here's our familiar X Y graph showing Net score on the Y axis, remember, that's, again, spending momentum and market share or pervasiveness in the survey on the horizontal axis. This data, by the way, includes on-prem and Cloud database data warehouse. So keep that in mind. Let's start with one of our favorite topics; Snowflake. We've reported again and again and again, that we've never seen anything like this. The company's net score has moderated ever so slightly this quarter, but it's still just below 80%. Very highly elevated. Well, above that 40% mark. It's Snowflake's presence continues to grow as a gain share in the market. Snowflake is growing revenue in the triple digits. It's an insane pace, hence its current $115 billion market cap as of this episode. Now that said, all three US-based Cloud players there are above the 40% line with AWS and Microsoft having significant presence on the horizontal axis. You see Cockroach Labs, Redis, Couchbase, they're all elevated or highly elevated. Couchbase just went public this summer. So that may help with its presence. MongoDB, they're killing it. They have a $37 billion market cap as of this episode. The stock has been on a tear. You see MariaDB was also in the mix. And then of course you have Oracle, the database leader. Look, they continue to invest in making the Oracle database and other software like MySQL, the best solution for mission critical workloads, and they're investing in their Cloud. But you can see overall, they just don't have the momentum from a spending standpoint that the others do because the declines in their legacy business. And they've been around a long time. Those declines are not fully offset by the growth in Cloud database and Cloud migration. But look, Oracle is a financial powerhouse with a $250 billion plus market cap. And the stock has done very well this past year. Up over 60%. Cloudera is going private. So it can hide the pain of the transitions that it's undergoing between the legacy install bases of Cloudera and Hortonworks. It's just a tough situation. When the companies came together, Cloudera essentially had a dead end. Each of those respective platforms and migrate their customers to a more modern stack as part of its Cloud strategy. Ironic that it's name is Cloudera. You know, that's always a difficult thing to do. So as a private company, Cloudera can maybe get off that 90 day shot clock and buy some time to invest without getting hammered by the street. And you know, Teradata consistently has not shown up well in the ETR dataset. It's transitioned to Cloud and cross-Cloud still hasn't shown momentum in the surveys. So, look right now, it's looking like the rich get richer. So just to quantify that a little bit, let's line up some of the database players and look a little bit more closely at net score. This chart shows the spending momentum or lack thereof with the net score or spending velocity granularity that we described before. Remember, green is spending more, red is spending less, bright red is leaving the platform, bright green is adding the platform. You take red, subtract red from the green, and that gives you a net score. Snowflake, as we said, tops the list. You can see the granularity there. You can compare the performance. In a little different view to understand how these scores are derived, look, the ideal profile is a solid lime green, a big forest green, a not too large gray and ideally little or no bright red AKA defections. And you can see the green funnel in the gray increasing prominence as the vendor momentum declines. Interestingly, with the exception of Cloudera and Teradata, defections are all in the single digits or nonexistent. In the case of Snowflake, Redis, red is no red at all, but small sample, Couchbase has no defections and very little defection for the giant Microsoft. Incredibly impressive. This speaks to how hard it is to migrate off of a database no matter how disgruntled you are. The more common scenario is to isolate the database and build new functionality on modern platforms. Okay, so what to watch out for. Well, reinvent this coming up next month. Oh this month. It's the first time someone other than Andy Jassy will be keynoting as CEO. 15 years of Cloud, this is the 10th re-invent, which is always a market for the direction of the industry. I've said many times that the last decade was largely about IT transformation powered by the Cloud. I believe we're entering a new era of business transformation where the Cloud is going to play a significant role. But the Cloud is evolving from a set of remote services out there in the Cloud to an omnipresent platform on top of which many customers and technology companies can innovate. And virtually every industry will be impacted by Cloud. However it evolves in the coming decade. The question will be, how fast can you go? And how will players like AWS and Microsoft and many others that are building on top of these platforms make it easier for you to go fast? That's what I'll be watching for at re-invent and beyond. Okay, that's a wrap for today. Remember, these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis podcasts. Check out ETR's website at etr.plus. We also publish a full report every week on wikibon.com and siliconangle.com. You can get in touch with me, david.vellante@siliconangle.com. You can DM me @dvellante or comment on our LinkedIn posts. This is Dave Vellante for theCUBE insights powered by ETR. Have a great week, everybody. Stay safe, be well. And we'll see you next time. We'll see you at re-invent. (soft upbeat music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> As we reported last week, we believe that in the next decade, there will be changes in public policy that are going to restrict the way in which big internet companies are able to appropriate user data. Big tech came under fire again this week with the CEOs of Facebook, Twitter, and Google going toe to toe with several U.S. senators. Microsoft CEO Satya Nadella, however, was not one of those CEOs in the firing line. Microsoft doesn't heavily rely on ad revenues, rather, the company's momentum is steadily building around Azure, which by my estimates is now roughly 19% of Microsoft's overall revenues. It's surpassed, maybe nearly got to $7 billion for the first time on a quarterly basis. I'll come back to you on that. Hello everyone, and welcome to this week's Wikibon CUBE insights powered by ETR. In this Breaking Analysis, we'll respond to the many requests we've had to dig into the business of Microsoft a little bit deeper and provide a snapshot of how the company is faring in the ETR dataset. Let's take a quick look at Microsoft's financials, and the scope of Microsoft's business is actually mind-boggling. The company has roughly $150 billion in revenue, and it grew its top line 12% last quarter. It has more than $136 billion in cash on the balance sheet. Microsoft generates over $60 billion annually in operating cashflow. And last quarter alone threw off more than 19 billion in operating cash. Its gross margins are expanding across virtually all of its major business lines. So let's look at those business sectors. Microsoft, it doesn't suffer from the nagging problems that we've talked about with a lot of older tech companies. Companies like IBM and Dell and Cisco and Oracle and SAP, they struggle with growth sometimes because their growth businesses are not yet large enough to offset the declines in their traditional on-premises business segments. Now at the highest level, Microsoft breaks its business into three broad categories, and they're all growing quite nicely. Let me add some color here. Let's start with the productivity and business process line of business. LinkedIn, which is growing at 16%, is in this category as is Office. This business is shifting from one of on-prem licenses, which are really headwinds right now from Microsoft, to the cloud, in the form of SaaS with Office 365, which is growing at a 20% clip within its commercial market base. Even the consumer side of O365 is growing in the double digits. Dynamics is Microsoft's ERP and CRM business, and that falls into this slice of the pie, that's growing at 18%. And then the newer Dynamics 365, that's growing at 37%. So you can see, Microsoft is easily able to show growth despite the transitions from its legacy business. Intelligent cloud is the next segment. It's kind of the kitchen sink category, meaning there's stuff in there that includes a bit of cloud washing in my opinion, but Microsoft is not nearly as egregious as IBM with the liberties that it takes around its cloud categorization. For Microsoft it's a $13 billion quarterly business. And it's growing at 19%, as we show in the pie chart. Azure is an increasingly large portion of this segment. Azure is the most direct comparison with AWS. And I have said in the past quarter, I'd say it's around 50% of the intelligent cloud, and that it's approaching by my estimates around $7 billion a quarter. Azure grew at 47% annually this past quarter, the same growth rate as last quarter. Ironically, both AWS and Google Cloud grew at the same year over year rate this quarter as they did last quarter. AWS is 29% GCP in the high 50s by at my estimates. AWS revenue was 11.6 billion this past quarter, and I have GCP still well under 2 billion. We'll be updating our cloud numbers and digging deeper next week into this topic. So consider these estimates preliminary for Azure and GCP, which the respective companies don't break out for as Amazon, as you know, breaks out AWS explicitly. Now, back to Microsoft's intelligent cloud business. It includes on-prem server software, which is a managed decline business from Microsoft. They also include enterprise services in this category. So as you can see, it's not a clean cloud number for comparison purposes. Now finally, the third big slice of the pie is more personal computing. I know, it's kind of a dorky name, but nonetheless it's nearly a $12 billion business that's growing at 6% annually. The Windows OEM business is in here, as is Windows 10 and some security offerings. Surface is also in here as well and it's growing in the mid-thirties. Search revenue is in this category as well. It's declining per my earlier statements that it's not a main piece of Microsoft's business. Now, one of the most interesting areas of this sector is gaming. Microsoft's gaming business is growing at 21% and they just acquired ZeniMax Media for seven and a half billion dollars. Let me land on gaming for a minute. The gaming experts at theCUBE are really excited about Microsoft's XBox content services, which grew at about 30% this past quarter. Game Pass is essentially Microsoft's Netflix, or you can think of it as maybe like a Spotify model. You can get in for as low as $5 a month. I think you can pay as much as $15 a month and get access to a huge catalog of games that you can download. In November of last year, Microsoft launched its xCloud beta service, which allows you to download to a PC or a game box. Now eventually with 5G, the box goes away. All you'll need is a screen and you know, controller with the joysticks, no download. In fact, this is how it works today for Android. Now, interestingly, Apple is blocking Microsoft and some others like Google's Stadia, saying that they don't allow streaming game apps like Microsoft's xCloud service, because they don't follow the company's guidelines. What Apple's not telling you is that its adjacent offering, Apple Arcade, is considered subpar by hardcore gamers. And while Apple allows the streaming of movies and music from any service on the iPhone, it's decided not to allow streaming games. Now, the last thing I want to stress about Microsoft is its leverage point around developers. Developers is a big one here, we all remember the sweaty Steve Ballmer running around the stage like a mad man, screaming, "Developers, developers, developers!" Well, despite his obsession with Windows, he sure got that one right. The GitHub acquisition was Microsoft's way of buying more developer love. It does concentrate power with a tech giant, but you know what, if it wasn't Microsoft that bought GitHub, it would have been Facebook or Amazon or Google or one of the other tech giants. Now, despite some angst in the developer community over this, GitHub, it really is a linchpin for Microsoft to more tightly integrate GitHub with its pretty vast developer tool set. All right. Let's look deeper into the Microsoft data and focus on the enterprise. We'll bring in the ETR as we always do. We said last week that Google needed to look to the cloud and edge and get its head out of its ads. Well, Microsoft recovered from its Windows myopia after Satya Nadella took over in 2014, and by all accounts from the ETR survey data, Microsoft is killing it across the board. Let me start by putting Microsoft in context with some of the most prominent companies that both compete with, and sometimes partner with Microsoft. So this xy graph, it's one of our favorites. I show it all the time and it shows net score on the vertical axis, which is a measure of spending momentum from ETR, and the horizontal axis shows what we call market share, which is a measure of pervasiveness in the survey. Now in the upper right hand table, you can see the data for each of the companies. There's an ETR survey taken in October and it had more than 1400 completes. Several points stand out here. Microsoft is by far the most pervasive in the dataset, and yet its net score or spending velocity is right there with AWS, ServiceNow, Salesforce, and Workday. Only Snowflake, which I put in there for context, because of its consistently strong net scores, shows a meaningfully higher net score, of course from a much smaller base. Now what makes this so impressive is it represents a pan-Microsoft view across its entire portfolio. And you can see where companies like IBM and Oracle struggle from a momentum standpoint compared to Microsoft, which is a much, much larger company. It's that problem that I referred to earlier regarding the smaller size of their respective growth businesses. Also called Cisco and SAP, which despite some earnings challenges lately, are able to maintain net scores that while not in the green, they're not in the red, either. Green essentially means your overall install base is expanding. Red indicates contraction. Now let's look at the spending patterns for Microsoft customers. This chart shows the granularity of ETR's net score for Microsoft. The green represents increased spend and the red decreased spend. What's impressive is that Microsoft's red zone, I mean it's essentially negligible at 6%, when you add two reds up, the pink and the bright red. Their customers, they're all spending more, or the same, and very few are leaving the platform. Now I made the case last week that Google should double or triple its efforts and focus on cloud and the edge. Microsoft has already made that transition in its business and is the, that's the premise really of my discussion today. Specifically, Microsoft Azure is powering the company across all of its products and services. It's giving Microsoft tremendous operating leverage and steadily improving marginal economics. You can see that in the gross margin lines this quarter, across all of its businesses. And here's a graphic showing its position within cloud computing in terms of net score. Microsoft Azure functions, which is the first bar on this chart, and Azure overall, which is the third set of bars, shows momentum that's as strong as any cloud category, including AWS Lambda, which as we've talked about many times is killing it. Now five over from the left, count them over, one, two, three, four, five, you can see AWS overall. So that's a really important reference point. And while its levels are still elevated, Azure overall, which again is number three from the left, has meaningfully more momentum with 65% net score versus 52% for AWS overall. Now reasonable people can debate the quality of these respective clouds and you could argue over feature sets, who's got the most features, who's got the most regions, which regions are most reliable, who's got the most data centers and all that stuff, but it's really hard to argue against Microsoft's "Good enough" strategy. It's working in the cloud, and it has been working for the company for decades. Now another Microsoft strategy has been to be a late comer to a category and then bundle multiple capabilities into one suite. We saw this at first, really in the late 1980s with Office, and it's continued in a number of areas. The latest example, Microsoft Teams. Teams combines features like meetings, phone, chat, collaboration, as well as business process workflows that leverage tools like SharePoint and PowerPoint. I mean, it's a killer strategy, and you can see the results in this chart. I mean, it's essentially competing with Zoom, it's competing with Slack and all the sort of productivity plays there in that space. And this graphic compares net scores from the year ago October survey for reference, the July survey from this year, and the most recent October survey, as I said, 1400 respondents. Look at the lead that Teams has relative to the competition. There's a story across Microsoft's portfolio. Look at Microsoft's products in the ETR taxonomy. Video conferencing with Teams, productivity apps, RPA, cloud, cloud functions, machine learning, artificial intelligence, containers, security, end point, analytics, mobile, even database. The only signs of softness are really seen in the company's legacy businesses like Skype or on-prem licenses business, which I said were a headwind for them. And while PCs and tablets are weaker, that's what you'd expect from this mature industry relative to some of these other categories. Now, again, the premise here today is that by pivoting to the cloud and going all in competing with infrastructure as a service, Microsoft has created a platform for innovation for its business, and its developer chops are really credible, so it's evolving its install base very successfully to Azure. It's got a very solid hybrid and multi-cloud strategy and story with Microsoft Arc, which eventually it can take to the edge. You know, we think its edge strategy needs some work, but nonetheless, the company is really, really well positioned. Microsoft has a huge partner ecosystem, heck, it even partners with Oracle and database, as well as using Azure to enter new markets, including vertical clouds like healthcare, which it talked about on its earnings call. I mean, there's really not much on which you can criticize Microsoft. You know, sure, they've had some high profile failures in the past. The Nokia acquisition, the Windows phone, you remember Zune? Mixer, you know, Bing. Is Bing a fail? I don't know. Maybe not really. I guess the fail is, you know, what I was talking about last week with antitrust, Microsoft was distracted by the DOJ and maybe that caused it to miss search, give it to Google, and in that sense, maybe it was a failure, but overall, pretty good track record from Microsoft. Yeah, maybe you can say Microsoft is somewhat of a copycat, you know, the graphical user interface that they copied from the Mac, but hey, even Steve Jobs stole that. Surface, okay. The cloud? But so what, ideas, they're plentiful, execution is the key, really. No matter how you slice it, the data doesn't lie. Microsoft's financial performance, its pivot to the cloud, and the success of its adjacent businesses, make it one of the most remarkable rebirths in the history of technology industry. Now I didn't use the word turnaround because the company was never really in trouble. It just became irrelevant and kind of boring. Today, Microsoft is far from immaterial. Okay. That's it for this week. Remember all these episodes are available as podcasts wherever you listen. So please subscribe. I publish weekly on Wikibon.com and Siliconangle.com. And don't forget to check out ETR.plus for all the survey data and analytics. I appreciate always the comments on my LinkedIn posts or you can DM me @DVellante, or email me at David.Vellante@SiliconAngle.com. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching everybody, be well, and we'll see you next time. 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>> Commentator: Live from Austin, Texas, it's the Cube. Covering KubeCon and CloudNativeCon 2017. Brought to you by Red Hat, the Linux foundation, and the Cube's ecosystem partners. >> Hey welcome back everyone. Live here in Austin, Texas the Cube's exclusive coverage of KubeCon and CloudNativeCon, its third year, not even third year I think it's second year and not even three years old as a community, growing like crazy. Over 4500 people here. Combined the bulk of the shows it's double than it was before. I'm John Ferrier, co-founder of SiliconANGLE. Stu Miniman, analysts here. Next is Gabe Monroy who was lead p.m. product manager for containers for Microsoft Azure, Gabe welcome to the Cube. >> Thanks, glad to be here. Big fan of the show. >> Great to have you on. I mean obviously container madness we've gotten past that now it's Kubernetes madness which really means that the evolution of the industry is really starting to get some clear lines of sight as a straight and narrow if you will people starting to see a path towards scale, developer acceleration, more developers coming in than ever before, this cloud native world. Microsoft's doing pretty well with the cloud right now. Numbers are great, hiring a bunch of people, give us a quick update big news what's going on? >> Yeah so you know a lot of things going on. I'm just excited to be here, I think for me, I'm new to Microsoft right. I came here about seven months ago by way of a Dais acquisition and I like to think of myself as kind of representing part of this new Microsoft trend. My career was built on open source. I started a company called Dais and we were focused on really Kubernetes based solutions and here at Microsoft I'm really doing a lot of the same thing but with Microsoft's Cloud as sort of the vehicle that we're trying to attract developers to. >> What news do you guys have here, some services? >> Yeah so we got a bunch of things, we're talking about so the first is something I'm especially excited about. So this is the virtual kubelet. Now, tell a little bit of story here, I think it's actually kind of fascinating, so back in July we launched this thing called Azure Container Instances and what ACI was first of its kind service containers in the cloud. Just run a container, runs in the cloud. It's micro build and it is invisible infrastructure, so part of the definition of serverless there. As part of that we want to make it clear that if you were going to do complex things with these containers you really need an orchestrator so we released this thing called the ACI Connector for Kubernetes along with it. And we were excited to see people just were so drawn its idea of serverless Kubernetes, Kubernetes that you know didn't have any VMs associated with it and folks at hyper.sh, who have a similar service container offering, they took our code base and forked it and did a version of theirs and you know Brent and I were thinking together when we were like "oh man there's something here, we should explore this" and so we got some engineers together, we put a lot of work together and we announced now, this in conjunction with hyper and others, this virtual kubelet that bridges the world of Kubernetes with the world of these new serverless container runtimes like ACI. >> Okay, can you explain that a little bit. >> Sure. >> People have been coming in saying wait does serverless replace, how does it work, is Kubernetes underneath still? >> Yeah so I think the best place to start is the definition of serverless and I think serverless is really the conflation of three things: it's invisible infrastructure, it is micro billing, and it is an event based programming model. It's sort of the classical definition right. Now what we did with ACI and serverless containers is we took that last one, the event based programming model, and we said look you don't need to do that. If you want to write a container, anything that runs in that container can work, not just functions and so that is I think a really important distinction that I believe it's really the best of serverless is you know that micro billing and invisible infrastructure. >> Well that's built in isn't it? >> Correct yeah. >> What are the biggest challenges of serverless because first of all its [Inaudible 00:03:58] in the mind of a developer who doesn't want to deal with plumbing. >> Yes. >> Meaning networking plumbing, storage, and a lot of the details around configurating, just program away, be creative, spend their time building. >> Yes. >> What is the big differences between that? What are the issues and challenges that service has for people adopting it or is it frictionless at this point? >> Well you know as far I mean it depends on what you're talking about right. So I think you know for functions you know it's very simple to you know get a function service and add your functions and deploy functions and start chaining those together and people are seeing rapid adoption and that's progressing nicely but there's also a contingent of folks who are represented here at the show who are really interested in containers as the primitive and not functions right. Containers are inclusive of lots of things, functions being one of them, betting on containers as like the compute artifact is actually a lot more flexible and solves a lot more use cases. So we're making sure that we can streamline ease of use for that while also bringing the benefits of serverless, really the way I think of this is marrying our AKS, our Managed Kubernetes Service with ACI, our you know serverless containers so you can get to a place where you can have a Kubernetes environment that has no VMs associated with it like literally zero VMs, you'd scale the thing down to zero and when you want to run a pod or container you just pay for a few seconds of time and then you kill it and you stop paying for it right. >> Alright so talk about customers. >> Yep. >> What's the customer experience you guys are going after, did you have any beta customers, who's adopting your approach, and can highlight some examples of some really cool and you don't have to name names or you can, anecdotal data will be good. >> Yeah well you know I think on the blog post announcement blog post page we have a really great video of Siemens Health and Years, I believe is the name, but basically a health care company that is looking, that is using Kubernetes on Azure, AKS specifically, to disrupt the health care market and to benefit real people and you know to me I think it's important that we remember that we're deep in this technology right but at the end of the day this is about helping developers who are in turn helping real world people and I think that video is a good example of that. >> An what was there impact, speed? Speed of developers? >> Yeah, I mean I think it's really the main thing is agility right, people want to move faster right and so that's the main benefit that we hear. I think cost is obviously a concern for folks but I think in practice the people cost of operating some of these systems is tends to be a lot higher than the infrastructure costs when you stack them up, so people are willing to pay a little bit of a premium to make it easier on people and we see that over and over again. >> Yeah Gabe, want you to speak to kind of the speed of company the size of Microsoft. So you know the Dais acquisition of course was already focused on Kubernetes before inside of Microsoft, see I mean big cloud companies moving really fast on Kubernetes. I've heard complaints from customers like "I can't get a good roadmap because it's moving so fast". >> You know I would say that was one of the biggest surprises for me joining Microsoft, is just how fast things move inside of Azure in particular. And I think it's terrific you know. I think that there's a really good focus of making sure that we're meeting customers where they are and building solutions that meet the market but also just executing and delivering and doing that with speed. One of the things that is most interesting to me is like the geographic spread. Microsoft is in so many different regions more than any other cloud. Compliance certification, we take to all that stuff really seriously and being able to do all those things, be the enterprise friendly cloud while also moving at this breakneck pace in terms of innovation, it's really spectacular to watch from the inside. >> A lot of people don't know that. When they think about Azure they think "oh they're copying Amazon" but Microsoft has tons of data centers. They've had browsers, they're all over the world, so it's not like they're foreign to region areas I mean they're everywhere. >> Microsoft is ever and not only is it not foreign but I mean you got to remember Microsoft is an enterprise software company at its core. We know developers, that is what we do and going into cloud in this way is just it's extremely natural for us. And I think that the same can't really be said for everyone who's trying to move into cloud. Like we've got history of working with developers, building platforms, we've entire division devoted to developer tooling right. >> I want to ask you about two things that comes up a lot, one is very trendy, one is kind of not so trendy but super important, one is AI. >> Yes. >> AI with software units impact disrupt storage and with virtual kubelets this is going to be changing storage game buts going to enhance the machine learning and AI capability. The other one is data warehousing or data analytics. Two very important trends, one is certainly a driver for growth and has a lot of sex appeal as the AI machine learning but all the analytics being done on cloud whether it's an IOT device, this is like a nice use case for containers and orchestration. Your comment and reaction for those two trends. >> Yeah and you know I think that AI and deep learning generally is something that we see driving a ton of demand for container orchestration. I've worked lots of customers including folks like OpenAI on there Kubernetes infrastructure running on a Azure today. Something that Elon Musk actually proudly mention, that was a good moment for the containers (chuckling) >> Get a free Tesla. Brokerage some Teslas and get that new one, goes from 0 to 100 and 4.5 seconds. >> Right yeah. >> So you got a good customer, OpenAI, what was the impact of them? What was the big? >> Well you know this is ultimately about empowering people, in this case they happen to be data scientists, to get their job done in a way where I mean I look at it has we're doing our jobs in the infrastructure space if the infrastructure disappears. The more conceptual overhead we're bringing to developers that means we're not doing our job. >> So question then specifically is deep learning in AI, is it enhanced by containers and Kubernetes? >> Absolutely. >> What order of magnitude? >> I don't know but in order of magnitude in enhancement I would argue. >> Just underlying that the really important piece is we're talking about data here >> Yes. >> and one of the things we've been kind of trying to tackle the last couple years of containers is you know storage and that's carried over to Kubernetes, how's Microsoft involved? What's you're you know prognosis as to where we go with cloud native storage? >> Yeah that's a fascinating question and I actually, so back in the early days when I was still contributing to Docker, I was one of the largest external contributors to the Docker Project earlier in my career. I actually wrote some of the storage stuff and so I've been going around Dockers inception 2013 saying don't run databases in containers. It's not cause you can't, right, you can, but just because you can doesn't mean you should (chuckling) >> Exactly. >> and I think that you know as somebody who has worked in my career as on the operation side things like an SLA mean a lot and so this leads me to another one of our announcements at the show which is the Open Service Broker for Azure. Now what we've done, thanks to the Cloud Foundry Foundation who basically took the service broker concept and spun it out, we now are able to take the world of Kubernetes and bridge it to the world of Azure services, data services being sort of some of the most interesting. Now the demo that I like to show this is WordPress which by the way sounds silly but WordPress powers tons of the web today still. WordPress is a PHP application and a MySQL database. Well if you're going to run WordPress at scale you're going to want to run that MySQL in a container? Probably not, you're probably going to want to use something like Azure database for MySQL which comes with an SLA, backup/restore, DR, ops team by Microsoft to manage the whole thing right. So but then the question is well I want to use Kubernetes right so how do I do that right, well with the Open Service Broker for Azure we actually shipped a helm chart. We can helm install Azure WordPress and it will install in Kubernetes the same way you would a container based system and behind the scenes it uses the broker to go spin up a Postgres, sorry a MySQL and dynamically attach it. Now the coolest thing to me about this yeah is the agility but I think that one of the underrated features is the security. The developer who does that doesn't ever touch credentials, the passwords are automatically generated and automatically injected into the application so you get to do things with rotations without ever touching the app. >> So we're at publisher we use WordPress, we'd love, will this help us with scale if we did Azure? >> Absolutely. After this is over we'll go set it up. (laughing) >> I love WordPress but when it breaks down well this is the whole point of where auto scaling shows a little bit of its capabilities in the world is that, PHP does you'd like to have more instances >> Yeah. >> that would be a use case. Okay Redshift in Amazon wasn't talking about much at re:Invent last week. We don't hear a lot of talk around the data warehouse which is a super important way to think about collecting data in cloud and is that going to be an enhanced feature because people want to do analytics. There's a huge analytics audience out there, they're moving off of tera-data. They're doing you guys have a lot of analytics at Microsoft. They might have moved from Hadoop or Hive or somewhere else so there's a lot of analytics workloads that would be prime or at least potentially prime for Kubernetes. >> Yeah I think >> Or is that not fully integrated. >> No I think it's interesting, I mean for us we look at, I personally think using something like the service broker, Open Service Broker API to bridge to something like a data lake or some of these other Azure hosted services is probably the better way of doing that because if you're going to run it on containers, these massive data warehouses, yes you can do it, but the operational burden is high, >> So your point about the >> its really high. >> database earlier. >> Yeah. Same general point there. Now can you do it? Do we see people doing it? Absolutely right. >> Yeah, they do you things sometimes that they shouldn't be doing. >> Yeah and of course back to the deep learning example those are typically big large training models that have similar characteristics. >> Alright as a newbie inside Azure, not new to the industry and the community, >> Yep. >> share some color. What's it like in there? Obviously a number two to Amazon, you guys have great geography presence, you're adding more and more services every day at Azure, what's the vibe, what's the mojo like over there, and share some inside baseball. >> Yeah I got to say so really I'm just saying it's a really exciting place to work. Things are moving so fast, we're growing so fast, customers really want what we're building. Honestly day to day I'm not spending a lot of time looking out I'm spending a lot of time dealing with enterprises who want to use our cloud products. >> And one of the top things that you have on your p.m. list that are the top stack ranked features people want? >> I think a lot of this comes down, in general I think this whole space is approaching a level of enterprise friendliness and enterprise hardening where we want to start adding governance, and adding security, and adding role based access controls across the board and really making this palatable to high trust environment. So I think a lot that's a lot of our focus. >> Stability, ease of use. >> Stability, ease of use are always there. I think the enterprise hardening and things like v-net support for all of our services, v-net service endpoints, those are some things that are high on the list. >> Gabe Monroy, lead product manager for containers at Microsoft Azure Cloud. Great to have you on and love to talk more about geographies and moving apps around the network and multi-cloud but another time, thanks for the time. >> Another time. >> It's the Cube live coverage I'm John Ferrier co-founder of [Inaudible 00:15:21]. Stu Miniman with Wikibon, back with more live coverage after this short break.

>> Announcer: Live from Austin, Texas, It's theCUBE, covering DockerCon 2017. Brought to you by Docker and support from its ecosystem partners. >> Welcome back to theCUBE here in Austin, Texas at DockerCon 2017. I'm Stu Miniman with my cohost for the two days of live broadcast, Jim Kobielus. Happy to welcome back to the program, John Gossman, who is the lead architect with Microsoft Azure. Also part of the keynote this morning. John, had the pleasure of interviewing you two years ago. We went though the obligatory wait, Microsoft Open Source, Linux, and Windows and everything living together. It's like cats and dogs. But thanks so much for joining us again. >> Yeah well as I was saying, that's 14 years in cloud years. So it's been a lot of change in that time, but thanks for having me again. >> Yeah. Absolutely. You said it was three years that you've been working Microsoft and Docker together. 21 years in it, dog or cloud years, if you will. I think Docker is more whales and turtles, as opposed to the dogs. But enough about the cartoons and the animals. Why don't you give our audience just a synopsis of kind of the key messages you were trying to get across in the keynote this morning. >> Okay well the very simple message is that what we enabled this new technology, Hyper-V isolation for Linux containers, is the ability to run Linux containers just seamlessly on Windows using the normal Docker experience. It's just Docker run, BusyBox or Docker run, MySQL, or whatever it is, and it just works. And of course if you know a little more technical detail about containers, you realize that one of the reasons that the containers are the way there are is that all the containers on a box normally share a kernel. And so you can run a Canonical, Ubuntu on user space, on a Red Hat kernel or vice versa. But Windows and Linux kernels are too different. So if you want to run Windows container, it's not going to run easily on Linux and vice versa. And you can still get this effect, if you want it, by also using a virtual machine. But then you've got the management overhead of managing the virtual machine, managing the containers, all the complexity that that involves. You have to get a VHD or AMI or something like that, as well a container image and you lose a lot of that sort of experience. >> John, first of all, I have to say congratulations to Microsoft. When the announcement was made that Windows containers were going to be developed, I have to say that I and most of my peers were a little bit skeptical as to how fast that would work; the development cycle. Probably because we have lots of experience and it's always okay, we understand how many man years this usually takes, but you guys hit and were delivering, got through the Betas, so can you speak to us about where we are with Windows containers? And one of the things people want to kind of understand is, compared to like Linux containers, how do you expect the adoption of that now that it's generally available to roll out? Do I have to wait for the next server refresh, OS refresh, how do you expect your customers to adopt and embrace? >> Well we were able to get this to work so quickly because if you remember, Docker didn't actually invent containers. They took a bunch of kernel primitives that were in Linux and put a really great user experience on it. And I'm not taking anything away from Docker by doing that, because oftentimes in the technology industry, it's easy to make something that was complicated, powerful, but not easy to use. And Windows already had a lot of those kernel primitives, same sort of similar kind of kernel primitives built-in. They had to take out Java javax, I think when Windows 2000. And so it was kind of the same experience. We took the Docker engine, so we got the API, we were using the open source project, so we have complete compatibility. And then we just had to write a basically a new back-end, and that's why it was able to come up rather quickly. And now we're in a mode you know, Windows server updates things more incrementally, than we did in the past. So this will just keep on improving as time goes on. >> Okay, one of the other big announcements in the keynote this morning was LinuxKit. And it was open source project, we actually saw Solomon move it to open source during the keynote, when they laid out the ecosystems for it like IBM, HPE, INTEL and Microsoft. So what does that mean for Microsoft? You are now a provider of Linux? How are we supposed to look at this? >> Yeah. So we're working with all the Linux vendors. So if you saw our blog about the work we did today. We also have announcements from SUSE and Red Hat and Canonical, and the usual people. And one of the things I said in this box, I said look there's the new model is that you could choose both the Linux container that you want and the kernel that you want to run it on. And we're open to all sorts of things. But we have been working with Docker for a long time. On making sure that there was a great experience for running Docker for Linux on Windows. This thing called Docker for Windows. Which they developed. And we have been helping out. And that's basically an earlier generation of this same Linux technology. So it's just the next step on that journey. >> Microsoft's pretty well recognized to have a robust solution for a hybrid cloud. Cause of course you go your Azure stack, that you're putting on premises. There's Azure itself, it's really the cloud first methodology that you've been rolling through and you offer as a service. Containers really anywhere in your environment, baked in anywhere? How should we be thinking about this going forward? >> Yeah absolutely. I mean one of the points of containers in general, one of the attractive parts of containers is that they run everywhere. Including from your laptop, to the various clouds to bare metal, to virtualized environments. And so we have both things. We want Windows containers, where we're the vendor of the container. We want those to work everywhere. And we also, as the vendors of Azure and Azure Stack, and just server system center, and other older enterprise technologies. We want containers to work on all those things. So both directions. I mean, that's kind of the world we're in now, where everything works everywhere. >> Can you square you container strategy as reflected in your partnership with Docker, With your serverless computer strategy for Azure Functions? I'm trying to get a sense for Microsoft's overall approach to running containers as it relates to the Azure strategy. >> In some ways, you can think of this as a serverless functions mode as a step even further. You just deploy a hardware machine and install everything on it. Next thing, you'd have a virtual machine and you install everything. And then you put your code and all its affinities to the container. And with serverless with Azure Functions, it's like, well why do any of that? Just write a function. Now at the same time, we think there's lots of reasons. Under the covers, all of these past systems, going all the way back, that's how Docker started. Run a container underneath the covers. in the same place, it's not literally a Docker container, but the same place down in functions has that sort of a capability. And we're certainly thinking about how Docker can handle for work in that serverless model in the future. >> See one of my core focus areas for Wikibon as an analyst, is looking at developers going more deeply into deep learning and machine learning. To what extent is Microsoft already taking its core tools in that area and containerizing them and enabling access to that functionality through serverless APIs and functions and so forth in Azure? On the serverless stuff, I'm not on the serverless team. I'm not really qualified to explain everything on their end. I do know that the CNT team has a Docker container that they put the bits in. There's the Azure Machine Learning team who's been working a lot of these sort of technologies. I'm just not the right guy to answer that question. >> As you talk to your customers, where does this fit in to the whole discussion? Do containers just happen in the background? Is it helping them with some of their application modernization? Does it help Microsoft change the way we architect things? What's kind of the practitioner, your ultimate end user viewpoint on this? Well cloud adoption is at all points on the curve simultaneously. Even the inside of individual companies. So everybody's in it, in a kind of different place. The two models that I think people have really concentrated on, is on one end, the path at least is infrastructure where you just bring your existing applications and another one would be PADS, where you rewrite the application for a more modern architecture, more cloud centric architecture. And containers fit kind of squarely in the middle of that in some respects. Because in many ways and primarily, I see Docker containers as a better form of infrastructure. It is an easier, more portable way to get all your dependency together and run them everywhere. So a lot of lift-and-shift works is in there, but once you're in containers, it is also easier to break the components apart and put them back together into a more microservice oriented cloud-native model. >> I think that's a great point because we've been having this discussion about okay, there's applications that I'm rewriting, but then I've got this huge amount of applications that I need some way to have the bridge to the future, if you will. Because I don't know, there's one analyst firm that calls it bimodal, but to customers we talked to in general, we don't segment everything we do. I have application type infrastructure and I need to be able to live across multiple environments. Wrapping versus refactoring. >> And they do both. But I always prefer to, you know some people come in and they talk about legacy and they're developers. I'm a developer, right? Developers we always want to rewrite everything. And there's a time and place to doing that. But the legacy applications are required for those applications to work. And if you don't need to refactor that thing, if you can get it into a container or virtual machine or however, and get it into that more environment, and then work around it, re-architect it, it's a whole different set of approaches. It's a good conversation to have with a customer to understand. I've seen people go both too slow, and I see people refactor their whole thing and then try to figure out how to get it to work again. >> So Microsoft has a gigantic user base, What kind of things are you doing to help educate and help the people that had certification or jobs were running exchange to move towards this new kind of world and cloud in general. And containers specifically maybe. >> Well we have a ton of stuff. I'm not familiar with the certification programs myself, but we certainly have our Developer Evangelism team, out going out training people. We've been trying to improve our documentation. And we have a bunch of guidance on cloud migration and things like that. There is a real challenge and it's the same problem for our customers and anybody looking at cloud. Is to re-educate people who have been working in some of their previous moment. Which is another reason again, where the lift and shift stuff is, you can make it more like it is on Premise, or more like it is on your laptop. It makes that journey a little easier. But we're indefinitely in one of those points where the industry is changing so fast, I personally have to spend a lot of time, What's going on? What happened this day? What's new today coming to the conference, I learn new things. >> You bring up a huge challenge that we see. I kind of like Docker has their two delivery models. They've got the Community Edition, CE, and the Enterprise Edition, EE. An EE feels more like traditional software. It's packaged, it's on the regular release cycle. CE is, Solomon talked this morning about the edge pieces. Can I keep up with every six months, or can I have stuff flying at me? People inside of Docker can't keep up with the pace of change that much. What do you see, I mean, I think back to the major Windows operating system releases that we used to, like the Intel tick-tock on releases. It's the pace of change is tough for everyone, how are you helping, you know with you product development and customers, you know, take advantage of things and try to keep up with this rapidly changing ecosystem? >> This is a constant challenge with physically software now. We can't afford to only ever ship things every three years. And at the same time there's stability. So with the major products like Windows, we have these stable branches, where things are pretty much the same going along. And then there's an inactive branch Where things are coming down and the changes and the updates are coming. I'd say the one biggest difference I'd say, but you know I've been in this industry for a long time. So say between the '90s and now, is that we have so much of it is actually off servers. Where when something crashes, we get a crash dump and we can debug the thing and so going out in the field we have much more capability in finding what's going on in the customer base than we did 20 years ago. But other than that, it's just a really hard challenge to both satisfy people that can't have anything to change, and everything changing. >> John you've been watching this for a number of years, what do we still have left to do? We come back to DockerCon next year, you know, we'll have more people, it'll be a bigger event, but you know, what's the progression, what kind of things are you looking forward to the ecosystem and yourself and Docker, knocking down and moving customers forward with? >> The first year was kind of like, what is this thing? Second year was now, the individual Docker container is there now how do you orchestrate them and next step is how do we network these things. And there's an initiative now to standardize on storage, for storage systems and docker containers. Monitoring. There's a lot of things that are still to do. We have a long ways to go. On the other side, I think this other track, which we talked about today, which is that virtualization and containers are going to blur and mend, and I don't think that seven years from now we're going to be talking about containers or virtual machines, we're just going to be saying it's some unit of compute and then there's so much in knobs and tweaks that you want it a little more isolated, you want it a little less isolated, you trade off some performance for something else. >> Business capability, in other words the enterprise architecture framework of business capabilities, will be paramount in terms of composing applications or microservices. From what I understand you saying. >> Yeah, I think where we're really going to get to is a model where people we get past this basics of storage of networking and start working up the next level So things like Helm or DCS Universe, or Storm Stacks, where you can describe more of an application, it just keeps moving up. And so I think in seven years, we won't be talking so much about this, it'll some other disruption, right? But there won't be talking about this virtualization layer as much as building apps again. >> On a visual composition of microservices, what is Microsoft doing, you say that you long ago entered Microsoft during the Vizio acquisition, what's Microsoft doing to enable more visual composition across these functions, across orchestrated team-like environments going forward? >> I think there is some work going on. It's not my area again, on visual composition, despite the fact that I came from Vizio. I kind of got away from that space >> Well I'm betraying my age. I remember that period. >> All right. Well John, always a pleasure catching up with you and thank you so much for joining us for this segment. Look forward to watching Microsoft going forward. >> Thanks. Thank you for having me. We'll be back with lots more coverage here from DockerCon 2017. You're watching theCUBE.

>> Narrator: Live from Las Vegas, Nevada, it's theCUBE covering Accelerate 2017 brought to you by Fortinett. Now, here are your hosts, Lisa Martin and Peter Burris. >> Hi, welcome back to theCUBE. We are SiliconANGLE's flagship program where we go out to the events and extract the signal from the noise. Today, we are with Fortinet at their 2017 Accelerate event in Las Vegas. I'm your host, Lisa Martin, and I'm joined by my cohost, Peter Burris. We are fortunate right now to be joined by George Moore. George is the technology, excuse me, the CSO for Microsoft Azure who is a big technology alliance partner for Fortinet. George, welcome to theCUBE. >> Nice to have you, thank you. >> We are excited to have you on. You are, as you mentioned, the CSO at Azure, but you are the CSO for all of the Azure computer services. You are one of the founders of the Azure engineering team from back in 2006, and we were talking off-line. You hold over 40 patents in things like security deployment, interactive design, et cetera. You are a busy guy. >> I am, yes. (laughing) >> One of the things we have been talking about with our guests on the show today, and a great topic that was in the general session was about the value of data, and how do businesses transform to digital businesses. The value in that data has to be critical. I'd love to get your take on as businesses have to leverage that data to become more successful or to become successful as digital businesses, we know the security of the perimeter is not the only thing. It needs to be with the data. What is Azure doing to secure the cloud for your customers, and how do you help them mitigate or deal with the proliferation of mobile devices and IOT devices that they have that are connecting to their networks? >> Digital disruption is affecting everybody, and it is a huge thing that many companies are struggling to understand and to adopt to their business models, and to really leverage what digital can do for them, and certainly we are doing in the public cloud with Azure helps that significantly. As you mentioned, there is just a proliferation of devices, a proliferation of data, so how do you have defense in depth so you don't have perimeter-based security, but you actually have defense in depth at every level, and at its heart, it really falls down to how do you do encryption at rest, how do you secure the data encrypted? Who holds the keys for the data? What is the proliferation of the keys? How did the controls manage for that? Of course, of the data is encrypted, you really want to be able to do things upon it. You want to be able computer over it. You want to be able to queries, analytics, everything, so there's the question of how to securely exchange the keys? How do you make sure that the right virtual machines are running, the right computers running at the time to do the queries? That's the set of controls and security models and services that we provide in Azure that makes it super easy for customers to actually use that. >> Azure represent what's called the second big transformation for Microsoft where the first one might have been associated with Explorer, those amazing things that Microsoft did to transform itself in the 1990s and it seems to be going pretty well. How is security facilitating this transformation from a customer value proposition? >> Security is absolutely the number one question that every customer has whenever they start talking about the cloud, and so we take that very, very seriously. Microsoft spends over billion dollars a year on all of our security products all up. We have literally armies of people who do nothing every day but wake up and make sure that the product is secure, and that really boils down to two big pieces. One is how do we keep the platform secure from the security control that we have ourselves in the compliance ADA stations and everything to make sure that when customers bring their workloads to us, they are in fact kept secure. Second is a set of security controls that we provide the customers so they can actually secure their workloads, integrate their security models with whatever they're running on premise, and have the right security models, ADA stations, multifactor authentication, identity controls, et cetera for their own workloads. >> Security is very context specific. I'm not necessarily getting into a conversation about industry or whatnot, but in terms of the classifications of services that need to be provided, we were talking a little bit about how some of the services that you provide end being part of the architecture for other services within the Azure cloud. Talk a little bit about how you envision security over time evolving as a way of thinking about how different elements of the cloud are going to be integrated and come together in the role that security is going to play in making that possible and easy. >> You are absolutely right. Azure is composed of, right now, 80 some-odd different services and there's definitely a layering where for example, my components around the compute pieces are used by the higher order of services around HD insight and some of the analytic services and such, and so the security models we have in place internally for compute in turn are used by those higher order services, and the real value we can provide is having a common customer-facing security model for customers, so there is a common way by which they can access the control plane, do management operations upon these services, how they can access the endpoints of the services using a common identity model, a common security model, role-based access control, again, from a common perspective, logging, auditing, reporting, so all this has to be cohesive, correct, and unified so that customers aren't facing this tumultuous array of different services that speak different languages, so to speak. >> We are here at Fortinet Accelerate 2017. Tell us how long Microsoft Azure and Fortinet have been working together, and what are you most excited about with some of the announcements from Fortinet today? >> Microsoft and Fortinet partnership has been going on for quite some time. Specifically in Azure space we've been doing two different, two major thrusts around integration with the Azure Security Center which is a set of services that we have within Azure that provides turnkey access to many, many different vendors including Fortinet as one of our primary partners, and Fortinet also has all their products in Azure marketplace so that customers can readily in a turnkey manner use Fortinet next generation firewalls and such as virtual machines, incorporate those directly within their workloads, and have a very seamless billing model, a very seamless partnership model, a very seamless go-to-market strategy for how we jointly promote, jointly provide the services. >> One of the things that one of our guests was talking with us about today was really about it's an easy sell, if you will, at the C-level to sell the value of investing in the right infrastructure to secure environments. Looking at that in correlation to the fact that there's always historically been a challenge or concerned with security when it comes to enterprises moving workloads to the cloud, I'm curious about this easy-sell position that cyber security and the rise of attacks brings to seeing the adoption of more enterprise workloads. We are seeing numbers that are going to show, or predicting that north of 85% of enterprise workloads will be in the cloud by 2020. How much is Microsoft Azure seeing the fact that cyber security attacks are becoming more and more common, hitting some pretty big targets, affecting a lot of big names. How much are using that as an impetus to and maybe drive that adoption higher and higher from an enterprise perspective? >> Absolutely, I see that everyday. I give many, many talks to the C-level, to CSOs, CEOs, et cetera, and I can say in many industries like the banking industry, financial sector, 18 months ago banks did not have any interest in public cloud. Is just like, "Thank you, we have no interest in cloud," but recently there has been the dawning realization that Azure and the public cloud products are in fact, in many cases, more secure than what the banks and other financial industry sectors can actually provide themselves because we are providing huge amounts of investments from an ongoing basis that we can actually provide better security, better integrated security than what they can afford on premise, so as a result, we are seeing this now, literally, stampede of customers coming to us and saying, "Okay, I get it. "You can actually have a very, very "highly secure environment. "You can provide security controls "that can go well above and beyond "whatever I could do on premise, "and it's better integrated "than what I could ever pull together on premise." >> One of the reasons for that is because of the challenge of finding talent, and you guys can find a really talented person, bring them in, and that person can build security architectures for your cloud that then can be served, can be used by a lot of different customers, so what will be the role of or how will this need for talent in the future, what would be the role for how people engage your people, client's people engage your people to ensure that that people side and moves forward, and how do you keep scaling that is you scale the cloud? >> Certainly people are always the bottleneck in virtually every industry, and specifically within the computing space. The value that we are seeing from customers is that the people that they had previously on premise who were working to secure the base level common infrastructure are now freed because they don't have to do that work. They can do other interesting things at the application level and move their value added further up the stack which means I can innovate more rapidly, they can add more features more quickly, because they are not having to worry about the lower-level infrastructure pieces that are secured by Azure, so we are seeing the dawning realization that we are moving to this new golden age where there is higher degree of agility with respect to innovation happening at the application level, because remember, applications have to be, if you are having a compliant workload, if you are having PCI compliance within the credit card industry for example, you have to have the entire application and its infrastructure part of the compliance boundary, so that means when you are building that app, you have to give your auditors the complete stack for them to pass that. If you are only having to worry about this much as opposed to that much, then the amount of work that you can do, the amount of integration, the amount agility, the amount of innovation you can do at that level is many orders of magnitude higher, so you really see that the value that a lot of customers are having here is that their talented people can be put to use on more important higher order business-related problems as opposed to lower-level infrastructure level issues. >> Let's talk about that for second because one of the things that we see within our research is that the era of cloud as renting virtual machines is starting to transition as people start renting applications, or applications as services that they themselves can start putting together. Partly the reason why that's exciting is because it will liberate more developers. It brings more developers into the process of creating value in the cloud, but as they do that, they now have visibility, or they are going to be doing things that touch an enormous set of resources, so how do you make security easier to developers in Azure? >> The key is that we can do high degrees of integration at the low level between these very services. >> Peter: It goes back to that issue of a cascading of your stuff up into the other Azure services. >> Absolutely, I mean think about it, we sat on top a mountain of information. We have analytics and log files that know about virtually everything that's happening in the cloud, and we can have machine learning, we can have intelligence, we can have machine intelligence and such, that can extract signals from noise that would otherwise be impossible to discover from a single customer's perspective. If you have a low and slow attack by some sort of persistent individual, the fact that they are trying the slow and low attack means that we are able to pull that signal out and extract that information that would not be really physically possible, or economically possible for most companies to do on premise. >> Does this get embedded to some of the toolkits that we are going to use to build these next-generation cloud-based apps? >> It gets embedded into the toolkits, but it also gets embedded at the set of services like the Azure Security Center. A single pane of glass that's integrated with the products from Fortinet and others where the customer can go and have a single view across all their work was running within Azure and get comprehensive alerts and understanding about the analytics that we are able to pull out and provide to those customers. >> What's next? >> Security is an ever evolving field, and the bad guys are always trying new things, so the work that is really happening, a lot of the innovation that's happening is within the analytics, machine learning space around being able to pull more log files out, being able to refine the algorithms and basically being able to provide more AI to the logs themselves so that we can provide integrated alerts, like for example, if you have a kill chain of an individual coming in attacking one of your product, and then using that to the lateral mobility to other products, or other services within your product, we can pull this together in a common log. We can show to customers here's the sequence of this one individual that across three, or four, or five different services. You have top level disability, and we can give you then guidance to say if you insert separation of duties between these two individuals, then you could've broken that kill chain. We can do proactive guidance to customers to help them secure their own workloads even if they necessarily initially were not deployed in a necessarily most secure manner. >> George, we just have a couple of minutes left, but I'd like to get your perspective. You showed a tremendous amount of the accomplishments that Azure has made in public cloud and in security. What are the opportunities for partners to sell and resell Azure services? >> Absolutely. Microsoft has historically always worked incredibly well with partners. We have a very large partner ecosystem. >> Peter: It's the biggest. >> Is the biggest, exactly. Okay, I don't want to brag too much, yes. (laughing) >> That's what I'm here for, George. >> We see specifically in the security space that partners are increasingly, around 40% of their revenue increasingly is coming from cloud-based assets, cloud-based sales. We are setting up the necessary partner channels and partner models where we can make sure that the reseller channels and our partners are an integral part of our environment, and they can get the necessary revenue shares, and we can give them the leads on how the whole system evolves. Absolutely we believe that partners are first and foremost to our success, and we are making deep, deep, deep investments in the partner programs to make that possible. >> Well George, we wish you and Microsoft Azure continued success as well as your partnership with Fortinet. We thank you so much for taking the time to join us on theCUBE today. >> Thank you. >> And for my cohost, Peter Burris, I'm Lisa Martin. Stick around, we will be right back on theCUBE.

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Spark became a top level Apache project in 2014, and then shortly thereafter, burst onto the big data scene. Spark, along with the cloud, transformed and in many ways, disrupted the big data market. Databricks optimized its tech stack for Spark and took advantage of the cloud to really cleverly deliver a managed service that has become a leading AI and data platform among data scientists and data engineers. However, emerging customer data requirements are shifting into a direction that will cause modern data platform players generally and Databricks, specifically, we think, to make some key directional decisions and perhaps even reinvent themselves. Hello and welcome to this week's wikibon theCUBE Insights, powered by ETR. In this Breaking Analysis, we're going to do a deep dive into Databricks. We'll explore its current impressive market momentum. We're going to use some ETR survey data to show that, and then we'll lay out how customer data requirements are changing and what the ideal data platform will look like in the midterm future. We'll then evaluate core elements of the Databricks portfolio against that vision, and then we'll close with some strategic decisions that we think the company faces. And to do so, we welcome in our good friend, George Gilbert, former equities analyst, market analyst, and current Principal at TechAlpha Partners. George, good to see you. Thanks for coming on. >> Good to see you, Dave. >> All right, let me set this up. We're going to start by taking a look at where Databricks sits in the market in terms of how customers perceive the company and what it's momentum looks like. And this chart that we're showing here is data from ETS, the emerging technology survey of private companies. The N is 1,421. What we did is we cut the data on three sectors, analytics, database-data warehouse, and AI/ML. The vertical axis is a measure of customer sentiment, which evaluates an IT decision maker's awareness of the firm and the likelihood of engaging and/or purchase intent. The horizontal axis shows mindshare in the dataset, and we've highlighted Databricks, which has been a consistent high performer in this survey over the last several quarters. And as we, by the way, just as aside as we previously reported, OpenAI, which burst onto the scene this past quarter, leads all names, but Databricks is still prominent. You can see that the ETR shows some open source tools for reference, but as far as firms go, Databricks is very impressively positioned. Now, let's see how they stack up to some mainstream cohorts in the data space, against some bigger companies and sometimes public companies. This chart shows net score on the vertical axis, which is a measure of spending momentum and pervasiveness in the data set is on the horizontal axis. You can see that chart insert in the upper right, that informs how the dots are plotted, and net score against shared N. And that red dotted line at 40% indicates a highly elevated net score, anything above that we think is really, really impressive. And here we're just comparing Databricks with Snowflake, Cloudera, and Oracle. And that squiggly line leading to Databricks shows their path since 2021 by quarter. And you can see it's performing extremely well, maintaining an elevated net score and net range. Now it's comparable in the vertical axis to Snowflake, and it consistently is moving to the right and gaining share. Now, why did we choose to show Cloudera and Oracle? The reason is that Cloudera got the whole big data era started and was disrupted by Spark. And of course the cloud, Spark and Databricks and Oracle in many ways, was the target of early big data players like Cloudera. Take a listen to Cloudera CEO at the time, Mike Olson. This is back in 2010, first year of theCUBE, play the clip. >> Look, back in the day, if you had a data problem, if you needed to run business analytics, you wrote the biggest check you could to Sun Microsystems, and you bought a great big, single box, central server, and any money that was left over, you handed to Oracle for a database licenses and you installed that database on that box, and that was where you went for data. That was your temple of information. >> Okay? So Mike Olson implied that monolithic model was too expensive and inflexible, and Cloudera set out to fix that. But the best laid plans, as they say, George, what do you make of the data that we just shared? >> So where Databricks has really come up out of sort of Cloudera's tailpipe was they took big data processing, made it coherent, made it a managed service so it could run in the cloud. So it relieved customers of the operational burden. Where they're really strong and where their traditional meat and potatoes or bread and butter is the predictive and prescriptive analytics that building and training and serving machine learning models. They've tried to move into traditional business intelligence, the more traditional descriptive and diagnostic analytics, but they're less mature there. So what that means is, the reason you see Databricks and Snowflake kind of side by side is there are many, many accounts that have both Snowflake for business intelligence, Databricks for AI machine learning, where Snowflake, I'm sorry, where Databricks also did really well was in core data engineering, refining the data, the old ETL process, which kind of turned into ELT, where you loaded into the analytic repository in raw form and refine it. And so people have really used both, and each is trying to get into the other. >> Yeah, absolutely. We've reported on this quite a bit. Snowflake, kind of moving into the domain of Databricks and vice versa. And the last bit of ETR evidence that we want to share in terms of the company's momentum comes from ETR's Round Tables. They're run by Erik Bradley, and now former Gartner analyst and George, your colleague back at Gartner, Daren Brabham. And what we're going to show here is some direct quotes of IT pros in those Round Tables. There's a data science head and a CIO as well. Just make a few call outs here, we won't spend too much time on it, but starting at the top, like all of us, we can't talk about Databricks without mentioning Snowflake. Those two get us excited. Second comment zeros in on the flexibility and the robustness of Databricks from a data warehouse perspective. And then the last point is, despite competition from cloud players, Databricks has reinvented itself a couple of times over the year. And George, we're going to lay out today a scenario that perhaps calls for Databricks to do that once again. >> Their big opportunity and their big challenge for every tech company, it's managing a technology transition. The transition that we're talking about is something that's been bubbling up, but it's really epical. First time in 60 years, we're moving from an application-centric view of the world to a data-centric view, because decisions are becoming more important than automating processes. So let me let you sort of develop. >> Yeah, so let's talk about that here. We going to put up some bullets on precisely that point and the changing sort of customer environment. So you got IT stacks are shifting is George just said, from application centric silos to data centric stacks where the priority is shifting from automating processes to automating decision. You know how look at RPA and there's still a lot of automation going on, but from the focus of that application centricity and the data locked into those apps, that's changing. Data has historically been on the outskirts in silos, but organizations, you think of Amazon, think Uber, Airbnb, they're putting data at the core, and logic is increasingly being embedded in the data instead of the reverse. In other words, today, the data's locked inside the app, which is why you need to extract that data is sticking it to a data warehouse. The point, George, is we're putting forth this new vision for how data is going to be used. And you've used this Uber example to underscore the future state. Please explain? >> Okay, so this is hopefully an example everyone can relate to. The idea is first, you're automating things that are happening in the real world and decisions that make those things happen autonomously without humans in the loop all the time. So to use the Uber example on your phone, you call a car, you call a driver. Automatically, the Uber app then looks at what drivers are in the vicinity, what drivers are free, matches one, calculates an ETA to you, calculates a price, calculates an ETA to your destination, and then directs the driver once they're there. The point of this is that that cannot happen in an application-centric world very easily because all these little apps, the drivers, the riders, the routes, the fares, those call on data locked up in many different apps, but they have to sit on a layer that makes it all coherent. >> But George, so if Uber's doing this, doesn't this tech already exist? Isn't there a tech platform that does this already? >> Yes, and the mission of the entire tech industry is to build services that make it possible to compose and operate similar platforms and tools, but with the skills of mainstream developers in mainstream corporations, not the rocket scientists at Uber and Amazon. >> Okay, so we're talking about horizontally scaling across the industry, and actually giving a lot more organizations access to this technology. So by way of review, let's summarize the trend that's going on today in terms of the modern data stack that is propelling the likes of Databricks and Snowflake, which we just showed you in the ETR data and is really is a tailwind form. So the trend is toward this common repository for analytic data, that could be multiple virtual data warehouses inside of Snowflake, but you're in that Snowflake environment or Lakehouses from Databricks or multiple data lakes. And we've talked about what JP Morgan Chase is doing with the data mesh and gluing data lakes together, you've got various public clouds playing in this game, and then the data is annotated to have a common meaning. In other words, there's a semantic layer that enables applications to talk to the data elements and know that they have common and coherent meaning. So George, the good news is this approach is more effective than the legacy monolithic models that Mike Olson was talking about, so what's the problem with this in your view? >> So today's data platforms added immense value 'cause they connected the data that was previously locked up in these monolithic apps or on all these different microservices, and that supported traditional BI and AI/ML use cases. But now if we want to build apps like Uber or Amazon.com, where they've got essentially an autonomously running supply chain and e-commerce app where humans only care and feed it. But the thing is figuring out what to buy, when to buy, where to deploy it, when to ship it. We needed a semantic layer on top of the data. So that, as you were saying, the data that's coming from all those apps, the different apps that's integrated, not just connected, but it means the same. And the issue is whenever you add a new layer to a stack to support new applications, there are implications for the already existing layers, like can they support the new layer and its use cases? So for instance, if you add a semantic layer that embeds app logic with the data rather than vice versa, which we been talking about and that's been the case for 60 years, then the new data layer faces challenges that the way you manage that data, the way you analyze that data, is not supported by today's tools. >> Okay, so actually Alex, bring me up that last slide if you would, I mean, you're basically saying at the bottom here, today's repositories don't really do joins at scale. The future is you're talking about hundreds or thousands or millions of data connections, and today's systems, we're talking about, I don't know, 6, 8, 10 joins and that is the fundamental problem you're saying, is a new data error coming and existing systems won't be able to handle it? >> Yeah, one way of thinking about it is that even though we call them relational databases, when we actually want to do lots of joins or when we want to analyze data from lots of different tables, we created a whole new industry for analytic databases where you sort of mung the data together into fewer tables. So you didn't have to do as many joins because the joins are difficult and slow. And when you're going to arbitrarily join thousands, hundreds of thousands or across millions of elements, you need a new type of database. We have them, they're called graph databases, but to query them, you go back to the prerelational era in terms of their usability. >> Okay, so we're going to come back to that and talk about how you get around that problem. But let's first lay out what the ideal data platform of the future we think looks like. And again, we're going to come back to use this Uber example. In this graphic that George put together, awesome. We got three layers. The application layer is where the data products reside. The example here is drivers, rides, maps, routes, ETA, et cetera. The digital version of what we were talking about in the previous slide, people, places and things. The next layer is the data layer, that breaks down the silos and connects the data elements through semantics and everything is coherent. And then the bottom layers, the legacy operational systems feed that data layer. George, explain what's different here, the graph database element, you talk about the relational query capabilities, and why can't I just throw memory at solving this problem? >> Some of the graph databases do throw memory at the problem and maybe without naming names, some of them live entirely in memory. And what you're dealing with is a prerelational in-memory database system where you navigate between elements, and the issue with that is we've had SQL for 50 years, so we don't have to navigate, we can say what we want without how to get it. That's the core of the problem. >> Okay. So if I may, I just want to drill into this a little bit. So you're talking about the expressiveness of a graph. Alex, if you'd bring that back out, the fourth bullet, expressiveness of a graph database with the relational ease of query. Can you explain what you mean by that? >> Yeah, so graphs are great because when you can describe anything with a graph, that's why they're becoming so popular. Expressive means you can represent anything easily. They're conducive to, you might say, in a world where we now want like the metaverse, like with a 3D world, and I don't mean the Facebook metaverse, I mean like the business metaverse when we want to capture data about everything, but we want it in context, we want to build a set of digital twins that represent everything going on in the world. And Uber is a tiny example of that. Uber built a graph to represent all the drivers and riders and maps and routes. But what you need out of a database isn't just a way to store stuff and update stuff. You need to be able to ask questions of it, you need to be able to query it. And if you go back to prerelational days, you had to know how to find your way to the data. It's sort of like when you give directions to someone and they didn't have a GPS system and a mapping system, you had to give them turn by turn directions. Whereas when you have a GPS and a mapping system, which is like the relational thing, you just say where you want to go, and it spits out the turn by turn directions, which let's say, the car might follow or whoever you're directing would follow. But the point is, it's much easier in a relational database to say, "I just want to get these results. You figure out how to get it." The graph database, they have not taken over the world because in some ways, it's taking a 50 year leap backwards. >> Alright, got it. Okay. Let's take a look at how the current Databricks offerings map to that ideal state that we just laid out. So to do that, we put together this chart that looks at the key elements of the Databricks portfolio, the core capability, the weakness, and the threat that may loom. Start with the Delta Lake, that's the storage layer, which is great for files and tables. It's got true separation of compute and storage, I want you to double click on that George, as independent elements, but it's weaker for the type of low latency ingest that we see coming in the future. And some of the threats highlighted here. AWS could add transactional tables to S3, Iceberg adoption is picking up and could accelerate, that could disrupt Databricks. George, add some color here please? >> Okay, so this is the sort of a classic competitive forces where you want to look at, so what are customers demanding? What's competitive pressure? What are substitutes? Even what your suppliers might be pushing. Here, Delta Lake is at its core, a set of transactional tables that sit on an object store. So think of it in a database system, this is the storage engine. So since S3 has been getting stronger for 15 years, you could see a scenario where they add transactional tables. We have an open source alternative in Iceberg, which Snowflake and others support. But at the same time, Databricks has built an ecosystem out of tools, their own and others, that read and write to Delta tables, that's what makes the Delta Lake and ecosystem. So they have a catalog, the whole machine learning tool chain talks directly to the data here. That was their great advantage because in the past with Snowflake, you had to pull all the data out of the database before the machine learning tools could work with it, that was a major shortcoming. They fixed that. But the point here is that even before we get to the semantic layer, the core foundation is under threat. >> Yep. Got it. Okay. We got a lot of ground to cover. So we're going to take a look at the Spark Execution Engine next. Think of that as the refinery that runs really efficient batch processing. That's kind of what disrupted the DOOp in a large way, but it's not Python friendly and that's an issue because the data science and the data engineering crowd are moving in that direction, and/or they're using DBT. George, we had Tristan Handy on at Supercloud, really interesting discussion that you and I did. Explain why this is an issue for Databricks? >> So once the data lake was in place, what people did was they refined their data batch, and Spark has always had streaming support and it's gotten better. The underlying storage as we've talked about is an issue. But basically they took raw data, then they refined it into tables that were like customers and products and partners. And then they refined that again into what was like gold artifacts, which might be business intelligence metrics or dashboards, which were collections of metrics. But they were running it on the Spark Execution Engine, which it's a Java-based engine or it's running on a Java-based virtual machine, which means all the data scientists and the data engineers who want to work with Python are really working in sort of oil and water. Like if you get an error in Python, you can't tell whether the problems in Python or where it's in Spark. There's just an impedance mismatch between the two. And then at the same time, the whole world is now gravitating towards DBT because it's a very nice and simple way to compose these data processing pipelines, and people are using either SQL in DBT or Python in DBT, and that kind of is a substitute for doing it all in Spark. So it's under threat even before we get to that semantic layer, it so happens that DBT itself is becoming the authoring environment for the semantic layer with business intelligent metrics. But that's again, this is the second element that's under direct substitution and competitive threat. >> Okay, let's now move down to the third element, which is the Photon. Photon is Databricks' BI Lakehouse, which has integration with the Databricks tooling, which is very rich, it's newer. And it's also not well suited for high concurrency and low latency use cases, which we think are going to increasingly become the norm over time. George, the call out threat here is customers want to connect everything to a semantic layer. Explain your thinking here and why this is a potential threat to Databricks? >> Okay, so two issues here. What you were touching on, which is the high concurrency, low latency, when people are running like thousands of dashboards and data is streaming in, that's a problem because SQL data warehouse, the query engine, something like that matures over five to 10 years. It's one of these things, the joke that Andy Jassy makes just in general, he's really talking about Azure, but there's no compression algorithm for experience. The Snowflake guy started more than five years earlier, and for a bunch of reasons, that lead is not something that Databricks can shrink. They'll always be behind. So that's why Snowflake has transactional tables now and we can get into that in another show. But the key point is, so near term, it's struggling to keep up with the use cases that are core to business intelligence, which is highly concurrent, lots of users doing interactive query. But then when you get to a semantic layer, that's when you need to be able to query data that might have thousands or tens of thousands or hundreds of thousands of joins. And that's a SQL query engine, traditional SQL query engine is just not built for that. That's the core problem of traditional relational databases. >> Now this is a quick aside. We always talk about Snowflake and Databricks in sort of the same context. We're not necessarily saying that Snowflake is in a position to tackle all these problems. We'll deal with that separately. So we don't mean to imply that, but we're just sort of laying out some of the things that Snowflake or rather Databricks customers we think, need to be thinking about and having conversations with Databricks about and we hope to have them as well. We'll come back to that in terms of sort of strategic options. But finally, when come back to the table, we have Databricks' AI/ML Tool Chain, which has been an awesome capability for the data science crowd. It's comprehensive, it's a one-stop shop solution, but the kicker here is that it's optimized for supervised model building. And the concern is that foundational models like GPT could cannibalize the current Databricks tooling, but George, can't Databricks, like other software companies, integrate foundation model capabilities into its platform? >> Okay, so the sound bite answer to that is sure, IBM 3270 terminals could call out to a graphical user interface when they're running on the XT terminal, but they're not exactly good citizens in that world. The core issue is Databricks has this wonderful end-to-end tool chain for training, deploying, monitoring, running inference on supervised models. But the paradigm there is the customer builds and trains and deploys each model for each feature or application. In a world of foundation models which are pre-trained and unsupervised, the entire tool chain is different. So it's not like Databricks can junk everything they've done and start over with all their engineers. They have to keep maintaining what they've done in the old world, but they have to build something new that's optimized for the new world. It's a classic technology transition and their mentality appears to be, "Oh, we'll support the new stuff from our old stuff." Which is suboptimal, and as we'll talk about, their biggest patron and the company that put them on the map, Microsoft, really stopped working on their old stuff three years ago so that they could build a new tool chain optimized for this new world. >> Yeah, and so let's sort of close with what we think the options are and decisions that Databricks has for its future architecture. They're smart people. I mean we've had Ali Ghodsi on many times, super impressive. I think they've got to be keenly aware of the limitations, what's going on with foundation models. But at any rate, here in this chart, we lay out sort of three scenarios. One is re-architect the platform by incrementally adopting new technologies. And example might be to layer a graph query engine on top of its stack. They could license key technologies like graph database, they could get aggressive on M&A and buy-in, relational knowledge graphs, semantic technologies, vector database technologies. George, as David Floyer always says, "A lot of ways to skin a cat." We've seen companies like, even think about EMC maintained its relevance through M&A for many, many years. George, give us your thought on each of these strategic options? >> Okay, I find this question the most challenging 'cause remember, I used to be an equity research analyst. I worked for Frank Quattrone, we were one of the top tech shops in the banking industry, although this is 20 years ago. But the M&A team was the top team in the industry and everyone wanted them on their side. And I remember going to meetings with these CEOs, where Frank and the bankers would say, "You want us for your M&A work because we can do better." And they really could do better. But in software, it's not like with EMC in hardware because with hardware, it's easier to connect different boxes. With software, the whole point of a software company is to integrate and architect the components so they fit together and reinforce each other, and that makes M&A harder. You can do it, but it takes a long time to fit the pieces together. Let me give you examples. If they put a graph query engine, let's say something like TinkerPop, on top of, I don't even know if it's possible, but let's say they put it on top of Delta Lake, then you have this graph query engine talking to their storage layer, Delta Lake. But if you want to do analysis, you got to put the data in Photon, which is not really ideal for highly connected data. If you license a graph database, then most of your data is in the Delta Lake and how do you sync it with the graph database? If you do sync it, you've got data in two places, which kind of defeats the purpose of having a unified repository. I find this semantic layer option in number three actually more promising, because that's something that you can layer on top of the storage layer that you have already. You just have to figure out then how to have your query engines talk to that. What I'm trying to highlight is, it's easy as an analyst to say, "You can buy this company or license that technology." But the really hard work is making it all work together and that is where the challenge is. >> Yeah, and well look, I thank you for laying that out. We've seen it, certainly Microsoft and Oracle. I guess you might argue that well, Microsoft had a monopoly in its desktop software and was able to throw off cash for a decade plus while it's stock was going sideways. Oracle had won the database wars and had amazing margins and cash flow to be able to do that. Databricks isn't even gone public yet, but I want to close with some of the players to watch. Alex, if you'd bring that back up, number four here. AWS, we talked about some of their options with S3 and it's not just AWS, it's blob storage, object storage. Microsoft, as you sort of alluded to, was an early go-to market channel for Databricks. We didn't address that really. So maybe in the closing comments we can. Google obviously, Snowflake of course, we're going to dissect their options in future Breaking Analysis. Dbt labs, where do they fit? Bob Muglia's company, Relational.ai, why are these players to watch George, in your opinion? >> So everyone is trying to assemble and integrate the pieces that would make building data applications, data products easy. And the critical part isn't just assembling a bunch of pieces, which is traditionally what AWS did. It's a Unix ethos, which is we give you the tools, you put 'em together, 'cause you then have the maximum choice and maximum power. So what the hyperscalers are doing is they're taking their key value stores, in the case of ASW it's DynamoDB, in the case of Azure it's Cosmos DB, and each are putting a graph query engine on top of those. So they have a unified storage and graph database engine, like all the data would be collected in the key value store. Then you have a graph database, that's how they're going to be presenting a foundation for building these data apps. Dbt labs is putting a semantic layer on top of data lakes and data warehouses and as we'll talk about, I'm sure in the future, that makes it easier to swap out the underlying data platform or swap in new ones for specialized use cases. Snowflake, what they're doing, they're so strong in data management and with their transactional tables, what they're trying to do is take in the operational data that used to be in the province of many state stores like MongoDB and say, "If you manage that data with us, it'll be connected to your analytic data without having to send it through a pipeline." And that's hugely valuable. Relational.ai is the wildcard, 'cause what they're trying to do, it's almost like a holy grail where you're trying to take the expressiveness of connecting all your data in a graph but making it as easy to query as you've always had it in a SQL database or I should say, in a relational database. And if they do that, it's sort of like, it'll be as easy to program these data apps as a spreadsheet was compared to procedural languages, like BASIC or Pascal. That's the implications of Relational.ai. >> Yeah, and again, we talked before, why can't you just throw this all in memory? We're talking in that example of really getting down to differences in how you lay the data out on disk in really, new database architecture, correct? >> Yes. And that's why it's not clear that you could take a data lake or even a Snowflake and why you can't put a relational knowledge graph on those. You could potentially put a graph database, but it'll be compromised because to really do what Relational.ai has done, which is the ease of Relational on top of the power of graph, you actually need to change how you're storing your data on disk or even in memory. So you can't, in other words, it's not like, oh we can add graph support to Snowflake, 'cause if you did that, you'd have to change, or in your data lake, you'd have to change how the data is physically laid out. And then that would break all the tools that talk to that currently. >> What in your estimation, is the timeframe where this becomes critical for a Databricks and potentially Snowflake and others? I mentioned earlier midterm, are we talking three to five years here? Are we talking end of decade? What's your radar say? >> I think something surprising is going on that's going to sort of come up the tailpipe and take everyone by storm. All the hype around business intelligence metrics, which is what we used to put in our dashboards where bookings, billings, revenue, customer, those things, those were the key artifacts that used to live in definitions in your BI tools, and DBT has basically created a standard for defining those so they live in your data pipeline or they're defined in their data pipeline and executed in the data warehouse or data lake in a shared way, so that all tools can use them. This sounds like a digression, it's not. All this stuff about data mesh, data fabric, all that's going on is we need a semantic layer and the business intelligence metrics are defining common semantics for your data. And I think we're going to find by the end of this year, that metrics are how we annotate all our analytic data to start adding common semantics to it. And we're going to find this semantic layer, it's not three to five years off, it's going to be staring us in the face by the end of this year. >> Interesting. And of course SVB today was shut down. We're seeing serious tech headwinds, and oftentimes in these sort of downturns or flat turns, which feels like this could be going on for a while, we emerge with a lot of new players and a lot of new technology. George, we got to leave it there. Thank you to George Gilbert for excellent insights and input for today's episode. I want to thank Alex Myerson who's on production and manages the podcast, of course Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our EIC over at Siliconangle.com, he does some great editing. Remember all these episodes, they're available as podcasts. Wherever you listen, all you got to do is search Breaking Analysis Podcast, we publish each week on wikibon.com and siliconangle.com, or you can email me at David.Vellante@siliconangle.com, or DM me @DVellante. Comment on our LinkedIn post, and please do check out ETR.ai, great survey data, enterprise tech focus, phenomenal. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis.

(upbeat music) >> Welcome everyone to theCUBE's presentation of the AWS Startup Showcase AI/ML Top Startups Building Foundation Model Infrastructure. This is season three, episode one of our ongoing series covering exciting startups from the AWS ecosystem to talk about data and analytics. I'm your host, Lisa Martin and today we're excited to be joined by two guests from Astronomer. Steven Hillion joins us, it's Chief Data Officer and Jeff Fletcher, it's director of ML. They're here to talk about machine learning and data orchestration. Guys, thank you so much for joining us today. >> Thank you. >> It's great to be here. >> Before we get into machine learning let's give the audience an overview of Astronomer. Talk about what that is, Steven. Talk about what you mean by data orchestration. >> Yeah, let's start with Astronomer. We're the Airflow company basically. The commercial developer behind the open-source project, Apache Airflow. I don't know if you've heard of Airflow. It's sort of de-facto standard these days for orchestrating data pipelines, data engineering pipelines, and as we'll talk about later, machine learning pipelines. It's really is the de-facto standard. I think we're up to about 12 million downloads a month. That's actually as a open-source project. I think at this point it's more popular by some measures than Slack. Airflow was created by Airbnb some years ago to manage all of their data pipelines and manage all of their workflows and now it powers the data ecosystem for organizations as diverse as Electronic Arts, Conde Nast is one of our big customers, a big user of Airflow. And also not to mention the biggest banks on Wall Street use Airflow and Astronomer to power the flow of data throughout their organizations. >> Talk about that a little bit more, Steven, in terms of the business impact. You mentioned some great customer names there. What is the business impact or outcomes that a data orchestration strategy enables businesses to achieve? >> Yeah, I mean, at the heart of it is quite simply, scheduling and managing data pipelines. And so if you have some enormous retailer who's managing the flow of information throughout their organization they may literally have thousands or even tens of thousands of data pipelines that need to execute every day to do things as simple as delivering metrics for the executives to consume at the end of the day, to producing on a weekly basis new machine learning models that can be used to drive product recommendations. One of our customers, for example, is a British food delivery service. And you get those recommendations in your application that says, "Well, maybe you want to have samosas with your curry." That sort of thing is powered by machine learning models that they train on a regular basis to reflect changing conditions in the market. And those are produced through Airflow and through the Astronomer platform, which is essentially a managed platform for running airflow. So at its simplest it really is just scheduling and managing those workflows. But that's easier said than done of course. I mean if you have 10 thousands of those things then you need to make sure that they all run that they all have sufficient compute resources. If things fail, how do you track those down across those 10,000 workflows? How easy is it for an average data scientist or data engineer to contribute their code, their Python notebooks or their SQL code into a production environment? And then you've got reproducibility, governance, auditing, like managing data flows across an organization which we think of as orchestrating them is much more than just scheduling. It becomes really complicated pretty quickly. >> I imagine there's a fair amount of complexity there. Jeff, let's bring you into the conversation. Talk a little bit about Astronomer through your lens, data orchestration and how it applies to MLOps. >> So I come from a machine learning background and for me the interesting part is that machine learning requires the expansion into orchestration. A lot of the same things that you're using to go and develop and build pipelines in a standard data orchestration space applies equally well in a machine learning orchestration space. What you're doing is you're moving data between different locations, between different tools, and then tasking different types of tools to act on that data. So extending it made logical sense from a implementation perspective. And a lot of my focus at Astronomer is really to explain how Airflow can be used well in a machine learning context. It is being used well, it is being used a lot by the customers that we have and also by users of the open source version. But it's really being able to explain to people why it's a natural extension for it and how well it fits into that. And a lot of it is also extending some of the infrastructure capabilities that Astronomer provides to those customers for them to be able to run some of the more platform specific requirements that come with doing machine learning pipelines. >> Let's get into some of the things that make Astronomer unique. Jeff, sticking with you, when you're in customer conversations, what are some of the key differentiators that you articulate to customers? >> So a lot of it is that we are not specific to one cloud provider. So we have the ability to operate across all of the big cloud providers. I know, I'm certain we have the best developers that understand how best practices implementations for data orchestration works. So we spend a lot of time talking to not just the business outcomes and the business users of the product, but also also for the technical people, how to help them better implement things that they may have come across on a Stack Overflow article or not necessarily just grown with how the product has migrated. So it's the ability to run it wherever you need to run it and also our ability to help you, the customer, better implement and understand those workflows that I think are two of the primary differentiators that we have. >> Lisa: Got it. >> I'll add another one if you don't mind. >> You can go ahead, Steven. >> Is lineage and dependencies between workflows. One thing we've done is to augment core Airflow with Lineage services. So using the Open Lineage framework, another open source framework for tracking datasets as they move from one workflow to another one, team to another, one data source to another is a really key component of what we do and we bundle that within the service so that as a developer or as a production engineer, you really don't have to worry about lineage, it just happens. Jeff, may show us some of this later that you can actually see as data flows from source through to a data warehouse out through a Python notebook to produce a predictive model or a dashboard. Can you see how those data products relate to each other? And when something goes wrong, figure out what upstream maybe caused the problem, or if you're about to change something, figure out what the impact is going to be on the rest of the organization. So Lineage is a big deal for us. >> Got it. >> And just to add on to that, the other thing to think about is that traditional Airflow is actually a complicated implementation. It required quite a lot of time spent understanding or was almost a bespoke language that you needed to be able to develop in two write these DAGs, which is like fundamental pipelines. So part of what we are focusing on is tooling that makes it more accessible to say a data analyst or a data scientist who doesn't have or really needs to gain the necessary background in how the semantics of Airflow DAGs works to still be able to get the benefit of what Airflow can do. So there is new features and capabilities built into the astronomer cloud platform that effectively obfuscates and removes the need to understand some of the deep work that goes on. But you can still do it, you still have that capability, but we are expanding it to be able to have orchestrated and repeatable processes accessible to more teams within the business. >> In terms of accessibility to more teams in the business. You talked about data scientists, data analysts, developers. Steven, I want to talk to you, as the chief data officer, are you having more and more conversations with that role and how is it emerging and evolving within your customer base? >> Hmm. That's a good question, and it is evolving because I think if you look historically at the way that Airflow has been used it's often from the ground up. You have individual data engineers or maybe single data engineering teams who adopt Airflow 'cause it's very popular. Lots of people know how to use it and they bring it into an organization and say, "Hey, let's use this to run our data pipelines." But then increasingly as you turn from pure workflow management and job scheduling to the larger topic of orchestration you realize it gets pretty complicated, you want to have coordination across teams, and you want to have standardization for the way that you manage your data pipelines. And so having a managed service for Airflow that exists in the cloud is easy to spin up as you expand usage across the organization. And thinking long term about that in the context of orchestration that's where I think the chief data officer or the head of analytics tends to get involved because they really want to think of this as a strategic investment that they're making. Not just per team individual Airflow deployments, but a network of data orchestrators. >> That network is key. Every company these days has to be a data company. We talk about companies being data driven. It's a common word, but it's true. It's whether it is a grocer or a bank or a hospital, they've got to be data companies. So talk to me a little bit about Astronomer's business model. How is this available? How do customers get their hands on it? >> Jeff, go ahead. >> Yeah, yeah. So we have a managed cloud service and we have two modes of operation. One, you can bring your own cloud infrastructure. So you can say here is an account in say, AWS or Azure and we can go and deploy the necessary infrastructure into that, or alternatively we can host everything for you. So it becomes a full SaaS offering. But we then provide a platform that connects at the backend to your internal IDP process. So however you are authenticating users to make sure that the correct people are accessing the services that they need with role-based access control. From there we are deploying through Kubernetes, the different services and capabilities into either your cloud account or into an account that we host. And from there Airflow does what Airflow does, which is its ability to then reach to different data systems and data platforms and to then run the orchestration. We make sure we do it securely, we have all the necessary compliance certifications required for GDPR in Europe and HIPAA based out of the US, and a whole bunch host of others. So it is a secure platform that can run in a place that you need it to run, but it is a managed Airflow that includes a lot of the extra capabilities like the cloud developer environment and the open lineage services to enhance the overall airflow experience. >> Enhance the overall experience. So Steven, going back to you, if I'm a Conde Nast or another organization, what are some of the key business outcomes that I can expect? As one of the things I think we've learned during the pandemic is access to realtime data is no longer a nice to have for organizations. It's really an imperative. It's that demanding consumer that wants to have that personalized, customized, instant access to a product or a service. So if I'm a Conde Nast or I'm one of your customers, what can I expect my business to be able to achieve as a result of data orchestration? >> Yeah, I think in a nutshell it's about providing a reliable, scalable, and easy to use service for developing and running data workflows. And talking of demanding customers, I mean, I'm actually a customer myself, as you mentioned, I'm the head of data for Astronomer. You won't be surprised to hear that we actually use Astronomer and Airflow to run all of our data pipelines. And so I can actually talk about my experience. When I started I was of course familiar with Airflow, but it always seemed a little bit unapproachable to me if I was introducing that to a new team of data scientists. They don't necessarily want to have to think about learning something new. But I think because of the layers that Astronomer has provided with our Astro service around Airflow it was pretty easy for me to get up and running. Of course I've got an incentive for doing that. I work for the Airflow company, but we went from about, at the beginning of last year, about 500 data tasks that we were running on a daily basis to about 15,000 every day. We run something like a million data operations every month within my team. And so as one outcome, just the ability to spin up new production workflows essentially in a single day you go from an idea in the morning to a new dashboard or a new model in the afternoon, that's really the business outcome is just removing that friction to operationalizing your machine learning and data workflows. >> And I imagine too, oh, go ahead, Jeff. >> Yeah, I think to add to that, one of the things that becomes part of the business cycle is a repeatable capabilities for things like reporting, for things like new machine learning models. And the impediment that has existed is that it's difficult to take that from a team that's an analyst team who then provide that or a data science team that then provide that to the data engineering team who have to work the workflow all the way through. What we're trying to unlock is the ability for those teams to directly get access to scheduling and orchestrating capabilities so that a business analyst can have a new report for C-suite execs that needs to be done once a week, but the time to repeatability for that report is much shorter. So it is then immediately in the hands of the person that needs to see it. It doesn't have to go into a long list of to-dos for a data engineering team that's already overworked that they eventually get it to it in a month's time. So that is also a part of it is that the realizing, orchestration I think is fairly well and a lot of people get the benefit of being able to orchestrate things within a business, but it's having more people be able to do it and shorten the time that that repeatability is there is one of the main benefits from good managed orchestration. >> So a lot of workforce productivity improvements in what you're doing to simplify things, giving more people access to data to be able to make those faster decisions, which ultimately helps the end user on the other end to get that product or the service that they're expecting like that. Jeff, I understand you have a demo that you can share so we can kind of dig into this. >> Yeah, let me take you through a quick look of how the whole thing works. So our starting point is our cloud infrastructure. This is the login. You go to the portal. You can see there's a a bunch of workspaces that are available. Workspaces are like individual places for people to operate in. I'm not going to delve into all the deep technical details here, but starting point for a lot of our data science customers is we have what we call our Cloud IDE, which is a web-based development environment for writing and building out DAGs without actually having to know how the underpinnings of Airflow work. This is an internal one, something that we use. You have a notebook-like interface that lets you write python code and SQL code and a bunch of specific bespoke type of blocks if you want. They all get pulled together and create a workflow. So this is a workflow, which gets compiled to something that looks like a complicated set of Python code, which is the DAG. I then have a CICD process pipeline where I commit this through to my GitHub repo. So this comes to a repo here, which is where these DAGs that I created in the previous step exist. I can then go and say, all right, I want to see how those particular DAGs have been running. We then get to the actual Airflow part. So this is the managed Airflow component. So we add the ability for teams to fairly easily bring up an Airflow instance and write code inside our notebook-like environment to get it into that instance. So you can see it's been running. That same process that we built here that graph ends up here inside this, but you don't need to know how the fundamentals of Airflow work in order to get this going. Then we can run one of these, it runs in the background and we can manage how it goes. And from there, every time this runs, it's emitting to a process underneath, which is the open lineage service, which is the lineage integration that allows me to come in here and have a look and see this was that actual, that same graph that we built, but now it's the historic version. So I know where things started, where things are going, and how it ran. And then I can also do a comparison. So if I want to see how this particular run worked compared to one historically, I can grab one from a previous date and it will show me the comparison between the two. So that combination of managed Airflow, getting Airflow up and running very quickly, but the Cloud IDE that lets you write code and know how to get something into a repeatable format get that into Airflow and have that attached to the lineage process adds what is a complete end-to-end orchestration process for any business looking to get the benefit from orchestration. >> Outstanding. Thank you so much Jeff for digging into that. So one of my last questions, Steven is for you. This is exciting. There's a lot that you guys are enabling organizations to achieve here to really become data-driven companies. So where can folks go to get their hands on this? >> Yeah, just go to astronomer.io and we have plenty of resources. If you're new to Airflow, you can read our documentation, our guides to getting started. We have a CLI that you can download that is really I think the easiest way to get started with Airflow. But you can actually sign up for a trial. You can sign up for a guided trial where our teams, we have a team of experts, really the world experts on getting Airflow up and running. And they'll take you through that trial and allow you to actually kick the tires and see how this works with your data. And I think you'll see pretty quickly that it's very easy to get started with Airflow, whether you're doing that from the command line or doing that in our cloud service. And all of that is available on our website >> astronomer.io. Jeff, last question for you. What are you excited about? There's so much going on here. What are some of the things, maybe you can give us a sneak peek coming down the road here that prospects and existing customers should be excited about? >> I think a lot of the development around the data awareness components, so one of the things that's traditionally been complicated with orchestration is you leave your data in the place that you're operating on and we're starting to have more data processing capability being built into Airflow. And from a Astronomer perspective, we are adding more capabilities around working with larger datasets, doing bigger data manipulation with inside the Airflow process itself. And that lends itself to better machine learning implementation. So as we start to grow and as we start to get better in the machine learning context, well, in the data awareness context, it unlocks a lot more capability to do and implement proper machine learning pipelines. >> Awesome guys. Exciting stuff. Thank you so much for talking to me about Astronomer, machine learning, data orchestration, and really the value in it for your customers. Steve and Jeff, we appreciate your time. >> Thank you. >> My pleasure, thanks. >> And we thank you for watching. This is season three, episode one of our ongoing series covering exciting startups from the AWS ecosystem. I'm your host, Lisa Martin. You're watching theCUBE, the leader in live tech coverage. (upbeat music)

(upbeat music) >> Hey everyone, welcome to this event: Build Your Cloud Center of Excellence. I'm your host, Lisa Martin, and I have two guests here with me today to talk about the hybrid cloud, the multi-cloud trends, and specifically the complexity. While we know these trends provide agility and flexibility for customers, they also bring in complexity. And this session is going to focus on exploring that with RBI and HitachiVantara. Please welcome my guests, Adithya Sastry the SVP of Digital Solutions at HitachiVantara and Werner Mayer, head of group core IT and head of group data at RBI International. Guys, welcome to the program. >> Thank you Lisa. Werner, nice to see you again. >> Great to see you both. >> And Werner, we're going to start with you. Talk about RBI. Tell the audience a little bit about what the business is and then we're going to get into your cloud transformation journey over the last couple of years. >> Yes, thank you. So Raiffeisen Bank International is international working banking groups. So our core markets are Central Eastern European, Central Eastern Europe and Austria. And we are serving around 50 million clients in this market. So we active in 13 markets. >> Got it. Talk to me, Werner about the cloud transformation journey that RBI has been on over the last couple of years and some of the complexities that you've experienced as you've launched it. >> Sure. Thank you for the question. So in 2020, we decided that we have to renew our IT strategy. And the aim of the strategy was to change the organization in a way that it can react and adapt fast to the future challenges. So one of the important pillars for us was that we are adapting fast also for new technologies. And this was core pillar in our strategy. So we're searching for technologies which are fit in to our HR transformation. And we found that the cloud and the public cloud environment fits to this venture. So we tested that. We are building up also the competent centers for that and also established the group cloud platform for that. Because our invoice to onboard our international group with the 13 units to this group cloud platform. So that means we have a lot to do to hardening the platforms in terms of security to put in. We have standard for that. We have to introduce large scale programs to train hundreds of engineers. We tested the approach, We convinced the top management and we implemented this, this program. So one of the highlights was, of course, also the the safeguarding of the Ukraine, let's say, banking environment. So we had to lift and shift the complete bank in three months. And it shows that let's say our platforms works. And let's say the approach is proven that we can scale it over the group. >> That's a big challenge. A lot of complexity especially with some of the global things going on. Adithya, these challenges are, are not unique to RBI. A lot of your customers are facing challenges with complexity around cloud management, cloud ops. What can you unpack was the real issue is here? >> Yeah, Lisa, absolutely. And you know, before I answer your question, I do want to, you know, just say a couple of things about Raiffeisen Bank. And you know, we've had the pleasure of working with them for about a year, a little bit more than a year now. And, and, and the way they approach the cloud transformation journey is - should be a template for a lot of the organizations in terms of the preparation in terms of understanding, you know. How other companies have done it and what are the pitfalls. What's worked, and really what's the recipe for their, you know, journey, right? Which is very unique because, you know, you look at you know, being present across 30 different countries within central and eastern Europe as Werner said. And the complexities of dealing with local regulations, GDPR and all these other issues that come with it, right? And not to mention the language variation from country to country. So, you know, phenomenal story there. The journey and the journey still goes, right Werner? It's not complete yet. But Lisa, to your question, you know. When we look at, you know, the complexities of this transformation, that most modern enterprises are going through. It's not very unique, right? What is unique for a Raiffeisen Bank is - has been the preparation. As you get into this journey of moving workloads to cloud, be it refactoring, modernizing, migrating, etc. One of the things that really is often overlooked is: "Are my applications and data workloads resilient on the cloud?" Meaning  how is the performance? Are they just running or are they performing with high availability to meet your customers goals? Is it scalable? And are my cost in line with what I projected when I moved prep. >> Because that's one of the areas we are seeing where you know, what enterprises projected from a cost savings to what they're realizing a year and a half into the journey is a pretty big delta, right? And, and, and a lot of it is dependent on are the cloud - are the applications and the workloads cloud, designed for the cloud? Or are they designed for on-prem which you just move to the cloud. >> So Werner, it sounds like what Adithya said is a compliment to, to you guys and the team at RBI in terms of this being a template for managing complexity. Give us, Werner, your perspective in terms of modern cloud ops. What's in? What's out? What is it that customers really need to be focusing on to be successful? >> Thanks for the compliment, Lisa. And I think this is a great relationship also in the journey. Topic is, is, is a - is a complex program where a lot of things have to fit together. But it was mentioning the resilience. The course, we call it finops, security operations and so on have to come together and have to work on spot. At the end, it's also, let's say, how we are able enabling our teams and how we are ramping out the skills of our teams to deal with these multidimensional, let's say environments. And this is something what we spend a lot of time in order to prepare, but also to bring up the people on a certain level that they can operate at. Because card guard handling is, is different than before. Because beforehand you have central operations team. They do everything for you. But in this world let's say we are also putting the responsibility of the run component of the absent to the - in the tribes and the application teams. And they have to do much more than before. On the other hand, we have first central rules. We have monitoring functions. We have support functions on that in order to best support them in their journey. So this is a hybrid between, let's say, what the teams have to do with the responsibility in the teams, but also with the central functions which are supporting them. And everything have to work together and goes hand in - right, to go hand-in-hand. >> Yeah. Yeah. And if, if I could just add Lisa really quick and and Werner hit the nail on the head, right? Because you cannot look at cloud operation the way we have traditionally looked at managed services. That's the key thing, right? You cannot, you know, traditional managed services you had L1, L2, L3 and then it goes into some sort of a vacuum and then all of a sudden somebody calls you at some point, right? >> Werner: Exactly. >> And it really has flipped, right? To, to Werner's point. And Werner hit that name on the head because you really have to understand. Bring an engineering led approach to make sure that the problems, you know, when you see an issue that you have some level of automation in terms of problem isolation. And then the problem is routed the right individual ie the application engineering team or the data engineering team for resolution in a rapid manner. Right? I think that the key - >> Yes. A very important point with that is said, yeah. So you cannot traditional transport let's say, the operation model what you have now into the cloud because this will not work, yeah. And finally at the end you will not benefit on the technology possibilities there. So super important point. My vision in the cloud and this is also something what we are working on is a sort of zero-ops environment, yeah? Because we're ultimately dealing with the automatization technologies and so on, you can that much - to much more compared to the traditional environment and the benefit of the cloud is: You can test it. You can give it feedback when it is not working, yeah? So it's a completely different operating model. What we try to establish in the cloud environment. >> So really what this seems like guys is is quite a delicate balance that you're solving for. Not the only delicate balance but Werner sticking with you. Talk to us about some of the challenges that you've had around cloud cost management in particular. Help us understand that. >> Thanks for the question. So in principle, we are doing very well on the cost side, surprisingly. And we also started the cloud journey that is said this is not the cost case. Because as I said before, let's say one of the pillars in the strategy strategy was the enablement of technology to the benefit of customer solutions to be adaptive, to be faster. But at the end it turned out that let's say with giving the responsibility of the operation to the dedicated team, they found they - they were working much closer to the cost, and let's say monitoring the cost, then we headed into traditional environments, yeah? I also saw some examples in the group where sort of gamification of the cost were going on. To say who can save more To say who can save more and make more much more out of that what you have in the cloud. And at the end we see that in minimum the cost are balance to the traditional environments in the data centers. But we also saw that let's say, the cost were brought down much more than before. So at the beginning we were relative conservative with the assumptions, yeah? But it turns out that we are really getting the benefit. The things are getting faster and also the costs are going down. And we see this in real cases. >> Yeah. And, and, and Lisa, if I could add something really quick, right? Because - There's been a mad rush to the cloud, right? Everybody kind of, it was, you know, the buzz the buzz was let's get to the cloud. We'll start to realize all these savings. And all of a sudden, everything kind of magically gets better, right? And what we have seen is also, you know, companies or customers or enterprises that have started this journey about 5, 6 years ago and are about, you know, a few years into it. What we are realizing is the cloud costs have increased significantly to what their projections were early on. And the way they're trying to address the cloud cost is by creating a FinOps organization that's looking at, you know, the cost of cloud from a structure standpoint and support as a reactive measure. Saying, "Hey if we move from Azure or one provider to another is there any benefit? If we move certain applications from the cloud back to on-prem, is there any benefit?" When in fact, one of the things that we have noticed really is: The problem needs to shift left to the engineering teams. Because if you are designing the applications and the systems the right way to begin with, then you can manage the data cost issues or the cost overruns, right? So you design for the cloud as opposed to designing and then looking at how do we optimize cloud. >> So Adithya, you talked about the RBI use case as really kind of a template but also some of the challenges with respect to hybrid and multi-cloud are kind of like a chicken and egg scenario. Talk to us kind of like overall about how Hitachi is really helping customers address these challenges and maximize the benefits to get the flexibility to get the agility so that they can deliver what their end user customers are expecting. >> Yeah, yeah. So, so one of the things we are doing, Lisa, when we work with customers, is really trying to understand, you know, look at their entire portfolio of applications, right? And, and look at what the intent of the applications is between customer facing, external customer, internal customer, high availability, production, etc., right? And then we go through a methodology called E3 which is envision, enable and execute. Which is really envision what the end stage should be regardless of what the environment is, right? And then we enable, which is really kind of go through a proof of value to move a few workloads, to modernize, rearchitect, replatform, etc. And look at the benefit of that application on its destination. If it's a cloud - if it's a cloud service provider or if it's another data center, whatever it may be, right? And finally, you know, once we've proven the value and the benefit and and say and kind of monetize the, you know realize the value of it from an agility, from a cost, from security and resilience, etc. Then we go through the execution, which was look we look at the entire portfolio, the entire landscape. And we go through a very disciplined manner working with our customers to roadmap it. And then we execute in a very deliberate manner where you can see value every 2-3 months. Because gone the days when you can do things as a science project that took 2-3 years, right? We, we - Everyone wants to see value, want to see - wants to see progress, and most importantly we want to see cost benefit and agility sooner than later. >> Those are incredibly important outcomes. You guys have done a great job explaining what you're doing together. This sounds like a great relationship. All right, so my last question to both of you is: "If I'm a customer and I'm planning a cloud transformation for my company, what are the two things you want me to remember and consider as I plan this? Werner, we'll start with you. >> I would pick up two things, yeah? The first one is: When you are organizing your company in HR way, then cloud is the HR technology for the HR transformation. Because HR teams needs HR technology. And the second important thing is, what I would say is: Cloud is a large scale and fast moving technology enabler to the company. So if your company is going forward to say: Technology is their enabler tool from a future business then cloud can support this journey. >> Excellent. I'm going to walk away with those. And Adithya, same question to you. I'm a, I'm a customer. I'm at an organization. I'm planning a cloud transformation. Top two things you want me to walk away with. >> Yeah. And I think Werner kind of actually touched on that in the second one, which is: it's not a tech, just an IT or a technology initiative. It is a business initiative, right? Because ultimately what you do from this cloud journey should drive, you know, should lead into business transformation or help your business grow top line or drive margin expansion, etc. So couple of things I would say, right? One is, you know, get Being and prioritize. Work with your business owners, with, you know with the cross-functional team not just the technology team. That's one. The second thing is: as the technology team or the IT team shepherds this journey, you know, keep everyone informed and engaged as you go through this journey. Because as you go through moving workloads modernizing workload, there is an impact to, you know receivables through omnichannel experiences the way customers interact and transact with you, right? And that comes with making making sure your businesses are aware your business stakeholders are aware. So in turn the end customers are aware. So you know, it's not a one and done from an engagement, it's a journey. And bring in the right experts. Talk to people who've done it, done this before, who have kind of stepped in all the pitfalls so you don't have to, right? That's the key. >> That's great advice. That's great advice for anything in life, I think. You talk about the collaboration, the importance of the business and the technology folks coming together. It really has to be - It's a delicate balance as we said before but it really has to be a holistic collaborative approach. Guys, thank you so much for joining me talking through what HitachiVantara and RBI are doing together. It sounds like you're well into this journey and it sounds like it's going quite well. We thank you so much for your insights and your perspectives. >> Thank you, Lisa. Werner, thank you again. >> Good stuff guys. For my guests, I'm Lisa Martin. Thank you so much for watching our event: Build Your Cloud Center of Excellence. (upbeat music)

(soothing music) >> Hey everyone, welcome to this event, "Build Your Cloud Center of Excellence." I'm your host, Lisa Martin. In the next 15 minutes or so my guest and I are going to be talking about redefining cloud operations, an application modernization for customers, and specifically how partners are helping to speed up that process. As you saw on our first two segments, we talked about problems enterprises are facing with cloud operations. We talked about redefining cloud operations as well to solve these problems. This segment is going to be focusing on how Hitachi Vantara's partners are really helping to speed up that process. We've got Johnson Controls here to talk about their partnership with Hitachi Vantara. Please welcome both of my guests, Prem Balasubramanian is with us, SVP and CTO Digital Solutions at Hitachi Vantara. And Suresh Mothikuru, SVP Customer Success Platform Engineering and Reliability Engineering from Johnson Controls. Gentlemen, welcome to the program, great to have you. >> Thank. >> Thank you, Lisa. >> First question is to both of you and Suresh, we'll start with you. We want to understand, you know, the cloud operations landscape is increasingly complex. We've talked a lot about that in this program. Talk to us, Suresh, about some of the biggest challenges and pin points that you faced with respect to that. >> Thank you. I think it's a great question. I mean, cloud has evolved a lot in the last 10 years. You know, when we were talking about a single cloud whether it's Azure or AWS and GCP, and that was complex enough. Now we are talking about multi-cloud and hybrid and you look at Johnson Controls, we have Azure we have AWS, we have GCP, we have Alibaba and we also support on-prem. So the architecture has become very, very complex and the complexity has grown so much that we are now thinking about whether we should be cloud native or cloud agnostic. So I think, I mean, sometimes it's hard to even explain the complexity because people think, oh, "When you go to cloud, everything is simplified." Cloud does give you a lot of simplicity, but it also really brings a lot more complexity along with it. So, and then next one is pretty important is, you know, generally when you look at cloud services, you have plenty of services that are offered within a cloud, 100, 150 services, 200 services. Even within those companies, you take AWS they might not know, an individual resource might not know about all the services we see. That's a big challenge for us as a customer to really understand each of the service that is provided in these, you know, clouds, well, doesn't matter which one that is. And the third one is pretty big, at least at the CTO the CIO, and the senior leadership level, is cost. Cost is a major factor because cloud, you know, will eat you up if you cannot manage it. If you don't have a good cloud governance process it because every minute you are in it, it's burning cash. So I think if you ask me, these are the three major things that I am facing day to day and that's where I use my partners, which I'll touch base down the line. >> Perfect, we'll talk about that. So Prem, I imagine that these problems are not unique to Johnson Controls or JCI, as you may hear us refer to it. Talk to me Prem about some of the other challenges that you're seeing within the customer landscape. >> So, yeah, I agree, Lisa, these are not very specific to JCI, but there are specific issues in JCI, right? So the way we think about these are, there is a common issue when people go to the cloud and there are very specific and unique issues for businesses, right? So JCI, and we will talk about this in the episode as we move forward. I think Suresh and his team have done some phenomenal step around how to manage this complexity. But there are customers who have a lesser complex cloud which is, they don't go to Alibaba, they don't have footprint in all three clouds. So their multi-cloud footprint could be a bit more manageable, but still struggle with a lot of the same problems around cost, around security, around talent. Talent is a big thing, right? And in Suresh's case I think it's slightly more exasperated because every cloud provider Be it AWS, JCP, or Azure brings in hundreds of services and there is nobody, including many of us, right? We learn every day, nowadays, right? It's not that there is one service integrator who knows all, while technically people can claim as a part of sales. But in reality all of us are continuing to learn in this landscape. And if you put all of this equation together with multiple clouds the complexity just starts to exponentially grow. And that's exactly what I think JCI is experiencing and Suresh's team has been experiencing, and we've been working together. But the common problems are around security talent and cost management of this, right? Those are my three things. And one last thing that I would love to say before we move away from this question is, if you think about cloud operations as a concept that's evolving over the last few years, and I have touched upon this in the previous episode as well, Lisa, right? If you take architectures, we've gone into microservices, we've gone into all these server-less architectures all the fancy things that we want. That helps us go to market faster, be more competent to as a business. But that's not simplified stuff, right? That's complicated stuff. It's a lot more distributed. Second, again, we've advanced and created more modern infrastructure because all of what we are talking is platform as a service, services on the cloud that we are consuming, right? In the same case with development we've moved into a DevOps model. We kind of click a button put some code in a repository, the code starts to run in production within a minute, everything else is automated. But then when we get to operations we are still stuck in a very old way of looking at cloud as an infrastructure, right? So you've got an infra team, you've got an app team, you've got an incident management team, you've got a soft knock, everything. But again, so Suresh can talk about this more because they are making significant strides in thinking about this as a single workload, and how do I apply engineering to go manage this? Because a lot of it is codified, right? So automation. Anyway, so that's kind of where the complexity is and how we are thinking, including JCI as a partner thinking about taming that complexity as we move forward. >> Suresh, let's talk about that taming the complexity. You guys have both done a great job of articulating the ostensible challenges that are there with cloud, especially multi-cloud environments that you're living in. But Suresh, talk about the partnership with Hitachi Vantara. How is it helping to dial down some of those inherent complexities? >> I mean, I always, you know, I think I've said this to Prem multiple times. I treat my partners as my internal, you know, employees. I look at Prem as my coworker or my peers. So the reason for that is I want Prem to have the same vested interest as a partner in my success or JCI success and vice versa, isn't it? I think that's how we operate and that's how we have been operating. And I think I would like to thank Prem and Hitachi Vantara for that really been an amazing partnership. And as he was saying, we have taken a completely holistic approach to how we want to really be in the market and play in the market to our customers. So if you look at my jacket it talks about OpenBlue platform. This is what JCI is building, that we are building this OpenBlue digital platform. And within that, my team, along with Prem's or Hitachi's, we have built what we call as Polaris. It's a technical platform where our apps can run. And this platform is automated end-to-end from a platform engineering standpoint. We stood up a platform engineering organization, a reliability engineering organization, as well as a support organization where Hitachi played a role. As I said previously, you know, for me to scale I'm not going to really have the talent and the knowledge of every function that I'm looking at. And Hitachi, not only they brought the talent but they also brought what he was talking about, Harc. You know, they have set up a lot and now we can leverage it. And they also came up with some really interesting concepts. I went and met them in India. They came up with this concept called IPL. Okay, what is that? They really challenged all their employees that's working for GCI to come up with innovative ideas to solve problems proactively, which is self-healing. You know, how you do that? So I think partners, you know, if they become really vested in your interests, they can do wonders for you. And I think in this case Hitachi is really working very well for us and in many aspects. And I'm leveraging them... You started with support, now I'm leveraging them in the automation, the platform engineering, as well as in the reliability engineering and then in even in the engineering spaces. And that like, they are my end-to-end partner right now? >> So you're really taking that holistic approach that you talked about and it sounds like it's a very collaborative two-way street partnership. Prem, I want to go back to, Suresh mentioned Harc. Talk a little bit about what Harc is and then how partners fit into Hitachi's Harc strategy. >> Great, so let me spend like a few seconds on what Harc is. Lisa, again, I know we've been using the term. Harc stands for Hitachi application reliability sectors. Now the reason we thought about Harc was, like I said in the beginning of this segment, there is an illusion from an architecture standpoint to be more modern, microservices, server-less, reactive architecture, so on and so forth. There is an illusion in your development methodology from Waterfall to agile, to DevOps to lean, agile to path program, whatever, right? Extreme program, so on and so forth. There is an evolution in the space of infrastructure from a point where you were buying these huge humongous servers and putting it in your data center to a point where people don't even see servers anymore, right? You buy it, by a click of a button you don't know the size of it. All you know is a, it's (indistinct) whatever that name means. Let's go provision it on the fly, get go, get your work done, right? When all of this is advanced when you think about operations people have been solving the problem the way they've been solving it 20 years back, right? That's the issue. And Harc was conceived exactly to fix that particular problem, to think about a modern way of operating a modern workload, right? That's exactly what Harc. So it brings together finest engineering talent. So the teams are trained in specific ways of working. We've invested and implemented some of the IP, we work with the best of the breed partner ecosystem, and I'll talk about that in a minute. And we've got these facilities in Dallas and I am talking from my office in Dallas, which is a Harc facility in the US from where we deliver for our customers. And then back in Hyderabad, we've got one more that we opened and these are facilities from where we deliver Harc services for our customers as well, right? And then we are expanding it in Japan and Portugal as we move into 23. That's kind of the plan that we are thinking through. However, that's what Harc is, Lisa, right? That's our solution to this cloud complexity problem. Right? >> Got it, and it sounds like it's going quite global, which is fantastic. So Suresh, I want to have you expand a bit on the partnership, the partner ecosystem and the role that it plays. You talked about it a little bit but what role does the partner ecosystem play in really helping JCI to dial down some of those challenges and the inherent complexities that we talked about? >> Yeah, sure. I think partners play a major role and JCI is very, very good at it. I mean, I've joined JCI 18 months ago, JCI leverages partners pretty extensively. As I said, I leverage Hitachi for my, you know, A group and the (indistinct) space and the cloud operations space, and they're my primary partner. But at the same time, we leverage many other partners. Well, you know, Accenture, SCL, and even on the tooling side we use Datadog and (indistinct). All these guys are major partners of our because the way we like to pick partners is based on our vision and where we want to go. And pick the right partner who's going to really, you know make you successful by investing their resources in you. And what I mean by that is when you have a partner, partner knows exactly what kind of skillset is needed for this customer, for them to really be successful. As I said earlier, we cannot really get all the skillset that we need, we rely on the partners and partners bring the the right skillset, they can scale. I can tell Prem tomorrow, "Hey, I need two parts by next week", and I guarantee it he's going to bring two parts to me. So they let you scale, they let you move fast. And I'm a big believer, in today's day and age, to get things done fast and be more agile. I'm not worried about failure, but for me moving fast is very, very important. And partners really do a very good job bringing that. But I think then they also really make you think, isn't it? Because one thing I like about partners they make you innovate whether they know it or not but they do because, you know, they will come and ask you questions about, "Hey, tell me why you are doing this. Can I review your architecture?" You know, and then they will try to really say I don't think this is going to work. Because they work with so many different clients, not JCI, they bring all that expertise and that's what I look from them, you know, just not, you know, do a T&M job for me. I ask you to do this go... They just bring more than that. That's how I pick my partners. And that's how, you know, Hitachi's Vantara is definitely one of a good partner from that sense because they bring a lot more innovation to the table and I appreciate about that. >> It sounds like, it sounds like a flywheel of innovation. >> Yeah. >> I love that. Last question for both of you, which we're almost out of time here, Prem, I want to go back to you. So I'm a partner, I'm planning on redefining CloudOps at my company. What are the two things you want me to remember from Hitachi Vantara's perspective? >> So before I get to that question, Lisa, the partners that we work with are slightly different from from the partners that, again, there are some similar partners. There are some different partners, right? For example, we pick and choose especially in the Harc space, we pick and choose partners that are more future focused, right? We don't care if they are huge companies or small companies. We go after companies that are future focused that are really, really nimble and can change for our customers need because it's not our need, right? When I pick partners for Harc my ultimate endeavor is to ensure, in this case because we've got (indistinct) GCI on, we are able to operate (indistinct) with the level of satisfaction above and beyond that they're expecting from us. And whatever I don't have I need to get from my partners so that I bring this solution to Suresh. As opposed to bringing a whole lot of people and making them stand in front of Suresh. So that's how I think about partners. What do I want them to do from, and we've always done this so we do workshops with our partners. We just don't go by tools. When we say we are partnering with X, Y, Z, we do workshops with them and we say, this is how we are thinking. Either you build it in your roadmap that helps us leverage you, continue to leverage you. And we do have minimal investments where we fix gaps. We're building some utilities for us to deliver the best service to our customers. And our intention is not to build a product to compete with our partner. Our intention is to just fill the wide space until they go build it into their product suite that we can then leverage it for our customers. So always think about end customers and how can we make it easy for them? Because for all the tool vendors out there seeing this and wanting to partner with Hitachi the biggest thing is tools sprawl, especially on the cloud is very real. For every problem on the cloud. I have a billion tools that are being thrown at me as Suresh if I'm putting my installation and it's not easy at all. It's so confusing. >> Yeah. >> So that's what we want. We want people to simplify that landscape for our end customers, and we are looking at partners that are thinking through the simplification not just making money. >> That makes perfect sense. There really is a very strong symbiosis it sounds like, in the partner ecosystem. And there's a lot of enablement that goes on back and forth it sounds like as well, which is really, to your point it's all about the end customers and what they're expecting. Suresh, last question for you is which is the same one, if I'm a partner what are the things that you want me to consider as I'm planning to redefine CloudOps at my company? >> I'll keep it simple. In my view, I mean, we've touched upon it in multiple facets in this interview about that, the three things. First and foremost, reliability. You know, in today's day and age my products has to be reliable, available and, you know, make sure that the customer's happy with what they're really dealing with, number one. Number two, my product has to be secure. Security is super, super important, okay? And number three, I need to really make sure my customers are getting the value so I keep my cost low. So these three is what I would focus and what I expect from my partners. >> Great advice, guys. Thank you so much for talking through this with me and really showing the audience how strong the partnership is between Hitachi Vantara and JCI. What you're doing together, we'll have to talk to you again to see where things go but we really appreciate your insights and your perspectives. Thank you. >> Thank you, Lisa. >> Thanks Lisa, thanks for having us. >> My pleasure. For my guests, I'm Lisa Martin. Thank you so much for watching. (soothing music)

(Upbeat music playing) >> Hey everyone, thanks for joining us today. Welcome to this event of Building your Cloud Center of Excellence with Hitachi Vantara. I'm your host, Lisa Martin. I've got a couple of guests here with me next to talk about redefining cloud operations and application modernization for customers. Please welcome Prem Balasubramanian the SVP and CTO at Hitachi Vantara, and Manoj Narayanan is here as well, the Managing Director of Technology at GTCR. Guys, thank you so much for joining me today. Excited to have this conversation about redefining CloudOps with you. >> Pleasure to be here. >> Pleasure to be here >> Prem, let's go ahead and start with you. You have done well over a thousand cloud engagements in your career. I'd love to get your point of view on how the complexity around cloud operations and management has evolved in the last, say, three to four years. >> It's a great question, Lisa before we understand the complexity around the management itself, the cloud has evolved over the last decade significantly from being a backend infrastructure or infrastructure as a service for many companies to become the business for many companies. If you think about a lot of these cloud bond companies cloud is where their entire workload and their business wants. With that, as a background for this conversation if you think about the cloud operations, there was a lot of there was a lot of lift and shift happening in the market where people lifted their workloads or applications and moved them onto the cloud where they treated cloud significantly as an infrastructure. And the way they started to manage it was again, the same format they were managing there on-prem infrastructure and they call it I&O, Infrastructure and Operations. That's kind of the way traditionally cloud is managed. In the last few years, we are seeing a significant shift around thinking of cloud more as a workload rather than as just an infrastructure. And what I mean by workload is in the cloud, everything is now code. So you are codifying your infrastructure. Your application is already code and your data is also codified as data services. With now that context apply the way you think about managing the cloud has to significantly change and many companies are moving towards trying to change their models to look at this complex environment as opposed to treating it like a simple infrastructure that is sitting somewhere else. So that's one of the biggest changes and shifts that are causing a lot of complexity and headache for actually a lot of customers for managing environments. The second critical aspect is even that, even exasperates the situation is multicloud environments. Now, there are companies that have got it right with things about right cloud for the right workload. So there are companies that I reach out and I talk with. They've got their office applications and emails and stuff running on Microsoft 365 which can be on the Azure cloud whereas they're running their engineering applications the ones that they build and leverage for their end customers on Amazon. And to some extent they've got it right but still they have a multiple cloud that they have to go after and maintain. This becomes complex when you have two clouds for the same type of workload. When I have to host applications for my end customers on Amazon as well as Azure, Azure as well as Google then, I get into security issues that I have to be consistent across all three. I get into talent because I need to have people that focus on Amazon as well as Azure, as well as Google which means I need so much more workforce, I need so many so much more skills that I need to build, right? That's becoming the second issue. The third one is around data costs. Can I make these clouds talk to each other? Then you get into the ingress egress cost and that creates some complexity. So bringing all of this together and managing is really become becoming more complex for our customers. And obviously as a part of this we will talk about some of the, some of the ideas that we can bring for in managing such complex environments but this is what we are seeing in terms of why the complexity has become a lot more in the last few years. >> Right. A lot of complexity in the last few years. Manoj, let's bring you into the conversation now. Before we dig into your cloud environment give the audience a little bit of an overview of GTCR. What kind of company are you? What do you guys do? >> Definitely Lisa. GTCR is a Chicago based private equity firm. We've been in the market for more than 40 years and what we do is we invest in companies across different sectors and then we manage the company drive it to increase the value and then over a period of time, sell it to future buyers. So in a nutshell, we got a large portfolio of companies that we need to manage and make sure that they perform to expectations. And my role within GTCR is from a technology viewpoint so where I work with all the companies their technology leadership to make sure that we are getting the best out of technology and technology today drives everything. So how can technology be a good compliment to the business itself? So, my role is to play that intermediary role to make sure that there is synergy between the investment thesis and the technology lures that we can pull and also work with partners like Hitachi to make sure that it is done in an optimal manner. >> I like that you said, you know, technology needs to really compliment the business and vice versa. So Manoj, let's get into the cloud operations environment at GTCR. Talk to me about what the experience has been the last couple of years. Give us an idea of some of the challenges that you were facing with existing cloud ops and and the solution that you're using from Hitachi Vantara. >> A a absolutely. In fact, in fact Prem phrased it really well, one of the key things that we're facing is the workload management. So there's so many choices there, so much complexities. We have these companies buying more companies there is organic growth that is happening. So the variables that we have to deal with are very high in such a scenario to make sure that the workload management of each of the companies are done in an optimal manner is becoming an increasing concern. So, so that's one area where any help we can get anything we can try to make sure it is done better becomes a huge value at each. A second aspect is a financial transparency. We need to know where the money is going where the money is coming in from, what is the scale especially in the cloud environment. We are talking about an auto scale ecosystem. Having that financial transparency and the metrics associated with that, it, these these become very, very critical to ensure that we have a successful presence in the multicloud environment. >> Talk a little bit about the solution that you're using with Hitachi and, and the challenges that it is eradicated. >> Yeah, so it end of the day, right, we we need to focus on our core competence. So, so we have got a very strong technology leadership team. We've got a very strong presence in the respective domains of each of the portfolio companies. But where Hitachi comes in and HAR comes in as a solution is that they allow us to excel in focusing on our core business and then make sure that we are able to take care of workload management or financial transparency. All of that is taken off the table from us and and Hitachi manages it for us, right? So it's such a perfectly compliment relationship where they act as two partners and HARC is a solution that is extremely useful in driving that. And, and and I'm anticipating that it'll become more important with time as the complexity of cloud and cloud associate workloads are only becoming more challenging to manage and not less. >> Right? That's the thing that complexity is there and it's also increasing Prem, you talked about the complexities that are existent today with respect to cloud operations the things that have happened over the last couple of years. What are some of your tips, Prem for the audience, like the the top two or three things that you would say on cloud operations that that people need to understand so that they can manage that complexity and allow their business to be driven and complimented by technology? >> Yeah, a big great question again, Lisa, right? And I think Manoj alluded to a few of these things as well. The first one is in the new world of the cloud I think think of migration, modernization and management as a single continuum to the cloud. Now there is no lift and shift and there is no way somebody else separately manages it, right? If you do not lift and shift the right applications the right way onto the cloud, you are going to deal with the complexity of managing it and you'll end up spending more money time and effort in managing it. So that's number one. Migration, modernization, management of cloud work growth is a single continuum and it's not three separate activities, right? That's number one. And the, the second is cost. Cost traditionally has been an afterthought, right? People move the workload to the cloud. And I think, again, like I said, I'll refer back to what Manoj said once we move it to the cloud and then we put all these fancy engineering capability around self-provisioning, every developer can go and ask for what he or she wants and they get an environment immediately spun up so on and so forth. Suddenly the CIO wakes up to a bill that is significantly larger than what he or she expected right? And, and this is this is become a bit common nowadays, right? The the challenge is because we think cost in the cloud as an afterthought. But consider this example in, in previous world you buy hard, well, you put it in your data center you have already amortized the cost as a CapEx. So you can write an application throw it onto the infrastructure and the application continues to use the infrastructure until you hit a ceiling, you don't care about the money you spent. But if I write a line of code that is inefficient today and I deploy it on the cloud from minute one, I am paying for the inefficiency. So if I realize it after six months, I've already spent the money. So financial discipline, especially when managing the cloud is now is no more an afterthought. It is as much something that you have to include in your engineering practice as much as any other DevOps practices, right? Those are my top two tips, Lisa, from my standpoint, think about cloud, think about cloud work, cloud workloads. And the last one again, and you will see you will hear me saying this again and again, get into the mindset of everything is code. You don't have a touch and feel infrastructure anymore. So you don't really need to have foot on the ground to go manage that infrastructure. It's codified. So your code should be managing it, but think of how it happens, right? That's where we, we are going as an evolution >> Everything is code. That's great advice, great tips for the audience there. Manoj, I'll bring you back into the conversation. You know, we, we can talk about skills gaps on on in many different facets of technology the SRE role, relatively new, skillset. We're hearing, hearing a lot about it. SRE led DevSecOps is probably even more so of a new skillset. If I'm an IT leader or an application leader how do I ensure that I have the right skillset within my organization to be able to manage my cloud operations to, to dial down that complexity so that I can really operate successfully as a business? >> Yeah. And so unfortunately there is no perfect answer, right? It's such a, such a scarce skillset that a, any day any of the portfolio company CTOs if I go and talk and say, Hey here's a great SRE team member, they'll be more than willing to fight with each of to get the person in right? It's just that scarce of a skillset. So, so a few things we need to look at it. One is, how can I build it within, right? So nobody gets born as an SRE, you, you make a person an SRE. So how do you inculcate that culture? So like Prem said earlier, right? Everything is software. So how do we make sure that everybody inculcates that as part of their operating philosophy be they part of the operations team or the development team or the testing team they need to understand that that is a common guideline and common objective that we are driving towards. So, so that skillset and that associated training needs to be driven from within the organization. And that in my mind is the fastest way to make sure that that role gets propagated across organization. That is one. The second thing is rely on the right partners. So it's not going to be possible for us, to get all of these roles built in-house. So instead prioritize what roles need to be done from within the organization and what roles can we rely on our partners to drive it for us. So that becomes an important consideration for us to look at as well. >> Absolutely. That partnership angle is incredibly important from, from the, the beginning really kind of weaving these companies together on this journey to to redefine cloud operations and build that, as we talked about at the beginning of the conversation really building a cloud center of excellence that allows the organization to be competitive, successful and and really deliver what the end user is, is expecting. I want to ask - Sorry Lisa, - go ahead. >> May I add something to it, I think? >> Sure. >> Yeah. One of the, one of the common things that I tell customers when we talk about SRE and to manages point is don't think of SRE as a skillset which is the common way today the industry tries to solve the problem. SRE is a mindset, right? Everybody in >> Well well said, yeah >> That, so everybody in a company should think of him or her as a cycle liability engineer. And everybody has a role in it, right? Even if you take the new process layout from SRE there are individuals that are responsible to whom we can go to when there is a problem directly as opposed to going through the traditional ways of AI talk to L one and L one contras all. They go to L two and then L three. So we, we, we are trying to move away from an issue escalation model to what we call as a a issue routing or a incident routing model, right? Move away from incident escalation to an incident routing model. So you get to route to the right folks. So again, to sum it up, SRE should not be solved as a skillset set because there is not enough people in the market to solve it that way. If you start solving it as a mindset I think companies can get a handhold of it. >> I love that. I've actually never heard that before, but it it makes perfect sense to think about the SRE as a mindset rather than a skillset that will allow organizations to be much more successful. Prem I wanted to get your thoughts as enterprises are are innovating, they're moving more products and services to the as a service model. Talk about how the dev teams the ops teams are working together to build and run reliable, cost efficient services. Are they working better together? >> Again, a a very polarizing question because some customers are getting it right many customers aren't, there is still a big wall between development and operations, right? Even when you think about DevOps as a terminology the fundamental principle was to make sure dev and ops works together. But what many companies have achieved today, honestly is automating the operations for development. For example, as a developer, I can check in code and my code will appear in production without any friction, right? There is automated testing, automated provisioning and it gets promoted to production, but after production, it goes back into the 20 year old model of operating the code, right? So there is more work that needs to be done for Devon and Ops to come closer and work together. And one of the ways that we think this is achievable is not by doing radical org changes, but more by focusing on a product-oriented single backlog approach across development and operations. Which is, again, there is change management involved but I think that's a way to start embracing the culture of dev ops coming together much better now, again SRE principles as we double click and understand it more and Google has done a very good job playing it out for the world. As you think about SRE principle, there are ways and means in that process of how to think about a single backlog. And in HARC, Hitachi Application Reliability Centers we've really got a way to look at prioritizing the backlog. And what I mean by that is dev teams try to work on backlog that come from product managers on features. The SRE and the operations team try to put backlog into the say sorry, try to put features into the same backlog for improving stability, availability and financials financial optimization of your code. And there are ways when you look at your SLOs and error budgets to really coach the product teams to prioritize your backlog based on what's important for you. So if you understand your spending more money then you reduce your product features going in and implement the financial optimization that came from your operations team, right? So you now have the ability to throttle these parameters and that's where SRE becomes a mindset and a principle as opposed to a skillset because this is not an individual telling you to do. This is the company that is, is embarking on how to prioritize my backlog beyond just user features. >> Right. Great point. Last question for both of you is the same talk kind of take away things that you want me to remember. If I am at an IT leader at, at an organization and I am planning on redefining CloudOps for my company Manoj will start with you and then Prem to you what are the top two things that you want me to walk away with understanding how to do that successfully? >> Yeah, so I'll, I'll go back to basics. So the two things I would say need to be taken care of is, one is customer experience. So all the things that I do end of the day is it improving the customer experience or not? So that's a first metric. The second thing is anything that I do is there an ROI by doing that incremental step or not? Otherwise we might get lost in the technology with surgery, the new tech, et cetera. But end of the day, if the customers are not happy if there is no ROI, everything else you just can't do much on top of that >> Now it's all about the customer experience. Right? That's so true. Prem what are your thoughts, the the top things that I need to be taking away if I am a a leader planning to redefine my cloud eye company? >> Absolutely. And I think from a, from a company standpoint I think Manoj summarized it extremely well, right? There is this ROI and there is this customer experience from my end, again, I'll, I'll suggest two two more things as a takeaway, right? One, cloud cost is not an afterthought. It's essential for us to think about it upfront. Number two, do not delink migration modernization and operations. They are one stream. If you migrate a long, wrong workload onto the cloud you're going to be stuck with it for a long time. And an example of a wrong workload, Lisa for everybody that that is listening to this is if my cost per transaction profile doesn't change and I am not improving my revenue per transaction for a piece of code that's going run in production it's better off running in a data center where my cost is CapEx than amortized and I have control over when I want to upgrade as opposed to putting it on a cloud and continuing to pay unless it gives me more dividends towards improvement. But that's a simple example of when we think about what should I migrate and how will it cost pain when I want to manage it in the longer run. But that's, that's something that I'll leave the audience and you with as a takeaway. >> Excellent. Guys, thank you so much for talking to me today about what Hitachi Vantara and GTCR are doing together how you've really dialed down those complexities enabling the business and the technology folks to really live harmoniously. We appreciate your insights and your perspectives on building a cloud center of excellence. Thank you both for joining me. >> Thank you. >> For my guests, I'm Lisa. Martin, you're watching this event building Your Cloud Center of Excellence with Hitachi Vantara. Thanks for watching. (Upbeat music playing) (Upbeat music playing) (Upbeat music playing) (Upbeat music playing)

(gentle music) >> Narrator: "TheCUBE's" live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) >> Hello everybody, welcome back to day four of "theCUBE's" coverage of MWC '23. We're here live at the Fira in Barcelona. Wall-to-wall coverage, John Furrier is in our Palo Alto studio, banging out all the news. Really, the whole week we've been talking about the disaggregation of the telco network, the new opportunities in telco. We're really excited to have AT&T and Snowflake here. Dave Whittington is the AVP, at the Chief Data Office at AT&T. Roddy Tranum is the Assistant Vice President, for Channel Performance Data and Tools at AT&T. And Phil Kippen, the Global Head Of Industry-Telecom at Snowflake, Snowflake's new telecom business. Snowflake just announced earnings last night. Typical Scarpelli, they beat earnings, very conservative guidance, stocks down today, but we like Snowflake long term, they're on that path to 10 billion. Guys, welcome to "theCUBE." Thanks so much >> Phil: Thank you. >> for coming on. >> Dave and Roddy: Thanks Dave. >> Dave, let's start with you. The data culture inside of telco, We've had this, we've been talking all week about this monolithic system. Super reliable. You guys did a great job during the pandemic. Everything shifting to landlines. We didn't even notice, you guys didn't miss a beat. Saved us. But the data culture's changing inside telco. Explain that. >> Well, absolutely. So, first of all IoT and edge processing is bringing forth new and exciting opportunities all the time. So, we're bridging the world between a lot of the OSS stuff that we can do with edge processing. But bringing that back, and now we're talking about working, and I would say traditionally, we talk data warehouse. Data warehouse and big data are now becoming a single mesh, all right? And the use cases and the way you can use those, especially I'm taking that edge data and bringing it back over, now I'm running AI and ML models on it, and I'm pushing back to the edge, and I'm combining that with my relational data. So that mesh there is making all the difference. We're getting new use cases that we can do with that. And it's just, and the volume of data is immense. >> Now, I love ChatGPT, but I'm hoping your data models are more accurate than ChatGPT. I never know. Sometimes it's really good, sometimes it's really bad. But enterprise, you got to be clean with your AI, don't you? >> Not only you have to be clean, you have to monitor it for bias and be ethical about it. We're really good about that. First of all with AT&T, our brand is Platinum. We take care of that. So, we may not be as cutting-edge risk takers as others, but when we go to market with an AI or an ML or a product, it's solid. >> Well hey, as telcos go, you guys are leaning into the Cloud. So I mean, that's a good starting point. Roddy, explain your role. You got an interesting title, Channel Performance Data and Tools, what's that all about? >> So literally anything with our consumer, retail, concenters' channels, all of our channels, from a data perspective and metrics perspective, what it takes to run reps, agents, all the way to leadership levels, scorecards, how you rank in the business, how you're driving the business, from sales, service, customer experience, all that data infrastructure with our great partners on the CDO side, as well as Snowflake, that comes from my team. >> And that's traditionally been done in a, I don't mean the pejorative, but we're talking about legacy, monolithic, sort of data warehouse technologies. >> Absolutely. >> We have a love-hate relationship with them. It's what we had. It's what we used, right? And now that's evolving. And you guys are leaning into the Cloud. >> Dramatic evolution. And what Snowflake's enabled for us is impeccable. We've talked about having, people have dreamed of one data warehouse for the longest time and everything in one system. Really, this is the only way that becomes a reality. The more you get in Snowflake, we can have golden source data, and instead of duplicating that 50 times across AT&T, it's in one place, we just share it, everybody leverages it, and now it's not duplicated, and the process efficiency is just incredible. >> But it really hinges on that separation of storage and compute. And we talk about the monolithic warehouse, and one of the nightmares I've lived with, is having a monolithic warehouse. And let's just go with some of my primary, traditional customers, sales, marketing and finance. They are leveraging BSS OSS data all the time. For me to coordinate a deployment, I have to make sure that each one of these units can take an outage, if it's going to be a long deployment. With the separation of storage, compute, they own their own compute cluster. So I can move faster for these people. 'Cause if finance, I can implement his code without impacting finance or marketing. This brings in CI/CD to more reality. It brings us faster to market with more features. So if he wants to implement a new comp plan for the field reps, or we're reacting to the marketplace, where one of our competitors has done something, we can do that in days, versus waiting weeks or months. >> And we've reported on this a lot. This is the brilliance of Snowflake's founders, that whole separation >> Yep. >> from compute and data. I like Dave, that you're starting with sort of the business flexibility, 'cause there's a cost element of this too. You can dial down, you can turn off compute, and then of course the whole world said, "Hey, that's a good idea." And a VC started throwing money at Amazon, but Redshift said, "Oh, we can do that too, sort of, can't turn off the compute." But I want to ask you Phil, so, >> Sure. >> it looks from my vantage point, like you're taking your Data Cloud message which was originally separate compute from storage simplification, now data sharing, automated governance, security, ultimately the marketplace. >> Phil: Right. >> Taking that same model, break down the silos into telecom, right? It's that same, >> Mm-hmm. >> sorry to use the term playbook, Frank Slootman tells me he doesn't use playbooks, but he's not a pattern matcher, but he's a situational CEO, he says. But the situation in telco calls for that type of strategy. So explain what you guys are doing in telco. >> I think there's, so, what we're launching, we launched last week, and it really was three components, right? So we had our platform as you mentioned, >> Dave: Mm-hmm. >> and that platform is being utilized by a number of different companies today. We also are adding, for telecom very specifically, we're adding capabilities in marketplace, so that service providers can not only use some of the data and apps that are in marketplace, but as well service providers can go and sell applications or sell data that they had built. And then as well, we're adding our ecosystem, it's telecom-specific. So, we're bringing partners in, technology partners, and consulting and services partners, that are very much focused on telecoms and what they do internally, but also helping them monetize new services. >> Okay, so it's not just sort of generic Snowflake into telco? You have specific value there. >> We're purposing the platform specifically for- >> Are you a telco guy? >> I am. You are, okay. >> Total telco guy absolutely. >> So there you go. You see that Snowflake is actually an interesting organizational structure, 'cause you're going after verticals, which is kind of rare for a company of your sort of inventory, I'll say, >> Absolutely. >> I don't mean that as a negative. (Dave laughs) So Dave, take us through the data journey at AT&T. It's a long history. You don't have to go back to the 1800s, but- (Dave laughs) >> Thank you for pointing out, we're a 149-year-old company. So, Jesse James was one of the original customers, (Dave laughs) and we have no longer got his data. So, I'll go back. I've been 17 years singular AT&T, and I've watched it through the whole journey of, where the monolithics were growing, when the consolidation of small, wireless carriers, and we went through that boom. And then we've gone through mergers and acquisitions. But, Hadoop came out, and it was going to solve all world hunger. And we had all the aspects of, we're going to monetize and do AI and ML, and some of the things we learned with Hadoop was, we had this monolithic warehouse, we had this file-based-structured Hadoop, but we really didn't know how to bring this all together. And we were bringing items over to the relational, and we were taking the relational and bringing it over to the warehouse, and trying to, and it was a struggle. Let's just go there. And I don't think we were the only company to struggle with that, but we learned a lot. And so now as tech is finally emerging, with the cloud, companies like Snowflake, and others that can handle that, where we can create, we were discussing earlier, but it becomes more of a conducive mesh that's interoperable. So now we're able to simplify that environment. And the cloud is a big thing on that. 'Cause you could not do this on-prem with on-prem technologies. It would be just too cost prohibitive, and too heavy of lifting, going back and forth, and managing the data. The simplicity the cloud brings with a smaller set of tools, and I'll say in the data space specifically, really allows us, maybe not a single instance of data for all use cases, but a greatly reduced ecosystem. And when you simplify your ecosystem, you simplify speed to market and data management. >> So I'm going to ask you, I know it's kind of internal organizational plumbing, but it'll inform my next question. So, Dave, you're with the Chief Data Office, and Roddy, you're kind of, you all serve in the business, but you're really serving the, you're closer to those guys, they're banging on your door for- >> Absolutely. I try to keep the 130,000 users who may or may not have issues sometimes with our data and metrics, away from Dave. And he just gets a call from me. >> And he only calls when he has a problem. He's never wished me happy birthday. (Dave and Phil laugh) >> So the reason I asked that is because, you describe Dave, some of the Hadoop days, and again love-hate with that, but we had hyper-specialized roles. We still do. You've got data engineers, data scientists, data analysts, and you've got this sort of this pipeline, and it had to be this sequential pipeline. I know Snowflake and others have come to simplify that. My question to you is, how is that those roles, how are those roles changing? How is data getting closer to the business? Everybody talks about democratizing business. Are you doing that? What's a real use example? >> From our perspective, those roles, a lot of those roles on my team for years, because we're all about efficiency, >> Dave: Mm-hmm. >> we cut across those areas, and always have cut across those areas. So now we're into a space where things have been simplified, data processes and copying, we've gone from 40 data processes down to five steps now. We've gone from five steps to one step. We've gone from days, now take hours, hours to minutes, minutes to seconds. Literally we're seeing that time in and time out with Snowflake. So these resources that have spent all their time on data engineering and moving data around, are now freed up more on what they have skills for and always have, the data analytics area of the business, and driving the business forward, and new metrics and new analysis. That's some of the great operational value that we've seen here. As this simplification happens, it frees up brain power. >> So, you're pumping data from the OSS, the BSS, the OKRs everywhere >> Everywhere. >> into Snowflake? >> Scheduling systems, you name it. If you can think of what drives our retail and centers and online, all that data, scheduling system, chat data, call center data, call detail data, all of that enters into this common infrastructure to manage the business on a day in and day out basis. >> How are the roles and the skill sets changing? 'Cause you're doing a lot less ETL, you're doing a lot less moving of data around. There were guys that were probably really good at that. I used to joke in the, when I was in the storage world, like if your job is bandaging lungs, you need to look for a new job, right? So, and they did and people move on. So, are you able to sort of redeploy those assets, and those people, those human resources? >> These folks are highly skilled. And we were talking about earlier, SQL hasn't gone away. Relational databases are not going away. And that's one thing that's made this migration excellent, they're just transitioning their skills. Experts in legacy systems are now rapidly becoming experts on the Snowflake side. And it has not been that hard a transition. There are certainly nuances, things that don't operate as well in the cloud environment that we have to learn and optimize. But we're making that transition. >> Dave: So just, >> Please. >> within the Chief Data Office we have a couple of missions, and Roddy is a great partner and an example of how it works. We try to bring the data for democratization, so that we have one interface, now hopefully know we just have a logical connection back to these Snowflake instances that we connect. But we're providing that governance and cleansing, and if there's a business rule at the enterprise level, we provide it. But the goal at CDO is to make sure that business units like Roddy or marketing or finance, that they can come to a platform that's reliable, robust, and self-service. I don't want to be in his way. So I feel like I'm providing a sub-level of platform, that he can come to and anybody can come to, and utilize, that they're not having to go back and undo what's in Salesforce, or ServiceNow, or in our billers. So, I'm sort of that layer. And then making sure that that ecosystem is robust enough for him to use. >> And that self-service infrastructure is predominantly through the Azure Cloud, correct? >> Dave: Absolutely. >> And you work on other clouds, but it's predominantly through Azure? >> We're predominantly in Azure, yeah. >> Dave: That's the first-party citizen? >> Yeah. >> Okay, I like to think in terms sometimes of data products, and I know you've mentioned upfront, you're Gold standard or Platinum standard, you're very careful about personal information. >> Dave: Yeah. >> So you're not trying to sell, I'm an AT&T customer, you're not trying to sell my data, and make money off of my data. So the value prop and the business case for Snowflake is it's simpler. You do things faster, you're in the cloud, lower cost, et cetera. But I presume you're also in the business, AT&T, of making offers and creating packages for customers. I look at those as data products, 'cause it's not a, I mean, yeah, there's a physical phone, but there's data products behind it. So- >> It ultimately is, but not everybody always sees it that way. Data reporting often can be an afterthought. And we're making it more on the forefront now. >> Yeah, so I like to think in terms of data products, I mean even if the financial services business, it's a data business. So, if we can think about that sort of metaphor, do you see yourselves as data product builders? Do you have that, do you think about building products in that regard? >> Within the Chief Data Office, we have a data product team, >> Mm-hmm. >> and by the way, I wouldn't be disingenuous if I said, oh, we're very mature in this, but no, it's where we're going, and it's somewhat of a journey, but I've got a peer, and their whole job is to go from, especially as we migrate from cloud, if Roddy or some other group was using tables three, four and five and joining them together, it's like, "Well look, this is an offer for data product, so let's combine these and put it up in the cloud, and here's the offer data set product, or here's the opportunity data product," and it's a journey. We're on the way, but we have dedicated staff and time to do this. >> I think one of the hardest parts about that is the organizational aspects of it. Like who owns the data now, right? It used to be owned by the techies, and increasingly the business lines want to have access, you're providing self-service. So there's a discussion about, "Okay, what is a data product? Who's responsible for that data product? Is it in my P&L or your P&L? Somebody's got to sign up for that number." So, it sounds like those discussions are taking place. >> They are. And, we feel like we're more the, and CDO at least, we feel more, we're like the guardians, and the shepherds, but not the owners. I mean, we have a role in it all, but he owns his metrics. >> Yeah, and even from our perspective, we see ourselves as an enabler of making whatever AT&T wants to make happen in terms of the key products and officers' trade-in offers, trade-in programs, all that requires this data infrastructure, and managing reps and agents, and what they do from a channel performance perspective. We still ourselves see ourselves as key enablers of that. And we've got to be flexible, and respond quickly to the business. >> I always had empathy for the data engineer, and he or she had to service all these different lines of business with no business context. >> Yeah. >> Like the business knows good data from bad data, and then they just pound that poor individual, and they're like, "Okay, I'm doing my best. It's just ones and zeros to me." So, it sounds like that's, you're on that path. >> Yeah absolutely, and I think, we do have refined, getting more and more refined owners of, since Snowflake enables these golden source data, everybody sees me and my organization, channel performance data, go to Roddy's team, we have a great team, and we go to Dave in terms of making it all happen from a data infrastructure perspective. So we, do have a lot more refined, "This is where you go for the golden source, this is where it is, this is who owns it. If you want to launch this product and services, and you want to manage reps with it, that's the place you-" >> It's a strong story. So Chief Data Office doesn't own the data per se, but it's your responsibility to provide the self-service infrastructure, and make sure it's governed properly, and in as automated way as possible. >> Well, yeah, absolutely. And let me tell you more, everybody talks about single version of the truth, one instance of the data, but there's context to that, that we are taking, trying to take advantage of that as we do data products is, what's the use case here? So we may have an entity of Roddy as a prospective customer, and we may have a entity of Roddy as a customer, high-value customer over here, which may have a different set of mix of data and all, but as a data product, we can then create those for those specific use cases. Still point to the same data, but build it in different constructs. One for marketing, one for sales, one for finance. By the way, that's where your data engineers are struggling. >> Yeah, yeah, of course. So how do I serve all these folks, and really have the context-common story in telco, >> Absolutely. >> or are these guys ahead of the curve a little bit? Or where would you put them? >> I think they're definitely moving a lot faster than the industry is generally. I think the enabling technologies, like for instance, having that single copy of data that everybody sees, a single pane of glass, right, that's definitely something that everybody wants to get to. Not many people are there. I think, what AT&T's doing, is most definitely a little bit further ahead than the industry generally. And I think the successes that are coming out of that, and the learning experiences are starting to generate momentum within AT&T. So I think, it's not just about the product, and having a product now that gives you a single copy of data. It's about the experiences, right? And now, how the teams are getting trained, domains like network engineering for instance. They typically haven't been a part of data discussions, because they've got a lot of data, but they're focused on the infrastructure. >> Mm. >> So, by going ahead and deploying this platform, for platform's purpose, right, and the business value, that's one thing, but also to start bringing, getting that experience, and bringing new experience in to help other groups that traditionally hadn't been data-centric, that's also a huge step ahead, right? So you need to enable those groups. >> A big complaint of course we hear at MWC from carriers is, "The over-the-top guys are killing us. They're riding on our networks, et cetera, et cetera. They have all the data, they have all the client relationships." Do you see your client relationships changing as a result of sort of your data culture evolving? >> Yes, I'm not sure I can- >> It's a loaded question, I know. >> Yeah, and then I, so, we want to start embedding as much into our network on the proprietary value that we have, so we can start getting into that OTT play, us as any other carrier, we have distinct advantages of what we can do at the edge, and we just need to start exploiting those. But you know, 'cause whether it's location or whatnot, so we got to eat into that. Historically, the network is where we make our money in, and we stack the services on top of it. It used to be *69. >> Dave: Yeah. >> If anybody remembers that. >> Dave: Yeah, of course. (Dave laughs) >> But you know, it was stacked on top of our network. Then we stack another product on top of it. It'll be in the edge where we start providing distinct values to other partners as we- >> I mean, it's a great business that you're in. I mean, if they're really good at connectivity. >> Dave: Yeah. >> And so, it sounds like it's still to be determined >> Dave: Yeah. >> where you can go with this. You have to be super careful with private and for personal information. >> Dave: Yep. >> Yeah, but the opportunities are enormous. >> There's a lot. >> Yeah, particularly at the edge, looking at, private networks are just an amazing opportunity. Factories and name it, hospital, remote hospitals, remote locations. I mean- >> Dave: Connected cars. >> Connected cars are really interesting, right? I mean, if you start communicating car to car, and actually drive that, (Dave laughs) I mean that's, now we're getting to visit Xen Fault Tolerance people. This is it. >> Dave: That's not, let's hold the traffic. >> Doesn't scare me as much as we actually learn. (all laugh) >> So how's the show been for you guys? >> Dave: Awesome. >> What're your big takeaways from- >> Tremendous experience. I mean, someone who doesn't go outside the United States much, I'm a homebody. The whole experience, the whole trip, city, Mobile World Congress, the technologies that are out here, it's been a blast. >> Anything, top two things you learned, advice you'd give to others, your colleagues out in general? >> In general, we talked a lot about technologies today, and we talked a lot about data, but I'm going to tell you what, the accelerator that you cannot change, is the relationship that we have. So when the tech and the business can work together toward a common goal, and it's a partnership, you get things done. So, I don't know how many CDOs or CIOs or CEOs are out there, but this connection is what accelerates and makes it work. >> And that is our audience Dave. I mean, it's all about that alignment. So guys, I really appreciate you coming in and sharing your story in "theCUBE." Great stuff. >> Thank you. >> Thanks a lot. >> All right, thanks everybody. Thank you for watching. I'll be right back with Dave Nicholson. Day four SiliconANGLE's coverage of MWC '23. You're watching "theCUBE." (gentle music)

>> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Hi everybody. Welcome back to Barcelona. We're here at the Fira Live, theCUBE's ongoing coverage of day two of MWC 23. Back in 2021 was my first Mobile World Congress. And you know what? It was actually quite an experience because there was nobody there. I talked to my friend, who's now my co-host, Chris Lewis about what to expect. He said, Dave, I don't think a lot of people are going to be there, but Danielle Royston is here and she's the CEO of Totoge. And that year when Erickson tapped out of its space she took out 60,000 square feet and built out Cloud City. If it weren't for Cloud City, there would've been no Mobile World Congress in June and July of 2021. DR is back. Great to see you. Thanks for coming on. >> It's great to see you. >> Chris. Awesome to see you. >> Yeah, Chris. Yep. >> Good to be back. Yep. >> You guys remember the narrative back then. There was this lady running around this crazy lady that I met at at Google Cloud next saying >> Yeah. Yeah. >> the cloud's going to take over Telco. And everybody's like, well, this lady's nuts. The cloud's been leaning in, you know? >> Yeah. >> So what do you think, I mean, what's changed since since you first caused all those ripples? >> I mean, I have to say that I think that I caused a lot of change in the industry. I was talking to leaders over at AWS yesterday and they were like, we've never seen someone push like you have and change so much in a short period of time. And Telco moves slow. It's known for that. And they're like, you are pushing buttons and you're getting people to change and thank you and keep going. And so it's been great. It's awesome. >> Yeah. I mean, it was interesting, Chris, we heard on the keynotes we had Microsoft, Satya came in, Thomas Curian came in. There was no AWS. And now I asked CMO of GSMA about that. She goes, hey, we got a great relationship with it, AWS. >> Danielle: Yeah. >> But why do you think they weren't here? >> Well, they, I mean, they are here. >> Mean, not here. Why do you think they weren't profiled? >> They weren't on the keynote stage. >> But, you know, at AWS, a lot of the times they want to be the main thing. They want to be the main part of the show. They don't like sharing the limelight. I think they just didn't want be on the stage with the Google CLoud guys and the these other guys, what they're doing they're building out, they're doing so much stuff. As Danielle said, with Telcos change in the ecosystem which is what's happening with cloud. Cloud's making the Telcos think about what the next move is, how they fit in with the way other people do business. Right? So Telcos never used to have to listen to anybody. They only listened to themselves and they dictated the way things were done. They're very successful and made a lot of money but they're now having to open up they're having to leverage the cloud they're having to leverage the services that (indistinct words) and people out provide and they're changing the way they work. >> So, okay in 2021, we talked a lot about the cloud as a potential disruptor, and your whole premise was, look you got to lean into the cloud, or you're screwed. >> Danielle: Yeah. >> But the flip side of that is, if they lean into the cloud too much, they might be screwed. >> Danielle: Yeah. >> So what's that equilibrium? Have they been able to find it? Are you working with just the disruptors or how's that? >> No I think they're finding it right. So my talk at MWC 21 was all about the cloud is a double-edged sword, right? There's two sides to it, and you definitely need to proceed through it with caution, but also I don't know that you have a choice, right? I mean, the multicloud, you know is there another industry that spends more on CapEx than Telco? >> No. >> Right. The hyperscalers are doing it right. They spend, you know, easily approaching over a $100 billion in CapEx that rivals this industry. And so when you have a player like that an industry driving, you know and investing so much Telco, you're always complaining how everyone's riding your coattails. This is the opportunity to write someone else's coattails. So jump on, right? I think you don't have a choice especially if other Telco competitors are using hyperscalers and you don't, they're going to be left behind. >> So you advise these companies all the time, but >> I mean, the issue is they're all they're all using all the hyperscalers, right? So they're the multi, the multiple relationships. And as Danielle said, the multi-layer of relationship they're using the hyperscalers to change their own internal operational environments to become more IT-centric to move to that software centric Telco. And they're also then with the hyperscalers going to market in different ways sometimes with them, sometimes competing with them. What what it means from an analyst point of view is you're suddenly changing the dynamic of a market where we used to have nicely well defined markets previously. Now they're, everyone's in it together, you know, it's great. And, and it's making people change the way they think about services. What I, what I really hope it changes more than anything else is the way the customers at the end of the, at the end of the supply, the value chain think this is what we can get hold of this stuff. Now we can go into the network through the cloud and we can get those APIs. We can draw on the mechanisms we need to to run our personal lives, to run our business lives. And frankly, society as a whole. It's really exciting. >> Then your premise is basically you were saying they should ride on the top over the top of the cloud vendor. >> Yeah. Right? >> No. Okay. But don't they lose the, all the data if they do that? >> I don't know. I mean, I think the hyperscalers are not going to take their data, right? I mean, that would be a really really bad business move if Google Cloud and Azure and and AWS start to take over that, that data. >> But they can't take it. >> They can't. >> From regulate, from sovereignty and regulation. >> They can't because of regulation, but also just like business, right? If they started taking their data and like no enterprises would use them. So I think, I think the data is safe. I think you, obviously every country is different. You got to understand the different rules and regulations for data privacy and, and how you keep it. But I think as we look at the long term, right and we always talk about 10 and 20 years there's going to be a hyperscaler region in every country right? And there will be a way for every Telco to use it. I think their data will be safe. And I think it just, you're going to be able to stand on on the shoulders of someone else for once and use the building blocks of software that these guys provide to make better experiences for subscribers. >> You guys got to explain this to me because when I say data I'm not talking about, you know, personal information. I'm talking about all the telemetry, you know, all the all the, you know the plumbing. >> Danielle: Yeah. >> Data, which is- >> It will increasingly be shared because you need to share it in order to deliver the services in the streamline efficient way that needs to be deliver. >> Did I hear the CEO of Ericsson Wright where basically he said, we're going to charge developers for access to that data through APIs. >> What the Ericsson have done, obviously with the Vage acquisition is they want to get into APIs. So the idea is you're exposing features, quality policy on demand type features for example, or even pulling we still use that a lot of SMS, right? So pulling those out using those APIs. So it will be charged in some way. Whether- >> Man: Like Twitter's charging me for APIs, now I API calls, you >> Know what it is? I think it's Twilio. >> Man: Oh, okay. >> Right. >> Man: No, no, that's sure. >> There's no reason why telcos couldn't provide a Twilio like service itself. >> It's a horizontal play though right? >> Danielle: Correct because developers need to be charged by the API. >> But doesn't there need to be an industry standard to do that as- >> Well. I think that's what they just announced. >> Industry standard. >> Danielle: I think they just announced that. Yeah. Right now I haven't looked at that API set, right? >> There's like eight of them. >> There's eight of them. Twilio has, it's a start you got to start somewhere Dave. (crosstalk) >> And there's all, the TM forum is all the other standard >> Right? Eight is better than zero- >> Right? >> Haven't got plenty. >> I mean for an industry that didn't really understand APIs as a feature, as a product as a service, right? For Mats Granryd, the deputy general of GSMA to stand on the keynote stage and say we partnered and we're unveiling, right. Pay by the use APIs. I was for it. I was like, that is insane. >> I liked his keynote actually, because I thought he was going to talk about how many attendees and how much economic benefiting >> Danielle: We're super diverse. >> He said, I would usually talk about that and you know greening in the network by what you did talk about a little bit. But, but that's, that surprised me. >> Yeah. >> But I've seen in the enterprise this is not my space as, you know, you guys don't live this but I've seen Oracle try to get developers. IBM had to pay $35 billion trying to get for Red Hat to get developers, right? EMC used to have a thing called EMC code, failed. >> I mean they got to do something, right? So 4G they didn't really make the business case the ROI on the investment in the network. Here we are with 5G, same discussion is having where's the use case? How are we going to monetize and make the ROI on this massive investment? And now they're starting to talk about 6G. Same fricking problem is going to happen again. And so I think they need to start experimenting with new ideas. I don't know if it's going to work. I don't know if this new a API network gateway theme that Mats talked about yesterday will work. But they need to start unbundling that unlimited plan. They need to start charging people who are using the network more, more money. Those who are using it less, less. They need to figure this out. This is a crisis for them. >> Yeah our own CEO, I mean she basically said, Hey, I'm for net neutrality, but I want to be able to charge the people that are using it more and more >> To make a return on, on a capital. >> I mean it costs billions of dollars to build these networks, right? And they're valuable. We use them and we talked about this in Cloud City 21, right? The ability to start building better metaverses. And I know that's a buzzword and everyone hates it, but it's true. Like we're working from home. We need- there's got to be a better experience in Zoom in 2D, right? And you need a great network for that metaverse to be awesome. >> You do. But Danielle, you don't need cellular for doing that, do you? So the fixed network is as important. >> Sure. >> And we're at mobile worlds. But actually what we beginning to hear and Crystal Bren did say this exactly, it's about the comp the access is sort of irrelevant. Fixed is better because it's more the cost the return on investment is better from fiber. Mobile we're going to change every so many years because we're a new generation. But we need to get the mechanism in place to deliver that. I actually don't agree that we should everyone should pay differently for what they use. It's a universal service. We need it as individuals. We need to make it sustainable for every user. Let's just not go for the biggest user. It's not, it's not the way to build it. It won't work if you do that you'll crash the system if you do that. And, and the other thing which I disagree on it's not about standing on the shoulders and benefiting from what- It's about cooperating across all levels. The hyperscalers want to work with the telcos as much as the telcos want to work with the hyperscalers. There's a lot of synergy there. There's a lot of ways they can work together. It's not one or the other. >> But I think you're saying let the cloud guys do the heavy lifting and I'm - >> Yeah. >> Not at all. >> And so you don't think so because I feel like the telcos are really good at pipes. They've always been good at pipes. They're engineers. >> Danielle: Yeah. >> Are they hanging on to the to the connectivity or should they let that go and well and go toward the developer. >> I mean AWS had two announcements on the 21st a week before MWC. And one was that telco network builder. This is literally being able to deploy a network capability at AWS with keystrokes. >> As a managed service. >> Danielle: Correct. >> Yeah. >> And so I don't know how the telco world I felt the shock waves, right? I was like, whoa, that seems really big. Because they're taking something that previously was like bread and butter. This is what differentiates each telco and now they've standardized it and made it super easy so anyone can do it. Now do I think the five nines of super crazy hardcore network criteria will be built on AWS this way? Probably not, but no >> It's not, it's not end twin. So you can't, no. >> Right. But private networks could be built with this pretty easily, right? And so telcos that don't have as much funding, right. Smaller, more experiments. I think it's going to change the way we think about building networks in telcos >> And those smaller telcos I think are going to be more developer friendly. >> Danielle: Yeah. >> They're going to have business models that invite those developers in. And that's, it's the disruption's going to come from the ISVs and the workloads that are on top of that. >> Well certainly what Dish is trying to do, right? Dish is trying to build a- they launched it reinvent a developer experience. >> Dave: Yeah. >> Right. Built around their network and you know, again I don't know, they were not part of this group that designed these eight APIs but I'm sure they're looking with great intent on what does this mean for them. They'll probably adopt them because they want people to consume the network as APIs. That's their whole thing that Mark Roanne is trying to do. >> Okay, and then they're doing open ran. But is it- they're not really cons- They're not as concerned as Rakuten with the reliability and is that the right play? >> In this discussion? Open RAN is not an issue. It really is irrelevant. It's relevant for the longer term future of the industry by dis aggregating and being able to share, especially ran sharing, for example, in the short term in rural environments. But we'll see some of that happening and it will change, but it will also influence the way the other, the existing ran providers build their services and offer their value. Look you got to remember in the relationship between the equipment providers and the telcos are very dramatically. Whether it's Ericson, NOKIA, Samsung, Huawei, whoever. So those relations really, and the managed services element to that depends on what skills people have in-house within the telco and what service they're trying to deliver. So there's never one size fits all in this industry. >> You're very balanced in your analysis and I appreciate that. >> I try to be. >> But I am not. (chuckles) >> So when Dr went off, this is my question. When Dr went off a couple years ago on the cloud's going to take over the world, you were skeptical. You gave a approach. Have you? >> I still am. >> Have you moderated your thoughts on that or- >> I believe the telecom industry is is a very strong industry. It's my industry of course I love it. But the relationship it is developing much different relationships with the ecosystem players around it. You mentioned developers, you mentioned the cloud players the equipment guys are changing there's so many moving parts to build the telco of the future that every country needs a very strong telco environment to be able to support the site as a whole. People individuals so- >> Well I think two years ago we were talking about should they or shouldn't they, and now it's an inevitability. >> I don't think we were Danielle. >> All using the hyperscalers. >> We were always going to need to transform the telcos from the conservative environments in which they developed. And they've had control of everything in order to reduce if they get no extra revenue at all, reducing the cost they've got to go on a cloud migration path to do that. >> Amenable. >> Has it been harder than you thought? >> It's been easier than I thought. >> You think it's gone faster than >> It's gone way faster than I thought. I mean pushing on this flywheel I thought for sure it would take five to 10 years it is moving. I mean the maths comp thing the AWS announcements last week they're putting in hyperscalers in Saudi Arabia which is probably one of the most sort of data private places in the world. It's happening really fast. >> What Azure's doing? >> I feel like I can't even go to sleep. Because I got to keep up with it. It's crazy. >> Guys. >> This is awesome. >> So awesome having you back on. >> Yeah. >> Chris, thanks for co-hosting. Appreciate you stay here. >> Yep. >> Danielle, amazing. We'll see you. >> See you soon. >> A lot of action here. We're going to come out >> Great. >> Check out your venue. >> Yeah the Togi buses that are outside. >> The big buses. You got a great setup there. We're going to see you on Wednesday. Thanks again. >> Awesome. Thanks. >> All right. Keep it right there. We'll be back to wrap up day two from MWC 23 on theCUBE. (upbeat music)

>> theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (ambient music) >> Lisa: Hey everyone, welcome back to Barcelona, Spain. It's theCUBE Live at MWC 23. Lisa Martin with Dave Vellante. This is day two of four days of cube coverage but you know that, because you've already been watching yesterday and today. We're going to have a great conversation next with EnterpriseWeb and Red Hat. We've had great conversations the last day and a half about the Telco industry, the challenges, the opportunities. We're going to unpack that from this lens. Please welcome Dave Duggal, founder and CEO of EnterpriseWeb and Azhar Sayeed is here, Senior Director Solution Architecture at Red Hat. >> Guys, it's great to have you on the program. >> Yes. >> Thank you Lisa, >> Great being here with you. >> Dave let's go ahead and start with you. Give the audience an overview of EnterpriseWeb. What kind of business is it? What's the business model? What do you guys do? >> Okay so, EnterpriseWeb is reinventing middleware, right? So the historic middleware was to build vertically integrated stacks, right? And those stacks are now such becoming the rate limiters for interoperability for so the end-to-end solutions that everybody's looking for, right? Red Hat's talking about the unified platform. You guys are talking about Supercloud, EnterpriseWeb addresses that we've built middleware based on serverless architecture, so lightweight, low latency, high performance middleware. And we're working with the world's biggest, we sell through channels and we work through partners like Red Hat Intel, Fortnet, Keysight, Tech Mahindra. So working with some of the biggest players that have recognized the value of our innovation, to deliver transformation to the Telecom industry. >> So what are you guys doing together? Is this, is this an OpenShift play? >> Is it? >> Yeah. >> Yeah, so we've got two projects right her on the floor at MWC throughout the various partners, where EnterpriseWeb is actually providing an application layer, sorry application middleware over Red Hat's, OpenShift and we're essentially generating operators so Red Hat operators, so that all our vendors, and, sorry vendors that we onboard into our catalog can be deployed easily through the OpenShift platform. And we allow those, those vendors to be flexibly composed into network services. So the real challenge for operators historically is that they, they have challenges onboarding the vendors. It takes a long time. Each one of them is a snowflake. They, you know, even though there's standards they don't all observe or follow the same standards. So we make it easier using models, right? For, in a model driven process to on boards or streamline that onboarding process, compose functions into services deploy those services seamlessly through Red Hat's OpenShift, and then manage the, the lifecycle, like the quality of service and the SLAs for those services. >> So Red Hat obviously has pretty prominent Telco business has for a while. Red Hat OpenStack actually is is pretty popular within the Telco business. People thought, "Oh, OpenStack, that's dead." Actually, no, it's actually doing quite well. We see it all over the place where for whatever reason people want to build their own cloud. And, and so, so what's happening in the industry because you have the traditional Telcos we heard in the keynotes that kind of typical narrative about, you know, we can't let the over the top vendors do this again. We're, we're going to be Apifi everything, we're going to monetize this time around, not just with connectivity but the, but the fact is they really don't have a developer community. >> Yes. >> Yet anyway. >> Then you have these disruptors over here that are saying "Yeah, we're going to enable ISVs." How do you see it? What's the landscape look like? Help us understand, you know, what the horses on the track are doing. >> Sure. I think what has happened, Dave, is that the conversation has moved a little bit from where they were just looking at IS infrastructure service with virtual machines and OpenStack, as you mentioned, to how do we move up the value chain and look at different applications. And therein comes the rub, right? You have applications with different requirements, IT network that have various different requirements that are there. So as you start to build those cloud platform, as you start to modernize those set of applications, you then start to look at microservices and how you build them. You need the ability to orchestrate them. So some of those problem statements have moved from not just refactoring those applications, but actually now to how do you reliably deploy, manage in a multicloud multi cluster way. So this conversation around Supercloud or this conversation around multicloud is very >> You could say Supercloud. That's okay >> (Dave Duggal and Azhar laughs) >> It's absolutely very real though. The reason why it's very real is, if you look at transformations around Telco, there are two things that are happening. One, Telco IT, they're looking at partnerships with hybrid cloud, I mean with public cloud players to build a hybrid environment. They're also building their own Telco Cloud environment for their network functions. Now, in both of those spaces, they end up operating two to three different environments themselves. Now how do you create a level of abstraction across those? How do you manage that particular infrastructure? And then how do you orchestrate all of those different workloads? Those are the type of problems that they're actually beginning to solve. So they've moved on from really just putting that virtualizing their application, putting it on OpenStack to now really seriously looking at "How do I build a service?" "How do I leverage the catalog that's available both in my private and public and build an overall service process?" >> And by the way what you just described as hybrid cloud and multicloud is, you know Supercloud is what multicloud should have been. And what, what it originally became is "I run on this cloud and I run on this cloud" and "I run on this cloud and I have a hybrid." And, and Supercloud is meant to create a common experience across those clouds. >> Dave Duggal: Right? >> Thanks to, you know, Supercloud middleware. >> Yeah. >> Right? And, and so that's what you guys do. >> Yeah, exactly. Exactly. Dave, I mean, even the name EnterpriseWeb, you know we started from looking from the application layer down. If you look at it, the last 10 years we've looked from the infrastructure up, right? And now everybody's looking northbound saying "You know what, actually, if I look from the infrastructure up the only thing I'll ever build is silos, right?" And those silos get in the way of the interoperability and the agility the businesses want. So we take the perspective as high level abstractions, common tools, so that if I'm a CXO, I can look down on my environments, right? When I'm really not, I honestly, if I'm an, if I'm a CEO I don't really care or CXO, I don't really care so much about my infrastructure to be honest. I care about my applications and their behavior. I care about my SLAs and my quality of service, right? Those are the things I care about. So I really want an EnterpriseWeb, right? Something that helps me connect all my distributed applications all across all of the environments. So I can have one place a consistency layer that speaks a common language. We know that there's a lot of heterogeneity down all those layers and a lot of complexity down those layers. But the business doesn't care. They don't want to care, right? They want to actually take their applications deploy them where they're the most performant where they're getting the best cost, right? The lowest and maybe sustainability concerns, all those. They want to address those problems, meet their SLAs meet their quality service. And you know what, if it's running on Amazon, great. If it's running on Google Cloud platform, great. If it, you know, we're doing one project right here that we're demonstrating here is with with Amazon Tech Mahindra and OpenShift, where we took a disaggregated 5G core, right? So this is like sort of latest telecom, you know net networking software, right? We're deploying pulling elements of that network across core, across Amazon EKS, OpenShift on Red Hat ROSA, as well as just OpenShift for cloud. And we, through a single pane of deployment and management, we deployed the elements of the 5G core across them and then connected them in an end-to-end process. That's Telco Supercloud. >> Dave Vellante: So that's an O-RAN deployment. >> Yeah that's >> So, the big advantage of that, pardon me, Dave but the big advantage of that is the customer really doesn't care where the components are being served from for them. It's a 5G capability. It happens to sit in different locations. And that's, it's, it's about how do you abstract and how do you manage all those different workloads in a cohesive way? And that's exactly what EnterpriseWeb is bringing to the table. And what we do is we abstract the underlying infrastructure which is the cloud layer. So if, because AWS operating environment is different then private cloud operating environment then Azure environment, you have the networking is set up is different in each one of them. If there is a way you can abstract all of that and present it in a common operating model it becomes a lot easier than for anybody to be able to consume. >> And what a lot of customers tell me is the way they deal with multicloud complexity is they go with mono cloud, right? And so they'll lose out on some of the best services >> Absolutely >> If best of, so that's not >> that's not ideal, but at the end of the day, agree, developers don't want to muck with all the plumbing >> Dave Duggal: Yep. >> They want to write code. >> Azhar: Correct. >> So like I come back to are the traditional Telcos leaning in on a way that they're going to enable ISVs and developers to write on top of those platforms? Or are there sort of new entrance and disruptors? And I know, I know the answer is both >> Dave Duggal: Yep. >> but I feel as though the Telcos still haven't, traditional Telcos haven't tuned in to that developer affinity, but you guys sell to them. >> What, what are you seeing? >> Yeah, so >> What we have seen is there are Telcos fall into several categories there. If you look at the most mature ones, you know they are very eager to move up the value chain. There are some smaller very nimble ones that have actually doing, they're actually doing something really interesting. For example, they've provided sandbox environments to developers to say "Go develop your applications to the sandbox environment." We'll use that to build an net service with you. I can give you some interesting examples across the globe that, where that is happening, right? In AsiaPac, particularly in Australia, ANZ region. There are a couple of providers who have who have done this, but in, in, in a very interesting way. But the challenges to them, why it's not completely open or public yet is primarily because they haven't figured out how to exactly monetize that. And, and that's the reason why. So in the absence of that, what will happen is they they have to rely on the ISV ecosystem to be able to build those capabilities which they can then bring it on as part of the catalog. But in Latin America, I was talking to one of the providers and they said, "Well look we have a public cloud, we have our own public cloud, right?" What we want do is use that to offer localized services not just bring everything in from the top >> But, but we heard from Ericson's CEO they're basically going to monetize it by what I call "gouge", the developers >> (Azhar laughs) >> access to the network telemetry as opposed to saying, "Hey, here's an open platform development on top of it and it will maybe create something like an app store and we'll take a piece of the action." >> So ours, >> to be is a better model. >> Yeah. So that's perfect. Our second project that we're showing here is with Intel, right? So Intel came to us cause they are a reputation for doing advanced automation solutions. They gave us carte blanche in their labs. So this is Intel Network Builders they said pick your partners. And we went with the Red Hat, Fort Net, Keysite this company KX doing AIML. But to address your DevX, here's Intel explicitly wants to get closer to the developers by exposing their APIs, open APIs over their infrastructure. Just like Red Hat has APIs, right? And so they can expose them northbound to developers so developers can leverage and tune their applications, right? But the challenge there is what Intel is doing at the low level network infrastructure, right? Is fundamentally complex, right? What you want is an abstraction layer where develop and this gets to, to your point Dave where you just said like "The developers just want to get their job done." or really they want to focus on the business logic and accelerate that service delivery, right? So the idea here is an EnterpriseWeb they can literally declaratively compose their services, express their intent. "I want this to run optimized for low latency. I want this to run optimized for energy consumption." Right? And that's all they say, right? That's a very high level statement. And then the run time translates it between all the elements that are participating in that service to realize the developer's intent, right? No hands, right? Zero touch, right? So that's now a movement in telecom. So you're right, it's taking a while because these are pretty fundamental shifts, right? But it's intent based networking, right? So it's almost two parts, right? One is you have to have the open APIs, right? So that the infrastructure has to expose its capabilities. Then you need abstractions over the top that make it simple for developers to take, you know, make use of them. >> See, one of the demonstrations we are doing is around AIOps. And I've had literally here on this floor, two conversations around what I call as network as a platform. Although it sounds like a cliche term, that's exactly what Dave was describing in terms of exposing APIs from the infrastructure and utilizing them. So once you get that data, then now you can do analytics and do machine learning to be able to build models and figure out how you can orchestrate better how you can monetize better, how can how you can utilize better, right? So all of those things become important. It's just not about internal optimization but it's also about how do you expose it to third party ecosystem to translate that into better delivery mechanisms or IOT capability and so on. >> But if they're going to charge me for every API call in the network I'm going to go broke (team laughs) >> And I'm going to get really pissed. I mean, I feel like, I'm just running down, Oracle. IBM tried it. Oracle, okay, they got Java, but they don't they don't have developer jobs. VMware, okay? They got Aria. EMC used to have a thing called code. IBM had to buy Red Hat to get to the developer community. (Lisa laughs) >> So I feel like the telcos don't today have those developer shops. So, so they have to partner. [Azhar] Yes. >> With guys like you and then be more open and and let a zillion flowers bloom or else they're going to get disrupted in a big way and they're going to it's going to be a repeat of the over, over the top in, in in a different model that I can't predict. >> Yeah. >> Absolutely true. I mean, look, they cannot be in the connectivity business. Telcos cannot be just in the connectivity business. It's, I think so, you know, >> Dave Vellante: You had a fry a frozen hand (Dave Daggul laughs) >> off that, you know. >> Well, you know, think about they almost have to go become over the top on themselves, right? That's what the cloud guys are doing, right? >> Yeah. >> They're riding over their backbone that by taking a creating a high level abstraction, they in turn abstract away the infrastructure underneath them, right? And that's really the end game >> Right? >> Dave Vellante: Yeah. >> Is because now, >> they're over the top it's their network, it's their infrastructure, right? They don't want to become bid pipes. >> Yep. >> Now you, they can take OpenShift, run that in any cloud. >> Yep. >> Right? >> You can run that in hybrid cloud, enterprise web can do the application layer configuration and management. And together we're running, you know, OSI layers one through seven, east to west, north to south. We're running across the the RAN, the core and the transport. And that is telco super cloud, my friend. >> Yeah. Well, >> (Dave Duggal laughs) >> I'm dominating the conversation cause I love talking super cloud. >> I knew you would. >> So speaking of super superpowers, when you're in customer or prospective customer conversations with providers and they've got, obviously they're they're in this transformative state right now. How, what do you describe as the superpower between Red Hat and EnterpriseWeb in terms of really helping these Telcos transforms. But at the end of the day, the connectivity's there the end user gets what they want, which is I want this to work wherever I am. >> Yeah, yeah. That's a great question, Lisa. So I think the way you could look at it is most software has, has been evolved to be specialized, right? So in Telcos' no different, right? We have this in the enterprise, right? All these specialized stacks, all these components that they wire together in the, in you think of Telco as a sort of a super set of enterprise problems, right? They have all those problems like magnified manyfold, right? And so you have specialized, let's say orchestrators and other tools for every Telco domain for every Telco layer. Now you have a zoo of orchestrators, right? None of them were designed to work together, right? They all speak a specific language, let's say quote unquote for doing a specific purpose. But everything that's interesting in the 21st century is across layers and across domains, right? If a siloed static application, those are dead, right? Nobody's doing those anymore. Even developers don't do those developers are doing composition today. They're not doing, nobody wants to hear about a 6 million lines of code, right? They want to hear, "How did you take these five things and bring 'em together for productive use?" >> Lisa: Right. How did you deliver faster for my enterprise? How did you save me money? How did you create business value? And that's what we're doing together. >> I mean, just to add on to Dave, I was talking to one of the providers, they have more than 30,000 nodes in their infrastructure. When I say no to your servers running, you know, Kubernetes,running open stack, running different components. If try managing that in one single entity, if you will. Not possible. You got to fragment, you got to segment in some way. Now the question is, if you are not exposing that particular infrastructure and the appropriate KPIs and appropriate things, you will not be able to efficiently utilize that across the board. So you need almost a construct that creates like a manager of managers, a hierarchical structure, which would allow you to be more intelligent in terms of how you place those, how you manage that. And so when you ask the question about what's the secret sauce between the two, well this is exactly where EnterpriseWeb brings in that capability to analyze information, be more intelligent about it. And what we do is provide an abstraction of the cloud layer so that they can, you know, then do the right job in terms of making sure that it's appropriate and it's consistent. >> Consistency is key. Guys, thank you so much. It's been a pleasure really digging through EnterpriseWeb. >> Thank you. >> What you're doing >> with Red Hat. How you're helping the organization transform and Supercloud, we can't forget Supercloud. (Dave Vellante laughs) >> Fight Supercloud. Guys, thank you so much for your time. >> Thank you so much Lisa. >> Thank you. >> Thank you guys. >> Very nice. >> Lisa: We really appreciate it. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live tech coverage coming to you live from MWC 23. We'll be back after a short break.

>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) >> Welcome back to the Fira in Barcelona. This is Dave Vellante with David Nicholson. Lisa Martin is also here. This is day two of our coverage of MWC 23 on theCUBE. We're super excited. We're in between hall four and five. Stop by if you're here. Dennis Hoffman is here. He's the senior vice president and general manager of the Telecom systems business at Dell Technologies, and he's joined by Yousef Khalidi, who's the corporate vice president of Azure for Operators from Microsoft. Gents, Welcome. >> Thanks, Dave. >> Thank you. >> So we saw Satya in the keynote. He wired in. We saw T.K. came in. No AWS. I don't know. They're maybe not part of the show, but maybe next year they'll figure it out. >> Indeed, indeed. >> Lots of stuff happened in the Telecom, but the Azure operator distributed service is the big news, you guys got here. What's that all about? >> Oh, first of all, we changed the name. >> Oh, you did? >> You did? >> Oh, yeah. We have a real name now. It's called the Azure Operator Nexus. >> Oh, I like Nexus better than that. >> David: That's much better, much better. >> Dave: The engineers named it first time around. >> I wish, long story, but thank you for our marketing team. But seriously, not only did we rename the platform, we expanded the platform. >> Dave: Yeah. >> So it now covers the whole spectrum from the far-edge to the public cloud as well, including the near-edge as well. So essentially, it's a hybrid platform that can also run network functions. So all these operators around you, they now have a platform which combines cloud technologies with the choice where they want to run, optimized for the network. >> Okay and so, you know, we've talked about the disaggregation of the network and how you're bringing kind of engineered systems to the table. We've seen this movie before, but Dennis, there are differences, right? I mean, you didn't really have engineered systems in the 90s. You didn't have those integration points. You really didn't have the public cloud, you didn't have AI. >> Right. >> So you have all those new powers that you can tap, so give us the update from your perspective, having now spent a day and a half here. What's the vibe, what's the buzz, and what's your take on everything? >> Yeah, I think to build on what Yousef said, there's a lot going on with people still trying to figure out exactly how to architect the Telecom network of the future. They know it's got to have a lot to do with cloud. It does have some pretty significant differences, one of those being, there's definitely got to be a hybrid component because there are pieces of the Telecom network that even when modernized will not end up centralized, right? They're going to be highly distributed. I would say though, you know, we took away two things, yesterday, from all the meetings. One, people are done, I think the network operators are done, questioning technology readiness. They're now beginning to wrestle with operationalization of it all, right? So it's like, okay, it's here. I can in fact build a modern network in a very cloud native way, but I've got to figure out how to do that all. And another big part of it is the ecosystem and certainly the partnership long standing between Dell and Microsoft which we're extending into this space is part of that, making it easier on people to actually acquire, deploy, and importantly, support these new technologies. >> So a lot of the traditional carriers, like you said, they're sort of beyond the technology readiness. Jose Maria Alvarez in the keynote said there are three pillars to the future Telecom network. He said low latency, programmable networks, and then cloud and edge, kind of threw that in. You agree with that, Yousef? (Dave and Yousef speaking altogether) >> I mean, we've been for years talking about the cloud and edge. >> Yeah. >> Satya for years had the same graphic. We still have it. Today, we have expanded the graphic a bit to include the network as one, because you can have a cloud without connectivity as well but this is very, very, very, very much true. >> And so the question then, Dennis, is okay, you've got disruptors, we had Dish on yesterday. >> Oh, did you? Good. >> Yeah, yeah, and they're talking about what they're doing with, you know, ORAN and all the applications, really taking account of it. What I see is a developer friendly, you know, environment. You got the carriers talking about how they're going to charge developers for APIs. I think they've published eight APIs which is nowhere near enough. So you've got that sort of, you know, inertia and yet, you have the disruptors that are going to potentially be a catalyst to, you know, cross the chasm, if you will. So, you know, put on your strategy hat. >> Yeah. >> Dave: How do you see that playing out? >> Well, they're trying to tap into three things, the disruptors. You know, I think the thesis is, "If I get to a truly cloud native, communications network first, I ought to have greater agility so that I can launch more services and create more revenue streams. I ought to be lower cost in terms of both acquisition cost and operating cost, right, and I ought to be able to create scale between my IT organization, everything I know how to do there and my Telecom network." You know, classic, right? Better, faster, cheaper if I embrace cloud early on. And people like Dish, you know, they have a clean sheet of paper with which to do that. So innovation and rate of innovation is huge for them. >> So what would you do? We put your Clay Christensen hat on, now. What if you were at a traditional Telco who's like, complaining about- >> You're going to get me in trouble. >> Dave: Come on, come on. >> Don't do it. >> Dave: Help him out. Help him out, help him out. So if, you know, they're complaining about CapEx, they're highly regulated, right, they want net neutrality but they want to be able to sort of dial up the cost of those using the network. So what would you do? Would you try to disrupt yourself? Would you create a skunkworks? Would you kind of spin off a disruptor? That's a real dilemma for those guys. >> Well for mobile network operators, the beauty of 5G is it's the first cloud native cellular standard. So I don't know if anybody's throwing these terms around, but 5G SA is standalone, right? >> Dave: Yeah, yeah. >> So a lot of 'em, it's not a skunkworks. They're just literally saying, "I've got to have a 5G network." And some of 'em are deciding, "I'm going to stand it up all by itself." Now, that's duplicative expense in a lot of ways, but it creates isolation from the two networks. Others are saying, "No, it's got to be NSA. I've got to be able to combine 4G and 5G." And then you're into the brownfield thing. >> That's the hybrid. >> Not hybrid as in cloud, but hybrid as in, you know. >> Yeah, yeah. >> It's a converge network. >> Dave: Yeah, yeah. >> So, you know, I would say for a lot of them, they're adopting, probably rightly so, a wait and see attitude. One thing we haven't talked about and you got to get on the table, their high order bit is resilience. >> Dave: Yeah, totally. >> David: Yeah. >> Right? Can't go down. It's national, secure infrastructure, first responder. >> Indeed. >> Anytime you ask them to embrace any new technology, the first thing that they have to work through in their minds is, you know, "Is the juice worth the squeeze? Like, can I handle the risk?" >> But you're saying they're not questioning the technology. Aren't they questioning ORAN in terms of the quality of service, or are they beyond that? >> Dennis: They're questioning the timing, not the inevitability. >> Okay, so they agree that ORAN is going to be open over time. >> At some point, RAN will be cloud native, whether it's ORAN the spec, open RAN the concept, (Yousef speaking indistinctly) >> Yeah. >> Virtual RAN. But yeah, I mean I think it seems pretty evident at this point that the mainframe will give way to open systems once again. >> Dave: Yeah, yeah, yeah. >> ERAN, ecosystem RAN. >> Any RAN. (Dave laughing) >> You don't have to start with the ORAN where they're inside the house. So as you probably know, our partner AT&T started with the core. >> Dennis: They almost all have. >> And they've been on the virtualization path since 2014 and 15. And what we are working with them on is the hybrid cloud model to expand all the way, if you will, as I mentioned to the far-edge or the public cloud. So there's a way to be in the brownfield environment, yet jump on the new bandwagon of technology without necessarily taking too much risk, because you're quite right. I mean, resiliency, security, service assurance, I mean, for example, AT&T runs the first responder network for the US on their network, on our platform, and I'm personally very familiar of how high the bar is. So it's doable, but you need to go in stages, of course. >> And they've got to do that integration. >> Yes. >> They do. >> And Yousef made a great point. Like, out of the top 30 largest Telcos by CapEx outside of China, three quarters of them have virtualized their core. So the cloudification, if you will, software definition run on industry standard hardware, embraced cloud native principles, containerized apps, that's happened in the core. It's well accepted. Now it's just a ripple-down through the network which will happen as and when things are faster, better, cheaper. >> Right. >> So as implemented, what does this look like? Is it essentially what we used to loosely refer to as Azure stacked software, running with Dell optimized Telecom infrastructure together, sometimes within a BBU, out in a hybrid cloud model communicating back to Azure locations in some cases? Is that what we're looking at? >> Approximately. So you start with the near-edge, okay? So the near-edge lives in the operator's data centers, edges, whatever the case may be, built out of off the shelf hardware. Dell is our great partner there but in principle, it could be different mix and match. So once you have that true near-edge, then you can think of, "Okay, how can I make sure this environment is as uniform, same APIs, same everything, regardless what the physical location is?" And this is key, key for the network function providers and the NEPs because they need to be able to port once, run everywhere, and it's key for the operator to reduce their costs. You want to teach your workforce, your operations folks, if you will, how to manage this system one time, to automation and so forth. So, and that is actually an expansion of the Azure capabilities that people are familiar with in a public cloud, projected into different locations. And we have technology called Arc which basically models everything. >> Yeah, yeah. >> So if you have trained your IT side, you are halfway there, how to manage your new network. Even though of course the network is carrier graded, there's different gear. So yes, what you said, a lot of it is true but the actual components, whatever they might be running, are carrier grade, highly optimized, the next images and our solution is not a DIY solution, okay? I know you cater to a wide spectrum here but for us, we don't believe in the TCO. The proper TCO can be achieved by just putting stuff by yourself. We just published a report with Analysys Mason that shows that our approach will save 36 percent of the cost compared to a DIY approach. >> Dave: What percent? >> 36 percent. >> Dave: Of the cost? >> Of, compared to DIY, which is already cheaper than classical models. >> And there's a long history of fairly failed DIY, right, >> Yeah. >> That preceded this. As in the early days of public cloud, the network operators wrestled with, "Do I have to become one to survive?" >> Dave: Yeah. Right. >> So they all ended up having cloud projects and by and large, they've all dematerialized in favor of this. >> Yeah, and it's hard for them to really invest at scale. Let me give you an example. So, your biggest tier one operator, without naming anybody, okay, how many developers do they have that can build and maintain an OS image, or can keep track of container technology, or build monitoring at scale? In our company, we have literally thousands of developers doing it already for the cloud and all we're doing for the operator segment is customizing it and focusing it at the carrier grade aspects of it. But so, I don't have half a dozen exterior experts. I literally have a building of developers who can do that and I'm being literal, here. So it's a scale thing. Once you have a product that you can give to multiple people, everybody benefits. >> Dave: Yeah, and the carriers are largely, they're equipment engineers in a large setting. >> Oh, they have a tough job. I always have total respect what they do. >> Oh totally, and a lot of the work happens, you know, kind of underground and here they are. >> They are network operators. >> They don't touch. >> It's their business. >> Right, absolutely, and they're good at it. They're really good at it. That's right. You know, you think about it, we love to, you know, poke fun at the big carriers, but think about what happened during the pandemic. When they had us shift everything to remote work, >> Dennis: Yes. >> Landline traffic went through the roof. You didn't even notice. >> Yep. That's very true. >> I mean, that's the example. >> That's very true. >> However, in the future where there's innovation and it's going to be driven by developers, right, that's where the open ecosystem comes in. >> Yousef: Indeed. >> And that's the hard transition for a lot of these folks because the developers are going to win that with new workloads, new applications that we can't even think of. >> Dennis: Right. And a lot of it is because if you look at it, there's the fundamental back strategy hat back on, fundamental dynamics of the industry, forced investment, flat revenues. >> Dave: Yeah. Right. >> Very true. >> Right? Every few years, a new G comes out. "Man, I got to retool this massive thing and where I can't do towers, I'm dropping fiber or vice a versa." And meanwhile, most diversification efforts into media have failed. They've had to unwind them and resell them. There's a lot of debt in the industry. >> Yousef: Yeah. >> Dennis: And so, they're looking for that next big, adjacent revenue stream and increasingly deciding, "If I don't modernize my network, I can't get it." >> Can't do it. >> Right, and again, what I heard from some of the carriers in the keynote was, "We're going to charge for API access 'cause we have data in the network." Okay, but I feel like there's a lot more innovation beyond that that's going to come from the disruptors. >> Dennis: Oh yeah. >> Yousef: Yes. >> You know, that's going to blow that away, right? And then that may not be the right model. We'll see, you know? I mean, what would Microsoft do? They would say, "Here, here's a platform. Go develop." >> No, I'll tell you. We are actually working with CAMARA and GSMA on the whole API layer. We actually announced a service as well as (indistinct). >> Dave: Yeah, yeah, right. >> And the key there, frankly, in my opinion, are not the disruptors as in operators. It's the ISV community. You want to get developers that can write to a global set of APIs, not per Telco APIs, such that they can do the innovation. I mean, this is what we've seen in other industries, >> Absolutely. >> That I critically can think of. >> This is the way they get a slice of that pie, right? The recent history of this industry is one where 4G LTE begot the smartphone and app store era, a bevy of consumer services, and almost every single profit stream went somewhere other than the operator, right? >> Yousef: Someone else. So they're looking at this saying, "Okay, 5G is the enterprise G and there's going to be a bevy of applications that are business service related, based on 5G capability and I can't let the OTT, over the top, thing happen again." >> Right. >> They'll say that. "We cannot let this happen." >> "We can't let this happen again." >> Okay, but how do they, >> Yeah, how do they make that not happen? >> Not let it happen again? >> Eight APIs, Dave. The answer is eight APIs. No, I mean, it's this approach. They need to make it easy to work with people like Yousef and more importantly, the developer community that people like Yousef and his company have found a way to harness. And by the way, they need to be part of that developer community themselves. >> And they're not, today. They're not speaking that developer language. >> Right. >> It's hard. You know, hey. >> Dennis: Hey, what's the fastest way to sell an enterprise, a business service? Resell Azure, Teams, something, right? But that's a resale. >> Yeah, that's a resale thing. >> See, >> That's not their service. >> They also need to free their resources from all the plumbing they do and leave it to us. We are plumbers, okay? >> Dennis: We are proud plumbers. >> We are proud plumbers. I'm a plumber. I keep telling people this thing. We had the same discussion with banks and enterprises 10 years ago, by the way. Don't do the plumbing. Go add value on the top. Retool your workforce to do applications and work with ISVs to the verticals, as opposed to either reselling, which many do, or do the plumbing. You'd be surprised. Traditionally, many operators do around, "I want to plumb this thing to get this small interrupt per second." Like, who cares? >> Well, 'cause they made money on connectivity. >> Yes. >> And we've seen this before. >> And in a world without telephone poles and your cables- >> Hey, if what you have is a hammer, everything's a nail, right? And we sell connectivity services and that's what we know how to do, and that both build and sell. And if that's no longer driving a revenue stream sufficient to cover this forced investment march, not to mention Huawei rip and government initiatives to pull infrastructure out and accelerate investment, they got to find new ways. >> I mean, the regulations have been tough, right? They don't go forward and ask for permission. They really can't, right? They have to be much more careful. >> Dennis: It is tough. >> So, we don't mean to sound like it's easy for these guys. >> Dennis: No, it's not. >> But it does require a new mindset, new skillsets, and I think some of 'em are going to figure it out and then pff, the wave, and you guys are going to be riding that wave. >> We're going to try. >> Definitely. Definitely. >> As a veteran of working with both Dell and Microsoft, specifically Azure on things, I am struck by how you're very well positioned in this with Microsoft in particular. Because of Azure's history, coming out of the on-premises world that Microsoft knows so well, there's a natural affinity to the hybrid nature of Telecom. We talk about edge, we talk about hybrid, this is it, absolutely the center of it. So it seems like a- >> Yousef: Indeed. Actually, if you look at the history of Azure, from day one, and I was there from day one, we always spoke of the hybrid model. >> Yeah. >> The third point, we came from the on-premises world. >> David: Right. >> And don't get me wrong, I want people to use the public cloud, but I also know due to physics, regulation, geopolitical boundaries, there's something called on-prem, something called an edge here. I want to add something else. Remember our deal on how we are partner-centric? We're applying the same playbook, here. So, you know, for every dollar we make, so many of it's been done by the ecosystem. Same applies here. So we have announced partnerships with Ericson, Nokia, (indistinct), all the names, and of course with Dell and many others. The ecosystem has to come together and customers must retain their optionality to drum up whatever they are on. So it's the same playbook, with this. >> And enterprise technology companies are, actually, really good at, you know, decoding the customer, figuring out specific requirements, making some mistakes the first time through and then eventually getting it right. And as these trends unfold, you know, you're in a good position, I think, as are others and it's an exciting time for enterprise tech in this industry, you know? >> It really is. >> Indeed. >> Dave: Guys, thanks so much for coming on. >> Thank you. >> Dave: It's great to see you. Have a great rest of the show. >> Thank you. >> Thanks, Dave. Thank you, Dave. >> All right, keep it right there. John Furrier is live in our studio. He's breaking down all the news. Go to siliconangle.com to go to theCUBE.net. Dave Vellante, David Nicholson and Lisa Martin, we'll be right back from the theater in Barcelona, MWC 23 right after this short break. (relaxing music)

(gentle music) >> Announcer: "theCube's" live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) (logo whooshing) >> Hey, everyone, welcome back to "theCube's" coverage of day one, MWC23 live from Barcelona, Lisa Martin here with Dave Vellante. Dave, we've got some great conversations so far This is the biggest, most packed show I've been to in years. About 80,000 people here so far. >> Yeah, down from its peak of 108, but still pretty good. You know, a lot of folks from China come to this show, but with the COVID situation in China, that's impacted the attendance, but still quite amazing. >> Amazing for sure. We're going to be talking about trends and mobility, and all sorts of great things. We have a couple of guests joining us for the first time on "theCUBE." Please welcome Dr. Srinivas Mukkamala or Sri, chief product officer at Ivanti. And Dave Shepherd, VP Ivanti. Guys, welcome to "theCUBE." Great to have you here. >> Thank you. >> So, day one of the conference, Sri, we'll go to you first. Talk about some of the trends that you're seeing in mobility. Obviously, the conference renamed from Mobile World Congress to MWC mobility being part of it, but what are some of the big trends? >> It's interesting, right? I mean, I was catching up with Dave. The first thing is from the keynotes, it took 45 minutes to talk about security. I mean, it's quite interesting when you look at the shore floor. We're talking about Edge, we're talking about 5G, the whole evolution. And there's also the concept of are we going into the Cloud? Are we coming back from the Cloud, back to the Edge? They're really two different things. Edge is all decentralized while you recompute. And one thing I observed here is they're talking about near real-time reality. When you look at automobiles, when you look at medical, when you look at robotics, you can't have things processed in the Cloud. It'll be too late. Because you got to make millisecond-based stations. That's a big trend for me. When I look at staff... Okay, the compute it takes to process in the Cloud versus what needs to happen on-prem, on device, is going to revolutionize the way we think about mobility. >> Revolutionize. David, what are some of the things that you're saying? Do you concur? >> Yeah, 100%. I mean, look, just reading some of the press recently, they're predicting 22 billion IoT devices by 2024. Everything Sri just talked about there. It's growing exponentially. You know, problems we have today are a snapshot. We're probably in the slowest place we are today. Everything's just going to get faster and faster and faster. So it's a, yeah, 100% concur with that. >> You know, Sri, on your point, so Jose Maria Alvarez, the CEO of Telefonica, said there are three pillars of the future of telco, low latency, programmable networks, and Cloud and Edge. So, as to your point, Cloud and low latency haven't gone hand in hand. But the Cloud guys are saying, "All right, we're going to bring the Cloud to the Edge." That's sort of an interesting dynamic. We're going to bypass them. We heard somebody, another speaker say, "You know, Cloud can't do it alone." You know? (chuckles) And so, it's like these worlds need each other in a way, don't they? >> Definitely right. So that's a fantastic way to look at it. The Cloud guys can say, "We're going to come closer to where the computer is." And if you really take a look at it with data localization, where are we going to put the Cloud in, right? I mean, so the data sovereignty becomes a very interesting thing. The localization becomes a very interesting thing. And when it comes to security, it gets completely different. I mean, we talked about moving everything to a centralized compute, really have massive processing, and give you the addition back wherever you are. Whereas when you're localized, I have to process everything within the local environment. So there's already a conflict right there. How are we going to address that? >> Yeah. So another statement, I think, it was the CEO of Ericsson, he was kind of talking about how the OTT guys have heard, "We can't let that happen again. And we're going to find new ways to charge for the network." Basically, he's talking about monetizing the API access. But I'm interested in what you're hearing from customers, right? 'Cause our mindset is, what value you're going to give to customers that they're going to pay for, versus, "I got this data I'm going to charge developers for." But what are you hearing from customers? >> It's amazing, Dave, the way you're looking at it, right? So if we take a look at what we were used to perpetual, and we said we're going to move to a subscription, right? I mean, everybody talks about subscription economy. Telcos on the other hand, had subscription economy for a long time, right? They were always based on usage, right? It's a usage economy. But today, we are basically realizing on compute. We haven't even started charging for compute. If you go to AWS, go to Azure, go to GCP, they still don't quite charge you for actual compute, right? It's kind of, they're still leaning on it. So think about API-based, we're going to break the bank. What people don't realize is, we do millions of API calls for any high transaction environment. A consumer can't afford that. What people don't realize is... I don't know how you're going to monetize. Even if you charge a cent a call, that is still going to be hundreds and thousands of dollars a day. And that's where, if you look at what you call low-code no-code motion? You see a plethora of companies being built on that. They're saying, "Hey, you don't have to write code. I'll give you authentication as a service. What that means is, Every single time you call my API to authenticate a user, I'm going to charge you." So just imagine how many times we authenticate on a single day. You're talking a few dozen times. And if I have to pay every single time I authenticate... >> Real friction in the marketplace, David. >> Yeah, and I tell you what. It's a big topic, right? And it's a topic that we haven't had to deal with at the Edge before, and we hear it probably daily really, complexity. The complexity's growing all the time. That means that we need to start to get insight, visibility. You know? I think a part of... Something that came out of the EU actually this week, stated, you know, there's a cyber attack every 11 seconds. That's fast, right? 2016, that was 40 seconds. So actually that speed I talked about earlier, everything Sri says that's coming down to the Edge, we want to embrace the Edge and that is the way we're going to move. But customers are mindful of the complexity that's involved in that. And that, you know, lens thought to how are we going to deal with those complexities. >> I was just going to ask you, how are you planning to deal with those complexities? You mentioned one ransomware attack every 11 seconds. That's down considerably from just a few years ago. Ransomware is a household word. It's no longer, "Are we going to get attacked?" It's when, it's to what extent, it's how much. So how is Ivanti helping customers deal with some of the complexities, and the changes in the security landscape? >> Yeah. Shall I start on that one first? Yeah, look, we want to give all our customers and perspective customers full visibility of their environment. You know, devices that are attached to the environment. Where are they? What are they doing? How often are we going to look for those devices? Not only when we find those devices. What applications are they running? Are those applications secure? How are we going to manage those applications moving forward? And overall, wrapping it round, what kind of service are we going to do? What processes are we going to put in place? To Sri's point, the low-code no-code angle. How do we build processes that protect our organization? But probably a point where I'll pass to Sri in a moment is how do we add a level of automation to that? How do we add a level of intelligence that doesn't always require a human to be fixing or remediating a problem? >> To Sri, you mentioned... You're right, the keynote, it took 45 minutes before it even mentioned security. And I suppose it's because they've historically, had this hardened stack. Everything's controlled and it's a safe environment. And now that's changing. So what would you add? >> You know, great point, right? If you look at telcos, they're used to a perimeter-based network. >> Yep. >> I mean, that's what we are. Boxed, we knew our perimeter. Today, our perimeter is extended to our home, everywhere work, right? >> Yeah- >> We don't have a definition of a perimeter. Your browser is the new perimeter. And a good example, segueing to that, what we have seen is horizontal-based security. What we haven't seen is verticalization, especially in mobile. We haven't seen vertical mobile security solutions, right? Yes, you hear a little bit about automobile, you hear a little bit about healthcare, but what we haven't seen is, what about food sector? What about the frontline in food? What about supply chain? What security are we really doing? And I'll give you a simple example. You brought up ransomware. Last night, Dole was attacked with ransomware. We have seen the beef producer colonial pipeline. Now, if we have seen agritech being hit, what does it mean? We are starting to hit humanity. If you can't really put food on the table, you're starting to really disrupt the supply chain, right? In a massive way. So you got to start thinking about that. Why is Dole related to mobility? Think about that. They don't carry service and computers. What they carry is mobile devices. that's where the supply chain works. And then that's where you have to start thinking about it. And the evolution of ransomware, rather than a single-trick pony, you see them using multiple vulnerabilities. And Pegasus was the best example. Spyware across all politicians, right? And CEOs. It is six or seven vulnerabilities put together that actually was constructed to do an attack. >> Yeah. How does AI kind of change this? Where does it fit in? The attackers are going to have AI, but we could use AI to defend. But attackers are always ahead, right? (chuckles) So what's your... Do you have a point of view on that? 'Cause everybody's crazy about ChatGPT, right? The banks have all banned it. Certain universities in the United States have banned it. Another one's forcing his students to learn how to use ChatGPT to prompt it. It's all over the place. You have a point of view on this? >> So definitely, Dave, it's a great point. First, we all have to have our own generative AI. I mean, I look at it as your digital assistant, right? So when you had calculators, you can't function without a calculator today. It's not harmful. It's not going to take you away from doing multiplication, right? So we'll still teach arithmetic in school. You'll still use your calculator. So to me, AI will become an integral part. That's one beautiful thing I've seen on the short floor. Every little thing there is a AI-based solution I've seen, right? So ChatGPT is well played from multiple perspective. I would rather up level it and say, generated AI is the way to go. So there are three things. There is human intense triaging, where humans keep doing easy work, minimal work. You can use ML and AI to do that. There is human designing that you need to do. That's when you need to use AI. >> But, I would say this, in the Enterprise, that the quality of the AI has to be better than what we've seen so far out of ChatGPT, even though I love ChatGPT, it's amazing. But what we've seen from being... It's got to be... Is it true that... Don't you think it has to be cleaner, more accurate? It can't make up stuff. If I'm going to be automating my network with AI. >> I'll answer that question. It comes down to three fundamentals. The reason ChatGPT is giving addresses, it's not trained on the latest data. So for any AI and ML method, you got to look at three things. It's your data, it's your domain expertise, who is training it, and your data model. In ChatGPT, it's older data, it's biased to the people that trained it, right? >> Mm-hmm. >> And then, the data model is it's going to spit out what it's trained on. That's a precursor of any GPT, right? It's pre-trained transformation. >> So if we narrow that, right? Train it better for the specific use case, that AI has huge potential. >> You flip that to what the Enterprise customers talk about to us is, insight is invaluable. >> Right. >> But then too much insight too quickly all the time means we go remediation crazy. So we haven't got enough humans to be fixing all the problems. Sri's point with the ChatGPT data, some of that data we are looking at there could be old. So we're trying to triage something that may still be an issue, but it might have been superseded by something else as well. So that's my overriding when I'm talking to customers and we talk ChatGPT, it's in the news all the time. It's very topical. >> It's fun. >> It is. I even said to my 13-year-old son yesterday, your homework's out a date. 'Cause I knew he was doing some summary stuff on ChatGPT. So a little wind up that's out of date just to make that emphasis around the model. And that's where we, with our Neurons platform Ivanti, that's what we want to give the customers all the time, which is the real-time snapshot. So they can make a priority or a decision based on what that information is telling them. >> And we've kind of learned, I think, over the last couple of years, that access to real-time data, real-time AI, is no longer nice to have. It's a massive competitive advantage for organizations, but it's going to enable the on-demand, everything that we expect in our consumer lives, in our business lives. This is going to be table stakes for organizations, I think, in every industry going forward. >> Yeah. >> But assumes 5G, right? Is going to actually happen and somebody's going to- >> Going to absolutely. >> Somebody's going to make some money off it at some point. When are they going to make money off of 5G, do you think? (all laughing) >> No. And then you asked a very good question, Dave. I want to answer that question. Will bad guys use AI? >> Yeah. Yeah. >> Offensive AI is a very big thing. We have to pay attention to it. It's got to create an asymmetric war. If you look at the president of the United States, he said, "If somebody's going to attack us on cyber, we are going to retaliate." For the first time, US is willing to launch a cyber war. What that really means is, we're going to use AI for offensive reasons as well. And we as citizens have to pay attention to that. And that's where I'm worried about, right? AI bias, whether it's data, or domain expertise, or algorithmic bias, is going to be a big thing. And offensive AI is something everybody have to pay attention to. >> To your point, Sri, earlier about critical infrastructure getting hacked, I had this conversation with Dr. Robert Gates several years ago, and I said, "Yeah, but don't we have the best offensive, you know, technology in cyber?" And he said, "Yeah, but we got the most to lose too." >> Yeah, 100%. >> We're the wealthiest nation of the United States. The wealthiest is. So you got to be careful. But to your point, the president of the United States saying, "We'll retaliate," right? Not necessarily start the war, but who started it? >> But that's the thing, right? Attribution is the hardest part. And then you talked about a very interesting thing, rich nations, right? There's emerging nations. There are nations left behind. One thing I've seen on the show floor today is, digital inequality. Digital poverty is a big thing. While we have this amazing technology, 90% of the world doesn't have access to this. >> Right. >> What we have done is we have created an inequality across, and especially in mobility and cyber, if this technology doesn't reach to the last mile, which is emerging nations, I think we are creating a crater back again and putting societies a few miles back. >> And at much greater risk. >> 100%, right? >> Yeah. >> Because those are the guys. In cyber, all you need is a laptop and a brain to attack. >> Yeah. Yeah. >> If I don't have it, that's where the civil war is going to start again. >> Yeah. What are some of the things in our last minute or so, guys, David, we'll start with you and then Sri go to you, that you're looking forward to at this MWC? The theme is velocity. We're talking about so much transformation and evolution in the telecom industry. What are you excited to hear and learn in the next couple of days? >> Just getting a complete picture. One is actually being out after the last couple of years, so you learn a lot. But just walking around and seeing, from my perspective, some vendor names that I haven't seen before, but seeing what they're doing and bringing to the market. But I think goes back to the point made earlier around APIs and integration. Everybody's talking about how can we kind of do this together in a way. So integrations, those smart things is what I'm kind of looking for as well, and how we plug into that as well. >> Excellent, and Sri? >> So for us, there is a lot to offer, right? So while I'm enjoying what I'm seeing here, I'm seeing at an opportunity. We have an amazing portfolio of what we can do. We are into mobile device management. We are the last (indistinct) company. When people find problems, somebody has to go remediators. We are the world's largest patch management company. And what I'm finding is, yes, all these people are embedding software, pumping it like nobody's business. As you find one ability, somebody has to go fix them, and we want to be the (indistinct) company. We had the last smile. And I find an amazing opportunity, not only we can do device management, but do mobile threat defense and give them a risk prioritization on what needs to be remediated, and manage all that in our ITSM. So I look at this as an amazing, amazing opportunity. >> Right. >> Which is exponential than what I've seen before. >> So last question then. Speaking of opportunities, Sri, for you, what are some of the things that customers can go to? Obviously, you guys talk to customers all the time. In terms of learning what Ivanti is going to enable them to do, to take advantage of these opportunities. Any webinars, any events coming up that we want people to know about? >> Absolutely, ivanti.com is the best place to go because we keep everything there. Of course, "theCUBE" interview. >> Of course. >> You should definitely watch that. (all laughing) No. So we have quite a few industry events we do. And especially there's a lot of learning. And we just raised the ransomware report that actually talks about ransomware from a global index perspective. So one thing what we have done is, rather than just looking at vulnerabilities, we showed them the weaknesses that led to the vulnerabilities, and how attackers are using them. And we even talked about DHS, how behind they are in disseminating the information and how it's actually being used by nation states. >> Wow. >> And we did cover mobility as a part of that as well. So there's a quite a bit we did in our report and it actually came out very well. >> I have to check that out. Ransomware is such a fascinating topic. Guys, thank you so much for joining Dave and me on the program today, sharing what's going on at Ivanti, the changes that you're seeing in mobile, and the opportunities that are there for your customers. We appreciate your time. >> Thank you >> Thank you. >> Yes. Thanks, guys. >> Thanks, guys. >> For our guests and for Dave Vellante, I'm Lisa Martin. You're watching "theCUBE" live from MWC23 in Barcelona. As you know, "theCUBE" is the leader in live tech coverage. Dave and I will be right back with our next guest. (gentle upbeat music)

(soothing music) >> Hey everyone, welcome to this event, "Build Your Cloud Center of Excellence." I'm your host, Lisa Martin. In the next 15 minutes or so my guest and I are going to be talking about redefining cloud operations, an application modernization for customers, and specifically how partners are helping to speed up that process. As you saw on our first two segments, we talked about problems enterprises are facing with cloud operations. We talked about redefining cloud operations as well to solve these problems. This segment is going to be focusing on how Hitachi Vantara's partners are really helping to speed up that process. We've got Johnson Controls here to talk about their partnership with Hitachi Vantara. Please welcome both of my guests, Prem Balasubramanian is with us, SVP and CTO Digital Solutions at Hitachi Vantara. And Suresh Mothikuru, SVP Customer Success Platform Engineering and Reliability Engineering from Johnson Controls. Gentlemen, welcome to the program, great to have you. >> Thank. >> Thank you, Lisa. >> First question is to both of you and Suresh, we'll start with you. We want to understand, you know, the cloud operations landscape is increasingly complex. We've talked a lot about that in this program. Talk to us, Suresh, about some of the biggest challenges and pin points that you faced with respect to that. >> Thank you. I think it's a great question. I mean, cloud has evolved a lot in the last 10 years. You know, when we were talking about a single cloud whether it's Azure or AWS and GCP, and that was complex enough. Now we are talking about multi-cloud and hybrid and you look at Johnson Controls, we have Azure we have AWS, we have GCP, we have Alibaba and we also support on-prem. So the architecture has become very, very complex and the complexity has grown so much that we are now thinking about whether we should be cloud native or cloud agnostic. So I think, I mean, sometimes it's hard to even explain the complexity because people think, oh, "When you go to cloud, everything is simplified." Cloud does give you a lot of simplicity, but it also really brings a lot more complexity along with it. So, and then next one is pretty important is, you know, generally when you look at cloud services, you have plenty of services that are offered within a cloud, 100, 150 services, 200 services. Even within those companies, you take AWS they might not know, an individual resource might not know about all the services we see. That's a big challenge for us as a customer to really understand each of the service that is provided in these, you know, clouds, well, doesn't matter which one that is. And the third one is pretty big, at least at the CTO the CIO, and the senior leadership level, is cost. Cost is a major factor because cloud, you know, will eat you up if you cannot manage it. If you don't have a good cloud governance process it because every minute you are in it, it's burning cash. So I think if you ask me, these are the three major things that I am facing day to day and that's where I use my partners, which I'll touch base down the line. >> Perfect, we'll talk about that. So Prem, I imagine that these problems are not unique to Johnson Controls or JCI, as you may hear us refer to it. Talk to me Prem about some of the other challenges that you're seeing within the customer landscape. >> So, yeah, I agree, Lisa, these are not very specific to JCI, but there are specific issues in JCI, right? So the way we think about these are, there is a common issue when people go to the cloud and there are very specific and unique issues for businesses, right? So JCI, and we will talk about this in the episode as we move forward. I think Suresh and his team have done some phenomenal step around how to manage this complexity. But there are customers who have a lesser complex cloud which is, they don't go to Alibaba, they don't have footprint in all three clouds. So their multi-cloud footprint could be a bit more manageable, but still struggle with a lot of the same problems around cost, around security, around talent. Talent is a big thing, right? And in Suresh's case I think it's slightly more exasperated because every cloud provider Be it AWS, JCP, or Azure brings in hundreds of services and there is nobody, including many of us, right? We learn every day, nowadays, right? It's not that there is one service integrator who knows all, while technically people can claim as a part of sales. But in reality all of us are continuing to learn in this landscape. And if you put all of this equation together with multiple clouds the complexity just starts to exponentially grow. And that's exactly what I think JCI is experiencing and Suresh's team has been experiencing, and we've been working together. But the common problems are around security talent and cost management of this, right? Those are my three things. And one last thing that I would love to say before we move away from this question is, if you think about cloud operations as a concept that's evolving over the last few years, and I have touched upon this in the previous episode as well, Lisa, right? If you take architectures, we've gone into microservices, we've gone into all these server-less architectures all the fancy things that we want. That helps us go to market faster, be more competent to as a business. But that's not simplified stuff, right? That's complicated stuff. It's a lot more distributed. Second, again, we've advanced and created more modern infrastructure because all of what we are talking is platform as a service, services on the cloud that we are consuming, right? In the same case with development we've moved into a DevOps model. We kind of click a button put some code in a repository, the code starts to run in production within a minute, everything else is automated. But then when we get to operations we are still stuck in a very old way of looking at cloud as an infrastructure, right? So you've got an infra team, you've got an app team, you've got an incident management team, you've got a soft knock, everything. But again, so Suresh can talk about this more because they are making significant strides in thinking about this as a single workload, and how do I apply engineering to go manage this? Because a lot of it is codified, right? So automation. Anyway, so that's kind of where the complexity is and how we are thinking, including JCI as a partner thinking about taming that complexity as we move forward. >> Suresh, let's talk about that taming the complexity. You guys have both done a great job of articulating the ostensible challenges that are there with cloud, especially multi-cloud environments that you're living in. But Suresh, talk about the partnership with Hitachi Vantara. How is it helping to dial down some of those inherent complexities? >> I mean, I always, you know, I think I've said this to Prem multiple times. I treat my partners as my internal, you know, employees. I look at Prem as my coworker or my peers. So the reason for that is I want Prem to have the same vested interest as a partner in my success or JCI success and vice versa, isn't it? I think that's how we operate and that's how we have been operating. And I think I would like to thank Prem and Hitachi Vantara for that really been an amazing partnership. And as he was saying, we have taken a completely holistic approach to how we want to really be in the market and play in the market to our customers. So if you look at my jacket it talks about OpenBlue platform. This is what JCI is building, that we are building this OpenBlue digital platform. And within that, my team, along with Prem's or Hitachi's, we have built what we call as Polaris. It's a technical platform where our apps can run. And this platform is automated end-to-end from a platform engineering standpoint. We stood up a platform engineering organization, a reliability engineering organization, as well as a support organization where Hitachi played a role. As I said previously, you know, for me to scale I'm not going to really have the talent and the knowledge of every function that I'm looking at. And Hitachi, not only they brought the talent but they also brought what he was talking about, Harc. You know, they have set up a lot and now we can leverage it. And they also came up with some really interesting concepts. I went and met them in India. They came up with this concept called IPL. Okay, what is that? They really challenged all their employees that's working for GCI to come up with innovative ideas to solve problems proactively, which is self-healing. You know, how you do that? So I think partners, you know, if they become really vested in your interests, they can do wonders for you. And I think in this case Hitachi is really working very well for us and in many aspects. And I'm leveraging them... You started with support, now I'm leveraging them in the automation, the platform engineering, as well as in the reliability engineering and then in even in the engineering spaces. And that like, they are my end-to-end partner right now? >> So you're really taking that holistic approach that you talked about and it sounds like it's a very collaborative two-way street partnership. Prem, I want to go back to, Suresh mentioned Harc. Talk a little bit about what Harc is and then how partners fit into Hitachi's Harc strategy. >> Great, so let me spend like a few seconds on what Harc is. Lisa, again, I know we've been using the term. Harc stands for Hitachi application reliability sectors. Now the reason we thought about Harc was, like I said in the beginning of this segment, there is an illusion from an architecture standpoint to be more modern, microservices, server-less, reactive architecture, so on and so forth. There is an illusion in your development methodology from Waterfall to agile, to DevOps to lean, agile to path program, whatever, right? Extreme program, so on and so forth. There is an evolution in the space of infrastructure from a point where you were buying these huge humongous servers and putting it in your data center to a point where people don't even see servers anymore, right? You buy it, by a click of a button you don't know the size of it. All you know is a, it's (indistinct) whatever that name means. Let's go provision it on the fly, get go, get your work done, right? When all of this is advanced when you think about operations people have been solving the problem the way they've been solving it 20 years back, right? That's the issue. And Harc was conceived exactly to fix that particular problem, to think about a modern way of operating a modern workload, right? That's exactly what Harc. So it brings together finest engineering talent. So the teams are trained in specific ways of working. We've invested and implemented some of the IP, we work with the best of the breed partner ecosystem, and I'll talk about that in a minute. And we've got these facilities in Dallas and I am talking from my office in Dallas, which is a Harc facility in the US from where we deliver for our customers. And then back in Hyderabad, we've got one more that we opened and these are facilities from where we deliver Harc services for our customers as well, right? And then we are expanding it in Japan and Portugal as we move into 23. That's kind of the plan that we are thinking through. However, that's what Harc is, Lisa, right? That's our solution to this cloud complexity problem. Right? >> Got it, and it sounds like it's going quite global, which is fantastic. So Suresh, I want to have you expand a bit on the partnership, the partner ecosystem and the role that it plays. You talked about it a little bit but what role does the partner ecosystem play in really helping JCI to dial down some of those challenges and the inherent complexities that we talked about? >> Yeah, sure. I think partners play a major role and JCI is very, very good at it. I mean, I've joined JCI 18 months ago, JCI leverages partners pretty extensively. As I said, I leverage Hitachi for my, you know, A group and the (indistinct) space and the cloud operations space, and they're my primary partner. But at the same time, we leverage many other partners. Well, you know, Accenture, SCL, and even on the tooling side we use Datadog and (indistinct). All these guys are major partners of our because the way we like to pick partners is based on our vision and where we want to go. And pick the right partner who's going to really, you know make you successful by investing their resources in you. And what I mean by that is when you have a partner, partner knows exactly what kind of skillset is needed for this customer, for them to really be successful. As I said earlier, we cannot really get all the skillset that we need, we rely on the partners and partners bring the the right skillset, they can scale. I can tell Prem tomorrow, "Hey, I need two parts by next week", and I guarantee it he's going to bring two parts to me. So they let you scale, they let you move fast. And I'm a big believer, in today's day and age, to get things done fast and be more agile. I'm not worried about failure, but for me moving fast is very, very important. And partners really do a very good job bringing that. But I think then they also really make you think, isn't it? Because one thing I like about partners they make you innovate whether they know it or not but they do because, you know, they will come and ask you questions about, "Hey, tell me why you are doing this. Can I review your architecture?" You know, and then they will try to really say I don't think this is going to work. Because they work with so many different clients, not JCI, they bring all that expertise and that's what I look from them, you know, just not, you know, do a T&M job for me. I ask you to do this go... They just bring more than that. That's how I pick my partners. And that's how, you know, Hitachi's Vantara is definitely one of a good partner from that sense because they bring a lot more innovation to the table and I appreciate about that. >> It sounds like, it sounds like a flywheel of innovation. >> Yeah. >> I love that. Last question for both of you, which we're almost out of time here, Prem, I want to go back to you. So I'm a partner, I'm planning on redefining CloudOps at my company. What are the two things you want me to remember from Hitachi Vantara's perspective? >> So before I get to that question, Lisa, the partners that we work with are slightly different from from the partners that, again, there are some similar partners. There are some different partners, right? For example, we pick and choose especially in the Harc space, we pick and choose partners that are more future focused, right? We don't care if they are huge companies or small companies. We go after companies that are future focused that are really, really nimble and can change for our customers need because it's not our need, right? When I pick partners for Harc my ultimate endeavor is to ensure, in this case because we've got (indistinct) GCI on, we are able to operate (indistinct) with the level of satisfaction above and beyond that they're expecting from us. And whatever I don't have I need to get from my partners so that I bring this solution to Suresh. As opposed to bringing a whole lot of people and making them stand in front of Suresh. So that's how I think about partners. What do I want them to do from, and we've always done this so we do workshops with our partners. We just don't go by tools. When we say we are partnering with X, Y, Z, we do workshops with them and we say, this is how we are thinking. Either you build it in your roadmap that helps us leverage you, continue to leverage you. And we do have minimal investments where we fix gaps. We're building some utilities for us to deliver the best service to our customers. And our intention is not to build a product to compete with our partner. Our intention is to just fill the wide space until they go build it into their product suite that we can then leverage it for our customers. So always think about end customers and how can we make it easy for them? Because for all the tool vendors out there seeing this and wanting to partner with Hitachi the biggest thing is tools sprawl, especially on the cloud is very real. For every problem on the cloud. I have a billion tools that are being thrown at me as Suresh if I'm putting my installation and it's not easy at all. It's so confusing. >> Yeah. >> So that's what we want. We want people to simplify that landscape for our end customers, and we are looking at partners that are thinking through the simplification not just making money. >> That makes perfect sense. There really is a very strong symbiosis it sounds like, in the partner ecosystem. And there's a lot of enablement that goes on back and forth it sounds like as well, which is really, to your point it's all about the end customers and what they're expecting. Suresh, last question for you is which is the same one, if I'm a partner what are the things that you want me to consider as I'm planning to redefine CloudOps at my company? >> I'll keep it simple. In my view, I mean, we've touched upon it in multiple facets in this interview about that, the three things. First and foremost, reliability. You know, in today's day and age my products has to be reliable, available and, you know, make sure that the customer's happy with what they're really dealing with, number one. Number two, my product has to be secure. Security is super, super important, okay? And number three, I need to really make sure my customers are getting the value so I keep my cost low. So these three is what I would focus and what I expect from my partners. >> Great advice, guys. Thank you so much for talking through this with me and really showing the audience how strong the partnership is between Hitachi Vantara and JCI. What you're doing together, we'll have to talk to you again to see where things go but we really appreciate your insights and your perspectives. Thank you. >> Thank you, Lisa. >> Thanks Lisa, thanks for having us. >> My pleasure. For my guests, I'm Lisa Martin. Thank you so much for watching. (soothing music)

(Upbeat music playing) >> Hey everyone, thanks for joining us today. Welcome to this event of Building your Cloud Center of Excellence with Hitachi Vantara. I'm your host, Lisa Martin. I've got a couple of guests here with me next to talk about redefining cloud operations and application modernization for customers. Please welcome Prem Balasubramanian the SVP and CTO at Hitachi Vantara, and Manoj Narayanan is here as well, the Managing Director of Technology at GTCR. Guys, thank you so much for joining me today. Excited to have this conversation about redefining CloudOps with you. >> Pleasure to be here. >> Pleasure to be here >> Prem, let's go ahead and start with you. You have done well over a thousand cloud engagements in your career. I'd love to get your point of view on how the complexity around cloud operations and management has evolved in the last, say, three to four years. >> It's a great question, Lisa before we understand the complexity around the management itself, the cloud has evolved over the last decade significantly from being a backend infrastructure or infrastructure as a service for many companies to become the business for many companies. If you think about a lot of these cloud bond companies cloud is where their entire workload and their business wants. With that, as a background for this conversation if you think about the cloud operations, there was a lot of there was a lot of lift and shift happening in the market where people lifted their workloads or applications and moved them onto the cloud where they treated cloud significantly as an infrastructure. And the way they started to manage it was again, the same format they were managing there on-prem infrastructure and they call it I&O, Infrastructure and Operations. That's kind of the way traditionally cloud is managed. In the last few years, we are seeing a significant shift around thinking of cloud more as a workload rather than as just an infrastructure. And what I mean by workload is in the cloud, everything is now code. So you are codifying your infrastructure. Your application is already code and your data is also codified as data services. With now that context apply the way you think about managing the cloud has to significantly change and many companies are moving towards trying to change their models to look at this complex environment as opposed to treating it like a simple infrastructure that is sitting somewhere else. So that's one of the biggest changes and shifts that are causing a lot of complexity and headache for actually a lot of customers for managing environments. The second critical aspect is even that, even exasperates the situation is multicloud environments. Now, there are companies that have got it right with things about right cloud for the right workload. So there are companies that I reach out and I talk with. They've got their office applications and emails and stuff running on Microsoft 365 which can be on the Azure cloud whereas they're running their engineering applications the ones that they build and leverage for their end customers on Amazon. And to some extent they've got it right but still they have a multiple cloud that they have to go after and maintain. This becomes complex when you have two clouds for the same type of workload. When I have to host applications for my end customers on Amazon as well as Azure, Azure as well as Google then, I get into security issues that I have to be consistent across all three. I get into talent because I need to have people that focus on Amazon as well as Azure, as well as Google which means I need so much more workforce, I need so many so much more skills that I need to build, right? That's becoming the second issue. The third one is around data costs. Can I make these clouds talk to each other? Then you get into the ingress egress cost and that creates some complexity. So bringing all of this together and managing is really become becoming more complex for our customers. And obviously as a part of this we will talk about some of the, some of the ideas that we can bring for in managing such complex environments but this is what we are seeing in terms of why the complexity has become a lot more in the last few years. >> Right. A lot of complexity in the last few years. Manoj, let's bring you into the conversation now. Before we dig into your cloud environment give the audience a little bit of an overview of GTCR. What kind of company are you? What do you guys do? >> Definitely Lisa. GTCR is a Chicago based private equity firm. We've been in the market for more than 40 years and what we do is we invest in companies across different sectors and then we manage the company drive it to increase the value and then over a period of time, sell it to future buyers. So in a nutshell, we got a large portfolio of companies that we need to manage and make sure that they perform to expectations. And my role within GTCR is from a technology viewpoint so where I work with all the companies their technology leadership to make sure that we are getting the best out of technology and technology today drives everything. So how can technology be a good compliment to the business itself? So, my role is to play that intermediary role to make sure that there is synergy between the investment thesis and the technology lures that we can pull and also work with partners like Hitachi to make sure that it is done in an optimal manner. >> I like that you said, you know, technology needs to really compliment the business and vice versa. So Manoj, let's get into the cloud operations environment at GTCR. Talk to me about what the experience has been the last couple of years. Give us an idea of some of the challenges that you were facing with existing cloud ops and and the solution that you're using from Hitachi Vantara. >> A a absolutely. In fact, in fact Prem phrased it really well, one of the key things that we're facing is the workload management. So there's so many choices there, so much complexities. We have these companies buying more companies there is organic growth that is happening. So the variables that we have to deal with are very high in such a scenario to make sure that the workload management of each of the companies are done in an optimal manner is becoming an increasing concern. So, so that's one area where any help we can get anything we can try to make sure it is done better becomes a huge value at each. A second aspect is a financial transparency. We need to know where the money is going where the money is coming in from, what is the scale especially in the cloud environment. We are talking about an auto scale ecosystem. Having that financial transparency and the metrics associated with that, it, these these become very, very critical to ensure that we have a successful presence in the multicloud environment. >> Talk a little bit about the solution that you're using with Hitachi and, and the challenges that it is eradicated. >> Yeah, so it end of the day, right, we we need to focus on our core competence. So, so we have got a very strong technology leadership team. We've got a very strong presence in the respective domains of each of the portfolio companies. But where Hitachi comes in and HAR comes in as a solution is that they allow us to excel in focusing on our core business and then make sure that we are able to take care of workload management or financial transparency. All of that is taken off the table from us and and Hitachi manages it for us, right? So it's such a perfectly compliment relationship where they act as two partners and HARC is a solution that is extremely useful in driving that. And, and and I'm anticipating that it'll become more important with time as the complexity of cloud and cloud associate workloads are only becoming more challenging to manage and not less. >> Right? That's the thing that complexity is there and it's also increasing Prem, you talked about the complexities that are existent today with respect to cloud operations the things that have happened over the last couple of years. What are some of your tips, Prem for the audience, like the the top two or three things that you would say on cloud operations that that people need to understand so that they can manage that complexity and allow their business to be driven and complimented by technology? >> Yeah, a big great question again, Lisa, right? And I think Manoj alluded to a few of these things as well. The first one is in the new world of the cloud I think think of migration, modernization and management as a single continuum to the cloud. Now there is no lift and shift and there is no way somebody else separately manages it, right? If you do not lift and shift the right applications the right way onto the cloud, you are going to deal with the complexity of managing it and you'll end up spending more money time and effort in managing it. So that's number one. Migration, modernization, management of cloud work growth is a single continuum and it's not three separate activities, right? That's number one. And the, the second is cost. Cost traditionally has been an afterthought, right? People move the workload to the cloud. And I think, again, like I said, I'll refer back to what Manoj said once we move it to the cloud and then we put all these fancy engineering capability around self-provisioning, every developer can go and ask for what he or she wants and they get an environment immediately spun up so on and so forth. Suddenly the CIO wakes up to a bill that is significantly larger than what he or she expected right? And, and this is this is become a bit common nowadays, right? The the challenge is because we think cost in the cloud as an afterthought. But consider this example in, in previous world you buy hard, well, you put it in your data center you have already amortized the cost as a CapEx. So you can write an application throw it onto the infrastructure and the application continues to use the infrastructure until you hit a ceiling, you don't care about the money you spent. But if I write a line of code that is inefficient today and I deploy it on the cloud from minute one, I am paying for the inefficiency. So if I realize it after six months, I've already spent the money. So financial discipline, especially when managing the cloud is now is no more an afterthought. It is as much something that you have to include in your engineering practice as much as any other DevOps practices, right? Those are my top two tips, Lisa, from my standpoint, think about cloud, think about cloud work, cloud workloads. And the last one again, and you will see you will hear me saying this again and again, get into the mindset of everything is code. You don't have a touch and feel infrastructure anymore. So you don't really need to have foot on the ground to go manage that infrastructure. It's codified. So your code should be managing it, but think of how it happens, right? That's where we, we are going as an evolution >> Everything is code. That's great advice, great tips for the audience there. Manoj, I'll bring you back into the conversation. You know, we, we can talk about skills gaps on on in many different facets of technology the SRE role, relatively new, skillset. We're hearing, hearing a lot about it. SRE led DevSecOps is probably even more so of a new skillset. If I'm an IT leader or an application leader how do I ensure that I have the right skillset within my organization to be able to manage my cloud operations to, to dial down that complexity so that I can really operate successfully as a business? >> Yeah. And so unfortunately there is no perfect answer, right? It's such a, such a scarce skillset that a, any day any of the portfolio company CTOs if I go and talk and say, Hey here's a great SRE team member, they'll be more than willing to fight with each of to get the person in right? It's just that scarce of a skillset. So, so a few things we need to look at it. One is, how can I build it within, right? So nobody gets born as an SRE, you, you make a person an SRE. So how do you inculcate that culture? So like Prem said earlier, right? Everything is software. So how do we make sure that everybody inculcates that as part of their operating philosophy be they part of the operations team or the development team or the testing team they need to understand that that is a common guideline and common objective that we are driving towards. So, so that skillset and that associated training needs to be driven from within the organization. And that in my mind is the fastest way to make sure that that role gets propagated across organization. That is one. The second thing is rely on the right partners. So it's not going to be possible for us, to get all of these roles built in-house. So instead prioritize what roles need to be done from within the organization and what roles can we rely on our partners to drive it for us. So that becomes an important consideration for us to look at as well. >> Absolutely. That partnership angle is incredibly important from, from the, the beginning really kind of weaving these companies together on this journey to to redefine cloud operations and build that, as we talked about at the beginning of the conversation really building a cloud center of excellence that allows the organization to be competitive, successful and and really deliver what the end user is, is expecting. I want to ask - Sorry Lisa, - go ahead. >> May I add something to it, I think? >> Sure. >> Yeah. One of the, one of the common things that I tell customers when we talk about SRE and to manages point is don't think of SRE as a skillset which is the common way today the industry tries to solve the problem. SRE is a mindset, right? Everybody in >> Well well said, yeah >> That, so everybody in a company should think of him or her as a cycle liability engineer. And everybody has a role in it, right? Even if you take the new process layout from SRE there are individuals that are responsible to whom we can go to when there is a problem directly as opposed to going through the traditional ways of AI talk to L one and L one contras all. They go to L two and then L three. So we, we, we are trying to move away from an issue escalation model to what we call as a a issue routing or a incident routing model, right? Move away from incident escalation to an incident routing model. So you get to route to the right folks. So again, to sum it up, SRE should not be solved as a skillset set because there is not enough people in the market to solve it that way. If you start solving it as a mindset I think companies can get a handhold of it. >> I love that. I've actually never heard that before, but it it makes perfect sense to think about the SRE as a mindset rather than a skillset that will allow organizations to be much more successful. Prem I wanted to get your thoughts as enterprises are are innovating, they're moving more products and services to the as a service model. Talk about how the dev teams the ops teams are working together to build and run reliable, cost efficient services. Are they working better together? >> Again, a a very polarizing question because some customers are getting it right many customers aren't, there is still a big wall between development and operations, right? Even when you think about DevOps as a terminology the fundamental principle was to make sure dev and ops works together. But what many companies have achieved today, honestly is automating the operations for development. For example, as a developer, I can check in code and my code will appear in production without any friction, right? There is automated testing, automated provisioning and it gets promoted to production, but after production, it goes back into the 20 year old model of operating the code, right? So there is more work that needs to be done for Devon and Ops to come closer and work together. And one of the ways that we think this is achievable is not by doing radical org changes, but more by focusing on a product-oriented single backlog approach across development and operations. Which is, again, there is change management involved but I think that's a way to start embracing the culture of dev ops coming together much better now, again SRE principles as we double click and understand it more and Google has done a very good job playing it out for the world. As you think about SRE principle, there are ways and means in that process of how to think about a single backlog. And in HARC, Hitachi Application Reliability Centers we've really got a way to look at prioritizing the backlog. And what I mean by that is dev teams try to work on backlog that come from product managers on features. The SRE and the operations team try to put backlog into the say sorry, try to put features into the same backlog for improving stability, availability and financials financial optimization of your code. And there are ways when you look at your SLOs and error budgets to really coach the product teams to prioritize your backlog based on what's important for you. So if you understand your spending more money then you reduce your product features going in and implement the financial optimization that came from your operations team, right? So you now have the ability to throttle these parameters and that's where SRE becomes a mindset and a principle as opposed to a skillset because this is not an individual telling you to do. This is the company that is, is embarking on how to prioritize my backlog beyond just user features. >> Right. Great point. Last question for both of you is the same talk kind of take away things that you want me to remember. If I am at an IT leader at, at an organization and I am planning on redefining CloudOps for my company Manoj will start with you and then Prem to you what are the top two things that you want me to walk away with understanding how to do that successfully? >> Yeah, so I'll, I'll go back to basics. So the two things I would say need to be taken care of is, one is customer experience. So all the things that I do end of the day is it improving the customer experience or not? So that's a first metric. The second thing is anything that I do is there an ROI by doing that incremental step or not? Otherwise we might get lost in the technology with surgery, the new tech, et cetera. But end of the day, if the customers are not happy if there is no ROI, everything else you just can't do much on top of that >> Now it's all about the customer experience. Right? That's so true. Prem what are your thoughts, the the top things that I need to be taking away if I am a a leader planning to redefine my cloud eye company? >> Absolutely. And I think from a, from a company standpoint I think Manoj summarized it extremely well, right? There is this ROI and there is this customer experience from my end, again, I'll, I'll suggest two two more things as a takeaway, right? One, cloud cost is not an afterthought. It's essential for us to think about it upfront. Number two, do not delink migration modernization and operations. They are one stream. If you migrate a long, wrong workload onto the cloud you're going to be stuck with it for a long time. And an example of a wrong workload, Lisa for everybody that that is listening to this is if my cost per transaction profile doesn't change and I am not improving my revenue per transaction for a piece of code that's going run in production it's better off running in a data center where my cost is CapEx than amortized and I have control over when I want to upgrade as opposed to putting it on a cloud and continuing to pay unless it gives me more dividends towards improvement. But that's a simple example of when we think about what should I migrate and how will it cost pain when I want to manage it in the longer run. But that's, that's something that I'll leave the audience and you with as a takeaway. >> Excellent. Guys, thank you so much for talking to me today about what Hitachi Vantara and GTCR are doing together how you've really dialed down those complexities enabling the business and the technology folks to really live harmoniously. We appreciate your insights and your perspectives on building a cloud center of excellence. Thank you both for joining me. >> Thank you. >> For my guests, I'm Lisa. Martin, you're watching this event building Your Cloud Center of Excellence with Hitachi Vantara. Thanks for watching. (Upbeat music playing) (Upbeat music playing) (Upbeat music playing) (Upbeat music playing)

(upbeat music) >> Hey everyone, welcome to this event: Build Your Cloud Center of Excellence. I'm your host, Lisa Martin, and I have two guests here with me today to talk about the hybrid cloud, the multi-cloud trends, and specifically the complexity. While we know these trends provide agility and flexibility for customers, they also bring in complexity. And this session is going to focus on exploring that with RBI and HitachiVantara. Please welcome my guests, Adithya Sastry the SVP of Digital Solutions at HitachiVantara and Werner Mayer, head of group core IT and head of group data at RBI International. Guys, welcome to the program. >> Thank you Lisa. Werner, nice to see you again. >> Great to see you both. >> And Werner, we're going to start with you. Talk about RBI. Tell the audience a little bit about what the business is and then we're going to get into your cloud transformation journey over the last couple of years. >> Yes, thank you. So Raiffeisen Bank International is international working banking groups. So our core markets are Central Eastern European, Central Eastern Europe and Austria. And we are serving around 50 million clients in this market. So we active in 13 markets. >> Got it. Talk to me, Werner about the cloud transformation journey that RBI has been on over the last couple of years and some of the complexities that you've experienced as you've launched it. >> Sure. Thank you for the question. So in 2020, we decided that we have to renew our IT strategy. And the aim of the strategy was to change the organization in a way that it can react and adapt fast to the future challenges. So one of the important pillars for us was that we are adapting fast also for new technologies. And this was core pillar in our strategy. So we're searching for technologies which are fit in to our HR transformation. And we found that the cloud and the public cloud environment fits to this venture. So we tested that. We are building up also the competent centers for that and also established the group cloud platform for that. Because our invoice to onboard our international group with the 13 units to this group cloud platform. So that means we have a lot to do to hardening the platforms in terms of security to put in. We have standard for that. We have to introduce large scale programs to train hundreds of engineers. We tested the approach, We convinced the top management and we implemented this, this program. So one of the highlights was, of course, also the the safeguarding of the Ukraine, let's say, banking environment. So we had to lift and shift the complete bank in three months. And it shows that let's say our platforms works. And let's say the approach is proven that we can scale it over the group. >> That's a big challenge. A lot of complexity especially with some of the global things going on. Adithya, these challenges are, are not unique to RBI. A lot of your customers are facing challenges with complexity around cloud management, cloud ops. What can you unpack was the real issue is here? >> Yeah, Lisa, absolutely. And you know, before I answer your question, I do want to, you know, just say a couple of things about Raiffeisen Bank. And you know, we've had the pleasure of working with them for about a year, a little bit more than a year now. And, and, and the way they approach the cloud transformation journey is - should be a template for a lot of the organizations in terms of the preparation in terms of understanding, you know. How other companies have done it and what are the pitfalls. What's worked, and really what's the recipe for their, you know, journey, right? Which is very unique because, you know, you look at you know, being present across 30 different countries within central and eastern Europe as Werner said. And the complexities of dealing with local regulations, GDPR and all these other issues that come with it, right? And not to mention the language variation from country to country. So, you know, phenomenal story there. The journey and the journey still goes, right Werner? It's not complete yet. But Lisa, to your question, you know. When we look at, you know, the complexities of this transformation, that most modern enterprises are going through. It's not very unique, right? What is unique for a Raiffeisen Bank is - has been the preparation. But as you get into this journey of moving workloads to cloud, be it refactoring, modernizing, migrating, etc. One of the things that really is often overlooked is: "Are my applications applications and data workloads resilient on, on the, on the cloud?" Meaning are they - How is the performance? Are they just running or are they performing with high availability to meet your customers goals? Is it scalable? And are my cost in line with what I projected when I moved prep, right? Because that's one of the areas we are seeing where you know, what enterprises projected from a cost savings to what they're realizing a year and a half into the journey is a pretty big delta, right? And, and, and a lot of it is dependent on are the cloud - are the applications and the workloads cloud, designed for the cloud? Or are they designed for on-prem which you just move to the cloud. >> So Werner, it sounds like what Adithya said is a compliment to, to you guys and the team at RBI in terms of this being a template for managing complexity. Give us, Werner, your perspective in terms of modern cloud ops. What's in? What's out? What is it that customers really need to be focusing on to be successful? >> Thanks for the compliment, Lisa. And I think this is a great relationship also in the journey. Topic is, is, is a - is a complex program where a lot of things have to fit together. But it was mentioning the resilience. The course, we call it finops, security operations and so on have to come together and have to work on spot. At the end, it's also, let's say, how we are able enabling our teams and how we are ramping out the skills of our teams to deal with these multidimensional, let's say environments. And this is something what we spend a lot of time in order to prepare, but also to bring up the people on a certain level that they can operate at. Because card guard handling is, is different than before. Because beforehand you have central operations team. They do everything for you. But in this world let's say we are also putting the responsibility of the run component of the absent to the - in the tribes and the application teams. And they have to do much more than before. On the other hand, we have first central rules. We have monitoring functions. We have support functions on that in order to best support them in their journey. So this is a hybrid between, let's say, what the teams have to do with the responsibility in the teams, but also with the central functions which are supporting them. And everything have to work together and goes hand in - right, to go hand-in-hand. >> Yeah. Yeah. And if, if I could just add Lisa really quick and and Werner hit the nail on the head, right? Because you cannot look at cloud operation the way we have traditionally looked at managed services. That's the key thing, right? You cannot, you know, traditional managed services you had L1, L2, L3 and then it goes into some sort of a vacuum and then all of a sudden somebody calls you at some point, right? >> Werner: Exactly. >> And it really has flipped, right? To, to Werner's point. And Werner hit that name on the head because you really have to understand. Bring an engineering led approach to make sure that the problems, you know, when you see an issue that you have some level of automation in terms of problem isolation. And then the problem is routed the right individual ie the application engineering team or the data engineering team for resolution in a rapid manner. Right? I think that the key - >> Yes. A very important point with that is said, yeah. So you cannot traditional transport let's say, the operation model what you have now into the cloud because this will not work, yeah. And finally at the end you will not benefit on the technology possibilities there. So super important point. My vision in the cloud and this is also something what we are working on is a sort of zero-ops environment, yeah? Because we're ultimately dealing with the automatization technologies and so on, you can that much - to much more compared to the traditional environment and the benefit of the cloud is: You can test it. You can give it feedback when it is not working, yeah? So it's a completely different operating model. What we try to establish in the cloud environment. >> So really what this seems like guys is is quite a delicate balance that you're solving for. Not the only delicate balance but Werner sticking with you. Talk to us about some of the challenges that you've had around cloud cost management in particular. Help us understand that. >> Thanks for the question. So in principle, we are doing very well on the cost side, surprisingly. And we also started the cloud journey that is said this is not the cost case. Because as I said before, let's say one of the pillars in the strategy strategy was the enablement of technology to the benefit of customer solutions to be adaptive, to be faster. But at the end it turned out that let's say with giving the responsibility of the operation to the dedicated team, they found they - they were working much closer to the cost, and let's say monitoring the cost, then we headed into traditional environments, yeah? I also saw some examples in the group where sort of gamification of the cost were going on. To say who can save more To say who can save more and make more much more out of that what you have in the cloud. And at the end we see that in minimum the cost are balance to the traditional environments in the data centers. But we also saw that let's say, the cost were brought down much more than before. So at the beginning we were relative conservative with the assumptions, yeah? But it turns out that we are really getting the benefit. The things are getting faster and also the costs are going down. And we see this in real cases. >> Yeah. And, and, and Lisa, if I could add something really quick, right? Because - You know, there's been a mad rush to the cloud, right? Everybody kind of, it was, you know, the buzz the buzz was let's get to the cloud. We'll start to realize all these savings. And all of a sudden, everything kind of magically gets better, right? And what we have seen is also, you know, companies or customers or enterprises that have started this journey about 5, 6 years ago and are about, you know, a few years into it. What we are realizing is the cloud costs have increased significantly to what their projections were early on. And the way they're trying to address the cloud cost is by creating a FinOps organization that's looking at, you know, the cost of cloud from a structure standpoint and support as a reactive measure. Saying, "Hey if we move from Azure or one provider to another is there any benefit? If we move certain applications from the cloud back to on-prem, is there any benefit?" When in fact, one of the things that we have noticed really is: The problem needs to shift left to the engineering teams. Because if you are designing the applications and the systems the right way to begin with, then you can manage the data cost issues or the cost overruns, right? So you design for the cloud as opposed to designing and then looking at how do we optimize cloud. >> So Adithya, you talked about the RBI use case as really kind of a template but also some of the challenges with respect to hybrid and multi-cloud are kind of like a chicken and egg scenario. Talk to us kind of like overall about how Hitachi is really helping customers address these challenges and maximize the benefits to get the flexibility to get the agility so that they can deliver what their end user customers are expecting. >> Yeah, yeah. So, so one of the things we are doing, Lisa, when we work with customers, is really trying to understand, you know, look at their entire portfolio of applications, right? And, and look at what the intent of the applications is between customer facing, external customer, internal customer, high availability, production, etc., right? And then we go through a methodology called E3 which is envision, enable and execute. Which is really envision what the end stage should be regardless of what the environment is, right? And then we enable, which is really kind of go through a proof of value to move a few workloads, to modernize, rearchitect, replatform, etc. And look at the benefit of that application on its destination. If it's a cloud - if it's a cloud service provider or if it's another data center, whatever it may be, right? And finally, you know, once we've proven the value and the benefit and and say and kind of monetize the, you know realize the value of it from an agility, from a cost, from security and resilience, etc. Then we go through the execution, which was look we look at the entire portfolio, the entire landscape. And we go through a very disciplined manner working with our customers to roadmap it. And then we execute in a very deliberate manner where you can see value every 2-3 months. Because gone the days when you can do things as a science project that took 2-3 years, right? We, we - Everyone wants to see value, want to see - wants to see progress, and most importantly we want to see cost benefit and agility sooner than later. >> Those are incredibly important outcomes. You guys have done a great job explaining what you're doing together. This sounds like a great relationship. All right, so my last question to both of you is: "If I'm a customer and I'm planning a cloud transformation for my company, what are the two things you want me to remember and consider as I plan this? Werner, we'll start with you. >> I would pick up two things, yeah? The first one is: When you are organizing your company in HR way, then cloud is the HR technology for the HR transformation. Because HR teams needs HR technology. And the second important thing is, what I would say is: Cloud is a large scale and fast moving technology enabler to the company. So if your company is going forward to say: Technology is their enabler tool from a future business then cloud can support this journey. >> Excellent. I'm going to walk away with those. And Adithya, same question to you. I'm a, I'm a customer. I'm at an organization. I'm planning a cloud transformation. Top two things you want me to walk away with. >> Yeah. And I think Werner kind of actually touched on that in the second one, which is: it's not a tech, just an IT or a technology initiative. It is a business initiative, right? Because ultimately what you do from this cloud journey should drive, you know, should lead into business transformation or help your business grow top line or drive margin expansion, etc. So couple of things I would say, right? One is, you know, get Being and prioritize. Work with your business owners, with, you know with the cross-functional team not just the technology team. That's one. The second thing is: as the technology team or the IT team shepherds this journey, you know, keep everyone informed and engaged as you go through this journey. Because as you go through moving workloads modernizing workload, there is an impact to, you know receivables through omnichannel experiences the way customers interact and transact with you, right? And that comes with making making sure your businesses are aware your business stakeholders are aware. So in turn the end customers are aware. So you know, it's not a one and done from an engagement, it's a journey. And bring in the right experts. Talk to people who've done it, done this before, who have kind of stepped in all the pitfalls so you don't have to, right? That's the key. >> That's great advice. That's great advice for anything in life, I think. You talk about the collaboration, the importance of the business and the technology folks coming together. It really has to be - It's a delicate balance as we said before but it really has to be a holistic collaborative approach. Guys, thank you so much for joining me talking through what HitachiVantara and RBI are doing together. It sounds like you're well into this journey and it sounds like it's going quite well. We thank you so much for your insights and your perspectives. >> Thank you, Lisa. Werner, thank you again. >> Good stuff guys. For my guests, I'm Lisa Martin. Thank you so much for watching our event: Build Your Cloud Center of Excellence. (upbeat music)