 From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. The next 10 years of cloud, they're going to differ dramatically from the past decade. You know, the early days of cloud deployed virtualization of standard off-the-shelf components, x86 microprocessors, disk drives, you know, et cetera, to then scale out and build a large distributed system. The coming decade is going to see a much more data-centric, real-time, intelligent, call it even hyper-decentralized cloud that will comprise on-prem, hybrid, cross-cloud and edge workloads with a services layer that will abstract the underlying complexity of the infrastructure, which will also comprise much more custom and varied components. This was a key takeaway of the guests from theCUBE on cloud, an event hosted by SiliconANGLE in theCUBE. Welcome to this week's Wikibon Cube Insights, powered by ETR. In this episode, we'll summarize the findings of our recent event and extract the signal from our great guests with a couple of series and comments and clips from the show. Cube on cloud is our very first virtual editorial event. It was designed to bring together our community in an open forum. We ran the day on our 365 software platform and had a great lineup of CEOs, CIOs, data practitioners, technologists, we had cloud experts, analysts, and many opinion leaders, all brought together in a day-long series of sessions that we developed in order to unpack the future of cloud computing in the coming decade. Let me briefly frame up the conversation and then turn it over to some of our guests. First, we put forth our view of how modern cloud has evolved and where it's headed. This graphic that we're showing here, it talks about the progression of cloud innovation over time. Of cloud, like many innovations, it started as a novelty. When AWS announced S3 in March of 2006, nobody in the vendor or user communities, really even in the trade press, really paid too much attention to it. Then later that year, Amazon announced EC2 and people started to think about a new model of computing. But it was largely tire kickers, bleeding edge developers that took notice and really leaned in. Now the financial crisis of 2007 to 2009 really created what we call a cloud awakening and it put cloud on the radar of many CFOs. Shadow IT emerged within departments that wanted to take IT and bite-sized chunks and along with the CFO wanted to take it as OPEX versus CAPEX. And then IT transformation, that phase really took hold. We came out of the financial crisis and we've been on an 11 year cloud boom. And it doesn't look like it's going to stop anytime soon. Cloud has really disrupted the on-prem model as we've reported and completely transformed IT. You know, ironically the pandemic hit at the beginning of this decade and it created a mandate to go digital. And so it accelerated the industry transformation that we're highlighting here, which probably would have taken several more years to mature, but overnight, the forced march to digital happened and it looks like it's here to stay. Now the next wave we think will be much more about business or industry transformation. We're seeing the first glimpses of that. Holger Müller of Constellation Research summed it up at our event very well, I thought. He basically said, the cloud is the big winner of COVID. Of course, we know that. Now normally we talk about seven year economic cycles, he said. He was talking about for planning and investment cycles. Now we operate in seven day cycles. You know, the examples he gave were, do we open or close the store? How do we pivot to support remote workers without the burden of CAPEX? And we think that the things listed on this chart are going to be front and center in the coming years. Data, AI, a fully digitized and intelligent stack that will support next gen disruptions in autos, manufacturing, finance, farming and virtually every industry. Where the system will expand to the edge and the underlying infrastructure across physical locations will be hidden. Many issues remain, not the least of which is latency which we talked about at the event in quite some detail. So let's talk about how the big three cloud players are going to participate in this next era. Well, in short, the consensus from the event was that the rich get richer. Let's take a look at some data. This chart shows our most recent estimates of IAS and PAS spending for the big three. Now we're going to update this after earning season but there's a couple of points stand out. First, I want to make the point that combined the big three now account for almost $80 billion of infrastructure spend last year. That $80 billion, that was not all incremental, no. It's caused consolidation and disruption in the on-prem data center business and within IT shops. Companies like Dell, HPE, IBM, Oracle, many others have felt the heat and have had to respond with hybrid and cross-cloud strategies. Second, well, it's true that Azure and GCP, they appear to be growing faster than AWS. You know, we don't know really the exact numbers of course because only AWS provides a clean view of IAS and PAS whereas Microsoft and Google, they kind of hide them all ball on their numbers which by the way, I don't blame them but they do leave breadcrumbs and clues on growth rates and we have other means of estimating through surveys and the like but it's undeniable that Azure is closing the revenue gap on AWS. The third is that despite the fact that Azure and Google are growing faster than AWS, AWS is the only company by our estimates to grow its business sequentially last quarter and in and of itself, that's not really important. What is significant is that because AWS is so large now at 45 billion, even at their slower growth rates, it grows much more in absolute terms than its competitors. So we think AWS is going to keep its lead for some time. We think Microsoft and AWS will continue to lead the pack, you know, they might converge, maybe it'll be a two horse race in terms of who's first, who's second in terms of cloud revenue and how it's counted depending on what they count in their numbers and Google, look, with its balance sheet and global network, it's going to play the long game and virtually everyone else with the exception of perhaps Alibaba is going to be secondary players on these platforms. Now this next graphic underscores that reality and kind of lays out the competitive landscape. What we're showing here is survey data from ETR of more than 1400 CIOs and IT buyers and on the vertical axis is net score which measures spending momentum on the horizontal axis is so-called market share which is a measure of pervasiveness in the data set. The key points are AWS and Microsoft, look at it, they stand alone, they're so far ahead of the pack. I mean, they really literally would have to fall down and lose their lead. High spending velocity and large share of the market or the hallmarks of these two companies. And we don't think that's going to change anytime soon. Now Google, even though it's far behind, they have the financial strength to continue to position themselves as an alternative to AWS and of course an analytics specialist. So it will continue to grow but it will be challenged we think to catch up to the leaders. Now take a look at the hybrid zone where the field is playing. These are companies that have a large on-prem presence and have been forced to initiate a coherent cloud strategy of course including multi-cloud and we include Google in this pack because they're behind and they have to take a differentiated approach relative to AWS and maybe cozy up to some of these traditional enterprise vendors to help Google get to the enterprise. And you can see from the on-prem crowd VMware cloud on AWS stands out having some momentum as does Red Hat OpenShift which is cloudy but it's really sort of an ingredient. It's not really broad IS specifically but it's a component of cloud. VMware cloud which includes VCF or VMware cloud foundation and even Dell's cloud. We would expect HPE with its GreenLake strategy its financials are shoring up should be picking up momentum in the future in terms of what the customers of this survey consider cloud. And then of course you can see IBM and Oracle you're in the game but they don't have the spending momentum and they don't have the capex chops to compete with the hyperscalers. IBM's cloud revenue actually dropped 7% last quarter so that highlights the challenges that that company facing Oracle's cloud business and then it's growing in the single digits kind of up and down but again underscores these two companies are really about migrating their software installed bases to their captive clouds. And as well for IBM for example it's launched a financial cloud as a way to differentiate and not take AWS head on in infrastructures of service. The bottom line is that other than the big three in Alibaba the rest of the pack will be plugging into hybridizing and cross a clouding those platforms. And there are definitely opportunities there specifically related to creating that abstraction layer that we talked about earlier and hiding that underlying complexity and importantly creating incremental value. Good examples, Snowflake what Snowflake is doing with its data cloud what the data protection guys are doing a company like Clumeo is headed in that direction as are others. So keep an eye on that and think about where the white space is and where the value can be across clouds that's where the opportunity is. So let's see, what is this all going to look like? How does the Cube community think it's going to unfold? Let's hear from the Cube guests and the Cube on cloud speakers and some of those highlights. Now, unfortunately we don't have time to show you clips from every speaker. We are like 10 plus hours of video content but we've tried to pull together some comments that summarize the sentiment from the community. So I'm going to have John Furrier briefly explain what the Cube on cloud is all about and then let the guests speak for themselves. After John Pradeep Sindhu is going to give a nice technical overview of how the cloud was built out and what's changing in the future. I'll give you a hint, has to do with data. And then speaking of data, Mylan Thompson Bukovic who heads up AWS's storage portfolio she'll explain how she views the changes, the coming changes in cloud and how they look at storage. Again, no surprise, it's all about data. Now, one of the themes that you'll hear from guests is the notion of a distributed cloud model and Jamak Deghani who's a data architect she'll explain her view of the future of data architectures. We also have thoughts from analysts like Zs Karavala and Maribel Lopez and some comments from both Microsoft and Google to compliment AWS's view of the world. In fact, we asked J.G. Chirapirath from Microsoft to comment on the common narrative that Microsoft's products are not best of breed. You know, they put out a 1.0 and then they get better. You know, or sometimes people say, well, they're just good enough. So we'll see what his response is to that. And Paul Gillan asks, Amit Zavri of Google his thoughts on the cloud leaderboard and how Google thinks about their third place position. D. Raj Pandey gives his perspective on how technology has progressed and been miniaturized over time and what's coming in the future. And then Simon Crosby gives us a framework to think about the edge as the most logical opportunity to process data not necessarily a physical place. And this was echoed by John Rose and Chris Wolfe to experienced CTOs who went into some great depth on this topic. Unfortunately, I don't have the clips of those two but their comments can be found on the CTO power panel. The technical edge it's called. That's the segment at the Cube on cloud event site which we'll share the URL later. Now the highlight reel ends with CEO, Joni Clipper. She talks about the changes in securing the cloud from a developer angle. And finally we wrap up with the CIO perspective. Dan Sheehan, he provides some practical advice on building on his experience as a CIO, CIO and CTO specifically. How do you as a business technology leader deal with the rapid pace of change and still be able to drive business results? Okay, so let's now hear from the community. Please run the highlights. Well, I think one of the things we talked about COVID is this personal impact to me, but other people as well. One of the things that people are craving right now is information factual, information truth, tech truth as we call it. But here this event for us, Dave, it's our first inaugural editorial event, Rob Bo, Kristen, Nicole, the entire Cube team, Silicon angle, really trying to put together more of a cadence. We're going to do more of these events where we can put out and feature the best people in our community that have great, fresh voices. You know, we do interview the big names, Andy Jassy, Michael Dell, the billionaires, the people making things happen, but it's often the people under them that are the real news makers. If you look at the architecture of a cloud data centers, the single most important invention was scale out. Scale out of identical or near identical servers all connected to a standard IP Ethernet network. That's the architecture. Now, the building blocks of this architecture is Ethernet switches, which make up the network, IP Ethernet switches. And then the servers are all built using general purpose x86 CPUs with DRAM, with SSD, with hard drives all connected inside the CPU. Now, the fact that you scale these server nodes as they're called out was very, very important in addressing the problem of how do you build very large scale infrastructure using general purpose compute. But this architecture is a compute-centric architecture. And the reason it's a compute-centric architecture is if you open this, a server node, what you see is a connection to the network, typically with a simple network interface card. And then you have CPUs, which are in the middle of the action. Not only are the CPUs processing the application workload, but they're processing all of the IO workload, what we call data-centric workload. And so when you connect SSDs and hard drives and GPUs and everything to the CPU, as well as to the network, you can now imagine that the CPU is doing two functions. It's running the applications, but it's also playing traffic cop for the IO. So every IO has to go to the CPU and you're executing instructions, typically in the operating system, and you're interrupting the CPU many, many millions of times a second. Now, general purpose CPUs and the architecture of these CPUs was never designed to play traffic cop, because the traffic cop function is a function that requires you to be interrupted very, very frequently. So it's critical that in this new architecture, where there's a lot of data, a lot of e-stressed traffic, the percentage of workload, which is data-centric has gone from maybe one to 2% to 30 to 40%. The path to innovation is paved by data. If you don't have data, you don't have machine learning. You don't have the next generation of analytics applications that helps you chart a path forward into a world that seems to be changing every week. And so in order to have that insight, in order to have that predictive forecasting that every company needs, regardless of what industry that you're in today, it all starts from data. And I think the key shift that I've seen is how customers are thinking about that data about being instantly usable. Whereas in the past, it might have been a backup, now it's part of a data lake. And if you can bring that data into a data lake, you can have not just analytics or machine learning or auditing applications, it's really what does your application do for your business and how can it take advantage of that vast amount of shared data set in your business? We are actually moving towards decentralization. If we think today, like if let's move data aside, if we said the only way web would work, the only way we get access to various applications on the web or pages is to centralize it, we would laugh at that idea. But for some reason, we don't question that when it comes to data, right? So I think it's time to embrace the complexity that comes with the growth of number of sources, the proliferation of sources and consumptions models, embrace the distribution of sources of data that they're not just within one part of organization, they're not just within even bounds of organization, they're beyond the bounds of organization. And then look back and say, okay, if that's the trend of our industry in general, given the fabric of computation and data that we put in globally in place, then how the architecture and technology and organizational structure incentives need to move to embrace that complexity. And to me, that requires a paradigm shift, a full stack from how we organize our organizations, how we organize our teams, how we put a technology in place to look at it from a decentralized angle. I actually think we're in the midst of the transition to what's called the distributing cloud, where if you look at modernized cloud apps today, they're actually made up of services from different clouds and also distributed edge locations. And that's going to have a pretty profound impact in the way we build apps. We wake up every day worrying about our customer and worrying about the customer condition and to absolutely make sure we deliver the best in the first attempt that we do. So when you take the plethora of products we've delivered in Azure, be it Azure SQL, be it Azure Cosmos DB, Synapse, Azure Databricks, which we did in partnership with Databricks, Azure Machine Learning. And recently, when we sort of offered the world's first comprehensive data governance solution in Azure Perview, I would humbly submit to you that we are leading the way. How important are rankings within the Google Cloud team or are you focused mainly more on growth and just consistency? No, I don't think, again, I'm not worried about, we are not focused on ranking or any of that stuff typically. I think we're worried about making sure customers are satisfied and we add in more and more customers. So if you look at the volume of customers we are signing up, a lot of the large deals we're doing, if you look at the announcements we made over the last year has been tremendous momentum around that. You know, the thing that is really interesting about where we have been versus where we're going is we spent a lot of time talking about virtualizing hardware and moving that around and what does that look like? And creating that as more of a software paradigm. And the thing we're talking about now is what does cloud as an operating model look like? What is the manageability of that? What is the security of that? What, you know, we've talked a lot about containers and moving into different, you know, dev sec ops and all those different trends that we've been talking about, like now we're doing them. So we've only gotten to the first crank of that. And I think every technology vendor we talked to now has to address how are they gonna do a highly distributed management and security landscape? Like what are they gonna layer on top of that? Because it's not just about, oh, I've taken a rack of something, server storage compute and virtualized it. I now have to create a new operating model around it. In a way, we're almost redoing what the OSI stack looks like and what the software and solutions are for that. And the whole idea of, you know, we in every recession, we make things smaller. You know, in 91, we said we're gonna go away from mainframes into UNIX servers and we made the unit of compute smaller. Then in the year 2000, when there was the next bubble burst and the recession afterwards, we moved from UNIX servers to Wintel, you know, Windows and Intel, x86 and eventually Linux as well. Again, we made things smaller, going from million dollar servers to $5,000 servers, shorter Lib servers. And that's what we did in 2008, 2009. I said, look, we don't even need to buy servers. We can do things with virtual machines, which are servers that are an incarnation in the digital world. There's nothing in the physical world that actually even lives, but we made it even smaller. And now with cloud in the last three, four years and what will happen in this coming decade, we're gonna make it even smaller, not just in space, which is size, you know, with functions and containers and virtual machines, but also in time. So I think the right way to think about edge is where can you reasonably process the data? And it obviously makes sense to process data at the first opportunity you have, but much data is encrypted between the original device say and the application. And so edge as a place doesn't make as much sense as edge as an opportunity to decrypt and analyze data in the clear. When I think of shift left, I think of that mobius that we all look at all of the time in how we deliver and like plan, write code, deliver software, and then manage it, monitor it, right? Like that entire DevOps workflow. And today when we think about where security lives, it either is a blocker to deploying production or most commonly it lives long after code has been deployed to production and there's a security team constantly playing catch up, trying to ensure that the development team, whose job is to deliver value to their customers quickly, right? Deploy as fast as we can as many great customer facing features. They're then looking at it months after software has been deployed and then hurrying and trying to assess where the bugs are and trying to get that information back to software developers so that they can fix those issues. Shifting left to me means software engineers are finding those bugs as they're writing code or in the CI CD pipeline long before code has been deployed to production. Doing this for quite a while now, it still comes down to the people. I can get the technology to do what it needs to do as long as I have the right requirements so that goes back to people, making sure you have the partnership that goes back to leadership and the people and then the change management aspects. Right out of the gate, you should be worrying about how this change is going to be, how it's going to affect and then the adoption and engagement because adoption is critical because you can go create the best thing you think from a technology perspective but if it doesn't get used correctly, it's not worth the investment. So I agree, whether it's digital transformation or innovation, it still comes down to understanding the business model and injecting and utilizing technology to grow or reduce costs, grow the business or reduce costs. Okay, so look, there's so much other content on theCUBE on Cloud Events site. We'll put the link in the description below. We have other CIOs like Kathy Southwick and Alan Nance. We have the CIO of UiPath, Daniel Dinez, talks about automation in the cloud. Anna Pinzuk from Anaplan, Anaplan is not her company, by the way. Dave Humphrey from Bain also talks about his $750 million investment in Nutanix. Interesting, Rachel Stevens from Redmonk talks about the future of software development in the cloud and CTO Hilary Hunter talks about the cloud going vertical into financial services. And of course, John Furrier and I, along with special guests like Sarbjit Johal, share our take on key trends, data and perspectives. So right here, you see theCUBE on cloud, there's the URL. Check it out again, we'll pop this URL in the description of the video. So there's some great content there. I want to thank everybody who participated. And thank you for watching this special episode of theCUBE Insights powered by ETR. This is Dave Vellante and I'd appreciate any feedback you might have on how we can deliver better event content for you in the future. We'll be doing a number of these and we look forward to your participation and feedback. Thank you. All right, take care. We'll see you next time.