>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> While never really meant to be a consumer tech event, the rapid ascendancy of smartphones sucked much of the air out of Mobile World Congress over the years, now MWC. And while the device manufacturers continue to have a major presence at the show, the maturity of intelligent devices, longer life cycles, and the disaggregation of the network stack, have put enterprise technologies front and center in the telco business. Semiconductor manufacturers, network equipment players, infrastructure companies, cloud vendors, software providers, and a spate of startups are eyeing the trillion dollar plus communications industry as one of the next big things to watch this decade. Hello, and welcome to this week's Wikibon CUBE Insights, powered by ETR. In this Breaking Analysis, we bring you part two of our ongoing coverage of MWC '23, with some new data on enterprise players specifically in large telco environments, a brief glimpse at some of the pre-announcement news and corresponding themes ahead of MWC, and some of the key announcement areas we'll be watching at the show on theCUBE. Now, last week we shared some ETR data that showed how traditional enterprise tech players were performing, specifically within the telecoms vertical. Here's a new look at that data from ETR, which isolates the same companies, but cuts the data for what ETR calls large telco. The N in this cut is 196, down from 288 last week when we included all company sizes in the dataset. Now remember the two dimensions here, on the y-axis is net score, or spending momentum, and on the x-axis is pervasiveness in the data set. The table insert in the upper left informs how the dots and companies are plotted, and that red dotted line, the horizontal line at 40%, that indicates a highly elevated net score. Now while the data are not dramatically different in terms of relative positioning, there are a couple of changes at the margin. So just going down the list and focusing on net score. Azure is comparable, but slightly lower in this sector in the large telco than it was overall. Google Cloud comes in at number two, and basically swapped places with AWS, which drops slightly in the large telco relative to overall telco. Snowflake is also slightly down by one percentage point, but maintains its position. Remember Snowflake, overall, its net score is much, much higher when measuring across all verticals. Snowflake comes down in telco, and relative to overall, a little bit down in large telco, but it's making some moves to attack this market that we'll talk about in a moment. Next are Red Hat OpenStack and Databricks. About the same in large tech telco as they were an overall telco. Then there's Dell next that has a big presence at MWC and is getting serious about driving 16G adoption, and new servers, and edge servers, and other partnerships. Cisco and Red Hat OpenShift basically swapped spots when moving from all telco to large telco, as Cisco drops and Red Hat bumps up a bit. And VMware dropped about four percentage points in large telco. Accenture moved up dramatically, about nine percentage points in big telco, large telco relative to all telco. HPE dropped a couple of percentage points. Oracle stayed about the same. And IBM surprisingly dropped by about five points. So look, I understand not a ton of change in terms of spending momentum in the large sector versus telco overall, but some deltas. The bottom line for enterprise players is one, they're just getting started in this new disruption journey that they're on as the stack disaggregates. Two, all these players have experience in delivering horizontal solutions, but now working with partners and identifying big problems to be solved, and three, many of these companies are generally not the fastest moving firms relative to smaller disruptive disruptors. Now, cloud has been an exception in fairness. But the good news for the legacy infrastructure and IT companies is that the telco transformation and the 5G buildout is going to take years. So it's moving at a pace that is very favorable to many of these companies. Okay, so looking at just some of the pre-announcement highlights that have hit the wire this week, I want to give you a glimpse of the diversity of innovation that is occurring in the telecommunication space. You got semiconductor manufacturers, device makers, network equipment players, carriers, cloud vendors, enterprise tech companies, software companies, startups. Now we've included, you'll see in this list, we've included OpeRAN, that logo, because there's so much buzz around the topic and we're going to come back to that. But suffice it to say, there's no way we can cover all the announcements from the 2000 plus exhibitors at the show. So we're going to cherry pick here and make a few call outs. Hewlett Packard Enterprise announced an acquisition of an Italian private cellular network company called AthoNet. Zeus Kerravala wrote about it on SiliconANGLE if you want more details. Now interestingly, HPE has a partnership with Solana, which also does private 5G. But according to Zeus, Solona is more of an out-of-the-box solution, whereas AthoNet is designed for the core and requires more integration. And as you'll see in a moment, there's going to be a lot of talk at the show about private network. There's going to be a lot of news there from other competitors, and we're going to be watching that closely. And while many are concerned about the P5G, private 5G, encroaching on wifi, Kerravala doesn't see it that way. Rather, he feels that these private networks are really designed for more industrial, and you know mission critical environments, like factories, and warehouses that are run by robots, et cetera. 'Cause these can justify the increased expense of private networks. Whereas wifi remains a very low cost and flexible option for, you know, whatever offices and homes. Now, over to Dell. Dell announced its intent to go hard after opening up the telco network with the announcement that in the second half of this year it's going to begin shipping its infrastructure blocks for Red Hat. Remember it's like kind of the converged infrastructure for telco with a more open ecosystem and sort of more flexible, you know, more mature engineered system. Dell has also announced a range of PowerEdge servers for a variety of use cases. A big wide line bringing forth its 16G portfolio and aiming squarely at the telco space. Dell also announced, here we go, a private wireless offering with airspan, and Expedo, and a solution with AthoNet, the company HPE announced it was purchasing. So I guess Dell and HPE are now partnering up in the private wireless space, and yes, hell is freezing over folks. We'll see where that relationship goes in the mid- to long-term. Dell also announced new lab and certification capabilities, which we said last week was going to be critical for the further adoption of open ecosystem technology. So props to Dell for, you know, putting real emphasis and investment in that. AWS also made a number of announcements in this space including private wireless solutions and associated managed services. AWS named Deutsche Telekom, Orange, T-Mobile, Telefonica, and some others as partners. And AWS announced the stepped up partnership, specifically with T-Mobile, to bring AWS services to T-Mobile's network portfolio. Snowflake, back to Snowflake, announced its telecom data cloud. Remember we showed the data earlier, it's Snowflake not as strong in the telco sector, but they're continuing to move toward this go-to market alignment within key industries, realigning their go-to market by vertical. It also announced that AT&T, and a number of other partners, are collaborating to break down data silos specifically in telco. Look, essentially, this is Snowflake taking its core value prop to the telco vertical and forming key partnerships that resonate in the space. So think simplification, breaking down silos, data sharing, eventually data monetization. Samsung previewed its future capability to allow smartphones to access satellite services, something Apple has previously done. AMD, Intel, Marvell, Qualcomm, are all in the act, all the semiconductor players. Qualcomm for example, announced along with Telefonica, and Erickson, a 5G millimeter network that will be showcased in Spain at the event this coming week using Qualcomm Snapdragon chipset platform, based on none other than Arm technology. Of course, Arm we said is going to dominate the edge, and is is clearly doing so. It's got the volume advantage over, you know, traditional Intel, you know, X86 architectures. And it's no surprise that Microsoft is touting its open AI relationship. You're going to hear a lot of AI talk at this conference as is AI is now, you know, is the now topic. All right, we could go on and on and on. There's just so much going on at Mobile World Congress or MWC, that we just wanted to give you a glimpse of some of the highlights that we've been watching. Which brings us to the key topics and issues that we'll be exploring at MWC next week. We touched on some of this last week. A big topic of conversation will of course be, you know, 5G. Is it ever going to become real? Is it, is anybody ever going to make money at 5G? There's so much excitement around and anticipation around 5G. It has not lived up to the hype, but that's because the rollout, as we've previous reported, is going to take years. And part of that rollout is going to rely on the disaggregation of the hardened telco stack, as we reported last week and in previous Breaking Analysis episodes. OpenRAN is a big component of that evolution. You know, as our RAN intelligent controllers, RICs, which essentially the brain of OpenRAN, if you will. Now as we build out 5G networks at massive scale and accommodate unprecedented volumes of data and apply compute-hungry AI to all this data, the issue of energy efficiency is going to be front and center. It has to be. Not only is it a, you know, hot political issue, the reality is that improving power efficiency is compulsory or the whole vision of telco's future is going to come crashing down. So chip manufacturers, equipment makers, cloud providers, everybody is going to be doubling down and clicking on this topic. Let's talk about AI. AI as we said, it is the hot topic right now, but it is happening not only in consumer, with things like ChatGPT. And think about the theme of this Breaking Analysis in the enterprise, AI in the enterprise cannot be ChatGPT. It cannot be error prone the way ChatGPT is. It has to be clean, reliable, governed, accurate. It's got to be ethical. It's got to be trusted. Okay, we're going to have Zeus Kerravala on the show next week and definitely want to get his take on private networks and how they're going to impact wifi. You know, will private networks cannibalize wifi? If not, why not? He wrote about this again on SiliconANGLE if you want more details, and we're going to unpack that on theCUBE this week. And finally, as always we'll be following the data flows to understand where and how telcos, cloud players, startups, software companies, disruptors, legacy companies, end customers, how are they going to make money from new data opportunities? 'Cause we often say in theCUBE, don't ever bet against data. All right, that's a wrap for today. Remember theCUBE is going to be on location at MWC 2023 next week. We got a great set. We're in the walkway in between halls four and five, right in Congress Square, stand CS-60. Look for us, we got a full schedule. If you got a great story or you have news, stop by. We're going to try to get you on the program. I'll be there with Lisa Martin, co-hosting, David Nicholson as well, and the entire CUBE crew, so don't forget to come by and see us. I want to thank Alex Myerson, who's on production and manages the podcast, and Ken Schiffman, as well, in our Boston studio. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor-in-chief over at SiliconANGLE.com. He does some great editing. Thank you. All right, remember all these episodes they are available as podcasts wherever you listen. All you got to do is search Breaking Analysis podcasts. I publish each week on Wikibon.com and SiliconANGLE.com. All the video content is available on demand at theCUBE.net, or you can email me directly if you want to get in touch David.Vellante@SiliconANGLE.com or DM me @DVellante, or comment on our LinkedIn posts. And please do check out ETR.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching. We'll see you next week at Mobile World Congress '23, MWC '23, or next time on Breaking Analysis. (bright music)

(upbeat music) >> Hello, everyone, welcome to theCUBE. I'm John Furrier, the host of theCUBE in Palo Alto, California. Also it's SiliconANGLE News. Got two great guests here to talk about AI, the impact of the future of the internet, the applications, the people. Amr Awadallah, the founder and CEO, Ed Alban is the CEO of Vectara, a new startup that emerged out of the original Cloudera, I would say, 'cause Amr's known, famous for the Cloudera founding, which was really the beginning of the big data movement. And now as AI goes mainstream, there's so much to talk about, so much to go on. And plus the new company is one of the, now what I call the wave, this next big wave, I call it the fifth wave in the industry. You know, you had PCs, you had the internet, you had mobile. This generative AI thing is real. And you're starting to see startups come out in droves. Amr obviously was founder of Cloudera, Big Data, and now Vectara. And Ed Albanese, you guys have a new company. Welcome to the show. >> Thank you. It's great to be here. >> So great to see you. Now the story is theCUBE started in the Cloudera office. Thanks to you, and your friendly entrepreneurship views that you have. We got to know each other over the years. But Cloudera had Hadoop, which was the beginning of what I call the big data wave, which then became what we now call data lakes, data oceans, and data infrastructure that's developed from that. It's almost interesting to look back 12 plus years, and see that what AI is doing now, right now, is opening up the eyes to the mainstream, and the application's almost mind blowing. You know, Sati Natel called it the Mosaic Moment, didn't say Netscape, he built Netscape (laughing) but called it the Mosaic Moment. You're seeing companies in startups, kind of the alpha geeks running here, because this is the new frontier, and there's real meat on the bone, in terms of like things to do. Why? Why is this happening now? What's is the confluence of the forces happening, that are making this happen? >> Yeah, I mean if you go back to the Cloudera days, with big data, and so on, that was more about data processing. Like how can we process data, so we can extract numbers from it, and do reporting, and maybe take some actions, like this is a fraud transaction, or this is not. And in the meanwhile, many of the researchers working in the neural network, and deep neural network space, were trying to focus on data understanding, like how can I understand the data, and learn from it, so I can take actual actions, based on the data directly, just like a human does. And we were only good at doing that at the level of somebody who was five years old, or seven years old, all the way until about 2013. And starting in 2013, which is only 10 years ago, a number of key innovations started taking place, and each one added on. It was no major innovation that just took place. It was a couple of really incremental ones, but they added on top of each other, in a very exponentially additive way, that led to, by the end of 2019, we now have models, deep neural network models, that can read and understand human text just like we do. Right? And they can reason about it, and argue with you, and explain it to you. And I think that's what is unlocking this whole new wave of innovation that we're seeing right now. So data understanding would be the essence of it. >> So it's not a Big Bang kind of theory, it's been evolving over time, and I think that the tipping point has been the advancements and other things. I mean look at cloud computing, and look how fast it just crept up on AWS. I mean AWS you back three, five years ago, I was talking to Swami yesterday, and their big news about AI, expanding the Hugging Face's relationship with AWS. And just three, five years ago, there wasn't a model training models out there. But as compute comes out, and you got more horsepower,, these large language models, these foundational models, they're flexible, they're not monolithic silos, they're interacting. There's a whole new, almost fusion of data happening. Do you see that? I mean is that part of this? >> Of course, of course. I mean this wave is building on all the previous waves. We wouldn't be at this point if we did not have hardware that can scale, in a very efficient way. We wouldn't be at this point, if we don't have data that we're collecting about everything we do, that we're able to process in this way. So this, this movement, this motion, this phase we're in, absolutely builds on the shoulders of all the previous phases. For some of the observers from the outside, when they see chatGPT for the first time, for them was like, "Oh my god, this just happened overnight." Like it didn't happen overnight. (laughing) GPT itself, like GPT3, which is what chatGPT is based on, was released a year ahead of chatGPT, and many of us were seeing the power it can provide, and what it can do. I don't know if Ed agrees with that. >> Yeah, Ed? >> I do. Although I would acknowledge that the possibilities now, because of what we've hit from a maturity standpoint, have just opened up in an incredible way, that just wasn't tenable even three years ago. And that's what makes it, it's true that it developed incrementally, in the same way that, you know, the possibilities of a mobile handheld device, you know, in 2006 were there, but when the iPhone came out, the possibilities just exploded. And that's the moment we're in. >> Well, I've had many conversations over the past couple months around this area with chatGPT. John Markoff told me the other day, that he calls it, "The five dollar toy," because it's not that big of a deal, in context to what AI's doing behind the scenes, and all the work that's done on ethics, that's happened over the years, but it has woken up the mainstream, so everyone immediately jumps to ethics. "Does it work? "It's not factual," And everyone who's inside the industry is like, "This is amazing." 'Cause you have two schools of thought there. One's like, people that think this is now the beginning of next gen, this is now we're here, this ain't your grandfather's chatbot, okay?" With NLP, it's got reasoning, it's got other things. >> I'm in that camp for sure. >> Yeah. Well I mean, everyone who knows what's going on is in that camp. And as the naysayers start to get through this, and they go, "Wow, it's not just plagiarizing homework, "it's helping me be better. "Like it could rewrite my memo, "bring the lead to the top." It's so the format of the user interface is interesting, but it's still a data-driven app. >> Absolutely. >> So where does it go from here? 'Cause I'm not even calling this the first ending. This is like pregame, in my opinion. What do you guys see this going, in terms of scratching the surface to what happens next? >> I mean, I'll start with, I just don't see how an application is going to look the same in the next three years. Who's going to want to input data manually, in a form field? Who is going to want, or expect, to have to put in some text in a search box, and then read through 15 different possibilities, and try to figure out which one of them actually most closely resembles the question they asked? You know, I don't see that happening. Who's going to start with an absolute blank sheet of paper, and expect no help? That is not how an application will work in the next three years, and it's going to fundamentally change how people interact and spend time with opening any element on their mobile phone, or on their computer, to get something done. >> Yes. I agree with that. Like every single application, over the next five years, will be rewritten, to fit within this model. So imagine an HR application, I don't want to name companies, but imagine an HR application, and you go into application and you clicking on buttons, because you want to take two weeks of vacation, and menus, and clicking here and there, reasons and managers, versus just telling the system, "I'm taking two weeks of vacation, going to Las Vegas," book it, done. >> Yeah. >> And the system just does it for you. If you weren't completing in your input, in your description, for what you want, then the system asks you back, "Did you mean this? "Did you mean that? "Were you trying to also do this as well?" >> Yeah. >> "What was the reason?" And that will fit it for you, and just do it for you. So I think the user interface that we have with apps, is going to change to be very similar to the user interface that we have with each other. And that's why all these apps will need to evolve. >> I know we don't have a lot of time, 'cause you guys are very busy, but I want to definitely have multiple segments with you guys, on this topic, because there's so much to talk about. There's a lot of parallels going on here. I was talking again with Swami who runs all the AI database at AWS, and I asked him, I go, "This feels a lot like the original AWS. "You don't have to provision a data center." A lot of this heavy lifting on the back end, is these large language models, with these foundational models. So the bottleneck in the past, was the energy, and cost to actually do it. Now you're seeing it being stood up faster. So there's definitely going to be a tsunami of apps. I would see that clearly. What is it? We don't know yet. But also people who are going to leverage the fact that I can get started building value. So I see a startup boom coming, and I see an application tsunami of refactoring things. >> Yes. >> So the replatforming is already kind of happening. >> Yes, >> OpenAI, chatGPT, whatever. So that's going to be a developer environment. I mean if Amazon turns this into an API, or a Microsoft, what you guys are doing. >> We're turning it into API as well. That's part of what we're doing as well, yes. >> This is why this is exciting. Amr, you've lived the big data dream, and and we used to talk, if you didn't have a big data problem, if you weren't full of data, you weren't really getting it. Now people have all the data, and they got to stand this up. >> Yeah. >> So the analogy is again, the mobile, I like the mobile movement, and using mobile as an analogy, most companies were not building for a mobile environment, right? They were just building for the web, and legacy way of doing apps. And as soon as the user expectations shifted, that my expectation now, I need to be able to do my job on this small screen, on the mobile device with a touchscreen. Everybody had to invest in re-architecting, and re-implementing every single app, to fit within that model, and that model of interaction. And we are seeing the exact same thing happen now. And one of the core things we're focused on at Vectara, is how to simplify that for organizations, because a lot of them are overwhelmed by large language models, and ML. >> They don't have the staff. >> Yeah, yeah, yeah. They're understaffed, they don't have the skills. >> But they got developers, they've got DevOps, right? >> Yes. >> So they have the DevSecOps going on. >> Exactly, yes. >> So our goal is to simplify it enough for them that they can start leveraging this technology effectively, within their applications. >> Ed, you're the COO of the company, obviously a startup. You guys are growing. You got great backup, and good team. You've also done a lot of business development, and technical business development in this area. If you look at the landscape right now, and I agree the apps are coming, every company I talk to, that has that jet chatGPT of, you know, epiphany, "Oh my God, look how cool this is. "Like magic." Like okay, it's code, settle down. >> Mm hmm. >> But everyone I talk to is using it in a very horizontal way. I talk to a very senior person, very tech alpha geek, very senior person in the industry, technically. they're using it for log data, they're using it for configuration of routers. And in other areas, they're using it for, every vertical has a use case. So this is horizontally scalable from a use case standpoint. When you hear horizontally scalable, first thing I chose in my mind is cloud, right? >> Mm hmm. >> So cloud, and scalability that way. And the data is very specialized. So now you have this vertical specialization, horizontally scalable, everyone will be refactoring. What do you see, and what are you seeing from customers, that you talk to, and prospects? >> Yeah, I mean put yourself in the shoes of an application developer, who is actually trying to make their application a bit more like magic. And to have that soon-to-be, honestly, expected experience. They've got to think about things like performance, and how efficiently that they can actually execute a query, or a question. They've got to think about cost. Generative isn't cheap, like the inference of it. And so you've got to be thoughtful about how and when you take advantage of it, you can't use it as a, you know, everything looks like a nail, and I've got a hammer, and I'm going to hit everything with it, because that will be wasteful. Developers also need to think about how they're going to take advantage of, but not lose their own data. So there has to be some controls around what they feed into the large language model, if anything. Like, should they fine tune a large language model with their own data? Can they keep it logically separated, but still take advantage of the powers of a large language model? And they've also got to take advantage, and be aware of the fact that when data is generated, that it is a different class of data. It might not fully be their own. >> Yeah. >> And it may not even be fully verified. And so when the logical cycle starts, of someone making a request, the relationship between that request, and the output, those things have to be stored safely, logically, and identified as such. >> Yeah. >> And taken advantage of in an ongoing fashion. So these are mega problems, each one of them independently, that, you know, you can think of it as middleware companies need to take advantage of, and think about, to help the next wave of application development be logical, sensible, and effective. It's not just calling some raw API on the cloud, like openAI, and then just, you know, you get your answer and you're done, because that is a very brute force approach. >> Well also I will point, first of all, I agree with your statement about the apps experience, that's going to be expected, form filling. Great point. The interesting about chatGPT. >> Sorry, it's not just form filling, it's any action you would like to take. >> Yeah. >> Instead of clicking, and dragging, and dropping, and doing it on a menu, or on a touch screen, you just say it, and it's and it happens perfectly. >> Yeah. It's a different interface. And that's why I love that UIUX experiences, that's the people falling out of their chair moment with chatGPT, right? But a lot of the things with chatGPT, if you feed it right, it works great. If you feed it wrong and it goes off the rails, it goes off the rails big. >> Yes, yes. >> So the the Bing catastrophes. >> Yeah. >> And that's an example of garbage in, garbage out, classic old school kind of comp-side phrase that we all use. >> Yep. >> Yes. >> This is about data in injection, right? It reminds me the old SQL days, if you had to, if you can sling some SQL, you were a magician, you know, to get the right answer, it's pretty much there. So you got to feed the AI. >> You do, Some people call this, the early word to describe this as prompt engineering. You know, old school, you know, search, or, you know, engagement with data would be, I'm going to, I have a question or I have a query. New school is, I have, I have to issue it a prompt, because I'm trying to get, you know, an action or a reaction, from the system. And the active engineering, there are a lot of different ways you could do it, all the way from, you know, raw, just I'm going to send you whatever I'm thinking. >> Yeah. >> And you get the unintended outcomes, to more constrained, where I'm going to just use my own data, and I'm going to constrain the initial inputs, the data I already know that's first party, and I trust, to, you know, hyper constrain, where the application is actually, it's looking for certain elements to respond to. >> It's interesting Amr, this is why I love this, because one we are in the media, we're recording this video now, we'll stream it. But we got all your linguistics, we're talking. >> Yes. >> This is data. >> Yep. >> So the data quality becomes now the new intellectual property, because, if you have that prompt source data, it makes data or content, in our case, the original content, intellectual property. >> Absolutely. >> Because that's the value. And that's where you see chatGPT fall down, is because they're trying to scroll the web, and people think it's search. It's not necessarily search, it's giving you something that you wanted. It is a lot of that, I remember in Cloudera, you said, "Ask the right questions." Remember that phrase you guys had, that slogan? >> Mm hmm. And that's prompt engineering. So that's exactly, that's the reinvention of "Ask the right question," is prompt engineering is, if you don't give these models the question in the right way, and very few people know how to frame it in the right way with the right context, then you will get garbage out. Right? That is the garbage in, garbage out. But if you specify the question correctly, and you provide with it the metadata that constrain what that question is going to be acted upon or answered upon, then you'll get much better answers. And that's exactly what we solved Vectara. >> Okay. So before we get into the last couple minutes we have left, I want to make sure we get a plug in for the opportunity, and the profile of Vectara, your new company. Can you guys both share with me what you think the current situation is? So for the folks who are now having those moments of, "Ah, AI's bullshit," or, "It's not real, it's a lot of stuff," from, "Oh my god, this is magic," to, "Okay, this is the future." >> Yes. >> What would you say to that person, if you're at a cocktail party, or in the elevator say, "Calm down, this is the first inning." How do you explain the dynamics going on right now, to someone who's either in the industry, but not in the ropes? How would you explain like, what this wave's about? How would you describe it, and how would you prepare them for how to change their life around this? >> Yeah, so I'll go first and then I'll let Ed go. Efficiency, efficiency is the description. So we figured that a way to be a lot more efficient, a way where you can write a lot more emails, create way more content, create way more presentations. Developers can develop 10 times faster than they normally would. And that is very similar to what happened during the Industrial Revolution. I always like to look at examples from the past, to read what will happen now, and what will happen in the future. So during the Industrial Revolution, it was about efficiency with our hands, right? So I had to make a piece of cloth, like this piece of cloth for this shirt I'm wearing. Our ancestors, they had to spend month taking the cotton, making it into threads, taking the threads, making them into pieces of cloth, and then cutting it. And now a machine makes it just like that, right? And the ancestors now turned from the people that do the thing, to manage the machines that do the thing. And I think the same thing is going to happen now, is our efficiency will be multiplied extremely, as human beings, and we'll be able to do a lot more. And many of us will be able to do things they couldn't do before. So another great example I always like to use is the example of Google Maps, and GPS. Very few of us knew how to drive a car from one location to another, and read a map, and get there correctly. But once that efficiency of an AI, by the way, behind these things is very, very complex AI, that figures out how to do that for us. All of us now became amazing navigators that can go from any point to any point. So that's kind of how I look at the future. >> And that's a great real example of impact. Ed, your take on how you would talk to a friend, or colleague, or anyone who asks like, "How do I make sense of the current situation? "Is it real? "What's in it for me, and what do I do?" I mean every company's rethinking their business right now, around this. What would you say to them? >> You know, I usually like to show, rather than describe. And so, you know, the other day I just got access, I've been using an application for a long time, called Notion, and it's super popular. There's like 30 or 40 million users. And the new version of Notion came out, which has AI embedded within it. And it's AI that allows you primarily to create. So if you could break down the world of AI into find and create, for a minute, just kind of logically separate those two things, find is certainly going to be massively impacted in our experiences as consumers on, you know, Google and Bing, and I can't believe I just said the word Bing in the same sentence as Google, but that's what's happening now (all laughing), because it's a good example of change. >> Yes. >> But also inside the business. But on the crate side, you know, Notion is a wiki product, where you try to, you know, note down things that you are thinking about, or you want to share and memorialize. But sometimes you do need help to get it down fast. And just in the first day of using this new product, like my experience has really fundamentally changed. And I think that anybody who would, you know, anybody say for example, that is using an existing app, I would show them, open up the app. Now imagine the possibility of getting a starting point right off the bat, in five seconds of, instead of having to whole cloth draft this thing, imagine getting a starting point then you can modify and edit, or just dispose of and retry again. And that's the potential for me. I can't imagine a scenario where, in a few years from now, I'm going to be satisfied if I don't have a little bit of help, in the same way that I don't manually spell check every email that I send. I automatically spell check it. I love when I'm getting type ahead support inside of Google, or anything. Doesn't mean I always take it, or when texting. >> That's efficiency too. I mean the cloud was about developers getting stuff up quick. >> Exactly. >> All that heavy lifting is there for you, so you don't have to do it. >> Right? >> And you get to the value faster. >> Exactly. I mean, if history taught us one thing, it's, you have to always embrace efficiency, and if you don't fast enough, you will fall behind. Again, looking at the industrial revolution, the companies that embraced the industrial revolution, they became the leaders in the world, and the ones who did not, they all like. >> Well the AI thing that we got to watch out for, is watching how it goes off the rails. If it doesn't have the right prompt engineering, or data architecture, infrastructure. >> Yes. >> It's a big part. So this comes back down to your startup, real quick, I know we got a couple minutes left. Talk about the company, the motivation, and we'll do a deeper dive on on the company. But what's the motivation? What are you targeting for the market, business model? The tech, let's go. >> Actually, I would like Ed to go first. Go ahead. >> Sure, I mean, we're a developer-first, API-first platform. So the product is oriented around allowing developers who may not be superstars, in being able to either leverage, or choose, or select their own large language models for appropriate use cases. But they that want to be able to instantly add the power of large language models into their application set. We started with search, because we think it's going to be one of the first places that people try to take advantage of large language models, to help find information within an application context. And we've built our own large language models, focused on making it very efficient, and elegant, to find information more quickly. So what a developer can do is, within minutes, go up, register for an account, and get access to a set of APIs, that allow them to send data, to be converted into a format that's easy to understand for large language models, vectors. And then secondarily, they can issue queries, ask questions. And they can ask them very, the questions that can be asked, are very natural language questions. So we're talking about long form sentences, you know, drill down types of questions, and they can get answers that either come back in depending upon the form factor of the user interface, in list form, or summarized form, where summarized equals the opportunity to kind of see a condensed, singular answer. >> All right. I have a. >> Oh okay, go ahead, you go. >> I was just going to say, I'm going to be a customer for you, because I want, my dream was to have a hologram of theCUBE host, me and Dave, and have questions be generated in the metaverse. So you know. (all laughing) >> There'll be no longer any guests here. They'll all be talking to you guys. >> Give a couple bullets, I'll spit out 10 good questions. Publish a story. This brings the automation, I'm sorry to interrupt you. >> No, no. No, no, I was just going to follow on on the same. So another way to look at exactly what Ed described is, we want to offer you chatGPT for your own data, right? So imagine taking all of the recordings of all of the interviews you have done, and having all of the content of that being ingested by a system, where you can now have a conversation with your own data and say, "Oh, last time when I met Amr, "which video games did we talk about? "Which movie or book did we use as an analogy "for how we should be embracing data science, "and big data, which is moneyball," I know you use moneyball all the time. And you start having that conversation. So, now the data doesn't become a passive asset that you just have in your organization. No. It's an active participant that's sitting with you, on the table, helping you make decisions. >> One of my favorite things to do with customers, is to go to their site or application, and show them me using it. So for example, one of the customers I talked to was one of the biggest property management companies in the world, that lets people go and rent homes, and houses, and things like that. And you know, I went and I showed them me searching through reviews, looking for information, and trying different words, and trying to find out like, you know, is this place quiet? Is it comfortable? And then I put all the same data into our platform, and I showed them the world of difference you can have when you start asking that question wholeheartedly, and getting real information that doesn't have anything to do with the words you asked, but is really focused on the meaning. You know, when I asked like, "Is it quiet?" You know, answers would come back like, "The wind whispered through the trees peacefully," and you know, it's like nothing to do with quiet in the literal word sense, but in the meaning sense, everything to do with it. And that that was magical even for them, to see that. >> Well you guys are the front end of this big wave. Congratulations on the startup, Amr. I know you guys got great pedigree in big data, and you've got a great team, and congratulations. Vectara is the name of the company, check 'em out. Again, the startup boom is coming. This will be one of the major waves, generative AI is here. I think we'll look back, and it will be pointed out as a major inflection point in the industry. >> Absolutely. >> There's not a lot of hype behind that. People are are seeing it, experts are. So it's going to be fun, thanks for watching. >> Thanks John. (soft music)

from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante you know we've often said that the next 10 years in cloud computing won't be like the last ten cloud has firmly planted its footprint on the other side of the chasm with the momentum of the entire multi-trillion dollar tech business behind it both sellers and buyers are leaning in by adopting cloud technologies and many are building their own value layers on top of cloud in the coming years we expect innovation will continue to coalesce around the three big u.s clouds plus alibaba in apac with the ecosystem building value on top of the hardware saw tooling provided by the hyperscalers now importantly we don't see this as a race to the bottom rather our expectation is that the large public cloud players will continue to take cost out of their platforms through innovation automation and integration while other cloud providers and the ecosystem including traditional companies that buy it mine opportunities in their respective markets as matt baker of dell is fond of saying this is not a zero sum game welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll update you on our latest projections in the cloud market we'll share some new etr survey data with some surprising nuggets and drill into this the important cloud database landscape first we want to take a look at what people are talking about in cloud and what's been in the recent news with the exception of alibaba all the large cloud players have reported earnings google continues to focus on growth at the expense of its profitability google reported that it's cloud business which includes applications like google workspace grew 45 percent to five and a half billion dollars but it had an operating loss of 890 billion now since thomas curion joined google to run its cloud business google has increased head count in its cloud business from 25 000 25 000 people now it's up to 40 000 in an effort to catch up to the two leaders but playing catch up is expensive now to put this into perspective let's go back to aws's revenue in q1 2018 when the company did 5.4 billion so almost exactly the same size as google's current total cloud business and aws is growing faster at the time at 49 don't forget google includes in its cloud numbers a big chunk of high margin software aws at the time had an operating profit of 1.4 billion that quarter around 26 of its revenues so it was a highly profitable business about as profitable as cisco's overall business which again is a great business this is what happens when you're number three and didn't get your head out of your ads fast enough now in fairness google still gets high marks on the quality of its technology according to corey quinn of the duck bill group amazon and google cloud are what he called neck and neck with regard to reliability with microsoft azure trailing because of significant disruptions in the past these comments were made last week in a bloomberg article despite some recent high-profile outages on aws not surprisingly a microsoft spokesperson said that the company's cloud offers industry-leading reliability and that gives customers payment credits after some outages thank you turning to microsoft and cloud news microsoft's overall cloud business surpassed 22 billion in the december quarter up 32 percent year on year like google microsoft includes application software and sas offerings in its cloud numbers and gives little nuggets of guidance on its azure infrastructure as a service business by the way we estimate that azure comprises about 45 percent of microsoft's overall cloud business which we think hit a 40 billion run rate last quarter microsoft guided in its earning call that recent declines in the azure growth rates will reverse in q1 and that implies sequential growth for azure and finally it was announced that the ftc not the doj will review microsoft's announced 75 billion acquisition of activision blizzard it appears ftc chair lena khan wants to take this one on herself she of course has been very outspoken about the power of big tech companies and in recent a recent cnbc interview suggested that the u.s government's actions were a meaningful contributor back then to curbing microsoft's power in the 90s i personally found that dubious just ask netscape wordperfect novell lotus and spc the maker of harvard presentation graphics how effective the government was in curbing microsoft power generally my take is that the u s government has had a dismal record regulating tech companies most notably ibm and microsoft and it was market forces company hubris complacency and self-inflicted wounds not government intervention these were far more effective than the government now of course if companies are breaking the law they should be punished but the u.s government hasn't been very productive in its actions and the unintended consequences of regulation could be detrimental to the u.s competitiveness in the race with china but i digress lastly in the news amazon announced earnings thursday and the company's value increased by 191 billion dollars on friday that's a record valuation gain for u.s stocks aws amazon's profit engine grew 40 percent year on year for the quarter it closed the year at 62 billion dollars in revenue and at a 71 billion dollar revenue run rate aws is now larger than ibm which without kindrel is at a 67 billion dollar run rate just for context ibm's revenue in 2011 was 107 billion dollars now there's a conversation going on in the media and social that in order to continue this growth and compete with microsoft that aws has to get into the sas business and offer applications we don't think that's the right strategy for amp from for amazon in the near future rather we see them enabling developers to compete in that business finally amazon disclosed that 48 of its top 50 customers are using graviton 2 instances why is this important because aws is well ahead of the competition in custom silicon chips is and is on a price performance curve that is far better than alternatives especially those based on x86 this is one of the reasons why we think this business is not a race to the bottom aws is being followed by google microsoft and alibaba in terms of developing custom silicon and will continue to drive down their internal cost structures and deliver price performance equal to or better than the historical moore's law curves so that's the recent news for the big u.s cloud providers let's now take a look at how the year ended for the big four hyperscalers and look ahead to next year here's a table we've shown this view before it shows the revenue estimates for worldwide is and paths generated by aws microsoft alibaba and google now remember amazon and alibaba they share clean eye ass figures whereas microsoft and alphabet only give us these nuggets that we have to interpret and we correlate those tidbits with other data that we gather we're one of the few outlets that actually attempts to make these apples to apples comparisons there's a company called synergy research there's another firm that does this but i really can't map to their numbers their gcp figures look far too high and azure appears somewhat overestimated and they do include other stuff like hosted private cloud services but it's another data point that you can use okay back to the table we've slightly adjusted our gcp figures down based on interpreting some of alphabet's statements and other survey data only alibaba has yet to announce earnings so we'll stick to a 2021 market size of about 120 billion dollars that's a 41 growth rate relative to 2020 and we expect that figure to increase by 38 percent to 166 billion in 2022 now we'll discuss this a bit later but these four companies have created an opportunity for the ecosystem to build what we're calling super clouds on top of this infrastructure and we're seeing it happen it was increasingly obvious at aws re invent last year and we feel it will pick up momentum in the coming months and years a little bit more on that later now here's a graphical view of the quarterly revenue shares for these four companies notice that aws has reversed its share erosion and is trending up slightly aws has accelerated its growth rate four quarters in a row now it accounted for 52 percent of the big four hyperscaler revenue last year and that figure was nearly 54 in the fourth quarter azure finished the year with 32 percent of the hyper scale revenue in 2021 which dropped to 30 percent in q4 and you can see gcp and alibaba they're neck and neck fighting for the bronze medal by the way in our recent 2022 predictions post we said google cloud platform would surpass alibaba this year but given the recent trimming of our numbers google's got some work to do for that prediction to be correct okay just to put a bow on the wikibon market data let's look at the quarterly growth rates and you'll see the compression trends there this data tracks quarterly revenue growth rates back to 20 q1 2019 and you can see the steady downward trajectory and the reversal that aws experienced in q1 of last year now remember microsoft guided for sequential growth and azure so that orange line should trend back up and given gcp's much smaller and big go to market investments that we talked about we'd like to see an acceleration there as well the thing about aws is just remarkable that it's able to accelerate growth at a 71 billion run rate business and alibaba you know is a bit more opaque and likely still reeling from the crackdown of the chinese government we're admittedly not as close to the china market but we'll continue to watch from afar as that steep decline in growth rate is somewhat of a concern okay let's get into the survey data from etr and to do so we're going to take some time series views on some of the select cloud platforms that are showing spending momentum in the etr data set you know etr uses a metric we talked about this a lot called net score to measure that spending velocity of products and services netscore basically asks customers are you spending more less or the same on a platform and a vendor and then it subtracts the lesses from the moors and that yields a net score this chart shows net score for five cloud platforms going back to january 2020. note in the table that the table we've inserted inside that chart shows the net score and shared n the latter metric indicates the number of mentions in the data set and all the platforms we've listed here show strong presence in the survey that red dotted line at 40 percent that indicates spending is at an elevated level and you can see azure and aws and vmware cloud on aws as well as gcp are all nicely elevated and bounding off their october figures indicating continued cloud momentum overall but the big surprise in these figures is the steady climb and the steep bounce up from oracle which came in just under the 40 mark now one quarter is not necessarily a trend but going back to january 2020 the oracle peaks keep getting higher and higher so we definitely want to keep watching this now here's a look at some of the other cloud platforms in the etr survey the chart here shows the same time series and we've now brought in some of the big hybrid players notably vmware cloud which is vcf and other on-prem solutions red hat openstack which as we've reported in the past is still popular in telcos who want to build their own cloud we're also starting to see hpe with green lake and dell with apex show up more and ibm which years ago acquired soft layer which was really essentially a bare metal hosting company and over the years ibm cobbled together its own public cloud ibm is now racing after hybrid cloud using red hat openshift as the linchpin to that strategy now what this data tells us first of all these platforms they don't have the same presence in the data set as do the previous players vmware is the one possible exception but other than vmware these players don't have the spending velocity shown in the previous chart and most are below the red line hpe and dell are interesting and notable in that they're transitioning their early private cloud businesses to dell gr sorry hpe green lake and dell apex respectively and finally after years of kind of staring at their respective navels in in cloud and milking their legacy on-prem models they're finally building out cloud-like infrastructure for their customers they're leaning into cloud and marketing it in a more sensible and attractive fashion for customers so we would expect these figures are going to bounce around for a little while for those two as they settle into a groove and we'll watch that closely now ibm is in the process of a complete do-over arvin krishna inherited three generations of leadership with a professional services mindset now in the post gerschner gerstner era both sam palmisano and ginny rometty held on far too long to ibm's service heritage and protected the past from the future they missed the cloud opportunity and they forced the acquisition of red hat to position the company for the hybrid cloud remedy tried to shrink to grow but never got there krishna is moving faster and with the kindred spin is promising mid-single-digit growth which would be a welcome change ibm is a lot of work to do and we would expect its net score figures as well to bounce around as customers transition to the future all right let's take a look at all these different players in context these are all the clouds that we just talked about in a two-dimensional view the vertical axis is net score or spending momentum and the horizontal axis is market share or presence or pervasiveness in the data set a couple of call-outs that we'd like to make here first the data confirms what we've been saying what everybody's been saying aws and microsoft stand alone with a huge presence many tens of billions of dollars in revenue yet they are both well above the 40 line and show spending momentum and they're well ahead of gcp on both dimensions second vmware while much smaller is showing legitimate momentum which correlates to its public statements alibaba the alibaba in this survey really doesn't have enough sample to make hardcore conclusions um you can see hpe and dell and ibm you know similarly they got a little bit more presence in the data set but they clearly have some work to do what you're seeing there is their transitioning their legacy install bases oracle's the big surprise look what oracle was in the january survey and how they've shot up recently now we'll see if this this holds up let's posit some possibilities as to why it really starts with the fact that oracle is the king of mission critical apps now if you haven't seen video on twitter you have to check it out it's it's hilarious we're not going to run the video here but the link will be in our post but i'll give you the short version some really creative person they overlaid a data migration narrative on top of this one tooth guy who speaks in spanish gibberish but the setup is he's a pm he's a he's a a project manager at a bank and aws came into the bank this of course all hypothetical and said we can move all your apps to the cloud in 12 months and the guy says but wait we're running mission critical apps on exadata and aws says there's nothing special about exadata and he starts howling and slapping his knee and laughing and giggling and talking about the 23 year old senior engineer who says we're going to do this with microservices and he could tell he was he was 23 because he was wearing expensive sneakers and what a nightmare they encountered migrating their environment very very very funny video and anyone who's ever gone through a major migration of mission critical systems this is gonna hit home it's funny not funny the point is it's really painful to move off of oracle and oracle for all its haters and its faults is really the best environment for mission critical systems and customers know it so what's happening is oracle's building out the best cloud for oracle database and it has a lot of really profitable customers running on-prem that the company is migrating to oracle cloud infrastructure oci it's a safer bet than ripping it and putting it into somebody else's cloud that doesn't have all the specialized hardware and oracle knowledge because you can get the same integrated exadata hardware and software to run your database in the oracle cloud it's frankly an easier and much more logical migration path for a lot of customers and that's possibly what's happening here not to mention oracle jacks up the license price nearly doubles the license price if you run on other clouds so not only is oracle investing to optimize its cloud infrastructure it spends money on r d we've always talked about that really focused on mission critical applications but it's making it more cost effective by penalizing customers that run oracle elsewhere so this possibly explains why when the gartner magic quadrant for cloud databases comes out it's got oracle so well positioned you can see it there for yourself oracle's position is right there with aws and microsoft and ahead of google on the right-hand side is gartner's critical capabilities ratings for dbms and oracle leads in virtually all of the categories gartner track this is for operational dvms so it's kind of a narrow view it's like the red stack sweet spot now this graph it shows traditional transactions but gartner has oracle ahead of all vendors in stream processing operational intelligence real-time augmented transactions now you know gartner they're like old name framers and i say that lovingly so maybe they're a bit biased and they might be missing some of the emerging opportunities that for example like snowflake is pioneering but it's hard to deny that oracle for its business is making the right moves in cloud by optimizing for the red stack there's little question in our view when it comes to mission critical we think gartner's analysis is correct however there's this other really exciting landscape emerging in cloud data and we don't want it to be a blind spot snowflake calls it the data cloud jamactagani calls it data mesh others are using the term data fabric databricks calls it data lake house so so does oracle by the way and look the terminology is going to evolve and most of the action action that's happening is in the cloud quite frankly and this chart shows a select group of database and data warehouse companies and we've filtered the data for aws azure and gcp customers accounts so how are these accounts or companies that were showing how these vendors were showing doing in aws azure and gcp accounts and to make the cut you had to have a minimum of 50 mentions in the etr survey so unfortunately data bricks didn't make it just not enough presence in the data set quite quite yet but just to give you a sense snowflake is represented in this cut with 131 accounts aws 240 google 108 microsoft 407 huge [ __ ] 117 cloudera 52 just made the cut ibm 92 and oracle 208. again these are shared accounts filtered by customers running aws azure or gcp the chart shows a net score lime green is new ads forest green is spending more gray is flat spending the pink is spending less and the bright red is defection again you subtract the red from the green and you get net score and you can see that snowflake as we reported last week is tops in the data set with a net score in the 80s and virtually no red and even by the way single digit flat spend aws google and microsoft are all prominent in the data set as is [ __ ] and snowflake as i just mentioned and they're all elevated over the 40 mark cloudera yeah what can we say once they were a high flyer they're really not in the news anymore with anything compelling other than they just you know took the company private so maybe they can re-emerge at some point with a stronger story i hope so because as you can see they actually have some new additions and spending momentum in the green just a lot of customers holding steady and a bit too much red but they're in the positive territory at least with uh plus 17 percent unlike ibm and oracle and this is the flip side of the coin ibm they're knee-deep really chest deep in the middle of a major transformation we've said before arvind krishna's strategy and vision is at least achievable prune the portfolio i.e spin out kindrel sell watson health hold serve with the mainframe and deal with those product cycles shift the mix to software and use red hat to win the day in hybrid red hat is working for ibm's growing well into the double digits unfortunately it's not showing up in this chart with little database momentum in aws azure and gcp accounts zero new ads not enough acceleration and spending a big gray middle in nearly a quarter of the base in the red ibm's data and ai business only grew three percent this last quarter and the word database wasn't even mentioned once on ibm's earnings call this has to be a concern as you can see how important database is to aws microsoft google and the momentum it's giving companies like snowflake and [ __ ] and others which brings us to oracle with a net score of minus 12. so how do you square the momentum in oracle cloud spending and the strong ratings and databases from gartner with this picture good question and i would say the following first look at the profile people aren't adding oracle new a large portion of the base 25 is reducing spend by 6 or worse and there's a decent percentage of the base migrating off oracle with a big fat middle that's flat and this accounts for the poor net score overall but what etr doesn't track is how much is being spent rather it's an account based model and oracle is heavily weighted toward big spenders running mission critical applications and databases oracle's non-gaap operating margins are comparable to ibm's gross margins on a percentage basis so a very profitable company with a big license and maintenance in stall basin oracle has focused its r d investments into cloud erp database automation they've got vertical sas and they've got this integrated hardware and software story and this drives differentiation for the company but as you can see in this chart it has a legacy install base that is constantly trying to minimize its license costs okay here's a little bit of different view on the same data we expand the picture with the two dimensions of net score on the y-axis and market share or pervasiveness on the horizontal axis and the table insert is how the data gets plotted y and x respectively not much to add here other than to say the picture continues to look strong for those companies above the 40 line that are focused and their focus and have figured out a clear cloud strategy and aren't necessarily dealing with a big install base the exception of course is is microsoft and the ones below the line definitely have parts of their portfolio which have solid momentum but they're fighting the inertia of a large install base that moves very slowly again microsoft had the advantage of really azure and migrating those customers very quickly okay so let's wrap it up starting with the big three cloud players aws is accelerating and innovating great example is custom silicon with nitro and graviton and other chips that will help the company address concerns related to the race to the bottom it's not a race to zero aws we believe will let its developers go after the sas business and for the most part aws will offer solutions that address large vertical markets think call centers the edge remains a wild card for aws and all the cloud players really aws believes that in the fullness of time all workloads will run in the public cloud now it's hard for us to imagine the tesla autonomous vehicles running in the public cloud but maybe aws will redefine what it means by its cloud microsoft well they're everywhere and they're expanding further now into gaming and the metaverse when he became ceo in 2014 many people said that satya should ditch xbox just as an aside the joke among many oracle employees at the time was that safra katz would buy her kids and her nieces and her nephews and her kids friends everybody xbox game consoles for the holidays because microsoft lost money for everyone that they shipped well nadella has stuck with it and he sees an opportunity to expand through online gaming communities one of his first deals as ceo was minecraft now the acquisition of activision will make microsoft the world's number three gaming company by revenue behind only 10 cent and sony all this will be powered by azure and drive more compute storage ai and tooling now google for its part is battling to stay relevant in the conversation luckily it can afford the massive losses it endures in cloud because the company's advertising business is so profitable don't expect as many have speculated that google is going to bail on cloud that would be a huge mistake as the market is more than large enough for three players which brings us to the rest of the pack cloud ecosystems generally and aws specifically are exploding the idea of super cloud that is a layer of value that spans multiple clouds hides the underlying complexity and brings new value that the cloud players aren't delivering that's starting to bubble to the top and legacy players are staying close to their customers and fighting to keep them spending and it's working dell hpe cisco and smaller predominantly on-plan prem players like pure storage they continue to do pretty well they're just not as sexy as the big cloud players the real interesting activity it's really happening in the ecosystem of companies and firms within industries that are transforming to create their own digital businesses virtually all of them are running a portion of their offerings on the public cloud but often connecting to on-premises workloads and data think goldman sachs making that work and creating a great experience across all environments is a big opportunity and we're seeing it form right before our eyes don't miss it okay that's it for now thanks to my colleague stephanie chan who helped research this week's topics remember these episodes are all available as podcasts wherever you listen just search breaking analysis podcast check out etr's website at etr dot ai and also we publish a full report every week on wikibon.com and siliconangle.com you can get in touch with me email me at david.velante siliconangle.com you can dm me at divalante or comment on my linkedin post this is dave vellante for the cube insights powered by etr have a great week stay safe be well and we'll see you next time [Music] you

(upbeat music) >> Hello, everyone and welcome to this CUBE Conversation. I'm Lisa Martin. I'm excited to be joined by one of our CUBE alumni, John Maddison, the EVP of Products and the Chief Marketing Officer at Fortinet. John, welcome back to the program. Good to see you. >> Hi, Lisa. Good to be here again. >> So we last saw you at the Fortinet Championship back in September, a few months ago, but we've had the opportunity to speak a number of times this year. I've also had the chance to talk with Derek Manky, at FortiGuard Labs. There's been so much going on. Let's kind of break down some of the main challenges that enterprises are facing still. And there's four of them here that you're going to address as we wrap up 2021 head into 2022. And then let's also talk about what Fortinet sees as the solution, the cybersecurity mesh architecture. Let's go ahead and kick off with some of those challenges as we know so much has gone on throughout landscape that work from anywhere is so persistent, but what are some of the main things enterprises are facing still? >> Yeah, there's a lot, it's very dynamic right now. And you know, I've been in cybersecurity almost 20 years now and there's always been these three drivers around the infrastructure changes the threat landscape and regulatory. And I think when you look at the infrastructure changes, this work from anywhere, which is, you know, kind of the hybrid mode where I'm in the office today, it could be hopefully in the future, traveling and home. That's going to be here for some time, it seems. And so, you know, enterprises are now saying, I need a longer term strategy around that. I can't just say flip on the VPN and a bit of endpoint security. So that definitely enterprises are thinking that's going to be here for at least another couple of years. I think they're still running very fast to get the digital infrastructure in place. And so, and you're seeing network security and the application journey continuing and securing all those things. And then there's, you know, there's the threat landscape, which, you know, we've said, I think back at the PGA, we're seeing this huge increase in ransomware. And yes, there's still activity going on and trying to breach data and intellectual property and identity and credit cards. But just about every industry now is seeing attacks and it could be financial, it could be manufacturing, ransomware attacks that's continues. And then I think there's the, there's a couple of other things. There's the supply chain things which are also happening, but we're definitely I was just speaking to a customer a minute ago and they were finding a very hard to find the right skilled professionals around cybersecurity. And it kind of, it's like a hierarchy. I need to find somebody, it's hard to find somebody in IT. It's hard to find somebody in cybersecurity and IT. Is hard to find somebody in IT, cybersecurity and container. And so, you know, the more you go in depth, the harder it becomes and it's not even finding people, just retaining people as well. And so, you know, recently Fortinet committed to training another million. We've already trained to 750,000, but training another million people by 2025 in cybersecurity. >> That's outstanding. We've talked about that skills gap before in a number of conversations about all the work that 40 minutes doing, including with veterans, which is something near and dear to my heart, but the work from anywhere I wanted to talk with you about that because that presents a lot of challenges for organizations. And I was reading some stats that a significant percentage of enterprises expect that this is going to increase in 2022. How can it increase from where it is now? What are some of the things that you're seeing and how can Fortinet help customers address this persistent challenge? >> Yeah, well, I think it's increased or it's just the ratio between home and at work and travel might be changing. And again as I said, I think a lot of companies said, well, let's just put something in place now and it's going to go away. Well, it isn't going away. And so what Fortinet are looking to do, and I think it's not just one point product. It is a combination of technologies. It could be end point security. We're even looking at you know, at home networking through our own devices or our partnership with Linksys. It is looking at that zero trust architecture. It is looking at more network security, whether it be in the data center or in a cloud. I think what's important though, is two things. One is that no matter if you're on the network, off the network or traveling per se, then you need the user experience to be the same or simple. I can't just change the way I work because I'm at home versus travel versus you know, in the office. And the security needs to be consistent on those three places as well. So our goal, when we bring some of those solutions together, zero trust and endpoint and network security and policy and identity is to give the same user experience, a simple user experience and the high level of enterprise security, no matter, you know, if you're on and off the network. And those are the key. And I think today customers kind of struggle because they probably got four or five vendors in those different areas and they're trying to make them to work and it's very hard. And so that's why we, you know, we put forward a more of a platform approach per use case with doing that. >> Let's talk about some of those key use cases. And you mentioned ransomware a minute ago, and I just as of a couple of days ago, Kronos is, you know, the latest big name organization to be hit. A lot of folks concerned so many big companies and small companies rely on them. It's not going to affect, you know, the last paycheck in December, but that's a use case that Fortinet has been covering for a long time. I think when we spoke a few months ago, 2020 to 2021 ransomware was up nearly 11 fold. What are some of the things going on there and how are you guys working with customers to address that as we enter 2022? >> Yeah. Well, I definitely think you also saw the, you know, the recent vulnerability, the Log4j and that sits in a lot of systems. Now that sits in a lot of customer systems. It sits in a lot of security systems as well, by the way. So we come back to this, you know, supply chain issue. And so customers kind of accepting that this is going to be as this attack surface of the network and cloud and devices and users and whether or not the network you know, keeps continuing to expand. They're going to accept that these zero days are going to come along. They're going to, they also understand the sophistication of the threats. We're seeing a lot of activity of the threats in the reconnaissance space, and they're looking at your external attack surface and working out how they can get in. And so, I think customers are accepting that this is just getting more sophistication, there's a bigger attack surface. And so what they're looking at is to deploy some more detection capabilities, more just training of people, not to click on stuff, but you know, building infrastructure so it's segmented, long-term though the only way to defend against these ransomware attacks is to usually platform that then allows you to build automation that long-term allows you to build some contextual engine. Why, when, where, what are you doing, otherwise it's just going to be too hard, just trying to bolt together, you know, 10 or 15 products from vendors that don't get on well, none the best of times. So yeah, that's, it's long, it's a longterm architecture is the only thing that's going to work for customers. >> And for a long time, I think probably since I've known you John, Fortinet has been talking about the security fabric. Now Gartner is talking about the cybersecurity mesh architecture. Talk to me about those two. How similar is that? How leading edge was Fortinet and describe what a cybersecurity mesh architecture is? >> Well, it always takes a while for Gartner to catch up with us, but they, if I'm in a joking Gartner please except the apologies. That, you know, I think they've started to talking about this cybersecurity mesh architecture mesh. And what the saying is that, you know, these products need to talk to each other. And yes you can send things off into a central location for SIM or operational management, but really need to talk to each other and transfer exchange, threat intelligence. They need to be able to exchange policy long. They also need to be able to build automation. You know, a really good example is if our EDR system detects that your laptop has got a virus or a vulnerability, then I can, the EDR system will tell the zero trust policy manager don't allow access application. Or it could if you're on the network, you could tell the Wi-Fi, take off, take them off the network. So this automation is integration is the real long-term goal of the Gartner mesh. It's always been the long-term goal of Fortinet. Yes, we do individual products. You can buy them, but the real power long-term is to get that automation built into the platform. And as I said, even longer term start applying contextual rules, which will be super powerful in stopping, you know, attacks and breaches. >> Tremendous amount of power and capabilities that that context will provide. I was looking at some stats from Gartner and they said that by 2024, which is we're two years basically away from that organizations that do adopt this cybersecurity mesh architecture to integrate security tools, to work as a collaborative ecosystem, significant reduction in the financial impact of security incidents by 90%. That's huge and I know that you guys also have integrations with over 450 third-party technology partners as part of the security fabric. So you're ahead of the game. >> Well, it's not saying, you know, just buy from Fortinet, that's what you need to do, but it's not saying that at all. What, I think what Gartner is saying, and what we've been saying is that take a use case like work from anywhere and then build your platform, a platform for that use case. Now, what we are saying is, again, it's not saying you go from 30 products down to one, you go from 30 products down to maybe five or six platforms, but those platforms need to work together. They also need to exchange threat intelligence and policy and build automation. And so I think the platform approach, every CSO I speak to is just tired of buying another product, another product. They just want to get something that works and is automated long-term. And so the platform and the Gartner mesh. It's a slightly different concept, but something else we call convergence. Okay. So consolidation is consolidation of the vendors, but you may still have the same number of products. You still may have an end point in a zero trust and an email. Convergence is different where we bring it together and eliminating individual products. A really good example of that is SD-WAN that brings together security and application routing. And that goes back to a concept that Fortinet had since our beginning 20 years ago. And that is the original internet that we still use a lot today really has no idea who you are, what device are you using, where are you going, what application, what's the content, no clue, it just connects you. And so that leads to a lot of security being bolted on afterwards in different places. And so this convergence, we call it security different networking, where you start to integrate the security, which may be contextual, it maybe identity, maybe application running like SD-WAN, maybe content like next gen firewall. You bring those together. Now, when you do that, you face some compute challenges. And we've been one of the pioneers and building asics that allow this acceleration to bring this convergence together. But that's another area that's happening as well. It's different from consolidation, but it's bringing together that security and networking so you're not bolting things together as you go forward. >> Different from consolidation, but incredibly important to be able to reduce those silos as businesses are facing some of the challenges that you talked about, the persistence of work from anywhere, the threat landscape, the cybersecurity skills gap. >> Yeah. And you can do this convergence in different places. So you can do it at the cloud edge because you can throw a lot of compute at it. At the one edge, you probably need a asic approach, data center edge, a 5G edge. There's the LAN edge, which is the connectivity. Cause I sometimes have people go, well, let's just put all the security in the cloud, but now yes, you do need security in the cloud. You needs security from the cloud before the cloud, but there's also security needed these ages. And there's also another area that's been under huge attack now is operational technologies. So manufacturers, energy, gas, everyone is really got some physical infrastructure. Even a branch you can consider to be operational technology and they got cameras and other capabilities. So that, especially for the traditional operational technology, that's hard to open up. Because you need access, you need remote access and what's a seeing a huge amount of attacks there. In that world, you know, you've got to put the security there, physically with it to make sure you secure those components. >> What about the, from a challenge perspective John, we talked a lot in the last year, 18, 20, 22 months, I'm losing count of the acceleration of digital. What are some of the security opportunities there that provides Fortinet to help customers solve that if the acceleration is happening faster than the, some of the, you know, that their security infrastructure can keep pace. What are some of the opportunities there for you guys to help customers address that problem? >> Well, this is always been a battle between security and networking. You know, networking is gone from this 400 times faster than it was before. Security is still a lot of it's software. And so, you know, what you don't want to do is and the security team saying is say no all the time. No, don't do that project, it's too insecure. Stop doing that. No slow down on that. And that's, you know, always been an issue for security in that people think of it as a tax or a burden that slows things down. That's why I come back to this convergence. When you're building a network, the security should be inside that. Should be built and integrated. So if I'm building my one edge, which connects my building to a cloud or whatever, when I put that connectivity in there to an SD-WAN device, it should have security integrated inside it. The same effect I found building, you know, a data center or a cloud capability. So I think, you know, customers are you know, security teams can't stop the business from moving forward and building these applications wherever they may be in retail or manufacturing or healthcare. And so they just need to take a different approach to enable that speed of acceleration and to our minds having it totally integrated and converge is the only way you're going to be able to achieve the speed and the security at the same time. >> And that speed is critical as is a security. But let's talk about that cybersecurity skills gap. Something that I think I read recently is in its fifth year, we've talked about this before, but as you alluded to at the beginning of our conversation, Fortinet is very dedicated to training, lots of individuals. Talk to me about that skills gap. And you talked that it also affects people, companies being able to retain talent. How are you guys helping to address? >> Yeah, we did actually a survey a few months ago, a 2500 cybersecurity professionals. And, you know, one really revealing fact was about, I think it was about 70% said they'd had an incident because of the lack of training. Now that could be people who are just clicking on things. Okay. Versus somebody who doesn't, is not trained enough to see a threat. So I think, you know, the question going to go, but either way, the 70% of that, you know, is attributed to that breach. And so it's so, so important. And right from the start Fortinet has provided training. We provide free training to our partners, free training to our customers. I have a quite a large team that's building on the curriculum. So we supply curriculum and gear to over 450 universities and colleges. You mentioned the re-skilling of the veterans as well, over 2000. And to us, it's very important. So this commitment to get people trained because in the end there's, yeah, there's always a people part of this problem, whether it be people clicking on things or whether it be people not understanding and configuring crying, and then people having passwords of one two three or whatever. All these things, all these human things need to get, you know, we need to get educated and trained on it. So we'll continue that. I think a million's probably not enough. It's probably should be two million, but we'll try our best to get people trained as much as possible. And the other thing that I also saw in the survey was that once certified employees thought that was extremely important. It does take a lot of time. So, you know, one of our NSE 4 courses on our firewalls takes a week. It does a lot of things to learn. So one thing we're going to try and do is try and modularize a bit more so we can break it up a bit. But there's going to be a problem. It's kind of like the supply chain, the supply is not there, the people, this is right. The chips, they're not there. They're not there, you've got to try and fix it and expand the training and education of people. >> And I think that's fantastic that Fortinet has been dedicated to that for so long. Look forward to hearing how you guys, the progress that you make on that training 1 million folks. Will we see you at Accelerate in 2022? >> Yeah. Well, so Accelerate 22 is going to be a hybrid, of course. I'm actually, you can't really see here cause I've got my great office here. But in front of me is the window. I can actually see the Apple campus just over there. And this is our new campus in Sunnyvale, Silicon valley. We've got a pretty expensive training center and executive briefing center. So we're going to probably do in the morning of Accelerate 22, a live broadcast of some of the execs and some of our partners and customers, and then have some online stuff. So hybrid probably this year again. But a bit of physical presence. But yeah, we're expecting quite a few partners to, a few partners to be here, live and a few partners, obviously a lot of partners to tune in to the live broadcast. >> That's fantastic. I look forward to that hybrid event. John, great to see you as always. Thank you so much for the update and sharing what enterprises, the battles that they're facing, how Fortinet and the cybersecurity mesh can help. We look forward to seeing you in 2022. >> Thank you Lisa. Thank you. >> For John Maddison, I'm Lisa Martin. You've been watching this CUBE conversation. We'll see you next time. (lively music)

(upbeat music) >> Welcome to this CUBE conversation. I am Lisa Martin, excited to welcome back one of our distinguished alumni, Derek Manky joins me next. Chief security Insights and Global Threat Alliances at Fortinet's FortiGuard Labs. Derek, welcome back to the program. >> Yes, it's great to be here and great to see you again, Lisa. Thanks for having me. >> Likewise, yeah, so a lot has happened. I know we've seen you during this virtual world, but so much has happened with ransomware in the last year. It's unbelievable, we had about 14 months ago, this dramatic shift to a distributed workforce, you had personal devices on in network perimeters and non-trusted devices or trusted devices on home networks and lots of change there. Talk to me about some of the things that you and FortiGuard Labs have seen with respect to the evolution of ransomware. >> Yeah, sure, so it's becoming worse, no doubt. We highlighted this in our Threat Landscape Report. If we just take a step back looking at ransomware itself, it actually started in the late 1980s. And it didn't, that was very, they relied on snail mail. It was obviously there was no market for it at the time. It was just a proof of concept, a failed experiment if you will. But it really started getting hot a decade ago, 10 years ago but the technology back then wasn't the cryptography they're using, the technique wasn't as strong as easily reversed. And so they didn't really get to a lot of revenue or business from the cyber criminal perspective. That is absolutely not the case today. Now they have very smart cryptography they're experts when say they, the cyber criminals at their game. They know there's a lot of the attack surfaces growing. There's a lot of vulnerable people out there. There's a lot of vulnerable devices. And this is what we saw in our threat landscape group. What we saw at seven times increase in ransomware activity in the second half of 2020. And that momentum is continuing in 2021. It's being fueled by what you just talked about. By the work from anywhere, work from home environment a lot of vulnerable devices unpatched. And these are the vehicles that the ransomware is the payload of course, that's the way that they're monetizing this. But the reality is that the attack surface has expanded, there's more vulnerable people and cyber criminals are absolutely capitalizing on that. >> Right, we've even seen cyber criminals capitalizing on the pandemic fears with things that were around the World Health Organization or COVID-19 or going after healthcare. Did you see an uptick in healthcare threats and activities as well in the last year? >> Yeah, definitely, so I would start to say that first of all, the... Nobody is immune when it comes to ransomware. This is such again, a hot target or a technique that the cybercriminals are using. So when we look at the verticals, absolutely healthcare is in the top five that we've seen, but the key difference is there's two houses here, right? You have what we call the broad blanketed ransomware attacks. So these aren't going after any particular vertical. They're really just trying to spray as much as they can through phishing campaigns, not through... there's a lot of web traffic out there. We see a lot of things that are used to open playing on that COVID-19 theme we got, right? Emails from HR or taxes and scams. It's all related to ransomware because these are how they're trying to get the masses to open that up, pay some data sorry, pay some cryptocurrency to get access to their data back. Oftentimes they're being held for extortions. They may have photos or video or audio captures. So it's a lot of fear they're trying to steal these people but probably the more concern is just what you talked about, healthcare, operational technology. These are large business revenue streams. These are take cases of targeted ransoms which is much different because instead of a big volumetric attack, these are premeditated. They're going after with specific targets in mind specific social engineering rules. And they know that they're hitting the corporate assets or in the case of healthcare critical systems where it hurts they know that there's high stakes and so they're demanding high returns in terms of ransoms as well. >> With respect to the broad ransomware attacks versus targeted a couple of questions to kind of dissect that. Are the targeted attacks, are they in like behind the network firewall longer and faster, longer and getting more information? Are they demanding higher ransom versus the broader attacks? What's what are some of the distinctions there besides what you mentioned? >> Yeah, absolutely so the targeted texts are more about execution, right? So if we look at the attack chain and they're doing more in terms of reconnaissance, they're spending more cycles and investment really on their end in terms of weaponization, how they can actually get into the system, how they can remain undetected, collecting and gathering information. What we're seeing with groups like Ragnar Locker as an example, they're going in and they're collecting in some cases, terabytes of information, a lot, they're going after definitely intellectual property, things like source code, also PII for customers as an example, and they're holding them. They have a whole business strategy and plan in mind on their place, right? They hold them for ransom. They're often, it's essentially a denial of service in some cases of taking a revenue stream or applications offline so a business can't function. And then what they're doing is that they're actually setting up crime services on their end. They, a lot of the the newest ransom notes that we're seeing in these targeted attacks are setting up channels to what they call a live chat support channel that the victim would log into and actually talk directly live to the cybercriminal or one of their associates to be able to negotiate the ransom. And they're trying to have in their point of view they're trying frame this as a good thing and say, we're going to show you that our technology works. We can decrypt some of the files on your system as an example just to prove that we are who we say we are but then they go on to say, instead of $10 million, we can negotiate down to 6 million, this is a good deal, you're getting 30% off or whatever it is but the fact is that they know by the time they've gotten to this they've done all their homework before that, right? They've done the targets, they've done all the things that they can to know that they have the organization in their grasp, right? >> One of the things that you mentioned just something I never thought about as ransomware as a business, the sophistication level is just growing and growing and growing and growing. And of course, even other bad actors, they have access to all the emerging technologies that the good guys do. But talk to me about this business of ransomware because that's what it seems like it really has become. >> Absolutely, it is massively sad. If you look at the cybercrime ecosystem like the way that they're actually pulling this off it's not just one individual or one cyber crime ring that, let's say five to 10 people that are trying to orchestrate this. These are big rings, we actually work closely as an example to, we're doing everything from the FortiGuard Labs with following the latest around some of the trends doing the protection and mitigation but also working to find out who these people are, what are their tactics and really attribute it and paint a picture of these organizations. And they're big, we're working some cases where there's over 50 people just in one ransomware gang. One of the cases we worked on, they were making over $60 million US in three months, as an example. And in some cases, keep in mind one of these targeted attacks like in terms of ransom demands and the targeted cases they can be an excess of $10 million just for one ransom attack. And like I said, we're seeing a seven times increase in the amount of attack activity. And what they're doing in terms of the business is they've set up affiliate marketing. Essentially, they have affiliates in the middle that will actually distribute the ransomware. So they're basically outsourcing this to other individuals. If they hit people with their ransomware and the people pay then the affiliate in the middle will actually get a commission cut of that, very high, typically 40 to 50%. And that's really what's making this lucrative business model too. >> Wow, My jaw is dropping just the sophistication but also the different levels to which they've put a business together. And unfortunately, for every industry it sounds very lucrative, so how then Derek do organizations protect themselves against this, especially knowing that a lot of this work from home stuff is going to persist. Some people want to stay home, what not. The proliferation of devices is only going to continue. So what are organizations start and how can you guys help? >> Start with the people, so we'll talk about three things, people, technology and processes. The people, unfortunately, this is not just about ransomware but definitely applies to ransomware but any attack, humans are still often the weakest link in terms of education, right? A lot of these ransomware campaigns will be going after people using nowadays seems like tax themes purporting to be from the IRS as an example or human resources departments or governments and health authorities, vaccination scams all these things, right? But what they're trying to do is to get people to click on that link, still to open up a malicious attachment that will then infect them with the ransomware. This of course, if an employee is up to date and hones their skills so that they know basically a zero trust mentality is what I like to talk about. You wouldn't just invite a stranger into your house to open a package that you didn't order but people are doing this a lot of the times with email. So really starting with the people first is important. There's a lot of free training information and security. There is awareness training, we offer that at Fortinet. There's even advanced training we do through our NSC program as an example. But then on top of that there's things like phishing tests that you can do regularly, penetration testing as well, exercises like that are very important because that is really the first line of defense. Moving past that you want to get into the technology piece. And of course, there's a whole, this is a security fabric. There's a whole array of solutions. Like I said, everything needs to be integrated. So we have an EDR and XDR as an example sitting on the end point, cause oftentimes they still need to get that ransomware payload to run on the end point. So having a technology like EDR goes a long way to be able to detect the threat, quarantine and block it. There's also of course a multi-factor authentication when it comes to identifying who's connecting to these environments. Patch management, we talk about all the time. That's part of the technology piece. The reality is that we highlight in the threat landscape report the software vulnerabilities that these rats more gangs are going after are two to three years old. They're not breaking within the last month they're two to three years old. So it's still about the patch management cycle, having that holistic integrated security architecture and the fabric is really important. NAC network access control is zero trust, network access is really important as well. One of the biggest culprits we're seeing with these ransom attacks is using IOT devices as launchpads as an example into networks 'cause they're in these work from home environments and there's a lot of unsecured or uninspected devices sitting on those networks. Finally process, right? So it's always good to have it all in your defense plan training and education, technology for mitigation but then also thinking about the what if scenario, right? So incident response planning, what do we do if we get hit? Of course we never recommend to pay the ransom. So it's good to have a plan in place. It's good to identify what your corporate assets are and the likely targets that cyber-criminals are going to go after and make sure that you have rigid security controls and threat intelligence like FortiGuard Labs applied to that. >> Yeah, you talk about the weakest link they are people I know you and I talked about that on numerous segments. It's one of the biggest challenges but I've seen some people that are really experts in security read a phishing email and almost fall for it. Like it looked so legitimately from like their bank for example. So in that case, what are some of the things that businesses can do when it looks so legitimate that it probably is going to have a unfortunately a good conversion rate? >> Yeah, so this is what I was talking about earlier that these targeted attacks especially when it comes to spear, when it comes to the reconnaissance they got so clever, it can be can so realistic. That's the, it becomes a very effective weapon. That's why the sophistication and the risk is rising like I said but that's why you want to have this multilayered approach, right? So if that first line of defense does yield, if they do click on the link, if they do try to open the malicious attachment, first of all again through the next generation firewall Sandboxing solutions like that, this technology is capable of inspecting that, acting like is this, we even have a FortiAI as an example, artificial intelligence, machine learning that can actually scan this events and know is this actually an attack? So that element goes a long way to actually scrub it like content CDR as well, content disarm as an example this is a way to actually scrub that content. So it doesn't actually run it in the first place but if it does run again, this is where EDR comes in like I said, at the end of the day they're also trying to get information out of the network. So having things like a Platinum Protection through the next generation firewall like with FortiGuard security subscription services is really important too. So it's all about that layered approach. You don't want just one single point of failure. You really want it, this is what we call the attack chain and the kill chain. There's no magic bullet when it comes to attackers moving, they have to go through a lot of phases to reach their end game. So having that layer of defense approach and blocking it at any one of those phases. So even if that human does click on it you're still mitigating the attack and protecting the damage. Keep in mind a lot of damages in some cases kind of a million dollars plus. >> Right, is that the average ransom, 10 million US dollars. >> So the average cost of data breaches ever seen which are often related to ransom attacks is close to that in the US, I believe it's around just under $9 million about 8.7 million, just for one data breach. And often those data breaches now, again what's happening is that the data it's not just about encrypting the data, getting access because a lot of organizations part of the technology piece and the process that we recommend is backups as well of data. I would say, organizations are getting better at that now but it's one thing to back up your data. But if that data is breached again, cybercriminals are now moving to this model of extorting that saying, unless you pay us this money we're going to go out and make this public. We're going to put it on piece and we're going to sell it to nefarious people on the dark web as well. >> One more thing I want to ask you in terms of proliferation we talked about the distributed workforce but one of the things, and here we are using Zoom to talk to each other, instead of getting to sit together in person we saw this massive proliferation in collaboration tools to keep people connected, families businesses. I talked a bit a lot of businesses who initially will say, oh we're using Microsoft 365 and they're protecting the data while they're not or Salesforce or Slack. And that shared responsibility model is something that I've been hearing a lot more about lately that businesses needing to recognize for those cloud applications that we're using and in which there's a lot of data traversing it could include PII or IP. We're responsible for that as the customer to protect our data, the vendor's responsible for protecting the integrity of the infrastructure. Share it with us a little bit about that in terms of your thoughts on like data protection and backup for those SaaS applications. >> Yeah, great question, great question tough one. It is so, I mean ultimately everybody has to have, I believe it has to have their position in this. It's not, it is a collaborative environment. Everyone has to be a stakeholder in this even down to the end users, the employees being educated and up-to-date as an example, the IT departments and security operation centers of vendors being able to do all the threat intelligence and scrubbing. But then when you extend that to the public cloud what is the cloud security stack look at, right? How integrated is that? Are there scrubbing and protection controls sitting on the cloud environments? What data is being sent to that, should it be cited center as an example? what's the retention period? How long does the data live on there? It's the same thing as when you go out and you buy one of these IOT devices as an example from say, a big box store and you go and just plug it into your network. It's the same questions we should be asking, right? What's the security like on this device model? Who's making it, what data is it going to ask for me? The same thing when you're installing an application on your mobile phone, this is what I mean about that zero trust environment. It should be earned trust. So it's a big thing, right? To be able to ask those questions and then only do it on a sort of need to know and medium basis. The good news is that a lot of CloudStack now and environments are integrating security controls. We integrated quite well with Fortinet as an example but this is an issue of supply chain. It's really important to know what lives upstream and how they're handling the data and how they're protecting it absolutely. >> Such interesting information and it's a topic ransomware that we could continue talking about, Derek, thank you for joining me on the program today updating us on what's going on, how it's evolving and ultimately what organizations in any industry need to do with protecting people and technology and processes to really start reducing their risks. I thank you so much for joining me today. >> All right it's a pleasure, thank you. >> Likewise Derek Manky I'm Lisa Martin. You're watching this CUBE conversation. (upbeat music)

>> From The Cube Studios in Palo Alto and Boston connecting with thought-leaders all around the world, this is a Cube Conversation. >> Hello, everyone, and welcome to this Cube Conversation, I'm Dave Vellante. Now, you know I love data, and today we're going to introduce you to a new data and analytical platform, and we're going to take it to the world of cloud database and data warehouses. And with me is Sagar Kadakia who's the head of Enterprise IT (indistinct) 7Park Data. Sagar, welcome back to the Cube. Good to see you. >> Thank you so much, David. I appreciate you having me back on. >> Hey, so new gig for you, how's it going? Tell us about 7Park Data. >> Yeah. Look, things are going well. It started at about two months ago, just a, you know, busy. I had a chance last, you know a few months to kind of really dig into the dataset. We have a tremendous amount of research coming out in Q4 Q1 around kind of the public cloud database market public cloud analytics market. So, you know, really looking forward to that. >> Okay, good. Well, let's bring up the first slide. Let's talk about where this data comes from. Tell us a little bit more about the platform. Where's the insight. >> Yeah, absolutely. So I'll talk a little about 7Park and then we'd kind of jump into the data a little bit. So 7Park was founded in 2012 in terms of differentiator, you know with other alternative data firms, you know we use NLP machine learning, you know AI to really kind of, you know, structure like noisy and unstructured data sets really kind of generate insight from that. And so, because a lot of that know how we ended up being acquired by Vista back in 2018. And really like for us, you know the mandate there is to really, you know look across all their different portfolio companies and try to generate insight from all the data assets you know, that these portfolio companies have. So, you know, today we're going to be talking about you know, one of the data sets from those companies it's that cloud infrastructure data set. We get it from one of the portfolio companies that you know, helps organizations kind of manage and optimize their cloud spend. It's real time data. We essentially get this aggregated daily. So this certainly different than, you know your traditional providers maybe giving you quarterly or kind of by annual data. This is incredibly granular, real time all the way down to the invoice level. So within this cloud infrastructure dataset we're tracking several billion dollars worth of spend across AWS, Azure and GCP. Something like 350 services across like 20 plus markets. So, you know, security machine learning analytics database which we're going to talk about today. And again like the granularity of the KPIs I think is kind of really what kind of you know, differentiates this dataset you know, with just within database itself, you know we're tracking over 20 services. So, you know, lots to kind of look forward to kind of into Q4 and Q1. >> So, okay. So the main spring of your data is if I'm a customer and I there's a service out there there are many services like this that can help me optimize my spend and the way they do that is I basically connect their APIs. So they have visibility on what the transactions that I'm making my usage statistics et cetera. And then you take that and then extrapolate that and report on that. Is that right? >> Exactly. Yeah. We're seeing just on this one data set that we're going to talk about today, it's something like six 700 million rows worth of data. And so kind of what we do is, you know we kind of have the insight layer on top of that or the analytics layer on top of all that unstructured data, so that we can get a feel for, you know a whole host of different kind of KPIs spend, adoption rates, market share, you know product size, retention rates, spend, you know, net price all that type of stuff. So, yeah, that's exactly what we're doing. >> Love it, there's more transparency the better. Okay. So, so right, because this whole world of market sizing has been very opaque you know, over the years, and it's like you know, backroom conversations, whether it's IDC, Gartner who's got what don't take, you know and the estimations and it's very, very, you know it's not very transparent so I'm excited to see what you guys have. Okay. So, so you have some data on the public cloud and specifically the database market that you want to share with our audience. Let's bring up the next graphic here. What are we looking at here Sagar? What are these blue lines and red lines what's this all about? >> Yeah. So and look, we can kind of start at the kind of the 10,000 foot view kind of level here. And so what we're looking at here is our estimates for the entire kind of cloud database market, including data warehousing. If you look all the way over to the right I'll kind of explain some of these bars in a minute but just high level, you know we're forecasting for this year, $11.8 billion. Now something to kind of remember about that is that's just AWS, Azure and GCP, right? So that's not the entire cloud database market. It's just specific to those three providers. What you're looking at here is the breakout and blue and purple is SQL databases and then no SQL databases. And so, you know, to no one's surprise here and you can see, you know SQL database is obviously much larger from a revenue standpoint. And so you can see just from this time last year, you know the database market has grown 40% among these three cloud providers. And, you know, though, we're not showing it here, you know from like a PI perspective, you know database is playing a larger and larger role for all three of these providers. And so obviously this is a really hot market, which is why, you know we're kind of discussing a lot of the dynamics. You don't need to Q and Q Q4 and Q1 >> So, okay. Let's get into some of the specific firm-level data. You have numbers that you want to share on Amazon Redshift and Google BigQuery, and some comments on Snowflake let's bring up the next graphic. So tell us, it says public cloud data, warehousing growth tempered by Snowflake, what's the data showing. And let's talk about some of the implications there. >> Yeah, no problem. So yeah, this is kind of one of the markets, you know that we kind of did a deep dive in tomorrow and we'll kind of get this, you know, get to this in a few minutes, we're kind of doing a big CIO panel kind of covering data, warehousing, RDBMS documents store key value, graph all these different database markets but I thought it'd be great, you know just cause obviously what's occurring here and with snowflake to kind of talk about, you know the data warehousing market, you know, look if you look here, these are some of the KPIs that we have you know, and I'll kind of start from the left. Here are some of the orange bars, the darker orange bars. Those are our estimates for AWS Redshift. And so you can see here, you know we're projecting about 667 million in revenue for Redshift. But if you look at the lighter arm bars, you can see that the service went from representing about 2% of you know, AWS revenue to about 1.5%. And we think some of that is because of Snowflake. And if we kind of, take a look at some of these KPIs you know, below those bar charts here, you know one of the things that we've been looking at is, you know how are longer-term customer spending and how are let's just say like newer customers spending, so to speak. So kind of just like organic growth or kind of net expansion analysis. And if you look at on the bottom there, you'll see, you know customers in our dataset that we looked at, you know that were there 3Q20 as well as 3Q19 their spend on AWS Redshift is 23%. Right? And then look at the bifurcation, right? When we include essentially all the new customers that onboard it, right after 3Q19, look at how much they're bringing down the spend increase. And it's because, you know a lot of spend that was perhaps meant for Redshift is now going to Snowflake. And look, you would expect longer-term customers to spend more than newer customers. But really what we're doing is here is really highlighting the stark contrast because you have kind of back to back KPIs here, you know between organic spend versus total spend and obviously the deceleration in market share kind of coming down. So, you know, something that's interesting here and we'll kind of continue tracking that. >> Okay. So let's maybe come back to this mass Colombo questions here. So the start with the orange side. So we're talking about Snowflake being 667 million. These are your estimates extrapolated based on what we talked about earlier, 1.5% of the AWS portfolio of course you see things like, they continue to grow. Amazon made a bunch of storage announcements last week at the first week of re-invent (indistinct) I mean just name all kinds of databases. And so it's competing with a lot of other services in the portfolio and then, but it's interesting to see Google BigQuery a much larger percentage of the portfolio, which again to me, makes sense people like BigQuery. They like the data science components that are built in the machine learning components that are built in. But then if you look at Snowflake's last quarter and just on a run rate basis, it's over there over $600 million. Now, if you just multiply their last quarter by four from a revenue standpoint. So they got Redshift in their sites, you know if this is, you know to the extent this is the correct number and I know it's an estimate but I haven't seen any better numbers out there. Interesting Sagar, I mean Snowflake surpassed the value of snowflakes or past service now last Friday, it's probably just in trading today you know, on Monday it's maybe Snowflake is about a billion dollars less than the in value than IBM. So you're saying snowflake in a lot of attention, post IPO the thing is even exploded more. I mean, it's crazy. And I presume that's rippled into the customer interest areas. Now the ironic thing here of course, is that that snowflake most of its revenue comes from AWS running on AWS at the same time, AWS and or Redshift and snowflake compete. So you have this interesting dynamic going on. >> Yeah. You know, we've spoken to so many CIOs about kind of the dynamics here with Redshift and BigQuery and Snowflake, you know as it kind of pertains to, you know, Redshift and Snowflake. I think, you know, what I've heard the most is, look if you're using Redshift, you're going to keep using it. But if you're new to data warehousing kind of, so to speak you're going to move to Snowflake, or you're going to start with Snowflake, you know, that and I think, you know when it comes to data warehousing, you're seeing a lot of decisions kind of coming from, you know, bottom up now. So a lot of developers and so obviously their preference is going to be Snowflake. And then when you kind of look at BigQuery here over to the right again, like look you're seeing revenue growth, but again, as a as a percentage of total, you know, GCP revenue you're seeing it come down and look, we don't show it here. But another dynamic that we're seeing amongst BigQuery is that we are seeing adoption rates fall versus this time last year. So we think, again, that could be because of Snowflake. Now, one thing to kind of highlight here with BigQuery look it's kind of the low cost alternative, you know, so to speak, you know once Redshift gets too expensive, so to speak, you know you kind of move over to, to BigQuery and we kind of put some price KPIs down here all the way at the bottom of the chart, you know kind of for both of them, you know when you kind of think about the net price per kind of TB scan, you know, Redshift does it pro rate right? It's five bucks or whatever you, you know whatever you scan in, whereas, you know GCP and get the first terabyte for free. And then everything is prorated after that. And so you can see the net price, right? So that's the price that people actually pay. You can see it's significantly lower that than Redshift. And again, you know it's a lower cost alternative. And so when you think about, you know organizations or CIO's that want to save some money certainly BigQuery, you know, is an option. But certainly I think just overall, you know, Snowflake is is certainly having, you know, an impact here and you can see it from, you know the percentage of total revenue for both these coming down. You know, if we look at other AWS database services or you mentioned a few other services, you know we're not seeing that trend, we're seeing, you know percentage of total revenue hang in or accelerate. And so that's kind of why we want to point this out as this is something unique, you know for AWS and GCP where even though you're seeing growth, it's decelerating. And then of course you can kind of see the percentage of revenue represents coming down. >> I think it's interesting to look at these two companies and then of course Snowflake. So if you think about Snowflake and BigQuery both of those started in the cloud they were true born in the cloud databases. Whereas Redshift was a deal that Amazon did, you know with parxl back in the day, one time license fee and then they re-engineered it to be kind of cloud based. And so there is some of that historical o6n-prem baggage in there. I know that AWS did a tremendous job in rearchitecting that but nonetheless, so I'll give you a couple of examples. If you go back to last year's reinvent 2019 of course Snowflake was really the first to popularize this idea of separating compute from storage and even compute from compute, which is kind of nuance. So I won't go into that, but the idea being you can dial up or dial down compute as you need it you can even turn off compute in the world of Snowflake and just, you know, you're paying an S3 for storage charges. What Amazon did last reinvent was they announced the separation of compute and storage, but what the way they did it was they did it with a tiering architecture. So you can't ever actually fully turn off the compute, but it's great. I mean, it's customers I've talked to say, yes I'm saving a lot of money, you know, with this approach. But again, there's these little nuances. So what Snowflake announced this year was their data cloud and what the data cloud is as a whole new architecture. It's based on this global mesh. It lives across both AWS and Azure and GCP. And what Snowflake has done is they've taken they've abstracted the complexity of the clouds. So you don't even necessarily have to know what you're running on. You have to worry about it any Snowflake user inside of that data cloud if given access can share data with any other user. So it's a very powerful concept that they're doing. AWS at reinvent this year announced something called AWS glue elastic views which basically allows you to take data across their entire database portfolio. And I'm going to put, share in quotes. And I put it in quotes because it's essentially doing copying from a source pushing to a target AWS database and then doing a change data management capture and pushes that over time. So it, it feels like kind of an attempt to do their own data cloud. The advantages of AWS is that they've got way more data stores than just Snowflake cause it's one data store. So was AWS says Aurora dynamo DB Redshift on and on and on streaming databases, et cetera where Snowflake is just Snowflake. And so it's going to be interesting to see, you know these two juxtaposing philosophies but I want it to sort of lay that out because this is just it's setting up as a really interesting dynamic. Then you can bring in Azure as well with Microsoft and what they're doing. And I think this is going to be really fascinating to see how this plays out over the next decade. >> Yeah. I think some of the points you brought up maybe a little bit earlier were just around like the functional limits of a Redshift. Right. And I think that's where, you know Snowflake obviously does it does very, very well you know, you kind of have these, you know kind of to come, you know, you kind of have these, you know if you kind of think about like the market drivers right? Like, let's think about even like the prior slide that we showed, where we saw overall you know, database growth, like what's driving all of that what's driving Redshift, right. Obviously proximity application, interdependencies, right. Costs. You get all the credits or people are already working with the big three providers. And so there's so many reasons to continue spending with them, obviously, you know, COVID-19 right. Obviously all these apps being developed right in the cloud versus data centers and things of that nature. So you have all of these market drivers, you know for the cloud database services for Redshift. And so from that perspective, you know you kind of think, well why are people even to go to a third party vendor? And I think, you know, at that point it has to be the functional superiority. And so again, like a lot of times it depends on, you know, where decisions are coming from you know, top down or bottom up obviously at the engineering at the developer level they're going to want better functionality. Maybe, you know, top-down sometimes, you know it's like, look, we have a lot of credits, you know we're trying to save money, you know from a security perspective it could just be easier to spin something up you know, in AWS, so to speak. So, yeah, I think these are all the dynamics that, you know organizations have to figure out every day, but at least within the data warehousing space, you are seeing spend go towards Snowflake and it's going away to an extent as we kind of see, you know growth decelerate for both of these vendors, right. It's not that revenue's not going out there is growth which is that growth is, it's just not the same as it used to be, you know, so to speak. So yeah, this is a interesting area to kind of watch and I think across all the other markets as well, you know when you think about document store, right you have AWS document DB, right. What are the impacts there with with Mongo and some of these other kind of third party data warehousing vendors, right. Having to compete with all the, you know all the different services offered by AWS Azure like the cosmos and all that stuff. So, yeah, it's definitely kind of turning into a battle Royal, you know as we kind of head into, into 2021. And so I think having all these KPIs is really helping us kind of break down and figure out, you know which areas like data warehousing are slowing down. But then what other areas in database where they're seeing a tremendous amount of acceleration, like as we said, database revenue is driving. Like it's becoming a bigger part of their overall revenue. And so they are doing well. It just, you know, there's obviously snowflake they have to compete with here. >> Well, and I think maybe to your point I infer from your point, it's not necessarily a zero sum game. And as I was discussing before, I think Snowflake's really trying to create a new market. It's not just trying to steal share from the Terra datas and the Redshifts and the PCPs of the world, big queries and and Azure SQL server and Oracle and so forth. They're trying to create a whole new concept called the data cloud, which to me is really important because my prediction is what Snowflake is doing. And they don't even really talk a ton about this but they sort of do, if you squint through the lines I think what they're doing is first of all, simplicity is there, what they're doing. And then they're putting data in the hands of business people, business line people who have domain context, that's a whole new way of thinking about a data architecture versus the prevalent way to do a data pipeline is you got data engineers and data scientists, and you ingest data. It's goes to the beginning of the pipeline and that's kind of a traditional way to do it. And kind of how I think most of the AWS customers do it. I think over time, because of the simplicity of Snowflake you're going to see people begin to look at new ways to architect data. Anyway, we're almost out of time here but I want to bring up the next slide which is a graphic, which talks about a database discussion that you guys are having on 12/8 at 2:00 PM Eastern time with Bain and Verizon who what's this all about. >> Yeah. So, you know, one of the things we wanted to do is we kind of kick off a lot of the, you know Q4 Q1 research or putting on the database spark. It is just like kind of, we did, you know we did today, which obviously, you know we're really going to expand on tomorrow at a at 2:00 PM is discuss all the different KPIs. You know, we track something like 20 plus database services. So we're going to be going through a lot more than just kind of Redshift and BigQuery. Look at all the dynamics there, look at, you know how they're very against some of the third party vendors like the Snowflake, like a Mongo DB, as an example we got some really great, you know, thought leaders you know, Michael Delzer and Praveen from verizon they're going to kind of help, or they're going to opine on all the dynamics that we're seeing. And so it's going to be a very kind of, you know structured wise, it's going to be very quantitative but then you're going to have this beautiful qualitative discussion to kind of help support a lot of the data points that we're capturing. And so, yeah, we're really excited about the panel you know, from, you know, why you should join standpoint. Look, it's just, it's great, competitive Intel. If you're a third party, you know, database, data warehousing vendor, this is the type of information that you're going to want to know, you know, adoption rates market sizing, retention rates, you know net price reservers, on demand dynamics. You know, we're going through a lot that tomorrow. So I'm really excited about that. I'm just in general, really excited about a lot of the research that we're kind of putting out. So >> That's interesting. I mean, and we were talking earlier about AWS glue elastic views. I'd love to see your view of all the database services from Amazon. Cause that's where it's really designed to do is leverage those across those. And you know, you listen to Andrew, Jesse talk they've got a completely different philosophy than say Oracle, which says, Hey we've got one database to do all things Amazon saying we need that fine granularity. So it's going to be again. And to the extent that you're providing market context they're very excited to see that data Sagar and see how that evolves over time. Really appreciate you coming back in the cube and look forward to working with you. >> Appreciate Dave. Thank you so much. >> All right. Welcome. Thank you everybody for watching. This is Dave Vellante for the cube. We'll see you next time. (upbeat music)

>> From theCube studios in Palo Alto in Boston, bringing you data-driven insights from theCube in ETR. This is Breaking Analysis with Dave Vellante. >> New data suggests the tech spending will be higher than we previously thought for 2021. COVID learnings, a faster than expected vaccine rollout, productivity gains in the last 10 months, and broad-based cloud leverage lead us to raise our outlook for next year. We now expect a three to 5% increase in 2021 technology spending, roughly double our previously forecasted growth rate of 2%. Hello everyone and welcome to this week's we keep on Cube Insights powered by ETR. In this breaking analysis, we're going to share new spending data from ETR partners and take a preliminary look at which sectors and which companies are showing momentum heading into next year. Let's get right into it. The data is pointing to a strong 2021 rebound. A latest survey from ETR and the information from theCube Community suggests that the accelerated pace of the vaccine rollout pent up demand for normalcy and learnings from COVID will boost 2021 tech spending higher than previously anticipated. Now a key factor we've cited is that the forced March to digital transformation due to the pandemic created a massive proof of concept for what works and what doesn't in a digital business. CIOs are planning to bet on those sure things to drive continued productivity improvements and new business opportunities. Now, speaking of productivity, nearly 80% of respondents in the latest ETR survey indicate that productivity either stayed the same or improved over the past three months. Now of those, the vast majority, more than 80% cited improvements in productivity. This has been a common theme throughout the year. As well, the expectation among CIOs is that many workers will return to the office in the second half of the year, which we expect will drive new spending in the infrastructure needs of company HQs, which have been neglected over the past 10 months. Now, despite the expectation that many workers will return to the office, 2020 has shown us that working remotely, hey, it's here to stay, and a much larger number of employees are going to be permanently remote working than pre pandemic. ETR survey data shows that that number is going to be approximately double over the longterm. We'll look at some of that specific data. In addition, cloud computing, it became the staple of business viability in 2020. Those that were up the cloud adoption ramp, well, they benefited greatly, those that weren't well, they had to learn fast. Now, along with remote work cloud necessitated new thinking around network security, and as we've reported identity access management, endpoint security and cloud security with the beneficiaries. Companies like Okta, CrowdStrike, Zscaler, a number of others continue to ride this wave. Larger established security companies like Cisco, Palo Alto Networks, F5, Fortunate and others, they have major portions of their business that are benefiting from the tailwinds in the shift and network traffic, as a result of cloud and remote work. Now, despite all the momentum in the market and the expect of improvements in 2021, these tailwinds are not expected to be evenly distributed, far from it. We think Q4 is going to remain soft relative to last year and Q1 2021 is going to be flat, maybe up slightly. Remember the COVID impact was definitely felt in March of this year. So based on the earnings that we saw, there may be some upside in Q1, given that organizations are still being cautious in Q4, and really there's still some uncertainty in Q1. Let's look at some of the survey responses and you'll see why we're more optimistic than we've previously reported. This chart shows the responses to key questions around spending trajectories from the March, June, September, and December surveys of this year. Now it's no surprise that there's been little change in remote workers and limiting business travel. But look at the other categories, seeing a dramatic reduction in hiring freezes. The percentage of companies freezing new IT deployments continues to drop throughout the year. And then conversely, the percentage of companies accelerating new it deployments that's sharply up to 34% from the March low of 12%. And look at the headcount trends. The percentage of companies instituting layoffs. It continues its downward trajectory while accelerated hiring is now up to 17%. So there's a lot to be excited about in these results. Now let's look the remote worker trend. How do CIO see that shift in the near to midterm? This chart shows the work from home data and it's amazingly consistent from the September survey drill down. You can see CIO's is indicate that on average, 15 to 60% of workers were remote prior to the pandemic, and that jumped up to 72 to 73% currently, and is expected to stay in the high fifties until the summer of 2021. Thereafter, organizations expect that the number of employees that work remotely on a permanent basis is going to more than double to 34% long term. By the way, I've talked to a number of executives, CEOs, CIOs, and CFOs that expect that number to be higher than these especially in the technology sector. They expect more than half of their workers to be remote and are looking to consolidate facilities cost to save money. As we've said, cloud computing has been the most significant contributor to business resilience and digital transformation this year. So let's look at cloud strategies and see how CIOs expect those to evolve. This chart shows responses to how organizations see multi-cloud evolving. It's interesting to note the ETR call-out, which concludes that the narrative around multi-cloud multi-cloud is real, and it is. But I want to talk to you about a flip side to this notion in that, as many customers have, or are planning to increasingly concentrate workloads in the cloud. This actually makes some sense. Sure, virtually every major company uses multiple clouds, but more often than not, it concentrate work on a primary cloud. CIO strategies, they're not generally evenly distributed across clouds. The data shows that this is the case for less than 20% of the respondents, rather organizations are typically going to apply an 80, 20 or a 70, 30 rule for their multi-cloud approach. Meaning they pick a primary cloud on which most work is done, and then they use alternative clouds as either a hedge or maybe for specific workloads or maybe even data protection purposes. Now, if you think about it, optimizing on a primary cloud allows organizations to simplify their security and governance and consolidate their skills. At this point in the cloud evolution, it seems CIOs feel there's more value that is going to come from leveraging the cloud to change their operating models, and maybe broadly spreading the wealth to reduce risk or maybe cut costs, or maybe even to tap specialized capabilities. What's more in thinking about AWS and Microsoft respectively. Each can make a very strong case from MANO cloud. AWS has more features than any other cloud, and as such can handle most workloads. Microsoft can make a similar argument for its customers that have an affinity and a largest state of Microsoft software. The key for multi-cloud in our view will be the degree to which technology vendors can abstract the underlying cloud complexity and create a layer that floats above the clouds and adds incremental value. Snowflakes data cloud is one of the best examples of this, and we've covered that pretty extensively. Now, clearly VMware and Red Hat have aspirations at the infrastructure layer in a similar fashion. Pure storage, and NetApp are a couple of the largest storage players with similar visions. And then Qumulo and Clumio are two other examples with promising technologies, but they have a much smaller install base. Take a look at Cisco, Dell, IBM and HPE. They have a lot to gain and a lot to lose in this cloud game. So multi-cloud is an imperative for these leaders, but for them it's much more complicated because of the complexity and vastness of their portfolios. And notably Dell has VMware and IBM of course has Red Hat, which are key assets that can be leveraged for this multi-cloud game. HPE has a channel and a large install base, but all of these firms, they have to spread R&D much more thinly than some of these other companies that we mentioned for example. The bottom line is that multi-cloud has to be more than just plugging into an operating well on any of the clouds. It require... Which is by the way, this is mostly where we are today. It requires an incremental value proposition that solves a clear problem, and at the same time runs efficiently, meaning it takes advantage of cloud native services at scale. What sectors are showing momentum heading into 2021? And who are some of the names that are looking strong? We've reported a lot that cloud containers and container orchestration, machine intelligence and automation are by far the hottest sectors, the biggest areas of investment with the greatest spending momentum. Now we measure this in ETR parlance, remember by net score. But here's the good news, almost every other sector in the ETR taxonomy with the notable exception of IT outsourcing and IT consulting is showing positive spending momentum relative to previous surveys this year. Yeah, maybe not, it's not a shock, but it appears that the tech spending recovery will be broad-based. It's also worth noting that there are several vendors that stand out and we show a number of them here. CrowdStrike, Microsoft has had consistent performance in the dataset throughout this year. Okta, we called out those guys last year and they've clearly performed as you can see in their earnings reports. Pure storage, interestingly, big acceleration and a turnaround from last quarter in the dataset, and of course, snowflake has been off the charts as we reported many times. These guys are all seeing highly accelerated momentum. UiPath just announced its intent to IPO, AWS, Google, Zscaler, SailPoint, ServiceNow, and Elastic, these all continue to trend up. And so, there are some real positives that we're looking for a member of the ETR surveys, they're forward-looking. So we'll see, as we catch up next quarter. Now, before we wrap, I want to say a few words on security, and maybe it's a bit of a non-sequitur here, but I think it's relevant to the trends that we've been discussing, especially as we talk about moving to the cloud. And as you know, we've reported many times on the security space, basically updating you quarterly with our scenarios and the spending and the technology trends and highlighting our four-star companies. Four-star company's insecurity on those with both momentum and significant market presence. And last year we put CrowdStrike, Okta and Zscaler, and some others on the radar. And we've closely track the cyber business of larger companies with a security portfolio like Palo Alto and Cisco, and more recently, VMware has made some acquisitions. Now the government hacked that became news this week. It really underscores the importance of security. It remains the most challenging area for organizations because well, failure's not an option, skills are short, tools are abundant, the adversaries are very well-funded and extremely capable yet failure is common as we saw this week. And there's a misconception that cloud solves the security problem, and it's important to point out that it does not. Cloud is a shared responsibility model, meaning the cloud provider is going to secure the infrastructure for example, but it's up to you as the customer to configure things properly and deal with application security. It's ultimately on you. And the example of S3 is instructive because we've seen a number S3 breaches over the years where the customer didn't properly configure the S3 bucket. We're talking about companies like Honda and Capital One, not just small businesses that don't have the SecOps resources. And generally it was because a non-security person was configuring things. Maybe they were Or developers who are not focused on security, and perhaps permission set too broadly, and access was given to far too many people. Whatever the issue, it took some breaches and subsequent education to increase awareness of this problem and tighten it up. We see some similar trends occurring with new workloads, especially in cloud databases. It's becoming so easy to spin up new data warehouses for example, and we believe that there are exposures out there due the lack of awareness or inconsistent corporate governance being applied to these new data stores. As well, even though important areas like threat intelligence and database security are important, SecOps budgets are stretched thin. And when you ask companies where the priorities are, these fall lower down the list, these areas specifically have taken a back seat, the endpoint, identity and cloud security. And we bring this up because it's a potential blind spot as we saw this week with the US government hack. It was stealthy, it wasn't detected for many, many months. Who knows maybe even years. And not to be a buzzkill, but the point is, cloud enthusiasm has to be concompetent with security vigilant. Enough preaching, let's wrap up here. As we enter 2020, this year, we said the cloud was going to be the force that drove innovation along with data and AI. And as we look in the rear view mirror and put 2020 behind us, I know many of you want to do that, it was the cloud that enabled businesses to not only continue to operate, but to actually increase productivity. Nonetheless, we still see IT spending declines of four to 5% this year with an expectation of a tepid Q4 relative to the last year. We see Q1 slowly rebounding and kind of a swoosh, let me try that again, recovery in the subsequent quarters with tech spending rebounding in 2021 to a positive three to 5%, let's call it 4%. Now supporting us scenario, the pandemic forced a giant Petri dish for digital. And we see some real successes and learnings that organizations will apply in 2021 to bet on sure things. These are cloud, containers, AI, ML, machine intelligence pieces and automation. For sure, along with upticks for virtually every other sector of technology because spending has been so depressed. The two exceptions are outsourcing and IT consulting and related services which continue to be a drag on overall spending. Priorities must be focused on security and governance and further improvements in applying corporate edicts in a cloud world. We also see new data architectures emerging where domain knowledge becomes central to data platforms. We'll be covering this in more detail on top of the work that we've already done in this area. Now, automation is not only an opportunity, it's become a mandate. Yes, RPA, but also broader automation agendas be on point tools. And importantly, we're not talking about paving the cow path here by automating existing processes. Rather we're talking about rethinking processes across the entire organization for a new digital reality where many of these processes are being invented. The work of Erik Brynjolfsson and Andrew McAfee on the second machine age. It was pressured back in 2014 and the conclusions they drew, they're becoming increasingly important in the 2020s, meaning that look machines have always replaced humans throughout time. But for the first time in history, it's happening for cognitive functions, and a huge base of workers is going to be, or as being marginalized, unless they're retrained. Education and public policy that supports this transition is critical. And I for one would like to see a much more productive discussion that goes beyond the cult of break up big tech. Rather I'd like to see governments partner with big tech to truly do good and help drive the re-skilling of workers for the digital age. Now cloud remains the underpinning of the digital business mandate, but the path forward isn't really always crystal clear. This is evidenced by the virtual dead heat between those organizations that are consolidating workloads in a cloud workloads versus those that are hedging bets on a multi-cloud strategy. One thing is clear cloud is the linchpin for our growth scenarios and will continue to be the substrate for innovation in the coming decade. Remember, these episodes, they're all available as podcasts, wherever you listen, all you got to do is search Breaking Analysis podcast, and please subscribe to the series, appreciate that. Check out ETR's website at ETR.plus. We also publish full report every week on wikibond.com and siliconangle.com and get in touch with me at David.vallante, siliconangle.Com, you can DM me at D. Vellante. And please by all means comment on our LinkedIn posts. This is Dave Vellante for theCube Insights powered by ETR. Have a great week everybody, Merry Christmas, happy Hanukkah, happy Kwanzaa, or happy, whatever holiday you celebrate. Stay safe, be well, and we'll see you next time. (upbeat music)

>>From around the globe. It's the cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS, and our community partners. >>Hi, everyone. Welcome back to the cubes. Live coverage of AWS reinvent 2020 I'm John Farrow, your hosts. We've got the cube virtual. We're not there in person with remote this year, and we're excited to cover three weeks of wall-to-wall coverage. It's virtual events, so they don't over three weeks. We're in week three, day two. Um, and if you're watching this live on the platform tomorrow, Thursday at two o'clock Andy Jassy, we'll be live here on the cube with one-on-one with me to address all the hard questions, but here we're doing a day two of week three analysis with Jeremy Burton industry legend entrepreneur. Now the CEO of observe Inc, um, formerly the CMO of Dell technologies before that EMC has done a variety of ventures, seeing many ways of innovation, friend of the cube. Jeremy, thank you for coming on. >>Yeah, my pleasure. Great. Always great to be on the cube. >>Uh, great to have you on in particularly because, um, yesterday Verner, Vogel's talked a lot about observability and I noticed you got your observed shirt on, uh, observe Inc is your company's name, which is one of the many, uh, hot startups around observability, where you're making a business out of basically what he talked about yesterday. Um, and today's keynote. You had the extended cloud, uh, edge applications. You had bill Vass who leads up both edge and quantum. And then you had Rudy Valdez who, who talked a lot about, uh, evolution of cloud architecture. And of course you finally had, um, David Richardson, who is the VP of serverless. So you got edge. Quantum serverless architecture speaks to the sea change, Jeremy, and you have a good read on these big waves. When you look at serverless and then quantum, you look at, uh, edge, which is data, and you look at, um, all this coming together and on their architecture, Verner's keynote yesterday kind of makes sense. It's a systems architecture and this new observability trend, isn't like a point product. It's a broader concepts. You have a complete rethinking of distributed computing in the cloud. This is kinda what this Amazon feels like. What's your, what's your take? >>Yeah, it's a, it's a good observation. You know, the, the, the, the sort of punchline is, is that people are building applications differently. Um, so the, the, the, the, the technologies that people are using to build apps are different, um, the way in which they build applications is different. Um, the way folks released codes into production is different, and it stands to reason. Therefore, you're going to need a different approach, uh, when you want to troubleshoot these applications. So, uh, when you find, uh, you know, w w what is show when you want to find out what issues customers are having? So what, what we fell a couple of three years ago when we started to observe was that, um, uh, a new approach was required, what you're going to need to monitor your application. And, you know, 2020 is not the same as what you needed in 2015 or 2010. >>And we felt very strongly that this new wave was, was going to be called observability. It, it brings a tear to my eye to hear a Verner, talk about it, because as much as we observe, you know, believe that we can do big things in future. It's the big vendors today that can move markets. And so the Amazon and vulnerable particular talk about observability, I think it lends more credence to the topic. Um, we think that organizations should have observability teams. We think there should be a head of observability. And again, you know, Amazon and Dawson this, uh, I think means that there's a much stronger chance that that's going to happen. And they're going to start, start to shine a light on, I think, a topic that almost everybody needs to pay attention to as they build their next generation of applications. >>When you guys, I know you guys are launched and you have couple of campaign customers now and growing rapidly, um, well-funded, um, uh, get some great investors have found that the investors of snowflake also, um, invested in you guys. So they see this cloud trend LC snowflake when public, and I know you're on the board of snowflake as well. So, uh, you, you, you know, a little bit about what's going on with Amazon and the opportunity when you look at observability, okay, you're building a business around it. And again, you think about head of observability. That's not like a small thing when you make, put someone in charge of something. So why do you say that? I mean, what, I mean, you know, some would say, you know, Hey, it's a feature, not a company. I mean, this is two mindsets that are different. How do you address that? >>Yeah, the, the, the, the thing I'd say is, look, the number one job in America is, um, is a software engineer is writing code. The number two job is fixing it. And so, you know, th th the job think about that for a second. The job of fixing our applications is almost as big as the job of creating our applications. Uh, something has to change, right? I know the job of fixing cars is not as big as the auto industry. Why, because over time that industry has matured and there are better tools to diagnose cars. Uh, and so they're, they, they become easy to fix over time. We've, we've not made that leap with our applications. Um, the tools that the engineering team use to debug and troubleshoot their application are often still very different to what the dev ops team is using, um, which is very different to what maybe the SRE team is using. >>And so it's a huge problem in our industry. Um, really not being able to diagnose troubleshoot issues when they arise. It, it costs the industry, a fortune, it costs, you know, sort of in indirect wasted productivity of development teams, but it also costs in terms of customer experience. Um, I mean, you know, you and I both know is, look, if we're, if we're having a bad experience with maybe a new service that we're trying out online, w w we're probably going to go somewhere else. And so the there's never been like a more important time for people to invest in observing the entire environment, the entire customer experience, not only will you have happier customers, you might actually reduce the costs and improve the productivity in your engineering team as well. So I feel like the opportunity there is, is, is, is, is vast. Um, I also think longer term, um, it doesn't just apply to troubleshooting distributed applications. >>Um, I think the security systems are very related to the way we build software. Um, I mean, I think in, in, in the news in recent days, we've, we've come attuned, uh, uh, to, to software defects, um, or malware in software causing breaches and government agencies. Um, Hey, that, that could be anybody's software right there. Yeah. And so security has got a role to play in observability and the customer experience. It doesn't stop when they have a bad experience on the website. What if they complain? You know, what if a help desk ticket get, how do you track that? >>Yeah, I'm going to, I have a lot of questions for chassis tomorrow. One of them I'm going to ask him, and I want to get your thoughts on it. Cause you brought that up. And I think it's a key point, you know, building applications and supporting them and fixing them. It kind of reminds me of the old adage of, um, you know, you know, you gotta run it running the operation, 70% of the budget using to running it. If you look at what's happening and if you talk to customers and this is what I'm going to ask chassis tomorrow, Verner actually talked about, I on day two operations in his keynote. Yeah. I mean, this is Amazon they're, they're targeting builders. And so I talked to, um, a few other entrepreneurs, um, who were growing companies and some CIA CIOs and CEOs and the basic enterprises. >>They don't want to be building things like they, that's not their DNA. They don't build things like, that's not what they do. I mean, first of all, I love the builder mentality and with Amazon. Um, but they might be at a time where there might not be enough builders, Jeremy right out there. So you've got skill shortages and then ultimately are enterprises really builders. Yeah. They'll build something, but then they just run it it's. So, so at what point do they stop building or they build their own thing in the cloud and then they got to run it. So I think Amazon is going to shift quickly to day two operations, get bill, bill, bill run, run, run. >>Yeah. That's a great topic of conversation. I think what you sort of poking out is, is sort of the maturation of this digital age in the state that we're at. Um, I mean, if you, if you go back, you, you know, to, you know, 10, 10, 20 years, um, I mean, look at the mid nineties, um, there were a lot of people building custom applications, right? I mean, you know, it was innovation, it was all about building custom apps. And I think that golden era of application development whack that now, um, and, and customers in order to get competitive advantage, they are building their own applications. When you talk about digital transformation, what does that mean? Well, it means, you know, often a traditional company building a new digital experience for services that they've potentially offered in a physical way, uh, in the past. So make no mistake, P people are builders or they are writing code, they are becoming digital. >>I think what you'll find at some point as the industry's mature, some of these digital experience is become packaged. And so you can buy those off the shelf. And so there's less building required. But I think as we sit today, um, that there's probably more code been written in anger by more organizations that at any point in the last 30 years. And, and I think this is another reason why observability is so important, um, as you're building that code and as you're developing that customer experience, you want to be able to understand, um, where the issues are and, and, um, uh, like along the way, you don't want to wait until there's a, a big customer disaster on the day of you roll that, something to production before you start investigate. And you want to do that as you go. >>Yeah. And I think that's a kill. I do agree with you, by the way. I think the, there is a builder mentality, but it's probably right. But remember those days back in it, if you want to put our, our time machine hat on and go through the time machine is, you know, that was during the mainframe client server transition. And it was called spaghetti code. You know, it's like the monoliths were built and then it had to be supported and that became legacy. So I kind of see that happening today, where, um, people are moving to the cloud, they are building, but at some point you got to build your thing in the cloud. If I'm a company. And again, this isn't some dots trying to connect in real time. I got serverless, which is totally cool. I'm gonna have quantum has headroom for compute. >>I'm going to have, um, kind of a S a SOA service oriented architecture with web services, with observability. I'm gonna have all these modern apps great that, or run them. And I'm now I'm gonna shift them. Multiple clouds is so, you know, maybe the private cloud waves coming back, you're seeing telco clouds. You start to see these new tier. I won't say tier two clouds, but I mean, people will build their own cloud environment. There's no doubt as going to the cloud. And Steve Malania, Aviatrix kind of made this point yesterday in his analysis where he's like, he thinks private cloud will be back. I was just, it'll just be public cloud. People will build their own clouds and run them. >>Yeah. I feel well, what happens over time is, is the, the sort of line above which you would add value rises. So I kind of feel like, look, cloud is just going to the infrastructure. We can debate, you know, private cloud, public cloud. Is it a public cloud, or is it a private cloud served up by a public cloud provider? My view is, is look, all of that is, is, um, just going to be commodity, right? Um, it's going to be served up for an ever decreasing cost. And so then it's incumbent on organizations to innovate above that line. And, you know, 20 years ago, you know, we, we built our own data centers. Um, and now increasingly that, that seeming like a crazy idea. Um, and you know, now you can get almost all of your infrastructure from the cloud. The great thing is, I mean, look at observe. >>We have no people running data center operations, none, right? We have no people building a database, non, you know, we use snowflake in the cloud. It runs on AWS. We have, we have one dev ops, uh, engineer. And so all the people in the company right now, we're focused on adding value, helping people understand and analyze data, uh, above that line. And we just pay for a service level and, and look, uh, as time goes by, there's going to be more and more services and that line's going to rise. And so, you know, what, what I care about and what I think a lot of CEOs care about is are most of my resources innovating above that sort of value creation line, um, because that's what people are going to pay for in our business. And I think that's, what's going to represent you, you know, sort of value add for you, you know, organizations big and small. >>Yeah. That's a good point. I want to shift to the next topic and then we'll get into some observability questions I have for you and update on your company. Um, complexity has been a big theme. That's come out of all the conversations with analysts that have come on the cube, as you hear it with Amazon, a lot of undifferentiated, heavy lifting, being extracted away to your point about value layers and competing on value. Amazon continues to do that all great stuff, but some are saying, and we had said on the cube, yes, two days ago you put them complexity behind the curtain. It's still complexity, right? So, so complexity with the edge is highlighted. Uh, even though they got green, uh, I, um, edge core Greengrass, which has core thing, IOT core, a lot of cool things happening, but it's still not yet super easy. So complexity tends to slow things down became striction, what's your view on this? Because taming, the complexity seems to be a post COVID pandemic mandate for cloud journeys. What's your thing. >>Yeah, I totally agree. I think, I think in certainly you look organizations that have been in existence, but you know, 30, 40 years, or maybe even 10 years look at there's an amount of technical debt and complexity that you build up over time. Um, but even newer companies, um, the way that people are building modern distributed applications and in some respects is, is more complex than in days gone by, you know, microservices. Um, some of which maybe you own some of which maybe you don't, and what you've gotta be able to do is, is see the big picture, you know, w w when, when there's something in my code, but then when am I making a call out to maybe a third party microservice and, and that microservices bailing out on me, like people have got to see the big picture. And I think what hasn't been available as people have changed the architecture and their applications, there hasn't been an equivalent set of innovation or evolution in the tools that they use to manage that environment. And so you, you, you, you've got this sort of dichotomy of, uh, a better way for software developers to write code and deploy it into production microservices. But at the same time, you don't have good information and good tools to make sense of that complexity. >>That's great stuff. Jeremy Burton is here. He's the CEO of observe Inc cube, alumni, VIP cube alumni, by the way, has been on the cube every year, since the Q has been around 2010, when he took the new job as the CMO of EMC prior to being bought by Dell, Jeremy, you're a legend in the industry, certainly on as an executive and a marketer. And as an entrepreneur, um, I gotta ask you observe Inc, your company now, um, you're right in the middle of all this, you, you got a big bet going on. Could you share, in your opinion, your words, what is the big bet that you're making with observing? Uh, what are you betting on? How do you see the preferred future unfolding and where are you guys going to capture that value? >>Yes, I I'll big bat. Hey, uh, really is to take a new approach, um, in, in, in, in terms of enabling people to observe their systems, that the term observability actually goes back, uh, to a guy in control systems theory in the sixties. And then it's got quite a simple definition, which is, you know, being able to determine the, uh, I've been able to diagnose a system by the telemetry data that it emits. So let's look at the external outputs. And then based on that, can I determine the internal state of the application? And so from the get-go, we felt like observability was not about building another tool, right? We're not, you know, it's not about building another monitoring tool, a logging tool. Um, it's about analyzing data. And I, I was struck many years ago. Uh, I spent a bit of time with, with Andy McAfee, uh, from the sea sail lab at MIT. >>And he made a statement that I thought at the time was quite profound, which he said, look, everything's a matter of data. If you have enough data, you can solve any problem. And that stuck with me for a long time. And, um, you know, observe really what we do is we ingest vast quantities of telemetry data. We treat everything as events and we try and make sense of it. And the economics of the infrastructure now is such, that is you truly can ingest all the Alltel telemetry data and it's affordable, right? I mean, one of the wonderful things that Amazon has done is they've brought you, you know, very cheap, affordable storage. You can ingest all your data and keep it forever. Um, but, but now can you make sense of it? Well, you know, compute is pretty cheap these days and you've got amazing processing engines like snowflake. >>And so I was sense was that if we could allow folks to ingest all of this telemetry data process, that data and help people easily analyze that data, then they could find almost any problem that existed, uh, in their applications or in their infrastructure. So we really set out to create a data company, which I think is fundamentally different to, to really what everybody else is doing. And today we're troubleshooting distributed applications, but I think in future, we, my hope is that we can, we can help people analyze almost anything around their applications or infrastructure. >>And what's the use case problem statement that you're entering the market on? Is it just making sure microservices can be deployed as a Kubernetes? Is it managing containers? Is there a specific, um, customer adoption use case that you're focused on right now? >>Yeah, we've tried to target our ideal customer if you like has been the three or 4,000, uh, uh, SAS companies. Uh, we're, we're really focused on the U S right now, but three to 5,000 SAS companies, um, predominantly, uh, obviously running on AWS often, uh, Kubernetes infrastructure, but, you know, people who, uh, having a hard time, uh, understanding the complexity of the application that they've created, and they're having a hard time understanding, uh, the experience that their customers are having and tracking that back to root cause. So, you know, really helping those SAS companies troubleshoot their applications and having a better customer experience that's where the early customers are. And if we can do a good job in that area, I think we can, you know, over time, you know, start to take on some of the bigger companies and maybe some of the more established companies that are moving in this, this digital direction. >>Jeremy, thanks for sharing that. And I got one last set of questions for you around the industry, but before I get there, give a quick plug for observe. What are you guys looking to do hire, I mean, give a quick, uh, a PSA on what's going on with observed. >>Yeah, so we're, uh, the company is now what a rough and tough. About three years old, we got about 40 people. Uh we're well-funded by sort of Hill ventures. Uh, they were the original investors in, in snowflake. Um, and, um, yeah, I mean, we we've, we've well, more than doubled in size since the COVID lockdown began. We had about 15 people when that began. We've got almost 40 now. Um, and I would anticipate in the next year we're, we're probably going to double in size again, but, um, yeah, really the core focus in the company is, is understanding and analyzing vast quantities of data. And so anybody who is interested in, uh, that space look us up >>Mainly any areas, obviously engineering and the other areas okay. >>Near in all over. I mean, we, you know, w w w as you'll see, if you go to observing.com, we've got a pretty slick front end. Uh, we invested very early on in design and UX design. So we believe that you are, can be a differentiator. So we've got some amazing engineers on the front end. Uh, so going to can always do with the help there, but obviously, um, you know, there's a data processing platform here as well. Um, we, uh, we do run on top of snowflake. We, we do have a number of folks here who are very familiar, uh, you know, with the snowflake database and, and how to write efficiency equals. So, so front and backend. Um, we very soon, I think we'll be starting to expand the sales team. Um, we're really starting to get our initial set of customers and the feedback loop rule in rolling into engineering. And my hope would be, you know, probably early part of next year, we re we really start to nail the product market fit. Um, and we've got a huge release coming in the early part of next year where that the metrics and alerting functionality will be in the product. So, yeah, it's, it's sort of all systems go right now. >>Congratulations. Love to see the entrepreneurial journey. We'll keep an eye out for you and you're in a hot space. So we'll be riding, you'll be riding that wave, uh, question for you on the, um, just kind of the industry, uh, you're in the heart of Silicon Valley. Like I am honestly, I'm fellow Alto, you're up in the Hillsborough area. Um, I think you're in Hillsborough, right? That's where you, where you live. Um, San Francisco, the Valley, the pandemic pretty hard hit right now. People are sheltering in place, but still a lot of activity. Um, what are you hearing in, um, in, in the VC circles, startup circles, as everyone looks at coming out of the pandemic and you look at Amazon and you look at what snowflake has done. I mean, snowflake was built on top of Amazon competing against Redshift. Um, okay. They were hugely successful at doing that. So there's kind of this new playbook emerging. What are, what are people talking about? What's the scuttlebutt. >>Yeah. I mean, clearly TAC has done very well throughout what has been, you know, like just a terrible environment. Um, I think both kind of socially and economically, and I think what's going on in the stock market right now is probably not reflective of the, of the economic situation. And I think a lot of the indices are dominated by tech companies. So you, if you're not careful, you can get a little bit of a false read. Um, but look, what is undisputed is, is that the world is going to become more digital, more tech centric than, than less. Um, so I think there is a very, very bright future, you know, for tech, um, that there is certainly plenty of VC money, um, available. Um, you know, that is not really changed materially in the last year. Um, so if you have a good idea, if you're on one of these major trends, I think that there is a very good chance that you can get the company funded. >>Um, and you know, our, our expectation is that, you know, next year, obviously industries are going to return to work that have been dominant maybe for the last six, nine months. And so some parts of the economy should pick up again, but I would also tell you, I think certain, uh, sort of habits are not going to die. I mean, I think more things are going to be done online and we've gotten used to that way of working and, and you know, what, not, some of it is measurable. I don't know about cocktails over zoom, but working with customers, um, in some respects is easier because they're not traveling, we're not traveling. So we both have more time. Uh, it's sometimes easy to get meetings with people that you would never get. Now. Now, can you do an efficient sales process, education proof of concept? You know, those processes maybe have to grow up a little bit to be taken online, but I think the certain parts of the last, maybe six to nine months that we don't want to throw away and go back to the way we were doing it, because I think, you know, maybe this way of doing it is, is more efficient. >>What do you think about the, uh, entrepreneurial journeys out there? Obviously, um, Amazon we're here covering re-invent is really kind of, you know, building a massive compute engine. They've got higher level services and, you know, I've been speculating for years. I think snowflake is the first kind of big sign. That points to kind of what I said five years ago, which is there's going to be an opportunity for these other clouds as specialty clouds. I called them might be the wrong word, but snowflake basically built on top of Amazon, you know, most valuable company ever on wall street, uh, IPO on someone else's cloud. So is that a playbook? I mean, is that a move? I mean, this is kind of like a new thing. >>Yeah. I mean, that's, I mean, I, I feel like on databases, I've got a lot of history on management, Oracle almost 10 years. And you know, what snowflake does they did was they, they rearchitected the database explicitly for the cloud. I mean, you can run Oracle on the cloud, but, but it, but it doesn't do things the way that snowflake does it. Right. I mean, snowflake uses commodity storage. It uses S3 it's elastic. And so when you're not using it, you're not paying it. And these things sound very simple and very obvious now, which is I think what, what, what the genius of the founders, you know, Ben Warren and Tre, uh, work, and, and I think there will be other costs, you know, categories of infrastructure that will get rearchitected and reinvented for the cloud. And, you know, I've got equally big opportunities. Um, and so, yeah, I mean, I think the model, I believe firmly that the model is if you're a startup, you don't need to waste a lot of time, like reinventing the wheel on data center, infrastructure and databases, and a lot of the services that you would use to construct an application. >>You, you, you can start, you know, if, if the building that you're trying to build is like 12 floors, you can start at the eighth or ninth floor. Um, you know, I've, I've got like what three or 400 quality engineers at snowflake that are building our database. I don't, I don't need to do that. I can just piggyback on top of what they've done and add value. And, you know, the, the, the beautiful thing, you know, now, if you're a business out there thinking of, of, of, of becoming digital and reinventing yourself, or you're a startup just getting going, there's a lot of stuff you just don't have to build anymore. You just don't even have to think about it. >>Yeah. This is the new program of bull internet. It's internet, truly 2.0 or 3.0, whatever 4.0, a complete reset of online. And I think the pandemic, as you pointed out on many cube interviews and Andy Jassy send his keynote is on full display right now. And I think the smart money and smart entrepreneurs are going to see the opportunities. Okay. >>Yeah. It comes back to ideas and a great, I mean, I've always been a product person. Um, but look at great idea, a great product idea and a great product idea that, that capitalizes on the big trends in the industry. I think there's always going to be funding for those kinds of things. I don't know a lot about the consumer world I've always worked in, in B2B, but, um, you know, the kind of things that you're going to be able to do in future. I mean, think about it. If storage is essentially free and compute is essentially free. Just imagine what you could do, right. Jeremy, >>This is the new consumer. Get out. Let's understand that. Finally, B2B is the new consumer enterprise is hot. I was, again, it was riffing on this all week. All the things going on in enterprise is complex is now the new consumers now all connected. It's all one thing. The consumerization of it, the condition of computing has happened. It's going on. So you're a leader. Thank you for coming on. Great to see you as always, um, say hi to your family and stay safe. >>Yeah, you too. Thanks for the invite. Always, always a pleasure. >>Jeremy Burton breaking down the analysis of day two of week three of re-invent coverage. I'm John furry with the cube virtual. We're not in person anymore. Virtualization has allowed us to do more interviews over 110 interviews so far for re-invent and tomorrow, Thursday at two o'clock, Andy Jassy will spend 30 minutes with me here on the cube, looking back at re-invent the highs, the lows, and what's next for Amazon web services. I'm chef Aria. Thanks for watching.

>>From around the globe. It's the queue with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >>Welcome back to the cubes. Live coverage for ADFS reinvent 2020 I'm John Ford with the cube, your host. We are the cube virtual. We're not there in person this year. We're remote with the pandemic and we're here for the keynote analysis for Verner Vogels, and we've got some great analysts on and friends of the cube cube alumni is Rob Hirschfeld is the founder and CEO of Rakin a pioneer in the dev ops space, as well as early on on the bare metal, getting on the whole on-premise he's seen the vision and I can tell you, I've talked to him many times over the years. He's been on the same track. He's on the right wave frog. Great to have you on. I'm going to have to start Veatch, come on. Y'all come on as well, but great to see you. Thanks, pleasure to be here. Um, so the keynote with Verna was, you know, he's like takes you on a journey, you know, and, and virtual is actually a little bit different vibe, but I thought he did an exceptional job of stage layout and some of the virtual stage craft. Um, but what I really enjoyed the most was really this next level, thinking around systems thinking, right, which is my favorite topic, because, you know, we've been saying, going back 10 years, the cloud is just, here's a computer, right. It's operating system. And so, um, this is the big thing. This is, what's your reaction to the keynote. >>Wow. So I think you're right. This is one of the challenges with what Amazon has been building is it's, you know, it is a lock box, it's a service. So you don't, you don't get to see behind the scenes. You don't really get to know how they run these services. And what, what I see happening out of all of those pieces is they've really come back and said, we need to help people operate this platform. And, and that shouldn't be surprising to anyone. Right? Last couple of years, they've been rolling out service, service service, all these new things. This talk was really different for Verner's con normal ones, because he wasn't talking about whizzbang new technologies. Um, he was really talking about operations, um, you know, died in the wool. How do we make the system easier to use? How do we expose things? What assistance can we have in, in building applications? Uh, in some cases it felt like, uh, an application performance monitoring or management APM talk from five or even 10 years ago, um, canaries, um, you know, Canary deployments, chaos engineering, observability, uh, sort of bread and butter, operational things. >>We have Savi Joel, who's a influencer cloud computing Xtrordinair dev ops guru. Uh, we don't need dev ops guru from Amazon. We got Sarpy and prop here. So it'd be great to see you. Um, you guys had a watch party. Um, tell me what the reaction was, um, with, of the influencers in the cloud or ADI out there that were looking at Vernon's announcement, because it does attract a tech crowd. What was your take and what was the conversation like? >>Yeah, we kinda geeked out. Um, we had a watch party and we were commenting back and forth, like when we were watching it. I think that the general consensus is that the complexity of AWS stack itself is, is increasing. Right. And they have been focused on developers a lot, I think a lot longer than they needed to be a little bit. I think, uh, now they need to focus on the operations. Like we, we are, we all love dev ops talks and it's very fancy and it's very modern way of building software. But if you think deep down that, like once we developed software traditionally and, and also going forward, I think we need to have that separation. Once you develop something in production, it's, it's, it's operating right. Once you build a car, you're operating car, you're not building car all the time. Right? >>So same with the software. Once you build a system, it should have some stability where you're running it, operating it for, for a while, at least before you touch it or refactoring all that stuff. So I think like building and operating at the same time, it's very good for companies like Amazon, AWS, especially, uh, and, and Google and, and, and Facebook and all those folks who are building technology because they are purely high-tech companies, but not for GM Ford Chrysler or Kaiser Permanente, which is healthcare or a school district. The, they, they need, need to operate that stuff once it's built. So I think, uh, the operationalization of cloud, uh, well, I think take focus going forward a lot more than it has and absorbable Deanna, on a funny note, I said, observability is one of those things. I, now these days, like, like, you know, and the beauty pageants that every contestant say is like, whatever question you asked, is it Dora and the answer and say at the end world peace, right? >>And that's a world peace term, which is the absorbability. Like you can talk about all the tech stuff and all that stuff. And at the end you say observability and you'll be fine. So, um, what I'm making is like observability is, and was very important. And when I was talking today about like how we can enable the building of absorbability into this new paradigm, which is a microservices, like where you pass a service ID, uh, all across all the functions from beginning to the end. Right. And so, so you can trace stuff. So I think he was talking, uh, at that level. Yeah. >>Let me, let's take an observer Billy real quick. I have a couple of other points. I want to get your opinions on. He said, quote, this three, enabling major enabling technologies, powering observability metrics, logging and tracing here. We know that it would, that is of course, but he didn't take a position. If you look at all the startups out there that are sitting there, the next observability, there's at least six that I know of. I mean, that are saying, and then you got ones that are kind of come in. I think signal effects was one. I liked, like I got bought by Splunk and then is observability, um, a feature, um, or is it a company? I mean, this is something that kind of gets talked about, right? I mean, it's, I mean, is it really something you can build a business on or is it a white space? That's a feature that gets pulled in what'd you guys react to that? >>So this is a platform conversation and, and, you know, one of the things that we've been having conversations around recently is this idea of platforms. And, and, you know, I've been doing a lot of work on infrastructure as code and distributed infrastructure and how people want infrastructure to be more code, like, which is very much what, what Verna was, was saying, right? How do we bring development process capabilities into our infrastructure operations? Um, and these are platform challenges. W what you're asking about from, uh, observability is perspective is if I'm running my code in a platform, if I'm running my infrastructure as a platform, I actually need to understand what that platform is doing and how it's making actions. Um, but today we haven't really built the platforms to be very transparent to the users. And observability becomes this necessary component to fix all the platforms that we have, whether they're Kubernetes or AWS, or, you know, even going back to VMware or bare metal, if you can't see what's going on, then you're operating in the blind. And that is an increasingly big problem. As we get more and more sophisticated infrastructure, right? Amazon's outage was based on systems can being very connected together, and we keep connecting systems together. And so we have to be able to diagnose and troubleshoot when those connections break or for using containers or Lambdas. The code that's running is ephemeral. It's only around for short periods of time. And if something's going wrong in it, it's incredibly hard to fix it, >>You know? And, and also he, you know, he reiterated his whole notion of log everything, right? He kept on banging on the drum on that one, like log everything, which is actually a good practice. You got to log everything. Why wouldn't you, >>I mean, how you do, but they don't make it easy. Right? Amazon has not made it easy to cross, cross, and, uh, connect all the data across all of those platforms. Right? People think of Amazon as one thing, but you know, the people who are using it understand it's actually a collection of services. And some of those are not particularly that tied together. So figuring out something that's going on across, across all of your service bundles, and this isn't an Amazon problem, this is an industry challenge. Especially as we go towards microservices, I have to be able to figure out what happened, even if I used 10 services, >>Horizontal, scalability argument. Sorry. Do you want to get your thoughts on this? So the observability, uh, he also mentioned theory kind of couched it before he went into the talk about systems theory. I'm like, okay. Let's, I mean, I love systems, and I think that's going to be the big wake up call here for the next 10 years. That's a systems mindset. And I think, you know, um, Rob's right. It's a platform conversation. When you're thinking about an operating system or a system, it has consequences when things change, but he talked about controllability versus, uh, observability and kinda T that teed up the, well, you can control systems controls, or you can have observability, uh, what's he getting at in all of this? What's he trying to say, keep, you know, is it a cover story? Is it this, is it a feature? What was the, what was the burner getting at with all this? >>Uh, I, I, I believe they, they understand that, that, uh, that all these services are very sort of micro in nature from Amazon itself. Right. And then they are not tied together as Rob said earlier. And they, he addressed that. He, uh, he, uh, announced that service. I don't know the name of that right now of problem ahead that we will gather all the data from all the different places. And then you can take a look at all the data coming from different services at this at one place where you have the service ID passed on to all the servers services. You have to do that. It's a discipline as a software developer, you have to sort of adhere to even in traditional world, like, like, you know, like how you do logging and monitoring and tracing, um, it's, it's your creativity at play, right? >>So that's what software is like, if you can pass on, I was treating what they gave an example of Citrix, uh, when, when, when you are using like tons of applications with George stream to your desktop, through Citrix, they had app ID concept, right? So you can trace what you're using and all that stuff, and you can trace the usage and all that stuff, and they can, they can map that log to that application, to that user. So you need that. So I think he w he was talking about, I think that's what he's getting too. Like we have to, we have to sort of rethink how we write software in this new Microsoft, uh, sort of a paradigm, which I believe it, it's a beautiful thing. Uh, as long as we can manage it, because Microsoft is, are spread across like, um, small and a smaller piece of software is everywhere, right? So the state, how do we keep the state intact? How do we, um, sort of trace things? Uh, it becomes a huge problem if we don't do it right? So it it's, um, it's a little, this is some learning curve for most of the developers out there. So 60 dash 70% >>Rob was bringing this up, get into this whole crash. And what is it kind of breakdown? Because, you know, there's a point where you don't have the Nirvana of true horizontal scalability, where you might have microservices that need to traverse boundaries or systems, boundaries, where, or silos. So to Rob's point earlier, if you don't see it, you can't measure it or you can't get through it. How do you wire services across boundaries? Is that containers, is that, I mean, how does this all work? How do you guys see that working? I just see a train wreck there. >>It's, it's a really hard problem. And I don't think we should underestimate it because everything we toast talked about sounds great. If you're in a single AWS region, we're talking about distributed infrastructure, right? If you think about what we've been seeing, even more generally about, you know, edge sites, uh, colo on prem, you know, in cloud multi-region cloud, all these things are actually taking this one concept and you're like, Oh, I just want to store all the log data. Now, you're not going to store all your log data in one central location anymore. That in itself, as a distributed infrastructure problem, where I have to be able to troubleshoot what's going on, you know, and know that the logs are going to the right place and capture the data, that's really important. Um, and one of the innovations in this that I think is going to impact the industry over the next couple of years is the addition of more artificial intelligence and machine learning, into understanding operations patterns and practices. >>And I think that that's a really significant industry trend where Amazon has a distinct advantage because it's their systems and it's captive. They can analyze and collect a lot of data across very many customers and learn from those things and program systems that learn from those things. Um, and so the way you're going to keep up with this is not by logging more and more data, but by doing exactly what we're talking through, which was how do I analyze the patterns with machine learning so that I can get predictive analysis so that I can understand something that looks wrong and then put people on checking it before it goes wrong. >>All right, I gotta, I gotta bring up something controversial. I can't hold back any longer. Um, you know, Mark Zuckerberg said many, many years ago, all the old people, they can do startups, they're too old and you gotta be young and hungry. You gotta do that stuff. If we're talking systems theory, uh, automated meta reasoning, evolvable systems, resilience, distributed computing, isn't that us old guys that have actually have systems experience. I mean, if you're under the age of 30, you probably don't even know what a system is. Um, and, or co coded to the level of systems that we use to code. And I'm putting my quote old man kind of theory, only kidding, by the way on the 30. But my point is there is a generation of us that had done computer science in the, in the eighties and seventies, late seventies, maybe eighties and nineties, it's all it was, was systems. It was a systems world. Now, when you have a software world, the aperture is increasing in terms of software, are the younger generation of developers system thinkers, or have we lost that art, uh, or is it doesn't matter? What do you guys think? >>I, I think systems thinking comes with age. I mean, that's, that's sort of how I think, I mean, like I take the systems thinking a greater sort of, >>Um, world, like state as a system country, as a system and everything is a system, your body's a system family system, so it's the same way. And then what impacts the system when you operated internal things, which happened within the system and external, right. And we usually don't talk about the economics and geopolitics. There's a lot of the technology. Sometimes we do, like we have, I think we need to talk more about that, the data sovereignty and all that stuff. But, but even within the system, I think the younger people appreciate it less because they don't have the, they don't see, um, software taught like that in the universities. And, and, and, and by these micro micro universities now online trainings and stuff like sweaty, like, okay, you learn this thing and you're good at it saying, no, no, it's not like that. So you've got to understand the basics and how the systems operate. >>Uh, I'll give you an example. So like we were doing the, the, the client server in early nineties, and then gradually we moved more towards like having ESB enterprise services, bus where you pass a state, uh, from one object to another, and we can bring in the heterogeneous, uh, languages. This thing is written in Java. This is in.net. This is in Python. And then you can pass it through that. Uh, you're gonna make a state for, right. And that, that was contained environment. Like ESBs were contained environment. We were, I, I wrote software for ESPs myself at commerce one. And so like, we, what we need today is the ESP equallant in the cloud. We don't have that. >>Rob, is there a reverse ageism developers? I mean, if you're young, you might not have systems. What do you think? I, I don't agree with that. I actually think that the nature of the systems that we're programming forces people into more distributed infrastructure thinking the platforms we have today are much better than they were, you know, 20 years ago, 30 years ago, um, in the sense that I can do distributed infrastructure programming without thinking about it very much anymore, but you know, people know, they know how to use cloud. They know how to use a big platform. They know how to break things into microservices. I, I think that these are inherent skills that people need to think about that you're you're right. There is a challenge in that, you know, you get very used to the platform doing the work for you, and that you need to break through it, but that's an experiential thing, right? >>The more experienced developers are going to have to understand what the platforms do. Just like, you know, we used to have to understand how registers worked inside of a CPU, something I haven't worried about for a long, long time. So I, I don't think it's that big of a problem. Um, from, from that perspective, I do think that the thing that's really hard is collaboration. And so, you know, it's, it's hard people to people it's hard inside of a platform. It's hard when you're an Amazon size and you've been rolling out services all over the place and now have to figure out how to fit them all together. Um, and that to me is, is a design problem. And it's more about being patient and letting things, uh, mature. If anything might take away from this keynote is, you know, everybody asked Amazon to take a breath and work on usability and, and cross cross services synchronizations rather than, than adding more services into the mix. And that's, >>That's a good point. I mean, again, I bring up the conversation because it's kind of the elephant in the room and I make it being controversial to make a point there. So our view, because, you know, I interviewed Judy Estrin who helped found the internet with Vince Cerf. She's well-known for her contributions for the TCP IP protocol. Andy Besta Stein. Who's the, who's the Rembrandt of motherboards. But as Pat Gelsinger, CEO of VMware, I would say both said to me on the cube that without systems thinking, you don't understand consequences of when things change. And we start thinking about this microservices conversation, you start to hear a little bit of that pattern emerging, where those systems, uh, designs matter. And then you have, on the other hand, you have this modern application framework where serverless takes over. So, you know, Rob back to your infrastructure as code, it really isn't an either, or they're not mutually exclusive. You're going to have a set of nerds and geeks engineering systems to make them better and easier and scalable. And then you're going to have application developers that need to just make it work. So you start to see the formation of kind of the, I won't say swim lanes, but I mean, what do you guys think about that? Because you know, Judy and, um, Andy better sign up. They're kind of right. Uh, >>Th th the enemy here, and we're seeing this over and over again is complexity. And, and the challenge has been, and serverless is like, those people like, Oh, I don't have to worry about servers anymore because I'm dealing with serverless, which is not true. What you're doing is you're not worrying about infrastructure as much, but you, the complexity, especially in a serverless infrastructure where you're pulling, you know, events from all sorts of things, and you have one, one action, one piece of code, you know, triggering a whole bunch of other pieces of code in a decoupled way. We are, we are bringing so much complexity into these systems, um, that they're very hard to conceive of. Um, and AIML is not gonna not gonna address that. Um, I think one of the things that was wonderful about the setting, uh, in the sugar factory and at all of that, you know, sort of very mechanical viewpoint, you know, when you're actually connecting all things together, you can see it. A lot of what we've been building today is almost impossible to observe. And so the complexity price that we're paying in infrastructure is going up exponentially and we can't sustain infrastructures like that. We have to start leveling that in, right? >>Your point on the keynote, by the way, great call out on, on the, on the setting. I thought that was very clever. So what do you think about this? Because as enterprises go through this transformation, one of the big conversations is the solution architecture, the architecture of, um, how you lay all this out. It's complexity involved. Now you've got on premise system, you've got cloud, you've got edge, which you're hearing more and more local processing, disconnected systems, managing it at the edge with visualization. We're going to hear more about that, uh, with Dirk, when he comes on the queue, but you know, just in general as a practitioner out there, what, what's, what's your, what do you see people getting their arms around, around this, this keynote? What do they, what's your thoughts? >>Yeah, I, I think, uh, the, the pattern I see emerging is like, or in the whole industry, regardless, like if you put, when does your sign is that like, we will write less and less software in-house I believe that SAS will emerge. Uh, and it has to, I mean, that is the solution to kill the complexity. I believe, like we always talk about software all the time and we, we try to put this in the one band, like it's, everybody's dining, same kind of software, and they have, I'm going to complexity and they have the end years and all that stuff. That's not true. Right. If you are Facebook, you're writing totally different kind of software that needs to scale differently. You needs a lot of cash and all that stuff, right. Gash like this and cash. Well, I ain't both gases, but when you are a mid size enterprise out there in the middle, like fly over America, what, uh, my friend Wayne says, like, we need to think about those people too. >>Like, how do they drive software? What kind of software do they write? Like how many components they have in there? Like they have three tiers of four tiers. So I think they're a little more simpler software for internal use. We have to distinguish these applications. I always talk about this, like the systems of record systems of differentiation, the system of innovation. And I think cloud will do great. And the newer breed of applications, because you're doing a lot of, a lot of experimentation. You're doing a lot of DevOps. You have two pizza teams and all that stuff, which is good stuff we talk about, well, when you go to systems of record, you need stability. You need, you need some things which is operational. You don't want to touch it again, once it's in production. Right? And so the, in between that, that thing is, I think that's, that's where the complexity lies the systems are, which are in between those systems of record and system or innovation, which are very new Greenfield. That, that's what I think that's where we need to focus, uh, our, um, platform development, um, platform as a service development sort of, uh, dollars, if you will, as an industry, I think Amazon is doing that right. And, and Azura is doing that right to a certain extent too. I, I, I, I worry a little bit about, uh, uh, Google because they're more tilted towards the data science, uh, sort of side of things right now. >>Well, Microsoft has the most visibility into kind of the legacy world, but Rob, you're shaking your head there. Um, on his comment, >>You know, I, I, you know, I, I watched the complexity of all these systems and, and, you know, I'm not sure that sass suffocation of everything that we're doing is leading to less is pushing the complexity behind a curtain so that you, you, you can ignore the man behind the curtain. Um, but at the end of the day, you know what we're really driving towards. And I think Amazon is accelerating this. The cloud is accelerating. This is a new set of standard operating processes and procedures based on automation, based on API APIs, based on platforms, uh, that ultimately, I think people could own and could come back to how we want to operate it. When I look at what we w we were just shown with the keynote, you know, it was an, is things that application performance management and monitoring do. It's, it's not really Amazon specific stuff. There's no magic beans that Amazon is growing operational knowledge, you know, in Amazon, greenhouses that only they know how to consume. This is actually pretty block and tackle stuff. Yeah. And most people don't need to operate it at that type of scale to be successful. >>It's a great point. I mean, let's, let's pick up on that for the last couple of minutes we have left. Cause I think that's a great, great double-down because you're thinking about the mantra, Hey, everything is a service, you know, that's great for business model. You know, you hand it over to the techies. They go, wait a minute. What does that actually mean? It's harder. But when I talk to people out there and you hear people talking about everything is a service or sanctification, I do agree. I think you're putting complexity behind the curtain, but it's kind of the depends answer. So if you're going to have everything as a service, the common thesis is it has to have support automation everywhere. You got to automate things to make things sassiphy specified, which means you need five nines, like factory type environments. They're not true factories, but Rob, to your point, if you're going to make something a SAS, it better be Bulletproof. Because if you're, if you're automating something, it better be automated, right? You can measure things all you want, but if it's not automated, like a, like a, >>And you have no idea what's going on behind the curtains with some of these, these things, right. Especially, you know, I know our business and you know, our customers' businesses, they're, they're reliant on more and more services and you have no idea, you know, the persistence that service, if they're going to break an API, if they're going to change things, a lot of the stuff that Amazon is adding here defensively is because they're constantly changing the wheels on the bus. Um, and that is not bad operational practice. You should be resilient to that. You should have processes that are able to be constantly updated and CICB pipelines and, you know, continuous deployments, you shouldn't expect to, to, you know, fossilize your it environment in Amber, and then hope it doesn't have to change for 10 years. But at the same time, we'll work control your house. >>That's angle about better dev ops hypothetical, like a factory, almost metaphor. Do you care if the cars are being shipped down the assembly line and the output works and the output, if you have self-healing and you have these kinds of mechanisms, you know, you could have do care. The services are being terminated and stood up and reformed as long as the factory works. Right? So again, it's a complexity level of how much it, or you want to bite off and chew or make work. So to me, if it's automated, it's simple, did it work or not? And then the cost of work to be, what's your, what's your angle on this? Yeah. >>I believe if you believe in systems thinking, right. You have to believe in, um, um, the concept of, um, um, Oh gosh, I'm losing over minor. Um, abstraction. Right? So abstraction is your friend in software. Abstraction is your friend anyways, right? That's how we, humans pieces actually make a lot more progress than any other sort of living things here in this world. So that's why we are smart. We can abstract complexity behind the curtains, right? We, we can, we can keep improving, like from the, the, you know, wooden cart to the car, to the, to the plane, to the other, like, we, we, we have this, like when, when we see we are flying these airplanes, like 90% of the time they're on autopilot, like that's >>Hi, hiding my attractions is, is about evolution. Evolvable software term. He said, it's true. All right, guys, we have one minute left. Um, let's close this out real quick. Each of you give a closing statement on what you thought of the keynote and Verner's talk prop, we'll start with you. >>Uh, you know, as always, it's a perf keynote, uh, very different this year because it was so operationally focused and using the platform and, and helping people run their, their, off their applications and software better. And I think it's an interesting turn that we've been waiting for for Amazon, uh, to look at, you know, helping people use their own platform more. Um, so, uh, refreshing change and I think really powerful and well delivered. I really did like the setting >>Great shopping. And when we found, I found out today, that's Teresa Carlson is now running training and certification. So I'm expecting that to be highly awesomely accelerated a success there. Sorry, what's your take real quick on burners talk, walk away. Keynote thoughts. >>I, I, I think it was what I expected it to be like, he focused on the more like a software architecture kind of discussion. And he focused this time a little more on the ops side and the dev side, which I think they, they are pivoting a little bit, um, because they, they want to sell more AWS stuff to us, uh, to the existing enterprises. So I think, um, that was, um, good. Uh, I wish at the end, he said, not only like, go, go build, but also go build and operate. So can, you know, they all say, go build, build, build, but like, who's going to operate this stuff. Right. So I think, um, uh, I will see a little shift, I think, going forward, but we were talking earlier, uh, during or watch party that I think, uh, going forward, uh, AWS will open start open sourcing the commoditized version of their cloud, which have been commoditized by other vendors and gradually they will open source it so they can keep the hold onto the enterprises. I think that's what my take is. That's my prediction is >>Awesome and want, I'll make sure I'm at your watch party next time. Sorry. I missed it. Nobody's taking notes. Try and prepare. Sorry, Rob. Thanks for coming on and sharing awesome insight and expertise to experts in cloud and dev ops. I know them. And can firstly vouch for their awesomeness? Thanks for coming on. I think Verner can verify what I thought already was reporting Amazon everywhere. And if you connect the dots, this idea of reasoning, are we going to have smarter cloud? That's the next conversation? I'm John for your host of the cube here, trying to get smarter with Aus coverage. Thanks to Robin. Sarvi becoming on. Thanks for watching.

>>From around the globe. It's the queue with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. >>Hi, this is Dave Volante. Welcome back to the cubes. Continuous coverage of AWS reinvent 2020, the virtual version of the cube and reinvent. I'm here with David foyer. Who's the CTO Wiki Bon, and we're going to break down today's infrastructure keynote, which was headlined by Peter DeSantis. David. Good to see you. Good to see you. So David, we have a very tight timeframe and I just want to cover a couple of things. Something that I've learned for many, many years, working with you is the statement. It's all about recovery. And that really was the first part of Peter's discussion today. It was, he laid out the operational practices of AWS and he talked a lot about, he actually had some really interesting things up there. You know, you use the there's no compression algorithm for experience, but he talked a lot about availability and he compared AWS's availability philosophy with some of its competitors. >>And he talked about generators being concurrent and maintainable. He got, he took it down to the batteries and the ups and the thing that impressed me, most of the other thing that you've taught me over the years is system thinking. You've got to look at the entire system. That one little component could have Peter does emphasis towards a huge blast radius. So what AWS tries to do is, is constrict that blast radius so he can sleep at night. So non-disruptive replacements of things like batteries. He talked a lot about synchronous versus asynchronous trade-offs and it was like, kind of async versus sync one-on-one synchronous. You got latency asynchronous, you got your data loss to exposure. So a lot of discussions around that, but what was most interesting is he CA he compared and contrasted AWS's philosophy on availability zones, uh, with the competition. And he didn't specifically call out Microsoft and Google, but he showed some screenshots of their websites and the competition uses terms like usually available and generally available this meaning that certain regions and availability zone may not be available. That's not the case with AWS, your thoughts on that. >>They have a very impressive track record, uh, despite the, a beta the other day. Um, but they've got a very impressive track record. I, I think there is a big difference, however, between a general purpose computing and, uh, mission critical computing. And when you've got to bring up, uh, databases and everything else like that, then I think there are other platforms, uh, which, uh, which in the longterm, uh, AWS in my view, should be embracing that do a better job in mission critical areas, uh, in terms of bringing things up and not using data and recovery. So that's, that's an area which I think AWS will need to partner with in the past. >>Yeah. So, um, the other area of the keynote that was critical was, um, he spent a lot of time on custom Silicon and you and I have talked about this a lot, of course, AWS and Intel are huge partners. Uh, but, but we know that Intel owns its own fabs, uh, it's competitors, you know, we'll outsource to the other, other manufacturers. So Intel is motivated to put as much function on the real estate as possible to create general purpose processors and, and get as much out of that real estate as they possibly can. So what AWS has been been doing, and they certainly didn't throw Intel under the bus. They were very complimentary and, and friendly, but they also lay it out that they're developing a number of components that are custom Silicon. They talked about the nitro controllers, uh, inferential, which is, you know, specialized chips around, around inference to do things like PI torch, uh, and TensorFlow. >>Uh, they talked about training them, you know, the new training ship for training AI models or ML models. They spent a lot of time on Gravatar, which is 64 bit, like you say, everything's 64 bit these days, but it's the arm processor. And so, you know, they, they didn't specifically mention Moore's law, but they certainly taught, they gave, uh, a microprocessor one Oh one overview, which I really enjoyed. They talked about, they didn't specifically talk about Moore's law, but they talked about the need to put, put on more, more cores, uh, and then running multithreaded apps and the whole new programming models that, that brings out. Um, and, and, and basically laid out the case that these specialized processors that they're developing are more efficient. They talked about all these cores and the overhead that, that those cores bring in the difficulty of keeping those processors, those cores busy. >>Uh, and so they talked about symmetric, uh, uh, a simultaneous multi-threading, uh, and sharing cores, which like, it was like going back to the old days of, of microprocessor development. But the point being that as you add more cores and you have that overhead, you get non-linear, uh, performance improvements. And so, so it defeats the notion of scale out, right? And so what I, what I want to get to is to get your take on this as you've been talking for a long, long time about arm in the data center, and remind me just like object storage. We talked for years about object storage. It never went anywhere until Amazon brought forth simple storage service. And then object storage obviously is, you know, a mainstream mainstream storage. Now I see the same thing happening, happening with, with arm and the data center specifically, of course, alternative processes are taking off, but, but what's your take on all this? You, you listened to the keynote, uh, give us your takeaways. >>Well, let's go back to first principles for a second. Why is this happening? It's happening because of volume, volume, volume, volume is incredibly important, obviously in terms of cost. Um, and if you, if you're, if you look at a volume, uh, arm is, is, was based on the volumes that came from that from the, uh, from the, um, uh, handhelds and all of their, all of the mobile stuff that's been generating. So there's billions of chips being made, uh, on that. >>I can interrupt you for a second, David. So we're showing a slide here, uh, and, and it's, it's, it, it, it relates to volume and somewhat, I mean, we, we talk a lot about the volume that flash for instance gained from the consumer. Uh, and, and, and now we're talking about these emerging workloads. You call them matrix workloads. These are things like AI influencing edge work, and this gray area shows these alternative workloads. And that's really what Amazon is going after. So you show in this chart, you know, basically very small today, 2020, but you show a very large and growing position, uh, by the end of this decade, really eating into traditional, the traditional space. >>That, that that's absolutely correct. And, and that's being led by what's happening in the mobile market. If you look at all of the work that's going on, on your, on your, uh, Apple, uh, Apple iPhone, there's a huge amount of, uh, modern, uh, matrix workloads are going there to help you with your photography and everything like that. And that's going to come into the, uh, into the data center within, within two years. Uh, and that's what, what, uh, AWS is focusing on is capabilities of doing this type of new workload in real time. And, and it's hundreds of times, hundreds of times more processing, uh, to do these workloads and it's gotta be done in real time. >>Yeah. So we have a, we have a chart on that this bar chart that you've, you've produced. Uh, I don't know if you can see the bars here. Um, I can't see them, but, but maybe we can, we can editorialize. So on the left-hand side, you basically have traditional workloads, uh, on blue and you have matrix workloads. What you calling these emerging workloads and red you, so you show performance 0.9, five versus 50, then price performance for traditional 3.6. And it's more than 150 times greater for ARM-based workload. >>Yeah. And that's a analysis of the previous generation of arm. And if you take the new ones, the M one, for example, which has come in to the, uh, to the PC area, um, that's going to be even higher. So the arm is producing hybrid computers, uh, multi, uh, uh, uh, heterogeneous computers with multiple different things inside the computer. And that is making life a lot more efficient. And especially in the inference world, they're using NPUs instead of GPU's, they conferred about four times more NPUs that you can GPU's. And, um, uh, it, it's just a, uh, it's a different world and, uh, arm is ahead because it's done all the work in the volume area, and that's now going to go into PCs and, and it's going to, going to go into the data center. >>Okay, great. Now, yeah, if we could, uh, uh, guys bring up the, uh, the, the other chart that's titled workloads moving to ARM-based servers, this one is just amazing to me, David, you'll see that I, for some reason, the slides aren't translating, so, uh, forget that, forget the slides. So, um, but, but basically you have the revenue coming from arm as to be substantially higher, uh, in the out years, uh, or certainly substantially growing more than the traditional, uh, workload revenue. Now that's going to take a decade, but maybe you could explain, you know, why you see that. >>Yeah, the, the, the, the, the reason is that these matrix workloads, uh, and also, uh, the offload of like nitro is doing it's the offload of the storage and the networking from the, the main CPU's, uh, the dis-aggregation of computing, uh, plus the traditional workloads, which can move, uh, over or are moving over and where AWS, uh, and, and Microsoft and the PC and Apple, and the PC where those leaders are leading us is that they are doing the hard work of making sure that their software, uh, and their API APIs can utilize the capabilities of arm. Uh, so, uh, it's, it's the it, and the advantage that AWS has of course, is that enormous economies of scale, across many, many users. Uh, that's going to take longer to go into the, the enterprise data center much longer, but the, the, uh, Microsoft, Google and AWS, they're going to be leading the charge of this movement, all of arm into the data center. Uh, it was amazing some of the people or what some of the arm customers or the AWS customers were seeing today with much faster performance and much lower price. It was, they were, they were affirming. Uh, and, and the fundamental reason is that arm are two generations of production. They are in at the moment at five nano meters, whereas, um, Intel is still at 10. Uh, so that's a big, big issue that, uh, Intel have to address. Yeah. And so >>You get, you've been getting this core creep, I'll call it, which brings a lot of overhead. And now you're seeing these very efficient, specialized processes in your premises. We're going to see these explode for these new workloads. And in particular, the edge is such an enormous opportunity. I think you've pointed out that you see a big, uh, uh, market for edge, these edge emergent edge workloads kind of start in the data center and then push out to the edge. Andy Jassy says that the edge, uh, or, or we're going to bring AWS to the edge of the data center is just another edge node. I liked that vision, your thoughts. >>Uh, I, I think that is a, a compelling vision. I think things at the edge, you have many different form factors. So, uh, you, you will need an edge and a car for example, which is cheap enough to fit into a car and it's, but it's gotta be a hundred times more processing than it is in the, in the computers, in the car at the moment, that's a big leap and, and for, to get to automated driving, uh, but that's going to happen. Um, and it's going to happen on ARM-based systems and the amount of work that's going to go out to the edge is enormous. And the amount of data that's generated at the edge is enormous. That's not going to come back to the center, that's going to be processed at the edge, and the edge is going to be the center. If you're like of where computing is done. Uh, it doesn't mean to say that you're not going to have a lot of inference work inside the data center, but a lot of, lot of work in terms of data and processing is move, is going to move into the edge over the next decade. >>Yeah, well, many of, uh, AWS is edge offerings today, you know, assume data is going to be sent back. Although of course you see outpost and then smaller versions of outposts. That's a, to me, that's a clue of what's coming. Uh, basically again, bringing AWS to, to, to the edge. I want to also touch on, uh, Amazon's, uh, comments on renewable. Peter has talked a lot about what they're doing to reduce carbon. Uh, one of the interesting things was they're actually reusing their cooling water that they clean and reuse. I think, I think you said three or multiple times, uh, and then they put it back out and they were able to purify it and reuse it. So, so that's a really great sustainable story. There was much more to it. Uh, but I think, you know, companies like Amazon, especially, you know, large companies really have a responsibility. So it's great to see Amazon stepping up. Uh, anyway, we're out of time, David, thanks so much for coming on and sharing your insights really, really appreciate it. Those, by the way, those slides of Wiki bond.com has a lot of David's work on there. Apologize for some of the data not showing through, but, uh, working in real time here. This is Dave Volante for David foyer. Are you watching the cubes that continuous coverage of AWS reinvent 2020, we'll be right back.

>> Announcer: From theCUBE studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is theCUBE conversation. >> Hi everyone, this is Dave Vellante and welcome to this CUBE conversation where we're going to dig in to this, the area of cloud databases. And Gartner just published a series of research in this space. And it's really a growing market, rapidly growing, a lot of new players, obviously the big three cloud players. And with me are three experts in the field, two long time industry analysts. Marc Staimer is the founder, president, and key principal at Dragon Slayer Consulting. And he's joined by David Floyer, the CTO of Wikibon. Gentlemen great to see you. Thanks for coming on theCUBE. >> Good to be here. >> Great to see you too Dave. >> Marc, coming from the great Northwest, I think first time on theCUBE, and so it's really great to have you. So let me set this up, as I said, you know, Gartner published these, you know, three giant tomes. These are, you know, publicly available documents on the web. I know you guys have been through them, you know, several hours of reading. And so, night... (Dave chuckles) Good night time reading. The three documents where they identify critical capabilities for cloud database management systems. And the first one we're going to talk about is, operational use cases. So we're talking about, you know, transaction oriented workloads, ERP financials. The second one was analytical use cases, sort of an emerging space to really try to, you know, the data warehouse space and the like. And, of course, the third is the famous Gartner Magic Quadrant, which we're going to talk about. So, Marc, let me start with you, you've dug into this research just at a high level, you know, what did you take away from it? >> Generally, if you look at all the players in the space they all have some basic good capabilities. What I mean by that is ultimately when you have, a transactional or an analytical database in the cloud, the goal is not to have to manage the database. Now they have different levels of where that goes to as how much you have to manage or what you have to manage. But ultimately, they all manage the basic administrative, or the pedantic tasks that DBAs have to do, the patching, the tuning, the upgrading, all of that is done by the service provider. So that's the number one thing they all aim at, from that point on every database has different capabilities and some will automate a whole bunch more than others, and will have different primary focuses. So it comes down to what you're looking for or what you need. And ultimately what I've learned from end users is what they think they need upfront, is not what they end up needing as they implement. >> David, anything you'd add to that, based on your reading of the Gartner work. >> Yes. It's a thorough piece of work. It's taking on a huge number of different types of uses and size of companies. And I think those are two parameters which really change how companies would look at it. If you're a Fortune 500 or Fortune 2000 type company, you're going to need a broader range of features, and you will need to deal with size and complexity in a much greater sense, and a lot of probably higher levels of availability, and reliability, and recoverability. Again, on the workload side, there are different types of workload and there're... There is as well as having the two transactional and analytic workloads, I think there's an emerging type of workload which is going to be very important for future applications where you want to combine transactional with analytic in real time, in order to automate business processes at a higher level, to make the business processes synchronous as opposed to asynchronous. And that degree of granularity, I think is missed, in a broader view of these companies and what they offer. It's in my view trying in some ways to not compare like with like from a customer point of view. So the very nuance, what you talked about, let's get into it, maybe that'll become clear to the audience. So like I said, these are very detailed research notes. There were several, I'll say analysts cooks in the kitchen, including Henry Cook, whom I don't know, but four other contributing analysts, two of whom are CUBE alum, Don Feinberg, and Merv Adrian, both really, you know, awesome researchers. And Rick Greenwald, along with Adam Ronthal. And these are public documents, you can go on the web and search for these. So I wonder if we could just look at some of the data and bring up... Guys, bring up the slide one here. And so we'll first look at the operational side and they broke it into four use cases. The traditional transaction use cases, the augmented transaction processing, stream/event processing and operational intelligence. And so we're going to show you there's a lot of data here. So what Gartner did is they essentially evaluated critical capabilities, or think of features and functions, and gave them a weighting, or a weighting, and then a rating. It was a weighting and rating methodology. On a s... The rating was on a scale of one to five, and then they weighted the importance of the features based on their assessment, and talking to the many customers they talk to. So you can see here on the first chart, we're showing both the traditional transactions and the augmented transactions and, you know, the thing... The first thing that jumps out at you guys is that, you know, Oracle with Autonomous is off the charts, far ahead of anybody else on this. And actually guys, if you just bring up slide number two, we'll take a look at the stream/event processing and operational intelligence use cases. And you can see, again, you know, Oracle has a big lead. And I don't want to necessarily go through every vendor here, but guys, if you don't mind going back to the first slide 'cause I think this is really, you know, the core of transaction processing. So let's look at this, you've got Oracle, you've got SAP HANA. You know, right there interestingly Amazon Web Services with the Aurora, you know, IBM Db2, which, you know, it goes back to the good old days, you know, down the list. But so, let me again start with Marc. So why is that? I mean, I guess this is no surprise, Oracle still owns the Mission-Critical for the database space. They earned that years ago. One that, you know, over the likes of Db2 and, you know, Informix and Sybase, and, you know, they emerged as number one there. But what do you make of this data Marc? >> If you look at this data in a vacuum, you're looking at specific functionality, I think you need to look at all the slides in total. And the reason I bring that up is because I agree with what David said earlier, in that the use case that's becoming more prevalent is the integration of transaction and analytics. And more importantly, it's not just your traditional data warehouse, but it's AI analytics. It's big data analytics. It's users are finding that they need more than just simple reporting. They need more in-depth analytics so that they can get more actionable insights into their data where they can react in real time. And so if you look at it just as a transaction, that's great. If you're going to just as a data warehouse, that's great, or analytics, that's fine. If you have a very narrow use case, yes. But I think today what we're looking at is... It's not so narrow. It's sort of like, if you bought a streaming device and it only streams Netflix and then you need to get another streaming device 'cause you want to watch Amazon Prime. You're not going to do that, you want one, that does all of it, and that's kind of what's missing from this data. So I agree that the data is good, but I don't think it's looking at it in a total encompassing manner. >> Well, so before we get off the horses on the track 'cause I love to do that. (Dave chuckles) I just kind of let's talk about that. So Marc, you're putting forth the... You guys seem to agree on that premise that the database that can do more than just one thing is of appeal to customers. I suppose that makes, certainly makes sense from a cost standpoint. But, you know, guys feel free to flip back and forth between slides one and two. But you can see SAP HANA, and I'm not sure what cloud that's running on, it's probably running on a combination of clouds, but, you know, scoring very strongly. I thought, you know, Aurora, you know, given AWS says it's one of the fastest growing services in history and they've got it ahead of Db2 just on functionality, which is pretty impressive. I love Google Spanner, you know, love the... What they're trying to accomplish there. You know, you go down to Microsoft is, they're kind of the... They're always good enough a database and that's how they succeed and et cetera, et cetera. But David, it sounds like you agree with Marc. I would say, I would think though, Amazon kind of doesn't agree 'cause they're like a horses for courses. >> I agree. >> Yeah, yeah. >> So I wonder if you could comment on that. >> Well, I want to comment on two vectors. The first vector is that the size of customer and, you know, a mid-sized customer versus a global $2,000 or global 500 customer. For the smaller customer that's the heart of AWS, and they are taking their applications and putting pretty well everything into their cloud, the one cloud, and Aurora is a good choice. But when you start to get to a requirements, as you do in larger companies have very high levels of availability, the functionality is not there. You're not comparing apples and... Apples with apples, it's two very different things. So from a tier one functionality point of view, IBM Db2 and Oracle have far greater capability for recovery and all the features that they've built in over there. >> Because of their... You mean 'cause of the maturity, right? maturity and... >> Because of their... Because of their focus on transaction and recovery, et cetera. >> So SAP though HANA, I mean, that's, you know... (David talks indistinctly) And then... >> Yeah, yeah. >> And then I wanted your comments on that, either of you or both of you. I mean, SAP, I think has a stated goal of basically getting its customers off Oracle that's, you know, there's always this urinary limping >> Yes, yes. >> between the two companies by 2024. Larry has said that ain't going to happen. You know, Amazon, we know still runs on Oracle. It's very hard to migrate Mission-Critical, David, you and I know this well, Marc you as well. So, you know, people often say, well, everybody wants to get off Oracle, it's too expensive, blah, blah, blah. But we talked to a lot of Oracle customers there, they're very happy with the reliability, availability, recoverability feature set. I mean, the core of Oracle seems pretty stable. >> Yes. >> But I wonder if you guys could comment on that, maybe Marc you go first. >> Sure. I've recently done some in-depth comparisons of Oracle and Aurora, and all their other RDS services and Snowflake and Google and a variety of them. And ultimately what surprised me is you made a statement it costs too much. It actually comes in half of Aurora for in most cases. And it comes in less than half of Snowflake in most cases, which surprised me. But no matter how you configure it, ultimately based on a couple of things, each vendor is focused on different aspects of what they do. Let's say Snowflake, for example, they're on the analytical side, they don't do any transaction processing. But... >> Yeah, so if I can... Sorry to interrupt. Guys if you could bring up the next slide that would be great. So that would be slide three, because now we get into the analytical piece Marc that you're talking about that's what Snowflake specialty is. So please carry on. >> Yeah, and what they're focused on is sharing data among customers. So if, for example, you're an automobile manufacturer and you've got a huge supply chain, you can supply... You can share the data without copying the data with any of your suppliers that are on Snowflake. Now, can you do that with the other data warehouses? Yes, you can. But the focal point is for Snowflake, that's where they're aiming it. And whereas let's say the focal point for Oracle is going to be performance. So their performance affects cost 'cause the higher the performance, the less you're paying for the performing part of the payment scale. Because you're paying per second for the CPUs that you're using. Same thing on Snowflake, but the performance is higher, therefore you use less. I mean, there's a whole bunch of things to come into this but at the end of the day what I've found is Oracle tends to be a lot less expensive than the prevailing wisdom. So let's talk value for a second because you said something, that yeah the other databases can do that, what Snowflake is doing there. But my understanding of what Snowflake is doing is they built this global data mesh across multiple clouds. So not only are they compatible with Google or AWS or Azure, but essentially you sign up for Snowflake and then you can share data with anybody else in the Snowflake cloud, that I think is unique. And I know, >> Marc: Yes. >> Redshift, for instance just announced, you know, Redshift data sharing, and I believe it's just within, you know, clusters within a customer, as opposed to across an ecosystem. And I think that's where the network effect is pretty compelling for Snowflake. So independent of costs, you and I can debate about costs and, you know, the tra... The lack of transparency of, because AWS you don't know what the bill is going to be at the end of the month. And that's the same thing with Snowflake, but I find that... And by the way guys, you can flip through slides three and four, because we've got... Let me just take a quick break and you have data warehouse, logical data warehouse. And then the next slide four you got data science, deep learning and operational intelligent use cases. And you can see, you know, Teradata, you know, law... Teradata came up in the mid 1980s and dominated in that space. Oracle does very well there. You can see Snowflake pop-up, SAP with the Data Warehouse, Amazon with Redshift. You know, Google with BigQuery gets a lot of high marks from people. You know, Cloud Data is in there, you know, so you see some of those names. But so Marc and David, to me, that's a different strategy. They're not trying to be just a better data warehouse, easier data warehouse. They're trying to create, Snowflake that is, an incremental opportunity as opposed to necessarily going after, for example, Oracle. David, your thoughts. >> Yeah, I absolutely agree. I mean, ease of use is a primary benefit for Snowflake. It enables you to do stuff very easily. It enables you to take data without ETL, without any of the complexity. It enables you to share a number of resources across many different users and know... And be able to bring in what that particular user wants or part of the company wants. So in terms of where they're focusing, they've got a tremendous ease of use, tremendous focus on what the customer wants. And you pointed out yourself the restrictions there are of doing that both within Oracle and AWS. So yes, they have really focused very, very hard on that. Again, for the future, they are bringing in a lot of additional functions. They're bringing in Python into it, not Python, JSON into the database. They can extend the database itself, whether they go the whole hog and put in transaction as well, that's probably something they may be thinking about but not at the moment. >> Well, but they, you know, they obviously have to have TAM expansion designs because Marc, I mean, you know, if they just get a 100% of the data warehouse market, they're probably at a third of their stock market valuation. So they had better have, you know, a roadmap and plans to extend there. But I want to come back Marc to this notion of, you know, the right tool for the right job, or, you know, best of breed for a specific, the right specific, you know horse for course, versus this kind of notion of all in one, I mean, they're two different ends of the spectrum. You're seeing, you know, Oracle obviously very successful based on these ratings and based on, you know their track record. And Amazon, I think I lost count of the number of data stores (Dave chuckles) with Redshift and Aurora and Dynamo, and, you know, on and on and on. (Marc talks indistinctly) So they clearly want to have that, you know, primitive, you know, different APIs for each access, completely different philosophies it's like Democrats or Republicans. Marc your thoughts as to who ultimately wins in the marketplace. >> Well, it's hard to say who is ultimately going to win, but if I look at Amazon, Amazon is an all-cart type of system. If you need time series, you go with their time series database. If you need a data warehouse, you go with Redshift. If you need transaction, you go with one of the RDS databases. If you need JSON, you go with a different database. Everything is a different, unique database. Moving data between these databases is far from simple. If you need to do a analytics on one database from another, you're going to use other services that cost money. So yeah, each one will do what they say it's going to do but it's going to end up costing you a lot of money when you do any kind of integration. And you're going to add complexity and you're going to have errors. There's all sorts of issues there. So if you need more than one, probably not your best route to go, but if you need just one, it's fine. And if, and on Snowflake, you raise the issue that they're going to have to add transactions, they're going to have to rewrite their database. They have no indexes whatsoever in Snowflake. I mean, part of the simplicity that David talked about is because they had to cut corners, which makes sense. If you're focused on the data warehouse you cut out the indexes, great. You don't need them. But if you're going to do transactions, you kind of need them. So you're going to have to do some more work there. So... >> Well... So, you know, I don't know. I have a different take on that guys. I think that, I'm not sure if Snowflake will add transactions. I think maybe, you know, their hope is that the market that they're creating is big enough. I mean, I have a different view of this in that, I think the data architecture is going to change over the next 10 years. As opposed to having a monolithic system where everything goes through that big data platform, the data warehouse and the data lake. I actually see what Snowflake is trying to do and, you know, I'm sure others will join them, is to put data in the hands of product builders, data product builders or data service builders. I think they're betting that that market is incremental and maybe they don't try to take on... I think it would maybe be a mistake to try to take on Oracle. Oracle is just too strong. I wonder David, if you could comment. So it's interesting to see how strong Gartner rated Oracle in cloud database, 'cause you don't... I mean, okay, Oracle has got OCI, but you know, you think a cloud, you think Google, or Amazon, Microsoft and Google. But if I have a transaction database running on Oracle, very risky to move that, right? And so we've seen that, it's interesting. Amazon's a big customer of Oracle, Salesforce is a big customer of Oracle. You know, Larry is very outspoken about those companies. SAP customers are many, most are using Oracle. I don't, you know, it's not likely that they're going anywhere. My question to you, David, is first of all, why do they want to go to the cloud? And if they do go to the cloud, is it logical that the least risky approach is to stay with Oracle, if you're an Oracle customer, or Db2, if you're an IBM customer, and then move those other workloads that can move whether it's more data warehouse oriented or incremental transaction work that could be done in a Aurora? >> I think the first point, why should Oracle go to the cloud? Why has it gone to the cloud? And if there is a... >> Moreso... Moreso why would customers of Oracle... >> Why would customers want to... >> That's really the question. >> Well, Oracle have got Oracle Cloud@Customer and that is a very powerful way of doing it. Where exactly the same Oracle system is running on premise or in the cloud. You can have it where you want, you can have them joined together. That's unique. That's unique in the marketplace. So that gives them a very special place in large customers that have data in many different places. The second point is that moving data is very expensive. Marc was making that point earlier on. Moving data from one place to another place between two different databases is a very expensive architecture. Having the data in one place where you don't have to move it where you can go directly to it, gives you enormous capabilities for a single database, single database type. And I'm sure that from a transact... From an analytic point of view, that's where Snowflake is going, to a large single database. But where Oracle is going to is where, you combine both the transactional and the other one. And as you say, the cost of migration of databases is incredibly high, especially transaction databases, especially large complex transaction databases. >> So... >> And it takes a long time. So at least a two year... And it took five years for Amazon to actually succeed in getting a lot of their stuff over. And five years they could have been doing an awful lot more with the people that they used to bring it over. So it was a marketing decision as opposed to a rational business decision. >> It's the holy grail of the vendors, they all want your data in their database. That's why Amazon puts so much effort into it. Oracle is, you know, in obviously a very strong position. It's got growth and it's new stuff, it's old stuff. It's, you know... The problem with Oracle it has like many of the legacy vendors, it's the size of the install base is so large and it's shrinking. And the new stuff is.... The legacy stuff is shrinking. The new stuff is growing very, very fast but it's not large enough yet to offset that, you see that in all the learnings. So very positive news on, you know, the cloud database, and they just got to work through that transition. Let's bring up slide number five, because Marc, this is to me the most interesting. So we've just shown all these detailed analysis from Gartner. And then you look at the Magic Quadrant for cloud databases. And, you know, despite Amazon being behind, you know, Oracle, or Teradata, or whomever in every one of these ratings, they're up to the right. Now, of course, Gartner will caveat this and say, it doesn't necessarily mean you're the best, but of course, everybody wants to be in the upper, right. We all know that, but it doesn't necessarily mean that you should go by that database, I agree with what Gartner is saying. But look at Amazon, Microsoft and Google are like one, two and three. And then of course, you've got Oracle up there and then, you know, the others. So that I found that very curious, it is like there was a dissonance between the hardcore ratings and then the positions in the Magic Quadrant. Why do you think that is Marc? >> It, you know, it didn't surprise me in the least because of the way that Gartner does its Magic Quadrants. The higher up you go in the vertical is very much tied to the amount of revenue you get in that specific category which they're doing the Magic Quadrant. It doesn't have to do with any of the revenue from anywhere else. Just that specific quadrant is with that specific type of market. So when I look at it, Oracle's revenue still a big chunk of the revenue comes from on-prem, not in the cloud. So you're looking just at the cloud revenue. Now on the right side, moving to the right of the quadrant that's based on functionality, capabilities, the resilience, other things other than revenue. So visionary says, hey how far are you on the visionary side? Now, how they weight that again comes down to Gartner's experts and how they want to weight it and what makes more sense to them. But from my point of view, the right side is as important as the vertical side, 'cause the vertical side doesn't measure the growth rate either. And if we look at these, some of these are growing much faster than the others. For example, Snowflake is growing incredibly fast, and that doesn't reflect in these numbers from my perspective. >> Dave: I agree. >> Oracle is growing incredibly fast in the cloud. As David pointed out earlier, it's not just in their cloud where they're growing, but it's Cloud@Customer, which is basically an extension of their cloud. I don't know if that's included these numbers or not in the revenue side. So there's... There're a number of factors... >> Should it be in your opinion, Marc, would you include that in your definition of cloud? >> Yeah. >> The things that are hybrid and on-prem would that cloud... >> Yes. >> Well especially... Well, again, it depends on the hybrid. For example, if you have your own license, in your own hardware, but it connects to the cloud, no, I wouldn't include that. If you have a subscription license and subscription hardware that you don't own, but it's owned by the cloud provider, but it connects with the cloud as well, that I would. >> Interesting. Well, you know, to your point about growth, you're right. I mean, it's probably looking at, you know, revenues looking, you know, backwards from guys like Snowflake, it will be double, you know, the next one of these. It's also interesting to me on the horizontal axis to see Cloud Data and Databricks further to the right, than Snowflake, because that's kind of the data lake cloud. >> It is. >> And then of course, you've got, you know, the other... I mean, database used to be boring, so... (David laughs) It's such a hot market space here. (Marc talks indistinctly) David, your final thoughts on all this stuff. What does the customer take away here? What should I... What should my cloud database management strategy be? >> Well, I was positive about Oracle, let's take some of the negatives of Oracle. First of all, they don't make it very easy to rum on other platforms. So they have put in terms and conditions which make it very difficult to run on AWS, for example, you get double counts on the licenses, et cetera. So they haven't played well... >> Those are negotiable by the way. Those... You bring it up on the customer. You can negotiate that one. >> Can be, yes, They can be. Yes. If you're big enough they are negotiable. But Aurora certainly hasn't made it easy to work with other plat... Other clouds. What they did very... >> How about Microsoft? >> Well, no, that is exactly what I was going to say. Oracle with adjacent workloads have been working very well with Microsoft and you can then use Microsoft Azure and use a database adjacent in the same data center, working with integrated very nicely indeed. And I think Oracle has got to do that with AWS, it's got to do that with Google as well. It's got to provide a service for people to run where they want to run things not just on the Oracle cloud. If they did that, that would in my term, and my my opinion be a very strong move and would make make the capabilities available in many more places. >> Right. Awesome. Hey Marc, thanks so much for coming to theCUBE. Thank you, David, as well, and thanks to Gartner for doing all this great research and making it public on the web. You can... If you just search critical capabilities for cloud database management systems for operational use cases, that's a mouthful, and then do the same for analytical use cases, and the Magic Quadrant. There's the third doc for cloud database management systems. You'll get about two hours of reading and I learned a lot and I learned a lot here too. I appreciate the context guys. Thanks so much. >> My pleasure. All right, thank you for watching everybody. This is Dave Vellante for theCUBE. We'll see you next time. (upbeat music)

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Welcome back to the Cubes Live coverage of AWS reinvent 2020. It's virtual this year. We're not in person because of the pandemic. We're doing the remote Cube Cube Virtual were the Cube virtual. I'm your host, John for here with Andy Jassy, the CEO of Amazon Web services, in for his annual at the end of the show comes on the Cube. This year, it's virtual Andy. Good to see you remotely in Seattle or in Palo Alto. Uh, Dave couldn't make it in a personal conflict, but he says, Hello, great to see you. >>Great to see you as well, John. It's an annual tradition. On the last day of reinvent. I wish we were doing it in person, but I'm glad at least were able to do it. Virtually >>the good news is, I know you could arrested last night normally at reinvent you just like we're all both losing our voice at the end of the show. At least me more than you, your and we're just at the end of like okay, Relief. It happens here. It's different. It's been three weeks has been virtual. Um, you guys had a unique format this year went much better than I expected. It would go on because I was pretty skeptical about these long, um, multiple days or weeks events. You guys did a good job of timing it out and creating these activations and with key news, starting with your keynote on December 1st. Now, at the end of the three weeks, um, tell me, are you surprised by the results? Can you give us, Ah, a feeling for how you think everything went? What's what's your take So far as we close out reinvented >>Well, I think it's going really well. I mean, we always gnome or a Z get past, reinvent and you start, you know, collecting all the feedback. But we've been watching all the metrics and you know, there's trade offs. Of course, now I think all of us giving our druthers would be together in Las Vegas, and I think it's hard to replace that feeling of being with people and the excitement of learning about things together and and making decisions together after you see different sessions that you're gonna make big changes in your company and for your customer experience. And yeah, and there's a community peace. And there's, you know, this from being there. There's a concert. The answer. I think people like being with one another. But, you know, I think this was the best that any of us could imagine doing doing a virtual event. And we had to really reinvent, reinvent and all the pieces to it. And now I think that some of the positive trade offs are they. You get a lot mawr engagement than you would normally get in person So normally. Last year, with about 65,000 people in Las Vegas this year, we had 530,000 people registered to reinvent and over 300,000 participate in some fashion. All the sessions had a lot more people who are participating just because you remove the constraints of of travel in costs, and so there are trade offs. I think we prefer being together, but I think it's been a really good community event, um, in learning event for for our customers, and we've been really pleased with it so >>far. No doubt I would totally agree with you. I think a lot of people like, Hey, I love to walk the floor and discover Harry and Sarah Davis moments of finding an exhibit her and the exhibit hall or or attending a session or going to a party, bumping into friends and seeing making new friends. But I think one of the things I want to get your reaction to it. So I think this is comes up. And, you know, we've been doing a lot of Q virtual for the past year, and and everyone pretty much agrees that when we go back, it's gonna be a hybrid world in the sense of events as well as cloud. You know that. But you know, I think one of the things that I noticed this year with reinvent is it almost was a democratization of reinvent. So you really had to reinvent the format. You had 300,000 plus people attend 500 pending email addresses, but now you've got a different kind of beehive community. So you're a bar raiser thinker. It's with the culture of Amazon. So I gotta ask you do the economics does this new kind of extra epiphany impact you and how you raise the bar to keep the best of the face to face when it comes back. And then if you keep the virtual any thoughts on how to leverage this and kind of get more open, it was free. You guys made it free this year and people did show up. >>Yeah, it's a really good question, and it's probably a question will be better equipped to answer in a month or two after we kind of debrief we always do after reading that we spend. Actually, I really enjoy the meeting because the team, the Collective A. W s team, works so hard in this event. There's so many months across everything. All the product teams, um, you know, all the marketing folks, all the event folks, and I think they do a terrific job with it. And we we do about 2.5 3 hour debrief on everything we did, things that we thought was really well the things that we thought we could do better and all the feedback we get from our community and so I wouldn't be surprised if we didn't find things from what we tried this year that we incorporate into what we do when we're back to being a person again. You know, of course, none of us really know when we'll be back in person again. Re event happens to fall on the time of the year, which is early December. And so you with with a lot of people seemingly able to get vaccinated, probably by you know, they'd spring early summer. You could kind of imagine that we might be able to reinvent in person next year. We'll have to see e think we all hope we will. But I'm sure there are a number of pieces that we will take from this and incorporate into what we do in person. And you know, then it's just a matter of how far you go. >>Fingers crossed and you know it's a hybrid world for the Cube two and reinvent and clouds. Let's get into the announcement. I want to get your your take as you look back now. I mean, how many announcements is you guys have me and a lot of announcements this year. Which ones did you like? Which one did you think were jumping off the page, which ones resonated the most or had impact. Can you share kind of just some stats on e mean how many announcements launches you did this >>year? But we had about 100 50 different new services and features that we announced over the last three weeks and reinvent And there, you know the question you're asking. I could easily spend another three hours like my Kino. You know, answering you all the ones that I like thought were important. You know, I think that, you know, some of the ones I think that really stood out for people. I think first on the compute side, I just think the, um the excitement around what we're doing with chips, um, is very clear. I think what we've done with gravitas to our generalized compute to give people 40% better price performance and they could find in the latest generation X 86 processors is just It's a huge deal. If you could save 40% price performance on computer, you get a lot more done for less on. Then you know some of the chip work we're doing in machine learning with inferential on the inference chips that we built And then what? We announced the trainee, um, on the machine learning training ship. People are very excited about the chip announcements. I think also, people on the container side is people are moving to smaller and smaller units of compute. I think people were very taken with the notion of E. K s and D. C s anywhere so they can run whatever container orchestration framework they're running in A. W s also on premises. To make it easier, Thio manage their deployments and containers. I think data stores was another space where I think people realize how much more data they're dealing with today. And we gave a couple statistics and the keynote that I think are kind of astonishing that, you know, every every hour today, people are creating mawr content that there was in an entire year, 20 years ago or the people expect more data to be created. The next three years in the prior 30 years combined these air astonishing numbers and it requires a brand new reinvention of data stores. And so I think people are very excited about Block Express, which is the first sand in the cloud and there really excited about Aurora in general, but then Aurora surveillance V two that allow you to scale up to hundreds of thousands of transactions per second and saved about 90% of supervision or people very excited about that. I think machine learning. You know, uh, Sage Maker has just been a game changer and the ease with which everyday developers and data scientists can build, train, tune into play machine learning models. And so we just keep knocking out things that are hard for people. Last year we launched the first i D for Machine Learning, the stage maker studio. This year, if you look at things that we announced, like Data Wrangler, which changes you know the process of Data Prep, which is one of the most time consuming pieces in machine learning or our feature store or the first see, I see deeper machine learning with pipelines or clarify, which allow you to have explain ability in your models. Those are big deals to people who are trying to build machine learning models, and you know that I'd say probably the last thing that we hear over and over again is really just the excitement around Connect, which is our call center service, which is just growing unbelievably fast and just, you know, the the fact that it's so easy to get started and so easy to scale so much more cost effective with, you know, built from the ground up on the cloud and with machine learning and ai embedded. And then adding some of the capabilities to give agents the right information, the right time about customers and products and real time capabilities for supervisors. Throw when calls were kind of going off the rails and to be ableto thio, stop the the contact before it becomes something, it hurts. The brand is there. Those are all big deals that people have been excited about. >>I think the connecting as I want to just jump on that for a second because I think when we first met many, many years ago, star eighth reinvent. You know the trends are always the same. You guys do a great job. Slew of announcements. You keep raising the bar. But one of the things that you mentioned to me when we talked about the origination of a W S was you were doing some stuff for Amazon proper, and you had a, you know, bootstrap team and you're solving your own problems, getting some scar tissue, the affiliate thing, all these examples. The trend is you guys tend to do stuff for yourself and then re factor it into potentially opportunities for your customers. And you're working backwards. All that good stuff. We'll get into that next section. But this year, more than ever, I think with the pandemic connect, you got chime, you got workspaces. This acceleration of you guys being pretty nimble on exposing these services. I mean, connect was a call center. It's an internal thing that you guys had been using. You re factored that for customer consumption. You see that kind of china? But you're not competing with Zoom. You're offering a service toe bundle in. Is this mawr relevant? Now, as you guys get bigger with more of these services because you're still big now you're still serving yourself. What? That seems to be a big trend now, coming out of the pandemic. Can you comment on um, >>yeah, It's a good question, John. And you know we do. We do a bunch of both. Frankly, you know, there there's some services where our customers. We're trying to solve certain problems and they tell us about those problems and then we build new services for him. So you know a good example that was red shift, which is our data warehouse and service, you know, two or three very large customers of ours. When we went to spend time with them and asked them what we could do to help them further, they just said, I wish I had a data warehousing service for the cloud that was built in the AWS style way. Um and they were really fed up with what they were using. Same thing was true with relation databases where people were just fed up with the old guard commercial, great commercial, great databases of Oracle and Sequel Server. And they hated the pricing and the proprietary nature of them and the punitive licensing. And they they wanted to move to these open engines like my sequel and post dress. But to get the same performance is the commercial great databases hard? So we solve that problem with them. With Aurora, which is our fastest growing service in our history, continues to be so there's sometimes when customers articulate a need, and we don't have a service that we've been running internally. But we way listen, and we have a very strong and innovative group of builders here where we build it for customers. And then there are other cases where customers say and connect with a great example of this. Connect with an example where some of our customers like into it. And Capital One said, You know, we need something for our contact center and customer service, and people weren't very happy with what they were using in that space. And they said, You, you've had to build something just to manage your retail business last 15, 20 years Can't you find a way to generalize that expose it? And when you have enough customers tell you that there's something that they want to use that you have experienced building. You start to think about it, and it's never a simple. It's just taking that technology and exposing it because it's often built, um, internally and you do a number of things to optimize it internally. But we have a way of building services and Amazon, where we do this working backwards process that you're referring to, where We build everything with the press release and frequently asked questions document, and we imagine that we're building it to be externalized even if it's an internal feature. But our feature for our retail business, it's only gonna be used as part of some other service that you never imagine Externalizing to third party developers. We always try and build it that way, and we always try to have well documented, hardened AP eyes so that other teams can use it without having to coordinate with those teams. And so it makes it easier for us to think about Externalizing it because we're a good part of the way there and we connect we. That's what we did way generalized it way built it from the ground up on top of the cloud. And then we embedded a bunch of AI and it so that people could do a number of things that would have taken him, you know, months to do with big development teams that they could really point, click and do so. We really try to do both. >>I think that's a great example of some of the scale benefits is worth calling out because that was a consistent theme this past year, The people we've reported on interviewed that Connect really was a lifeline for many during the pandemic and way >>have 5000 different customers who started using connect during the pandemic alone. Where they, you know, overnight they had to basically deal with having a a call center remotely. And so they picked up connect and they spun up call center remotely, and they didn't really quickly. And you know, it's that along with workspaces, which are virtual desktops in the cloud and things like Chime and some of our partners, Exume have really been lifelines for people. Thio have business continuity during a tandem. >>I think there's gonna be a whole set of new services that are gonna emerge You talked about in your keynote. We talked about it prior to the event where you know, if this pandemic hit with that five years ago, when there wasn't the advancements in, say, videoconferencing, it'd be a whole different world. And I think the whole world can see on full display that having integrated video communications and other cool things is gonna have a productivity benefit. And that's kind >>of could you imagine what the world would have been like the last nine months and we didn't have competent videoconferencing. I mean, just think about how different it would have been. And I think that all of these all of these capabilities today are kind of the occult 1.5 capabilities where, by the way, thank God for them. We've we've all been able to be productive because of them. But there's so early stage, they're all going to get evolved. I'm so significantly, I mean, even just today, you know, I was spending some time with with our team thinking about when we start to come back to the office and bigger numbers. And we do meetings with our remote partners, how we think about where the center of gravity should be and who should be on video conferencing and whether they should be allowed to kind of video conference in conference rooms, which are really hard to see them. We're only on their laptops, which are easier and what technology doesn't mean that you want in the conference rooms on both sides of the table, and how do you actually have it so that people who are remote could see which side of the table. I mean, all this stuff is yet to be invented. It will be very primitive for the next couple few years, even just interrupting one another in video conferencing people. When you do it, the sound counsel cancels each other out. So people don't really cut each other off and rip on one another. Same way, like all that, all that technology is going to get involved over time. It's a tremendous >>I could just see people fighting for the mute button. You know, that's power on these meetings. You know, Chuck on our team. All kidding aside, he was excited. We talked about Enron Kelly on your team, who runs product marketing on for your app side as well as computer networking storage. We're gonna do a green room app for the Q because you know, we're doing so many remote videos. We just did 112 here for reinvent one of things that people like is this idea of kind of being ready and kind of prepped. So again, this is a use case. We never would have thought off if there wasn't a pandemic. So and I think these are the kinds of innovation, thinking that seems small but works well when you start thinking about how easy it could be to say to integrate a chime through this sdk So this is the kind of things, that kind thing. So so with that, I want to get into your leadership principles because, you know, if you're a startup or a big company trying to reinvent, you're looking at the eight leadership principles you laid out, which were, um don't be afraid to reinvent. Acknowledge you can't fight gravity. Talent is hungry to reinvent solving real customer problems. Speed don't complex. If I use the platform with the broader set of tools, which is more a plug for you guys on cloud pull everything together with top down goals. Okay, great. How >>do you >>take those leadership principles and apply them broadly to companies and start ups? Because I think start ups in the garage are also gonna be there going. I'm going to jump on this wave. I'm inspired by the sea change. I'm gonna build something new or an enterprise. I'm gonna I'm gonna innovate. How do you How do you see these eight principles translating? >>Well, I think they're applicable to every company of every size and every industry and organization. Frankly, also, public sector organizations. I think in many ways startups have an advantage. And, you know, these were really keys to how to build a reinvention culture. And startups have an advantage because just by their very nature, they are inventive. You know, you can't you can't start a company that's a direct copy of somebody else that is an inventive where you have no chance. So startups already have, you know, a group of people that feel insurgent, and they wanted their passionate about certain customer experience. They want to invent it, and they know that they they only have so much time. Thio build something before money runs out and you know they have a number of those built in advantages. But I think larger companies are often where you see struggles and building a reinvention and invention culture and I've probably had in the last three weeks is part of reinvent probably about 40 different customer meetings with, you know, probably 75 different companies were accomplished in those or so and and I think that I met with a lot of leaders of companies where I think these reinvention principles really resonated, and I think they're they're battling with them and, you know, I think that it starts with the leaders if you, you know, when you have big companies that have been doing things a certain way for a long period of time, there's a fair bit of inertia that sets in and a lot of times not ill intended. It's just a big group of people in the middle who've been doing things a certain way for a long time and aren't that keen to change sometimes because it means ripping up something that they that they built and they remember how hard they worked on it. And sometimes it's because they don't know what it means for themselves. And you know, it takes the leadership team deciding that we are going to change. And usually that means they have to be able to have access to what's really happening in their business, what's really happening in their products in the market. But what customers really think of it and what they need to change and then having the courage and the energy, frankly, to pick the company up and push him to change because you're gonna have to fight a lot of inertia. So it always starts with the leaders. And in addition to having access that truth and deciding to make the change, you've gotta also set aggressive top down goal. The force of the organization moved faster than otherwise would and that also, sometimes leaders decide they're gonna want to change and they say they're going to change and they don't really set the goal. And they were kind of lessons and kind of doesn't listen. You know, we have a term the principal we have inside Amazon when we talk about the difference between good intentions and mechanisms and good intentions is saying we need to change and we need to invent, reinvent who we are and everyone has the right intentions. But nothing happens. Ah, mechanism, as opposed to good intention, is saying like Capital One did. We're going to reinvent our consumer digital banking platform in the next 18 months, and we're gonna meet every couple of weeks to see where we are into problem solved, like that's a mechanism. It's much harder to escape getting that done. Then somebody just saying we're going to reinvent, not checking on it, you know? And so, you know, I think that starts with the leaders. And then I think that you gotta have the right talent. You gotta have people who are excited about inventing, as opposed to really, Justin, what they built over a number of years, and yet at the same time, you're gonna make sure you don't hire people who were just building things that they're interested in. They went where they think the tech is cool as opposed to what customers want. And then I think you've got to Really You gotta build speed into your culture. And I think in some ways this is the very biggest challenge for a lot of enterprises. And I just I speak to so many leaders who kind of resigned themselves to moving slowly because they say you don't understand my like, companies big and the culture just move slow with regulator. There are a lot of reasons people will give you on why they have to move slow. But, you know, moving with speed is a choice. It's not something that your preordained with or not it is absolutely a leadership choice. And it can't happen overnight. You can't flip a switch and make it happen, but you can build a bunch of things into your culture first, starting with people. Understand that you are gonna move fast and then building an opportunity for people. Experiment quickly and reward people who experiment and to figure out the difference between one way doors and two way doors and things that are too way doors, letting people move quick and try things. You have to build that muscle or when it really comes, time to reinvent you won't have. >>That's a great point in the muscle on that's that's critical. You know, one of things I want to bring up. You brought on your keynote and you talk to me privately about it is you gave attribute in a way to Clay Christensen, who you called out on your keynote. Who was a professor at Harvard. Um, and he was you impressed by him and and you quoted him and he was He was your professor there, Um, your competitive person and you know, companies have strategy departments, and competitive strategy is not necessarily departments of mindset, and you were kind of brought this out in a zone undertone in your talk, we're saying you've got to be competitive in the sense of you got to survive and you've got to thrive. And you're kind of talking about rebuilding and building and, you know, Clay Christians. Innovative dilemma. Famous book is a mother, mother teachings around metrics and strategy and prescriptions. If he were alive today and he was with us, what would he be talking about? Because, you know, you have kind of stuck in the middle. Strategy was not Clay Christensen thing, but, you know, companies have to decide who they are. Their first principles face the truth. Some of the things you mentioned, what would we be talking with him about if we were talking about the innovator's dilemma with respect to, say, cloud and and some of the key decisions that have to be made right now? >>Well, then, Clay Christensen on it. Sounds like you read some of these books on. Guy had the fortunate, um, you know, being able to sit in classes that he taught. And also I got a chance. Thio, meet with him a couple of times after I graduated. Um, school, you know, kind of as more of a professional sorts. You can call me that. And, uh, he he was so thoughtful. He wasn't just thoughtful about innovation. He was thoughtful about how to get product market fit. And he was thoughtful about what your priorities in life were and how to build families. And, I mean, he really was one of the most thoughtful, innovative, um, you know, forward thinking, uh, strategist, I had the opportunity Thio encounter and that I've read, and so I'm very appreciative of having the opportunity Thio learn from him. And a lot of I mean, I think that he would probably be continuing to talk about a lot of the principles which I happen to think are evergreen that he he taught and there's it relates to the cloud. I think that one of the things that quite talked all the time about in all kinds of industries is that disruption always happens at the low end. It always happens with products that seem like they're not sophisticated enough. Don't do enough. And people always pooh pooh them because they say they won't do these things. And we learned this. I mean, I watched in the beginning of it of us. When we lost just three, we had so many people try and compare it Thio things like e m. C. And of course, it was very different than EMC. Um, but it was much simpler, but And it and it did a certain set of activities incredibly well at 1 1/100 of the price that's disrupted, you know, like 1 1/100 of the price. You find that builders, um, find a lot of utility for products like that. And so, you know, I think that it always starts with simple needs and products that aren't fully developed. That overtime continue to move their way up. Thio addressing Maura, Maura the market. And that's what we did with is what we've done with all our services. That's three and easy to and party ass and roar and things like that. And I think that there are lots of lessons is still apply. I think if you look at, um, containers and how that's changing what compute looks like, I think if you look at event driven, serverless compute in Lambda. Lambda is a great example of of really ah, derivative plays teaching, which is we knew when we were building Lambda that as people became excited about that programming model it would cannibalize easy to in our core compute service. And there are a lot of companies that won't do that. And for us we were trying to build a business that outlasts all of us. And that's you know, it's successful over a long period of time, and the the best way I know to do that is to listen to what customers We're trying to solve an event on their behalf, even if it means in the short term you may cannibalize yourself. And so that's what we always think about is, you know, wherever we see an opportunity to provide a better customer experience, even if it means in the short term, make cannibalism revenue leg lambda with complete with easy to our over our surveillance with provisions or are we're going to do it because we're gonna take the long view, and we believe that we serve customers well over a long period of time. We have a chance to do >>that. It's a cannibalize yourself and have someone else do it to you, right? That's that's the philosophy. Alright, fine. I know you've got tight for time. We got a you got a hard stop, But let's talk about the vaccine because you know, you brought up in the keynote carrier was a featured thing. And look at the news headlines. Now you got the shots being administered. You're starting to see, um, hashtag going around. I got my shot. So, you know, there's a There's a really Momenta. Mit's an uplifting vibe here. Amazon's involved in this and you talked about it. Can you share the innovation? There can just give us an update and what's come out of that and this supply chain factor. The cold chain. You guys were pretty instrumental in that share your your thoughts. >>We've been really excited and privileged partner with companies who are really trying to change what's possible for all of us. And I think you know it started with some of the companies producing vaccines. If you look at what we do with Moderna, where they built their digital manufacturing sweet on top of us in supply chain, where they used us for computing, storage and data warehousing and machine learning, and and on top of AWS they built, they're Cove in 19 vaccine candidate in 42 days when it normally takes 20 months. I mean, that is a total game changer. It's a game changer for all of us and getting the vaccine faster. But also, you just think about what that means for healthcare moving forward, it zits very exciting. And, yeah, I love what carriers doing. Kariya is building this product on top of AWS called links, which is giving them end and visibility over the transportation and in temperature of of the culture and everything they're delivering. And so it, uh, it changes what happens not only for food, ways and spoilage, but if you think about how much of the vaccine they're gonna actually transport to people and where several these vaccines need the right temperature control, it's it's a big deal. And what you know, I think there are a great example to what carrier is where. You know, if you think about the theme of this ring and then I talked about in my keynote, if you want to survive as an organization over a long period of time, you're gonna have to reinvent yourself. You're gonna have to probably do it. Multiple times over and the key to reinventing his first building, the right reinvention culture. And we talk about some of those principles earlier, but you also have to be aware of the technology that's available that allows you to do that. If you look at Carrier, they have built a very, very strong reinvention culture. And then, if you look at how they're leveraging, compute and storage and I o. T at the edge and machine learning, they know what's available, and they're using that technology to reinvent what's what's possible, and we're gonna all benefit because of >>it. All right. Well, Andy, you guys were reinventing the virtual space. Three weeks, it went off. Well, congratulations. Great to go along for the ride with the cube virtual. And again. Thank you for, um, keeping the show alive over there. Reinvent. Um, thanks for your team to for including the Cube. We really appreciate the Cube virtual being involved. Thank you. >>It's my pleasure. And thanks for having me, John and, uh, look forward to seeing you soon. >>All right? Take care. Have a hockey game in real life. When? When we get back, Andy Jesse, the CEO of a W s here to really wrap up. Reinvent here for Cuba, Virtual as well as the show. Today is the last day of the program. It will be online for the rest of the year and then into next month there's another wave coming, of course. Check out all the coverage. Come, come back, It's It's It's online. It's all free Cube Cube stuff is there on the Cube Channel. Silicon angle dot com For all the top stories, cube dot net tons of content on Twitter. Hashtag reinvent. You'll see all the commentary. Thanks for watching the Cube Virtual. I'm John Feehery.

>>From around the globe with digital coverage of AWS reinvent 2020, sponsored by Intel and AWS welcome everyone to the cube live and our coverage of AWS reinvent 2020. I'm your host Rebecca Knight. Today we are joined by Andre due for, he is the general manager of Amazon location service. Thank you so much for coming on the show. Andre. >>Thanks so much, Rebecca. It's a pleasure. >>So Amazon, AWS is announcing a Amazon location service in preview. Tell us a little bit more about what it does. What was the impetus for it? >>Of course. Well, Amazon location service is a new geospatial service that makes it easy for customers on AWS to integrate location information into their applications. And when I say location information, I mean a couple of specific things, mops points of interest places, and geocodes from trusted global high quality data partners. And one of the things that's really cool about Amazon location is we enable customers to access this high-quality data in a way that's incredibly cost effective. It's up to 10 times cheaper than some of the alternatives. And so what that means for customers is they can bring to life use cases that previously would have been inconceivable because they just weren't cost effective. Additionally, Amazon location takes privacy very seriously. And so, you know, customers have told us many times that they're, they're, they're very concerned about their location information, leaving their control. Whereas with Amazon location, we keep customer's location data in their AWS account unless they decide otherwise. And finally, what we've seen with customers who are using Amazon location is they're able to move from experimentation with location ideas, to scale production, much more quickly than they otherwise could have because it's a native AWS service. So we're so excited to be announcing this >>Well, you just mentioned cost privacy scale production, three things that are definitely on customers' minds right now. Tell us a little bit more about these use cases. How are customers using it? >>Yeah, that's a great question. I think it's often easiest to understand the capabilities through the lens of a use case. Now it turns out location in, in more and more customer conversations is pervasive across a bunch of different use cases, but I'll touch on maybe just for today. So one thing that we're seeing customers commonly using location for is location-based customer engagement. And so what that means is including a location component, when you are reaching out to your customers with timely offers. So for example, when they're in close proximity to one of your retail locations, sending them an offer tends to increase their satisfaction and their conversion an additional use case that Springs to mind immediately in many of the conversations is using maps for striking visualizations of data, either showing a route between two points or dropping location pins on a map in order to enhance the visual understanding of subject matter. >>Additionally, customers tend to use Amazon location for asset tracking. They want to know where their things are in the world and be able to reason over that both in real time in order to make decisions or retrospectively in order to optimize or to audit. And additionally, um, customers also use us in end to end delivery use cases, be it last mile delivery for, uh, goods that were ordered online or, uh, food delivery, which of course is, uh, increasingly prevalent these days. And so, yeah, you know, one of the customer examples that I think is especially compelling here because it touches on a couple of these is a company called Singleton solutions and their product is called mobile log. Uh, it's effectively last mile as a service in the cloud. And what it lets customers do is manage the logistics of a delivery business. And so what mobile log and Singleton have been able to do is retire a lot of the custom code that they had built because nothing was really available to meet their location needs. They were able to consolidate their location infrastructure from multiple clouds onto just AWS, which simplifies their solution. They were able to move more quickly as they innovate on behalf of their customers. And they managed to reduce their costs while doing this by up to 60%. So I think it's a pretty cool example of what location can do for customers. >>What are some other industries and apps and applications that would benefit most from this affordable location data? >>Yeah, well, it's, uh, it tends to spend many different industries. So we're seeing a lot of uses as you can imagine in transportation and logistics and, and certainly that's, uh, an industry that's growing very quickly, um, government and public sector attempt to have a need to, uh, visualize a lot of information, uh, on, on maps. Um, we are seeing retail and folks interested in customer engagement. Um, it really is springing up everywhere and often B uh, the conversations kind of have a location component in disguise. For example, we were talking to a telecom service provider who is telling us, well, you know, I can save billions of dollars if I increase the efficiency of my truck rolls. Well, that's the location use case, right? If people are talking about, uh, actually one, one customer, uh, or a person who has used us in beta is post NL, and they're telling us, you know, if they can increase just the, um, loading factor of their trucks by 1%, uh, in, uh, over time, this is big dollar savings for them. And not, that's all about location and about optimizing, uh, the, the routing and dispatch of their vehicles. And so really it's springing up everywhere, but it doesn't always sound like a map or a geocode it's, uh, more of these business level considerations around optimization around moving faster and around serving customers more quickly. >>You mentioned a couple of, of industries and logistics areas where this is being used. What are, which customers are currently using Amazon location service? >>Well, so there are a couple that I, uh, I mentioned, so of course we're only just launching today. We've had a beta program, uh, and we have a couple of references that we can talk about publicly. So Singleton is the very first that we touched on, and this is a company that's operative in the delivery and, uh, dispatch logistics space. And so they they've been using us to, to advantage and, and have realized some pretty significant cost savings. Uh, the other company that's been, uh, experimenting with Amazon location, uh, again in sort of a similar space, but with a different geography is posted on owl. And so they're the number one, uh, e-commerce and delivery, uh, her postal logistics company in the Netherlands. And what, what they're actually using us for is to, uh, do asset tracking on their delivery roller cages in order to, uh, understand where they are in the world and make better decisions as to where they should be in relation to the demand. >>Andre, I want you to close this out here. And as you said, you launched today, you've been in beta, what is in store for 2021 with Amazon location service? What can, what can we expect? What can customers expect? >>Yeah, so we're, we're in preview today and it's an open preview, so people can, can just go to the console and directly use it. You don't need to sign up. And what we have to look forward to in the first part of 2021 is general availability of the service. And you can imagine that we'll be rolling that out over everyone regions, because there's significant demand for this all over the world. And then it's a fairly typical, uh, AWS motion where what we're going to do is listen, because 90% of our roadmap is compelled by customer requests. And so we'll be very attentive to how people are using the service, where they see additional opportunities for us to serve them better. And we will move with vigor on those. >>Great. And for customers who want to find out more, what, what should they do? >>Well, the easiest thing to do is to go to aws.amazon.com/location, and then, uh, check, check us out there and get started with the service today. >>Great, well, Andre do for, thank you so much for coming on the Cuba really interesting conversation. >>Thank you so much. It's been a privilege. >>I'm Rebecca Knight stay tuned for more of the cubes coverage of AWS reinvent 2020.

>>From the cubes studios in Palo Alto, in Boston, connecting with thought leaders all around the world. This is a cute conversation. >>The external storage array business, as we know it has changed forever. You know, you can see that in the survey data that we do and the financial information from the largest public storage companies. And it's not just because of COVID, although that's clearly a factor which has accelerated the shifts that we see in the market, specifically, those CIO is, are rationalizing their infrastructure portfolios by consolidating workloads to simplify, reduce costs and minimize vendor sprawl. So they can shift resources toward digital initiatives that include cloud containers, machine intelligence, and automation all while reducing their risks. Hello everyone. This is Dave Vellante and welcome to this cube conversation where we're going to discuss strategies related to workload consolidation at petabyte scale. And with me is Dr. Rico. He's the vice president office of the CTO at INFINIDAT welcome back to the cube doc, always a pleasure to see you >>And great to be here. Always a pleasure to work with you, Dave. >>So doc, I just published a piece over the weekend and I pointed out that of the largest storage companies, only one showed revenue growth last quarter, and that was on a significantly reduced compare with last year. So my first question to you is, is INFINIDAT growing its business. >>Oh, absolutely. It's been a very interesting year all across as you can quite imagine. Um, but you know, our footprint is such that with our elastic pricing models and the, and the fact that we've got excess capacity, uh, in almost every single system that's out there, we were really given our customers a, an opportunity to take advantage of that, to increase their capacity levels while maintaining the same levels of performance and availability, but not have to have anybody on premises during this crazy, you know, COVID struck era. >>Yeah. So you're bringing that cloud model to the, to the data center, which has obviously been a challenge. I mean, you mentioned the subscription sort of like pricing, we're going to get into the cloud more, but I wonder if we could step back a little bit and look at some of the macro trends that you're seeing in the market and specifically as it relates to on-prem storage strategies that CEO's are taking. >>Yeah. You know, it's been interesting, we've seen over the course of the past five years or so, certainly a big uptick in people looking at next generation or what they believe in perceived to be next generation storage platforms, which are really just evolutions of media. They're not really taking advantage of any new innovations in storage and, you know, not withstanding our own products, which are all software driven. We've talked about that before, but what what's really happened in this past year, as you, as you said, CEOs and CTOs, they're always looking for that, that next point of leverage advantage. And they're looking for more agility in application deployment, they're looking in a way to rapidly respond to business requirements. So they're looking very much at those cloud-like requirements. They're looking at those capabilities to containerize applications. They're looking at how they can, um, you know, shift out virtual machines if they're not in a directly in a container, uh, and how the storage by the way, can, can have the same advantage and in order to do so, they really need to look at storage consolidation. You know, I think Dave, to, to sum it up from the storage perspective, you know, I love Ken Steinhardt was recently on a video and, you know, he was, he was challenged that, you know, people aren't looking at spinning rust, riff, you know, a derogatory wave of referring a disc and, and Ken, so rightly and accurately responded. Yeah. But people weren't really looking for QLC either. You know, what they're looking for is performance, scale availability and certainly cost effectiveness and price. >>Yeah. It was like, I set up front dock. I mean, if you're a C level executive today, you don't want to worry about your storage infrastructure. You've got bigger problems to worry about. You just want it to work. And so when you talk about consolidating workloads, people often talk about the so-called blast radiation. In other words, people who run data centers, they understand that things fail. And sometimes something as simple, it might be a power supply can have a catastrophic downstream effect on application availability. So my question is, how do you think about architecting systems? So as to minimize the effects of component failures on the business? >>Yeah. You know, it's a very interesting term, Dave blast radius, right? We've, we've heard this referred to storage over the last several decades. In fact, when it really should refer to the data center and the application infrastructure. Uh, but you know, if we're talking about just the storage footprint itself, one of the things that we really need to look, look at is the resilience and the reliability of the architecture. And when you look at something that is maybe dual controller single or double power supply, there are issues and concerns that take in, in, into, into play. And what we've done is we've designed something that's really triple redundant, which is typically only been applied to the very high end of the market before. And we do it in a very active, active, active manner. And naturally we have suggestions for best practices for deployment within a data center as well, you know, multiple sources of power coming into the array and things of that nature. But everything needs to be this active, active, active type of architecture in order to bring those reliability levels up to the point where as long as it's a component failure within the array, it's not going to cause an outage or data on availability event. >>Yeah. So imagine a heat map when people talk about the blast radius. So imagine the heat map is green. There's a big, you know, there's a yellow area and there's a, there's a red area. And what you're saying is, as far as the array goes, you're essentially eliminating the red area. Now, if you take it to the broader installation, you know, that red area, you have to deal with it in different ways, remote replication, then you can at the sink and in a sink. Uh, but, but essentially what I'm hearing you say, doc, is, is you're squeezing that red area out. So, so your customers could sleep at night. >>That absolutely sleep at night is so appropriate. And in fact, we've got a large portion of our customer base is, or they're running mission critical businesses. You know, we have some of the most mission critical companies in our, in our logo portfolio, in the world. We also have, by the way, some very significant service provider businesses who were we're providing, you know, mission critical capabilities to their customers in turn, and they need to sleep at night. And it it's, you know, availability is only one factor. Certainly manageability is another cause you know, not meeting a service level is just like data unavailability in some respects. So making manageability is automatic as it can be making sure that the, that the system is not only self-healing, but can re respond to variations in workload appropriately is very, very critically important as well. >>Yeah. So that, that you mentioned mission critical workloads, and those are the, those are the workloads that let's face it. They're not moving into the cloud, certainly not in any, any big way, you know, why would they generally are CIO CTO is they're putting a brick wall around that saying, Hey, it works. We don't want to migrate that piece, but I want to talk more about how your customers are thinking about workload consolidation and rationalizing their storage portfolios. What are those conversations like? Where do they start and what are some of the outcomes that you're seeing with your customers? >>Yeah, I think the funny thing about that point Dave, is that customers are really starting to think about a cloud in an entirely different way. You know, at one point cloud meant public cloud and men, this entity, uh, outside the walls of the data center and people were starting to use services without realizing that that was another type of cloud. And then they were starting to build their own versions of cloud. You know, we were referring to them as private clouds, but they were, you know, really spread beyond the walls of a single data center. So now it's a very hybrid world and there's lots of different ways to look at it, hybrid cloud multi-cloud, whatever moniker you want to put on it. It really comes down to a consistency in how you manage that infrastructure, how you interface with that infrastructure and then understanding what the practicality is of putting workloads in different places. >>And practicality means not only the, you know, the latency of access of the data, but the costs associated with it. And of course the other aspects that we talked about, like what the, the availability metrics, and as you increase the availability and performance metrics, those costs go up. And that's one of the reasons why some of these larger mission critical data centers are really, you know, repatriating their, their mission, critical workloads, at least the highest, highest levels of them and others are looking at other models, for example, AWS outposts, um, which, you know, talked about quite a bit recently in AWS reinvent. >>Yeah. I just wrote, again, this weekend that you guys were one of the, uh, partners that was qualified now, uh, to run on AWS outpost, it's interesting as Amazon moves, it's, you know, it's, it's it's model to the edge, which includes the data center to them. They need partners that can, that really understand how to operate in an on-premise world, how to service those customers. And so that's great to see you guys as part of that. >>Yeah. Thank you. And, you know, it was actually a very seamless integration because of the power and capability of all of the different interface models that we have is they all are fully and tightly integrated and work seamlessly. So if you want to use a, you know, a CSI type model, uh, you know, do you interface with your storage again, uh, with, with INFINIDAT and, you know, we work with all of the different flavors so that the qualification process, the certification process and the documentation process was actually quite easy. And now we're able to provide, you know, people who have particularly larger workloads that capability in the AWS on premises type environment. >>Yeah. Now I implied upfront that that cloud computing was the main factor, if not the primary factor, really driving some of the changes that we're seeing in the marketplace. Now, of course, it's all, not all pink roses with the cloud. We've seen numerous public cloud outages this year, certainly from Microsoft. We saw the AWS Kinesis outage in November. Google just had a major outage this month. Gmail was down G suite was down for an extended period of time. And that disrupted businesses, we rely on that schools, for example. So it's always caveat emptor as we know, but, but talk to INFINIDAT cloud strategy, you mentioned hybrid, uh, particularly interested in, in how you're dealing with things like orchestration and containers and Kubernetes. >>Yeah, well, of course we have a very feature rich set of interfaces for containers, Kubernetes interfaces, you know, downloadable through native, uh, native. So they're, they're very easy to integrate with, you know, but our cloud strategy is that, you know, we are a software centric model and we, you know, all of the, all of the value and feature function that we provide is through the software. The hardware of infiniboxes really a reference architecture that we, uh, we deliver to make it easier for customers to enjoy say 100% availability model. But if, if you want to run something in a traditional on premises data center, you know, straighten InfiniBox is fine, but we also give you the flexibility of cloud-like consumption through our pricing models, our, our elastic pricing models. So you don't need to consume an entire InfiniBox day one. You can grow and shrink that environment with, uh, with an OPEX model, or you can, um, buy it as you consume it in a, in a cap ex model. >>And you can switch, uh, from OPEX over to CapEx if it becomes more cost effective for you in time, which I think is, is what a lot of people are looking for. If you're looking for that public cloud, we, you know, we have our new tricks cloud offering, which is now being delivered more through partners, but you know, some businesses and especially the, the mid tier, um, you know, the SMB all the way through the mid enterprise are also now looking to cloud service providers, many of which use InfiniBox as, as their backend. And now with AWS outposts, of course, you know, we can give you that on premises, uh, uh, experience of the public cloud, >>You guys were early on. And obviously in that, that subscription-based model, and now everyone's doing it. I noticed in the latest Gartner magic quadrant on, on storage arrays, which you guys were named a leader, uh, they, I think they had a stat in there and said, I, I forget what the exact timeframe was that 50% of customers would be using that type of model. And again, I guarantee you by whatever time frame, that was a hundred percent of the vendor community is going to be delivering that type of model. So, so congratulations on being named a leader, I will say this there's there's there's consolidation happening in the market. So this, to me, this bodes well, to the extent that you can guarantee high availability and consistent performance, uh, at, at scale, that bodes well for, for you guys in a consolidating market. And I know IDC just released a paper, it was called, uh, I got, uh, I got a copy here. >>It's called a checklist for, uh, storage, workload consolidation at petabyte scale. It was written by Eric Bergner, who I've known for a number of years. He's the VP of infrastructure. Uh, he knows his stuff and the paper is very detailed. So I'm not going to go through the checklist items, but I, but I think if you don't mind, doc, I think it's worth reading an excerpt from this. If I can, as part of his conclusions, when workload consolidation, it organizations should carefully consider their performance availability, functionality, and affordability requirements. Of course, few storage systems in the market will be able to cost effectively consolidate different types of workloads with different IO profiles onto a single system. But that is in INFINIDAT forte. They're very good at it. So that's a, that's quite a testimonial, you know, why is that your thoughts on what Eric wrote? >>Well, you know, first of all, thank you for the kudos on the Gartner MQ, you know, being a leader on the second year in a row for primary storage, only because that documents only existed for two years, but, uh, you know, we were also a leader in hybrid storage arrays before that. And, you know, we, we love Gardner. We think they're, they're, you know, um, uh, real critical, you know, reliable source for, for a lot of large companies and, and IDC, you know, Eric of course is, uh, he's a name in the industry. So we, you know, we very much appreciate when he writes something, you know, that positive about us. But to answer your question, Dave, you know, there's, there's a lot that goes on inside InfiniBox and is the neural cash capabilities, the deep learning engine that is able to understand the different types of workloads, how they operate, uh, how to provide, you know, predictable performance. >>And that I think is ultimately key to an application. It's not just high performance. It's, it's predictable performance is making sure the application knows what to expect. And of course it has to be performant. It can't just be slow, but predictable. It has to be fast and predictable providing a multi-tenant infrastructure that is, that is native to the architecture, uh, so that these workloads can coexist whether they're truly just workloads from multiple applications or workloads from different business units, or potentially, as we mentioned with cloud service providers, workloads from different customers, you know, they, they need to be segmented in such a way so that they can be managed, operating and provide that performance and availability, you know, at scale because that's where data centers go. That's where data centers are. >>Great. Well, so we'll bring that graphic back up just to show you, obviously, this is available on your website. Uh, you can go download this paper from Erik, uh, from IDC, www infinidat.com/ian/resource. I would definitely recommend you check it out. Uh, as I say, Ericsson, you know, I've been in the business a long, long time, so, so that's great, doc, we'll give you the last word. Anything we didn't cover any big takeaways you want to, you want to share with the audience? >>Yeah. You know, I think I'll go back to that point. You know, consolidation is absolutely key for, uh, not just simplicity of management, but capability for you respond quickly to changing business requirements and or new business requirements, and also do it in a way that is cost-effective, you know, just buying the new shiny object is it's expensive and it's very limited in, in shelf life. You're just going to be looking for the next one the next year. You want to provide something that is going to provide you that predictable capability over time, because frankly, I have never met a C X O of anything that wasn't trying to increase their profit. >>You know, that's a great point. And I just, I would add, I mean, the shiny new object thing. Look, if you're in an experimental mode and playing around with, you know, artificial intelligence or automation thinking, you know, areas that you really don't know a lot about, you know, what, check out the shiny new objects, but I would argue you're on-prem storage. You don't want to be messing around with that. That's, it's not a shiny new objects business. It's really about, you know, making sure that that base is stable. And as you say, predictable and reliable. So doc Terico thanks so much for coming back into cube. Great to see you. >>Great to see you, David, and look forward to next time. >>And thank you for watching everybody. This is Dave Volante and we'll see you next time on the queue.

>>From around the globe. It's the cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS, and our community partners. >>Hello, everyone. Welcome back to the cubes. Virtual coverage of AWS reinvent 2020 it's virtual this year because of the pandemic. We're not there in person and in real life, we're remote. I'm John for a year hosting the cube or the cube virtual. Um, as we continue to cover the three weeks of AWS reinvent and analyze the keynotes, we bring it in, uh, from our Cuban alumni, uh, network experts. And we have here great guest, Steve Malaney, CEO of Ava Trex, industry executive legend, former entrepreneur had done startups, um, been very, very successful with luminary and Silicon Valley, um, Palo Alto networks and the Sierra Cisco, I me, all the companies you've worked for. Um, Steve, great to see you again. >>Oh yeah. Hey awesome. Even if it's just virtual, John's great to be back in the cube. >>Okay, Steve, what's up? Am I muted? I got you. Okay. >>Gotcha. Oh, okay. I just said it's great. They're great to be back in the cube. >>I had to shut up my volume, got to love live cube TV. Um, I wanted to bring you on, because one, we've been talking with you guys and your company that you're now heading. You came off the board to take the helm of Ava tricks. You really saw the vision early on before the pandemic. We were actually, we did a hybrid event with you guys, a digital hybrid and your vision of multi-cloud and hybrid was pretty much in line with what Andy Jassy. And Amazon's now rolling out, except they're not calling it. Multi-cloud, they're just saying hybrid. But when you factor in the edge, the complexity there, you're really talking multiple environments. So I want to get your take, as you look at what Amazon has done in their announcements, they're continuing to power long. What's your analysis. What's your industry take? >>Yeah, I, I think it's, uh, you know, I think it's great. I think, you know, when we were a year ago, it was just a little over a year ago, we were at a multi-cloud conference and I think people kind of thought, wow, is multicloud something that the vendors are wanting to happen because they don't want to be killed by AWS. And you know, I mean, I saw this two years ago, I call it the Cambridge and explosion to cloud where every enterprise to we are now going to move to cloud. And they had been talking about it for six or seven years, but they didn't really mean it. And two years ago I saw they meant it and I knew what was going to happen. It was going to go multi-cloud they we're going to care about day two operations, visibility, control, security, all the things that enterprises care about. And I think, um, you know, what we've seen really over the last year is AWS and all the other cloud providers recognizing this, that the world is going multicloud. Um, and day two operations matter. You've gotta be able to operationalize this and enterprises. Can't just, it's not just about wiring it and building it up. You got do, you can operate it. And so that's, I think the thing that's really interesting is the maturity of the messaging. I would say from AWS to recognize, um, where enterprises are in their journey. >>You know, Steve, I want to just reflect on something. When I was 19 years old in my first job, uh, in New York, it was on a prime mini computer, my first exposure to the enterprise office and then went and worked for IBM and HP and others. I've been in the, around the enterprise. Let me just go back 10 years in Silicon Valley, you could literally count on one or two hands. The number of enterprise experts out there that you knew of that were out circulating that weren't retired. Um, because it went through this kind of commodity stage of outsource everything kind of down to the bone, you know, just keeping the lights on there. Wasn't really a lot of innovation in the enterprise. Now it's the hottest thing in the world. And you, and you look at what's happening with cloud. They're redefining the enterprise in Andy Jassy said to me, and I'm going to interview him, uh, later this week. And you know, he said, we're done with eyes and pads. We checked that's anything. I say anyone, but he's kind of implying that we did. I, as in pass, we're targeting global it. >>Yeah. Well, you know, >>Now enterprise is super hot and you know, it's, it's a whole nother ball game to restructuring on G >>Yeah, I mean, so I, uh, the AWS is marketing slogan, Mark. My words I'll bet you a hundred bucks within the next year is going to change. They are not going to say go build anymore. Right? Because that's what they're going to say. Go consume because no enterprise wants to build and Oh, by the way, here's the other thing that they're now also figuring out. Cause I know Andy Jassy analysis, there's a skills shortage of cloud, so they don't have the skills at the aptitude, but there's also a people shortage. It's not just the skills, it's the amount of people. They don't have the ability to go deploy this. And they're going to, you're going to need solutions like ABA tricks, abstract the way a lot of the complexities of the underlying clouds and deliver this architecture for people to be able to actually deploy. >>Where is the skill gaps in your opinion, where do you see them? >>You know, I was just talking to a customer yesterday and he said most of my, most of my team are CLI jockeys. And so for networking, that means the CLI the command line interface that a human manipulates to control the Cisco router. That's the old operational model. The model of this, these days are Terraform. You're going to infrastructure is code everything. You need scriptures. You need, you need developers that are going to be driving your infrastructure. And, and, but I can't, I can't fire all these people that I've had in my enterprise for the last 30 years. I got to bring them along. I got to bring them along and the tools and the platforms to be able to go, to go do that. >>Andy's argument and Amazon's position is we eliminate the undifferentiated heavy lifting and we have all this training and content to bring everyone along. Okay. By that. >>Well, I mean, here's, here's the thing that I think AWS and all the, all the cloud providers are figuring out is the enterprise is a different beast. You know, when you go to a company as AWS and say, Hey, you can get it as long as it's any color you want, as long as it's black. And so guess what, I'm a service. And the beautiful thing is you don't need to know anything about how we do anything and just trust me, it's all going to work that does not go over well with an enterprise because they say, I'm the guy that needs to know I will get fired. If this infrastructure goes down, you know, you saw us East one go down two weeks ago, Google had a outage to two days ago or whatever it was, shit happens. I don't know if I can say that on the cube. >>We're not going to actually see regulated at this point, but who's going to know. >>Um, and you know what? I've got to have that visibility in controls and enterprise, and I need the granular controls and the visibility to troubleshoot and the security controls and the performance controls that I used to have on prem, because I'm a regulated enterprise. I need that visibility and control. And the cloud providers just say, look, I deliver a service and I deliver it to everybody. And it's the same service. And you don't need to know that does not fly with the >>Well, certainly you're seeing more regulated industries. It used to be just public sector. I just talked with Teresa Carlson. She now took over all the industries. So FinTech is regulated. Energy is regulated. Telecom's regulated. The only thing that's not regulated is a VC and startup sectors, right? So there's a >>Well, and, and, and every, every good CIO of an enterprise knows nothing good comes from your, from your infrastructure that gets outsourced. We tried that it doesn't work. Now, maybe in 20 years, I can outsource my infrastructure if I'm the CIO of a major enterprise corporation. But right now I am not outsourcing that I have to have control. Now, am I going to leverage services and basic infrastructure from the cloud providers? Absolutely. I'm not going to build it on my own data centers. That world is over, but what I'm going to maintain is the visibility and control. >>Yeah. And that's what we heard from Verner. Vogel's around observability systems, thinking control versus observability, um, evolvable systems, things like reasoning, um, you know, these are, these are innovations, right? So, so let's get back to that builders thing, because you mentioned that earlier, I think there might be an opportunity. And I think this is where I think Jassy will either look brilliant or it might not pan out. So go big or go home moment. Can Amazon create a market for companies to say, instead of bringing along everybody, I'm going to bring along some people and hire more builders because there's rewards as spoils to be had for those builders. At this point in time, given the pandemic, it's kind of put everything on full display in terms of what to do. What's your thoughts on that? >>I think, I think outside in meaning I, I look at the customer and I, and I sit at the same side of the table as a customer. I think, what did they want? And every enterprise customer right now is building out their PRI it's just like in 1992, when they built out their private infrastructures, global infrastructure, and they did it with on-prem and data centers. I bought my stories, my compute, my networking, my MPLS, and I built my infrastructure. And it was my infrastructure. They're doing the same thing. It's just, they're architecting on top of cloud and they're doing it in a multi-cloud world because they're not going to be locked in to just one cloud. And they're going to have some applications that run better on GCP. Some have better in AWS and some on Oracle, and all of our customers are doing this. And what they want though, is a common infrastructure. That's their architecture and their infrastructure, not an AWS architecture and a Google architecture and an Azure architecture. What architecture, abstracted away above the clouds. That's my architecture. And it's common for my global network that that's what enterprises want to do. And I think each of the individual clouds are going to have to understand that they are a piece of the puzzle. They are not the puzzle. And I think you're going to have to come to that realization. >>I appreciate your expertise and insight into the commentary real quick, last 30 seconds, give a quick plug for Ava tricks. What are you guys doing? What's new cause the quick update. >>I mean, it's, it's, it's crazy just since, uh, I've been the CEO for two years and you know, the, the logos of large enterprise that we're getting right now. My, my Cambrian explosion that I saw two years ago is real, um, more executing on that strategy. It's a, who's who of logos right now. We've got 450 customers now we're, uh, exploding and more importantly, enterprises are now getting that deployment phase. They have, they're done with the architecture phase of, Hey, let me check this whole thing out in cloud. And now they're pushing the button and they're, they're accelerating, which my guess is it's not a coincidence that AWS is now talking about operations. And what Aviatrix does is, is, is, does gives that visibility and control cloud networking, but in a very cloud native way with Terraform simplicity, agility, because agility is part of mission critical infrastructure. Now can't be like it was in 1994 with a Cisco infrastructure where it said, what year do you want your, your, your infrastructure, Mr. Customer? >>Great. And the biggest thing people should pay attention to this year, uh, for around the enterprise dynamics with cloud and scale what's what should people be watching >>In your opinion? Just the continued movement of big enterprises, uh, all into cloud. The center of gravity is now into cloud and, uh, they're going to be completely running away from everything on prem. >>All right. Steven Landy, CEO of VBA tricks, a proven success entrepreneur CEO, back in the two years of the helm, the VBA tricks. Great to see you. I wish we were in person. One of our last events was your altitude event. It's on YouTube. If anyone was interested in watching, we had a great time. Steve, thank you so much for your candid commentary. Yeah. Thanks, John. Okay. I'm Jennifer with the cube. You're watching the cube virtual here on the cube. Thanks for watching..