(upbeat music) >> Welcome to VMworld 2021, a two day virtual event, hosted by the company which permanently changed data center operations last decade. My name is Dave Vellante, and you're watching theCUBE's coverage of VMworld 2021, where we want to know what VMware and its ecosystem have in store for the next 10 years and how your digital business can survive and thrive in the coming decade, and who better to give us a glimpse as to how that's being done both inside VMware and within its customer base, than Mike Hayes, who is the chief digital transformation officer at VMware. Mike, great to have you on the program. >> No Dave, thank you for having me, we appreciate you and all that you do for this great event. Thank you, sir. >> Oh, I appreciate that. So talk about, what's involved with your role as chief digital transformation officer. What's that all about? >> Yeah thank you for, many people, are chief digital transformation officer in a lot of different places, different things. Here at VMware I'm responsible for worldwide business operations and digital transformation of the firm. Just like first and foremost, we're focused on our customers and how our customers can improve their own business models, whether it's cost, flexibility, speed, imagining new things, that's what gets us really excited. And at the same time, we're transforming internally in order to bring ourselves into our exciting third chapter. >> Yeah, everybody wants to be a SAS company these days, VMware obviously is accelerating its move towards SAS. Maybe you could talk a little bit about your strategy for leading business operations as well as that transformation. >> Absolutely, I think there's a couple of things. And first of all, the most important thing in an organization is agility we have or transforming our own ability to transform. As we all know, everybody listening knows that markets don't sit still, they pivot quickly, and so the organizations that win aren't the organizations that prepare for tomorrow, but they prepare for the ability to change for tomorrow, and as the markets change, they stay ahead of that. So that's what we're doing at VMware and that's what we're really excited about our entire suite of products and services so that we can help organizations do the same. >> Yes so, if I could stay on this for a second, Mike, when you think about what you have to deal with there, and you're moving to that as a service subscription model, you got to the external factors, you mentioned you start with the customer, but you also have internal factors, right? Your salespeople might be used to one and done move on to the next one, more transactional, it's a whole different mindset, isn't it? >> It absolutely is, and so any organization as large as VMware is, should always be staring at itself and saying, how can we be more flexible? And so we just like everywhere else are looking at our foundational data, we're looking at our ERP systems, we're looking at our own internal processes to say, as we pivot to SAS, and the back office becomes closer to the front office. That's really where it's at, there's not a customer in the world that cares about any of their... Where they're buying from, the back offices from where they're buying from don't matter, what matters is that experience, it's that front layer, it's that first touch with the customer. We recognize that, and we're preparing for that, and I'm really excited about how it's going. >> Let's talk about some of the waves that you're riding here, the major trends that are driving digitally. I often call it the forced march to digital in 2020. It was like, we were just thrown into the fire. And it's just the way it was. If you weren't a digital business, you were out of business. And now people are kind of sitting back and saying okay, let's take those learnings, fill those gaps, and really set us on a course over the next decade. So what do you see as the major trends? What are the technologies that are enabling digital business and how are you applying them both in your own business and what you're seeing with your customers? >> We first of all I think what's important is to recognize that every organization needs the ability to scale. So what we're doing at VMware is simplifying our foundation. And so then as we 2x or 5x or 10x, our own business, we're multiplying off a much simpler base. And so as we drive our own transformation, our internal principles of like simplicity and clarity and accountability, and really streamlining is what VMware is doing. And that's what we're also not surprisingly recommending and helping our own customers with. And so that's what gets really exciting for us. I think that, one of the things that you're alluding to with this a forced march to digital which I totally agree with, is really, it is about experience and for us there are a couple of KPIs that are really interesting to us, and it should be for everybody, no surprise here, but the velocity that it takes for operations to go from an idea to a closure, from quote to cash, or from idea to implementation, whatever that front and back end words your own business uses are what's important, but how fast do you get through that? And so for us, we're imagining a touch less future. So no, are we there yet? Absolutely not. Is any organization? Very few are. And so how do we constantly say, ask ourselves what don't we need to be doing? When I walk into a room in a lot of places VMware or otherwise, and you say who's in charge of what we're not doing? That's where all the good ideas are, the good idea spaces, like what organizations aren't doing, so you have that culture of pulling awesome ideas to the front and saying, how do we just prioritize? The hardest thing Dave right now, is that there are so many shiny objects for all of our enterprises, for everybody that's listening. I think one of the hardest things is prioritizing and saying, how do we spend our resources in the smartest way possible, so that we are doing the things that will have the greatest impact for our customers. Something that we feel like we have a great plan for, and we're excited about the execution over the coming year. >> I wonder if you could comment on what you're seeing and just in terms of spending patterns. All throughout last year, we reported that CIO's expected budget contractions of around 5% relative to 2019, and what happened is in the second half, he really saw, companies had to respond to the cyber threats, they had to respond, of course to hybrid work, this whole digital march that we talked about, and it was actually pretty strong. Many people expected that a lot of the traditional companies that relied on data center and on-prem and HQ spend, were really going to get hit and they actually got through it okay. And meanwhile, the cloud is exploding, your cloud businesses exploding, security is exploding. What was interesting is, just this weekend, we published some data that suggested, that is not only continuing into 2021, but CIO's are expecting, more of this in 2022. So we used to have this sort of steady IT spend, refresh cycles, et cetera, but it seems like we're in a step function right now, in terms of investment, and it seems like CEOs are saying, if we don't lead this digital transformation, we're going to become toast. >> Absolutely Dave, yeah, the first thing you mentioned was budget. Let's remember budgets are a function of a company's focus on either short term goals or long-term goals. And so the organizations that are really smartest are thinking three, four, five years out and you're investing now, so that you can always really be high-performing in that 2, 3, 4 year window. Because any organization that mortgages it's future for this current year is not doing itself any favors. So the cycles that I'm seeing that are aligned exactly as you described, organizations are understanding, key leaders get that they need to invest. But the question is, how do you invest in the things that are classically thought of as maybe back office, or let me just say boring, just to be provocative. How do we choke out the boring stuff from a budget standpoint, and then really give a lot of oxygen and energy to the things that are fun and really transformative? And that's what we're seeing, and that's why we feel like our strategy is so great Dave, because we're part of that for the future, and as organizations think about freeing up capital so that they can invest in those fun things that really accelerate their own business models, that's what it's about. >> Now VMware of course has always had an amazing ecosystem, always been very proud of the value that you created, not just free for your own selves, but for your customers, and also your ecosystem partners. So as it relates to your digital transformation role Mike, we talked about customers, we talked about some of the internal stuff and operations. How does the ecosystem fit in? How do you collaborate with them? What kind of learnings do you get from them? How do you plug them into your digital platform if you will? >> Absolutely, I think the most important element you're drawing out, Dave, is the concept of trust. We have incredible partners, and without whom VMware's business and success that we enable in the world would be very limited. So we recognize that we all go through life with friends and partners, it's obviously not just true in business, I was a Navy Seal for 20 years and the most important thing is that foundational element. Now, what we do and what we're always trying to do is be as transparent and fast and helpful as we can. I think that in the partner world, anytime you can reach across the table more than halfway and with another organization, that's easy to intersect. If you're not willing to meet people in places more than halfway, there is no middle. So for us, what we're doing is constantly listening and getting feedback and saying, where can we improve? That's what's really awesome. Sandy Hogan is an incredible colleague of mine who runs our channel, and Sandy runs a board with 30 of our largest partners in the channel, and the first question that she always asks is, what can we be doing better? And that's for us the most important thing is listening. Just like you were in developing an individual product. What's important is product market fit, right? Does your product fit in the market, and then how do you get feedback from it? We apply that as an institution and an enterprise. >> Mike, you mentioned your experience in the military, thank you for your service, I wanted to ask you something about that. So I wrote a piece one time and talked about Frank Slootman, who is becoming a Silicon Valley icon, how he's going to apply his playbook at his new company, Bubba. And he wrote me back, he said, "Dave I learned in the military that, it's not a playbook. I am a situational leader and I learned that in the military." So my question to you is, what did you learn as a Navy Seal to deal with situations, especially in a condition like we are now, where there's a lot unknown. How do you apply that in today's world? >> Yeah Look, the there's the parallels between the Seals and VMware are perfect, right? Because all we're doing is quickly defining an outcome. What's the vision for the organization? What's the outcomes we'd want to achieve? That's the where we're going. Then there's the strategy, which is the how. How are we going to get there? How do you develop strategy? There are a hundred different ways to go achieve the vision, but how do we think about the different risks along the way? And like I said earlier, draw those risks out, so they're known risks. Then we can price them and size them and understand that for our strategy. And then how do we execute well and how do we get feedback throughout the whole thing? But you know Dave, the best thing I would say, the analogy from the Seals in the military, really is what you hit on. A lot of people say that they have a plan, but in the Seals the only plan that we had was for our plan to change, it's that concept I said earlier of transforming our ability to transform. So we go in on any given night with complicated missions and have a plan, but we knew that that plan was going to very quickly change, it's no different than what we're doing here at VMware, with our own customers in this technology market. >> It's a great lesson to apply Mike. I really appreciate you sharing that and appreciate you coming on the queue. >> Thank you for having me, it's such a pleasure. >> Really a pleasure was ours, and thank you for watching over. Keep it right there for more great content from Vmworld 2021, you're watching theCUBE. (upbeat music)

>> Live from San Francisco, it's theCUBE. Covering Google Cloud Next 19. Brought to you by Google Cloud and its eco system partners. >> Hello everyone welcome back here to theCUBE live coverage here in San Francisco, California. We're in the Moscone Center on the ground floor here. Day three of three days of coverage for Google Cloud Next 2019. I'm John Furrier, my co-host, Dave Vellante, Stew Miniman out there getting stories out there He's also been hosting. Dave, great to see you! Evren, Director of Product Management at Google Cloud, doing all the data streaming the data. We're streaming data right now. >> Absolutely, this is it. This is it. >> So let's stream some data. So streaming data has certainly been around for awhile. Dave and I when we first started theCUBE ten years ago, it was part of Silk and Angle Media hadoop was just a small little project. That really kind of was the catalyst moment for around big data that's now evolved to it's own position. Now you have streaming data, you have cloud scale, the Cloud has really changed the game on big data. Changed the nature and dynamics of it and one of the things is streaming data, streaming analytics as a core value proposition for enterprises, and this is fairly new. >> Very true. >> What's your take on it and how does it relate to what's going on with Google Cloud? >> I am glad we're talking about that. This is an exciting time for us. Streaming like you said is growing. Batch is not going away, but streaming is actually overtaking a lot of the applications that we're seeing. Today we're seeing more streaming applications taking place than batch. One of the things that we're seeing is everybody is gathering data from all over the place from your websites, from your mobile phones, from your IoT devices, just like we're doing right now. There's data coming in and people want to make decisions real time whether it's in the banking industry, in your healthcare, retail, it doesn't matter which word cycle you're working with and we're seeing how those messages how those events are coming in and where the decisions are being made real time, milliseconds we're talking about. >> Why is it happening, what's the real catalyst here? Just tsunami of data, nature of the value, all of the above, what's the? >> We believe one of the things is like you mentioned Cloud really changed the game. Where people actually can reach globally data and messages at scale. We're talking about billions of messages coming in and processing capacity is available now we can actually process it and make a decision within milliseconds and get to the results. To me, that was the biggest catalyst. And we're seeing many of us have grown up using batch data, making decisions now everybody is talking about M.L. and A.I. You need that data coming in real time and we can actual process it and make the decision. To me, that's the catalyst. >> First of all we love streaming data, this topic. One we believe streaming where shooting video but data, real time, has been one of the keys you see self driving cars monging of data, mixing and matching of data to get better signal and better machine learning and I got to ask you, because batch is certainly the role for batch is kind of old school it's some old techniques it's been around for awhile, >> It's not going to go away though. >> It's not going to go away it's established it's place but the knee jerk reaction of existing old school people who haven't migrated to the new modern version they go to the batch kind of mind set. I want to get you're reaction. Data lakes, there's nothing flowing in a lake. Okay, so there is a role for a data lake streaming gives me the impression of like an ocean or a river or something moving fast. Talk about the differences because it's not just the data lake okay that's a batch kind of reaction. >> It is a complementary. Actually it's not going away because all of that data that we had in the back is something we're relying on to really augment and see what's changing. So if you're in a retail house you're buying something, you're going to make a decision and your support is actually behind it. OK here's Evren, he's actually shopping around this and he wants this for his son. That's what the models built around it is looking at what is my behavior and in the moment making a decision for me. So that's not going away. The other thing is batch users are able to take advantage of the technology today. If you look at our data flow, same set of codes, same set of capability can be used by the same folks that are used to batch. You don't have to change anything so that actually we help folks to be up skilled using the same set of tools and become much more experienced and experts in the streaming too. That's not going away we help both of the worlds. >> So, complementary. >> Very complementary. >> So data lakes are good for kind of setting the table if you have to store it somewhere but that's not the end game though. >> No. >> Okay. >> I wonder if we could talk about the evolution from batch to real time streaming. And my favorite example, because I think people can relate to it, is fraud detection. Ten years ago, it was up to the user to go through his or her bill, right? And then you started to get inundated with false positives, and now lately, last couple of years it's getting better and better. Fewer false positives, usually when you usually no news is good news. News is usually bad news now, so take that example and use that to describe how things have evolved. >> I am a student of AI I did my Master's and PhD in that and I went through that change in my career because we had to collect the data, batch it and analyze it, and actually make a decision about it and we had a lot of false positives and in some cases some negative misses too which you don't want that either. And what happened is our modeling capabilities became much better. With this rich data, and you actually tap into that data lake, you can go in there the data is there, and this is spread data we can pull in data from different sources and actually remove the outliers and make our decision real time right there. We didn't have the processing capability we didn't have a place like PostUp where globic can scan and bring in data at hundreds of gigabytes of data. That's messaging you want to deal with at scale no matter where it is and process that, that wasn't available for us. Now it's available it's like a candy shelf for technologists, all the technology is in our hands and we wanted all these things. >> You were talking about I think the simplicity of, I'm able to use my batch processes and apply them. One of the complaints I hear from developers sometimes is that the data pipeline is getting so complicated. You were talking about you're grabbing stuff from websites, from financial databases, and so depending on what data store you're using and what streaming tools you're using or other A.I. tools, the pipeline gets very complicated the A.P.Is start to get complicated but I'm hearing a story of simplicity. Can you elaborate on that and add some color? >> Yeah I'm glad you're asking that question you may have heard, yesterday we announced a whole bunch of new things and ease of use is the top of the line for us. Really are trying to make it easy. If you look at this eco pipeline we're building with data flow, it helps you end to end. Data engineered no matter which angle their coming in should be able to use their known skill sets and be able to build their pipelines end to end so that you can achieve your goals around streaming. We aren't really having to go through a lot of the clusters of the pipelines we are going to continue to push that ease of use over and over, we're not going to let it go because make it easier, everyone will adapt it faster. >> You mentioned you got a PhD in A.I., Master's in A.I., A.I. has been around for awhile. A lot of people have been saying that but machine learning certainly has changed the game. Machine learning plus cloud has been a real accelerant in the academic and now commercial aspects of A.I. So I want to get your thoughts on the notion of scale which you talk about, plus the diversity of data. So if you can bring in data at scale get more signaling points more access to data signaling the diversity of data becomes very key. But cleanliness, data cleaning, used to be an old practice of you get a bunch of data, stack it up, put it in a pile corpus, and you kind of go clean it. With streaming, if it's always flowing there's kind of a behavioral characteristic of data cleanliness, data monitoring, talk about that diversity of data clean data and how that feeds machine learning and makes better A.I. >> Good one, so that's where we actually are able to, if you look at PostUp, you're building joint your table set of datas with streaming set of datas you can actually put it into data filter it and make those analyses. And within both, we provide enough of a window for you to be able to go back, hey are there things that I should be looking at, up to seven days we can provide a snapshot because you will always find something you can go back, you know what I'm going to remove this outlier. All worrying about all the processing we do before we bring in the data so there's a lot of cleanliness that takes place but we have the built in tools we have the built in capabilities for everyone to get going. It's ready to scale for you from the moment you open it up. That's the beauty of it, that's the beauty of when you start from PostUp to data flow to streaming engine it's ready for you to run. >> Talk about what's changed though when people hear diversity of data they get scared, oh my god I work, heavy lifting. Now it's a benefit. What's easier now to deal with all of these diverse data sets, what's the easy revolution? >> So do you remember the big V's of big data right? Volume, velocity, variety. People were scared about the variety. Now I can actually bring in my data from different places. Again, let's go back to the shopping example. Where I shop, what I shop for, that actually defines my behavior around it. Those data sit somewhere else. We bring those in to make a decision about okay everyone wants to go buy a scooter or whatever else, that's the diversity of the data. We're now able to deal to with this at scale. That was not available we could actually bring in and render this, now everything is going to do this much more sequential. We're now able to bring all of them together process it at the same time and make the decision. >> What's the key products that will make all of those happen, take us through the portfolio if I want that would you just said which is a great value. It sounds like not a heavy lift all I have to do is point the data sources into this engine, what are the products that make up that capability? >> So if I look at the overall portfolio on Google Cloud from our data analysts point of view, so you actually can bring in your data through PostUp, lots of messaging capability globally and you can actually do it regionally because we have a lot of regional requirements coming from various countries and data flow is where we actually transfer the data. That's where you do the processing. And you use all of these advance analytics capabilities through your streaming engine that we released and you have your B query, you have your OMLs, you have all kinds of things that you can bring in you're big tables and what have you. That's all easily integrated end to end for any analyst to be able to use. >> What is beam? >> Beam ah that's great I'm so glad you asked that question I almost forgot! Beam is one of our open sources we donated the same set, just like we did with Koppernes few years ago, we donated to the open source it's growing. This year actually it won The Technology Awards. So the source is open the community really took it upon, they use that toolkit to build their pipelines you can use any kind of a code that you want Java, Gold, whatever you want to do it and they contribute. We use it internally and externally. It's one of those things that's going to grow. We have a lot of community events coming up this year. We might, and I've seen the increase, I'm really really proud of that community. >> Evren, I love the A.I. can't get my mind off your background and academic because I studied A.I. as well in the 80s and 90s all that good stuff. Young kids are flocking to computer science now because A.I. is very sexy, it's very intoxicating and it's so easy to deal with now. You guys had a hack-a-thon here with NCAA using data really kind of real time and kind of cool things are happening. So it's a moment now for A.I. this is the moment. What's your advice, you've been through the wars you've done your chore duty all those years now it's actually happening. What's your advice for young people who want to come in, get their hands dirty, build things, use A.I., what's your advice, how they should tackle that? >> I am living it, both of my sons one is finishing junior high, the other one is a senior in high school, their both in it. So when I hear my young kids come and say, "hey bubba we just built this using transfer flow." Like it is making me really proud. At the middle school level they were doing it. So the good news is we have all of this publicly available data for them. I encourage every one of them. If you look at what we provide from Google Cloud, you come in there, we have the data for them, we have the tools for them, it's all ready for them to play so schools get free access to it too. >> It's a major culture but how do they get someone who's interested but never coded before, how do they jump right in and get ingratiated and immersed into the code, what do they do? >> We have some community reaches that we're actually doing as Google. We go out to them and we're actually establishing centers to really build community events for them to really learn some new skills. And we're making this easy for them. And I'm happy to hear more and do it, but I'm an advocate I go to middle schools, I go to high schools, I go to colleges. Colleges are a different story. We provide school classes and we provide our technologies at the universities because enterprises need that talent, need that skill, when they graduate, their going to hire them just like I'm going to hire them into my organization. >> So my number one complaint my kids have about school, they're talking about kids that, oh school's going to be a waste it's so linear I can learn everything on YouTube and Google.com. All the stuff I learned in school I'm never going to use in the real world. So the question is, what skill should kids learn that could be applied to machine learning, thinking, the kind of constructs, data structures, or methodologies, what are some of the skills and classes that can tease out and be natural lead into computer science and machine learning A.I.? >> You know, actually their going to build up the skills. The languages will evolve and so forth. As long as they have that inner curiosity asking new questions, how can I find the answer a little faster, that will push them towards different sets of tools, different sets of areas. If you go to Berkeley in here, you will see a whole bunch of high school kids working side by side with graduate students asking those questions, developing those skill sets, but it's all coming down to their curiosity. >> And I think that applies for business too. I mean there's a big gap between the A.I. haves and have-nots I always say. And the good news here that my take away is, you're going to buy A.I, you're going to buy it from people like Google and you're going to build it and apply it, you're going to spend time applying it, and that's how these incumbents can close the gap and that's the good news here. >> Very true if you look at it, look at all the A.P.Is that we have. From text recognition to image recognition to whatever it is, those are all built models and I've seen some customers build some fantastic applications starting from there and they use their own data, bring it in, they update their model for their own businesses cases. >> It's composition it's composing. It's not coding it's composing. >> Exactly, it's composing. We are taking it to the next level. That abstraction is going to actually help others come into the field because they know their field of expertise, they can ask direct questions. You and I may not know it but, they will ask direct questions. And they will go with the tools available for them for the curiosity that they reach. >> Okay what's the coolest thing you're working on right now? >> Coolest thing, I just y'know streaming is my baby. We are working on, I want to solve all the streaming challenges, whatever the industry is. I really want to welcome everyone, bring you to us. I think, if I look at it, one of the things we discussed today was Antos was fantastic right? I mean we're really going to change the game for all enterprises to be able to provide those capabilities at the infrastructure. But imagine what we can do with all the data analytics capabilities we have on top of it. I think this is the next five years is going to be fantastic for us. >> What's the coolest use case thing you see emerging out of streaming? >> Ah you know, yesterday I actually had one of my clients with me onstage, AB Tasty. They had a fantastic capability that they built. They tried everything. And we were not their first choice, I'll be very open. They said the same thing to everybody, you guys were not our first choice. They went around, they looked at all the tool kits, everything. They came they used PostUp, they used data flow, they used engine, streaming engine. And they AB testing for marketing. And they do that at scale, billions of messages every minute, and they do it within seconds, milliseconds, 32 milliseconds at most. Because they have to make the decision. That was awesome, go check. I don't know if you're familiar with that. One of our customers, they provide these real time delivery. In India, imagine where things are. In global leaders, you can actually ask for a food to be delivered and they have to optimize, depending on what the traffic is and go with their scooters, and provide you this delivery. They aren't doing it as well. Okato, they believe, provide food in UK 70% of the population use our technologies for real time delivery. Those are some great examples. >> Evren, great insight, great to have you on. Just a final word here, next couple years, how do you see the trajectory of machine learning A.I. Analytics feeding into the value of making life easier society better, and businesses more productive? >> We are seeing really good pull from enterprises from every archival that you can think of. Regulated, retail, what have you. And we're going to solve some really hard problems whether it's in health care industry, financial industry, retail industry, we're going to make lives of people much easier. And their going to benefit from it at scale. And I believe we're just scratching the tip of it and you're seeing this energy in here. Year over year this has gotten better and better. I can't wait to see what's going to happen next year. >> Evren Eryurek great energy, expert at A.Is, streaming analytics, again this is early days of a brand new shift that's happening. You get on the right side of history it's A.I. machine learning, streaming analysts. Thanks for coming, I appreciate it. >> Thank you so much, take care guys. >> More live coverage here in theCUBE in San Francisco at Google next Cloud 2019. We'll be back after this short break.

>>Like for Las Vegas, Nevada, that's the cue governor AWS reinvent 2016, brought to you by AWS and its ecosystem partners. Now, here are your hosts, John furrier and Stu minimum. >>We are here, live in Las Vegas with the cube all week. I'm John minimum. We are breaking down all the re-invent coverage. The cube is going on for three days. Um, Stu and I are going to break down here and studio B the analysis of Andy Jassy, his keynote. This is really day one of the event yesterday was kind of a preview at James Hamilton. Uh, Tuesday evening, I had a great band up there. Uh, and then he came on and delivered a really an Epic performance laying out as a, he's not a showman in the sense of, uh, uh, Steve jobs like, but he has a Steve jobs like cred, uh, James Hamilton, when it comes to the gigs in the community, he delivered the, what I call the secret sauce with AWS as data centers. And then Andy Jassy today with his keynote again is so high pack. >>They start at 8:00 AM, which is kind of not usual for events with so much to up their pack. Councilor came on stage AI Stu. First, I want to get your take on today's keynote with Andy Jassy. You were in the front row. What was going on inside the room? Tip, tell us your perspective, give us the vibe. What was the energy level and what was, what was it like? Yeah. John, as you said, starting at 8:00 AM, it's like a up, we must be talking to the tech audience because developers usually like to start a little bit later than that. Um, it was an embarrassment of riches. Uh, Andy gets on stage, as he told you, when you met with him up at his home in Seattle, uh, they've got, they're going to have about a thousand, you know, major new features updates. Uh, and you know, I think Andy went through a couple of hundred of them up on stage. >>Uh, you know, this is a group of true believers pack. Keynote people started streaming in over an hour ahead of time because only 10,000 could fit in the main tent. They had other remote locations where you could go get, you know, mimosas, bloody Marys or coffee. Uh, if you wanted to watch us, all over that. But it, it, it just to tell you, my fourth year here at the show and it's like, Oh yeah, another tech show. You're going to get keynotes. They're going to make some announcements yawn, no Amazon impresses every year. And they delivered this year. Andy might not be a showman, but you know, he was punching at a, you know, Larry Ellison and Oracle quite a bit. He got huge ovations. Like every time they announced a new compute instance, uh, in lots of these things, uh, and a little bit of show flare, uh, at the end, uh, certainly the going into the database market. >>Uh, but also they're making some really good infrastructure enhancements with the new services. What was your highlight if you're going to look at what the most significant, most important story this morning, what, what was squinting through all the great announcements? What ones you liked best? Oh boy. John, I have to pick one. I mean, here, here's a few number one is, you know, there's, there's some pushback from people in the community that, Oh, you know, they announced another ton of news, you know, compute instances, there's all these different storage configurations. Uh aren't we supposed to be making things simple. Uh, and that's when they had a one Amazon LightSail, which is the virtual private servers in seconds really goes after, you know, kind of a, you know, simple, low cost model, uh, really digital ocean's the leader in that space starting at like $5 a month, John, uh, you know, very exciting. A lot of people, uh, you know, really getting, uh, you know, as to where this could go every year, Amazon has a number of competitors that they're just like up, we see this opportunity. We can go after this. And John, this is not a high margin business. I mean, usually it's like, Oh, okay, database. I understand there's huge margin there. The storage market, of course, LightSail $5 a month. I mean, you know, they make it up in volume, but it's super fast. >>It was on a playbook. It drive the price down as low as possible, and then shift the value with the analytics. Um, and, uh, Aurora PA um, um, uh, pack housing or any chassis said fastest growing service in the history of Amazon last year, he said red shift was that this surpass red shift, uh, the announced Postgres equal on a roar, another big significant customer request. Um, just on and on the database seems to be the lock-in spec that they're trying to undo from Oracle. Um, they're not stopping. I mean, the rhetoric was all time high, John, the picture Larry Ellison popped out, popped in the Oracle. Oh, in the, in, in the O >>We know the long pole in the tent for enterprises is the applications you have making any changes in that, uh, doing any refactoring, you know, tinkering, you know, those are hard things to do. Um, but you know, we've heard a lot from Amazon this week as to how they're helping with migration, how they're giving options, how they're giving bridges, uh, things like VMware on AWS to bridge over from where you are, you know, you can lift and shift it. You can move it, you can rewrite it, lots of options there. Uh, and Amazon just has so many services and so many customers, thousands of systems integrators, uh, you know, thousands of ASVs, uh, and really big enterprises, you know, making statements up on stage. When you get Workday up on stage, John, you get McDonald's up on stage. Uh, you know, it's impressive. >>Some big name accounts, no doubt about it. That's do I want to get your thoughts on James Hamilton? Again, Amazon's got some of the announcements. I mean, some companies will launch entire conference keynote around maybe one or two of what they've done out of the many that they've had here also to note, there's been over 150 partner announcements. So the ecosystems do before we get to Hamilton, I want to talk about the ecosystem. This feels a lot like 2011, VMware. I was kind of joking with Sanjay Poonen the CEO of VMware was just on the cube with us and saying, what do you think about VMworld this year? I mean, re-invent, I was kind of tongue in cheek. I wanted to zinc them a little bit, but stew, this feels like, >>So John, I'm an infrastructure guy, and I want to talk about James Hamilton. One thing we got to cover first green grass. I, you know, green grass is how Amazon is taking their serverless architecture, really Lambda and taking it beyond the cloud. So how do I get, you know, that, that kind of hybrid edge, we talked about it a little bit with Sanjay, but number one, I can start pulling VMware into AWS. Number two, I can now get, you know, my Lambda services, uh, out on the edge, they talked about some IOT plays on, they talked about the snowball edge, uh, which is going to allow me to have kind of compute and storage, uh, down at that edge. Uh, I've seen huge excitement at this show, uh, on the serverless piece developers, it's really quick to work with, uh, twenty-five thousand Amazon echo dots were handed out and I've already talked to people that are already, you know, writing functions for that and figuring out how to can play with it. And God, we haven't even talked about the AI, John with voice and images. How many hours do we have John? >>I we'll get there. Let's stay on green grass for a minute, because if you think about what that's about, I want to get your thoughts on your thoughts on the impact of green grass. I mean, obviously the lamb done, that's got a little edge piece of snowball tied to it. Uh, you know, green grass and high ties forever. The old song by, you know, Southern rock band Outlaws back in the day, this is a significant announcement. What is the impact of that? >>Yeah, well, John, I mean the grass is greener in the cloud, right? So now we're going to bring the green grass, >>No ball when it snowball, my melts extends in the green grass. >>So we're going to be riffing all day on this stuff. So David foyer, uh, our CTO at Wiki bond has been talking for awhile, uh, that, you know, while cloud is great for data, the problem we have is that IOT is going to have most of the, you know, most of the data out on the edge. And we know the physics of moving large amounts of data is really tough. And especially if it's spread out things like sensors, things like wind farms, getting the networking to that last mile can be difficult. That's where things like green grass are going to be able to play in. How can I take really that cloud type of compute and put it on the edge. It really has potential to be a real game changer. I think John, we talked about what hybrid means, uh, and you know, we'll, we'll see a lot, a lot of buzz in the industry about what Microsoft's doing with Azure stack, uh, and you know, lots of pieces, but you know, grass, you know, it gives this new model of programming. It gives the developers, uh, it gives me, you know, I can use the arm processors, uh, out on the edge and, you know, we could try and talk about how that fits with James Hamilton too. >>We are inside the hall next to the cube studio, being so much content. We have to actually set up a separate set. Stu I want to get your thoughts on, I mean, obviously we can go on forever, but the significant innovation on multiple fronts for Amazon, you mentioned Greengrass, snowball, multiple instances. Um, and certainly they got all the analytics on Bubba, the top of the stack with Redshift and other stuff. And he says, streaming goes on and on the list goes on and on, but you look at what they're doing with Greengrass and snowball. And then you go look at what James Hamilton talked about yesterday. Now they're going down an innovating down to the actual physical chip level. They're doing stuff with the network routes, the control in the packet there, no one's touching the packets. They are significantly building the next global infrastructure backbone for themselves to power the world. This is, to me, I thought a subtle talk that James gave. There's a ton of nuance in there. Your thoughts on last, night's a really Epic presentation. I know we're gonna have a sit down exclusive interview with James Hamilton with Rob Hoff, our new editor in chief Silicon angle, but still give us a preview. What blew you away? What got you excited? I mean, it was certainly a geek dream. >>Yeah. I mean, John, you know, James Hamilton is just one of those. You talk about tech athletes, you know, just the, the real heroes in this space, uh, that so many of us look up to, uh, it's been one of the real pleasures of my career working, uh, with the cube that I've gotten to speak to James a few times. Uh, and the first article I wrote three years ago, uh, about what James Hamilton has done is it's hyper optimization. The misconception that people had about cloud is, Oh, it's just a white box. They're taking standard stuff, Amazon. And what James always talks about is how to, you know, really grow and innovate at scale. And that means they build for their environments and they really get down to every piece of the environment, all the software, all the hardware, they either customize it or make their own. So, you know, the big monitor >>And Stu to your point for their own use cases, the home, a prime Fridays and those spike days, he was talking about how they would have to provision months and months in advance to add, to understand some estimated peak that they were spinning up, literally thousands of servers. >>Yeah. So John, you know, Amazon doesn't make a lot of acquisitions, but one that they made is Annapurna labs. So they've got their own custom Silicon that they're making. Uh, so this will really allows them to control, uh, how they're doing their build-out. They can focus on things like performance. Uh, James talked about, uh, you know, how they're, they're really innovating on the network side. He was very early with 25 gigabit ethernet, uh, which really drove down. Some of the costs, gave them huge bandwidth advantages, uh, and kind of leading the way in the industry. Uh, the, the, the thing we've been poking out a bit is while Amazon leverages a lot of open source, they don't tend to give back as much. Uh, they've got the big MX net announcement as to how they're going to be involved in, in the machine learning. And that's good to see they hired Adrian Cockcroft, uh, you know, who lots of us knew from his Netflix days. Uh, and when he was a venture capitalist, he's going to be driving a lot of the open source activity. But James, you know, kind of went through everything from, >>By the way, on your point about source, I set it on the cube and I'll say it again. And you Mark my words. If Amazon does not start thinking about the open source equation, they could see a revolt that no one's ever seen before in the tech industry. And that is the open source community. Now as a tier one, it has been for a long time tier one contributor to innovation, and as a difference between using open source for an application like Facebook and a specific point application or Google for search, if you are building open source to build a company, to take territory from others, there will be a revolts. Do you, John, do you agree? Am I off, >>Uh, revolt might be a little strong, but absolutely. We already see some pushback there. And anytime a company gets large power in the marketplace, you see pushback. We saw it with Oracle, with salt, with Microsoft, we see it with VMware. Uh, so you know, and I think Amazon, here's this point, uh, Andy Jassy talks about how they're making meaningful contributions. I expect Adrian, uh, to make that much more visible. Um, we'll have to get into some of the James Hamilton stuff at a later date, but >>Down with him with Rob posts more on that later, you and I will hit James Hamilton analysis on the key later final thoughts you were giving me some help before we came on to talk here about me saying, I'm bullish on VMware's relationship with AWS. And you said, really? And I said, I am because I am a big fan of VMware, um, also AWS, but for their customers, for AI, for VMware customers, this is a good thing. Now you might have some thoughts on execution. Maybe what's your, why? Why did you roll your eyes when I said that? >>So, John, I mean, you know, I've lots of love for the VMware community. Uh, you know, spent lots of time in that space. Uh, and it, it's good to see, uh, VMware working with the public clouds. However, uh, I think the balance of power Shilton shifts in the side of Amazon being in control here. Uh, and you know, there's a lot of nuance. Where are the services where the value is what's going to be good for customer. Amazon's really good at listening. Uh, and you know, this embarrassment of riches that they do, right? >>A real summary, what bottom line, what happened this morning and your mind abstracted all the way in one soundbite, wait, >>They rolled a truck out, out stage, John, this snowmobile a hundred terabytes, a hundred petabytes of storage and a terabyte of information. Something that, you know, we were like, this is amazing. It's it's the, the maturation of the hybrid message is different from what people have been talking about hybrid, uh, you know, where SAS lives, all the ISV is. Where's the data, where's the application. Amazon's in a really good position. John, there's a big and growing ecosystem here. Uh, but there's a huge battles that I know we're going to get into, uh, out in the marketplace. You know, who's going to win voice, uh, you know, everybody's their apples, their Microsoft, >>Because everyone's jocking for position. Got Google, you got Oracle, you've got IBM. You've got Microsoft all looking at AWS and saying, how do we change the game on them? And we'll be covering this. The cute we are here in Las Vegas studio B cube three days of wall-to-wall Cubs, I'm Jeffers do minimum, breaking it down on day one, keynotes and analysis. Thanks for watching. We'll be right back. Stay tuned to the cube cube siliconangle.tv. You go to siliconangle.com for all the special exclusive stories from re-invent specifically to, with Andy Jassy, James Hamilton, and more thanks for watching.