>> And it'll be the fastest 15 minutes of your day from there. >> In three- >> We go Lisa. >> Wait. >> Yes >> Wait, wait, wait. I'm sorry I didn't pin the right speed. >> Yap, no, no rush. >> There we go. >> The beauty of not being live. >> I think, in the background. >> Fantastic, you all ready to go there, Lisa? >> Yeah. >> We are speeding around the horn and we are coming to you in five, four, three, two. >> Hey everyone, welcome to theCUBE's coverage of AWS re:Invent 2022. Lisa Martin here with you with Subbu Iyer one of our alumni who's now the CEO of Aerospike. Subbu, great to have you on the program. Thank you for joining us. >> Great as always to be on theCUBE Lisa, good to meet you. >> So, you know, every company these days has got to be a data company, whether it's a retailer, a manufacturer, a grocer, a automotive company. But for a lot of companies, data is underutilized yet a huge asset that is value added. Why do you think companies are struggling so much to make data a value added asset? >> Well, you know, we see this across the board. When I talk to customers and prospects there is a desire from the business and from IT actually to leverage data to really fuel newer applications, newer services newer business lines if you will, for companies. I think the struggle is one, I think one the, the plethora of data that is created. Surveys say that over the next three years data is going to be you know by 2025 around 175 zettabytes, right? A hundred and zettabytes of data is going to be created. And that's really a growth of north of 30% year over year. But the more important and the interesting thing is the real time component of that data is actually growing at, you know 35% CAGR. And what enterprises desire is decisions that are made in real time or near real time. And a lot of the challenges that do exist today is that either the infrastructure that enterprises have in place was never built to actually manipulate data in real time. The second is really the ability to actually put something in place which can handle spikes yet be cost efficient to fuel. So you can build for really peak loads, but then it's very expensive to operate that particular service at normal loads. So how do you build something which actually works for you for both users, so to speak. And the last point that we see out there is even if you're able to, you know bring all that data you don't have the processing capability to run through that data. So as a result, most enterprises struggle with one capturing the data, making decisions from it in real time and really operating it at the cost point that they need to operate it at. >> You know, you bring up a great point with respect to real time data access. And I think one of the things that we've learned the last couple of years is that access to real time data it's not a nice to have anymore. It's business critical for organizations in any industry. Talk about that as one of the challenges that organizations are facing. >> Yeah, when we started Aerospike, right? When the company started, it started with the premise that data is going to grow, number one exponentially. Two, when applications open up to the internet there's going to be a flood of users and demands on those applications. And that was true primarily when we started the company in the ad tech vertical. So ad tech was the first vertical where there was a lot of data both on the supply set and the demand side from an inventory of ads that were available. And on the other hand, they had like microseconds or milliseconds in which they could make a decision on which ad to put in front of you and I so that we would click or engage with that particular ad. But over the last three to five years what we've seen is as digitization has actually permeated every industry out there the need to harness data in real time is pretty much present in every industry. Whether that's retail, whether that's financial services telecommunications, e-commerce, gaming and entertainment. Every industry has a desire. One, the innovative companies, the small companies rather are innovating at a pace and standing up new businesses to compete with the larger companies in each of these verticals. And the larger companies don't want to be left behind. So they're standing up their own competing services or getting into new lines of business that really harness and are driven by real time data. So this compelling pressures, one, you know customer experience is paramount and we as customers expect answers in you know an instant, in real time. And on the other hand, the way they make decisions is based on a large data set because you know larger data sets actually propel better decisions. So there's competing pressures here which essentially drive the need one from a business perspective, two from a customer perspective to harness all of this data in real time. So that's what's driving an incessant need to actually make decisions in real or near real time. >> You know, I think one of the things that's been in short supply over the last couple of years is patience. We do expect as consumers whether we're in our business lives our personal lives that we're going to be getting be given information and data that's relevant it's personal to help us make those real time decisions. So having access to real time data is really business critical for organizations across any industries. Talk about some of the main capabilities that modern data applications and data platforms need to have. What are some of the key capabilities of a modern data platform that need to be delivered to meet demanding customer expectations? >> So, you know, going back to your initial question Lisa around why is data really a high value but underutilized or under-leveraged asset? One of the reasons we see is a lot of the data platforms that, you know, some of these applications were built on have been then around for a decade plus. And they were never built for the needs of today, which is really driving a lot of data and driving insight in real time from a lot of data. So there are four major capabilities that we see that are essential ingredients of any modern data platform. One is really the ability to, you know, operate at unlimited scale. So what we mean by that is really the ability to scale from gigabytes to even petabytes without any degradation in performance or latency or throughput. The second is really, you know, predictable performance. So can you actually deliver predictable performance as your data size grows or your throughput grows or your concurrent user on that application of service grows? It's really easy to build an application that operates at low scale or low throughput or low concurrency but performance usually starts degrading as you start scaling one of these attributes. The third thing is the ability to operate and always on globally resilient application. And that requires a really robust data platform that can be up on a five nine basis globally, can support global distribution because a lot of these applications have global users. And the last point is, goes back to my first answer which is, can you operate all of this at a cost point which is not prohibitive but it makes sense from a TCO perspective. 'Cause a lot of times what we see is people make choices of data platforms and as ironically their service or applications become more successful and more users join their journey the revenue starts going up, the user base starts going up but the cost basis starts crossing over the revenue and they're losing money on the service, ironically as the service becomes more popular. So really unlimited scale predictable performance always on a globally resilient basis and low TCO. These are the four essential capabilities of any modern data platform. >> So then talk to me with those as the four main core functionalities of a modern data platform, how does Aerospike deliver that? >> So we were built, as I said from day one to operate at unlimited scale and deliver predictable performance. And then over the years as we work with customers we build this incredible high availability capability which helps us deliver the always on, you know, operations. So we have customers who are who have been on the platform 10 years with no downtime for example, right? So we are talking about an amazing continuum of high availability that we provide for customers who operate these, you know globally resilient services. The key to our innovation here is what we call the hybrid memory architecture. So, you know, going a little bit technically deep here essentially what we built out in our architecture is the ability on each node or each server to treat a bank of SSDs or solid-state devices as essentially extended memory. So you're getting memory performance but you're accessing these SSDs. You're not paying memory prices but you're getting memory performance. As a result of that you can attach a lot more data to each node or each server in a distributed cluster. And when you kind of scale that across basically a distributed cluster you can do with Aerospike the same things at 60 to 80% lower server count. And as a result 60 to 80% lower TCO compared to some of the other options that are available in the market. Then basically, as I said that's the key kind of starting point to the innovation. We lay around capabilities like, you know replication, change data notification, you know synchronous and asynchronous replication. The ability to actually stretch a single cluster across multiple regions. So for example, if you're operating a global service you can have a single Aerospike cluster with one node in San Francisco one node in New York, another one in London and this would be basically seamlessly operating. So that, you know, this is strongly consistent, very few no SQL data platforms are strongly consistent or if they are strongly consistent they will actually suffer performance degradation. And what strongly consistent means is, you know all your data is always available it's guaranteed to be available there is no data lost any time. So in this configuration that I talked about if the node in London goes down your application still continues to operate, right? Your users see no kind of downtime and you know, when London comes up it rejoins the cluster and everything is back to kind of the way it was before, you know London left the cluster so to speak. So the ability to do this globally resilient highly available kind of model is really, really powerful. A lot of our customers actually use that kind of a scenario and we offer other deployment scenarios from a higher availability perspective. So everything starts with HMA or Hybrid Memory Architecture and then we start building a lot of these other capabilities around the platform. And then over the years what our customers have guided us to do is as they're putting together a modern kind of data infrastructure, we don't live in the silo. So Aerospike gets deployed with other technologies like streaming technologies or analytics technologies. So we built connectors into Kafka, Pulsar, so that as you're ingesting data from a variety of data sources you can ingest them at very high ingest speeds and store them persistently into Aerospike. Once the data is in Aerospike you can actually run Spark jobs across that data in a multi-threaded parallel fashion to get really insight from that data at really high throughput and high speed. >> High throughput, high speed, incredibly important especially as today's landscape is increasingly distributed. Data centers, multiple public clouds, Edge, IoT devices, the workforce embracing more and more hybrid these days. How are you helping customers to extract more value from data while also lowering costs? Go into some customer examples 'cause I know you have some great ones. >> Yeah, you know, I think, we have built an amazing set of customers and customers actually use us for some really mission critical applications. So, you know, before I get into specific customer examples let me talk to you about some of kind of the use cases which we see out there. We see a lot of Aerospike being used in fraud detection. We see us being used in recommendations engines we get used in customer data profiles, or customer profiles, Customer 360 stores, you know multiplayer gaming and entertainment. These are kind of the repeated use case, digital payments. We power most of the digital payment systems across the globe. Specific example from a specific example perspective the first one I would love to talk about is PayPal. So if you use PayPal today, then you know when you're actually paying somebody your transaction is, you know being sent through Aerospike to really decide whether this is a fraudulent transaction or not. And when you do that, you know, you and I as a customer are not going to wait around for 10 seconds for PayPal to say yay or nay. We expect, you know, the decision to be made in an instant. So we are powering that fraud detection engine at PayPal. For every transaction that goes through PayPal. Before us, you know, PayPal was missing out on about 2% of their SLAs which was essentially millions of dollars which they were losing because, you know, they were letting transactions go through and taking the risk that it's not a fraudulent transaction. With Aerospike they can now actually get a much better SLA and the data set on which they compute the fraud score has gone up by you know, several factors. So by 30X if you will. So not only has the data size that is powering the fraud engine actually gone up 30X with Aerospike but they're actually making decisions in an instant for, you know, 99.95% of their transactions. So that's- >> And that's what we expect as consumers, right? We want to know that there's fraud detection on the swipe regardless of who we're interacting with. >> Yes, and so that's a really powerful use case and you know, it's a great customer success story. The other one I would talk about is really Wayfair, right, from retail and you know from e-commerce. So everybody knows Wayfair global leader in really in online home furnishings and they use us to power their recommendations engine. And you know it's basically if you're purchasing this, people who bought this also bought these five other things, so on and so forth. They have actually seen their cart size at checkout go up by up to 30%, as a result of actually powering their recommendations engine through Aerospike. And they were able to do this by reducing the server count by 9X. So on one ninth of the servers that were there before Aerospike, they're now powering their recommendations engine and seeing cart size checkout go up by 30%. Really, really powerful in terms of the business outcome and what we are able to, you know, drive at Wayfair. >> Hugely powerful as a business outcome. And that's also what the consumer wants. The consumer is expecting these days to have a very personalized relevant experience that's going to show me if I bought this show me something else that's related to that. We have this expectation that needs to be really fueled by technology. >> Exactly, and you know, another great example you asked about you know, customer stories, Adobe. Who doesn't know Adobe, you know. They're on a mission to deliver the best customer experience that they can. And they're talking about, you know great Customer 360 experience at scale and they're modernizing their entire edge compute infrastructure to support this with Aerospike. Going to Aerospike basically what they have seen is their throughput go up by 70%, their cost has been reduced by 3X. So essentially doing it at one third of the cost while their annual data growth continues at, you know about north of 30%. So not only is their data growing they're able to actually reduce their cost to actually deliver this great customer experience by one third to one third and continue to deliver great Customer 360 experience at scale. Really, really powerful example of how you deliver Customer 360 in a world which is dynamic and you know on a data set which is constantly growing at north of 30% in this case. >> Those are three great examples, PayPal, Wayfair, Adobe, talking about, especially with Wayfair when you talk about increasing their cart checkout sizes but also with Adobe increasing throughput by over 70%. I'm looking at my notes here. While data is growing at 32%, that's something that every organization has to contend with data growth is continuing to scale and scale and scale. >> Yap, I'll give you a fun one here. So, you know, you may not have heard about this company it's called Dream11 and it's a company based out of India but it's a very, you know, it's a fun story because it's the world's largest fantasy sports platform. And you know, India is a nation which is cricket crazy. So you know, when they have their premier league going on and there's millions of users logged onto the Dream11 platform building their fantasy league teams and you know, playing on that particular platform, it has a hundred million users a hundred million plus users on the platform, 5.5 million concurrent users and they have been growing at 30%. So they are considered an amazing success story in terms of what they have accomplished and the way they have architected their platform to operate at scale. And all of that is really powered by Aerospike. Think about that they're able to deliver all of this and support a hundred million users 5.5 million concurrent users all with, you know 99 plus percent of their transactions completing in less than one millisecond. Just incredible success story. Not a brand that is, you know, world renowned but at least you know from what we see out there it's an amazing success story of operating at scale. >> Amazing success story, huge business outcomes. Last question for you as we're almost out of time is talk a little bit about Aerospike AWS the partnership Graviton2 better together. What are you guys doing together there? >> Great partnership. AWS has multiple layers in terms of partnerships. So, you know, we engage with AWS at the executive level. They plan out, really roll out of new instances in partnership with us, making sure that, you know those instance types work well for us. And then we just released support for Aerospike on the Graviton platform and we just announced a benchmark of Aerospike running on Graviton on AWS. And what we see out there is with the benchmark a 1.6X improvement in price performance. And you know about 18% increase in throughput while maintaining a 27% reduction in cost, you know, on Graviton. So this is an amazing story from a price performance perspective, performance per watt for greater energy efficiencies, which basically a lot of our customers are starting to kind of talk to us about leveraging this to further meet their sustainability target. So great story from Aerospike and AWS not just from a partnership perspective on a technology and an executive level, but also in terms of what joint outcomes we are able to deliver for our customers. >> And it sounds like a great sustainability story. I wish we had more time so we would talk about this but thank you so much for talking about the main capabilities of a modern data platform, what's needed, why, and how you guys are delivering that. We appreciate your insights and appreciate your time. >> Thank you very much. I mean, if folks are at re:Invent next week or this week come on and see us at our booth and we are in the data analytics pavilion and you can find us pretty easily. Would love to talk to you. >> Perfect, we'll send them there. Subbu Iyer, thank you so much for joining me on the program today. We appreciate your insights. >> Thank you Lisa. >> I'm Lisa Martin, you're watching theCUBE's coverage of AWS re:Invent 2022. Thanks for watching. >> Clear- >> Clear cutting. >> Nice job, very nice job.

(bright music) >> Welcome back everyone to theCUBE's coverage of AWS re:Invent 2021 in person. So a live event, physical in-person, also virtual hybrid. So a lot of great action online, check out the website. All the videos are there on theCUBE, as well as what's going on all of the actions on site and theCUBE's here. I'm John Furrier, your host with Dave Vellante, my cohost. Finally, we've got David Brown, VP of Elastic Compute Cloud. EC2, the bread and butter. Our favorite part of Amazon. David, great to have you back on theCUBE in person. >> John, it's great to be back. It's the first time I'd been on theCUBE in person as well. A lot of virtual events with you guys, but it's amazing to be back at re:Invent. >> We're so excited for you. I know, Matt Garman and I've talked in the past. We've talked in the past. EC2 is just an amazing product. It's always been the core block of AWS. More and more action happening and developers are now getting more action and there's well, we wrote a big piece about it. What's going on? The Silicon's really paying off. You've got to also general purpose Intel and AMD, and you've got the custom silicon, all working together. What's the new update? Give us a scoop. >> Well, John, it's actually 15 years of EC2 this year and I've been lucky to be on that team for 14 years and so incredible to see the growth. It's been an amazing journey. The thing that's really driven us, two things. One is supporting new workloads. And so what are the workloads that customers have available out there trying to do on the cloud that we don't support and launch new instance types. And that's the first thing. The second one is price performance. How do we give customers more performance at a continuously decreasing price year-over-year? And that's just driven innovation across EC2 over the years with things like Graviton. All of our inferential chips are custom silicon, but also instance types with the latest Intel Ice Lake CPU's, latest Milan. We just announced the AMD Milan instance. It's just constantly innovation across the ever-increasing list of instances. So super exciting. >> So instances become the new thing. Provision an instance, spin up an instance. Instance becomes, and you can get instances, flavors, almost like flavors, right? >> David: Yeah. >> Take us through the difference between an instance and then the EC2 itself. >> That's correct, yeah. So we actually have, by end of the year, right now we have over 475 different instances available to you whether it's GPU accelerators, high-performance computing instances, memory optimized, just enormous number. We'll actually hit 500 by the end of the year, but that is it. I mean, customers are looking for different types of machines and those are the instances. >> So the Custom Silicon, it's one of the most interesting developments. We've written about it. AWS secret weapon is one of them. I wonder if you could take us back to the decision points and the journey. The Annapurna acquisition, you started working with them as a partner, then you said, all right, let's just buy the company. >> David: Yeah. >> And then now, you're seeing the acceleration, your time to tapeout is way, way compressed. Maybe what was the catalyst and maybe we can get into where it's going. >> Yeah, absolutely. Super interesting story 'cause it actually starts all the way back in 2008. In 2008, EC2 had actually been around for just a little under two years. And if you remember back then, everybody was like, will virtualize and hypervisors, specialization would never really get you the same performances, what they were calling bare metal back then. Everybody's looking at the cloud. And so we took a look at that. And I mean, network latencies, in some cases with hypervisors were as high as 200 or 300 milliseconds. And it was a number of real challenges. And so we knew that we would have to change the way that virtualization works and get into hardware. And so in 2010, 2011, we started to look at how could I offload my network processing, my IO processing to additional hardware. And that's what we delivered our first Nitro card in 2012 and 2013. We actually offloaded all of the processing of network to a Nitro card. And that Nitro card actually had a Annapurna arm chip on it. Our Nitro 1 chip. >> For the offload? >> The offload card, yeah. And so that's when my team started to code for Arm. We started to work on our Linux works for Arm. We actually had to write our own operating system initially 'cause there weren't any operating systems available we could use. And so that's what we started this journey. And over the years, when we saw how well it worked for networking, we said, let's do it for storage as well. And then we said, Hey, we could actually improve security significantly. And by 2017, we'd actually offloaded 100% of everything we did on that server to our offload cards Leaving a 100% of the server available for customers. And we're still actually the only cloud provider that does that today. >> Just to interject, in the data center today, probably 30% of the general purpose cores are used for offloads. You're saying 0% in the cloud. >> On our nitro instances, so every instance we've launched since 2017, our C5. We use 0% of that central core. And you can actually see that in our instance types. If you look at our largest instance type, you can see that we're giving you 96 cores and we're giving you, and our largest instance, 24 terabytes of memory. We're not giving you 23.6 terabytes 'cause we need some. It's all given to you as the customer. >> So much more efficient, >> Much, much more efficient, much better, better price performance as well. But then ultimately those Nitro chips, we went through Nitro 1, Nitro 2, Nitro 3, Nitro 4. We said, Hey, could we build a general purpose server chip? Could we actually bring Arm into the cloud? And in 2018, we launched the A1 instance, which was our Graviton1 instance. And what we didn't tell people at the time is that it was actually the same chip we were using on our network card. So essentially, it was a network card that we were giving to you as a server. But what it did is it sparked the ecosystem. That's why we put it out there. And I remember before launch, some was saying, is this just going to be a university project? Are we going to see people from big universities using Arm in the cloud? Was it really going to take off? And the response was amazing. The ecosystem just grew. We had customers move to it and immediately begin to see improvements. And we knew that a year later, Graviton2 was going to come out. And Graviton2 was just an amazing chip. It continues to see incredible adoption, 40% price performance improvement over other instances. >> So this is worth calling out because I think that example of the network card, I mean, innovation can come from anywhere. This is what Jassy always would say is do the experiments. Think about the impact of what's going on here. You're focused on a mission. Let's get that processing of the lowest cost, pick up some workloads. So you're constantly tinkering with tuning the engine. New discovery comes in. Nitro is born. The chip comes in. But I think the fundamental thing, and I want to get your reaction to this 'cause we've put this out there on our post on Sunday. And I said, in every inflection point, I'm old enough, my birthday was yesterday. I'm old enough to know that. >> David: I saw that. >> I'm old enough to know that in the eighties, the client server shifts. Every inflection point where development changed, the methodology, the mindset or platforms change, all the apps went to the better platform. Who wants to run their application on a slower platform? And so, and those inflects. So now that's happening now, I believe. So you got better performance and I'm imagining that the app developers are coding for it. Take us through how you see that because okay, you're offering up great performance for workloads. Now it's cloud workloads. That's almost all apps. Can you comment on that? >> Well, it has been really interesting to see. I mean, as I said, we were unsure who was going to use it when we initially launched and the adoption has been amazing. Initially, obviously it's always, a lot of the startups, a lot of the more agile companies that can move a lot faster, typically a little bit smaller. They started experimenting, but the data got out there. That 40% price performance was a reality. And not only for specific workloads, it was broadly successful across a number of workloads. And so we actually just had SAP who obviously is an enormous enterprise, supporting enterprises all over the world, announced that they are going to be moving the S/4 HANA Cloud to run on Graviton2. It's just phenomenal. And we've seen enterprises of that scale and game developers, every single vertical looking to move to Graviton2 and get that 40% price performance. >> Now we have to, as analysts, we have to say, okay, how did you get to that 40%? And you have to make some assumptions obviously. And it feels like you still have some dry powder when you looked at Graviton2. I think you were running, I don't know, it's speculated anyway. I don't know if you guys, it's your data, two and a half, 2.5 gigahertz. >> David: Yeah. >> I don't know if we can share what's going on with Graviton3, but my point is you had some dry powder and now with Graviton3, quite a range of performance, 'cause it really depends on the workload. >> David: That's right. >> Maybe you could give some insight as to that. What can you share about how you tuned Graviton3? >> When we look at benchmarking, we don't want to be trying to find that benchmark that's highly tuned and then put out something that is, Hey, this is the absolute best we can get it to and that's 40%. So that 40% is actually just on average. So we just went and ran real world workloads. And we saw some that were 55%. We saw some that were 25. It depends on what it was, but on average, it was around the 35, 45%, and we said 40%. And the great thing about that is customers come back and say, Hey, we saw 40% in this workload. It wasn't that I had to tune it. And so with Graviton3, launching this week. Available in our C7g instance, we said 25%. And that is just a very standard benchmark in what we're seeing. And as we start to see more customer workloads, I think it's going to be incredible to see what that range looks like. Graviton2 for single-threaded applications, it didn't give you that much of a performance. That's what we meant by cloud applications, generally, multi-threaded. In Graviton3, that's no longer the case. So we've had some customers report up to 80% performance improvements of Graviton2 to Graviton3 when the application was more of a single-threaded application. So we started to see. (group chattering) >> You have to keep going, the time to market is compressing. So you have that, go ahead, sorry. >> No, no, I always want to add one thing on the difference between single and multi-threaded applications. A lot of legacy, you're single threaded. So this is kind of an interesting thing. So the mainframe, migration stuff, you start to see that. Is that where that comes in the whole? >> Well, a lot of the legacy apps, but also even some of the new apps, like single threading like video transcoding, for example, is all done on a single core. It's very difficult. I mean, almost impossible to do that multi-threaded way. A lot of the crypto algorithms as well, encryption and cryptography is often single core. So with Graviton3, we've seen a significant performance boost for video encoding, cryptographic algorithms, that sort of thing, which really impacts even the most modern applications. >> So that's an interesting point because now single threaded is where the vertical use cases come in. It's not like more general purpose OS kind of things. >> Yeah, and Graviton has already been very broad. I think we're just knocking down the last few verticals where maybe it didn't support it and now it absolutely does. >> And if an ISV then ports, like an SAP's ports to Graviton, then the customer doesn't see any, I mean, they're going to see the performance difference, but they don't have to think about it. >> David: Yeah. >> They just say, I choose that instance and I'm going to get better price performance. >> Exactly, so we've seen that from our ISVs. We've also been doing that with our AWS services. So services like EMR, RDS, Elastic Cache, it will be moving and making Graviton2 available for customers, which means the customer doesn't have to do the migration at all. It's all done for them. They just pick the instance and get the price performance benefits, and so yeah. >> I think, oh, no, that was serverless. Sorry. >> Well, Lambda actually just did launch on Graviton2. And I think they were talking about a 35% price performance improvement. >> Who was that? >> Lambda, a couple of months ago. >> So what does an ISV have to do to port to Graviton. >> It's relatively straightforward, and this is actually one of the things that has slowed customers down is the, wow, that must be a big migration. And that ecosystem that I spoke about is the important part. And today, with all the Linux operating systems being available for Arm running on Graviton2, with all of the container runtimes being available, and then slowly open source applications in ISV is being available. It's actually really, really easy. And we just ran the Graviton2 four-day challenge. And we did that because we actually had an enterprise migrate one of the largest production applications in just four days. Now, I probably wouldn't recommend that to most enterprises that we see is a little too fast, but they could actually do that. >> But just from a numbers standpoint, that's insanely amazing. I mean, when you think about four days. >> Yeah. >> And when we talked on virtually last year, this year, I can't remember now. You said, we'll just try it. >> David: That's right. >> And see what happens, so I presume a lot of people have tried it. >> Well, that's my advice. It's the unknown, it's the what will it take? So take a single engineer, tell them and give them a time. Say you have one week, get this running on Graviton2, and I think the results are pretty amazing, very surprised. >> We were one of the first, if not the first to say that Arm is going to be dominant in the enterprise. We know it's dominant in the Edge. And when you look at the performance curves and the time to tape out, it's just astounding. And I don't know if people appreciate that relative to the traditional Moore's law curve. I mean, it's a style. And then when you combine the power of the CPU, the GPU, the NPU, kind of what Apple does in the iPhone, it blows away the historical performance curves. And you're on that curve. >> That's right. >> I wonder if you could sort of explain that. >> So with Graviton, we're optimizing just across every single part of AWS. So one of the nice things is we actually own that end-to-end. So when it starts with the early design of Graviton2 and Graviton3, and we obviously working on other chips right now. We're actually using the cloud to do all of the electronic design automation. So we're able to test with AWS how that Graviton3 chip is going to work long before we've even started taping it out. And so those workloads are running on high-frequency CPU's on Graviton. Actually we're using Graviton to build Graviton now in the cloud. The other thing we're doing is we're making sure that the Annapurna team that's building those CPUs is deeply engaged with my team and we're going to ultimately go and build those instances so that when that chip arrives from tapeout. I'm not waiting nine months or two years, like would normally be the case, but I actually had an instance up and running within a week or two on somebody's desk studying to do the integration. And that's something we've optimized significantly to get done. And so it allows us to get that iteration time. It also allows us to be very, very accurate with our tapeouts. We're not having to go back with Graviton. They're all A1 chips. We're not having to go back and do multiple runs of these things because we can do so much validation and performance testing in the cloud ahead of time. >> This is the epiphany of the Arm model. >> It really is. >> It's a standard. When you send it to the fab, they know what's going to work. You hit volume and it's just no fab. >> Well, this is a great thread. We'll stay on this 'cause Adam told us when we met with them for re:Invent that they're seeing a lot more visibility into use cases at the scale. So the scale gives you an advantage on what instances might work. >> And makes the economics works. >> Makes the economics work, hence the timing, the shrinking time to market, not there, but also for the apps. Talk about the scale advantage you guys have. >> Absolutely. I mean, the scale advantage of AWS plays out in a number of ways for our customers. The first thing is being able to deliver highly optimized hardware. So we don't just look at the Graviton3 CPU, you were speaking about the core count and the frequency and Peter spoke about a lot of that in his keynote yesterday. But we look at how does the Graviton3 CPU work with the rest of the instance. What is the right balance between the CPU and memory? The CPU and the Hydro. What's the performance and the drive? We just launched the Nitro SSD, which is now we've actually building our own custom SSDs for Nitro getting better performance, being able to do updates, better security, making it more cloudy. We're just saying, we've been challenged with the SSD in the parts. The other place that scales really helping is in capacity. Being able to make sure that we can absorb things like the COVID spike, or the stuff you see in the financial industry with just enormous demand for compute. We can do that because of our scale. We are able to scale. And the final area is actually in quality because I have such an enormous fleet. I'm actually able to drive down AFR. So annual failure rates, are we well below what the mathematical theoretical tenant or possibility is? So if you look at what's put on that actual sticker on the box that says you should be able to get a full percent AFR. At scale and with focus, we're actually able to get that down to significantly below what the mathematical entitlement was actually be. >> Yeah, it's incredible. I've got a great, and this is the advantage, and that's why I believe anyone who's writing applications that has includes a database, data transfer, any kind of execution of code will use the stack. >> Why would they? Really, why? We've seen this, like you said before, whether it was PC, then the fastest Pentium or somebody. >> Why would you want your app to run slower? >> Unix box, right? ISVS want it to run as fast and as cheaply as possible. Now power plays into it as well. >> Yeah, well, we do have, I agree with what you're saying. We do have a number of customers that are still looking to run on x86, but obviously customers that want windows. Windows isn't available for Arm and so that's a challenge. They'll continue to do that. And you know the way we do look at it is most law kind of died out on us in 2002, 2003. And what I'm hoping is, not necessarily bringing wars a little back, but then we say, let's not accept the 10%, 15% improvement year-over-year. There's absolutely more we can all be doing. And so I'm excited to see where the x86 world's going and they doing a lot of great stuff. Intel Ice Lakes looking amazing. Milan is really great to have an AWS as well. >> Well, I'm thinking it's fair point 'cause we certainly look what Pat's doing it at Intel and he's remaking the company. I've said he's going to follow on the Arm playbook in my mind a little bit, and which is the right thing to do. So competition is a good thing. >> David: Absolutely. >> We're excited for you and a great to see Graviton and you guys have this kind of inflection point. We've been tracking for a while, but now the world's starting to see it. So congratulations to your team. >> David: Thank you. >> Just a couple of things. You guys have some news on instances. Talk about the deprecation issue and how you guys are keeping instances alive real quick. >> Yeah, we're super customer obsessed at Amazon. And so that really drives us. And one of the worst things for us to do is to have to tell a customer that we no longer supporting a service. We recently actually just deprecated the ECG classic network. I'm not sure if you saw that and that's actually off the 10 years of continuing to support it. And the only reason we did it is we have a tiny percentage of customers still using that from back in 2012. But one of the challenges is obviously instance hardware eventually will ultimately time out and fail and have hardware issues as it gets older and older. And so we didn't want to be in a place, in EC2, where we would have to constantly go to customers and say that M1 small, that C3, whatever you were running, it's no longer supported, please move. That's just a text that customers shouldn't have to do. And if they still getting value out of an older instance, let them keep using it. So we actually just announced at re:Invent, in my keynote on Tuesday, the longevity support for EC2 instances, which means we will never come back to you again and ask you to please get off an instance, because we can actually emulate all those instances on our Nitro system. And so all of these instances are starting to migrate to Nitro. You're getting all the benefits of Nitro for now some of our older zen instances, but also you don't have to worry about that work. That's just not something you need to do to get off in all the instance. >> That's great. That's a great test service. Stay on as long as you want. When you're ready to move, move. Okay, final question for you. I know we've got time, I want to get this in. The global network, you guys are known for AWS cloud WAN serve. Gives you updates on what's going on with that. >> So Werner just announced that in his keynote and over the last two to three years or so, we've seen a lot of customers starting to use the AWS backbone, which is extensive. I mean, you've seen the slides in Werner's keynote. It really does span the world. I think it's probably one of the largest networks out there. Customers starting to use that for actually their branch office communication. So instead of going and provisioning the own international MPLS networks and that sort of thing, they say, let me onboard to AWS with VPN or direct connect, and I can actually run the AWS backbone around the world. Now doing that actually has some complexity. You got to think about transit gateways. You got to think about those inter-region peering. And AWS cloud when takes all of that complexity away, you essentially create a cloud WAN, connecting to it to VPN or direct connect, and you can even go and actually set up network segments. So essentially VLANs for different parts of the organization. So super excited to get out that out of there. >> So the ease of use is the key there. >> Massively easy to use. and we have 26 SD-WAN partners. We even partnering with folks like Verizon and Swisscom in Switzerland to telco to actually allow them to use it for their customers as well. >> We'll probably use your service someday when we have a global rollout date. >> Let's do that, CUBE Global. And then the other was the M1 EC2 instance, which got a lot of applause. >> David: Absolutely. >> M1, I think it was based on A15. >> Yeah, that's for Mac. We've got to be careful 'cause M1 is our first instance as well. >> Yeah right, it's a little confusion there. >> So it's a Mac. The EC2 Mac is with M1 silicon from Apple, which super excited to put out there. >> Awesome. >> David Brown, great to see you in person. Congratulations to you and the team and all the work you guys have done over the years. And now that people starting to realize the cloud platform, the compute just gets better and better. It's a key part of the system. >> Thanks John, it's great to be here. >> Thanks for sharing. >> The SiliconANGLE is here. We're talking about custom silicon here on AWS. I'm John Furrier with Dave Vellante. You're watching theCUBE. The global leader in tech coverage. We'll be right back with more covers from re:Invent after this break. (bright 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. >> Despite all the talk about repatriation, hybrid and multi-Cloud opportunities, and Cloud is an increasingly expensive option for customers, the data continues to show the importance of public Cloud to the digital economy. Moreover, the two leaders, AWS and Azure, are showing signs of accelerated momentum that point to those two giants pulling away from the pack in the years ahead, with each firm's showing broad based momentum across their respective product lines. It's unclear if anything, other than government intervention or self-inflicted wounds will slow these two companies down this decade. Despite their commanding lead, a winning strategy for companies that don't run their own Cloud continues to be innovating on top of their massive CapEx investments. The most notable example here being Snowflake. Hello, everyone. Welcome to this week's Wikibon CUBE insights powered by ETR. In this breaking analysis, we provide our quarterly market share update for the big four hyperscale Cloud providers. And we'll share some new ETR data from their most recent survey. And we'll drill into some of the reasons for the momentum of these two companies and drill further into the database and data warehouse sector to see what, if anything, has changed in that space. First, let's look at some of the noteworthy comments from AWS and Microsoft in their recent earnings updates. We heard from Amazon, the following, "AWS has seen a reacceleration of revenue growth as customers have expanded their commitment to the Cloud and selected AWS as their Cloud partner." Notably, AWS revenues increased 39% in Q3 2021. That's a thousand basis point increase in growth relative to Q3 2020. That's an astounding milestone for a company that we expect to surpass $60 billion in revenue this year. Further, AWS touted the adoption of its custom silicon, and specifically its Graviton2 processors. AWS is fond of emphasizing Graviton's 40% price performance improvements relative to x86 processors, something we've reported on quite extensively. AWS is investing in custom silicon, encouraging ISVs to port their code to the platform so that customers will experience little or no code changes when they migrate. Again, we believe this is a secret weapon for AWS as its cost structure will continue to improve at a rate faster than competitors that don't have the resources or the skills or the stomach to develop such capabilities. Microsoft, for its part, also saw astoundingly good growth of 48% this past quarter for Azure. This is a company that we forecast will approach $40 billion in IaaS and PaaS public Cloud revenue this year. Microsoft's CEO, Satya Nadella, on its earnings call, emphasized the changing nature of Cloud expanding in a distributed fashion to the edge. He referenced Azure as the world's computer. Building on his statements last year that Microsoft is building out a powerful, ubiquitous, intelligent, sensing and predictive Cloud. Yes, folks, it does feel like we're entering the so-called Metaverse, doesn't it? Okay, to underscore the momentum of these two companies, let's take a look at the ETR breakdown of Net score, which measures spending momentum. This chart will be familiar to our listeners. It shows the breakdown of net score for AWS, with the lime green showing new adoptions. That's 11%. The forest green is spending more than 6% relative to the first half of this year. That's a very robust 53%. The gray is flat spending. That's 30% on a very, very large base. And the pink is spending declines of minus 6% or worse. That's 4%. And the bright red is defections i.e those leaving AWS. That's 1%. That's virtually non-existent. You subtract the reds from the greens and you get a net score of 59. Remember, anything over 40, we can still consider to be elevated. Let's look at that same data for Microsoft again. You have some new ads that lime green, that's 7%. The forest green is at 46% of customers spending more, which is an incredible figure for a company with revenues that will in the near term surpass $200 billion. And the red is in the low single digits. Buffered by its enormous PC software profits over the years, Microsoft is powered through its Window's Dogma and transitioned into a Cloud powerhouse. Let's now share some of our latest numbers for the big four hyperscale players, AWS, Azure, Alibaba and Google. Here, we show data for these companies from 2018 and our estimates for 2021. This data includes our final figures for AWS, Azure and GCP for Q3 with Alibaba yet to report. Remember, only AWS and Alibaba report IaaS revenue cleanly with Microsoft and Google, they give us a little breadcrumb nuggets that allow us to triangulate with our survey data and other intelligence. But it's our attempt to do an apples to apples comparison for those four companies using AWS and it's reporting as a baseline. In Q3, AWS reported more than $16 billion in revenue. We estimate Azure at 10 billion, Alibaba, we expect to come in at just under 3 billion, and GCP at 2.5 billion for the quarter. With three quarters of data in, with the exception of Alibaba, we're forecasting AWS to capture 51% of the big four revenue, the hyperscale revenue. And really we believe these are the only four hyperscalers. AWS will surpass 60 billion with Azure just under 40 billion, Alibaba approaching 11 billion, and Google coming in just under 10 billion for the year is our expectation. We forecast these four will account for $120 billion this year. That's a 41% increase over 2020 and the same collective growth rate as 2020 relative to 2019. We expect Azure to be 63% of the size of AWS revenue. So it is gaining share. Both of those companies, however, saw accelerated growth this past quarter with Alibaba and GCP's growth rates decelerating relative to last year. Now, let's take a closer look at those growth rates. This chart shows the quarterly growth rates for each of the four going back to the beginning of 2019. Both GCP and Alibaba are showing dramatic declines in growth rates, whereas, this past quarter Azure saw accelerated growth and AWS has now seen an increased rate of growth for the past two quarters. In fact, AWS' growth is about where it was in 2019 when it was around half of its current revenue size. And in 2019 growth was decelerating through the quarters as you can see where today that trend has reversed. It's quite amazing. All right, let's take a look at the broader Cloud landscape and bring back some ETR data. This chart that we're showing here, it shows net score or spending momentum on the vertical axis and market share or presence in the dataset on the horizontal axis. Note that red dotted line, anything above that we can still consider elevated and impressive. As when we've previously shared this data, AWS and Microsoft Azure are up and to the right. Now remember, this chart is not just counting IaaS and PaaS as we showed you earlier, it's however the customers views whatever they think Cloud is. And so they're likely including Microsoft SaaS in this picture. Which is why Microsoft shows larger than AWS despite what we showed you earlier. Nonetheless, these two are well ahead of the pack and the growth rates indicate that they're pulling away. But we've added some of the other players, most notably VMware Cloud on AWS. It's showing momentum as is VMware Cloud, which is VMware Cloud foundation and other on-prem Cloud offerings, even though it's below the red line for the on-prem piece, it's very respectable. The VMware Cloud on AWS has been consistently up above that red line. Has popped beneath it in some quarters, but it's very, very strong. As is, you know, Red Hat OpenShift, it's a little bit below the line, but it is respectable. We've superimposed this by the way. Red Hat OpenShift in the ETR platform is under the container orchestration taxonomy, but we'd like to put it in next to the Cloud players for context. That's how Red Hat sort of thinks about this as well. They think about OpenShift as Cloud. And then you can see the other players. Alibaba has got a small sample in the ETR dataset. Just does not enough presence in China. But Dell and HPE have started to show up in the Cloud taxonomy. So buyers are associating their private Clouds with Cloud. So Dell's Apex, HPE's GreenLake. So that's a positive. And you can see Oracle, which of course is OCI, Oracle Cloud infrastructure. And then IBM with its public Cloud. So, it's a positive that these on-prem players are showing up in this data, but the reality is the hyperscalers are growing collectively at 40% annually and the on-prem players are growing in the low single digits. So, and if you carve out the IaaS business of AWS and Azure, they're larger than most of the on-premises infrastructure players. And all the on-prem players are moving toward an as a service model, as I just alluded to. So, undoubtedly, hybrid multicloud edge are going to present opportunities for the likes of Dell, HPE, Cisco, VMware, IBM, Red Hat, et cetera. But they also present opportunities for the public Cloud players who have vibrant ecosystems and marketplaces much more diverse and deep than the traditional vendors. You know, we have a clearer picture of Microsoft's sort of hybrid and edge strategy because the company has such an enormous legacy business, it really had to think about that much more deeply. It wasn't a blank sheet of paper like AWS. It's going to be interesting at reinvent this year if new CEO, Adam Selipsky, will talk about this. And it will be good to hear how he's thinking about the next decade, how AWS thinks about hybrid and edge, I guarantee that with their developer affinity and custom Silicon capabilities, they're thinking about it differently than traditional enterprise players. And as we've stressed in this segment, they have across the board momentum. Now to quantify that, let's take a look at AWS as portfolio in the spending momentum within its product segments. This chart shows AWS's net scores or spending momentum in the areas where AWS participates in the ETR taxonomy. Again, note that red line. Anything above 40% is considered an elevated watermark. We're showing data from last October, this past July and the latest October 21 survey. That yellow line or a bar. What's notable is the yellow versus the gray bars up across the board for the most part, other than chime... And by the way, other than chime, everything is above the 40% mark as well. Now, we've highlighted database because we feel it's one of the most strategic sectors in a real battleground. So we want to drill into that a bit. Here's our familiar X Y graph showing Net score on the Y axis, remember, that's, again, spending momentum and market share or pervasiveness in the survey on the horizontal axis. This data, by the way, includes on-prem and Cloud database data warehouse. So keep that in mind. Let's start with one of our favorite topics; Snowflake. We've reported again and again and again, that we've never seen anything like this. The company's net score has moderated ever so slightly this quarter, but it's still just below 80%. Very highly elevated. Well, above that 40% mark. It's Snowflake's presence continues to grow as a gain share in the market. Snowflake is growing revenue in the triple digits. It's an insane pace, hence its current $115 billion market cap as of this episode. Now that said, all three US-based Cloud players there are above the 40% line with AWS and Microsoft having significant presence on the horizontal axis. You see Cockroach Labs, Redis, Couchbase, they're all elevated or highly elevated. Couchbase just went public this summer. So that may help with its presence. MongoDB, they're killing it. They have a $37 billion market cap as of this episode. The stock has been on a tear. You see MariaDB was also in the mix. And then of course you have Oracle, the database leader. Look, they continue to invest in making the Oracle database and other software like MySQL, the best solution for mission critical workloads, and they're investing in their Cloud. But you can see overall, they just don't have the momentum from a spending standpoint that the others do because the declines in their legacy business. And they've been around a long time. Those declines are not fully offset by the growth in Cloud database and Cloud migration. But look, Oracle is a financial powerhouse with a $250 billion plus market cap. And the stock has done very well this past year. Up over 60%. Cloudera is going private. So it can hide the pain of the transitions that it's undergoing between the legacy install bases of Cloudera and Hortonworks. It's just a tough situation. When the companies came together, Cloudera essentially had a dead end. Each of those respective platforms and migrate their customers to a more modern stack as part of its Cloud strategy. Ironic that it's name is Cloudera. You know, that's always a difficult thing to do. So as a private company, Cloudera can maybe get off that 90 day shot clock and buy some time to invest without getting hammered by the street. And you know, Teradata consistently has not shown up well in the ETR dataset. It's transitioned to Cloud and cross-Cloud still hasn't shown momentum in the surveys. So, look right now, it's looking like the rich get richer. So just to quantify that a little bit, let's line up some of the database players and look a little bit more closely at net score. This chart shows the spending momentum or lack thereof with the net score or spending velocity granularity that we described before. Remember, green is spending more, red is spending less, bright red is leaving the platform, bright green is adding the platform. You take red, subtract red from the green, and that gives you a net score. Snowflake, as we said, tops the list. You can see the granularity there. You can compare the performance. In a little different view to understand how these scores are derived, look, the ideal profile is a solid lime green, a big forest green, a not too large gray and ideally little or no bright red AKA defections. And you can see the green funnel in the gray increasing prominence as the vendor momentum declines. Interestingly, with the exception of Cloudera and Teradata, defections are all in the single digits or nonexistent. In the case of Snowflake, Redis, red is no red at all, but small sample, Couchbase has no defections and very little defection for the giant Microsoft. Incredibly impressive. This speaks to how hard it is to migrate off of a database no matter how disgruntled you are. The more common scenario is to isolate the database and build new functionality on modern platforms. Okay, so what to watch out for. Well, reinvent this coming up next month. Oh this month. It's the first time someone other than Andy Jassy will be keynoting as CEO. 15 years of Cloud, this is the 10th re-invent, which is always a market for the direction of the industry. I've said many times that the last decade was largely about IT transformation powered by the Cloud. I believe we're entering a new era of business transformation where the Cloud is going to play a significant role. But the Cloud is evolving from a set of remote services out there in the Cloud to an omnipresent platform on top of which many customers and technology companies can innovate. And virtually every industry will be impacted by Cloud. However it evolves in the coming decade. The question will be, how fast can you go? And how will players like AWS and Microsoft and many others that are building on top of these platforms make it easier for you to go fast? That's what I'll be watching for at re-invent and beyond. Okay, that's a wrap for today. Remember, these episodes, they're all available as podcasts, wherever you listen. All you got to do is search Breaking Analysis podcasts. Check out ETR's website at etr.plus. We also publish a full report every week on wikibon.com and siliconangle.com. You can get in touch with me, david.vellante@siliconangle.com. You can DM me @dvellante or comment on our LinkedIn posts. This is Dave Vellante for theCUBE insights powered by ETR. Have a great week, everybody. Stay safe, be well. And we'll see you next time. We'll see you at re-invent. (soft upbeat music)

(upbeat rhythmic music) >> Everyone, I'm John Furrier with theCUBE here at Palo Alto on a remote interview for a special video interview. The EC2 15th birthday party celebration event. Raj Pai, who's the Vice President of EC2 Product Management AWS is here with me. Congratulations on Amazon Web Services, EC2 with the compute. What a journey. 15 years old. Soon we got the keys to the car at a couple more years. So Raj, great to see you. You guys have been doing great work. Congratulations. >> Thank you. It's great being here. It's super exciting for me too. I can't believe it's 15 years and you know that big, we're still at the very beginning as you know, that we often say. >> The building blocks that have been there from the beginning really set the table, and it's just been fun to watch the innovation on behalf of customers that you guys have done at AWS and more, and for entrepreneurs and for developers, it just continues to be great and the edge is right on the corner. Wavelength, all the great stuff. But let's talk about the specific topic here that I really want to drill into is that as you look at the 15th year and birthday for EC2, okay? You're looking at the future as well. You're looking at the past, present and future. And one of the things that's most compelling about recent re-invent was the Graviton performance numbers are amazing. You guys have been building custom silicon for a while. You also worked with Intel and AMD. What is it about? What's the huge investment for you guys? Where do you started to see some returns? Are you seeing returns? And then why did AWS decide to build its own processors? >> Yeah, now, that's a really good question. And I mean, like with everything else we do in AWS, it's all about innovating on behalf of our customers. And one of the things our customers are telling us, that they continue to tell us is they want to see better performance at lower prices. And we've been able to deliver that with our hardware partners for the last 15 years. But as we've understood the workloads that run on EC2 and AWS, we saw an opportunity. Like, what if we were going to go and design our own processor that was really optimized for the sort of workload that customers run on the Cloud? And make design decisions when designing the CPU and the system and the chip around the CPU that does things like bring a lot more core local cache and speed up the parts of the operations that really benefit real-world workload. So, this isn't about benchmarks. It's about how do real world workloads perform and how do we build systems that optimize that performance? And with Graviton, we were able to hit the nail on the head. We were also very pleasantly surprised when we got our first chips off the line. And we're seeing that a customer, like about 40% performance improvement at significantly lower cost. And that's super exciting. And that's one of the reasons we're getting so much interest from our customers. >> I got to say as a geek and a tech nerd, I love the silicon development. And there's benefits there, also the performance is there. The thing that also is pretty obvious that's happening is and the world seeing it is the shift towards ARM-based computing. What kinds of customers and use cases are you seeing adopt to Graviton? And what kind of workloads were they running on? What are the things that surprise you guys, that didn't surprise me. Did you guys always talk about the upcheck and how everyone's leveraging it? What are some of the examples? Take us through some of the customers, use cases, workloads. What's surprising you and what's going on with Graviton? >> Yes, so I think that the biggest surprise for us is how broadly applicable it's been. So one of the things we did, we launched with reinvent is like we have different form factors of compute. We have memory-optimized instances that are good for databases and in memory caches. We have compute optimized for HPC and workloads that really take advantage of the performance of the chip and then we have general purpose workloads. And we we introduced Graviton variants of all those instance families And we're actually seeing the same sort of performance benefits across workload. So, and it's one of the reasons why companies like Metrol, and Snap and SmugMug, they move one workload over, they see the performance benefit and before you know it, they're starting to move workloads and mass over across kind of that spectrum. So, I think that's one of the biggest surprises is that Graviton seems to do well across a wide range and we're going to keep on introducing it more and more of instance families, because we've seen this uptick well. >> You're seeing a lot of people move to the Graviton. You mentioned a few of those early adopters who were pushing the envelope, and they're always kind of trotted out there as examples at reinvent, which is always fun to see what they're working on next. And now is that people see the Graviton2 instances, okay, the architecture's different, higher performance. How much effort do our customers typically need to move to Graviton2 instances? And what are some of the benefits they're seeing on performance and price performance? Can you talk about that transition? Because that's natural evolution for them. >> Yeah. It's actually a lot less than they originally think. So, some of the hardest effort is just getting them over the line to try it. So, one of the things that we tell our customers who are considering Graviton is it just takes one or two developers take one workload and go off for a couple of weeks and just try reporting it to Graviton. And more often than not, they come back to us in four or five days. They're like, it works. And we just had to do some testing and verification, but we were able to afford it because, you know, the operating system support was there, the ISP support was there and the tools that they use, and they're using most cases, modern programming languages like Python or Go or Java or PhD where, you know, interpret the language and it just run. And so there's very little lift in comparison to what people think it's going to be. And that's one of the reasons that, you know, one of the big announcements we made in the last few weeks is what we're calling the Graviton challenge, right? So it's a set of blueprints for customers to essentially have best practices on how to in four days take, you know, a piece of code and piece of that workload and execute it and run it and migrate it to the Graviton. And we're seeing a lot of interest in that as people in the community realize how easy that actually is. >> What are some of the cool price performance things that are emerging? Obviously it makes sense if you don't really need it, don't pay for it, but you have that option. A lot of people are going there. Is there a wave you see coming that Graviton2 is going to be really set up for that you kind of see some early signals coming in, Raj? Because, I can see the 64 bit. I can see where Graviton fits today. Obviously, performance is key. Is it certain things that are emerging? What's the main problems that it solves? >> Well, I think anything that's a multi-threaded architecture is going to do really well in Graviton because of the, we have really densely packed 64 course. And so you're going to see things like microservices and containers and workloads that are more, that are able to take advantage of that parallel execution do really, really well. And so, we say 40% performance improvement, but like, when our customers have gone and tried this, they've seen upwards of 50% depending on the workload. So yeah, it's going to be more your multi-threaded application. There's some applications that may not be a fit, like it can give a legacy, you know, for example, like, there's some software that hasn't yet been moved over and we're going to continue to invest super heavily in our whole ecosystem of hardware, for the longterm. So I think that because there's a great option and we just encourage them to try it. And then they'll learn from their experience what works and what doesn't. >> Wow. 15th birthday. Still growing up and it's starting to get more mature. You're the VP of Product Management. You have the keys to the kingdom. So, you have wide-ranging responsibilities. Share with us if you can. I know that you really can't say much, but try to give a little bit of teaser. You got Wavelength. I can see the dots connecting at the edge. You got Outposts, so we see all that emerging. I can almost imagine that this is going to get stronger. What should people think about? Where's the headroom for EC2 with Graviton and Graviton2? >> Yeah, I know. I think like, a new architect (mumbles) yourself. But like, our goal is to have AWS kind of everywhere our customers are. And that means the full power of AWS. So, I think you're going to see more and more of us having EC2 in compute capacity, wherever customers need it. That could be in an Outpost. That could be on their 5G network. That could be in a city right next to them, right? And you're going to see us continue to offer the variety, the selection of instances and platforms in all those locations as well. So, I think the key for us is to be ubiquitous and have compute power everywhere our customers need it, in the form factors they need it. >> That's awesome. Congratulations. I love the power. You can't go wrong with sending computers where the data is, where the customers are. AWS, Amazon Web Services. Building their own custom silicon with Graviton2 processors. This is EC2 continuing to grow up. Raj Pai, Vice President of EC2 Product Management. Thank you for coming on and sharing the update and congratulations on the 15th birthday to EC2. >> Yeah, thanks for having me. It's been great. Have a great Friday. >> All right. Great. I'm Jeffrey with theCUBE. You're watching theCUBE coverage of EC2's 15th birthday event. Thanks for watching. (soft rhythmic music)

(upbeat music) >> Welcome back to "theCube's" coverage of Mobile World Congress 2021. We're here in person and remote. This is a physical and virtual. It's a hybrid event, and "theCube's" got wall-to-wall coverage. I'm John Furrier, your host of "theCube." We've got a great guest here, Adolfo Hernandez, Vice-President, Global Telco Business Unit for Amazon Web Services, AWS. Adolfo, thank you for coming on remotely for this virtual hybrid Mobile World Congress. >> Thanks for having me, John, exciting. >> You have an impressive background in telecom industry. Over the years the technology industry has been great innovation. We've seen, I mean, how many Gs have been we've gone through, but I remember the days when wifi wasn't even around. So (laughing) You got a complete change in the past couple decades. This year, more than ever with the pandemic coming through this, you're starting to see some clear visibility on the trends, and also, this is the first Mobile World Congress in person since 2019, so a lot has changed. What is your view on the marketplace, and what is your message you're telling the telecom industry from Amazon's and your perspective? What do you see? >> Yeah, you're absolutely right, John. This is a fascinating time to be on the cloud, to be at Mobile World Congress. I remember Mobile World Congress 2020 was the first event that actually got canceled. So that was the beginning of the pandemic. And now, here we are, a year and a bit later, working with the leading telecommunications operators with the leading telecommunication sides based on solution providers and what better place that would be in doing that with AWS in this very transformational time in this space. We are supporting telecom operators around the world, as they reinvent communications in many different ways. This is not just one more G, we are definitely transforming the industry. Like any industry, we see telecom operators having to get simplification on their operations and transforming the IT side of the house. So they've go the internal IT, that needs a big transformation, they also got the network IT, everything related with OSS and BSS, and they need to migrate that to the cloud. And we've got a lot of experience by doing that with telcos around the world, to really help them accelerate that journey to the cloud. And we can help them with data center consolidation, migrations and a number of things. So we've got examples like GiffGaff, which is one of the largest MVNOs, and one of the first ones in Europe to go all in on the AWS cloud and they move all the data and the heart of the business there. So once you're sort of dealing with the network, the IT transformation, then you've got to go and look at how do you reinvent and accelerate the delivery of 5G connectivity? Well, that's very current as we're doing now. And we really want to help them because when they accelerate to the cloud, they get more flexibility, they get more agility, they get more cost effectiveness. And if you think about how traditional telco networks were built, where you have to provision a lot of systems you have to provision a lot on the base stations, and then you needed to provision a lot of systems on the Ram side, and then you needed to put aggregation centers, traffic centers, and then you would have the headquarters, and then you would have all the network functions, going from the radio all the way into the center. All of the systems needed to be provision for peak capacity. They sort of famous Mother's Day moment. As you move to the cloud, you can provision on the different parts of the cloud, you can provision on the AWS Outpost, you can provision on locals phone, you can provision on regions, and you leverage right away the experience that we've got on all of our infrastructure, reducing costs, getting a lot of flexibility and being able to embark, just and consume what you need. And, an example of that, it's been a Telefonica Vivo in Brazil. We talked about that a couple of weeks ago, and they've accelerated their move by deploying a 5G standalone cloud native platform. And that gives them a lot of automation capabilities. It gives them faster CI/CD/CT. So really cool stuff that you couldn't do in the old ways of building networks- >> It's interesting you mentioned CI/CD pipeline and developers. To me that's what comes to my mind when I think of AWS, the enablement of developers, now the enterprise. Now you've got the telco cloud and Amazon is not known for being a 5G player, but you guys are enabling a lot of 5G. Could you address that question? How is Amazon web services enabling 5G? What's your answer to that? >> So first of all, I have to say that 5G is an absolutely great example that this is a lot about moving to the cloud. 5G is cloud native, it's cloud friendly. You can virtualize pretty much every function. You can separate every function from the hardware and the software move everything to the cloud. And that is really lending itself to move to a cloud delivery model. As we were talking about earlier, we are enabling people to go and take the AWS infrastructure like AWS Outpost and bringing all the AWS infrastructure, all the services, all the APIs and all the tools that you have on AWS, virtually to any single location. And that allows you to really deploy themes like thousands of cell sites across a run, you couldn't do that before. On the AWS local zones, you can take everything that compute storage databases and a lot of different services. And those are perfect for large metro areas where you need to do a lot of network traffic aggregation, and this makes them really good to deploy in parts of the network core. Again, that's another re-innovation. And then you can look at then the regions and the regions have everything that you need from a compute storage and services perspective. And that those are really well suited for BSS for OSS to keeping the network running and to do all of that. And you can do that today, leveraging existing infrastructure. You don't have to acquire that, you don't have to provision, that you don't have to provision for the peak capacity and then you don't have to install and manage, and I think that's a serious breakthrough for the industry. >> Okay, so let me just capture that, 'cause I heard a bunch of things that I really like, cloud native 5G. What does cloud native 5G mean for the telco industry specifically? >> Well, I think if I had to put it down to one thing, it's just about making it really easy to roll out. And it's about being able to deploy easily to automate easily, so you can free up investment and you can free up resources and you can free up overhead. You can really start taking advantage of all that flexibility and scalability and automation that you get with the cloud and you apply that to a network, and that is the very first time we're able to do that in wireless. And it's just going to give you a lot of advantages. Look at Dish. We made this announcement with Dish that they are moving with one of the industry first 5G cloud native networks out there. Look at the example I talked about earlier, Telefonica Vivo, we're doing that 5G standalone solution. So you're going to be seeing, this is just the beginning, but this is going to be not the end because there's a lot of interest in getting these benefits. >> I saw the Dave Brown announcement with Dish a while back just recently. So I want to ask you, does Graviton processors play a role on the Dish deal? Do you mind answering that? If you comment on that? >> Yeah, I think you might remember Dave Brown being very proud of everything that Graviton2 processors can do in terms of increase in the price performance, helping telco operators, not only with the price performance factor, but also with the energy equation. So it's just really exciting to have that differentiation and being able to deliver that innovation and that value to telco operators in a cloud native 5G network. >> I got to ask you about some of the open source and cloud scale things coming together. That's a big trend I'm seeing here at Mobile World Congress. Openness, multi-vendor, scaling up quickly, provisioning stuff fast and easy, leveraging existing technologies and of course, developer friendly. So with that, I got to ask you, what's all the big deal about with this Open RAN. Obviously radios are key and wireless. What does Open RAN mean? Can you take us through, what's the importance of this? >> Yeah, Open RAN is an industry wide or mostly industry-wide initiative to look into effectively trying to apply some of these open and sharing models to the RAN. You've got vendors and you've got telco operators participating. But what we do and you know as well John, 'cause you've been working with AWS for a while, you know, that we're very customer focused, and 90% of what we do is what we hear that they are trying to solve because it's the things that matter to them. So what we engage with them, what we engage with somebody like Dish, and they tell us that they are interested in Open RAN, we will go and partner with the right partners who can provide the right solution to deliver on that Open RAN. And you've seen we signed agreements with the likes of Nokia to do research and solutions on cloud RAN. You also saw a couple of weeks ago, we did another collaboration announcement with Mavenir, to deliver not only cloud run, but I said of 5G solutions like IMS, the 4G 5G converge packet, or messaging and others. So we are engaging with the complete ecosystem on our customer's behalf to deliver whatever thereafter, and Open RAN is one of these topics and that we're delivering to operators like Deutsche and others in the market. >> Do you think that this new shift with cloud is going to increase the surface area? 'Cause that to me is the big theme I'm seeing what this new shift, as we look at, even telco cloud and the Edge, it's the classic surface area. And this is well known in the security world, but the there's no perimeter anymore. The surface area for security is everywhere. So things have changed. But telco just seems like the edge is expanding, you got satellite, you got space, you got more 5G, more commercial, so much more surface area. What's the impact going to be to the industry and to applications? >> Well, I think what we're seeing is 5G comes out there because there is a need for more data, more bandwidth obviously increased security, new standards, but there is also about latency, latency reduction. And I think that's really going to change the paradigm as we inject these increased responsiveness, these low latency, closer to the edge, and we bring the applications and we bring the compute and we bring storage as we do with wavelength right through to the edge as we are doing with Verizon, Vodafone, KDDI, SK Telecom and operators around the world. This is going to enable a number of transformational use cases for society, whether they are in virtual reality, whether they are with autonomous driving, whether it's about automating and getting more intelligence into manufacturing processes, there is just so much potential to transform society. And it all comes back with these sort of new 5G and some of the themes that enables moving closer to the edge. So as I said, really interesting times. >> Adolfo Hernandez, Vice President of Global Telco Business Unit with Amazon Web Services. Thanks for the great insight here on "theCube" for our Mobile World Congress coverage. Really, really great insight. Thanks so much. >> Thanks, John, delighted to be here. >> If you don't mind, I'd like to just quickly shift gears to something while I got you here on the industry. Adolfo you're very well known in the industry for someone who knows how to turn things around. You've done that in the past. You've been part of growth companies, you've been part of companies that have refocused. Telco has been a big change over people looking at this new opportunity as a growth opportunity. And people are looking at divesting some non-critical divisions and looking at acquisitions. I mean the private equity's on fire right now, and you're starting to see a lot more formation because there's more visibility into territory to take, there's more opportunities to be had. So there's more potential revenue than there is you can do on the cost cutting side. So everyone I talked to who's been in the industry has got their eyes are really popping out of their head, they're saying there's more opportunities if we can reconfigure our resources to take advantage of cloud. You're an expert in this area. For the folks out there who are in the boardrooms, cranking away thinking through how to organize for the cloud scale, what would be your advice to those teams? >> Well, I mean, there's a lot of insight to be had from the experience that AWS we've gained through the years, of doing this IT. And you definitely have to get a top down vision. Obviously it's really got to start at the C-suite, is moving to the cloud for what it bring. Either faster pace of innovation, the cost reduction, the agility. And that's you've got to be thinking about going to the cloud top down. Then the next thing you've got to go and say, "Okay, what are the parts of my operation "that I can go after with cloud? "Where do I start? "Do I start with the IT applications? "Do I start with some new go-to market initiatives? "Do I start by infusing some machine learning capabilities "into existing operations? "Do I start by building a data links "that I can go and monetize, "or I can go on and use to generate "best at customer service, "or I can go and fundamentally transform my networks?" Now, every telco's going to start in in different place, but I would say is you've got to start looking at that agility, that faster innovation, that better use of resources that cloud brings to telco for the very first time in a time in, in decades. And then if you're going to do that, I would strongly recommend people to talk to the provider that's got the capabilities, the broader set of services, the deepest set of services, and the most relevant experience to do that, 'cause we've been doing that in IT, and we've been working on telcos now for five plus years. And we've got pretty much every relationship. And as you know, John, this is really important. In telco you depend on collaborations on ISBs on software vendors, and every vendor out there, every software company out there will develop certainly on AWS. So we would be delighted to engage with them and help them move forward. >> Yeah, and Andy Jassy the CEO of AWS last year at re:Invent really made that the hallmark of his keynote around get those teams together, the executives top-down be a builder, think like a builder. McKinsey just put out a report, trillion dollar opportunities that no one sees yet that's coming. So a lot of emphasis on revenue, new revenue opportunities that are coming. And certainly this has been something that telcos been looking for for a long time. So great opportunity and thank you for sharing your insight. Appreciate it. >> Thanks, John. >> Okay this is "theCube's" coverage of ABS Mobile World Congress, 2021, I'm John Furrier, your host. Thanks for watching.

(gentle music) >> Okay, thank you Adam. Thank you everyone for joining us on the main stage here, folks watching, appreciate it. I'm John Furrier, Dave Vellante co-hosts of theCube. We're here in the main stage to talk to the two main players of Totogi, Danielle Royston, CEO as of today, the big news. Congratulations. >> Danielle: Yeah. Thank you. >> And Robin Langdon the CTO, Totogi. >> Robin: Thanks. So big news, CEO news today and $100 million investment. Every wants to know where's all the action? Why is this so popular right now? (Danielle chuckles) What's going on? Give us the quick update. >> Yeah, I met the Totogi guys and they have this great product I was really excited about. They're focused purely on telco software and bringing, coupling that with the Public Cloud, which is everything that I talk about, what I've been about for so long. And I really wanted to give them enough funding so they could focus on building great products. A lot of times, telcos, startups, you know they try to get a quick win. They kind of chase the big guys and I really wanted to make sure they were focused on building a great product. #2, I really wanted to show the industry, they had the funding they needed to be a real player. This wasn't like $5 million or a couple million dollars, so that was really important. And then #3, I want to make sure that we could hire great talent and you need money for compensation. And so $100 million it is. >> $100 million is a lot of fresh fat financing as they say. I got to ask you, what's different? Because I've been researching on the refactoring aspect of with the Cloud, obviously public cloud with AWS, a big deal. What's different about the charging aspect of this? >> Yeah I mean, charging hasn't been exciting, maybe ever. I mean, it's kind of like this really sort of sleepy area, but I think what the Totogi guys are doing is they're really coupling the idea of charging and network data to bring hyper-personalization to subscribers. And I think that's where it changes from being a charging engine to become an engagement engine. Telcos know more about us than Google, which is kind of crazy to think about it. They know when we wake up, they know what apps we use. If we call or text, if we game or stream and it's time to start using that data to drive a better experience to us. And I think to Totogi is enabling that. I'm super excited to do that. >> So Robin, I wonder if you could talk about that a little bit. I mean, maybe we get into the plumbing and I don't want to go too deep in it, but I think it's important because we've seen this movie before where people take their on-prem stacks, they wrap it in containers and they shove it into the Public Cloud and they say, "Hey, we're cloud too." If reading a press release, you guys are taking advantage of things like Amazon Nitro of course, but also Graviton and Graviton2 and eventually 3, which is the underlying capabilities, give you a cloud native advantage. Can you explain that a little bit? >> Yeah, absolutely. I mean, we wanted to build this in the Cloud using all of those great cloud innovations. So Graviton2, DynamoDB and using their infrastructure, just allowing us to be able to scale out. These all available to us to use and essentially free for us to use. And it's great, so as you say, we're not shoehorning something in that's decade's old technology, wrapping it in some kind of container and pushing it in. Which is just then, you just can't use any of those great innovations. >> And you've selected DynamoDB as the database. Okay, that's fine. We don't have to get so much into why, but maybe you could explain the advantage because I saw some benchmark numbers which were, like an order of magnitude greater than the competition, like share with us, why? How you were able to get there? And maybe share those numbers. >> Yeah, no, we do. So we just launched our benchmark. So, a million transactions per second. So we just blew away everyone else out there. And that's really because we could take advantage of all that great AWS technology in there and the database side we're using DynamoDB, where we had a huge debate about using what kind of database to go and use? There's a lot of people out there probably get very religious about the kind of database technology that you should be using. And whether it should it be SQL in-memory object database type technology, but really a single table design, gives you that true scalability. You can just horizontally scale that easily, across the whole planet. >> You know, Danielle. Again, I said that we've seen this movie before. There are a lot of parallels in telco with the enterprise. And if you look at enterprise SAS pricing, a lot of it is very static, kind of lock you in, per seat pricing, kind of an old model. And you're seeing a lot of the modern SAS companies who are emerging with a consumption pricing models. How are you guys thinking about pricing? >> Yeah, I don't know of any other company in telco that's starting to price by usage. And that is a very standard offering with the cloud providers, right? Google we know, Amazon, all those guys have a price by the API, price by the transaction. So we're really excited to offer that to telcos. They've been asking for it for awhile, right? Pay for what you need, when you need it, by the use. And so we're really excited to offer that, but I think what's really cool is the idea of a free tier, right? And so I think it's smaller telcos have a trade-off to make, whether, am I going to buy the best technology and pay through the nose and maybe at an unaffordable level, or do I compromise and buy something more affordable, but not as great. And what's so great about Totogi, it's the same product just priced for what you need. And so I think a CSP it'll, below 250,000 subscribers should be able to use the Totogi absolutely for free. And that is, and it's the same product that the big guy would get. So it's not a junior version or scaled back. And so I think that's really exciting. I think we're the only ones that do it. So here we go. >> Love the freemium model. So Robin, maybe you could explain why that's so much, so important in the charging space, because you've got a lot of different options that you want to configure for the consumer. >> Yeah. >> Maybe you could talk about sort of how the old world does that, the old guard and how long it takes and how you're approaching this. >> Yeah so it's, I mean traditionally, charging design, there's as you say, there's lots of different pricing leavers you want to be able to move and change to charge different people. And these systems, even if they say they're configurable, if they normally turn into an IT project where it takes weeks, months, even years to build out the system, you know, marketing can't just go in there and configure the dials and push out your new plans and tariffs. They have to go and create a requirement specification. They hand it down to IT. Those guys go and create a big change project. And by the time they're finished, the market's moved on. They're on to their next plan, their next tariff to go and build. So we wanted to create something that was truly configurable from a marketing standpoint. You know, user-friendly, they can go in there, configure it and be live in minutes, not even days or weeks. >> No, IT necessary. >> Robin: No IT necessary. >> So you know, I've been thinking about, John and I talk about this all the time, It's that there's a data play here. And what I think you're doing is actually building a data product. I think there's a new metric emerging in the industry, which is how long does it take me to go from idea to monetization with a data product. And that's what this is. This is a data product >> Yeah. >> for your customers. >> Absolutely, what Robin was talking about is totally the way the industry works. It's weeks before you have an idea and get it out to the market. And like Robin was mentioning, the market's changed by the time you get it out there, the data's stale. And so we researched every single plan in the world from every single CSP. There is about 30,000 plans in the world, right? The bigger you are, the more plans you have. On average, a tier one telco has 40 to 50 plans. And so how many offers, I mean think about, that's how many phones to buy, plans to buy. And so we're like, let's get some insight on the plans. Let's drive it into a standardization, right? Let's make them, which ones work, which ones don't. And that's, I think you're right. I think it's a data play and putting the power back into the marketer's hands and not with IT. >> So there's a lot of data on-prem. Explain why I can't do this with my on-prem data. >> Oh, well today that, I mean, sorry if you want to jump in. Feel free to jump in, right. But today, the products are designed in a way where they're, perpetually licensed, by the subscriber, rigid systems, not API based. I mean, there might be an API, but you got to pay through the nose to use it or you got to use the provider's people to code against it. They're inflexible. They were written when voice was the primary revenue driver, not data, right? And so they've been shoehorned, right? Like Robin was saying, shoehorned to be able to move into the world that we are now. I mean, when the iPhone came about that introduced apps and data went through the roof and the systems were written for voice, not written for data. >> And that's a good point, if you think about the telco industry, it seems like it could be a glacier that just needs to just break and just like, just get modern because we all have phones. We have apps. We can delete them. And the billing plans, like either nonexistent or it has to be all free. >> Well I mean, I'll ask you. Do you know what your billing plan is? Do you know how much data you use on a monthly basis? No one knows. >> I have no clue. >> A lot. >> No one. And so what you do is you buy unlimited. >> Dave: Right. >> You overpay. And so what we're seeing in the plans is that if you actually knew how much you used, you would be able to maybe pay less, which I remember the telcos are not excited to hear that message, but it's a win for the subscriber. And if you could >> I mean it's only >> accurately predict that. >> get lower and lower. I having a conversation last night at dinner with industry analysts, we're talking about a vehicle e-commerce, commerce in your car as you're driving. You can get that kind of with a 5G. The trend is transactions everywhere, ad-hoc, ephemeral... >> Yeah. >> The new apps are going to demand this kind of subscriber billing. >> Yeah >> Do people get this? Are you guys the only ones kind of like on this? >> No I think people have been talking about it for years. I think there's vendors out there that have been trying to offer this idea of like, build your own plan and all that other stuff but I think it's more than just minutes, text and data. It's starting to really understand what subscribers are using, right? Are you a football fan? Are you a golf fan? Are you a shopper? Are you a concert goer? And couple that with how you use your phone and putting out offers that are really exciting to subscribers so that we love our telco. Like we should be loving our telco. And I don't... I don't know that people talk >> They saved us >> about loving their telco. >> from the pandemic >> They saved us during the pandemic. The internet didn't crash, we got our zoom meetings. We got everything going on. What's the technical issue on solving these problems? Is it just legacy? Is it just mindset? Robin, what's your take on that? >> I'll keep talking as long as Robin will let me. (Daniel laughing) >> So the big technical issues, you're trying to build in this flexibility so that you can have, we don't know what people are going to configure in the future. It's minutes and text messages are given away for free. They're unlimited. Data is where it's at, about charging for apps and about using all that data in the network the telcos have, which is extremely valuable and there's a wealth of information in there that can be used to be monetized and push that out. And they need a charging system on top that can manage that and we have the flexibility that you don't have to go off and then start creating programs and IT projects that are going to do that. >> Well it's funny Danielle, you say that the telcos might not like that, right? 'Cause you might pay less. But in fact, that is the kind of on-prem mindset because when you have a fixed resource, you say, okay, don't use too much because we have to buy more. Or you overbuy to your point. The cloud mindset is, I'll try it. I'll try some more, I'll try some more. I'm aligning it with business value. Oh, I'm making money. Oh, great. I'm going to keep buying more. And it's very clear. It's transparent where the business value is. So my question is when you think about your charging engine and all this data conversation, is there more than just a charging engine in this platform? >> Well, I think just going back to what Robin was talking about. I think what Totogi is doing differently is by building it on the Public Cloud gives you virtually unlimited resources, right? In a couple of different directions, certainly hardware and capacity and scalability and all those other things, right? But also as Amazon is putting out more and more product, when you build it in this new way, you can take advantage of these new services very, very easily. And that is a different mindset. It's a different way to deploy applications. And I think that's what makes Totogi really different. You couldn't build Totogi on-premise because you need the infinite scalability. You need the machine learning, you need the AI of Amazon, which they have been investing in for decades, if they now charge you by the API call. And you get to use it like you were saying. Just give it a try, don't like it, stop. And it's just a completely different way of thinking, yeah. >> If I have to ask you a question about the Public Cloud, because the theme here in Cloud City is the Public Cloud is driving innovation, which is also includes disruption. And the new brands are coming in, old brands are either reinventing themselves or falling away. What is the Public Cloud truly enabling? Is it the scale? Is it the data? Is it the refactoring capability? What is the real driver of the Public Cloud innovation? >> I think the insight that CSPs are going to have is what Jamie Dimon had in banking. Like I think he was pretty famously saying, "I'm never going to use the Public Cloud. Our data is too precious, you know, regulations and all that stuff." But I think the insight they're going to have, and I hopefully, I do a keynote and I mentioned this, which is feature velocity. The ability to put out features in a day or two. Our feature velocity in telco is months. Months, months. >> Seriously? >> Yeah, sometimes years. It's just so slow between big iterations of new capability and to be able to put out new features in minutes or days and be able to outmaneuver your competition is unheard of. So the CSPs that starts to get this, it's going to be a real big get, and then they're going to start to.. (Danielle makes swishing sound) >> We just interviewed (Dave speaking indistinctly) a venture capitalist, Dave and I last month. And he's a big investor in Snowflake, on the big deals. He said that the new strategy that's working is you go to be agile with feature acceleration. We just talked about this at lunch and you get data. And you can dismantle the bad features quickly and double down >> Yup. >> on the winners. >> Ones that are working. So what used to be feature creep now is a benefit if you play it right? >> Danielle: It's feature experimentation. >> That's essentially what you- >> It's experimentation, right? And you're like, that one worked, this one didn't, kill that one, double down on this one, go faster and faster and so feature experimentation, which you can't do in telco, because every time we ask for a feature from your current vendor, it's hundreds of thousands, if not millions of dollars. So you don't experiment. And so yeah- >> You can make features disposable. >> Correct. And I think that we just discovered that on this stage just now. (group chuckling) >> Hey look at this. Digital revolution, DR. Telco DR. >> Yeah. >> Great to have you guys. >> This is super awesome. Thanks so much. >> You guys are amazing. Congratulations. And we're looking forward to the more innovation stories again, get out there, get the momentum. Great stuff. >> Danielle: It's going to be great. >> And awesome. >> Feature experimentation. >> Yeah. >> Hashtag. >> And Dave and I are going to head back over to our Cube set here, here on the main stage. We'll toss it back to the Adam in the studio. Adam, back to you and take it from here.

>> Announcer: From around the globe, it's theCUBE. With digital coverage of AWS reInvent Executive Summit 2020, sponsored by Accenture and AWS. >> Hello and welcome back to theCUBE's coverage of AWS reInvent 2020. This is special programming for the Accenture Executive Summit where all the thought leaders are going to extract the signal from those share with you their perspective of this year's reInvent conference as it respects the customers' digital transformation. Brian Bohan is the director and head of Accenture, AWS Business Group at Amazon web services. Brian, great to see you. And Chris Wegmann is the Accenture Amazon Business Group technology lead at Accenture. Guys this is about technology vision this conversation. Chris, I want to start with you because you're Andy Jackson's keynote. You heard about the strategy of digital transformation, how you got to lean into it. You got to have the guts to go for it and you got to decompose. He went everywhere.(chuckles) So what did you hear? What was striking about the keynote? Because he covered a lot of topics. >> Yeah. It was epic as always from Andy. Lot of topics, a lot to cover in the three hours. There was a couple of things that stood out for me. First of all, hybrid. The concept, the new concept of hybrid and how Andy talked about it, bringing the compute and the power to all parts of an enterprise, whether it be at the edge or are in the big public cloud, whether it be in an Outpost or wherever it'd be, right with containerization now. Being able to do Amazon containerization in my data center and that's awesome. I think that's going to make a big difference. All that being underneath the Amazon console and billing and things like that, which is great. I'll also say the chips, right? I know computer is always something that we always kind of take for granted but I think again, this year, Amazon and Andy really focused on what they're doing with the chips and compute and the compute is still at the heart of everything in cloud. And that continued advancement is making an impact and will make and continue to make a big impact. >> Yeah, I would agree. I think one of the things that really... I mean the container thing was I think really kind of a nuance point. When you've got Deepak Singh on the opening day with Andy Jassy and he runs a container group over there. When we need a small little team, he's on the front stage. That really is the key to the hybrid. I think this showcases this new layer. We're taking advantage of the Graviton2 chips, which I thought was huge. Brian, this is really a key part of the platform change, not change, but the continuation of AWS. Higher level servers, >> Yep. building blocks that provide more capabilities, heavy lifting as they say but the new services that are coming on top really speaks to hybrid and speaks to the edge. >> It does. Yeah. I think like Andy talks about and we talked about we really want to provide choice to our customers, first and foremost. And you can see that in the array of services we have, we can see it in the the hybrid options that Chris talked about. Being able to run your containers through ECS or EKS anywhere. It just get to the customers choice. And one of the things that I'm excited about as you talk about going up the stack and on the edge are things, most certainly Outpost, right? So now Outpost was launched last year but then with the new form factors and then you look at services like Panorama, right? Being able to take computer vision and embed machine learning and computer vision, and do that as a managed capability at the edge for customers. And so we see this across a number of industries. And so what we're really thinking about is customers no longer have to make trade-offs and have to think about those choices, that they can really deploy natively in the cloud and then they can take those capabilities, train those models, and then deploy them where they need to whether that's on premises or at the edge, whether it be in a factory or retail environment. I think we're really well positioned when hopefully next year we start seeing the travel industry rebound and the need more than ever really to kind of rethink about how we kind of monitor and make those environments safe. Having this kind of capability at the edge is really going to help our customers as we come out of this year and hopefully rebound next year. >> Chris, I want to go back to you for a second. It's hard to pick your favorite innovation from the keynote because, Brian, just reminded me of some things I forgot happened. It was like a buffet of innovation. Some keynotes have one or two, there was like 20. You got the industrial piece that was huge. Computer vision, machine learning, that's just a game changer. The connect thing came out of nowhere in my opinion. I mean, it's a call center technology so it's boring as hell, what are you going to do with that?(Brian and Chris chuckle) It turns out it's a game changer. It's not about the calls but the contact and that's distant intermediating in the stack as well. So again, a feature that looks old is actually new and relevant. What was your favorite innovation announcement? >> It's hard to say. I will say my personal favorite was the Mac OS. I think that is a phenomenal just addition, right? And the fact that AWS has worked with Apple to integrate the Nitro chip into the iMac and offer that out. A lot of people are doing development for IOS and that stuff and that's just been a huge benefit for the development teams. But I will say, I'll come back to Connect. You mentioned it but you're right. It's a boring area but it's an area that we've seen huge success with since Connect was launched and the additional features that Amazon continues to bring, obviously with the pandemic and now that customer engagement through the phone, through omni-channel has just been critical for companies, right? And to be able to have those agents at home, working from home versus being in the office, it was a huge advantage for several customers that are using Connect. We did some great stuff with some different customers but the continue technology like you said, the call translation and during a call to be able to pop up those keywords and have a supervisor listen is awesome. And some of that was already being done but we are stitching multiple services together. Now that's right out of the box. And that Google's location is only going to make that go faster and make us to be able to innovate faster for that piece of the business. >> It's interesting not to get all nerdy and business school like but you've got systems of records, systems of engagement. If you look at the call center and the Connect thing, what got my attention was not only the model of disintermediating that part of the engagement in the stack but what actually cloud does to something that's a feature or something that could be an element like say call center, the old days of calling the 800 number and getting some support. You got infra chip, you have machine learning, you actually have stuff in the in the stack that actually makes that different now. The thing that impressed me was Andy was saying, you could have machine learning detect pauses, voice inflections. So now you have technology making that more relevant and better and different. So a lot going on. This is just one example of many things that are happening from a disruption innovation standpoint. What do you guys think about that? Am I getting it right? Can you share other examples? >> I think you are right and I think what's implied there and what you're saying and even in the other Mac OS example is the ability... We're talking about features, right? Which by themselves you're saying, Oh, wow! What's so unique about that? But because it's on AWS and now because whether you're a developer working with Mac iOS and you have access to the 175 plus services that you can then weave into your new application. Talk about the Connect scenario. Now we're embedding that kind of inference and machine learning to do what you say, but then your data Lake is also most likely running in AWS, right? And then the other channels whether they be mobile channels or web channels or in-store physical channels, that data can be captured and that same machine learning could be applied there to get that full picture across the spectrum, right? So that's the power of bringing you together on AWS, the access to all those different capabilities and services and then also where the data is and pulling all that together for that end to end view. >> Can you guys give some examples of work you've done together? I know there's stuff we've reported on, in the last session we talked about some of the connect stuff but that kind of encapsulates where this is all going with respect to the tech. >> Yeah. I think one of them, it was called out on Doug's Partner Summit is a SAP Data Lake Accelerator, right? Almost every enterprise has SAP, right? And getting data out of SAP has always been a challenge, right? Whether it be through data warehouses and AWS, or sorry, SAP BW. What we've focused on is getting that data when you have SAP on AWS, getting that data into the Data Lake, right? Getting it into a model that you can pull the value out and the customers can pull the value out, use those AI models. So that's one thing we worked on in the last 12 months. Super excited about seeing great success with customers. A lot of customers had ideas. They want to do this, they had different models. What we've done is made it very simplified. Framework which allows customers to do it very quickly, get the data out there and start getting value out of it and iterating on that data. We saw customers are spending way too much time trying to stitch it all together and trying to get it to work technically. And we've now cut all of that out and they can immediately start getting down to the data and taking advantage of those different services that are out there by AWS. >> Brian, you want to weigh in as things you see as relevant builds that you guys done together that kind of tease out the future and connect the dots to what's coming? >> I'm going to use a customer example. We worked with, it just came out, with Unilever around their blue air, connected, smart air purifier. And what I think is interesting about that, I think it touches on some of the themes we're talking about as well as some of the themes we talked about in the last session, which is we started that program before the pandemic, but Unilever recognized that they needed to differentiate their product in the marketplace, move to more of a services oriented business which we're seeing as a trend. We enabled this capability. So now it's a smart air purifier that can be remote managed. And now when the pandemic hit, they are in a really good position, obviously, with a very relevant product and capability to be used. And so, that data then as we were talking about is going to reside on the cloud. And so the learning that can now happen about usage and about filter changes, et cetera can find its way back into future iterations of that picked out that product. And I think that's keeping with what Chris is talking about where we might be systems of record like in SAP, how do we bring those in and then start learning from that data so that we can get better on our future iterations? >> Hey, Chris, on the last segment we did on the business mission session, Andy Tay from your team talked about partnerships within a century and working with other folks. I want to take that now on the technical side because one of the things that we heard from Doug's keynote and during the partner day was integrations and data were two big themes. When you're in the cloud technically, the integrations are different. You're going to get unique things in the public cloud that you're just not going to get on-premise access to other cloud native technologies and companies. How do you see the partnering of Accenture with people within your ecosystem and how the data and the integration play together? What's your vision? >> Yeah. I think there's two parts of it. One there's from a commercial standpoint, right? Some marketplace, you heard Dave talk about that in the partner summit, right? That marketplace is now bringing together this ecosystem in a very easy way to consume by the customers and by the users and bringing multiple partners together. And we're working with our ecosystem to put more products out in the marketplace that are integrated together already. I think one from a technical perspective though. If you look at Salesforce, I talked a little earlier about Connect. Another good example technically underneath the covers, how we've integrated Connect and Salesforce, some of it being pre-built by AWS and Salesforce, other things that we've added on top of it, I think are good examples. And I think as these ecosystems these ISVs put their products out there and start exposing more and more APIs on the Amazon platform may opening it up, having those pre-built network connections there between the different VPCs of the different areas within within a customer's network and having them all opened up and connected and having all that networking done underneath the covers. It's one thing to call the APIs, it's one thing to have access to those and that's not a big focus of a lot of ISVs and customers who build those APIs and expose them but having that network infrastructure underneath and being able to stay within the cloud, within AWS to make those connections that pass that data. We always talk about scale, right? It's one thing if I just need to pass like a simple user ID back and forth, right? That's fine. We're not talking massive data sets, whether it be seismic data or whatever it be, passing those large data sets between customers across the Amazon network is going to open up the world. >> Yeah, I see huge possibilities there and love to keep on this story. I think it's going to be important and something to keep track of. I'm sure you guys will be on top of it. One of the things I want to dig into with you guys now is Andy had kind of this philosophical thing in his keynote talk about societal change and how tough the pandemic is. Everything's on full display and this kind of brings out kind of like where we are and the truth. If you look at the truth it's a virtual event. I mean, it's a website and you got some sessions out there, we're doing remote best we can and you've got software and you've got technology and the other concept of a mechanism, it's software, it does something It does a purpose. Accenture, you guys have a concept called Living Systems where growth strategy powered by technology. How do you take the concept of a living organism or a system and replace the mechanism staleness of computing and software? And this is kind of interesting because we're on the cusp of a major inflection point post COVID. I get the digital transformation being slow. That's yes, that's happening. There's other things going on in society. What do you guys think about this Living Systems concept? Yeah. I'll start. I think the living system concept, it started out very much thinking about how do you rapidly change your system, right? And because of cloud, because of DevOps, because of all these software technologies and processes that we've created, that's where it started making it much easier, make it a much faster being able to change rapidly. But you're right. I think if you now bring in more technologies, the AI technology, self-healing technologies. Again, you heard Andy in his keynote talk about the systems and services they're building to detect problems and resolve those problems, right? Obviously automation is a big part of that. Living Systems, being able to bring that all together and to be able to react in real time to either when a customer asks, either through the AI models that have been generated and turning those AI models around much faster and being able to get all the information that came in the last 20 minutes, right? Society is moving fast and changing fast and even in one part of the world, if something in 10 minutes can change. And being able to have systems to react to that, learn from that and be able to pass that on to the next country especially in this world of COVID and things changing very quickly and diagnosis and medical response all that so quickly to be able to react to that and have systems pass that information, learn from that information is going to be critical. >> That's awesome. Brian, one of the things that comes up every year is, oh, the cloud's scalable. This year I think we've talked on theCUBE before, years ago certainly with the Accenture and Amazon. I think it was like three or four years ago. Yeah. The clouds horizontally scalable but vertically specialized at the application layer. But if you look at the Data Lake stuff that you guys have been doing where you have machine learning, the data is horizontally scalable and then you got the specialization in the app changes the whole vertical thing. You don't need to have a whole vertical solution or do you? So, how has this year's cloud news impacted vertical industries? Because it used to be, oh, oil and gas, financial services. They've got a team for that. We got a stack for that. Not anymore. Is it going away? What's changing? >> Well. It's a really good question. I think what we're seeing, and I was just on a call this morning talking about banking and capital markets and I do think the challenges are still pretty sector specific. But what we do see is the kind of commonality when we start looking at the, and we talked about this, the industry solutions that we're building as a partnership, most of them follow the pattern of ingesting data, analyzing that data and then being able to provide insights and then actions, right? So if you think about creating that kind of common chassis of that in just the Data Lake and then the machine learning, and you talk about the nuances around SageMaker and being able to manage these models, what changes then really are the very specific industries' algorithms that you're writing, right, within that framework. And so, we're doing a lot and Connect is a good example of this too, where you look at it and yeah, customer service is a horizontal capability that we're building out, but then when you stamp it into insurance or retail banking, or utilities, there are nuances then that we then extend and build so that we meet the unique needs of those industries and that's usually around those models. >> Yeah. I think this year was the first reInvent that I saw real products coming out that actually solved that problem. I mean, it was there last year SageMaker was kind of moving up the stack, but now you have apps embedding machine learning directly in and users don't even know it's in there. I mean, cause this is kind of where it's going, right? I mean-- >> You saw that was in announcements, right? How many announcements where machine learning is just embedded in? I mean, CodeGuru, DevOps Guru, the Panorama we talked about, it's just there. >> Yeah. I mean having that knowledge about the linguistics and the metadata, knowing the business logic, those are important specific use cases for the vertical and you can get to it faster. Chris, how is this changing on the tech side, your perspective? >> Yeah. I keep coming back to AWS and cloud makes it easier, right? All this stuff can be done and some of it has been done, but what Amazon continues to do is make it easier to consume by the developer, by the customer and to actually embed it into applications much easier than it would be if I had to go set up the stack and build it all on them and embed it, right? So it's shortcoming that process and again, as these products continue to mature, right, and some of this stuff is embedded, it makes that process so much faster. It reduces the amount of work required by the developers the engineers to get there. So, I'm expecting you're going to see more of this, right. I think you're going to see more and more of these multi connected services by AWS, that has a lot of the AI ML pre-configured Data Lakes, all that kind of stuff embedded in those services. So you don't have to do it yourself and continue to go up the stack. And we always talk about Amazon's built for builders, right? But, builders have been super specialized and are becoming, as engineers were being asked to be bigger and bigger and to be be able to do more stuff and I think these kind of integrated services are going to help us do that >> And certainly needed more now when you have hybrid edge that they're going to be operating with microservices on a cloud model and with all those advantages that are going to come around the corner for being in the cloud. I mean, I think there's going to be a whole clarity around benefits in the cloud with all these capabilities and benefits. Cloud Guru I think it's my favorite this year because it just points to why that could happen. I mean that happens because of the cloud data.(laughs) If you're on-premise, you may not have a little Cloud Guru. you are going to get more data but they're all different. Edge certainly will come in too. Your vision on the edge, Chris, how you see that evolving for customers because that could be complex, new stuff. How is it going to get easier? >> Yeah. It's super complex now, right? I mean, you got to design for all the different edge 5G protocols are out there and solutions, right? Amazon's simplifying that. Again, I come back to simplification, right? I can build an app that works on any 5G network that's been integrated with AWS, right. I don't have to set up all the different layers to get back to my cloud or back to my my bigger data set. And that's kind of choking. I don't even know where to call the cloud anymore. I got big cloud which is a central and I go down then you've got a cloud at the edge. Right? So what do I call that? >> Brian: It's just really computing.(laughing) Exactly. So, again, I think is this next generation of technology with the edge comes right and we put more and more data at the edge. We're asking for more and more compute at the edge, right? Whether it be industrial or for personal use or consumer use, that processing is going to get more and more intense to be able to maintain under a single console, under a single platform and be able to move the code that I developed across that entire platform, whether I have to go all the way down to the very edge at the 5G level, right, or all the way back into the bigger cloud and how that processing in there, being able to do that seamlessly is going to allow the speed of development that's needed. >> Wow. You guys done a great job and no better time to be a techie or interested in technology or computer science or social science for that matter. This is a really perfect store. A lot of problems to solve, a lot of change happening, positive change opportunities, a lot of great stuff. Final question guys. Five years working together now on this partnership with AWS and Accenture. Congratulations, you guys are in pole position for the next wave coming. What's exciting you guys? Chris, what's on your mind? Brian, what's getting you guys pumped up? >> Well, again, I come back to Andy mentioned it in his keynote, right? We're seeing customers move now, right. Five years ago we knew customers were going to do this. We built a partnership to enable these enterprise customers to make that journey, right? But now, even more we're seeing them move at such great speed, right? Which is super excites me, right? Because I can see... Being in this for a long time now, I can see the value on the other end. We've been wanting to push our customers as fast as they can through the journey and now they're moving. Now they're getting the religion, they're getting there. They see they need to do it to change your business so that's what excites me. It just the excites me, it's just the speed at which we're going to to see the movement. >> Yeah. >> Yeah. I'd agree with that. I mean, I just think getting customers to the cloud is super important work and we're obviously doing that and helping accelerate that. It's what we've been talking about when we're there all the possibilities that become available, right? Through the common data capabilities, the access to the 175 somewhat AWS services. I also think and this is kind of permeated through this week at Re:invent is the opportunity, especially in those industries that do have an industrial aspect, a manufacturing aspect, or a really strong physical aspect of bringing together IT and operational technology and the business with all these capabilities and I think edge and pushing machine learning down to the edge and analytics at the edge is really going to help us do that. And so I'm super excited by all that possibility because I feel like we're just scratching the surface there. >> It's a great time to be building out. and this is the time for reconstruction, reinvention. Big theme, so many storylines in the keynote and the events . It's going to keep us busy here at SiliconANGLE on theCUBE for the next year. Gentlemen, thank you for coming on. I really appreciate it. Thanks. >> Thank you. All right. Great conversation. We're getting technical. We're going to go another 30 minutes A lot to talk about. A lot of storylines here at AWS Re:Invent 2020 at the Accenture Executive Summit. I'm John Furrier. Thanks for watching. (upbeat music)