>>LA Las Vegas. It's the cube covering AWS reinvent 2019 brought to you by Amazon web services and don't along with its ecosystem partners. >>Hey, welcome back to the cubes coverage of AWS reinvent 19 from Las Vegas. This is our third day of covering the event. Lots of conversations, two cube sets, as John would say, a Canon of cube content. Lisa Martin here with my esteemed colleague Justin. Um, and Justin, I have a couple of guests joining us. We've got to my left jus bhandarkar had a product for FreshWorks inc and Broughton Sahar VP and GM of machine learning services from Amazon. Gentlemen, welcome to the cube. You still have voices, which is very impressive after three days. A lot of practice it does or hiding out in quiet areas. Right? So Tay, Jess FreshWorks inc I souping on the website. Justin and I were talking before we went live, you guys have 150,000 of businesses using your technologies. I hadn't heard of FreshWorks, but it looks like it's about customer relationship management and customer experience. Tell our audience a little bit about what FreshWorks is and the technologies that you deliver. >>Okay. So we were founded in, uh, back in 2010. We were born in the cloud in the AWS cloud. Uh, and we started off as a, uh, customer support, uh, application. And we have grown on to now deliver a suite of customer engagement applications that include marketing and automation capabilities, CRM, uh, customer support and customer success. And so what we really are looking after is, is to deliver a value across the entire customer journey. Uh, you know, >>so there's been some big legacy CRMs around for a long time. What was the market opportunity back in 2010? The FreshWorks folks saw there's a gap here. We need to fill it. >>Yeah. We, well, we, uh, like any other startup, we decided to focus in one place and our focus, uh, was really around SMBs. We felt like SMBs were underserved and, uh, we felt like as rich as the technology is and the experiences have become, uh, we felt like we needed to democratize access to that. And because SMBs tended to have fewer resources and maybe, uh, in some cases weren't as tech savvy. Uh, we felt like they were kind of getting left behind. And so we wanted to step in there and make them whole and kind of offer them the same set of richness that you would expect, you know, for a large enterprise customer to have. And for that actually working in conjunction with AWS has been super important for us cause we have really been able to deliver on that promise. >>Maybe you can tell us a bit about the relationship between yourselves and FreshWorks. I believe the fresh works is built completely on AWS and always has been. >>Yeah. So how did that relationship begin and how has that grown as, as FreshWorks has grown into, into this massive company that you've become? >>Yeah, so, um, FreshWorks got off on AWS and then when we launched Sage maker and as you know, we have 700 tens of thousands of customers today doing the machine learning on AWS and on Sage maker. What customers have seen is that they get significant benefits in terms of features and developer productivity. And lower cost of ownership and FreshWorks saw that they could reduce that time to getting the models out by an order of magnitude. And their house was saying for example, that they used to take couple of days to get the models out to production. And by using Sage maker they were able to get it down to a couple of hours. And we have seen this happen with many other customers into it. For example, got down from six months to about a week. And just because of the productivity, performance and cost benefits that Sage makeup provides, you have seen the house FreshWorks and then many other companies, many of the customers more to AWS for the machine learning. >>Are they what are you using this machine learning to do? So you have all of these different models and we were talking a little bit before we went live about how you, how you use different models for different customers. But what are those models actually used to do? What service do they provide? >>Okay. So as you know, we have a set of these applications which are built around functional use cases. And so if you take a given customer, they might have multiple products from us and they might be doing multiple different use cases on us. And so you can quickly think of this as being, you know, maybe three to five specific use cases that require, you know, machine learning, you know, assistance. Uh, and so as a result, as we scale this up to the our entire, uh, set of customers, we now literally have thousands and thousands of these ML models that we have built, addressed, uh, geared to, uh, addressing specific pain points of that particular customer. Right? So it's all about catering the ML model for a specific use in a specific context. And then it's not only just about building it, uh, which, you know, obviously Sage Merker does a great job of helping us do that, but it's also about maintaining it over time and making sure that it stays relevant and fresh and so on. >>And again, working with AWS has been instrumental in for us to kind of stay ahead of that curve and make sure that we're continuing to drive accuracy and scale and simplicity into, uh, into, you know, into those particular use cases for customers. Then, you know, we released many features this year that makes this important. So one of the things that we have as part of Sage maker studio is a Sage make a model monitor that automatically monitors predictions and allows a customer to say, when are those predictions not being of the appropriate quality? And then we can send an allowance. So we are really building Sage maker out as a machine learning platform that they get all of the undifferentiated heavy lifting so that customers can really focus on what they need to do to build a model, train the model, and deploy the model. >>So in terms of your users, you mentioned too just the, the, the gap in the market back in 2010 was the small, the SMB space that probably something like a Salesforce or an Oracle was possibly too complex for an SMB. But now we're talking about emerging technologies, machine learning, AI. What is the appetite for the smaller, are you dealing with, I guess my question is a lot of SMBs that are born in the cloud companies, so smaller and more agile and more willing to understand and embrace technology versus legacy SMBs that might be, I don't want to say technology averse but not born within it. >>Yeah. So, so we, uh, we run through the entire gamut. So we obviously have, uh, you know, Silicon Valley based startups. We have more traditional companies around travel and hospitality and real estate and other, other verticals. Uh, and what we have really, really seen the commonality has been is that, uh, as good as the technology has become for AI and ML, uh, there is still some disparity in how people are able to consume it. Right. And if you have a lot of resources, a lot of skilled engineers, it is very easy for you to do that, thanks to all of the capabilities that are delivered by AWS. But in the other cases, uh, they do require more handholding specifically for those use cases that really impact them. Like how do I reduce my churn amongst customers? How do I maximize the chances of closing a deal? How do I make sure that the marketing campaign I run delivers on all of the, the objectives that I have? Right? So all of those things they re they need help. And so we are in there to kind of simplify that for them and leveraging all of the underlying technologies from AWS. We're able to deliver that together >>and going in from the beginning all in on AWS when AWS was only about four years old or so, right? Back in 2010. Um, talk to me about the opportunities that that is opened up for FreshWorks to evolve, you know, offer a suite of different solutions. Talk to us about Amazon and AWS is evolution and how quickly that they're evolving and developing new products and services as like fuel for FreshWorks business. >>Yeah. So really the big focus that we have always had is to deliver the right experiences that really impact end users. For those particular functional use cases around marketing, sales support and customer success, right? So as part of that, while we are focusing on on that experience, we also need to be focusing on delivering all of these services at scale, right? And with all the right security built in and all the right, uh, other, you know, tool set that that's built in. And so, so the synergy that we have found with between us and AWS is that we're able to rely on all of the right things for AWS to deliver upon. So they are also all about offering simple API APIs about making things scalable right from the get go about being extremely cost effective about uh, continuing to drive innovation. And these are all the things that drive us as well for our customers. And so it's been a very complimentary partnership from that respect is, you know, we kind of like go on this journey together and in our customer obsession is a key leadership principle. And so everything we do at AWS is really working back from the customer and making sure that we are really addressing all of the pain points. And making them successful? >>Well, because customer experience is a D it can be a deal breaker for companies, right? You think of you have a problem with your ISP and you call in or you go through social media or um, a chat bot and you can't get that problem resolved. As a consumer, you have so much choice to go to another vendor who might be able to better meet your needs or have the use the data to make sure they already know what's the problem. It's the same thing in the CRM space, right? If businesses don't have the right technologies to use the data to really know their customers, this customer's churn. And so it's really, we see CX as a driving force in any industry that if you can't get that right, customers are going to go, I'm going to go somewhere else because I have that choice. >>Yes. I mean customer expectations that you said have risen customer inpatients with bad experiences gone down. And one of the things that we have really focused on is as we go through this entire journey, we collect the data of that customer's journey. And we learn from it and we're able to visualize that for the sales person or the tech support person who's actually working with that customer. So they can actually see the journey of that customer. They visited the pricing page a couple of times, maybe they're interested to make a purchase or they visited the cancellation policy page. Okay, maybe I need to do something about that. Right. And so that is really been instrumental kind of in success success. And you know, what we are doing at AWS and Sage maker is making sure that all our customers get access to this technology. And that is where we start with how do we make machine learning accessible to all developers so that all of the experiences that we have gained at Amazon from investing in machine learning for the last 20 years, we take all of those learnings and make it available to our customers so they can apply machine learning for transforming their businesses. >>Yup. >>And that's exactly what it can be as transformational. Well gentlemen, thank you very much for joining Justin and me on the program talking to us about FreshWorks. What you guys are doing with Amazon and the opportunity to really dial up that CX experience with machine learning. We appreciate your time. >>Thank you. Thank you very much. >>All right. For my car is Justin Warren. I'm Lisa Martin and your Archie, the cube from AWS. Reinvent 19 from Vegas. Thanks.

live from san jose in the heart of Silicon Valley it's the cube covering AWS summit 2016 hey welcome back everyone we are live in Silicon Valley for AWS Amazon Web Services summit in Silicon Valley this is the cube silicon angles flagship program we go out to the events and extract the signal from the noise i'm john for with my co-host Lisa Martin our next guest is Lowell anderson senior manager product marketing of AWS Amazon Web Services welcome to the cube thanks for having me it's great to be here first time cube alumni welcome to the cube alumni list love to get you on because you know you're in the product team and you're in go to market as well as you gotta look into the product suites and one of the things that's been super impressive of AWS over the years since I've been following you guys for a decade since you started in the cube of the past four years is the tsunami of product releases the cadence of jesse's law I call it yeah and Amazon's law which is just constant slew of releases more and more every time not just reinvented yeah you get the summit's which are exploding right there were tiny right years ago right got new york and here what's what's coming out now what's the secret sauce how do you guys do it and give us some insight into what's what's happening here well you know for us innovations in our blood it's a part of our DNA it's what we do we're really except to over 460 new services and features and we'll hit over a thousand this year of new services and features launched compared to last year when we hit like 720 I think something about in that range so the innovation train train keeps going and you know the way we do it is we number one we really focus on our customers one of the benefits of the cloud is that we can innovate and roll out changes really rapidly for them so just that the whole cloud environment allows us to innovate very quickly and very rapidly so that that's exciting and you see that in just a number of releases that we think that I just asked the previous guest on how do you explain the Phenom that is AWS and you know Andy Jassy went to business school the same year us I did and back then the competitive strategy ethos was built some proprietary technology build a fence protected with guards and guys with guns and old you fold the line yeah with open source though the new model is you can't do that anymore so there's one the open source is now a Tier one citizen right and two there's no real walls to build around proprietary technology so the name of the game is speed yeah it's all about speed and the cloud really enables that agility that's one of the biggest benefits that our customers talk about is how freeing up breaking down the walls of your data center effectively so that now your compute and your analytics and your storage expand beyond the walls of that building as rapidly as possible and and the use of open source as you measured I mean we're we're big proponents of open source we have a lot of open source services that that we support as well and and trying to help the developer community really bring those types of technologies to the cloud and enable that's a big part of our success as well it's clear that the competitive strategy game in this new world that Andy and the team are executing is really just more features faster than the competition there is kind of an arms race going on but that is the open source game so with that what is the are the big announcements here obviously this show is much more developer focused yeah yes more getting get getting the weeds breakout sessions one of the key goods that are being talked about here down here in Silicon Valley we really wanted to bring some more technical topics to the table and talk in that vein talk about a couple really key areas around focused around big data and what we're doing to help enable both small and large enterprises use data across their companies in in a more and to develop more competitive applications and make it cheaper make it easier to use and make it more performant than they could possibly imagine without the cloud so using big data is one of the key themes of the conference that we had today and then the other thing that we wanted to talk about was this movement from how we've been architecting services our applications in the past from being based on server to using server list which is really a whole new architectural concept that's allowing our customers to build applications in ways that they could never do before and do it at a cost that they could never make feasible in the past there's some great examples of customer successes that dr. Matt would talked about in the keynote one redfin I think we've all in orcutt have experiences with buying and selling homes but i loved how we talked about friends don't let friends build data centers that in the future it's most organizations are going to run their own data centers are not going to run their own Dana centers and move to AWS benefits like becoming data-driven big data the more users more data more insight you also talked about some of the things coming up you mentioned it to about building with services versus building with servers talk to us about some of the if you could spend a little bit on some of those examples one that particularly spoke to me was what alumina is doing and germs of genome sequencing I got my masters in biological sciences a long time ago and that wasn't even a thought back then or certainly was a massively expensive Todd was a little bit more about how alumina is doing that with AWS and scaling at cost to really facilitate breakthroughs they're saving lives right right well you know that's an exciting example because people that weren't able to see the keynote alumina is the largest genomic secant sequencing company in the world and they've really been able to implement a new architecture that's brought genomic sequencing from an industry that was done you know just for very specific scientific purposes to now something that can be done all over the world to support disease research yeah and and its really the power of big data that's made that happen and the reason they selected AWS for that is really just the breadth and depth of the big data services that we provide along with the global deployments that we support with genomic data they mentioned that for many many many many countries in the world they don't want that genomic data to move outside the boundaries of their specific geographic region and so sensitivity eight AWS is one of the few very few cloud providers that has that level of geographic specificity so you can keep the data within that specific compliance issues as well with that too lots of compliance issues of course genomic sequencing lots of federal and health care and HIPAA type requirements surrounding all of that type of information that AWS with our focus on security you know is able to achieve so so number one you know it's this Geographic capability which is a lot of luminarias lee deploy this in a global way but second it's really just a depth of services that we offer whether it's the data warehousing using redshift whether it's the ability to process that data at scale on Hadoop using EMR whether it's the ability to then deliver that data across the world and visualize it and upload it from all those different genomic machines that they've that they put into their individual customers research facilities all of that is capability that AWS is able to deliver to them at a cost I think one of the things he talked about they were looking for I think a hundred percent reduction or a hundred times reduction in cost over trying to do this themselves and and we've achieved that help working together with them you know they've been able to achieve that well I got to get your thoughts on the hybrid cloud because you know I'll see Amazon gets was traditionally pigeon-holed as just public cloud the lines are blurring clearly the success you guys are having it's been moving into the enterprise obviously the CIA delia beat IBM on that was a again different instance in the gov cloud but again in the enterprise deals you're seeing yeah it's up against the Oracles and the IBM's yeah what and they're all talking hybrid yeah yeah how are you guys are dressing it from a product standpoint how do you talk to a customer says hey amazon slow down i love you guys but yeah we need a hybrid on-premise solution yeah that's great great great question i think you know first of all I would say that what we've always said at AWS is really in the fullness of time we expect that you know no Enterprise is really going to want to run their own data center and so we still see that as the end vision that that's that we're gonna achieve in the long run and that most of our customers want to achieve in the long run as well but a critical conversations that they have what are their requirements and you got here is it migration of data yeah that's it so that said you know there's there's a lot of work to do between now and this in this long-term vision and so you know a few of those things that need to be addressed like data migration and we're working really hard to help enterprises move data up into the cloud it seems like it'd be a simple thing right you you take a picture you upload it to dropbox what why is that so hard but when you're talking about terabytes of data that have been in the corporate data centers with applications for years and years and years moving that volume of data up to the cloud is a significant about moving back to the enterprise and then vice versa again making it available for them to use and to and to move back and forth is a critical component so we've done a lot of work on a specific set of features and capabilities to make that happen amazon direct connect or AWS direct connect is one of those services that allows our enterprise customers to establish a high bandwidth connection to AWS regions so that they can move data back and forth the interconnect or to direct connect not going through the internet yes direct connect allows them to leverage private backhaul to establish a really high bandwidth connection and so we'd curity wise alone that's a big deal absolutely it is and then earlier or last year we announced amazon s3 transfer acceleration which is a service that allows them to utilize our backhaul to actually accelerate the upload of data into s3 before you has to use the internet to upload data to s3 and now what we've done is really extended that down to customers where if we can accelerate the transfer of their data to s3 will do that using our backhaul network for them so the next question on top that compounds the problem with data which you guys are solving and because this is I agree is a big challenge for enterprise customers IOT just complicates the hell out of it so yeah that's all about moving data around putting computer where the edges yeah this whole edge of the network definition really plays into some of the train around serverless concepts that you were mentioning earlier how does that relate to the data equation yeah so a couple of things let's touch on IOT for so I OT brings a whole new level of complexity in terms of the number of devices and the distribution of data that you need to bring up into the cloud and so we released this service we call AWS IOT last year at reinvent and what that does is it makes it really easy for customers to acquire data from billions of devices that might be generating trillions of messages at a time and when you think about IOT devices it becomes almost more complex because these devices may or may not be online all the time they may not have a high bandwidth connection they may not have the processing capability on the device itself to be able to update and optimize and do a lot of complex computing so you need a specialized service that can work with those devices when there's intermittent connections pull very small messages from those devices and ingest them on a huge huge scale and so aw SI io t is a service that does that allows our customers to ingest those billions of messages and then connect them to AWS endpoints big data services like red shift and s3 and Kinesis and lambda to process that data and generate applications that could never really be conceived before and today i thought i thought that the the whole discussion from iRobot was super interesting about how they're using AWS IOT to connect their what they call their home robots it's as you know their Roomba vacuum devices to the cloud and and really enable a whole new set of applications and vision for the connected home really interesting stuff enabled by the clouds well before at least answer question I just want to quote been Keogh who was with iRobot his analyst over there Sarah scientist transition I won't get your reaction to maybe Lisa you can chime in he just tweeted transition to the cloud colon treat servers like cattle not pets transition to server less cloud architecture yeah Crete servers like roaches wow that's a pretty bold statement yeah yeah it is but note note not a pet yeah I don't cuddle like a roach Amy's not not cattle it's roaches put the roaches out so taught some mean serverless sure caring servers to roaches let's talk about that that's that yeah let's talk about the evolution a little bit i mean if you went back you know a few years back to when i was writing software as a graduate from from college when you wanted to start off a project first thing you had to do was go buy a server have it delivered find a place to put it plug it in cola network guys get aboard cole router your security what you had it all plugged in you had to put the operating system on it and then you could put your development system on it and then you could finally get started to be months later before you could actually get the project started and it seems strange to even talk about it now but back then this was a a key thing that that limited our ability to start projects forget the cost yeah it's the time and then when you when you finally got it done and you release the application and you wanted to scale it you had to buy more servers and put them in the racks and figure out where to put them and so this just slowed everything down and so when we move to the cloud and we got the ability to lease or really rent servers in the cloud it took away a lot of the hardware aspects of that but still when you had to scale you still needed to provision more servers and you still needed to maintain and patch those operating systems in that software stack and so now what's happening with serverless and with services like lambda is all that goes away now it doesn't mean there aren't servers under the hood of course lambda has lots of servers under the hood that are cranking away and implementing your code at lightning speed but the difference is is you don't have to manage them anymore you don't have to think about them you don't have to worry about them and so with lambda all you do is is load your code up into the cloud it's executed instantaneously when you need it to be executed it scales on demand so as your application scale we can scale the number of lamb functions in parallel to execute your code depending on the load that you're putting on it and you only pay when that code is actually running so you're no longer paying every month for those servers that are sitting in that room whether you're using them or not so we've talked a lot about the services a tremendous amount of services that that AWS is offering compared with the three that you started with ten years ago we've talked about hybrid cloud the opportunities there enterprise in fact you're CTO just last week in London was talking about the challenges with enterprise are really kind of the shift that they want to help customers grow through a lot of capabilities a lot of speeds and feeds what's the the message brother who's the target audience as we wrap up here who are you selling these services to within organizations as we see the empowerment moving from IT to the c-suite two lines of business who are you going after to share with them and get them to come on board as customers whether it's Enterprise yeah yeah I think that's a really good question and it speaks a little bit to our evolution of as a company as well wear when AWS started over 10 years ago really focused on our developer messaging but what we've seen is the just the impact of the cloud is so significant that across the entire suite of different whether that's executives whether that's IT managers whether that's developers there's a significant value proposition that that really at every level across the organization high level of interest and so we're starting to see I think you saw today just across all sizes of companies across all industries and in even within government and an education and public sector a strong interest in motion there's really no industry or government type of agency that's not you know right now looking at not just are they going to move to the cloud but how quickly can we get to the cloud and so that's that's really expanded the scope gray synopsis that actually what dr. Matt would talked about with how infiltrated amazon is into of all the industries big in public sector big and startups born in the cloud now getting to be big and enterprise yeah so low we got one minute left I want to get your thoughts on as an insider at Amazon I'll see you out in the field here you talk to customers in the product marketing you have to look at that 20 mile stare in the marketplace but also talk to the folks internally engineering product management or talk about the coolest things that are going on right now in AWS that people should know about is the machine learning is it lamb does it rip yeah Reds what's the fastest growing what's the coolest tech yeah what is what are the jewels on the table right now that we should look at it and then explore and discover more about you touch on so many cool things I mean the fastest growing service now today is Aurora Aurora is our own my sequel database engine that runs on RDS and it's responsive that's been tremendous it it really offers enterprise-class database capability at a tenth the cost of on-premises solution so that's been that's really our fastest-growing service now it's really exciting in terms of this other stuff that we're just seeing tremendous excitement about you mentioned machine learning predictive analytics a lot of the work that we've been doing at amazon it's been part of our history at amazon for a long time mike says that was thing all everyone wants that right right right so machine learning of course is is something that you know we're gonna continue to see significant cars coming soon I don't know about flying cars it's certainly not on our roadmap that I'm aware of but you know who knows what Steve or what Jeff is working on right now so but we don't have flying cars on our super exciting I'm yeah I'm sure this is but it's again it's a software driven world mark injury since new thesis is not software eating the world but software powering the world and I think that's a whole nother concept its patents you know it's a global economy so a lot of great stuff always a great surprise to see the coolness yeah they did to us the new stuff thanks so much for sharing thank you in the cube this is the cube bringing you all the goodness of AWS here at if your summit in Silicon Valley I'm John Ford Lisa Martin you're watching the q

>> From theCUBE studios in Palo Alto, in Boston, bringing you data-driven insights from theCUBE and ETR. This is breaking analysis with Dave Vellante. >> Despite the posture from some that big tech generally and Amazon specifically, should be regulated and/or broken apart, recent survey research suggests that Amazon faces many disruption challenges, independent of any government intervention. Specifically, respondents to our recent survey believe that history will repeat itself in that there's a 60% probability that Amazon Inc. will be disrupted by market forces, including self-inflicted wounds. Amazon faces at least seven significant disruption scenarios of varying likelihood and impact, perhaps leading to the conclusion that the government should just let the market adjudicate Amazon Inc's ultimate destiny. Hello, and welcome to this week's Wikibon CUBE insights powered by ETR. In this breaking analysis and ahead of AWS reinvent, we share the results of our survey designed to assess what if anything, could disrupt Amazon specifically, Amazon Inc. not just AWS. Now here's the background of the survey. Recently, in collaboration with author David Mitchell, the cube initiated a community research project to understand one, what scenarios could disrupt Amazon and two, what's the likelihood that each scenario would occur. We developed the scenarios, we tested them in small samples and then refine the questions and launch the survey. Here are the key findings. The survey asked respondents to rate the likelihood of each scenario disrupting Amazon on a scale of 1-10. As we show here, we have inferred that the ratings are a proxy for probability of disruption. And now in the interest of simplicity, we chose not to have respondents evaluate the impact of the disruption, at this time anyway. Here's the ranking by order of likelihood for each scenario. The end in the survey was just under 600 at 597 respondents. On average, across all scenarios, respondents indicate there's a 60% probability that Amazon will be disrupted. By one of, or some combination of these seven scenarios. Now by a notable margin, respondents felt that complacency, I.e a self-inflicted wound or series of wounds would be the most likely disruption scenario for Amazon. Now history in the industry would support this scenario is leadership in the tech business has proven to be transitory. The likelihood of a technological disruption was rated the lowest at 5.5, although some of the open-ended responses suggested that new models of computing could emerge. Look in the mainframe days, sharing resources in a timeshare model was very popular and then that gave way to a model of dedicated centralized infrastructure. The prevailing model then became distributed computing, which has seeded momentum back to a more centralized cloud. It's not inconceivable that with edge computing, the pendulum could swing back again. Now on balance, the remaining scenarios hovered around 60% likelihood individually, but taken all together The combination of these factors, it could be argued, present a multitude of challenges to Amazon Inc. Now, by looking at the distribution of responses, you can see further evidence of potential to disrupt the company. Here are the distribution results for each scenario and the order of the questions that they were presented. First, was government mandated separation, divestment and/or limits on Amazon's cloud computing, retail, media, credit card, and/or in-house product groups. 47% of the respondents believe there's a 70% or better chance of the government disrupting Amazon. Next question was major companies increasingly choose to do their own cloud computing and/or sell their products directly for competitive costs, security, or other reasons. Think of this as do it yourself cloud. That was not as prominent, but still 42% of respondents gave this a 70% chance or better. So think Walmart, the Walmart cloud or the target cloud. Okay, the next question was environmental policies raise, or the next scenario, environmental policies raise costs, change packaging delivery, recycling rules, and/or consumer preferences. If you think about it Amazon, they ship, you know, they order a toothpaste that comes in a box and every little piece you order every little item that you order comes in its own separate package. So environmental policy intervention showed a similar profile as above with a somewhat less likelihood in that 70% plus range. Okay next scenario was price or trade wars with the U.S and/or China create friction with e-commerce giants. So for instance, the China cloud or/and or e-commerce giants and protectionism would start to favor national players. Think again pricing wars, trade wars, you know, with China and others had a similar profile for likelihood as we just showed you earlier. But you know, what if you went, think about this thought exercise? What if you go on the web to order an item and AWS doesn't have it but Alibaba does. You know, maybe that's not such a huge factor at the U.S because really we don't buy directly from Alibaba but certainly outside of the United States particularly in Asia Pacific, it could be a scenario that disrupts Amazon Inc. Okay, the next scenario, major computing innovations, such as quantum edge or machine-to-machine obsolete today's cloud architectures. Tech disruptions ranked the lowest of all of these scenarios presumably because AWS is seen as on the cutting edge technically. So only 36% of respondents felt there was a 70% or better probability of this scenario disrupting Amazon. Next scenario, software replaces, centralized warehouses as delivery services are directly connected to suppliers and factories. Perhaps this is one of the most interesting scenarios I mean, imagine if Google creates software that upon a search, you can then order the item and have it shipped directly to you, no middle person. You know, like an airline ticket actually is today, except now it's physical goods. This direct model would disrupt Amazon's warehouse approach, but as you can see, it didn't really strike the respondents as highly likely. We think it's actually again, one of the more interesting scenarios, and it's certainly being put to the test by, for instance Alibaba, which really doesn't rely on a massive warehouse infrastructure. Now by far, the most likely scenario as rated by their respondents was this one; Complacency, arrogance, blindness, abusive power, loss of trust, consumer and/or employee backlash/boycotts. Think of it as self-inflicted wounds. More than half of the respondents indicated that there's a better than 70% chance that Amazon Inc. would shoot itself in the foot over time. And again, history would suggest this is consistent in the most likely pattern, especially when new executives come in. I mean, you saw this with famous companies at the time, like Wang, Digital, IBM eventually, Intel going through some of the challenges that we see today, Microsoft under bomber. And you know you see these founder led companies like Dell and Oracle they continue to thrive. Salesforce as well but it could be that today's executives and systems are more tuned to longevity, Andy Jassy is a long time Amazonian, Adam Selipsky the new CEO of AWS, he boomeranged back to AWS from Tableau, he's got a deep understanding of the company and its culture. So it's by no means assured that Amazon is going to trip up, However, taken together in combination, these factors suggest that government intervention may not be necessary. Indeed, the history of government breakups and pressure on big tech has been mixed and arguably futile. AT&T, IBM and Microsoft all came under close government scrutiny. and in the case of AT&T, the company was broken up. Generally these actions led to the US companies being less competitive, certainly was the case with AT&T is international telcos became dominant in the market. And in the case of IBM and Microsoft antitrust actions by the government while a distraction, were less a factor in the challenges that these firms ultimately faced and challenges to their leadership then were market disruptions. Think about an IBM unwittingly and famously handed its monopoly power to Intel and Microsoft in the PC era, and Microsoft under Ballmer, yeah kind of hugged onto its windows past and it became much less relevant in the industry until Satya Nadella initiated Microsoft's current hugely successful strategy, on top of the Azure cloud. The point is, despite the saber rattling of governments, history would suggest that market forces will be much more successful in moderating the power of giants like Amazon. We'll leave you with one last thought. At a $64 billion run rate and a 39% growth rate last quarter, AWS is the profit engine of Amazon. AWS accounts for over a hundred percent of Amazon Incs overall operating profit, so it was surprising to us last quarter when the stock dropped kind of precipitously after Amazon Inc. announced its earnings, its retail business underperformed, but AWS blew away expectations. The profit engine, the stock rebounded since then, and many investors saw it as a buying opportunity by the dip. But the point is that AWS is the most critical part of Amazon Inc. in our opinion. It helps fund Amazon's massive capex investment and gives Amazon a platform to enter other industries like payments, and content and groceries and other industries that Amazon wants to disrupt. So if you look at the ETR data across AWS's vast portfolio, The picture is very solid. This chart shows net score or spending momentum for AWS in its businesses comparing three survey snapshots, October 2020, July 21 and October, 2021, that's the yellow bar. Note, the comments from ETR at every sector, AWS spending velocity's up relative to last year. And we certainly saw that in this year's AWS results, accelerating growth with a much larger revenue base across the board and infrastructure, AI data, database analytics, core cloud, everything is up even chime, which is amazing because chime is horrible compared to other tools that you use of that like, but other than that weak spot, AWS is hitting on all cylinders. So what do you think should the government put the shackles on Amazon Inc? Or should it just let the market forces do their thing? Now, by the way we asked respondents, what else could disrupt Amazon, other than these seven scenarios? And we received some pretty interesting open-ended responses that we'll publish for your enjoyment, including my favorite; God could disrupt the Amazon. Okay, that's it for now, thanks to my colleague, David Mitchell for his excellent work on these scenarios. Don't forget these episodes of Braking Analysis, They're all available as podcasts, wherever you listen. All you're got to do is search Braking Analysis podcast. Don't forget to 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 directly David.volante@siliconangle.com or you can DM me at @DVellante. You can comment on our LinkedIn posts. This is Dave Vellante for The Cube Insights, powered by ETR. Have a great week, be safe, be well and we'll see you next time. (upbeat music)