>>Hey, welcome back and roll here. Live in San Francisco for Amazon web services summit. that's the hashtag. Go on Twitter. Go to crowd chat.net/aws summit. Rolling a special crowd chat document in the conversation. According every tweet in that room, join that community. I'm John furry, the founder's Silicon angle. This is the cube, our flagship program. We go out to the events and extract the signal from the noise. I'm joined my cohost, Jeff Frick filling in for Dave Volante. Uh, Jeff, always hard to fill up with Dave a lot day. Um, who was on those per, it doesn't look good on you. I know you're from California and Ariel Ariel Kelman worldwide marketing lead head of worldwide. Margaret Amazon. Welcome back to the cube. Thanks for having me. You were here last less than that. Reinvent, um, kinda markets itself, the company. I mean, you just tried to features out there on stage and keep on pushing new. What we try and do is lean back and just like the customers' testimonials. Let me come on. >>Yeah, I mean we try and just focusing on educating our customers. About what our services are doing, how customers are using them, which is something they ask for a lot. And then, you know, go pretty light on the marketing. Most technical people don't like to be marketed to and they find our approach quite refreshing. >>And when you're in the lead, you don't need to really worry about too much layer. You've got some meat on the bone, you've got great use cases, you've got great technology and a market leader in cloud and you're forging it a new territory. So there is a new element in the enterprise now coming in where you guys are being attacked. Certainly in the market. Google had some moves this week, as you can see, know IBM is doing HP, Oracle, the list goes on and on. So okay, those guys are kind of putting up the seawall for the big innovation way that you guys have built. The question is will it last? And so there is people really moving quickly to Amazon. The customer uptake is pretty comprehensive. So I'd say it's mainstream. So now as you go to the enterprise, you've got to do some messaging, right? You gotta you gotta have the innovation message. So what is the core opportunity for you there? >>There's a couple of things in the enterprise I think, you know, first of all we're helping people save money. We have organizations like Dow Jones that predict they're going to save over a hundred million dollars essentially by shutting down data centers and moving more of their infrastructure to the cloud. But I think the real interesting part is how we make these companies more innovative that if we can lower the cost of using technology to roll out their new projects, then essentially we take the cost of experimentation and have it almost approach zero. So then now if you want to try something new, the costs of failure aren't so high that they prevent people from sticking their neck out of the line and trying new things. And so we see a lot of these companies are adopting us more heavily. Their culture is changing their employees or are excited about trying things because when they try something out, the cost of failure is a fraction of what it was before because they don't have to buy servers. >>Delta buys all this equipment, get data center space, they can try something quickly. If it works, great, they expand. If not, they don't have to live with all this expense that they tried it out. So it's increasing the pace of innovation and also allowing more people in the company to be able to try new things, involve technology because we're eliminating these gatekeepers where before if you get a project required a lot of money, a lot of infrastructure, think about the committees you have to go, all the justifications. But if anyone could go spin up these resources with self-service, totally changed the dynamics of who can innovate. >>Yeah. I mean the whole try before you buy the puppy dog close as they used to say in the sales tactics is, let me try it before you buy it. Yeah. Shadow it as the, legitimize the fact that for very little cost and collateral damage, as Andy talks about, you can get something up and running pretty quickly. So the old I, that'll never work. Comment. That's a killer phrase of innovation gets eliminated because, no, no, no, I already tried it. Here's the numbers. Is that, is that a big part of it too? >>I'm a little bit, I mean it's almost like we need a new term there. There's, you know, people talk about shadow it and what we typically see is that once you give the CIO the keys to the cloud infrastructure and you set up a governance approach where you can decide what people can do, how much money they can spend, what things they can try. Um, then you get the best of both worlds. You still have a vetted platform from a security perspective. You have governance controls and sure people doing the right thing, but then it doesn't have to say, no, sorry, you've got to wait in line. You got to wait till next year. Um, so that is the new model that we're seeing where you're seeing developers distributed across the organization and smaller official it departments, but more people doing it stuff in the company because everyone can have access to infrastructure when they go big on cloud, especially with AWS. >>And are they getting it? Are the corporate it guys getting it that this is a good thing for them and they can leverage this to actually add more value in the company and enable more at the end of the day. More ideas. Yeah, absolutely. The companies that we talked to, look, they've got a lot of questions. If you're a big organization, you want to know if we can meet your security requirements, your compliance requirements. Can you run a sends Alaska? Well look, we want to do two things. We want to run the software the last 20 years in the cloud. Can you help us with that? And then we want to build these new cloud native applications so we can be as agile and efficient as some of these new internet startups that now we're competing with. And so we spent a lot of time with them to talk through what it should do first, how I should think about it, what apps make sense to run on us and, and you know, more importantly with the sequences, which lady first us should ask us. Like we want to go, we've, we've played around, we've tested, we've had lots of developers using this for years, but now we want to go big. I having a material percentage of our infrastructure in the cloud so we can fundamentally change how it adds value to the business. And like those are the conversations we love having the customers. >>I want to ask you about just to show by, just to get, check this out. Check the box on the interview here because I want to make sure people can understand Amazon. Reinvent your mega show. That's your global conference. And why don't you explain, explain, reinvent versus the, >>sure. So the AWS summits, um, it's our three one day event, uh, that we do maybe like 14, 15 around the world. It's two purposes. One for people that are new to AWS, they can come in one day, get an overview of what it's about, how to use it and get inspired on what they can do with it. And then for our existing customers who are having users, they get an update on what's new, which may sound kind of tactical, but we released them, you gotta do stuff right. And so that's of my biggest challenge is how do we make sure that people know what all the new stuff is. They come here for one day, go to our keynote, go to a bunch of breakout sessions, do some training, and they get ramped up on everything we've done in the past year. Speaking of it, so we had you on last year and we were here. >>So what's been the big change from 2013 to 2014? I mean, we've had a lot of new services that we've released. We're going to new areas and think about Amazon workspaces. It's more of an it business application, right? Um, what you saw our demo today wasn't people coding. It was someone actually as an end user using, um, a virtual desktop on their iPad, on their computer. And so different types of applications, but we're, we're still going after that same goal, which is to allow these enterprise it organizations to take advantage of the cloud with more workloads. Essentially the larger percentage of their projects that they're doing that we can help them with, the happier they are with the relationship and the test, the test dev conversation seems to have simmer down quite a bit where it seemed like last year that was, and that was everybody's kind of testing waters. >>That's where you had initial traction, the initial shadowing it and that, that seems to really have dying down. And I mean, I think it's kind of gone mainstream or whatever is past mainstream where, you know, if you're a big SAP shop and your developers don't have their own SAP development environments, you're kinda, you're behind the curve. Same for Oracle, for SharePoint, if that's the new standard. Um, and so people don't talk about as much because they're already doing it. Right. It's, it's a, you know, the idea of well, you know, what are the big bets, um, you know, what should we use it for next? Should I do big data analytics using, um, like our Redshift product or should they build new high-scale web applications? Should this be my mobile infrastructure? That's where more of the conversation is coming on. Now >>Eric, I want to ask you about marketing and kind of one-on-one, you know, take me through the business school level marketing relative to your vision of Amazon and how the company's operating. I see Andy sets the tone up on stage, very customer centric. We hear all the people on Amazon talk about, Hey, we listened to the customer. They said they're tight on the messaging, they're really tight on the messaging. But you know, you starting to see, you know, tweets on the wild emerge. Like the new strategy for Amazon is price reduction as a service. And you know, it's like, so you seeing these messages come out. So is that, is that your plan to message just the price reduction to show the continuous improvement in terms of cost reductions and improvements in innovation and capability and just kind of be humble. >>So what, what our market organization is trying to do is to educate our customers in the easiest, most scalable way about what our services do, what are the best practices, how could they can use them and how they can save money near site. Andy talked about it a little bit earlier. We want our customers to feel like they're spending the least amount of money they need with us cause we want a longterm relationship and a price reductions. I mean it's probably one of the top three or four most boring parts of marketing AWS because every service team is trying to relentlessly take costs out of uh, their services. And when they get to a certain point, we pass those cost savings along to customers. It's kind of like clockwork two of them. Is that an internal metric for you guys? You guys all under pressure or mandated? >>That's just the DNA of the company. Let's get the cost out. Let's strap, distract away, cost and complexity. There's some bragging rights, little competition between the teams. How many price reductions have you done? I mean, it's a sign that they're being efficient and that they're making customers happy. It's a great metric. Price reduction and also feature increase. So again, now with flash, you start to see some new stuff hit the table. Yeah, that's part of the plan, right? Price reductions and more functioning. I mean the most, one of the most important parts of our overall strategy is to constantly innovate both on building new services, let people run more things in the cloud, but then also adding new functionality based on feedback we get from our customers. We'd like to release services relatively early versus sitting in an ivory tower trying to figure out what the perfect feature set is. >>We'll get this out early. Uh, get feedback from customers because you know, we're often surprised what people do with these services and uh, you know, they take on a life of their own. But ultimately that's how we get the best. You guys are like, you guys are like the big gorilla in the industry, but I was talking to someone last night at a VIP event, San Francisco, all these CEO of venture capitalists, Oh, Amazon, they loaded with money. You know, I'm like guys, they're like a lean startup. So that's pretty much the case. We've validated in talking to some folks, you guys are like a startup. I mean you're huge, you got great resources, but it's not like you're like Swoon and money thrown it around. You guys are very tight on budgets. You don't like just throwing around money. If you want to know about Amazon's culture, just type into Google, Amazon leadership principles. >>And there's about a, is it about a dozen or so core values? One of them is frugality. It's kind of, you know, part of how we operate the company and believe in what it means is that we only spend money on things that are useful to our customers. And that's a real good grounding. And then you see, we don't have 80 foot tall posters of our products or our executives here. You know, we spend the time on computers for people to do training and when we're planning events, we want to have everything focused on stuff that's useful to customers. We build the service too. We try and be relentless and driving cost out of our suppliers so we can pass on those costs and these customers. And it's just, you know, when you, um, when you operate a frugal fashion where you really think about costs, you end up being scrappy or, and you end up innovating more, it sends a good signal to your customer base because it's like a probably a laundry list of things that you guys have laid out then you still need to do and do innovate. >>Yes, exactly. If you wasting money on, you know, weirdness people that say, Hey, we didn't, why aren't they spending that energy on building new stuff? Exactly. Like we didn't 10 Howard street and close off the road to have a rock concert held companies. I mean, we have our crowd chat. Have you've seen that? We built that all on Amazon would not be possible without it. We hear testimony and testimonial customers saying, Hey, Amazon would have been 15 people minimum just to actually manage the gear on an offside without avatars. So yeah, it's just pretty massive. So, so with that, I got to ask you, the marketing question is how do you roll up all that Goodwill, Tony, when this great, great case study data you have? I mean referenceability it's not about, I mean, the number one marketing strategy we have is let our customers do the marketing for us. >>So I mean, part of why we do these events is to let our customers and people who are not customers yet interact with each other. And even when we have a reception and one of the best marketing strategies, if you have a product that people like is you combined your customers, your prospects and alcohol, and then they, you let them talk, right? You haven't asked questions. And that's how you get the relevant. Like, okay, you don't wanna believe our salespeople talk to our customers and really get a sense of what's going on. All right, there's too much smoke and mirrors. But these old guard hardware and software companies for much more open, much more transparent, um, because we believe in our, in our products and they're available for anyone. Anytime. It's almost like it's not even worth making up things that aren't true because anyone in the world can evaluate any of our services anytime they want. >>It's almost boringly boringly good. And you hear Andy talking about, well we did this for that. We did definitely, it was like a laundry list. I was listening to the keynote. I'm like, okay, he's going to stop now. Yeah, no, I'm just like, it's more and more just dropping, dropping more and more feature releases. Um, so obviously you guys are shipping more product. You reducing the prices for shipping. I mean, pushing on services. Yeah. You push code in the cloud, we can create a box for you. You can ship that ship means, you know, Sam sends send to the cloud. But that's the dev ops culture that DevOps culture is to be scrappy but think differently. So you guys are thinking differently. Like I gotta ask you, how do you thinking differently because it's clear and ecosystems developing around me and that's something that you do have to nurture. >>You have to invest in this community and you're helping them as business partners now, not just customers. Your customer base now spans the partners. Yeah. Have you balanced it? Still? Same philosophy. What tweaks if you've made your job and an organization based upon the tsunami of an ecosystem growth. I mean our customer ecosystem is really important to our strategy and to our customers. The way we think about it as a um, cloud's new and people are gonna need help. So from consulting firms, systems integrators, managed service providers, which is a really fast growing space. We want to make sure that when our customers want to bet big on AWS, there are those trusted people with certified engineers who can help them either in the short term or longterm basis. And then on the technology partner ISV side, we spent a lot of time making sure that we work collaboratively with these companies to pre sort of certify these applications to run on AWS. >>And then we create pre configured versions of them that run in our marketplace where our customers can browse through a catalog of software pre-configured or run in AWS. They can install with one click of the button and then it just shows up on their AWS bill. So we're trying to make it a lot easier for people to use a lot of these partners technology. And you know what, we're not going to come out with everything. You know, we'd like the creativity of our partners. The customers like to know if they, if they bet on AWS and they say, huh, you know, I wonder if you know, there's some good no SQL databases that run on AWS. Oh there's Mongo, there's Cassandra and whatever space you pick, there may be something we offer and there may be four or five other solutions from our partners. We love that choice because that's what customers ask us. Well, >>congratulations on all your success now. And my final question for you is really probably the hardest question and you can answer it or not answer it. Um, obviously the competitive landscape has significantly increased the heat in the kitchen around you guys for a while you were uncontested. Yes. Some people kind of pick an ankle biting around Amazon's, you know, leadership. But now you've got some pretty big players. IBM, HP, Oracle, Google, EMC, pivotal, VMware gunning, Rackspace, trickles, OpenStack, all of those kind of going around and no, you don't focus on competition and you focus on the customer. We've heard that before, but like you gotta think about that. That's going to put some pressure. How is that affecting you guys? I see you're mindful of it. Are you guys doing anything different to address it? >>I've never seen a market before where it wasn't healthy for both the leader and for the customers to have competition. And we've always expected this to be a market that would have multiple vendors. We look at our, every other technology, a space that was new and became large. There's multiple vendors and it, you know, it enhances innovation, keeps people honest. It's a good thing. >>So the final question then is what will you tell the folks out there who are watching? Is Amazon enterprise ready, um, what's going on right now? This event, you get the big announcements, give them a recap of what you guys did today and comment on the, on the Amazon is enterprise ready or the enterprise may be ready, not ready for the Amazon. So how do you respond to all that FID out? >>Yeah, I mean that was a question people asked a lot about us in the enterprise three, four years ago. I think we've invested a pretty big deal of our R and D over the past four or five years on just maniacally going through all these enterprise features. I mean, if you look at Gartner's magic quadrant for infrastructure and service, which is 100% designed for enterprise decision makers, we're, we're the faraway leader. Uh, and um, you know, we Mark off their checklist pretty well. And I think that's one of the reasons why we're really becoming the safe choice for it managers and large organizations, large enterprises, large government agencies. Um, I mean, my biggest point of advice is to take a look at our website and we're constantly coming out with new services. And if you haven't looked at this recently, I bet you're going to go there and find some things that you didn't know. Randomness and you'll get some ideas about new projects, new workloads that you can run in the cloud. >>Okay. Final word on re-invent to now. Three major things were announced Canisius app stream and workspaces. Are you happy with what's happened since then and now? It gives a quick guys a feeling of >>yeah, I mean the, the uh, we did a private beta for all three of them. We had a lot of participation. Uh, we showed in the keynote some of the real creative applications people are building with app stream where they're streaming very graphically intensive applications out to a variety of devices. Really making it easier for developers, workspaces, the interest. I've never seen a product like this before. Um, where the customer is in the private beta are just so excited about giving us some features, talk about how we can make it better. Um, tons of, tons of energy, tons of excitement. And Canisius is one of these things where, you know, we didn't know what to expect. I mean it's, it's a, a, a realtime analytics service to ingest massive amounts of data and you can build all kinds of apps on top of it. And I think, uh, one of the things we talked about today, uh, was a gaming company. Supersolid makes classic plans to take all the click stream and usage data of their application to figure all these intelligent endgame offers and how to make their games more efficient and more fun. And uh, that's the best part is when we can come out with technology that is pretty broad and can be used for a lot of things. And then we let customers be creative and we can see what they do. >>Then they do Italia. Luckily they generally anymore, right there you'll come and you actually have the hardest and easiest job in the world kind of at the same time. One is you just have great customers. You have the sizzle and the steak, as we say, meat on the bone. Um, great product mix. You guys introducing that stuff here, prices dropping and functionality increasing and innovation having the same time. It's actually quite an amazing thing. So we're really impressed. Again, we're happy customer with Bouchut that's coming on the cube. Again, appreciate it for having me. This is the cube. This is what we do. We go out to the events, we go where the action is, and the action is at Amazon web services summit in San Francisco. This is the cube. We'll be right back with our next guest after this short break.

>>Hey, welcome back everyone. We're here live here in San Francisco for Amazon web services summit. This is the smaller event compared to reinvent the big conference in Vegas, which we were broadcasting live. I'm John furry, the founder's SiliconANGLE. This is the cube. Our flagship program where we go out to the events district to see live from the noise and a an Amazon show would not be complete without talking to the Amazon guys directly about what's going on under the hood. And our next guest is ADI Krishnan and Ryan Wade have run the Canisius teams. Guys, welcome to the cube. So we, Dave Vellante and I was not here unfortunately. He has another commitment but we were going Gaga over the says we'd love red shift in love with going with the data. I see glaciers really low cost options, the store stuff, but when you start adding on red shift and you know can, he says you're adding in some new features that really kind of really pointed where the market's game, which is I need to deal with real time stuff. >>I'll need to deal with a lot of data. I need to manage it effectively at a low latency across any work use case. Okay. So how the hell do you come up with an ISA? Give us the insight into how it all came together. We'd love the real time. We'd love how it's all closing the loop if you will for developer. Just take us through how it came about. What are some of the stats now post re-invent share with us will be uh, the Genesis for Canisius was trying to solve our metering problem. The metering problem inside of AWS is how do we keep track with how our customers are using our products. So every time a customer does a read out of dynamo DB or they read a file out of S3 or they do some sort of transaction with any of our products, that generates a meeting record, it's tens of millions of records per second and tens of terabytes per hour. >>So it's a big workload. And what we were trying to do is understand how to transition from being a batch oriented processing where we using large hitting clusters to process all that data to a continuous processing where we could read all of that data in real time and make decisions on that data in real time. So you basically had created an aspirin for yourself is Hey, a little pain point internally, right? Yeah. It's kind of an example of us building a product to solve some of our own problems first and then making that available to the public. Okay. So when you guys do your Amazon thing, which I've gotten to know about it a little bit, the culture there, you guys kind of break stuff, kind of the quote Zuckerberg, you guys build kind of invented that philosophy, you know stuff good. Quickly iterating fast. So you saw your own problem and then was there an aha moment like hell Dan, this is good. We can bring it out in the market. What were customers asking for at the same time was kind of a known use case. Did you bring it to the market? What happened next? >>We spend a lot of time talking to a lot of customers. I mean that was kind of the logistical, uh, we had customers from all different sorts of investigative roles. Uh, financial services, consumer online services from manufacturing conditional attic come up to us and say, we have this canonical workflow. This workflow is about getting data of all of these producers, uh, the sources of data. They didn't have a way to aggregate that data and then driving it through a variety of different crossing systems to ultimately light up different data stores. Are these data source could be native to AWS stores like S3 time would be be uh, they could be a more interesting, uh, uh, higher data warehousing services like Gretchen. But the key thing was how do we deal with all this massive amount of data that's been producing real time, ingested, reliably scale it elastically and enable continuous crossing in the data. >>Yeah, we always loved the word of last tickets. You know, a term that you guys have built your business around being elastic. You need some new means. You have a lot of flexibility and that's a key part of being agile. But I want you guys at while we're here in the queue, define Kenny SIS for the folks out there, what the hell is it? Define it for the record. Then I have some specific questions I want to ask. Uh, so Canisius is a new service for processing huge amounts of streaming data in real time. Shortens and scales elastically. So as your data volume increases or decreases the service grows with you. And so like a no JS error log or an iPhone data. This is an example of this would be example of streaming. Yeah, exactly. You can imagine that you were tailing a whole bunch of logs coming off of servers. >>You could also be watching event streams coming out of a little internet of things type devices. Um, one of our customers we're talking about here is a super cell who's capturing in gain data from their game, Pasha, the plans. So as you're playing clash of the plans, you're tapping on the screen. All of that data is captured in thesis and then processed by my super Supercell. And this is validated. I mean obviously you mentioned some of the use cases you needed of things, just a sensor network to wearable computers or whatever. Mobile phones, I'll see event data coming off machines. So you've got machine data, you've got human data, got application data. That's kind of the data sets we're seeing with Kinesis, right? Traverse set. Um, also attraction with trends like spark out of Berkeley. You seeing in memory does this kind of, is this in your wheelhouse? >>How does that all relate to, cause you guys have purpose-built SSDs now in your new ECQ instances and all this new modern gear we heard in the announcements. How does all the in-memory stuff affect the Canisius service? It's a great question. When you can imagine as Canisius is being a great service for capturing all of that data that's being generated by, you know, hundreds of thousands or millions of sources, it gets sent to Canisius where we replicated across three different availability zones. That data is then made available for applications to process those that are processing that data could be Hadoop clusters, they could be your own Kaloosas applications. And it could be a spark cluster. And so writing spark applications that are processing that data in real time is a, it's a great use case and the in memory capabilities and sparker probably ideal for being able to process data that's stored in pieces. >>Okay. So let's talk about some of the connecting the dots. So Canisius works in conjunction with what other services are you seeing that is being adopted most right now? Now see I mentioned red shift, I'm just throwing that in there. I'll see a data warehousing tool seeing a lot of business tells. So basically people are playing with data, a lot of different needs for the data. So how does connect through the stack? I think they are the number one use case we see is customers capturing all of this data and then archiving all of it right away to S3 just been difficult to capture everything. Right. And even if you did, you probably could keep it for a little while and then you had to get, do you have to get rid of it? But, uh, with the, the prices for us three being so low and Canisius being so easy to capture tiny rights, these little tiny tales of log data, they're coming out of your servers are little bits of data coming off of mobile devices capture all of that, aggregate it and put it in S3. >>That's the number one use case we see as customers are becoming more sophisticated with using Kinesis, they then begin to run real time dashboards on top of Kinesis data. So you could, there's all the data into dynamo DB where you could push all that data into even something like Redshift and run analytics on top of that. The final cases, people in doing real time decision making based on PISA. So once you've got all this data coming in, putting it into a dynamo DB or Redshift or EMR, you then process it and then start making decisions, automated decisions that take advantage of them. So essentially you're taking STEM the life life cycle of kind of like man walking the wreck at some point. Right? It's like they start small, they store the data, usually probably a developer problem just in efficiencies. Log file management is a disaster. >>We know it's a pain in the butt for developers. So step one is solve that pain triage, that next step is okay I'm dashboard, I'm starting to learn about the data and then three is more advanced like real time decision making. So like now that I've got the data coming in in real time and not going to act. Yeah, so when I want to bring that up, this is more of a theoretical kind of orthogonal conversation is where you guys are basically doing is we look, we like that Silicon angles like the point out to kind of what's weird in the market and kind of why it's important and that is the data things. There's something to do with data. It really points to a new developer. Fair enough. And I want to give you guys comments on this. No one's really come out yet and said here's a development kit or development environment for data. >>You see companies like factual doing some amazing stuff. I don't know if you know those guys just met with um, new Relic. They launched kind of this data off the application. So you seeing, you seeing what you guys are doing, you can imagine that now the developer framework is, Hey I had to deal with as a resource constraint so you haven't seen it. So I want to get your thoughts. Do you see that happening in that direction? How will data be presented to developers? Is it going to be abstracted away? Will there be development environments? Is it matter? And just organizing the data, what's your vision around? So >>that's really good person because we've got customers that come up to us and say I want to mail real time data with batch processing or I have my data that is right now lots of little data and now I want to go ahead and aggregate it to make sense of it over a longer period of time. And there's a lot of theory around how data should be modeled, how we should be represented. But the way we are taking the evolution set is really learning from our customers and customers come up and say we need the ability to capture data quickly. But then what I want to do is apply my existing Hadoop stack and tools to my data because then you won't understand that. And as a response to that classroom demand, uh, was the EMR connect. Somehow customers can use say hi queries or cascading scripts and apply that to real time data. That can means is ingesting. Another response to pass was, was the, that some customers that would really liked the, the, the stream processing construct a storm. And so on, our step over there was to say, okay, we shipped the Canisius storm spout, so now customers can bring their choice of matter Dame in and mail back with Canisius. So I think the, the short answer there right now is that, >>you know, it's crazy. It's really early, right? I would also add like, like just with, uh, as with have you, there's so many different ways to process data in the real time space. They're going to be so many different ways that people process that data. There's never going to be a single tool that you use for processing real time data. It's a lot of tools and it adapts to the way that people think about data. So this also brings us back to the dev ops culture, which you guys essentially founded Amazon early in the early days and you know I gotta give you credit for that and you guys deserve it. Dev ops was really about building from the ground good cloud, which post.com bubble. Really the thing about that's Amazon's, you've lived your own, your own world, right? To survive with lesson and help other developers. >>But that brings up a good point, right? So okay, data's early and I'm now going to be advancing slowly. Can there be a single architecture for dealing with data or is it going to be specialized systems? You're seeing Oracle made some mates look probably engineered systems. You seeing any grade stacks work? What's the take on the data equation? I'm not just going to do because of the data out the internet of things data. What is the refer architecture right now? I think what we're going to see is a set of patterns that we can do alone and people will be using those patterns for doing particular types of processing. Uh, one of the other teams that I run at is the fraud detection team and we use a set of machine learning algorithms to be able to continuously monitor usage of the cloud, to identify patterns of behavior which are indicative of fraud. >>Um, that kind of pattern of use is very different than I'm doing clickstream analysis and the kind of pattern that we use for doing that would naturally be different. I think we're going to see a canonical set of patterns. I don't know if we're going to see a very particular set of technologies. Yeah. So that brings us back to the dev ops things. So how do I want to get your take on this? Because dev ops is really about efficiencies. Software guys don't want to be hardware guys the other day. That's how it all started. I don't want to provision the network. I don't want a stack of servers. I just want to push code and then you guys have crazy, really easy ways to make that completely transparent. But now you joke about composite application development. You're saying, Hey, I'm gonna have an EMR over here for my head cluster and then a deal with, so maybe fraud detection stream data, it's going to be a different system than a Duke or could be a relational database. >>Now I need to basically composite we build an app. That's what we're talking about here. Composite construction resource. Is that kind of the new dev ops 2.0 maybe. So we'll try to tease out here's what's next after dev ops. I mean dev ops really means there's no operations. And how does a developer deal with these kinds of complex environments like fraud detection, maybe application here, a container for this bass. So is it going to be fully composite? Well, I don't know if we run the full circuit with the dev ops development models. It's a great model. It's worked really well for a number of startups. However, making it easy to be able to plug different components together. I get just a great idea. So, like as ADI mentioned just a moment ago, our ability to take data and Kinesis and pump that right into a elastic MapReduce. >>It's great. And it makes it easy for people to use their existing applications with a new system like pieces that kind of composing of applications. It's worth well for a long time. And I think you're just going to see us continuing to do more and more of that kind of work. So I'm going to ask both of you guys a question. Give me an example of when something broke internally. This is not in a sound, John, I don't go negative here, but you got your, part of your culture is, is to move fast, iterate. So when you, these important projects like Canisius give me an example of like, that was a helpful way in which I stumbled. What did you learn? What was the key pain points of the evolution of getting it out the door and what key things did you learn from media success or kind of a speed bump or a failure along the way? >>Well, I think, uh, I think one of the first things we learned right after we chipped and we were still in a limited previous and we were trying it out with our customers who are getting feedback and learning with, uh, what they wanted to change in the product. Uh, one of the first things that we learned was that the, uh, the amount of time that it took to put data into Canisius and receive a return code was too high for a lot of our customers. It was probably around a hundred milliseconds for the, that you put the data in to the time that we've replicated that data across multiple availability zones and return success to the client. Uh, that was, that was a moment for us to really think about what it meant to enable people to be pushing tons of data into pieces. And we went back a hundred milliseconds. >>That's low, no bad. But right away we went back and doubled our efforts and we came back in around, you know, somewhere between 30 and 40 milliseconds depending on your network connectivity. Hey, the old days, that was, that was the spitting disc of the art. 10, 20 Meg art. It's got a VC. That's right. Those Lotus files out, you know, seeing those windows files. So you guys improve performance. So that's an example. You guys, what's the biggest surprise that you guys have seen from a customer use case that was kind of like, wow, this is really something that we didn't see happening on a, on a larger scale that caught me by surprise. >>Uh, I is in use case it'd be a corner use case. Like, well, I'd never figured that, you know, I would say like, uh, some of the one thing that actually surprised us was how common it is for people to have multiple applications reading out of the same stream. Uh, like again, the basic use case for so many customers is I'm going to take all this data and I'm just going to throw it into S3. Uh, and we kind of envisioned that there might be a couple of different applications reading data of that stream. We have a couple of customers that actually have uh, as many as three applications that are reading that stream of events that are coming out of Kinesis. Each one of them is reading from a different position in the stream. They're able to read from different locations, process that data differently. >>But uh, but the idea that cleanses is so different from traditional queuing systems and yet provides, uh, a real time emotionality and that multiple applications can read from it. That was, that was a bit of a versa. The number one use case right now, who's adopting, can you sit there, watch folks watching out there, did the Canisius brain trust right here with an Amazon? Um, what are the killer no brainer scenarios that you're seeing on the uptake side right now that people should be aware of that they haven't really kicked the tires on Kinesis where they should be? What should they be looking at? I think the number one use case is log and ingestion. So like I'm tailing logs that are coming off of web servers, my application servers, uh, data that's just being produced continuously who grab all that data. And very easily put it into something like us through the beauty of that model is I now have all the logo that I got it off of all of my hosts as quickly as possible and I can go do log nights later if there's a problem that is the slam dunk use case for using crisis. >>Uh, there are other scenarios that are beginning to emerge as well. I don't know audio if you want to talk, that's many interesting and lots of customers are doing so already is emit data from all sorts of devices. So this is, these devices are not just your smartphones and tablets that are practically food computing machines, but also seemingly low power, seemingly dumb devices. And the design remains the same. There are millions of these out there and having the ability to capture that in a day produce in real time is, you know, I think just, uh, just to highlight that, one of things I'm hearing on the cube interviews, all the customers we talk to is the number one thing is I just got to scroll the date. I know what I want to do with it yet. Now that's a practice that's a hangover from the BI data warehouse in business of just store from a compliance reasons now, which is basically like, that's like laser as far as I'm concerned. >>Traditional business intelligence systems are like their version of Galatians chipped out somewhere and give me those reports. Five weeks later they come back. But that's different. Now you see people store that data and they realize that I need to touch it faster. I don't know yet when, that's why I'm teasing out this whole development 2.0 model because I'm just seeing more and more people want the data hanging around but not fully parked out in Malaysia or some sort of, you know, compliance storage. So there's, you know, I think, I think I kind of understand where you're going. There's a, I'm going to use a model for like how we used to do BI analytics and our own internal data warehouse. I also run the data warehouse for AWS. Um, and the classic BI model there is somebody asks a question, we go off and we just do some analysis and if it's a question that we're going to ask repeatedly, we don't, you know, a special fact table or a dimensional view or something to be able to grind through that particular view and do it very quickly. >>A Kunis is offers a different kind of data processing model, which is I'm collecting all of the data and make it easy to capture everything, but now I can start doing things like, Oh, there's, there's certain pieces of data that I want to respond to you quickly. Just like we would create dimensional views that would give us access to particular sets of data and very quick pace. We can now also respond to when those events are generated very quickly. Well, you guys are the young guns in the industry now. I'm a little bit older and the gray hair showing, we actually use the word data processing back in the day. The data processing that the DP department or the MIS department, if you remember those those days, MIS was the management information. Are we going back to those terms? I mean we're looking at look what's happening. >>Is it the software mainframe in the cloud? I mean these are some of the words you're using. Just data processing data pipeline. Well, I my S that's my work, but I mean we're back to those old school stuff but different, well and I think those kinds of very generic terms make a lot of sense for what we're doing is we, especially as we move into these brand new spaces like wow, what do I do with real time data? Like real time data processing is kind of the third type of big data processing or data warehousing was the first time I know what my data looks like. I've created indices like a pre computation of the data, uh, uh, Hadoop clusters and the MapReduce model was kind of the second wave of big data processing and realtime processing I think will be the third way. I think our process, well, I'm getting the hook here, but I got to just say, you guys are doing an amazing job. >>We're big fans of Amazon. I always say that, uh, you know, it was very rare in the history the world. We look at innovations like the printing press, the Wright brothers discover, you know, flying and things like we, Amazon with cloud. You guys have done something that's pretty amazing. But what I find fascinating is it's very rare to see a company that's commoditizing and disrupting and innovating at the same time. And it's really a unique value proposition and the competition is responding. IBM, Google. So you guys have a lot of targets painted on your back by a lot of big players. So, uh, one congratulations on your success, which means that you, you know, you're not going to go in the open field and fight the, the British if they said use the American revolution analogy. You've got to continue to compete. So what's your view of that? >>I mean, and I'm sure you don't talk about competition. You'd probably told him not to talk about it, but I mean, you got to know that all the guns are on you right now. The big guys are putting up the sea wall for your wave of innovation. How do you guys deal with that? It's just cause it's not like we, we ignore our competitors but we obsess about our customers, right? Like it's just constantly looking for what are people trying to do and how can we help them and can seem like a very simple strategy. But the strategy is built with people want and we get a lot of great feedback on how we can make our products better. And it certainly will force you to up your game when you have the competition citing on you. You've got more focused on the customer, which is cool. >>But like you guys kind of aware of like games on, I mean Amazon is at any given a little pep talk, Hey, game is on guys. Let's rock and roll. Right? You guys are aware, right? I think we're totally wearing, I think we're actually sometimes a little surprised at how long it's taken to our competitors to kind of get into this industry with us. So, uh, again, as Andy talked about earlier today, we've had eight years in the cloud computing market. It's been a great eight years and we have a lot of work to do, a lot of stuff that we're going to be almost ready for middle school. Um, final final question for you guys and give you the final word here. Share the photos on the last word is why is this show so important, right this point in time in this market. Why is this environment of the thousands of people that are here learning about Amazon, why, what should they know about why this is such an important advance? I think our summits are a great opportunity for us to share with customers how to use our AWS services. Learn firsthand from not only our hands on labs, but also our partners that are providing information about how they use AWS resources. It's, it's a great opportunity to meet a lot of people that are taking advantage of the cloud computing wave and see how to use the cloud most effectively. >>It's a great time to be in the cloud right now and the Olin's amazing services coming up. There's no better mind now of people coming together and so that's probably as good reasons. Then you guys are doing a great job disrupting change in the future. Modern enterprise and modern business, modern applications. Excited to watch it. If you guys keep focusing on your customer, but that customer base, you keep up the pace that's sick. That question, can you finish the race? That's what I always tell Dave a lot. They, I know Jay's watching Dave. Shout out to Dave Volante, who's on the mobile app right now is traveling. Guys, thanks for coming inside. Can he says great stuff. Closing the loop real time. Amazon really building it out. Thanks for coming on. If you'd be right back with our next guest after this short break. Thank you.