>> Voiceover: Live from San Francisco, it's the CUBE covering AWS Summit 2017. Brought to you by Amazon Web Services. (electronic music) >> Welcome back to the CUBE. We have spent a great day in San Francisco at the AWS Summit. My co-host, George Gilbert, and I are very excited next to be talking to Eric Pan, the Senior Director of Alliances Marketing at Equinix. And Eric and I know each other when I worked at NetUP and you worked at VMware, so it's great to see you again. >> Back in the day. >> Back in the day. >> Eric: Yeah. It's great to be here, Lisa. >> It's great to have you on the CUBE. >> Eric: Thank you. >> So tell us about Equinix and what you're doing to help customers get to the cloud. >> Yes, love to. So Equinix was founded in 199-- ... 1998. We really have established what we call an interconnection data center platform. So Platform Equinix is a company that helps customers to interconnect with their trading partners, with networks, and customers. >> Excellent. And so one of the things that I actually just read yesterday, a press release, that Equinix just became part of the AWS partner network as an advanced technology partner. >> Eric: Right. >> Big news. >> Big news. So we've had a relationship with AWS for many years. We've established 14 points of presence around the world for what AWS calls their Direct Connect, which is, it's a great way for customers to be able to manage their hybrid clouds or mainline, if you will, directly into AWS, privately and bypassing the Internet entirely. So for us to be able to gain this certification, this badge if you will, it's a proud day at Equinix. >> Well, congratulations. Fantastic. I'm sure a lot of hard work has gone into that. >> Eric: Yes. >> So help us, talk though from a customer perspective, where they want to say, "I don't really want to apply any more of my real estate, and I, you know, I don't want to buy a lot more gear, but I have some stuff with legacy apps. And I'm actually starting to build out more in Amazon." What's that scenario? How do you help with that scenario? >> Right, so this is a very typical scenario we see every day with our customers. If I may just color this with what we call interconnection, Interconnection is, it is a set of ideas and concepts that we've established through many years of observing how our customers have worked with us and have built their infrastructure, both on-premises and into the cloud. So what you're referring to is really a hybrid cloud situation or scenario. And where a customer ideally says, "I would like to put the majority of my workloads and applications and maybe even data up in the cloud." But we know that's not practical. There's a lot of different reasons. Some of the reasons are data sovereignty or compliance or regulatory concerns. We see a lot of customers that have very specific hardware devices. For hardware maybe, certification or validation for certain things. So those sort of customers will come to Equinix. They'll place their own equipment within our data center. They'll manage that or they'll have a managed service provider come and help them with that. But they'll also be able to directly connect up into AWS. So that's one of the beauties of working with Equinix from our customers' perspective, is they get the best of both worlds. So they get to move their equipment out of their own data center, but they still have the look-and-feel or the management capability of on-premises. And then they also get to enjoy all the benefits of working in the cloud with AWS. >> So you've grown since early 2016, as we were chatting about before, Equinix has grown customer connections to AWS >> Eric: Yes, 250. >> 250% That's massive. >> Eric: Over 250%, yes. >> Over 250. Tell me just to get a little bit, kind of following on what you were just saying, what type of business would choose that route versus going, either keeping some on-prem then going right right to AWS or a cloud? Give us an understanding of really who this target market is. >> Sure, so really any and all enterprises would need to have this capability. The concept here with Direct Connect, it's really AWS' concept and where they say, "If you have certain applications that may be really heavy and are very compute-intensive or very data-intensive, you'll want to run those applications in AWS, and you want to make sure that you have good user experience around that." So Direct Connect privately connects from the end-user to AWS without zig-zagging through the Internet. You get predictability and performance. And what's really the most important thing is great user experience. >> And are you seeing the rise of enterprise as being more and more comfortable with migrating business-critical workloads? >> Oh absolutely yes. Yes, I went to Andy Jassy's fireside chat earlier today >> Lisa: Yeah, it was fantastic wasn't it? >> And he had a whole list of customers that are running business-critical applications. So we see a lot of customers that do that. And we also see, on the flip-side, a lot of customers, like what we were speaking about earlier in the hybrid cloud sense, that are running business-critical applications in AWS but they need to have their data local. So marked by regulatory or compliance issues in health care or in retail environments where PCI compliance demands that you have private data. And then in countries like, I'm just going to give you two examples, Canada and Germany, they have very stringent data sovereignty rules where you must have data in-country from operating on that data. So a lot of customers will use Direct Connect to connect up into AWS, but they'll also be able to maintain their data privacy if they need to. >> Just a drill down on that scenario, you know, there's debate as to, is there one cloud, one ring to rule them all? Or where is the sweet spots of different clouds? Would Equinix be for a customer who has a mission-critical application that's been running for years, that's got an Oracle database? They want to add some low-latency analytics, machine learning where they're scoring or predicting. So they want to put something close to where it's running. So they take the equipment from their data center, put it in Equinix, add around that application the low-latency stuff. >> Eric: Yes. >> And then maybe the digital experience part is in Amazon. >> Right. Yes. So we see many customers doing that very thing. And we also have a very close relationship with NetApp as a storage provider. And NetApp has an offering called NPS, or NetApp Private Storage. So symbiotically, we work together to provide what NetApp has as a ... Data Fabric, which they call. And in that scenario, the whole entire concept is based on running heavy applications or business applications in the cloud but having your data privately and distributed locally or close to where people live, work, and play. >> George: Okay. >> So one of the topics, actually, in, you mentioned attending Andy Jassy's fireside chat. I think we all did. It was fantastic. >> And one of the things that was really interesting was that he was talking about of all of the buzzwords, and as marketers, you know, we both know this, that IOT is the buzzword that he has seen really come to fruition. >> Eric: Come to life, right. >> The fastest. >> That was a fascinating part of his discussion. So we, Equinix, are at the center of, if you will, some of the things that are going on in the IOT world. So IOT, if you can imagine the Internet, a thing says that there's lots of different little devices or big devices like cars or huge devices like hydroelectric dams or jet engines. Those are all producing vast amounts of data that have to go somewhere. And the companies that, like Andy used GE for example in the wind turbines, the companies that need to look at that data, that are having to store that data or do something with it, they typically say, "Well, if we are based in one geographical city, and all this data is coming in from all over the world or all over some region, you need to have natural ingestion points for that data. So we, Equinix, are at the center of where data comes in. And then the next piece is, well, now that we have all this data or now that the organization has all this data in one place or maybe distributed in a few places, how do they then go operate on that? So the scenarios that we spoke about earlier, in where you have an application running up in AWS, to look at that data or, in some cases, there may be, like Andy talked about the Snowball and the Edge computing, Edge computing is something that Equinix very much puts forward as one of the concepts in our interconnection ideas. So that, it's kind of loud there. >> Sorry for the overhead announcement (laughs) >> So the idea around having all of these big data ingestion points, having Edge compute or cloud compute, Equinix becomes a really logical place for customers to be able to do all of that. And then, of course, there's all the data visualization. There's all the data analytics that have to occur with the data scientists. So maybe some of those analytics are running in AWS, but maybe some of the visualization pieces are running in other companies. I won't name the companies, but we all know who the data visualization companies are. >> Lisa: (laughs) >> So your points of presence are about 150 if ... >> Yes, we have 150 data centers in 40 of the biggest business-rich metros around the world. >> Now, do you see a need for a mini-data center or a point of presence that's more like when AOL had those dial-in >> Eric: (laughs) >> I mean, literally, it could've been one box that received phone calls and then ran them out over the network. And the reason I ask is when we have billions of devices, you might want points of presence in the thousands or hundreds of thousands even. >> Eric: Right. That is a very interesting question, and I kind of liken this to something that maybe is an easier idea to understand. A lot of us live in big cities. A lot of us work or ... A lot of us, yes, work at a big company. Some of us don't. A lot of us conduct our banking with big banks or small banks. So if you can imagine the world of maybe retail or banking where there's lots of little branch offices, those could be, we could think of those as maybe the mini-data center idea that you've brought up earlier. So in what Equinix calls interconnection, we have a concept that we call Edge Hub or Communications Hub, which is an idea in where we want to shorten the distance between where users live, work, and play and where the application is running. And so by doing that and simplifying the network topology, in the case that we're talking about, IOT, yes. You would definitely want to do that. So think of a branch office connecting up to a hub, if you will, a communications hub, as a natural ingestion point to bring in that data. >> So last question, Eric, as we wrap up here. We talked about the tremendous growth that Equinix has had just in the last not even 18 months alone and also the great news yesterday that you're very proud of and should be, as becoming an advanced technology partner of Amazon. So last word to you, what's next as an advanced technology partner of AWS? >> Wow. Well, if I can just maybe borrow some of Andy Jassy's words, we're not done here yet. There's no end in sight where Equinix goes. We continue to grow. We have over a third of the Fortune 500 customers that we've managed to attract and that are happy customers. We want to continue down that road and have 100% of the Fortune 500 customers. And we want to make all of our customers happy in working in this new era that we call cloud computing. >> Fantastic. Well, I think we can feel the momentum coming from you and very much Matt Schpive, the guys and the gals from AWS that were on stage today. So, Eric Pan, it's so great to see you after a few years of back in the day. >> Great to see you. Thanks for having me here. >> Absolutely, and for Eric Pan and my co-host George Gilbert, I'm Lisa Martin. You've been watching the CUBE live from the Amazon Web Services Summit in San Francisco. We will be right back. (futuristic electronic music)

(upbeat music) >> Announcer: Live from San Francisco, it's theCUBE! Covering AWS Summit 2017. Brought to you by Amazon Web Services. >> Welcome back to theCUBE. We thank you so much for hanging out with us today. We've had an amazing day, Jeff Frick, George Gilbert with me, Lisa Martin. I think guys, first impressions or overall impressions of the day, it started with Werner Vogels very energetic, very passionate keynote. It was almost what can't Amazon do. The amount of services that they're offering, the amount of customer logos validating, presumably, and substantiating all of these services. It was really quite eye opening. >> Yeah. >> I think for me. But also some of the use cases that they've shared were, those that were on main stage, those that were in breakout sessions or here with us, really shows that the culture that they're building, or have built over the last 11 years now at AWS, is really one of experimentation, failure is okay, let's keep moving. Speed, speed, speed and undulate. >> So many, so many great things. I just want to touch on some of the culture, pivot off the cuture. For instance, Andy Jassy and his keynote. And I think the culture is so, so important. But one of the things he talked about is they banned PowerPoint. He said because it wasn't interactive, wasted a lot of time, no one was prepared for a deep dive 'cause they just put the slides together. And they went to this thing he called the six page narrative, which I thought was pretty interesting. And everyone reads the narrative at the beginning of the meeting. So, you know, everyone's busy. >> Before the meeting. >> Yeah. >> Oh. >> But I think at the beginning of the meeting. So everyone's had a common point >> Right. >> 'Cause let's face it, everyone's busy, no one really preps as much as they should before the meeting. So now, they force it with a 20 minute read the narrative. And so everyone is at the same kind of depth of knowledge. I thought that was really powerful. And then, to write the press release and the FAQs- >> That was phenomenal! >> Before you write the line of codes. >> Yes! >> So what are the issues that people are going to raise and what's the really exciting value that you're delivering to the market that you defined in a press release. >> Yeah. >> Lisa: Yeah. >> You know, I think it's great stuff. >> That was as interesting, I thought, as any of the product releases. >> I agree, yeah. >> 'Cause it almost told us how they keep the wheel spinning so fast. >> Right >> Exactly! But that is really culturally different than I think a lot of the companies that we talked to who, when you get to a six dot one dot two press release. >> Yeah. Is it really that interesting? >> Right, right. >> So that was really, really revolutionary. And I think speaks to your point, you know, how have they been able to build this dominance this quickly and not let their competitors gain on what they project as a six or seven year advantage. >> Like he said though, 'cause they don't look at the competitors. They just keep movin', right. And they didn't have the kind of the legacy thing holding them back. You know, Clayton Christensen, innovator's dilemma. They just kept moving forward. But I thought the other really insightful thing that came out of his fireside chat was the conversation around third-party sales when they were still just Amazon. And do they let other people sell on their platform. And he said "You can't fight gravity". So, it goes back, it reminds me of like when Schwab went to $19 trades. Dave Pottruck tells the story of online trading. And they were giving up these expensive commissions but he basically said "If I don't kill my own business, somebody else is going to do it for me. So I better be the one that kills it and at least try to take advantage of that next wave". Really powerful concepts. >> But there's an analog to the "fulfilled by Amazon", which is where the third-parties went. Where they sort of, essentially, took the eBay model and said "We're going to essentially make our fulfillment platform, and commerce platform, stronger because we're going to take all of those other third-parties". And then what they did with Amazon, AWS, was take the whole commerce platform. >> Right. >> And open it up for other people 'cause that made it more powerful for them. And there's still more to come. What they really didn't talk about. They talked a lot about AI, and mostly at the framework and tools levels. And where framework levels would be for, you know, world-class scientists and the tools would be for data scientists. But when they talked about the image recognition, the voice recognition, and text-to-speech, things like that, they were saying then they're leveraging the Amazon data and training those models so that mere mortal developers can do that. What he didn't say, and when we had their product marketing guy here, what he didn't want to say was there's whole lot of other areas where Amazon the commerce company, the retail company, has data that no other cloud has that they can offer. Not to think about really the machine learning as tools again, but as semi-finished applications. >> Right. >> And I think that's going to be pretty profound differentiated versus other clouds. >> Right. And just the basic scale, right. The slide that Werner showed, not only with all the customers and partners of this, but just the breadth of services and the way they keep adding more based on whatever your special function is. I need High I/O, I need ML, I need really cheap cold storage, I need whatever. They can apply the scale to all those kind of sub-segments and offer a breadth at scale that, you know, pretty tough to compete against. >> Absolutely! And they continue to innovate. And Andy's fireside chat, he was really kind of talking about why and how they're able to do that. Being customer focused, not having to look at the competition, is a major advantage. And one of the themes I also heard and felt today was you think back 11 years ago to their genesis, they were very much focused on the start-up community, the developers, really won long ago the hearts and the minds of those developers. Because they were the ones that would try and innovate, and fail, and try again. >> Right. >> But as the code becomes, in I think Werner's words this morning, "the new normal", they've done a very good job of continuing to foster and enable developers within start-ups and those entrepreneurs who want to start SaaS companies. >> Right. >> All the way up to the enterprise. As we see the dynamic and buying software change dramatically, thinking about the Amazon marketplace as a great example, we are now seeing the C-suite being mandated sometimes by the board. You've got to move more applications into the cloud. Well how do I do that? >> Right. >> So it's developers, it's lines of business like the marketing folks, or the sales folks that Shadow IT say "We need to do this. You can help us move fast enough". All the way up to the C-suite and the board. And they've done a great job of expanding the conversation. >> Jeff: Right. >> Expanding the services to really target multiple audiences and meet a lot of pain points. >> You know, there was a press briefing, pre-brief for the announcement of the marketplace expansion yesterday. And what came out really interesting was, you know, when you go to the Amazon marketplace homepage and there's dozens of categories and about, I think it's 35 hundred actual products from third-parties and 12 hundred vendors. And, you know, you can't go to an enterprise, you can't go to JP Morgan and say "here, you know, go to town". But what IBM does with sort of their own rich library of stuff is they have their global business services and their industry solutions development groups. They take the piece parts and put solutions together for their customers. But what Amazon is now in a position to do is they have solution architects working either for them, who are billing out at maybe two- or three-hundred thousand a year, or who are working for VARS who turned into manage service providers who configure these solutions. And so, what looks like a self-service marketplace now can serve, you know, a bank with a hundred billion in assets or a trillion in assets because there's now the IBM equivalent of a system integrator who can put the pieces together. And who can run them for you if you don't want to. >> Right, and have the aggregated data of everybody else runnin' those services. So for best practices and stuff, you're leveraging the whole ecosystem, not a single instance at a single company. And that is so big! >> And that was actually, that was one of the themes of our last guest. From Datadog. Which is, they can watch so much of what's going on. Not just a customer's workload, but maybe they're not doing it now but they will be able to do it in the future, where they can look across workloads and identify best practices in configurations and things like that. >> Right. >> And then you send that back to the customer and they pay for that advice. >> Right. It's just interesting, you know, three years ago the conversation was all about security around public cloud and, you know, we're done with that conversation. Especially since most security breeches are people lose their laptops, right. It's an employee, or a disgruntled employee. But the thing that's interesting to me on this start-up and rent versus own is, again, the answer to every question in a Cube interview. Why do you want to do the undifferentiated heavy lifting of managing infrastructure? Those guys, ThinkLogic, still like 14 people and a couple of dozen developers that are attacking the IOT space. They would never even get an approved vendor status at somebody like Boeing or GE. They would never even get to the procurement issue. But now, as part of this marketplace, you know, they can come in either as a partner, part of a solution, an adjunct, part of an SI, or as a standalone app that you still buy through your approved vendor process with AWS. Why would you go anywhere else? >> Right. That was a great point that you brought up a number of times today. Showing, not only how Amazon is innovating internally and to enable the start-ups to the enterprises from a public cloud perspective, but they're also enabling businesses to be born that would never have gotten off the ground. >> Jeff: Right, right. And, to your point, it's very valid about even becoming an approved vendor for a company the size of ThinkLogics, they would never have been able to do that. So, it's really exciting I think overall, I think we'd all summarize the day as a very positive, very enlightening. I think, for me, I was really excited to hear what was going to be going on for IOT and Hybrid. Heard some interesting things there today, so I think that's just a dot dot dot to be continued. >> Yes. >> I think overall, really strong announcements from them. The passion was there. Culturally, I think they really reap what they sow and I think that was reflected in the conversations that we were able to have today. >> One thing I want to ask you about, George, you're a smart guy. Speed of light's too damn slow. >> So you think so. (laughter) >> The speed of light's too damn slow. >> Right. >> Jeff: Hear it over and over and over again. >> Yes! >> And still, cloud-based, soft underbelly of cloud, you got to be connected. Do you think that the speed of light issues with Edge and shifting resources, co-locating storage compute in the data. You see any really big hurdles that are just really scary? >> Like, following on the "dot dot dot", computing always follows a pendulum. Centralization, decentralization. No side ever goes away, it's just a change in emphasis. And we're going to see some analysis have to move to the edge because for the speed of light, you know, your smart car, you know, it doesn't have time to say "That looks like an old lady who's actually in the crosswalk, you know, I'm going to go back to the cloud and ask whether I should plow through her or, you know, the car next to me". You know, that needs a low-latency analytic. >> Jeff: Right, right. >> But at the same time, and one of our guests was talking about it, if you're looking at the pressure at valve at, you know, a thousand-mile pipeline, you probably don't need to react instantaneously. You send that back to the cloud and it'll look at it over, you know, a period of time and say "This one's looking like it's going to leak". >> Right. Anomalies. >> So, different scenarios. >> Okay. >> And, unfortunately, we are going to have to say "dot dot dot". We talked all day about this! Jeff Frig, thank you so much! George Gilbert, what a fantastic day we've had here at the AWS Summit in San Francisco. We thank you for joining! You can follow all of the replays here on siliconangle.tv. And Jeff, what do we got comin' up next week? We're at several events. NAB next week. >> NAB, Oracal, Modern Customer Experience, and you're doing a red carpet, I guess a green carpet award show. >> A green carpet award show at the Computer History Museum next week. So stay tuned, stick around on siliconangle.tv to find out all the things we're doing. It's going to be a exciting spring. Again, thanks for joining. See you next time. (light, upbeat music)

>> Narrator: Live from San Francisco, it's The Cube! Covering AWS Summit 2017, brought to you by Amazon Web Services. (upbeat music) >> Hi, welcome back to The Cube. We are live in San Francisco at the AWS Summit at Moscone Center. Really excited to be here. A tremendous amount of buzz going on. I'm Lisa Martin with my cohost George Gilbert and we're very excited to have Lowell Anderson, product marketing guru at AWS. Welcome back, Cube alumni! >> Lowell: It's great to be here, Lisa, thank you. >> Great to have you here as well. The keynote this morning was so energetic with Werner and Nextdoor is going to be on the program in a little bit. Over a thousand product launches last year. Not only are there superpowers now that AWS, I like that. You don't have a T-shirt, but maybe next time. But I think the word that I heard most today so far is customer. And I think that it's such a, and as AWS really talks about, it's a really differentiated way of thinking, of doing business. I'd love to understand what the products that were announced today. Walk us through some of the key highlights there. Customer logos were everywhere. So talk to us about how customers are influencing the development of the new services and products coming from AWS. >> Yeah, well, you know, for us, customers are always core to what drives our innovation. It's how we start, we start with what our customers want, and we work backwards from that to try to deliver a lot of the new features and services that we talked about today. And Werner covered a huge breadth of things, but they really fall into maybe four or five categories. He started talking about, directly for developers, talking about what we're doing with a product called CodeStar, which is designed to really help developers build and deploy software applications in the Cloud. He also then went and talked about our new marketplace, SaaS Contracts' capability, which makes it super easy for customers to sign up and purchase SaaS applications using multi-year contracts on AWS, but it also makes it easier for ISVs to make their offerings available for our customers. So again, really trying to make that easy for customers. We talked a lot about what we're doing in artificial intelligence, with the general availability of Amazon Lex today, and then a really entertaining video with Polly, where we saw that avatar speaking and the new whispering capability, so adding a lot more value to our suite of artificial intelligence services. Some exciting stuff in analytics, where we talked about Redshift Spectrum, which is the new search capability on Amazon Redshift that allows customers to search not just the data in their Redshift database, but also search all the unstructured data they have in S3. And then some really exciting announcements here on the database space with DynamoDB DAX, which is an accelerator for DynamoDB. And we also talked about the availability of a new version of Aurora for Postgres. So a lot of new capabilities, both in databases, big data, analytics, machine learning and artificial intelligence, and our offerings for SaaS Contracts as well. >> And that was all before lunch. (laughs) >> Lowell: Yeah, a lot of stuff. >> Lowell, following up on, in order of, let's say the comments on AI and the announcements made there. Microsoft, Google, Amazon all have gone beyond frameworks and tools to fully trained services that a normal developer can get their hands around. But in the areas of conversational user interface, natural language understanding, image recognition. Why do you think that those three vendors, the three vendors have been able to make such progress in those areas, to make that capability accessible, and there's so many other areas where we're still down in the weeds? >> I think there's, we sort of see it in, sort of focusing in maybe three different areas that are really targeted at what our customers are asking for. We have some very sophisticated customers who really want to build their own deep learning and machine learning applications, and they want services like MXNet, which is a highly scalable deep learning framework, that they can do and build these deep learning models. So there's a very sophisticated, targeted customer who wants that. But we also have customers that want to build and train and create prediction algorithms, and they use Amazon Machine Learning, which is a managed service which allows them to look at their past transactional data and build prediction models from it. And then the third piece is kind of what you mentioned, which is services that are really designed for the average developer, so they can really easily add capabilities like chatbots and speech and visual recognition to their applications with a simple API interface. And I think what you touched on is, why did we focus here, Well I think, as Andy also talked about today, that it's really early days in this space. And we're going to see a really, really strong amount of innovation here. And Amazon, which has been doing this for many, many years, and thousands of developers focused on this in our retail side, we're really working hard to bring that technology out, so that our customers can use it. And Lex, which is based on Alexa, which we're all familiar with from using the Echo. Bringing that out and making that type of capability available for average developers to use is a piece of that. So I think you're just going to continue to see that and over the course of the next year you're going to see continued new services coming from us on machine learning and artificial intelligence, across all those three spectrums. >> So let me jump to another subject which is really a hot button for our customers, both on the vendor side and the enterprise side, which is the hybrid cloud, I don't know whether we should call it migration or journey or endpoint. But let's take a couple scenarios. Let's say you're a Hadoop customer, and you've got Cloudera on-prem, you're a big bank, you've put an instance of it on Amazon and on Azure so that you can move your data around and you're relatively free. >> Lowell: Sure. >> Now the big use case has been data warehouse offload. So all of a sudden you have two really great data warehouses that are best in class on Amazon. With Redshift, with now the significant expansion of it, and Snowflake, and then you have Teradata, which now can take their on-prem capabilities and put them on the Cloud. How does the customer weigh the cost/benefit of lowest common denominator versus-- >> Yeah, yeah, sure. I think for us and for our customers it's not a one-size-fits-all. Every customer approaches this differently, and so what our focus has been on is to give them the range of choice. So if you want to use Cloudera, you can deploy it on EC2 and you can manage that yourself, and that's going to work great for you. But if you want a more managed service where maybe you don't want to have to manage the scalability of that Cloudera deployment, maybe you want to use EMR and deploy your Hadoop applications on EMR which manages that scalability for you. And so you make those tradeoffs and each of our customers makes those tradeoffs for different reasons and in different ways and at different times. And so our focus has always been to really try to give them that flexibility, to give them services where they can make the choice themselves about which direction they want to go for their individual applications, and maybe mix it up and try different ways of running these types of applications. And so we have a full range of those types of, from the ability to deploy those directly onto EC2 and manage it themselves, all the way to fully managed services that we maintain all the scalability and management and monitoring ourselves. >> One of the interesting things that Andy Jassy said in his fireside chat just in the last hour or so about HyperCloud was that most enterprises are going to operate in HyperCloud for the next several years, and there are those customers that are going to have to, or want to have their own data centers for whatever type of application. But something also that he brought up in that context, and I know you know a lot about this, George, is VMware. So when I was looking at the announcement that was made in the last six months or so about VMware, vSphere-based cloud services, VMware has just sold off their vCloud Air, kind of competing product, wondering with the VMware Cloud on Amazon, how does that... what are really the primary drivers there? Is that sort of a way to take those VMware customers eventually towards hybrid cloud, or is that an opportunity to maybe compete with some of the other guys who might have more traction in the legacy application migration space? >> I think for us, it's again, it comes back to our customers saying, some of our workloads that maybe for a long period of time have been deployed on VMware and we've been using VMware ESX for many, many years on-premise, and we have these applications that have been deployed for many years there, and they're highly integrated, they use specific features of VMware, and maybe we also like using VMware's management tools, we like using vCloud to manage all of these different instances of our VMware virtualization platform, but we just want to run it in the Cloud, because we want that scalability. When you deploy that stuff on-premise, you're still kind of locked in. Every time you want to expand, you've got to go out and you've got to buy more hardware. You really don't have the agility to expand that business, both as it grows, or as it declines. So you're paying for that hardware to power it and run it no matter what. And so they're telling us we'd like to get some of this up into the Cloud, but we don't want necessarily to have to, we've built these apps, we're comfortable with how they're running them, but we want to run them up in the Cloud and we want to do it with low risk. And that's what this VMware relationship is about, is letting those enterprises that have spent years building and maintaining and using VMware and their various management tools, to do that up in the Cloud. That's really what it's about. >> So let's switch gears to another topic that Andy talked about, since all his topics were topical. Edge computing and IIoT. That's another big shift that's coming along and changing the architecture so we have more computing at the edge again, and huge amounts of data. Obviously there's many scenarios, but how do you think customers will basically think through this, or how should they think through how much analytics and capability is at the edge, that issue of should it look like what is in the Cloud? Or should it be really tight and light and embedded? >> I think we're seeing just an increasing range. And also a really interesting mix, where you have some very intelligent devices, your laptop and so on, that is connected to the Cloud and it has a pretty significant amount of processing power, and so there can be applications that run on that machine that are very sophisticated. But if we're going to start to expand that universe of edge devices out to simple sensors for pipelines, and simple ways to monitor the thermostat in your home, and simple ways to measure and monitor and track all sorts of, you know, automobiles and so on, that there's going to be a range of different on-premise or edge types of compute, that we need to support in the Cloud. And so I think what Andy's saying is that we want to build the Cloud to be the system that can act as the, has the analytics power to ingest data from these maybe tens of millions of different devices, which will have a range of different compute power, and support those applications on a case by case basis. >> We've got to wrap things up here, and I know this conversation could continue for many hours. I think what we've heard here today is a tremendous amount of innovation, and I made the joke, all announced before lunch, but really it was. We're seeing the flexibility, we're seeing the customers really drive the innovation. Also the fact that AWS starting in the startup space with the developers, that's still a very key target market for you, even as things go up to the enterprise. So continued best luck with everything going forward. We're excited to be at re:Invent in just, what, five or six months from now, and with many, many more thousands of people and hearing the great things that continue to come from the leader in public cloud. >> Lowell: All right. Thank you, Lisa. >> Thanks for joining us, Lowell, we appreciate it. Next time I want the superpower T-shirt. (laughs) >> (laughs) Okay, I'll take you up on that. >> All right. I'm Lisa Martin for my cohost George Gilbert. Thanks so much for watching, stick around. We are live at the AWS Summit in San Francisco, and we will be right back. (upbeat music)

>> Announcer: Live, from San Francisco, it's theCUBE, covering AWS Summit 2017, brought to you by Amazon Web Services. (bouncy techno music) >> Hi, welcome back to theCUBE, live in San Francisco at the AWS Summit here. I'm Lisa Martin, joined by my co-host Jeff Frick. Our next guest is from Sumo Logic. We have the VP of Product Marketing, Kalyan Ramanathan. Welcome to theCUBE! >> Thank you very much. Very excited to be here. >> Very excited to have you here. So, tell us a little bit about what Sumo Logic is doing with AWS and machine data. What services are you delivering, who's your target audience, all that good stuff. >> Yeah, absolutely. We are a cloud native, i.e., SaaS-based, machine data analytics platform, and what we do is to help our customers manage the operations and security of their machine-critical applications. Right, so we are an entirely AWS-based customer, we've been using AWS since our inception. What we do is to provide machine data and machine learning so that our customers can manage the performance of their applications, right. So, what is machine data, you might ask. So machine data typically includes logs, metrics, events, anything that your application is generating when it is running, when it is serving the enterprise's customers. And what Sumo Logic excels at is to ingest this data. We collect and ingest this data, and then we apply a lot of analytics on that data. We have some patented machine learning technologies that helps us correlate this data, get insights from this data, and then using this data, our customers manage the applications that they are providing to their end customers. >> And it's not just their applications that are co-located at AWS with your application, it's beyond that, I assume. >> Absolutely, I mean, we have customers from, you know, very different walks of life, we have customers who are on-prem, customers who are down the hybrid path and moving to AWS, and customers who are on an AWS. You know, I can rattle off a queue of great names, Pinterest, Twitter, Airbnb, are examples of customers who are born in the cloud. They run on AWS from the very get-go. And they use us today to manage the security and performance of their applications. We have other customers who have migrated to AWS, Scripps Network, the guys behind HGTV, it's a great example of a customer who was running applications in their on-prem data center, and then one day decided that they are a content company, and they don't want to be running their own data center. >> Right. >> And so they wanted to move their applications to the cloud, and they used Sumo Logic to help migrate their applications to AWS. >> What are some of the barriers that you help customers overcome when it comes to maybe that daunting task of migrating services? >> Yeah, that's a great question. You know, the first thing that someone has to do before they start to migrate their applications to the cloud is to understand what is it that they have within the data centers, right. If I don't know what I have, how do I even migrate that to the cloud? The first task is obviously provide visibility into what is within their data center. And that's where Sumo Logic comes in, right. If you deploy Sumo Logic, and if you implement Sumo Logic as a SaaS service, the first thing that we do is to provide you complete visibility into your applications. All the application components, the infrastructures that the application is deployed on, the services that the application may be using. The next thing that you want to do is start to migrate your workload to the cloud. But you want to do this in a very thoughtful way, and what that means is that you start to move your applications and your infrastructure to AWS, but then you do this cut of work to AWS, only when you are convinced about the performance as well as the security of that application in this new environment. So the ability to baseline what you have in your current environment, and then compare it to what it might look like in this new environment within AWS is extremely critical, and what Sumo Logic helped Scripps Network do is to essentially compare and contrast how they are performing in this new environment. And when they were extremely comfortable that their security and their performance was no less in this new environment compared to what they were doing in the data center, they were able to flip that switch and complete the move over to AWS. >> You guys are in an interesting position, because you were born in AWS, essentially, cloud-native, and you have a lot of customers that are running in AWS. And so you guys did a survey, a report, really kind of taking a look at what's actually happening with cloud-native companies running their apps in AWS. I wonder if you can kind of give-- What did you guys find in this thing? >> Yeah, absolutely Jeff. And this is, the report that we put out towards the end of last year, I think is one of the first start leadership reports that gives, you know, people in AWS, a birds-eye view into how are their peers, you know, deploying, architecting, and managing their applications within the AWS environment. So, how did we put this report together? Sumo Logic has over 1200 customers under management today and more than 80% of our customers are, you know, using AWS today. They are implementing their applications within AWS. So what we did was to anonymously mine data from our customers, and publish a report that provides the set of best practices, and the commonly-used techniques and architectures that, you know, the leaders are doing and implementing today as they move to AWS. Now there were some great learnings that we found out as we put this report together, alright. First and foremost, we discovered that the stack, that a customer typically deploys in AWS, is very unlike the stack that they deploy within their on-premise data center. So, how does that work out? I mean, so, many of the AWS customers that we mined here, happen to use Docker extensively within their AWS environment. In fact, 18% of our customers, this was last year, already are using Docker, you know, for the production application. Which is pretty amazing, given that Docker is just, you know, two or three years-- >> Well hopefully Solomon and Ben are watching, we actually have another crew with Docker-- >> Absolutely. >> Right now. >> We'll have to report that back. >> You know, Docker is all the rage, no doubt about, and we are seeing, you know, increased adoption of Docker across the board, among all of, for AWS customer. The other thing that we found very interesting was that the applications that you may typically expect to succeed in your data center, are not quite doing that well in the AWS world. I'll give you a good example, in the database world, you would expect to see Oracle and SQL Server, you know, ruling the root within a typical data center today. You go on AWS, that's not the case at all. The NoSQL databases, right, are the leading vendors of databases within the AWS world. MongoDB, Redis, you know, are well ahead of Oracle and SQL Server when it comes to AWS. When it comes to web server technologies. You know, Nginx and Apache, you know, are well ahead of IAS, which happens to be the web server of choice within the data center world. Now we've also seen, you know, pretty amazing adoption of Lambda Technologies within AWS. I mean, that's to be expected, a certain bit, because I know AWS is definitely pushing it, but again, 12% use it within a production environment. You know, one year into Lambda, GA in some sense, is pretty astonishing numbers, so-- >> What was your takeaway? Was it because of the applications that are deployed, is it because, kind of, historical legacy of what Amazon offered, kind of for an on-prem versus an on-prem, you know, those early business decisions, not so much today, but, you know, years ago, when there was the security and public cloud, you know, it was a very different conversation three years ago. What were some of your takeaways as to the why? >> The takeaways that I think, there's a meta takeaway here, and let me start with that. The meta takeaway is that as people are building applications in AWS, native AWS applications, or as they are migrating their applications from an on-prem data center to, let's say, AWS, this is giving IT architects the opportunity rethink how their applications are constructed. You know, they are no longer bound by the old shackles of, if I have to use a database, it's Oracle or SQL Server. If I have to use a IIS web server, it's IIS or some other option. >> Right. >> So, once you are unchained from these shackles, you have the ability now to rethink and re-architect your application from scratch to target and to focus on this amazing new world that the cloud, you know, offers. So that's the, that's a big meta takeaway for us, and, what we have learned is that once you are unbound, you can come up with new technologies and new ways of doing things that are adopted and better suitable for this new space. That's one. The second thing that we do see, obviously, is that the vendors of yesterday are not yet focused on the cloud technologies. It may be heresy to say this, but, you know, Oracle has not found a cult religion until very recently. And that's why you see Oracle as not doing a lot, or not making a dent in, you know, in cloud places or in cloud technologies like AWS. >> Right, right, it's just interesting, that procurement angle, because, as anyone who's ever been at a relatively small company, trying to sell into a big company, one of the biggest hurdles is actually just getting on the procurement list, becoming an approved vendor. So, it's interesting to think about that from the other side as a consumer. That if now you are unshackled from the approved vendor list, and you, because if now the only approved vendor is Amazon, and now you have this whole breadth of things to choose from within that ecosystem, that, how that could really impact your behavior and what you actually buy, build, and deliver. >> Yeah, I mean, I think that's a great point too. I mean, there are economics involved here, there is the friction of adopting certain technologies to AWS, which also makes it a little harder to adopt some of the more traditional software applications in the AWS world. Now that's why AWS obviously has come up with the notion of a marketplace, and Sumo Logic, you know, we face the same challenges when we are signing up customers, right. We have some big-name customers who, you know, if we have to sell into those customers, you know, we have to get into their procurement list, we have to, you know, go through a few rigamaroles-- >> Jeff: Right, Right >> To even get into that list. That's where, you know, getting into the AWS marketplace has really helped us a lot. Now you have one vendor, you have one relationship, you have one payment terms, and that vendor is already on your approved list. And so, hey, Sumo Logic comes along with the rights. >> So, definitely a simplification there, which was one of the themes in the keynote this morning, as well as this unshackling. What are your objectives for the report, are you going to be either going back to some of your existing customers or to new customers to show them all of these best practices that you've developed? >> Yeah, I mean, I think our goal of this report, obviously, first thing from us is to make this an annual report, we plan to do this every year, write it on reinvent. And what we want to do is to provide our community, who are mostly AWS shops today. We do have a few Microsoft Azure customers, and we are starting to see some Google Cloud platform customers too. But what we want to do is become the hot leader, who not only serves his customers, but also provides them a road map, in terms of, you know, how should they be adopting these cloud technologies. >> Jeff: Right. >> What are their leading-edge peers like the Twitters and the Airbnbs and the Pinterests of the world starting to do. Obviously, in a anonymized way, we don't want to be calling out any of our customers by name, but here is how you need to think about architecting your applications in the cloud. There is an opportunity, as we said, to, you know, break open from the chains of the past, redo this. We want to help our customer redo this well. >> I'd love to get your perspective, what are the, you know, and I think we're past the security and some of those kind of historic impediments, to you will, to public cloud adoption, but one of the ones that still comes up all the time is the rent versus buy, and you know I think it goes back to the tested roots of, yes, it's great to rent for awhile, but at some point in time, when you hit some scale-- >> Kalyan: Right. >> The business model flips and now it's more economical to buy and operate your own. But what we see in the slide that Werner showed today, there's plenty of customers, Netflix, of course always being the flagship, that are giant, and must have a giant AWS bill every month, who have chosen to still leverage them as their IT platform, and not flip the switch to a purchase. So you know, kind of either from the survey or anecdotally with your own customers, and you as a company, you know, what impacts that decision and do you have, like this review every couple of years, when those CFOs go, "Ah, we're paying these guys a lot of money," should we build our own stuff, but clearly you haven't gone that route. >> I mean, there are definitely enterprises who are still on-prem today, I think the last stat that I heard from Gartner is that 20% of enterprises have flipped over to public cloud infrastructure. 80% is still running things in the cloud, you know, within the data center, maybe a private cloud or maybe in the traditional old ways of running applications. But that tide is definitely turning. And what we see from many of our customers is that there are many reasons for customers or enterprises to now start adopting public cloud. Economics is obviously one, I mean, there is a big advantage of going from Capex to Opex, it obviously makes a lot of sense to do that. The second thing is that what we see is that it's not just about moving the application to the cloud, it's also having the right tooling around the application that can now allow you to manage that application, manage the performance of that application, the security of that application, the deployment of that application in the public cloud environment. And that has taken a while to mature, and I think we are already there, I mean, in an event like this, you can see so many companies come up with new, innovative ways of managing applications within the public cloud environment. And I think we are there now, I mean, the pendulum has swung, and we have enough technologies now to do this with a very high level of confidence. The third thing I would say, and you know, we keep hearing this from our customers again and again, and you know, I brought up Scripps as a great example, you know, we just did a public webinar with a company called Hootsuite, and, you know, they are a social media management platform company, and one of the comments from the Hootsuite VP of Operations was very telling, he said, "Look, I can do this, I can run my own stuff, but do I really want to do it, right? I am a social media company, I want to provide the best application to my customers. I'm not in the business of running a management technology, you know, on-prem or even, for that matter, you know, within the four walls of the company itself. What I want to do is focus on where I can deliver the best value to my customer, and that is by delivering a great social media application." >> Lisa: Exactly. >> "And I want to let the infrastructure game, the management game to the experts," right. >> Focusing on their core competencies to really drive more business. >> I mean I think we are definitely starting to see that, there are certain verticals that have adopted this, you know, wholeheartedly, retail is a good one, media is a good one, there are also cost pressures in those verticals that are forcing them to adopt this at a much faster pace. Financial is kicking and screaming, but they are also getting on board. >> But definitely from a thematic perspective, you talk about maturation, maturation of the services, maturation of the technologies, and maturation of the user. So we want to thank you so much for stopping by theCUBE, great to have you here. >> Thank you very much, I mean, it's been a great conversation with you guys, and it's a great event. >> Excellent, well for my co-host Jeff Frick, I am Lisa Martin, you're watching this on theCUBE live in San Francisco as the AWS Summit. Stick around, we'll be right back. (bouncy techno music)

>> Voiceover: Live from San Francisco it's theCUBE. Covering AWS Summit 2017. Brought to you by Amazon Web Services. (upbeat music) >> Hey welcome back to theCUBE live at the Moscone Center at the Amazon Web Services Summit San Francisco. Very excited to be here, my co-host Jeff Rick. We're now talking to the Chief Scientist and professor at University of San Francisco, Greg Benson of SnapLogic. Greg, welcome to theCUBE, this is your first time here we're excited to have you. >> Thanks for having me. >> Lisa: So talk to us about what SnapLogic is, what do you do, and what did announce recently, today, with Amazon Web Services? >> Greg: Sure, so SnapLogic is a data integration company. We deliver a cloud-native product that allows companies to easily connect their different data sources and cloud applications to enrich their business processes and really make some of their business processes a lot easier. We have a very easy-to-use what we call self-service interface. So previously a lot of the things that people would have to do is hire programmers and do lots of manual programming to achieve some of the same things that they can do with our product. And we have a nice drag-and-drop. We call it digital programming interface to achieve this. And along those lines, I've been working for the last two years on ways to make that experience even easier than it already is. And because we're Cloud-based, because we have access to all of the types of problems that our customers run into, and the solutions that they solve with our product, we can now leverage that, and use it to harness machine-learning. We call this technology Iris, is what we're calling it. And so we've built out this entire meta-data framework that allows us to do data science on all of our meta-data in a very iterative and rapid fashion. And then we look for patterns, we look for historical data that we can learn from. And then what we do is we use that to train machinery and algorithms, in order to improve the customer experience in some way. When they're trying to achieve a task, specifically the first product feature that is based on the Iris technology is called the Integration Assistant. And the Integration Assistant is a very practical tool that is involved in the process of actually building out these pipelines. We call, when you build a pipeline it consists of these things called snaps, right? Snaps encapsulate functionality and then you can connect these snaps together. Now, it's often challenging when you have a problem to figure, OK, it's like a puzzle what snaps do I put together, and when do I put them together? Well, now that we've been doing this for a little while and we have quite a few customers with quite a few pipelines, we have a lot of knowledge about how people have solved those puzzles in the past. So, what we've done with Iris, is we've learned from all of those past solutions and now we give you automatic suggestions on where you might want to head next. And, we're getting pretty good accuracy for what we're predicting. So, we're basically, and this integration system is, a recommendation engine for connecting snaps into your pipelines as they're developing. So it's a real-time assistant. >> Jeff: So if I'm getting this right, it's really the intelligence of the crowd and the fact that you have so many customers that are executing many of the similar, same processes that you use as the basis to start to build the machine-learning to learn the best practices to make suggestions as people are going through this on their own. >> Greg: That's absolutely right. And furthermore, not only can we generalize from all of our customers to help new customers take advantage of this past knowledge, but what we can also do is tailor the suggestions for specific companies. So as you, as a company, as you start to build out more solutions that are specific to your problems, your different integration problems... >> Jeff: Right. >> The algorithms can now be, can learn from those specific things. So we both generalize and then we also make the work that you're doing easier within your company. >> And what's the specific impact? Are there any samples, stories you can share of what is the result of this type of activity? >> Greg: We're just, we're releasing it in May. >> Jeff: Oh OK. >> So it's going to be generally available to customers. >> Couple weeks still. >> Greg: Yeah. So... So... And... So... So we've done internal tests, so we've dove both through sort of the data science, so the experimentation to see, to feed it and get the feedback around how accurately it works. But we've also done user studies and what the user studies, not only did the science show but the user studies show that it can improve the time to completion of these pipelines, as you're building them. >> Lisa: So talk to us a little bit about who your target audience is. We're AWS, as we said. They really started 10 years ago in the start of space and have grown tremendous at getting to enterprise. Who is the target audience for SnapLogic that you're going after to help them really significantly improve their infrastructure get to the cloud, and beyond? >> Greg: So, so, so basically, we work with, largely with IT organizations within enterprises, who are, you know, larger companies are tasked with having sort of a common fabric for connecting, you know, which in an organization is lots of different databases for different purposes, ERP systems, you know, now, increasingly, lots of cloud applications and that's where part of our target is, we work with a lot of companies that still have policies where of course their data must be behind their firewall and maybe even on their premise, so our technology, while we're... we're hosted and run in the cloud, and we get the advantage of the SAS, a SAS platform, we also have the ability to run behind a firewall, and execute these data pipelines in the security domains of the customers themselves. So, they get the advantage of SAS, they get the advantage of things like Iris, and the Integration Assistant, right, because we can leverage all of the knowledge, but they get to adhere to any, you know, any regulatory or security policies that they have. And we don't have to see their data or touch their data. >> Lisa: So helping a customer that was, you know, using a service-oriented architecture or an ETL, modernize their infrastructure? >> Greg: Oh it's completely about modernization. Yeah, I mean, we, you know, our CEO, Gaurav Dhillon has been in the space for a while. He was formerly the CEO of Informatica. And so he has a lot of experience. And when he set out to start SnapLogic he wanted to look, you know, embrace the technologies of the time, right? So we're web-focused, right? We're HTTP and REST and JSON data. And we've centered the core technologies around these modern principles. So that makes us work very well with all the modern applications that you see today. >> Jeff: Look Greg, I want to shift gears a little bit. >> Greg: Yeah. >> You're also a professor. >> Greg: Correct. >> At University of San Francisco and UC Davis. I'd just love to get your perspective from the academic side of the house on what's happening at schools, around this new opportunity with big data, machine-learning, and AI and how that world is kind of changing? And then you are sitting in this great position where you kind of cross-over both... How does that really benefit, you know, to have some of that fresh, young blood, and learning, and then really take that back over, back into the other side of the house? >> Greg: Yeah, so a couple of things. Yeah, professor at University of San Francisco for 19 years. I did my PhD at UC Davis in computer science. And... My background is research in operating systems, parallel and distributed computing, in recent years, big data frameworks, big data processing. And University of San Francisco, itself, we have a, what we call the Senior and Masters Project Programs. Where, we've been doing this for, ever since I've been at USF, where what we do is we partner groups of students with outside sponsors, who are looking for opportunities to explore a research area. Maybe one that they can't allocate, you know, they can't justify allocating funds for, because it's a little bit outside of the main product, right? And so... It's a great win, 'cause our students get experience with a San Francisco, Silicon Valley company, right? So it helps their resume. It enhances their university experience, right? And because, you know, a lot of research happens in academia and computer science but a lot of research is also happening in industry, which is a really fascinating thing, if you look at what has come out of some of the bigger companies around here. And we feel like we're doing the same thing at SnapLogic and at the University of San Francisco. So just to kind of close that loop, students are great because they're not constrained by, maybe, some of us who have been in the industry for a while, about maybe what is possible and what's no so possible. And it's great to have somebody come and look at a problem and say, "You know, I think we could approach this differently." And, in fact, really, the impetus for the Integration Assistant came out of one of these projects where I pitched to our students, and I said "OK, we're going to explore SnapLogic meta-data and we're going to look at ways we can leverage machine-learning in the product on this data." But I left it kind of vague, kind of open. This fantastic student of mine from Thailand, his name is Jump, he kind of, he spent some time looking at the data and he actually said, "You know I'm seeing some patterns here. I'm seeing that, you know, we've got this great repository of these," like I described, "of these solved puzzles. And I think we could use that to train some algorithms." And so we spent, in the project phase, as part of his coursework, he worked on this technology. Then we demoed it at the company. The company said, "Wow, this is great technology. Let's put this into production." And then, there was kind of this transition from sort of this more academic, sort of experimental project into, going with engineers and making it a real feature. >> Lisa: What a great opportunity though, not just for the student to get more real-world applicability, like you're saying, taking it from that very experimental, investigational, academic approach and seeing all of the components within a business, that student probably gets so much more out of just an experiment. But your other point is very valid of having that younger talent that maybe doesn't have a lot of the biases and the pre-conceived notions that those of us that have been in the industry for a while. That's a great pipeline, no pun intended... >> Greg: Sure. >> For SnapLogic, is that something that you helped bring into the company by nature of being a professor? Just sort of a nice by-product? >> Well, so a couple of things there. One is that, like I said, University of San Francisco we were running this project class for a while, and... I got involved, you know, I had been at USF for a long time before I got involved with SnapLogic. I was introduced to Gaurav and there was this opportunity. And initially, right, initially, I was looking to apply some of my research to the technology, their product and their technology. But then it became clear that hey, you know we have this infrastructure in place at the university, they go through the academic training, our students are, it's a very rigorous program, back to your point about what they are exposed to, we have, you know, we're very modern, around big data, machine-learning, and then all of the core computer science that you would expect from a program. And so, yeah, it's been... It's been a great mutually beneficial relationship with SnapLogic and the students. But many other companies also come and pitch projects and those students also do similar types of projects at other companies. I would like to say that I started it at USF but I didn't. It was in existence. But I helped carry it forward. >> Jeff: That's great. >> Lisa: That is fantastic. >> And even before we got started, I mean you said your kind of attitude was to be the iPhone in this space. >> Greg: Of integration, yeah. >> Jeff: So again, taking a very different approach a really modern approach, to the expected behavior of things is very different. And you know, the consumerization of IT in terms of the expected behavior of how we interact with stuff has been such a powerful driver in the development of all these different applications. It's pretty amazing. >> Greg: And I think, you know, just like maybe, now you couldn't imagine most sort-of consumer-facing products not having a mobile application of some sort, increasingly what you're seeing is applications will require machine-learning, right, will require some amount of augmented intelligence. And I would go as far to say that the technology that we're doing at SnapLogic with self-service integration is also going to be a requirement. That, you just can't think of self-service integration without having it powered by a machine-learning framework helping you, right? It almost, like, in a few years we won't imagine it any other way. >> Lisa: And I like the analogy that Jeff, you just brought up, Greg, the being the iPhone of data integration. The simplicity message, something that was very prevalent today at the keynote, about making things simpler, faster, enabling more. And it sounds like that's what you're leveraging computer science to do. So, Greg Benson, Chief Scientist at SnapLogic. Thank you so much for being on theCUBE, you're now CUBE alumni, so that's fantastic. >> Alright. >> Lisa: We appreciate you being here and we appreciate you watching. For my co-host Jeff Rick, I'm Lisa Martin, again we are live from the AWS Summit in San Francisco. Stick around, we'll be right back. (upbeat music)

>> Narrator: Live from San Francisco, it's the Cube, covering AWS Summit 2017. Brought to you by Amazon Web Services. (upbeat music) >> Hi, welcome back to the Cube, live from the AWS Summit San Francisco. Jeff Frick, and I are here with the CMO of Splunk, Brian Goldfarb. Hey Brian, welcome to the Cube. >> Thanks, thanks for having us, we're really glad to be here. >> You've been the CMO at the Cube, the Cube, congratulations! >> Brian: Promotion, this is amazing. (laughs) >> You've been promoted. Let me start again, you've been the CMO with Splunk, am I red yet, for about six months. Talk to us about the new role that you have there, what do you, what's exciting, what's happening? >> Yeah, it has been almost six months now. It's been an amazing experience. Splunk was super attractive to me as I was looking at opportunities, because it has both an amazing product and customers who love it. And that combination, particularly in technology, is that rare first place. That's a marketer's dream. You're not creating champions, you're not convincing anyone that it's great. And so I've been coming in focusing on how do take that incredible asset, our community, and our users and really expand it. And that's been a big focus for me over the last five months. It's an amazing company. I'm very honored and lucky to be working with such a great place. And in fact, we won, "Best Places to Work." >> Lisa: Congratulations. >> For the tenth year in a row. >> The Santana row office are pretty nice. I was lucky enough to go down there and check those out when you opened them. >> Oh yeah, that's awesome. Our headquarters is in San Francisco, but as you think about the expansion of the area having facilities down in San Jose is super great for as we grow our company. >> So I guess, it's a match made in heaven, but the word on the street is you're a data guy. You want data to support everything. Data driven solutions. Data backed decision making. What a perfect fit because the essence of Splunk is basically sitting on that machine data that's flowing through the system. >> That's right. You think about where our roots are, is really how do take big data and make it useful for people. Like machine data is often forgotten. All the information flowing from sensors and hardware and servers. And as we sit here, at the Amazon Web Services show in San Francisco, all of that infrastructure is core to creating machine data. And we want to make it accessible and usable for everyone to get insights. And what we see is that manifest itself in a lot of interesting ways. I'll give you an example, Yelp. Think about food, think about reviews, but they're using Splunk for a couple things. One, make sure that their core infrastructure is up and running, obviously important. Because we need that restaurant review, you need it now. That's a very San Francisco thing. But more importantly as they've rolled out their new food delivery capabilities, all of the business analytics required to make sure that operations business runs tip top is critical. So they're using Splunk for all those pieces. >> So I wonder if you can speak a little bit about the relationship with AWS? I know you're relatively new, but Doug Merritt is relatively new. And of all of the logos that Verner went which were numerous and hard to see, (Brian laughs) he picked Doug to come up and really help out with the keynote. Obviously, Cloud, big deal, AWS, big deal. What is the relationship, how has it evolved over time, and how is this cloud-enabled delivery impacting the way Splunk does business? >> Yeah, we're very fortunate to have a wonderful partnership with Amazon Web Services. We've been a strategic partner of them for almost five years. And we made a big bet of our business on using their product to deliver our product in the cloud. Our business started 14 years ago with Splunk Enterprise, an on-premises based software solutions that's been adopted by over 13,000 customers around the globe. And we heard time and time again, as the cloud became more important in the decisions people were making, how do we get the visibility that we need both across our on-premises assets and our cloud assets? And so the relationship with Amazon has been predicated on how do we deliver Splunk in the cloud and more importantly, how do we give everyone who's now adopting Amazon at this amazing clip the visibility into all the components that they're using, so they can maintain their solutions, they can make sure things are running, they can optimize their span, et cetera. >> And it's even a building partner, right? So it's an infrastructure partner, it's a delivery slash sales channel partner, and there you can even build directly through Amazon, if I heard right today. >> That's right. So we're both a customer and a partner is one way to think about it. And today in the keynote, we announced with their new AWS marketplace, SaaS Contracts API release, that we're one of their first partners delivering our product through that new delivery model. And what's really interesting about it is today enterprises are trying to innovate faster. They get stuck sometimes through things that shouldn't matter. Procurement, legal, how do you actually get the assets that you need in order to do the things they need to do? Speed is such an important part of being successful. And now that we can deliver Splunk through the AWS marketplace, customers can easily find it. They can now easily buy it using their existing building relationship with Amazon. They can use friendly terms that are defined there. And they can buy on one year, two year or three year contracts with the appropriate term-based discount. So the longer you buy, the cheaper it is. So, procurement's happy, legal's happy, the technical user's happy 'cause they can move faster than they ever have before. >> One of things that we're hearing in a lot of enterprises is that directives coming down from the board to the CIO. You've got to move more legacy applications to the hub, but you've also got to try to find more value from digital assets. With that respect, what are some of the core functions that Splunk Enterprise on AWS is delivering to customers from a value out of our assets perspective? >> There's assets across so many different categories, so we look at, what are we doing across the infrastructure side of the business? What are we doing across the security side of the business and now this emerging category of IOT, how do we get all of the assets working together? And one of the things that we think about a lot with our customers is we have all this data. How do you apply different lenses so that different people can ask different questions of this same data and get the key insights back. So if I'm a security investigatory trying to prevent fraud, that's something that we can do, but that's also helping the people in IT maintain systems faster and it's also doing business, process management, working with supply chain and we see that happening everywhere. We were talking just before we started about this mental model that enterprises have where they're stuck in this reactive place. Something breaks, then you fix it. Or a customer complains and you deal with it and everyone's on this journey to being more proactive. How do I get notified that something broke so that I can fix it, or better yet, predictive? So we're taking machine learning and artificial intelligence concepts, baking them in directly into the Splunk platform and using that to help people go from that reactive state that they're in to this forward state of predictive intelligence and being able to fix things before they even become a problem. >> I would love to dig in a little bit deeper on IOT, 'cause you guys are into IOT when it was called machines. Machines are just a subset of the things and now, the IOT thing is really taking off. Obviously, we to the GE shows and also people are things, too, which sometimes gets forgotten in the conversations, and we all throw off a ton of digitals off, so you guys are pretty well positioned to apply your technology techniques, processes now to a whole giant new set of data flows coming off all these things. >> You put the words in my mouth. People forget about people being things. We talk about machine data, the word machine can mean anything, really. It's how do you take all of this data, correlate it together in interesting ways, then do something with it. Thing about the retail use case. Customers now have an expectation of the experience that they're going to have, higher than ever before. You just expect more, you know they have the information, so you want it. You think about beacons and knowing your preferences, so retailers need to take advantage of that and they can use technology like Splunk to really get there. Another example around customer expectation, think about travel. We all travel here, you guys probably flew in or drove in, and we have mediocre experiences at the airport in particular. We have a customer Gatwick Airports in the UK who's completely Splunked everything they're doing at the airport with a goal of reducing the amount of time that it takes to go from the front desk to your gate to less than five minutes. So on a dashboard, they can see wait times at any particular security terminal, they can redeploy assets, they get alerts, and they can monitor all the different data streams, whether it's weather data, air traffic control data, airline data, sensors from all the different parts of the airport, and pull all that together into a people-based experience to drive up that engagement. >> Gatwick, great example, and your CEO was also talking about Coca Cola on stage, for example. You've got over 13,000 customers, so as we look at where we are today with cloud users maturing, cloud providers maturing, looking at what Amazon has to date, over 90 services. As customers look at getting more legacy applications out of operations, how is Splunk helping customers on this journey to hybrid, or is hybrid a destination? What's the conversation there like with the senior leaders that you talk to down to the IT folks? >> In my job, I get the luxury of talking to hundreds of CIOs and I'll tell you, all of them see hybrid as the destination. Most of the enterprises that exist in the world have investments in things from mainframes to existing infrastructure and data centers and even as they consolidate more and more into the cloud, we're going to be in a world where people have assets in many different places. What we've seen with Amazon and why I think our partnership has been so successful is we're helping a lot of these enterprises justify and control how they're able to get to the cloud faster. We talked about innovation and speed. Being able to adopt services in the cloud in addition to what we're doing on premise is critical. And with Splunk, they get insight across all their different components. They feel that they can manage the security across both on premises and the cloud and they get the peace of mind that they have that operational visibility because they're going to be hybrid, they're going to be running in the cloud, they're always going to have their existing investments. That's kind of the state of the world for the foreseeable future. >> So, looking forward, you've been in the job about six months or so, what are your priorities for the next six months? Doug says, "alright, warm up time's over, "get to work, Brian." >> He said that on the third day. >> (laughs) On the third day. So what are some of your priorities? >> As a business, we have a collection of priorities. One is the cloud, full stop. We know that the journey to the cloud is coming full speed and what we can do around Splunk cloud and being able to fulfill and delivers services for our customers there is absolutely critical and continuing to grow that capability. And second for us is customer success. How we get people beyond single use case to multi use case. Using it in IT, how to take advantage of it in security. How do you take advantage of it in supply chain? Because that magic moment that customers have is really when they have the same data in and they get value across their entire business. For me, as the CMO, my priority is piggy back on that. First and foremost is digital. It's kind of trite, everyone's talking about it but I came from Google and sales force. I'm a performance guy and so I'm looking at how we can reconstitute the entire buyer journey from the moment someone says, "I'm interested "in a topic that's relevant to our product" to "I transact online" and that's a big initiative for what we're doing across web and sales team to work through all those pieces, and then second, I now am the chief t-shirt officer. >> Jeff: That's not an easy job. >> It's the hardest job I've ever had, 'cause I'm not in my strength and always innovating on what's next. I hear I was trending on Twitter, Doug's t-shirt versus Werner's t-shirt today. >> Jeff: That's right. >> I think we were winning. >> And you guys have the biggest t-shirt booth installation, device at trade shows than anyone rather than just giving away, in the back, the entire booth is basically built around the t-shirts. >> Oh, and we're Splunking everything, too. >> Impressive. >> And we saw a spike in traffic, too. Our store this morning after we went on stage. >> I put the picture up, so I sent the link, hopefully it will get me some Amazon affiliate money back. I don't know. >> The t-shirts match the buyer's journey. >> Of course. >> Of course, as a marketer, of course. >> Stop chasing your tail dash f. You got to connect to your logs and always keep watching. >> Before we let you go, let's get a plug in for splunk.conf. The Cube has been going, I think this will be our fifth or sixth year, I can't count that high, I'm out of fingers and toes. >> Eighth. >> Your eighth, our sixth there, I think. >> There you go, you're a regular. >> So where is it, what's the highlights this year? It's always a great event. >> Much like AWS, we're doing events all across the world all the time. We have a series called Splunk live, we just did one in San Francisco last week which are super great ways to come and learn about the product and get hands-on keyboard to improve your skills, but it all culminates in .conf which is our leading event in the category. It's going to be in D.C. this year, September 25th to 28th and that's the best place to come, learn about Splunk, get hands-on with the product, meet the product team, learn from your peers, which to me, is the thing that matters the most. To see all the innovative ideas that everyone is doing, 'cause one of the great things about Splunk is the use cases for the product are basically infinite, and so you hear more and more stories, whether it's the city of San Francisco or shazaam or Yelp or Gatwick or thousands of others and .conf is the place, so you guys are going to be there, I'm going to be there, which is the reason everyone should come, obviously. >> Exactly, t-shirts for all. >> Brian: T-shirts for everybody. >> Well, Brian Goldfarb, CMO of Splunk, I got that right this time, thank you so much. >> Brian: And the Cube. >> And the Cube, apparently. (laughs) >> Jeff: Watch out, John, we've got a new CMO. >> Lisa: Thank you so much for joining us. Great, your passion is evident, we wish you the best of luck and continued success in your role. For my co-host Jeff Frick, I'm Lisa Martin. We are live at the AWS Summit San Francisco. Stick around, we'll be right back. (upbeat music) Is changing and this entire process, you started to mention a little bit, how is-- (upbeat music)

>> Announcer: Live from San Francisco, it's the Cube, covering AWS Summit 2017. Brought to you by Amazon Web Services. >> Hi, welcome to the Cube. We are live in San Francisco, at the Amazon Web Services Summit, 2017 AWS Summit. I'm Lisa Martin, with my co-host Jeff Frick. We've got George Gilbert here, as well. Packed house here. We all just came from the keynote, where there were some fantastic announcements. Lot of passion, Dr. Werner Vogels, the CTO and VP at AWS did a fantastic keynote, and some of the themes that I heard, guys, were really customers, customers, customers. We know how obsessed AWS is with customers. A lot of great announcements, all really substantiated by phenomenal customers from enterprise, startups, public sector. We've obviously seen how quickly they've been innovating. They've done a fantastic job turning this first mover status into sustained market leadership. What are some of the things, Jeff, that really kind of caught your eye in the CTO's keynote this morning? >> Lisa, the thing that I was actually taken back to Tuesday night with James Hamilton at AWS re:Invent, which if you are not going to re:Invent, you should register just for that. And really, the idea is that scale just trumps everything. And because Amazon has so many customers in so many areas, they can apply such scale to all their infrastructure, across such a broad array of services. I mean, all the slides that Werner kept popping up had so many little squares, 'cause they have so many services, so if you need fast I/O, you need fast compute, you want facial recognition, you want machine learning, they have a set of services for you. So a lot of people talk about the application-centric view of the world, but Amazon is actually delivering that to people, and they had Nextdoor app as kind of their showcase customer where they focus on the application, because Amazon does the rest, and now I thought it was interesting now they're moving into the development sphere. So now you can do your native development in AWS. Again, use that set of services that most apply to the applications you're building, and focus on your application and your customer. I mean, how do you compete with the scale? And who wants to compete in infrastructure scale if you're a company that's building a web-centric or native application? The other thought I think was interesting, at the beginning, he had his NASCAR slides, his logo slides, went through the startups, great, went through the enterprises, great, went through public sector, great, went through ISVs, great, went through system integrators, great. I mean, the ecosystem is phenomenal. So again, James Hamilton, I just love his talks, but the amount of resources he can apply to his business problems, compared to any individual company, it's just, you can't even compare. What'd you think, George? >> I look at the capabilities, the top three vendors are providing. You know, Amazon, Azure, and Google. And they each bring some different strengths to bear. Google is still building out for commercial access to services that they built internally for their own use. So you have what's a spectacular relational database that's globally distributed, called Spanner, but it's not actually something that commercial customers are used to. That's was built really for Google internal gurus. Now, it's in many ways better than anything that commercial developers have access to, but it's a bit of a migration hurdle in terms of learning. So, now, Amazon took, they took their internal infrastructure, but they built it so much differently. It wasn't meant to sort of stretch the capabilities of their internal developers and external developers. But they've been getting richer over time. Let's just use an example of a product that got significantly enhanced today. Redshift, which with, they called it Spectrum. Redshift used to be a traditional MPP data warehouse, and its data was tied into the same servers, or nodes, as the compute analytic functions. And so it was not that elastic, it was almost like a on PRIM product ported to the cloud, but they've been improving it, and today, there was a huge step forward where they put the storage on S3, which is completely separate from the sequel, Compute. And so now they go from what was essentially data warehouse that can max out at two petabytes to something that can go to the exabyte range. And because the data's on a cheap S3 storage, you can spend the compute down, and then you're just essentially paying for archive. So that's something that now looks more like Snowflake which was the best in class cloud data warehouse up until this point. Now there, I'm sure, are many other differences. But Amazon has that iteration to taking more and more advantage of taking what were conventional products and turning them into, you know, cloud ready services. >> You mention the re:Invent show last November. 32,000 attendees, sold out. >> Right, right. >> Lisa: And then 50,000 watching the livestream of the keynote. Andy Jassy was on the Cube talking with John and one of the things that I found interesting about that and also, some recent press that Andy has done is talking about how, which they're normally very customer focused, and the theme today was customer obsession, which I think we saw with all those logos up there. But they talk about, they don't really talk about competition. What, one of the things that I found interesting was that Andy has talked recently about them being six to seven years ahead of their competition. We see them continue to innovate. Add capabilities, add technology integrations. Jeff, you mentioned the ecosystem partners growing. We've had a number of them on the show today. They're so far ahead of competitors. And kind of going off what you said about Google, George. Amazon is now starting to productize some of the technologies like Amazon Connect that was announced last month, a virtual call center, that they use in-house, which is something we hadn't seen from a Google yet. >> That's a great point. And that was actually one of the differences, that I didn't get to sort of talking database. But both companies or all, Amazon, Azure, Google, IBM, all have really advanced machine learning, essentially engines and algorithms. But what makes machine learning really useful as the data is when you combine those with the data that trains those algorithms. And that's what makes essentially application ready services. Otherwise it's just tooling. And Google can leverage its data for, from search, from voice search, from video and image recognition with YouTube. So it has a bunch of machine learning services that are good for a conversational user interface and a visual user interface, but what Amazon is going... Amazon is leveraging the Alexa and Echo product to get, to train their natural language understanding and speech to text, text to speech. So that was added to today. But the thing that they're doing that's really interesting that Google and Microsoft can't yet is they're taking the machine learning capabilities that they use for fashion merchandising, price optimization, fulfillment, and they're going to be taking those and putting them out on AWS for developers to use just the way they their compute and basic software middleware and put them out for other companies to use. So in other words, they're going to take some of their core, most core mission critical, machine learning capabilities and open them up for others. But the key thing is they're trained on Amazon data so that they're immediately useful by corporate developers, not data scientists. And that's something in those areas where Amazon's unique. Every cloud vendor will have their, you know, areas of data where they can make it accessible to corporate developers. But Amazon has a unique set. >> And the other thing we talk often about, founder-led companies. And I think the culture thing, it just can't be overstated. Recently, Jeff Bezos says day one, you know, kind of internal memo is making the rounds again on social media. So I took a minute to reread it and you know, we talk often on the key of are we in the first inning, are we in the second inning or the third inning of whatever trend we happen to be covering, and I think his attitude that it's always day one is pretty significant. And you can't bet against the guy. That's why I love to say never bet against Bezos, 'cause he's got a vision, he's got to execute it. And the team that he's put in place with Andy, you know, it's just a quiet execution. Like you said, they don't really look at the competition. That's not who they're competing against. Werner said it today. They're competing against time. And their customers are competing against time. And I thought the examples again, from the keynote of next door about the time compression for all the various processes in their company were giant, which allow again, better application development. It allows their customers to better serve their customers. And I don't think that can be really overstated. And you don't get that as much in Google, where you know, Google Cloud is a different thing and they brought in new leadership. Obviously Satya has done a hell of a job turning Microsoft around from what it was before. But you know, you just see this quiet, confident execution within AWS team that I think is pretty special. >> There's one thing... Oh, sorry Lisa, let me just add on that execution point and the lead that they have over the competition. Internally, Andy Jassy tells his team there's no compression algorithm for a lead time of six years. It's not like just because Azure got started a little bit later, and they know what things are going to look like sooner because they can see the future before Amazon had to wait ten years to get there. That, you still have to go through that learning curve. And in other words what he's trying to say is their lead is, it's not, they can maintain their lead just by continuing to execute that flywheel affect that Jeff was talking about. >> Right and they continue to innovate. One of the things that I know that Jeff, you and John, George, have been following AWS since symphysis ten years ago. And they continue to innovate, they continue to add integrations. One thing that I was particularly interested in and just doing some prep for today's event is what they announced with VMware a few months ago. VMware vSphere base cloud services. Is that a... Couple things. Is that a foray to be able to bring VMware legacy customer applications into the cloud? Is that maybe a step towards saying hey, we're ready to start taking our customers to hybrid cloud? I'm curious to hear from some of our guests today what they think the next steps are. It wasn't talked about in the keynote but if you talk about competition, or rather growth, one of the areas that they've really excelled in obviously with the developer community and the start-ups, where they started is in greenfield, right. They have a great rich set of application developmentals, ideal for cloud development, ideal for greenfield. If you look at the legacy application space, you might think Microsoft, IBM, do they have an advantage there. But now what Amazon's doing in hopefully later this year with VMware is that, a bat signal. That hey, we're ready to take these customers and their legacy applications into the cloud as a competitive signal or really as a signal to hey, customers, we're ready to take you to the hybrid cloud. What are your thoughts on that? >> I guess that they started with start-ups. They were the ones who were the most demanding on the infrastructure because they were greenfield apps. And so there was, you know, they needed to go beyond the constraints of legacy systems. And in fact, Satya Nadella said of Azure, we need our Netflix, which was, you know the lighthouse customer for Amazon that was always pushing the envelope of what was possible. What's happening now though is that there was this journey that I just want to touch on that there was a pre-brief yesterday about the sort of the typical customer journey where they start with dev test workloads, then they go to new greenfield apps, then digital experience and user experience, then analytics and mobile. And what's now happening is that we're getting to the mission critical systems. And that's why like we heard a lot on database issues. 'Cause that's where, application databases are the foundation of mission critical apps. >> Speaking of that, I think, well we're really excited. We have a great guest line up today. We've got Splunk's CMO on the show. We've got a number of ecosystem partners. Datadog as well, so guys I think it's going to be a fantastic day. A lot to talk about. Really excited to hear about a lot of the innovation, the evolution that's going on and where these partners are going to be able to take their customers next. So, you're watching the Cube. Again, we're live at the Amazon Web Services Summit in San Francisco for George Gilbert and Jeff Frick, I'm Lisa Martin. Stick around, we'll be right back. (techno music)