(gentle electronic music) >> Hello, everybody, welcome back to the Virtual Vertica Big Data Conference. My name is Dave Vellante and you're watching theCUBE, the leader in digital coverage. This is the Virtual BDC, as I said, theCUBE has covered every Big Data Conference from the inception, and we're pleased to be a part of this, even though it's challenging times. I'm here with Dan Woicke, the senior director of CernerWorks Engineering. Dan, good to see ya, how are things where you are in the middle of the country? >> Good morning, challenging times, as usual. We're trying to adapt to having the kids at home, out of school, trying to figure out how they're supposed to get on their laptop and do virtual learning. We all have to adapt to it and figure out how to get by. >> Well, it sure would've been my pleasure to meet you face to face in Boston at the Encore Casino, hopefully next year we'll be able to make that happen. But let's talk about Cerner and CernerWorks Engineering, what is that all about? >> So, CernerWorks Engineering, we used to be part of what's called IP, or Intellectual Property, which is basically the organization at Cerner that does all of our software development. But what we did was we made a decision about five years ago to organize my team with CernerWorks which is the hosting side of Cerner. So, about 80% of our clients choose to have their domains hosted within one of the two Kansas City data centers. We have one in Lee's Summit, in south Kansas City, and then we have one on our main campus that's a brand new one in downtown, north Kansas City. About 80, so we have about 27,000 environments that we manage in the Kansas City data centers. So, what my team does is we develop software in order to make it easier for us to monitor, manage, and keep those clients healthy within our data centers. >> Got it. I mean, I think of Cerner as a real advanced health tech company. It's the combination of healthcare and technology, the collision of those two. But maybe describe a little bit more about Cerner's business. >> So we have, like I said, 27,000 facilities across the world. Growing each day, thank goodness. And, our goal is to ensure that we reduce errors and we digitize the entire medical records for all of our clients. And we do that by having a consulting practice, we do that by having engineering, and then we do that with my team, which manages those particular clients. And that's how we got introduced to the Vertica side as well, when we introduced them about seven years ago. We were actually able to take a tremendous leap forward in how we manage our clients. And I'd be more than happy to talk deeper about how we do that. >> Yeah, and as we get into it, I want to understand, healthcare is all about outcomes, about patient outcomes and you work back from there. IT, for years, has obviously been a contributor but removed, and somewhat indirect from those outcomes. But, in this day and age, especially in an organization like yours, it really starts with the outcomes. I wonder if you could ratify that and talk about what that means for Cerner. >> Sorry, are you talking about medical outcomes? >> Yeah, outcomes of your business. >> So, there's two different sides to Cerner, right? There's the medical side, the clinical side, which is obviously our main practice, and then there's the side that I manage, which is more of the operational side. Both are very important, but they go hand in hand together. On the operational side, the goal is to ensure that our clinicians are on the system, and they don't know they're on the system, right? Things are progressing, doctors don't want to be on the system, trust me. My job is to ensure they're having the most seamless experience possible while they're on the EMR and have it just be one of their side jobs as opposed to taking their attention away from the patients. That make sense? >> Yeah it does, I mean, EMR and meaningful use, around the Affordable Care Act, really dramatically changed the unit. I mean, people had to demonstrate in order to get paid, and so that became sort of an unfunded mandate for folks and you really had to respond to that, didn't you? >> We did, we did that about three to four years ago. And we had to help our clients get through what's called meaningful use, there was different stages of meaningful use. And what we did, is we have the website called the Lights On Network which is free to all of our clients. Once you get onto the website the Lights On Network, you can actually show how you're measured and whether or not you're actually completing the different necessary tasks in order to get those payments for meaningful use. And it also allows you to see what your performance is on your domain, how the clinicians are doing on the system, how many hours they're spending on the system, how many orders they're executing. All of that is completely free and visible to our clients on the Lights On Network. And that's actually backed by some of the Vertica software that we've invested in. >> Yeah, so before we get into that, it sounds like your mission, really, is just great user experiences for the people that are on the network. Full stop. >> We do. So, one of the things that we invented about 10 years ago is called RTMS Timers. They're called Response Time Measurement System. And it started off as a way of us proving that clients are actually using the system, and now it's turned into more of a user outcomes. What we do is we collect 2.5 billion timers per day across all of our clients across the world. And every single one of those records goes to the Vertica platform. And then we've also developed a system on that which allows us in real time to go and see whether or not they're deviating from their normal. So we do baselines every hour of the week and then if they're deviating from those baselines, we can immediately call a service center and have them engage the client before they call in. >> So, Dan, I wonder if you could paint a picture. By the way, that's awesome. I wonder if you could paint a picture of your analytics environment. What does it look like? Maybe give us a sense of the scale. >> Okay. So, I've been describing how we operate, our remote hosted clients in the two Kansas City data centers, but all the software that we write, we also help our client hosted agents as well. Not only do we take care of what's going on at the Kansas City data center, but we do write software to ensure that all of clients are treated the same and we provide the same level of care and performance management across all those clients. So what we do is we have 90,000 agents that we have split across all these clients across the world. And every single hour, we're committing a billion rows to Vertica of operational data. So I talked a little bit about the RTMS timers, but we do things just like everyone else does for CPU, memory, Java Heap Stack. We can tell you how many concurrent users are on the system, I can tell you if there's an application that goes down unexpected, like a crash. I can tell you the response time from the network as most of us use Citrix at Cerner. And so what we do is we measure the amount of time it takes from the client side to PCs, it's sitting in the virtual data centers, sorry, in the hospitals, and then round trip to the Citrix servers that are sitting in the Kansas City data center. That's called the RTT, our round trip transactions. And what we've done is, over the last couple of years, what we've done is we've switched from just summarizing CPU and memory and all that high-level stuff, in order to go down to a user level. So, what are you doing, Dr. Smith, today? How many hours are you using the EMR? Have you experienced any slowness? Have you experienced any hourglass holding within your application? Have you experienced, unfortunately, maybe a crash? Have you experienced any slowness compared to your normal use case? And that's the step we've taken over the last few years, to go from summarization of high-level CPU memory, over to outcome metrics, which are what is really happening with a particular user. >> So, really granular views of how the system is being used and deep analytics on that. I wonder, go ahead, please. >> And, we weren't able to do that by summarizing things in traditional databases. You have to actually have the individual rows and you can't summarize information, you have to have individual metrics that point to exactly what's going on with a particular clinician. >> So, okay, the MPP architecture, the columnar store, the scalability of Vertica, that's what's key. That was my next question, let me take us back to the days of traditional RDBMS and then you brought in Vertica. Maybe you could give us a sense as to why, what that did for you, the before and after. >> Right. So, I'd been painting a picture going forward here about how traditionally, eight years ago, all we could do was summarize information. If CPU was going to go and jump up 8%, I could alarm the data center and say, hey, listen, CPU looks like it's higher, maybe an application's hanging more than it has been in the past. Things are a little slower, but I wouldn't be able to tell you who's affected. And that's where the whole thing has changed, when we brought Vertica in six years ago is that, we're able to take those 90,000 agents and commit a billion rows per hour operational data, and I can tell you exactly what's going on with each of our clinicians. Because you know, it's important for an entire domain to be healthy. But what about the 10 doctors that are experiencing frustration right now? If you're going to summarize that information and roll it up, you'll never know what those 10 doctors are experiencing and then guess what happens? They call the data center and complain, right? The squeaky wheels? We don't want that, we want to be able to show exactly who's experiencing a bad performance right now and be able to reach out to them before they call the help desk. >> So you're able to be proactive there, so you've gone from, Houston, we have a problem, we really can't tell you what it is, go figure it out, to, we see that there's an issue with these docs, or these users, and go figure that out and focus narrowly on where the problem is as opposed to trying to whack-a-mole. >> Exactly. And the other big thing that we've been able to do is corelation. So, we operate two gigantic data centers. And there's things that are shared, switches, network, shared storage, those things are shared. So if there is an issue that goes on with one of those pieces of equipment, it could affect multiple clients. Now that we have every row in Vertica, we have a new program in place called performance abnormality flags. And what we're able to do is provide a website in real time that goes through the entire stack from Citrix to network to database to back-end tier, all the way to the end-user desktop. And so if something was going to be related because we have a network switch going out of the data center or something's backing up slow, you can actually see which clients are on that switch, and, what we did five years ago before this, is we would deploy out five different teams to troubleshoot, right? Because five clients would call in, and they would all have the same problem. So, here you are having to spare teams trying to investigate why the same problem is happening. And now that we have all of the data within Vertica, we're able to show that in a real time fashion, through a very transparent dashboard. >> And so operational metrics throughout the stack, right? A game changer. >> It's very compact, right? I just label five different things, the stack from your end-user device all the way through the back-end to your database and all the way back. All that has to work properly, right? Including the network. >> How big is this, what are we talking about? However you measure it, terabytes, clusters. What can you share there? >> Sorry, you mean, the amount of data that we process within our data centers? >> Give us a fun fact. >> Absolute petabytes, yeah, for sure. And in Vertica right now we have two petabytes of data, and I purge it out every year, one year's worth of data within two different clusters. So we have to two different data centers I've been describing, what we've done is we've set Vertica up to be in both data centers, to be highly redundant, and then one of those is configured to do real-time analysis and corelation research, and then the other one is to provide service towards what I described earlier as our Lights On Network, so it's a very dedicated hardened cluster in one of our data centers to allow the Lights On Network to provide the transparency directly to our clients. So we want that one to be pristine, fast, and nobody touch it. As opposed to the other one, where, people are doing real-time, ad hoc queries, which sometimes aren't the best thing in the world. No matter what kind of database or how fast it is, people do bad things in databases and we just don't want that to affect what we show our clients in a transparent fashion. >> Yeah, I mean, for our audience, Vertica has always been aimed at these big, hairy, analytic problems, it's not for a tiny little data mart in a department, it's really the big scale problems. I wonder if I could ask you, so you guys, obviously, healthcare, with HIPAA and privacy, are you doing anything in the cloud, or is it all on-prem today? >> So, in the operational space that I manage, it's all on-premises, and that is changing. As I was describing earlier, we have an initiative to go to AWS and provide levels of service to countries like Sweden which does not want any operational data to leave that country's walls, whether it be operational data or whether it be PHI. And so, we have to be able to adapt into Vertia Eon Mode in order to provide the same services within Sweden. So obviously, Cerner's not going to go up and build a data center in every single country that requires us, so we're going to leverage our partnership with AWS to make this happen. >> Okay, so, I was going to ask you, so you're not running Eon Mode today, it's something that you're obviously interested in. AWS will allow you to keep the data locally in that region. In talking to a lot of practitioners, they're intrigued by this notion of being able to scale independently, storage from compute. They've said they wished that's a much more efficient way, I don't have to buy in chunks, if I'm out of storage, I don't have to buy compute, and vice-versa. So, maybe you could share with us what you're thinking, I know it's early days, but what's the logic behind the business case there? >> I think you're 100% correct in your assessment of taking compute away from storage. And, we do exactly what you say, we buy a server. And it has so much compute on it, and so much storage. And obviously, it's not scaled properly, right? Either storage runs out first or compute runs out first, but you're still paying big bucks for the entire server itself. So that's exactly why we're doing the POC right now for Eon Mode. And I sit on Vertica's TAB, the advisory board, and they've been doing a really good job of taking our requirements and listening to us, as to what we need. And that was probably number one or two on everybody's lists, was to separate storage from compute. And that's exactly what we're trying to do right now. >> Yeah, it's interesting, I've talked to some other customers that are on the customer advisory board. And Vertica is one of these companies that're pretty transparent about what goes on there. And I think that for the early adopters of Eon Mode there were some challenges with getting data into the new system, I know Vertica has been working on that very hard but you guys push Vertica pretty hard and from what I can tell, they listen. Your thoughts. >> They do listen, they do a great job. And even though the Big Data Conference is canceled, they're committed to having us go virtually to the CAD meeting on Monday, so I'm looking forward to that. They do listen to our requirements and they've been very very responsive. >> Nice. So, I wonder if you could give us some final thoughts as to where you want to take this thing. If you look down the road a year or two, what does success look like, Dan? >> That's a good question. Success means that we're a little bit more nimble as far as the different regions across the world that we can provide our services to. I want to do more corelation. I want to gather more information about what users are actually experiencing. I want to be able to have our phone never ring in our data center, I know that's a grand thought there. But I want to be able to look forward to measuring the data internally and reaching out to our clients when they have issues and then doing the proper corelation so that I can understand how things are intertwining if multiple clients are having an issue. That's the goal going forward. >> Well, in these trying times, during this crisis, it's critical that your operations are running smoothly. The last thing that organizations need right now, especially in healthcare, is disruption. So thank you for all the hard work that you and your teams are doing. I wish you and your family all the best. Stay safe, stay healthy, and thanks so much for coming on theCUBE. >> I really appreciate it, thanks for the opportunity. >> You're very welcome, and thank you, everybody, for watching, keep it right there, we'll be back with our next guest. This is Dave Vellante for theCUBE. Covering Virtual Vertica Big Data Conference. We'll be right back. (upbeat electronic music)

>> Live from San Jose, in the heart of Silicon Valley, it's theCUBE, covering DataWorks Summit 2018, brought to you by Hortonworks. >> Welcome back to theCUBE's live coverage of DataWorks here in San Jose, California. I'm your host, Rebecca Knight, along with my co-host, James Kobielus. We're joined by Stephanie McReynolds. She is the Vice President of Marketing at Alation. Thanks so much for, for returning to theCUBE, Stephanie. >> Thank you for having me again. >> So, before the cameras were rolling, we were talking about Kevin Slavin's talk on the main stage this morning, and talking about, well really, a background to sort of this concern about AI and automation coming to take people's jobs, but really, his overarching point was that we really, we shouldn't, we shouldn't let the algorithms take over, and that humans actually are an integral piece of this loop. So, riff on that a little bit. >> Yeah, what I found fascinating about what he presented were actual examples where having a human in the loop of AI decision-making had a more positive impact than just letting the algorithms decide for you, and turning it into kind of a black, a black box. And the issue is not so much that, you know, there's very few cases where the algorithms make the wrong decision. What happens the majority of the time is that the algorithms actually can't be understood by human. So if you have to roll back >> They're opaque, yeah. >> in your decision-making, or uncover it, >> I mean, who can crack what a convolutional neural network does, at a layer by layer, nobody can. >> Right, right. And so, his point was, if we want to avoid not just poor outcomes, but also make sure that the robots don't take over the world, right, which is where every like, media person goes first, right? (Rebecca and James laugh) That you really need a human in the loop of this process. And a really interesting example he gave was what happened with the 2015 storm, and he talked about 16 different algorithms that do weather predictions, and only one algorithm predicted, mis-predicted that there would be a huge weather storm on the east coast. So if there had been a human in the loop, we wouldn't have, you know, caused all this crisis, right? The human could've >> And this is the storm >> Easily seen. >> That shut down the subway system, >> That's right. That's right. >> And really canceled New York City for a few days there, yeah. >> That's right. So I find this pretty meaningful, because Alation is in the data cataloging space, and we have a lot of opportunity to take technical metadata and automate the collection of technical and business metadata and do all this stuff behind the scenes. >> And you make the discovery of it, and the analysis of it. >> We do the discovery of this, and leading to actual recommendations to users of data, that you could turn into automated analyses or automated recommendations. >> Algorithmic, algorithmically augmented human judgment is what it's all about, the way I see it. What do you think? >> Yeah, but I think there's a deeper insight that he was sharing, is it's not just human judgment that is required, but for humans to actually be in the loop of the analysis as it moves from stage to stage, that we can try to influence or at least understand what's happening with that algorithm. And I think that's a really interesting point. You know, there's a number of data cataloging vendors, you know, some analysts will say there's anywhere from 10 to 30 different vendors in the data cataloging space, and as vendors, we kind of have this debate. Some vendors have more advanced AI and machine learning capabilities, and other vendors haven't automated at all. And I think that the answer, if you really want humans to adopt analytics, and to be comfortable with the decision-making of those algorithms, you need to have a human in the loop, in the middle of that process, of not only making the decision, but actually managing the data that flows through these systems. >> Well, algorithmic transparency and accountability is an increasing requirement. It's a requirement for GDPR compliance, for example. >> That's right. >> That I don't see yet with Wiki, but we don't see a lot of solution providers offering solutions to enable more of an automated roll-up of a narrative of an algorithmic decision path. But that clearly is a capability as it comes along, and it will. That will absolutely depend on a big data catalog managing the data, the metadata, but also helping to manage the tracking of what models were used to drive what decision, >> That's right. >> And what scenario. So that, that plays into what Alation >> So we talk, >> And others in your space do. >> We call that data catalog, almost as if the data's the only thing that we're tracking, but in addition to that, that metadata or the data itself, you also need to track the business semantics, how the business is using or applying that data and that algorithmic logic, so that might be logic that's just being used to transform that data, or it might be logic to actually make and automate decision, like what they're talking about GDPR. >> It's a data artifact catalog. These are all artifacts that, they are derived in many ways, or supplement and complement the data. >> That's right. >> They're all, it's all the logic, like you said. >> And what we talk about is, how do you create transparency into all those artifacts, right? So, a catalog starts with this inventory that creates a foundation for transparency, but if you don't make those artifacts accessible to a business person, who might not understand what is metadata, what is a transformation script. If you can't make that, those artifacts accessible to a, what I consider a real, or normal human being, right, (James laughs) I love to geek out, but, (all laugh) at some point, not everyone is going to understand. >> She's the normal human being in this team. >> I'm normal. I'm normal. >> I'm the abnormal human being among the questioners here. >> So, yeah, most people in the business are just getting our arms around how do we trust the output of analytics, how do we understand enough statistics and know what to apply to solve a business problem or not, and then we give them this like, hairball of technical artifacts and say, oh, go at it. You know, here's your transparency. >> Well, I want to ask about that, that human that we're talking about, that needs to be in the loop at every stage. What, that, surely, we can make the data more accessible, and, but it also requires a specialized skill set, and I want to ask you about the talent, because I noticed on your LinkedIn, you said, hey, we're hiring, so let me know. >> That's right, we're always hiring. We're a startup, growing well. >> So I want to know from you, I mean, are you having difficulty with filling roles? I mean, what is at the pipeline here? Are people getting the skills that they need? >> Yeah, I mean, there's a wide, what I think is a misnomer is there's actually a wide variety of skills, and I think we're adding new positions to this pool of skills. So I think what we're starting to see is an expectation that true business people, if you are in a finance organization, or you're in a marketing organization, or you're in a sales organization, you're going to see a higher level of data literacy be expected of that, that business person, and that's, that doesn't mean that they have to go take a Python course and learn how to be a data scientist. It means that they have to understand statistics enough to realize what the output of an algorithm is, and how they should be able to apply that. So, we have some great customers, who have formally kicked off internal training programs that are data literacy programs. Munich Re Insurance is a good example. They spoke with James a couple of months ago in Berlin. >> Yeah, this conference in Berlin, yeah. >> That's right, that's right, and their chief data officer has kicked off a formal data literacy training program for their employees, so that they can get business people comfortable enough and trusting the data, and-- >> It's a business culture transformation initiative that's very impressive. >> Yeah. >> How serious they are, and how comprehensive they are. >> But I think we're going to see that become much more common. Pfizer has taken, who's another customer of ours, has taken on a similar initiative, and how do they make all of their employees be able to have access to data, but then also know when to apply it to particular decision-making use cases. And so, we're seeing this need for business people to get a little bit of training, and then for new roles, like information stewards, or data stewards, to come online, folks who can curate the data and the data assets, and help be kind of translators in the organization. >> Stephanie, will there be a need for a algorithm curator, or a model curator, to, you know, like a model whisperer, to explain how these AI, convolutional, recurrent, >> Yeah. >> Whatever, all these neural, how, what they actually do, you know. Would there be a need for that going forward? Another as a normal human being, who can somehow be bilingual in neural net and in standard language? >> I think, I think so. I mean, I think we've put this pressure on data scientists to be that person. >> Oh my gosh, they're so busy doing their job. How can we expect them to explain, and I mean, >> Right. >> And to spend 100% of their time explaining it to the rest of us? >> And this is the challenge with some of the regulations like GDPR. We aren't set up yet, as organizations, to accommodate this complexity of understanding, and I think that this part of the market is going to move very quickly, so as vendors, one of the things that we can do is continue to help by building out applications that make it easy for information stewardship. How do you lower the barrier for these specialist roles and make it easy for them to do their job by using AI and machine learning, where appropriate, to help scale the manual work, but keeping a human in the loop to certify that data asset, or to add additional explanation and then taking their work and using AI, machine learning, and automation to propagate that work out throughout the organization, so that everyone then has access to those explanations. So you're no longer requiring the data scientists to hold like, I know other organizations that hold office hours, and the data scientist like sits at a desk, like you did in college, and people can come in and ask them questions about neural nets. That's just not going to scale at today's pace of business. >> Right, right. >> You know, the term that I used just now, the algorithm or model whisperer, you know, the recommend-er function that is built into your environment, in similar data catalog, is a key piece of infrastructure to rank the relevance rank, you know, the outputs of the catalog or responses to queries that human beings might make. You know, the recommendation ranking is critically important to help human beings assess the, you know, what's going on in the system, and give them some advice about how to, what avenues to explore, I think, so. >> Yeah, yeah. And that's part of our definition of data catalog. It's not just this inventory of technical metadata. >> That would be boring, and dry, and useless. >> But that's where, >> For most human beings. >> That's where a lot of vendor solutions start, right? >> Yeah. >> And that's an important foundation. >> Yeah, for people who don't live 100% of their work day inside the big data catalog. I hear what you're saying, you know. >> Yeah, so people who want a data catalog, how you make that relevant to the business is you connect those technical assets, that technical metadata with how is the business actually using this in practice, and how can we have proactive recommendation or the recommendation engines, and certifications, and this information steward then communicating through this platform to others in the organization about how do you interpret this data and how do you use it to actually make business decisions. And I think that's how we're going to close the gap between technology adoption and actual data-driven decision-making, which we're not quite seeing yet. We're only seeing about 30, when they survey, only about 36% of companies are actually confident they're making data-driven decisions, even though there have been, you know, millions, if not billions of dollars that have gone into the data analytics market and investments, and it's because as a manager, I don't quite have the data literacy yet, and I don't quite have the transparency across the rest of the organization to close that trust gap on analytics. >> Here's my feeling, in terms of cultural transformations across businesses in general. I think the legal staff of every company is going to need to get real savvy on using those kinds of tools, like your catalog, with recommendation engines, to support e-discovery, or discovery of the algorithmic decision paths that were taken by their company's products, 'cause they're going to be called by judges and juries, under a subpoena and so forth, and so on, to explain all this, and they're human beings who've got law degrees, but who don't know data, and they need the data environment to help them frame up a case for what we did, and you know, so, we being the company that's involved. >> Yeah, and our politicians. I mean, anyone who's read Cathy's book, Weapons of Math Destruction, there are some great use cases of where, >> Math, M-A-T-H, yeah. >> Yes, M-A-T-H. But there are some great examples of where algorithms can go wrong, and many of our politicians and our representatives in government aren't quite ready to have that conversation. I think anyone who watched the Zuckerberg hearings you know, in congress saw the gap of knowledge that exists between >> Oh my gosh. >> The legal community, and you know, and the tech community today. So there's a lot of work to be done to get ready for this new future. >> But just getting back to the cultural transformation needed to be, to make data-driven decisions, one of the things you were talking about is getting the managers to trust the data, and we're hearing about what are the best practices to have that happen in the sense, of starting small, be willing to experiment, get out of the lab, try to get to insight right away. What are, what would your best advice be, to gain trust in the data? >> Yeah, I think the biggest gap is this issue of transparency. How do you make sure that everyone understands each step of the process and has access to be able to dig into that. If you have a foundation of transparency, it's a lot easier to trust, rather than, you know, right now, we have kind of like the high priesthood of analytics going on, right? (Rebecca laughs) And some believers will believe, but a lot of folks won't, and, you know, the origin story of Alation is really about taking these concepts of the scientific revolution and scientific process and how can we support, for data analysis, those same steps of scientific evaluation of a finding. That means that you need to publish your data set, you need to allow others to rework that data, and come up with their own findings, and you have to be open and foster conversations around data in your organization. One other customer of ours, Meijer, who's a grocery store in the mid-west, and if you're west coast or east coast-based, you might not have heard of them-- >> Oh, Meijers, thrifty acres. I'm from Michigan, and I know them, yeah. >> Gigantic. >> Yeah, there you go. Gigantic grocery chain in the mid-west, and, Joe Oppenheimer there actually introduced a program that he calls the social contract for analytics, and before anyone gets their license to use Tableau, or MicroStrategy, or SaaS, or any of the tools internally, he asks those individuals to sign a social contract, which basically says that I'll make my work transparent, I will document what I'm doing so that it's shareable, I'll use certain standards on how I format the data, so that if I come up with a, with a really insightful finding, it can be easily put into production throughout the rest of the organization. So this is a really simple example. His inspiration for that social contract was his high school freshman. He was entering high school and had to sign a social contract, that he wouldn't make fun of the teachers, or the students, you know, >> I love it. >> Very simple basics. >> Yeah, right, right, right. >> I wouldn't make fun of the teacher. >> We all need social contract. >> Oh my gosh, you have to make fun of the teacher. >> I think it was a little more formal than that, in the language, but that was the concept. >> That's violating your civil rights as a student. I'm sorry. (Stephanie laughs) >> Stephanie, always so much fun to have you here. Thank you so much for coming on. >> Thank you. It's a pleasure to be here. >> I'm Rebecca Knight, for James Kobielus. We'll have more of theCUBE's live coverage of DataWorks just after this.

live from Las Vegas it's the Cuban covering AWS reinvent 2017 presented by AWS Intel and our ecosystem of partners ok welcome back everyone we're here live in Las Vegas forty two thousand plus people maybe forty five huge numbers here at AWS reinvent twin seventeen Amazon Web Services annual conference wall-to-wall coverage our third day I'm John Ferrier the co-founder of silicon Anglo what's two Minutemen we're here with Andy Jesse the CEO of Amazon Web Services the Andy crate to see you again great to see you thanks for having me on graduations we had a great chat a week ago you and I sat down for breakfast and you kind of laid out you kind of laid out with a plan for the show here but I you kind of left a lot out of this you hold it back I've know every three hours from I thought I had a great story you needed the floor our breakfast oh damn it's good what an announcement I mean your keno two and a half hours I mean the longest keynote I've seen just non-stop announces you went right into a no preamble right into the announcements how many announcements did you do like fifty plus or what was the number I think there were 22 news services and features announced in the keynote I did alright so you gotta look back now as it's coming down to an end to reap the parties tonight what's your take I mousey you're absorbing it still he's still kind of like numb pinch me moment what's what's the vibe what are you feeling right now you know it's been a fantastic week and this is our favorite week of the year just having the chance to spend the week with our entire community and I think that it's been a very successful week in terms of what we were trying to accomplish which was it's always first and foremost of learning and education conference and I think that people feel like the array of sessions they've been able to go to and what they've learned both about the services altogether the new services we announced and then just especially what other peers are doing on top of the platform I think has been really valuable and I've had a lot of customer meetings over the last few days and the conversations have been so excited you know people saying I just can't you know you guys already had so much functionality but I just can't believe the amount of innovation and capability the two guys just released over the last couple days and several people said to me you know how to I knew I was having a meeting with you so I had a list of things I was gonna ask you to to deliver and during your keynote I kept going check check check so they're a really positive excited conversation talk about the flywheel what's going on with you guys right now I use that term kind of a pun intended because you've got some flywheel going on as you add more services I detailed in my story after we met I teased out this is a competitive advantage for you you just listen to listening to customers but you're putting out more services there's leveraging those services so it's good for customers but I worry about the complexity and they might worry about the complexity how do you talk about that and how does your team address that because I mean tsunami of services yeah well you know I think that the first thing to remember is that simply because we have a lot of functionality doesn't mean that customers have to know about every single service and every single feature they use what they need when they need it and they don't have to pay for it up front and so you know one of the reasons we release so many things during the area of over 1300 services and features this year alone and in about 70 new releases just at reinvent this week is that when you have millions of active customers you have lots of diversity in those customers you know lots of different businesses lots of different priorities lots of different needs and so you know even in the set of customer meetings I've had this week the first question I asked every single customer i sat down with is what are your impressions what are you excited about they were some who said I can't believe I'm so excited about sage maker it's gonna completely change the accessibility of doing machine learning in my org and some said oh I really really wanted those language application services and machine learning others were totally focused on the multi master or aurora on the global tables for dynamodb and the graph database and then still others said you know I love ECS but I've wanted a kubernetes option and then now that I don't even have to manage containers at the server level and I can manage the task level is what I'm excited about still others who are IOT customers that's what cared about so we have so many customers it was such diversity in their businesses and their priorities that they all have a bunch of needs keep on delivering on that and I want to get your reaction something that we've been talking about in the cube all week which is well I've been pushing its due and I've been kind of debating it but we see a clear path towards a new renaissance in software development and invention and it comes down to some of the things that you guys have enabled we saw a lot of go get excited by some of the deep learning I'll see lecture for business and two other things it's easier to do stuff now the application layer because you don't have to build the full stack so we're you guys are talking about a reimagining architecture that was Vernors keynote it's all kind of pointing to a new Renaissance a new way to create value what's your reaction then how do you share that the customers because it's kind of a new new model yeah well I think that this has been happening now for you know the last ten years and I think that people aren't building applications for the most part the way they used to it you know if you if you're building new applications and you're trying to build all the hosting software and all the storage software and all the database software at all the messaging and queuing and analytics and and machine learning you're just wasting resource because because when you when you have the option of using 120 services from a platform like AWS that has thousands and thousands of people working on it delivering on average three-and-a-half new features a day that you could choose to use or not it's so much faster and so much more empowering to let your builders take advantage of that platform you get from idea to implementation and orders of magnitude faster using the cloud and that you know what keeps happening is we just keep adding more and more capabilities that allow people get now even the marketplace we just had Barry Russell on and you go now are bringing a global reach opportunity so not only can you help them get to market faster with coding and building value this growth so it's not just parking the marketplace and hope that something happens they're taking advantage of that growth I think it's a really important point it's it's not just a set of services that we're building but are thousands and thousands vis--vis and SAS providers who are also building products on top of AWS where their business is growing by leaps and bounds I mean one of the interesting things about the marketplace I don't know how much you guys have talked about this in the past or currently is that most if you talk to most software buyers they hate the process it you know it's just how long it takes the negotiation process most the software sellers also hate the process and so if you can find a mechanism which is what we're trying to provide with the AWS marketplace where buyers and sellers can complete those transactions and find each other so much faster it totally changes the world of buying software and consuming software Andy I came in this week pretty excited to look at the adoption of server lists and you know congratulations you've impressed a lot of announcements talked a lot of customers the thing that probably impressed me the most is it went from being kind of just lambda to really integrated all the service it's a much more holistic view but you made a comment that I that a lot of us in the community kind of you know poked at a little witches if you were to build AWS today in 2017 you would build it you know on you mean Amazon yes sorry Amazon on it today now I've talked to startups that are building all server list but you know it was on D gigantic company and you know I talked to Tim I talked to the team a lot of things I can't do so is this a goal or you know it just being kind of kind of the future or you know do you feel that I can put you know a global you know company of your size you know built with yeah yeah it's a good question and you know I really the comment I made was really about directionally what Amazon would do you know in the city in the very earliest days of AWS Jeff used to say a lot if I were starting Amazon today I'd have built it on top AWS we didn't have all the capability and all the functionality at that very moment but he knew what was coming and he saw what people were still able to accomplish even with where the services were at that point I think the same thing is true here with lambda which is I think if Amazon we're starting today it's a given they would build it on the cloud and I think we with a lot of the applications that comprise Amazon's consumer business we would build those on our server list capabilities now we still have plenty of capabilities and features and functionality we need to add to to lambda and our various serverless services so that may not be true from the get-go right now but I think if you look at the hundreds of thousands of customers who are building on top of lambda and lots of real applications you know FINRA is built a good chunk of their market watch application on top of lambda and Thompson Reuters has built you know that one of their key analytics apps like people are building real serious things on top of lambda and the pace of iteration you'll see there will increase as well and I really believe that to be true over the next year or two and you talked a little bit more about competition than then I'm used to hearing in the keynote I mean there's been some pokes at some of the database stuff in that migration but you know when it walked talked about there was this colorful bar chart you put up and you had some data pointing about that you know in your market chairs growing your continuing growth you know how do you look at the market landscape what are people you know still getting wrong yeah I think that I don't think that we actually talked that much more or less about competitors in the keynote there was a slide that had a color chart that may have been the only difference but you know for us it's always about you you could spend so much your time trying to look at what others are doing and wondering what they're gonna do the reality is if you don't stay focused on your customers and what they actually care about you know you're wasting your time about mobile and business years ago Alexa for business is a new thing voice we heard from Berner today it's a new interface so we were talking on the cube it's the first time we're kind of talking about this constant maybe we're the first ones to say it so we'll just say it voice first strategy mobile first created a massive wealth creation iPhone new kinds of application development voice has that same feel voice first interface could spawn massive innovation yeah what's your view their reaction what do you guys talk about internally at Amazon in terms of a how voice will take advantage of all your scale yeah well I strongly agree with what you heard Verner communicate in the in his keynote today which is just you know when we first had phones that had apps and you could do all kinds of things by tapping on the phone like that was revolutionary but then when you experienced a voice app it makes tapping on your phone so circa 2010 and so I think that the world will have a huge amount of voice applications it's gonna be people's preference and in part because it's just a more natural expression than actually tapping and trying to click and type things and so we we had so many customers almost a good chunk of our enterprise meetings that we have throughout the year one of the things customers want to talk about is how can I actually be involved in using Alexa how can I build skills for Alexa and then over the last few months that conversation has started to turn to hey you thinking about making Alexa more useful inside of businesses and for work and so there's so much applicability I think that voice first it's gonna have the same kind of impact or more than the mobile trend or I think it has a chance to have as big an impact I mean all the devices have to continue to evolve and you can see that at Amazon we're continuing to build all kinds of diverse devices but I think voice is gonna be a major mode of how people interact with handi 42,000 people I don't know how you top it congratulations on all your success and appreciate the growth and you've done with the company congratulate breaking chicken wing contest to Tonka yeah we said a Guinness I what is that about come on tell us about this door well I Tatanka is a buffalo wing eating club that we started in Seattle back in 1997 and we go for wings we used to go every Tuesday night for wings and we have membership standards you can become a regular member if you need 10 wings with five pasty wings a pasty wing is you know when the wing sauce sits the room temperature and it kind of congeals it gets Spacey so it's five wings wrapped in that pays platinum membership is 25 wings plus five pasties then we started having eating contests and we call it a tonka Bowl and so when we start a reinvent we very much wanted to have a conference that had a lot of interesting fun quirky events and one of the ideas we had was we said well let's try an eating contest and the first year we tried it we did it a lunchtime down in the basement and nobody wanted to have an eating contest at one o'clock in the afternoon in the middle of rain BAM so then we moved it to Lagasse Stadium here in the Venetian and people started coming so this year we had two groups of about a hundred each one at Lagasse won at the MGM and they they did a 30-minute round and then the top five wing eaters in each venue came back to one place for a second round and the winner apparently ate a cumulative total of 59 wings there were three thousand eight hundred and fifty-seven Wings consumed in the contest about as many features as Amazon has released since the first time event sounds like to continue the momentum and you're eating away at the competition congratulations Andy jazzy CEOs on Web Services the cube thanks for coming in man and I appreciate it guys thanks for being here appreciate it live coverage here from Las Vegas Amazon webster's reinvent annual conference 2017 s the cube I'm John Force to Minutemen be back with more live coverage after this short break [Music]