(gentle melody) >> Welcome back to theCUBE's live coverage of AWS Summit in San Francisco, California. Events are back. AWS Summit in New York City this summer, theCUBE will be there as well. Check us out there. I'm glad to have events back. It's great to have of everyone here. I'm John Furrier, host of theCUBE. Dr. Matt Wood is with me, CUBE alumni, now VP of Business Analytics Division of AWS. Matt, great to see you. >> Thank you, John. It's great to be here. I appreciate it. >> I always call you Dr. Matt Wood because Andy Jackson always says, "Dr. Matt, we would introduce you on the arena." (Matt laughs) >> Matt: The one and only. >> The one and only, Dr. Matt Wood. >> In joke, I love it. (laughs) >> Andy style. (Matt laughs) I think you had walk up music too. >> Yes, we all have our own personalized walk up music. >> So talk about your new role, not a new role, but you're running the analytics business for AWS. What does that consist of right now? >> Sure. So I work. I've got what I consider to be one of the best jobs in the world. I get to work with our customers and the teams at AWS to build the analytics services that millions of our customers use to slice dice, pivot, better understand their data, look at how they can use that data for reporting, looking backwards. And also look at how they can use that data looking forward, so predictive analytics and machine learning. So whether it is slicing and dicing in the lower level of Hadoop and the big data engines, or whether you're doing ETL with Glue, or whether you're visualizing the data in QuickSight or building your models in SageMaker. I got my fingers in a lot of pies. >> One of the benefits of having CUBE coverage with AWS since 2013 is watching the progression. You were on theCUBE that first year we were at Reinvent in 2013, and look at how machine learning just exploded onto the scene. You were involved in that from day one. It's still day one, as you guys say. What's the big thing now? Look at just what happened. Machine learning comes in and then a slew of services come in. You've got SageMaker, became a hot seller right out of the gate. The database stuff was kicking butt. So all this is now booming. That was a real generational change over for database. What's the perspective? What's your perspective on that's evolved? >> I think it's a really good point. I totally agree. I think for machine learning, there's sort of a Renaissance in machine learning and the application of machine learning. Machine learning as a technology has been around for 50 years, let's say. But to do machine learning right, you need like a lot of data. The data needs to be high quality. You need a lot of compute to be able to train those models and you have to be able to evaluate what those models mean as you apply them to real world problems. And so the cloud really removed a lot of the constraints. Finally, customers had all of the data that they needed. We gave them services to be able to label that data in a high quality way. There's all the compute you need to be able to train the models. And so where you go? And so the cloud really enabled this Renaissance with machine learning. And we're seeing honestly a similar Renaissance with data and analytics. If you look back five to ten years, analytics was something you did in batch, your data warehouse ran an analysis to do reconciliation at the end of the month, and that was it. (John laughs) And so that's when you needed it. But today, if your Redshift cluster isn't available, Uber drivers don't turn up, DoorDash deliveries don't get made. Analytics is now central to virtually every business, and it is central to virtually every business's digital transformation. And being able to take that data from a variety of sources, be able to query it with high performance, to be able to actually then start to augment that data with real information, which usually comes from technical experts and domain experts to form wisdom and information from raw data. That's kind of what most organizations are trying to do when they kind of go through this analytics journey. >> It's interesting. Dave Velanta and I always talk on theCUBE about the future. And you look back, the things we're talking about six years ago are actually happening now. And it's not hyped up statement to say digital transformation is actually happening now. And there's also times when we bang our fists on the table saying, say, "I really think this is so important." And David says, "John, you're going to die on that hill." (Matt laughs) And so I'm excited that this year, for the first time, I didn't die on that hill. I've been saying- >> Do all right. >> Data as code is the next infrastructure as code. And Dave's like, "What do you mean by that?" We're talking about how data gets... And it's happening. So we just had an event on our AWS startups.com site, a showcase for startups, and the theme was data as code. And interesting new trends emerging really clearly, the role of a data engineer, right? Like an SRE, what an SRE did for cloud, you have a new data engineering role because of the developer onboarding is massively increasing, exponentially, new developers. Data science scientists are growing, but the pipelining and managing and engineering as a system, almost like an operating system. >> Kind of as a discipline. >> So what's your reaction to that about this data engineer, data as code? Because if you have horizontally scalable data, you've got to be open, that's hard (laughs), okay? And you got to silo the data that needs to be siloed for compliance and reason. So that's a big policy around that. So what's your reaction to data's code and the data engineering phenomenon? >> It's a really good point. I think with any technology project inside of an organization, success with analytics or machine learning, it's kind of 50% technology and then 50% cultural. And you have often domain experts. Those could be physicians or drug design experts, or they could be financial experts or whoever they might be, got deep domain expertise, and then you've got technical implementation teams. And there's kind of a natural, often repulsive force. I don't mean that rudely, but they just don't talk the same language. And so the more complex a domain and the more complex the technology, the stronger their repulsive force. And it can become very difficult for domain experts to work closely with the technical experts to be able to actually get business decisions made. And so what data engineering does and data engineering is, in some cases a team, or it can be a role that you play. It's really allowing those two disciplines to speak the same language. You can think of it as plumbing, but I think of it as like a bridge. It's a bridge between the technical implementation and the domain experts, and that requires a very disparate range of skills. You've got to understand about statistics, you've got to understand about the implementation, you got to understand about the data, you got to understand about the domain. And if you can put all of that together, that data engineering discipline can be incredibly transformative for an organization because it builds the bridge between those two groups. >> I was advising some young computer science students at the sophomore, junior level just a couple of weeks ago, and I told them I would ask someone at Amazon this question. So I'll ask you, >> Matt: Okay. since you've been in the middle of it for years, they were asking me, and I was trying to mentor them on how do you become a data engineer, from a practical standpoint? Courseware, projects to work on, how to think, not just coding Python, because everyone's coding in Python, but what else can they do? So I was trying to help them. I didn't really know the answer myself. I was just trying to kind of help figure it out with them. So what is the answer, in your opinion, or the thoughts around advice to young students who want to be data engineers? Because data scientists is pretty clear on what that is. You use tools, you make visualizations, you manage data, you get answers and insights and then apply that to the business. That's an application. That's not the standing up a stack or managing the infrastructure. So what does that coding look like? What would your advice be to folks getting into a data engineering role? >> Yeah, I think if you believe this, what I said earlier about 50% technology, 50 % culture, the number one technology to learn as a data engineer is the tools in the cloud which allow you to aggregate data from virtually any source into something which is incrementally more valuable for the organization. That's really what data engineering is all about. It's about taking from multiple sources. Some people call them silos, but silos indicates that the storage is kind of fungible or undifferentiated. That's really not the case. Success requires you to have really purpose built, well crafted, high performance, low cost engines for all of your data. So understanding those tools and understanding how to use them, that's probably the most important technical piece. Python and programming and statistics go along with that, I think. And then the most important cultural part, I think is... It's just curiosity. You want to be able to, as a data engineer, you want to have a natural curiosity that drives you to seek the truth inside an organization, seek the truth of a particular problem, and to be able to engage because probably you're going to some choice as you go through your career about which domain you end up in. Maybe you're really passionate about healthcare, or you're really just passionate about transportation or media, whatever it might be. And you can allow that to drive a certain amount of curiosity. But within those roles, the domains are so broad you kind of got to allow your curiosity to develop and lead you to ask the right questions and engage in the right way with your teams, because you can have all the technical skills in the world. But if you're not able to help the team's truth seek through that curiosity, you simply won't be successful. >> We just had a guest, 20 year old founder, Johnny Dallas who was 16 when he worked at Amazon. Youngest engineer- >> Johnny Dallas is a great name, by the way. (both chuckle) >> It's his real name. It sounds like a football player. >> That's awesome. >> Rock star. Johnny CUBE, it's me. But he's young and he was saying... His advice was just do projects. >> Matt: And get hands on. Yeah. >> And I was saying, hey, I came from the old days where you get to stand stuff up and you hugged on for the assets because you didn't want to kill the project because you spent all this money. And he's like, yeah, with cloud you can shut it down. If you do a project that's not working and you get bad data no one's adopting it or you don't like it anymore, you shut it down, just something else. >> Yeah, totally. >> Instantly abandon it and move on to something new. That's a progression. >> Totally! The blast radius of decisions is just way reduced. We talk a lot about in the old world, trying to find the resources and get the funding is like, all right, I want to try out this kind of random idea that could be a big deal for the organization. I need $50 million and a new data center. You're not going to get anywhere. >> And you do a proposal, working backwards, documents all kinds of stuff. >> All that sort of stuff. >> Jump your hoops. >> So all of that is gone. But we sometimes forget that a big part of that is just the prototyping and the experimentation and the limited blast radius in terms of cost, and honestly, the most important thing is time, just being able to jump in there, fingers on keyboards, just try this stuff out. And that's why at AWS, we have... Part of the reason we have so many services, because we want, when you get into AWS, we want the whole toolbox to be available to every developer. And so as your ideas develop, you may want to jump from data that you have that's already in a database to doing realtime data. And then you have the tools there. And when you want to get into real time data, you don't just have kinesis, you have real time analytics, and you can run SQL against that data. The capabilities and the breadth really matter when it comes to prototyping. >> That's the culture piece, because what was once a dysfunctional behavior. I'm going to go off the reservation and try something behind my boss' back, now is a side hustle or fun project. So for fun, you can just code something. >> Yeah, totally. I remember my first Hadoop projects. I found almost literally a decommissioned set of servers in the data center that no one was using. They were super old. They're about to be literally turned off. And I managed to convince the team to leave them on for me for another month. And I installed Hadoop on them and got them going. That just seems crazy to me now that I had to go and convince anybody not to turn these servers off. But what it was like when you- >> That's when you came up with Elastic MapReduce because you said this is too hard, we got to make it easier. >> Basically yes. (John laughs) I was installing Hadoop version Beta 9.9 or whatever. It was like, this is really hard. >> We got to make it simpler. All right, good stuff. I love the walk down memory Lane. And also your advice. Great stuff. I think culture is huge. That's why I like Adam's keynote at Reinvent, Adam Selipsky talk about Pathfinders and trailblazers, because that's a blast radius impact when you can actually have innovation organically just come from anywhere. That's totally cool. >> Matt: Totally cool. >> All right, let's get into the product. Serverless has been hot. We hear a lot of EKS is hot. Containers are booming. Kubernetes is getting adopted, still a lot of work to do there. Cloud native developers are booming. Serverless, Lambda. How does that impact the analytics piece? Can you share the hot products around how that translates? >> Absolutely, yeah. >> Aurora, SageMaker. >> Yeah, I think it's... If you look at kind of the evolution and what customers are asking for, they don't just want low cost. They don't just want this broad set of services. They don't just want those services to have deep capabilities. They want those services to have as low an operating cost over time as possible. So we kind of really got it down. We got built a lot of muscle, a lot of services about getting up and running and experimenting and prototyping and turning things off and turning them on and turning them off. And that's all great. But actually, you really only in most projects start something once and then stop something once, and maybe there's an hour in between or maybe there's a year. But the real expense in terms of time and operations and complexity is sometimes in that running cost. And so we've heard very loudly and clearly from customers that running cost is just undifferentiated to them. And they want to spend more time on their work. And in analytics, that is slicing the data, pivoting the data, combining the data, labeling the data, training their models, running inference against their models, and less time doing the operational pieces. >> Is that why the service focuses there? >> Yeah, absolutely. It dramatically reduces the skill required to run these workloads of any scale. And it dramatically reduces the undifferentiated heavy lifting because you get to focus more of the time that you would have spent on the operations on the actual work that you want to get done. And so if you look at something just like Redshift Serverless, that we launched a Reinvent, we have a lot of customers that want to run the cluster, and they want to get into the weeds where there is benefit. We have a lot of customers that say there's no benefit for me, I just want to do the analytics. So you run the operational piece, you're the experts. We run 60 million instant startups every single day. We do this a lot. >> John: Exactly. We understand the operations- >> I just want the answers. Come on. >> So just give me the answers or just give me the notebook or just give me the inference prediction. Today, for example, we announced Serverless Inference. So now once you've trained your machine learning model, just run a few lines of code or you just click a few buttons and then you got an inference endpoint that you do not have to manage. And whether you're doing one query against that end point per hour or you're doing 10 million, we'll just scale it on the back end. I know we got not a lot of time left, but I want to get your reaction on this. One of the things about the data lakes not being data swamps has been, from what I've been reporting and hearing from customers, is that they want to retrain their machine learning algorithm. They need that data, they need the real time data, and they need the time series data. Even though the time has passed, they got to store in the data lake. So now the data lake's main function is being reusing the data to actually retrain. It works properly. So a lot of post mortems turn into actually business improvements to make the machine learnings smarter, faster. Do you see that same way? Do you see it the same way? >> Yeah, I think it's really interesting >> Or is that just... >> No, I think it's totally interesting because it's convenient to kind of think of analytics as a very clear progression from point A to point B. But really, you're navigating terrain for which you do not have a map, and you need a lot of help to navigate that terrain. And so having these services in place, not having to run the operations of those services, being able to have those services be secure and well governed. And we added PII detection today. It's something you can do automatically, to be able to use any unstructured data, run queries against that unstructured data. So today we added text queries. So you can just say, well, you can scan a badge, for example, and say, well, what's the name on this badge? And you don't have to identify where it is. We'll do all of that work for you. It's more like a branch than it is just a normal A to B path, a linear path. And that includes loops backwards. And sometimes you've got to get the results and use those to make improvements further upstream. And sometimes you've got to use those... And when you're downstream, it will be like, "Ah, I remember that." And you come back and bring it all together. >> Awesome. >> So it's a wonderful world for sure. >> Dr. Matt, we're here in theCUBE. Just take the last word and give the update while you're here what's the big news happening that you're announcing here at Summit in San Francisco, California, and update on the business analytics group. >> Yeah, we did a lot of announcements in the keynote. I encourage everyone to take a look at, that this morning with Swami. One of the ones I'm most excited about is the opportunity to be able to take dashboards, visualizations. We're all used to using these things. We see them in our business intelligence tools, all over the place. However, what we've heard from customers is like, yes, I want those analytics, I want that visualization, I want it to be up to date, but I don't actually want to have to go from my tools where I'm actually doing my work to another separate tool to be able to look at that information. And so today we announced 1-click public embedding for QuickSight dashboard. So today you can literally as easily as embedding a YouTube video, you can take a dashboard that you've built inside QuickSight, cut and paste the HTML, paste it into your application and that's it. That's what you have to do. It takes seconds. >> And it gets updated in real time. >> Updated in real time. It's interactive. You can do everything that you would normally do. You can brand it, there's no power by QuickSight button or anything like that. You can change the colors, fit in perfectly with your application. So that's an incredibly powerful way of being able to take an analytics capability that today sits inside its own little fiefdom and put it just everywhere. Very transformative. >> Awesome. And the business is going well. You got the Serverless detail win for you there. Good stuff. Dr. Matt Wood, thank you for coming on theCUBE. >> Anytime. Thank you. >> Okay, this is theCUBE's coverage of AWS Summit 2022 in San Francisco, California. I'm John Furrier, host of theCUBE. Stay with us for more coverage of day two after this short break. (gentle music)

(upbeat music) >> When Oracle acquired Sun in 2009, it paid $5.6 billion net of Sun's cash and debt. Now I argued at the time that Oracle got one of the best deals in the history of enterprise tech, and I got a lot of grief for saying that because Sun had a declining business, it was losing money, and its revenue was under serious pressure as it tried to hang on for dear life. But Safra Catz understood that Oracle could pay Sun's lower profit and lagging businesses, like its low index 86 product lines, and even if Sun's revenue was cut in half, because Oracle has such a high revenue multiple as a software company, it could almost instantly generate $25 to $30 billion in shareholder value on paper. In addition, it was a catalyst for Oracle to initiate its highly differentiated engineering systems business, and was actually the precursor to Oracle's Cloud. Oracle saw that it could capture high margin dollars that used to go to partners like HP, it's original exit data partner, and get paid for the full stack across infrastructure, middleware, database, and application software, when eventually got really serious about cloud. Now there was also a major technology angle to this story. Remember Sun's tagline, "the network is the computer"? Well, they should have just called it cloud. Through the Sun acquisition. Oracle also got a couple of key technologies, Java, the number one programming language in the world, and MySQL, a key ingredient of the LAMP stack, that's Linux, Apache, MySQL and PHP, Perl or Python, on which the internet is basically built, and is used by many cloud services like Facebook, Twitter, WordPress, Flicker, Amazon, Aurora, and many other examples, including, by the way, Maria DB, which is a fork of MySQL created by MySQL's creator, basically in protest to Oracle's acquisition; the drama is Oscar worthy. It gets even better. In 2020, Oracle began introducing a new version of MySQL called MySQL HeatWave, and since late 2020 it's been in sort of a super cycle rolling, out three new releases in less than a year and a half in an attempt to expand its Tam and compete in new markets. Now we covered the release of MySQL Autopilot, which uses machine learning to automate management functions. And we also covered the bench marketing that Oracle produced against Snowflake, AWS, Azure, and Google. And Oracle's at it again with HeatWave, adding machine learning into its database capabilities, along with previously available integrations of OLAP and OLTP. This, of course, is in line with Oracle's converged database philosophy, which, as we've reported, is different from other cloud database providers, most notably Amazon, which takes the right tool for the right job approach and chooses database specialization over a one size fits all strategy. Now we've asked Oracle to come on theCUBE and explain these moves, and I'm pleased to welcome back Nipun Agarwal, who's the senior vice president for MySQL Database and HeatWave at Oracle. And today, in this video exclusive, we'll discuss machine learning, other new capabilities around elasticity and compression, and then any benchmark data that Nipun wants to share. Nipun's been a leading advocate of the HeatWave program. He's led engineering in that team for over 10 years, and he has over 185 patents in database technologies. Welcome back to the show Nipun. Great to see you again. Thanks for coming on. >> Thank you, Dave. Very happy to be back. >> Yeah, now for those who may not have kept up with the news, maybe to kick things off you could give us an overview of what MySQL HeatWave actually is so that we're all on the same page. >> Sure, Dave, MySQL HeatWave is a fully managed MySQL database service from Oracle, and it has a builtin query accelerator called HeatWave, and that's the part which is unique. So with MySQL HeatWave, customers of MySQL get a single database which they can use for transactional processing, for analytics, and for mixed workloads because traditionally MySQL has been designed and optimized for transaction processing. So in the past, when customers had to run analytics with the MySQL based service, they would need to move the data out of MySQL into some other database for running analytics. So they would end up with two different databases and it would take some time to move the data out of MySQL into this other system. With MySQL HeatWave, we have solved this problem and customers now have a single MySQL database for all their applications, and they can get the good performance of analytics without any changes to their MySQL application. >> Now it's no secret that a lot of times, you know, queries are not, you know, most efficiently written, and critics of MySQL HeatWave will claim that this product is very memory and cluster intensive, it has a heavy footprint that adds to cost. How do you answer that, Nipun? >> Right, so for offering any database service in the cloud there are two dimensions, performance and cost, and we have been very cognizant of both of them. So it is indeed the case that HeatWave is a, in-memory query accelerator, which is why we get very good performance, but it is also the case that we have optimized HeatWave for commodity cloud services. So for instance, we use the least expensive compute. We use the least expensive storage. So what I would suggest is for the customers who kind of would like to know what is the price performance advantage of HeatWave compared to any database we have benchmark against, Redshift, Snowflake, Google BigQuery, Azure Synapse, HeatWave is significantly faster and significantly lower price on a multitude of workloads. So not only is it in-memory database and optimized for that, but we have also optimized it for commodity cloud services, which makes it much lower price than the competition. >> Well, at the end of the day, it's customers that sort of decide what the truth is. So to date, what's been the customer reaction? Are they moving from other clouds from on-prem environments? Both why, you know, what are you seeing? >> Right, so we are definitely a whole bunch of migrations of customers who are running MySQL on-premise to the cloud, to MySQL HeatWave. That's definitely happening. What is also very interesting is we are seeing that a very large percentage of customers, more than half the customers who are coming to MySQL HeatWave, are migrating from other clouds. We have a lot of migrations coming from AWS Aurora, migrations from RedShift, migrations from RDS MySQL, TerriData, SAP HANA, right. So we are seeing migrations from a whole bunch of other databases and other cloud services to MySQL HeatWave. And the main reason we are told why customers are migrating from other databases to MySQL HeatWave are lower cost, better performance, and no change to their application because many of these services, like AWS Aurora are ETL compatible with MySQL. So when customers try MySQL HeatWave, not only do they get better performance at a lower cost, but they find that they can migrate their application without any changes, and that's a big incentive for them. >> Great, thank you, Nipun. So can you give us some names? Are there some real world examples of these customers that have migrated to MySQL HeatWave that you can share? >> Oh, absolutely, I'll give you a few names. Stutor.com, this is an educational SaaS provider raised out of Brazil. They were using Google BigQuery, and when they migrated to MySQL HeatWave, they found a 300X, right, 300 times improvement in performance, and it lowered their cost by 85 (audio cut out). Another example is Neovera. They offer cybersecurity solutions and they were running their application on an on-premise version of MySQL when they migrated to MySQL HeatWave, their application improved in performance by 300 times and their cost reduced by 80%, right. So by going from on-premise to MySQL HeatWave, they reduced the cost by 80%, improved performance by 300 times. We are Glass, another customer based out of Brazil. They were running on AWS EC2, and when they migrated, within hours they found that there was a significant improvement, like, you know, over 5X improvement in database performance, and they were able to accommodate a very large virtual event, which had more than a million visitors. Another example, Genius Senority. They are a game designer in Japan, and when they moved to MySQL HeatWave, they found a 90 times percent improvement in performance. And there many, many more like a lot of migrations, again, from like, you know, Aurora, RedShift and many other databases as well. And consistently what we hear is (audio cut out) getting much better performance at a much lower cost without any change to their application. >> Great, thank you. You know, when I ask that question, a lot of times I get, "Well, I can't name the customer name," but I got to give Oracle credit, a lot of times you guys have at your fingertips. So you're not the only one, but it's somewhat rare in this industry. So, okay, so you got some good feedback from those customers that did migrate to MySQL HeatWave. What else did they tell you that they wanted? Did they, you know, kind of share a wishlist and some of the white space that you guys should be working on? What'd they tell you? >> Right, so as customers are moving more data into MySQL HeatWave, as they're consolidating more data into MySQL HeatWave, customers want to run other kinds of processing with this data. A very popular one is (audio cut out) So we have had multiple customers who told us that they wanted to run machine learning with data which is stored in MySQL HeatWave, and for that they have to extract the data out of MySQL (audio cut out). So that was the first feedback we got. Second thing is MySQL HeatWave is a highly scalable system. What that means is that as you add more nodes to a HeatWave cluster, the performance of the system improves almost linearly. But currently customers need to perform some manual steps to add most to a cluster or to reduce the cluster size. So that was other feedback we got that people wanted this thing to be automated. Third thing is that we have shown in the previous results, that HeatWave is significantly faster and significantly lower price compared to competitive services. So we got feedback from customers that can we trade off some performance to get even lower cost, and that's what we have looked at. And then finally, like we have some results on various data sizes with TPC-H. Customers wanted to see if we can offer some more data points as to how does HeatWave perform on other kinds of workloads. And that's what we've been working on for the several months. >> Okay, Nipun, we're going to get into some of that, but, so how did you go about addressing these requirements? >> Right, so the first thing is we are announcing support for in-database machine learning, meaning that customers who have their data inside MySQL HeatWave can now run training, inference, and prediction all inside the database without the data or the model ever having to leave the database. So that's how we address the first one. Second thing is we are offering support for real time elasticity, meaning that customers can scale up or scale down to any number of nodes. This requires no manual intervention on part of the user, and for the entire duration of the resize operation, the system is fully available. The third, in terms of the costs, we have double the amount of data that can be processed per node. So if you look at a HeatWave cluster, the size of the cluster determines the cost. So by doubling the amount of data that can be processed per node, we have effectively reduced the cluster size which is required for planning a given workload to have, which means it reduces the cost to the customer by half. And finally, we have also run the TPC-DS workload on HeatWave and compared it with other vendors. So now customers can have another data point in terms of the performance and the cost comparison of HeatWave with other services. >> All right, and I promise, I'm going to ask you about the benchmarks, but I want to come back and drill into these a bit. How is HeatWave ML different from competitive offerings? Take for instance, Redshift ML, for example. >> Sure, okay, so this is a good comparison. Let's start with, let's say RedShift ML, like there are some systems like, you know, Snowflake, which don't even offer any, like, processing of machine learning inside the database, and they expect customers to write a whole bunch of code, in say Python or Java, to do machine learning. RedShift ML does have integration with SQL. That's a good start. However, when customers of Redshift need to run machine learning, and they invoke Redshift ML, it makes a call to another service, SageMaker, right, where so the data needs to be exported to a different service. The model is generated, and the model is also outside RedShift. With HeatWave ML, the data resides always inside the MySQL database service. We are able to generate models. We are able to train the models, run inference, run explanations, all inside the MySQL HeatWave service. So the data, or the model, never have to leave the database, which means that both the data and the models can now be secured by the same access control mechanisms as the rest of the data. So that's the first part, that there is no need for any ETL. The second aspect is the automation. Training is a very important part of machine learning, right, and it impacts the quality of the predictions and such. So traditionally, customers would employ data scientists to influence the training process so that it's done right. And even in the case of Redshift ML, the users are expected to provide a lot of parameters to the training process. So the second thing which we have worked on with HeatWave ML is that it is fully automated. There is absolutely no user intervention required for training. Third is in terms of performance. So one of the things we are very, very sensitive to is performance because performance determines the eventual cost to the customer. So again, in some benchmarks, which we have published, and these are all available on GitHub, we are showing how HeatWave ML is 25 times faster than Redshift ML, and here's the kicker, at 1% of the cost. So four benefits, the data all remain secure inside the database service, it's fully automated, much faster, much lower cost than the competition. >> All right, thank you Nipun. Now, so there's a lot of talk these days about explainability and AI. You know, the system can very accurately tell you that it's a cat, you know, or for you Silicon Valley fans, it's a hot dog or not a hot dog, but they can't tell you how the system got there. So what is explainability, and why should people care about it? >> Right, so when we were talking to customers about what they would like from a machine learning based solution, one of the feedbacks we got is that enterprise is a little slow or averse to uptaking machine learning, because it seems to be, you know, like magic, right? And enterprises have the obligation to be able to explain, or to provide a answer to their customers as to why did the database make a certain choice. With a rule based solution it's simple, it's a rule based thing, and you know what the logic was. So the reason explanations are important is because customers want to know why did the system make a certain prediction? One of the important characteristics of HeatWave ML is that any model which is generated by HeatWave ML can be explained, and we can do both global explanations or model explanations as well as we can also do local explanations. So when the system makes a specific prediction using HeatWave ML, the user can find out why did the system make such a prediction? So for instance, if someone is being denied a loan, the user can figure out what were the attribute, what were the features which led to that decision? So this ensures, like, you know, fairness, and many of the times there is also like a need for regulatory compliance where users have a right to know. So we feel that explanations are very important for enterprise workload, and that's why every model which is generated by HeatWave ML can be explained. >> Now I got to give Snowflakes some props, you know, this whole idea of separating compute from storage, but also bringing the database to the cloud and driving elasticity. So that's been a key enabler and has solved a lot of problems, in particular the snake swallowing the basketball problem, as I often say. But what about elasticity and elasticity in real time? How is your version, and there's a lot of companies chasing this, how is your approach to an elastic cloud database service different from what others are promoting these days? >> Right, so a couple of characteristics. One is that we have now fully automated the process of elasticity, meaning that if a user wants to scale up or scale down, the only thing they need to specify is the eventual size of the cluster and the system completely takes care of it transparently. But then there are a few characteristics which are very unique. So for instance, we can scale up or scale down to any number of nodes. Whereas in the case of Snowflake, the number of nodes someone can scale up or scale down to are the powers of two. So if a user needs 70 CPUs, well, their choice is either 64 or 128. So by providing this flexibly with MySQL HeatWave, customers get a custom fit. So they can get a cluster which is optimized for their specific portal. So that's the first thing, flexibility of scaling up or down to any number of nodes. The second thing is that after the operation is completed, the system is fully balanced, meaning the data across the various nodes is fully balanced. That is not the case with many solutions. So for instance, in the case of Redshift, after the resize operation is done, the user is expected to manually balance the data, which can be very cumbersome. And the third aspect is that while the resize operation is going on, the HeatWave cluster is completely available for queries, for DMLS, for loading more data. That is, again, not the case with Redshift. Redshift, suppose the operation takes 10 to 15 minutes, during that window of time, the system is not available for writes, and for a big part of that chunk of time, the system is not even available for queries, which is very limiting. So the advantages we have are fully flexible, the system is in a balanced state, and the system is completely available for the entire duration operation. >> Yeah, I guess you got that hypergranularity, which, you know, sometimes they say, "Well, t-shirt sizes are good enough," but then I think of myself, some t-shirts fit me better than others, so. Okay, I saw on the announcement that you have this lower price point for customers. How did you actually achieve this? Could you give us some details around that please? >> Sure, so there are two things for announcing this service, which lower the cost for the customers. The first thing is that we have doubled the amount of data that can be processed by a HeatWave node. So if we have doubled the amount of data, which can be a process by a node, the cluster size which is required by customers reduces to half, and that's why the cost drops to half. The way we have managed to do this is by two things. One is support for Bloom filters, which reduces the amount of intermediate memory. And second is we compress the base data. So these are the two techniques we have used to process more data per node. The second way by which we are lowering the cost for the customers is by supporting pause and resume of HeatWave. And many times you find customers of like HeatWave and other services that they want to run some other queries or some other workloads for some duration of time, but then they don't need the cluster for a few hours. Now with the support for pause and resume, customers can pause the cluster and the HeatWave cluster instantaneously stops. And when they resume, not only do we fetch the data, in a very, like, you know, a quick pace from the object store, but we also preserve all the statistics, which are used by Autopilot. So both the data and the metadata are fetched, extremely fast from the object store. So with these two capabilities we feel that it'll drive down the cost to our customers even more. >> Got it, thank you. Okay, I promised I was going to get to the benchmarks. Let's have it. How do you compare with others but specifically cloud databases? I mean, and how do we know these benchmarks are real? My friends at EMC, they were back in the day, they were brilliant at doing benchmarks. They would produce these beautiful PowerPoints charts, but it was kind of opaque, but what do you say to that? >> Right, so there are multiple things I would say. The first thing is that this time we have published two benchmarks, one is for machine learning and other is for SQL analytics. All the benchmarks, including the scripts which we have used are available on GitHub. So we have full transparency, and we invite and encourage customers or other service providers to download the scripts, to download the benchmarks and see if they get any different results, right. So what we are seeing, we have published it for other people to try and validate. That's the first part. Now for machine learning, there hasn't been a precedence for enterprise benchmarks so we talk about aiding open data sets and we have published benchmarks for those, right? So both for classification, as well as for aggression, we have run the training times, and that's where we find that HeatWave MLS is 25 times faster than RedShift ML at one percent of the cost. So fully transparent, available. For SQL analytics, in the past we have shown comparisons with TPC-H. So we would show TPC-H across various databases, across various data sizes. This time we decided to use TPC-DS. the advantage of TPC-DS over TPC-H is that it has more number of queries, the queries are more complex, the schema is more complex, and there is a lot more data skew. So it represents a different class of workloads, and which is very interesting. So these are queries derived from the TPC-DS benchmark. So the numbers we have are published this time are for 10 terabyte TPC-DS, and we are comparing with all the four majors services, Redshift, Snowflake, Google BigQuery, Azure Synapse. And in all the cases, HeatWave is significantly faster and significantly lower priced. Now one of the things I want to point out is that when we are doing the cost comparison with other vendors, we are being overly fair. For instance, the cost of HeatWave includes the cost of both the MySQL node as well as the HeatWave node, and with this setup, customers can run transaction processing analytics as well as machine learning. So the price captures all of it. Whereas with the other vendors, the comparison is only for the analytic queries, right? So if customers wanted to run RDP, you would need to add the cost of that database. Or if customers wanted to run machine learning, you would need to add the cost of that service. Furthermore, with the case of HeatWave, we are quoting pay as you go price, whereas for other vendors like, you know, RedShift, and like, you know, where applicable, we are quoting one year, fully paid upfront cost rate. So it's like, you know, very fair comparison. So in terms of the numbers though, price performance for TPC-DS, we are about 4.8 times better price performance compared to RedShift We are 14.4 times better price performance compared to Snowflake, 13 times better than Google BigQuery, and 15 times better than Synapse. So across the board, we are significantly faster and significantly lower price. And as I said, all of these scripts are available in GitHub for people to drive for themselves. >> Okay, all right, I get it. So I think what you're saying is, you could have said this is what it's going to cost for you to do both analytics and transaction processing on a competitive platform versus what it takes to do that on Oracle MySQL HeatWave, but you're not doing that. You're saying, let's take them head on in their sweet spot of analytics, or OLTP separately and you're saying you still beat them. Okay, so you got this one database service in your cloud that supports transactions and analytics and machine learning. How much do you estimate your saving companies with this integrated approach versus the alternative of kind of what I called upfront, the right tool for the right job, and admittedly having to ETL tools. How can you quantify that? >> Right, so, okay. The numbers I call it, right, at the end of the day in a cloud service price performance is the metric which gives a sense as to how much the customers are going to save. So for instance, for like a TPC-DS workload, if we are 14 times better price performance than Snowflake, it means that our cost is going to be 1/14th for what customers would pay for Snowflake. Now, in addition, in other costs, in terms of migrating the data, having to manage two different databases, having to pay for other service for like, you know, machine learning, that's all extra and that depends upon what tools customers are using or what other services they're using for transaction processing or for machine learning. But these numbers themselves, right, like they're very, very compelling. If we are 1/5th the cost of Redshift, right, or 1/14th of Snowflake, these numbers, like, themselves are very, very compelling. And that's the reason we are seeing so many of these migrations from these databases to MySQL HeatWave. >> Okay, great, thank you. Our last question, in the Q3 earnings call for fiscal 22, Larry Ellison said that "MySQL HeatWave is coming soon on AWS," and that caught a lot of people's attention. That's not like Oracle. I mean, people might say maybe that's an indication that you're not having success moving customers to OCI. So you got to go to other clouds, which by the way I applaud, but any comments on that? >> Yep, this is very much like Oracle. So if you look at one of the big reasons for success of the Oracle database and why Oracle database is the most popular database is because Oracle database runs on all the platforms, and that has been the case from day one. So very akin to that, the idea is that there's a lot of value in MySQL HeatWave, and we want to make sure that we can offer same value to the customers of MySQL running on any cloud, whether it's OCI, whether it's the AWS, or any other cloud. So this shows how confident we are in our offering, and we believe that in other clouds as well, customers will find significant advantage by having a single database, which is much faster and much lower price then what alternatives they currently have. So this shows how confident we are about our products and services. >> Well, that's great, I mean, obviously for you, you're in MySQL group. You love that, right? The more places you can run, the better it is for you, of course, and your customers. Okay, Nipun, we got to leave it there. As always it's great to have you on theCUBE, really appreciate your time. Thanks for coming on and sharing the new innovations. Congratulations on all the progress you're making here. You're doing a great job. >> Thank you, Dave, and thank you for the opportunity. >> All right, and thank you for watching this CUBE conversation with Dave Vellante for theCUBE, your leader in enterprise tech coverage. We'll see you next time. (upbeat music)

(upbeat music) >> Welcome to this Cube Conversation about women in tech and women in cybersecurity, two things I'm very passionate about. Lisa Martin here, with two guests, Debbie Briggs joins us, the Area Vice President, and Chief Security Officer at NETSCOUT, and Tyler Cohen Wood is here as well, the Founder and CEO of MyConnectedHealth. Ladies, it's an honor to have you on the program. I'm excited to talk to you. >> Thank you so much for having us. >> Completely agree. Tyler and I talked a couple of minutes last week and she has a lot to offer to this. >> I know, I was looking at both of your backgrounds. Very impressive. Tyler, starting with you. I see that you are a nationally recognized Cybersecurity Intelligence, National Security Expert, and former Director of Cyber Risk Management for AT&T. And I also saw that you just won a Top 50 Women in Tech Influencers to Follow for 2021 Award. Congratulations, that's amazing. I would love to know way back in the day, how did you even first become interested in tech? >> Well, it was kind of inevitable that I would go into something like tech because as a kid, I was kind of nerdy. I was obsessed with "Star Trek". I would catalog my "Star Trek" tapes by Stardate. I was just really into it. But when I was in college, I mean, it was the late 90's. Cybersecurity just really wasn't a thing. So I went into music and I worked for a radio station. I loved it, but the format of the radio station changed and I wanted to do something different. And I thought, well, computers. I'll move to San Francisco, and I'm sure I can get a job, 'cause they were hiring anyone with a brain, 'cause it was really the dot com boom. And that's really how I got into it. It was just kind of one of those things. (laughs) >> Did you have, was it like network connection, going from music to tech is quite a jump? >> It's a huge jump. It was, but you know, I was young. I was still fresh out of school. I was really interested in learning and I really wanted to get involved in cyber in some capacity, because I became really fascinated with it. So it was just kind of one of those things, that just sort of happened. >> What an interesting talk about a zig-zaggy path. That's a very, very interesting one. And I have to talk about music with you later. That would be interesting. And Debbie, you also have, as Tyler does, 20 years plus experience in cybersecurity. You've been with NETSCOUT since '04. Were you always interested in tech? Did you study engineering or computer science in school, Debbie? >> Yeah, so I think my interest in tech, just like Tyler started at a very young age. I was always interested in how things worked and how people worked. And some day over a drink, I will tell you some funny stories about things I took apart in my parents house, to figure out how it worked. (Lisa and Tyler laughing) They still don't know it. So I guess I- >> I love that. >> I just love that putting it back together, but I took a more traditional route than Tyler did. I do have a degree in Computer Science, went to school a little bit earlier than Tyler. What I would say is, when I was in college, the Computer Science Center was in the basement of the library and we had these really tiny windows and they sort of hit you in the dark. And I think it was my senior year and I went, "I don't want to sit in a room by myself and write code all day and talk to no one." So, you know, I'm a senior and I'm like, "Okay, I got to, this is not, I did not want to write code all day." And so I happened to fall into a great company and moved onto PCs. And from there went to messaging, to networking and into that, I fell into cybersecurity. So I took that more traditional route and I think I've done every job in IT, except for programming, which is what I really got my degree in. >> But you realized early on, you know, "I don't quite think this is for me." And that's an important thing for anybody in any career, to really listen to your gut. It's telling you something. I love how you both got into cybersecurity, which is now, especially in the last 18 months, with what we've seen with the threat landscape, such an incredible opportunity for anyone. But I'd like to know there's not a lot of women in tech, as we know we've been talking about this for a long time now. We've got maybe a quarter of women at the technology roles are filled by women. Tyler, talk to me about some of the challenges that you faced along your journey to get where you are today. >> Well, I mean, you know, like I said, when I started, it was like 1999, 2000. And there were even less women in cybersecurity and in these tech roles than there are now. And you know, it was difficult because, you know, I remember at my first job, I was so interested in learning about Unix and I would learn everything, I read everything about it. And I ended up getting promoted over all of my male colleagues. And you know, it was really awkward because there was the assumption, they would just say things like, "Oh, well you got that because you're a woman." And that was not the case, but it's that type of stereotyping, you know, that we've had to deal with in this industry. Now I do believe that is changing. And I've seen a lot of evidence of that. We're getting there, but we're not there yet. >> And I agree. I agree completely with what Tyler said. You know, when I started, you were the only woman in the room, you got promoted over your male counterparts. You know, I would say even 10 years ago, you know, someone was like, "Well, you could go for any CISCO role and you'd get the job because you're a woman." And I've had to go and say, "No, I might get an interview because I'm a woman, but you don't get the job just because, you know, you check a box." You know, some of that is still out there, but Tyler you're right, things are changing. I think, you know, three things that we all need to focus in on to continue to move us forward and get more women into tech is the first thing is we have to start younger. I think by high school, a lot of girls and young women have been turned off by technology. So maybe, we need to start in the middle school and ensuring that we've got young girls interested. The second thing is, is we have to have mentors. And I always say, if you're in the security industry, you have to turn around and help the next person out. And if that person is a woman, that's great, but we have to mentor others. And it can be young girls, it could be young gentlemen, but we need to mentor that next group up. And you know, if you're in the position to offer internships during the summer, we don't have to stay to the traditional role and go, "Oh, let me hire just intern from the you know IT, they're getting degrees in IT." You can get creative. And my best worker right now was an intern that worked for me, was an intern for me six years ago. And she has a degree in Finance, so nontraditional route into cyber security. And the third thing I think we need to do is, is there things the industry could do to change things and make things, I don't want to say even 'cause they're not uneven, but for example, I forget what survey it was, but if a woman reads a job description and I can do half of it, I'm not going to apply because I don't feel I'll qualify, where men, on the other hand, if they can do three out of ten they'll apply. So do we need to look at the way we write job descriptions, and use different words, you know, rather than must have these skills. You know, sort of leave it a little bit open, like here are the skills we'd like you to have, or have, you know, a handful of the following. So soften some of those job descriptions. And the second thing is once we get women in, we have to be a little bit more, I'll say inclusive. So, if you're a high tech company, look at, you know, your sales organization. When you go to big shows, do you pay more attention to men on the floor than women on the floor? If you have a sales event where you get different customers together, is it a golf outing or is it something that's maybe a little bit more inclusive than just male? So those are the three things I think as an industry we have to focus in on, start younger, get them, you know, work on mentorships specifically in cyber, and the third thing is, look at some of the things that we're doing, as companies both in our HR and sales practices. >> That's a great, that last piece of advice, Debbie is fantastic. That's one that I hadn't thought about, but you're right. If a job description is written, for must have all of these things and a woman that goes, "I only got three out of the ten. I'm not going to even get past, you know, the recruiter here." How can we write things differently? I also loved your idea of bringing in people with diverse backgrounds. I've been in marketing for 16 years and I've met very few people that actually have marketing degrees, a lot of people. So you get that diversity of thought. Tyler, what are some of your thoughts about how we can help expand the role of women in technology? Do you agree with some of the things that Debbie said? >> I love what Debbie said. I agree 100%. And I started laughing because I was thinking about all the golf outings that I've been on and I don't play golf. (all laughing) I think that there is an untapped resource because there's a lot of women who are now interested in changing their careers and that's a big pool of people. And I think that making it more accessible and making it so that people understand what the different cyber security or cyber jobs are, because a lot of people just assume that it's coding, or it's, you know, working on AI, but that's not necessarily true. I mean, there's so many different avenues. There's marketing, there's forensics, there's incident response. I mean, I could go on and on and on. And oftentimes if people don't know that these types of jobs exist, they're not even going to look for them. So making that more well-known, what the different types of opportunities are to people, I think that that would help kind of open more doors. >> And that goes along beautifully with what Debbie was talking about with respect to mentorship. And I would even add sponsorship in there, but becoming a sponsor of a younger female, who's maybe considering tech or is already in tech to help her navigate the career. Look for the other opportunities. Tyler, as you mentioned, there's a lot to cybersecurity, that is beyond coding and AI for example. So maybe getting the awareness out there more. Did either of you have sponsors when you were early in your career? Are you a sponsor now? Debbie, let's start with you. >> So, I'll answer your first question. I guess I was really fortunate that my first job out of college, I had an internship and I happened to have a female boss. And so, although we may not have called it sponsorship or mentor, she taught me and showed me that, you know, women can be leaders. And she always believed in us and always pushed us to do things beyond what we may have thought we were capable of. Throughout the years, someone once told me that we should all have our own personal board of directors. You know, a group of people that when we're making a decision, that may be life-changing or we're unsure, rather than just having one mentor, having a group of people that you, that you know, they don't have to be in cybersecurity. Yeah, I want someone that's on my board of directors that maybe, is a specialist in cybersecurity, but having other executives in other companies, that can also give you that perspective. You know, so I've always had a personal board of directors. I think I've had three or four different mentors. Some of them, I went out and found. Some of them I have joined organizations that have been fortunate enough to become not only a mentor, but a mentee. And I've kept those relationships up over three or four years. And all those people are now on my personal board of directors, that, you know, if I have a life-changing question, I've got a group of people that I can go back on. >> That is brilliant advice. I love that having a... Isn't that great Tyler? Having a personal- >> Yes Yes! >> Board of directors, especially as we look at cybersecurity and the cybersecurity skills gap Tyler has been, I think it's in its 5th year now, which is there's so much opportunity. What we saw in the threat landscape in the last 18, 19 months during the pandemic was this explosion and the attack surface, ransomware becoming a word that even my mom knows these days. What do you advise Tyler for, you talked about really making people much more aware of all of the opportunities within cyber, but when you think about how you would get women interested in cybersecurity specifically, what are some of the key pieces of advice you would offer? >> Well, again, I think I love the board of directors. I love that. That is brilliant, but I really think that it is about finding mentors, and it is about doing the research, and really asking questions. Because if you reach out to someone on LinkedIn, you know, they may just not respond, but chances are some someone will and, you know, most people in this community are very willing to help. And, you know, I found that to be great. I mean, I've got my board of directors too. I realize that now. (Debbie laughs) But I also like to help other people as well, that are just kind of entering into the field or if they're changing their careers. And it's not necessarily just women, it's people that are interested in getting into an aspect of this industry. And this is a industry where, you know, you can jump from this, to this, to this, to this. I mean, I think that I've had six different major career shifts still within the cybersecurity realm. So, just because you start off doing one thing doesn't mean that that's what you're going to do forever. There're so many different areas. And it's really interesting. I think about my 11 year old niece and she may very well have a job someday, that doesn't even exist right now. That's how quickly cyber and everything connected is moving. And if you think about it, we are connected, there is a cyber component to every single thing that we do, and that's going to continue to expand and continue to grow. And we need more people to be interested, and to want to get into these careers. And I think also it's important for younger girls to let them know these careers are really fun and they're extremely rewarding. And I mean, I hate to use this as an incentive, but there's also a lot of money that can be made too, and that's an incentive to get, you know, women and girls into these careers as well. >> And Tyler, I think you're right. In addition to that, you're always going to have a job. And I think cyber is a great career for someone that are lifelong learners, because like you said, your 11 year old niece, the job, when she graduates from college, she may have, probably doesn't even exist today. And so I think you have to be a lifelong learner. I think one of the things that people may not be aware of is, you know, for women who may have gone the non-traditional route and got degrees later in life, or took time off to raise children and want to come back to work, cyber security is something that, you know, doesn't have to be a nine to five job. I have, it happens to be a gentlemen on my team, who has to get kids on the bus and off the bus. And so we figured out how, you know, he gets up and he works for a couple hours, puts kids on the bus, is in the office. And then he gets the kids off. And once they've had dinner and gone to bed, he puts in a couple more hours. And I think, you know, people need to be aware of, there is some flexibility, there is flexibility in cyber jobs. I mean, it's not a nine to five job, it's not like banking. Well, if you were teller, and your hours are when the bank is open, cyber is 7/24 and jobs can be flexible. And I think people need to be aware of that. >> I agree on the flexibility front, and people also need to be flexible themselves. I do want to ask you both, we're getting low on time, but I've got to ask you, how do you get the confidence, to be, like you said, back in the day, in the room, maybe the only female and I've been in that as well, even in marketing, product marketing years ago. How do you get the confidence to continue moving forward? Even as someone says, "You're only here because you're a female." Tyler, what's your advice to help young women and young men as well fight any sort of challenges that are coming their way? >> I had a mentor when I first moved to the Defense Intelligence Agency, I had an Office Chief and she said to me, "Tyler, you're a Senior Intelligence Officer, you always take a seat at the table. Do not let anyone tell you that you cannot have a seat at the table." And you know, that was good advice. And I think confidence is great. But courage is something that's much more important, because courage is what leads up to confidence. And you really have to believe in yourself and do things that you know are right for you, not because you think it's going to make other people happy. And I think, you know, as women, it's really finding that courage to be brave and to be strong and to be willing to stand out, you know, alone on something, because it's what you care about and what you believe in. And that's really what helps kind of motivate me. >> I love that courage. Debbie, what are your thoughts? >> (laughs) So I was going to say, this is going to be really hard to believe, but when I was 16 years old, I was so shy that if I went to a restaurant and someone served me stone cold food, I wouldn't say a word. I would just eat it. If I bought something in a store and I didn't like it, I'd refuse, I just couldn't bring myself to go to that customer service desk and return it. And my first job in high school, was it a fast food place. And I worked for a gentleman who was a little bit of a tyrant, but you know, I learned how to get a backbone very quickly. And I would have to say now looking back, he was probably my first mentor without even trying to do that. He mentored me on how to believe in myself and how to stand up for what's right. So, Tyler, I completely agree with you. And you know, that's something that people think when they get a mentorship, sometimes it's someone going to mentor them on, you know, something tactical, something they want to know how to do, but sometimes what you need to be mentored in, could be, "How do I believe in myself?" Or "How do I find the courage to be that the only female in the room?" And I think that is where some of that mentorship comes from and, you know, I think, you know, if we go back to mentoring at the middle school, there's lots of opportunities, career fairs, the first robotically, get the middle school level, gives all of us an opportunity to sort of mentor girls at that level. And for all the guys out there who have daughters, this is, you know, how to... It's not like you can get a parenting checklist, "Teach my kid courage." And Tyler, I love that word, but I think that's something that we all need to aspire to bring out in others. >> I love that. I love that. >> Okay with that, I think I love both of your stories, are zig-zaggy in certain ways, one in a more direct cybersecurity path, Debbie with yours. Tyler, yours, very different coming from the music industry. But you both have such great advice. It's really, I would say, I'm going to add that, open your mind to be open to, you can do anything. As Tyler said, there's a very great possibility that right now the job that your niece who's 11 is going to get in the next 10 years, doesn't exist yet. How exciting is that? To have the opportunity to be open-minded enough and flexible enough to say, "I'm going to try that." And I'm going to learn from my mentors, whether it's a fast food cook, which I wouldn't think would be a direct mentor, and recognizing years later, "Wow, what an impact that person had on me, having the courage to do what I have." And so I would ask you like each one more question in terms of just your inspiration for what you're currently doing. Debbie, as the leader of security for NETSCOUT, what inspires you to continue in your current role and seek more? >> So, I'm a lifelong learner. So, I love to learn cybersecurity. You know, every day is a different day. So, it's definitely the ability to continue to learn and to do new things. But the second thing is, is I think I've always been, I don't want to call it a fixer-upper because cybersecurity isn't a fixer-upper, I'm just always wanted to improve upon things. If I've seen something that I think can do better, or a product that could have something new or better in it, you know, that's what excites me is to give people that feedback and to improve on what we've had out there. You know, you had mentioned, we've got this block of jobs that we can't fill. We have to give feedback and how we get the tools and what we have today smarter, so that if there are less of us, we're working smarter and not harder. And so if there is some low-level tasks that we could put back into tools, and talk to vendors and have them do this for us, that's how I think we start to get our way sort of out of the hole. Tyler, any thoughts on that? >> I again, I love that answer. I mean, I think for me, you know, I do like, it's that problem solving thing too. But for me it's also about, it's about compassion. And when I see, you know, a story of some child that's been involved in some kind of cyber bullying attack, or a company that has been broken into, I want to do whatever I can to help people, and to teach people to really protect themselves, so that they feel empowered and they're not afraid of cyber security. So for me, it's also really that drive to really make a difference and really help people. >> And you've both done, I'm sure, so much of that made such a big difference in many communities in which you're involved. I thank you so much for sharing your journeys with me on the program today, and giving such great pointed advice to young men and women, and even some of the older men and women out there that might be kind of struggling about, where do I go next? Your advice is brilliant, ladies. Thank you so much. It's been a pleasure talking with you. >> Thank you. >> Thank you. >> For Debbie Briggs and Tyler Cohen Wood, I'm Lisa Martin. You've been watching this Cube Conversation. (upbeat music)

(upbeat music) >> Welcome to this Cube Conversation about women in tech and women in cybersecurity, two things I'm very passionate about. Lisa Martin here, with two guests, Debbie Briggs joins us, the Area Vice President, and Chief Security Officer at NETSCOUT, and Tyler Cohen Wood is here as well, the Founder and CEO of MyConnectedHealth. Ladies, it's an honor to have you on the program. I'm excited to talk to you. >> Thank you so much for having us. >> Completely agree. Tyler and I talked a couple of minutes last week and she has a lot to offer to this. >> I know, I was looking at both of your backgrounds. Very impressive. Tyler, starting with you. I see that you are a nationally recognized Cybersecurity Intelligence, National Security Expert, and former Director of Cyber Risk Management for AT&T. And I also saw that you just won a Top 50 Women in Tech Influencers to Follow for 2021 Award. Congratulations, that's amazing. I would love to know way back in the day, how did you even first become interested in tech? >> Well, it was kind of inevitable that I would go into something like tech because as a kid, I was kind of nerdy. I was obsessed with "Star Trek". I would catalog my "Star Trek" tapes by Stardate. I was just really into it. But when I was in college, I mean, it was the late 90's. Cybersecurity just really wasn't a thing. So I went into music and I worked for a radio station. I loved it, but the format of the radio station changed and I wanted to do something different. And I thought, well, computers. I'll move to San Francisco, and I'm sure I can get a job, 'cause they were hiring anyone with a brain, 'cause it was really the dot com boom. And that's really how I got into it. It was just kind of one of those things. (laughs) >> Did you have, was it like network connection, going from music to tech is quite a jump? >> It's a huge jump. It was, but you know, I was young. I was still fresh out of school. I was really interested in learning and I really wanted to get involved in cyber in some capacity, because I became really fascinated with it. So it was just kind of one of those things, that just sort of happened. >> What an interesting talk about a zig-zaggy path. That's a very, very interesting one. And I have to talk about music with you later. That would be interesting. And Debbie, you also have, as Tyler does, 20 years plus experience in cybersecurity. You've been with NETSCOUT since '04. Were you always interested in tech? Did you study engineering or computer science in school, Debbie? >> Yeah, so I think my interest in tech, just like Tyler started at a very young age. I was always interested in how things worked and how people worked. And some day over a drink, I will tell you some funny stories about things I took apart in my parents house, to figure out how it worked. (Lisa and Tyler laughing) They still don't know it. So I guess I- >> I love that. >> I just love that putting it back together, but I took a more traditional route than Tyler did. I do have a degree in Computer Science, went to school a little bit earlier than Tyler. What I would say is, when I was in college, the Computer Science Center was in the basement of the library and we had these really tiny windows and they sort of hit you in the dark. And I think it was my senior year and I went, "I don't want to sit in a room by myself and write code all day and talk to no one." So, you know, I'm a senior and I'm like, "Okay, I got to, this is not, I did not want to write code all day." And so I happened to fall into a great company and moved onto PCs. And from there went to messaging, to networking and into that, I fell into cybersecurity. So I took that more traditional route and I think I've done every job in IT, except for programming, which is what I really got my degree in. >> But you realized early on, you know, "I don't quite think this is for me." And that's an important thing for anybody in any career, to really listen to your gut. It's telling you something. I love how you both got into cybersecurity, which is now, especially in the last 18 months, with what we've seen with the threat landscape, such an incredible opportunity for anyone. But I'd like to know there's not a lot of women in tech, as we know we've been talking about this for a long time now. We've got maybe a quarter of women at the technology roles are filled by women. Tyler, talk to me about some of the challenges that you faced along your journey to get where you are today. >> Well, I mean, you know, like I said, when I started, it was like 1999, 2000. And there were even less women in cybersecurity and in these tech roles than there are now. And you know, it was difficult because, you know, I remember at my first job, I was so interested in learning about Unix and I would learn everything, I read everything about it. And I ended up getting promoted over all of my male colleagues. And you know, it was really awkward because there was the assumption, they would just say things like, "Oh, well you got that because you're a woman." And that was not the case, but it's that type of stereotyping, you know, that we've had to deal with in this industry. Now I do believe that is changing. And I've seen a lot of evidence of that. We're getting there, but we're not there yet. >> And I agree. I agree completely with what Tyler said. You know, when I started, you were the only woman in the room, you got promoted over your male counterparts. You know, I would say even 10 years ago, you know, someone was like, "Well, you could go for any CISCO role and you'd get the job because you're a woman." And I've had to go and say, "No, I might get an interview because I'm a woman, but you don't get the job just because, you know, you check a box." You know, some of that is still out there, but Tyler you're right, things are changing. I think, you know, three things that we all need to focus in on to continue to move us forward and get more women into tech is the first thing is we have to start younger. I think by high school, a lot of girls and young women have been turned off by technology. So maybe, we need to start in the middle school and ensuring that we've got young girls interested. The second thing is, is we have to have mentors. And I always say, if you're in the security industry, you have to turn around and help the next person out. And if that person is a woman, that's great, but we have to mentor others. And it can be young girls, it could be young gentlemen, but we need to mentor that next group up. And you know, if you're in the position to offer internships during the summer, we don't have to stay to the traditional role and go, "Oh, let me hire just intern from the you know IT, they're getting degrees in IT." You can get creative. And my best worker right now was an intern that worked for me, was an intern for me six years ago. And she has a degree in Finance, so nontraditional route into cyber security. And the third thing I think we need to do is, is there things the industry could do to change things and make things, I don't want to say even 'cause they're not uneven, but for example, I forget what survey it was, but if a woman reads a job description and I can do half of it, I'm not going to apply because I don't feel I'll qualify, where men, on the other hand, if they can do three out of ten they'll apply. So do we need to look at the way we write job descriptions, and use different words, you know, rather than must have these skills. You know, sort of leave it a little bit open, like here are the skills we'd like you to have, or have, you know, a handful of the following. So soften some of those job descriptions. And the second thing is once we get women in, we have to be a little bit more, I'll say inclusive. So, if you're a high tech company, look at, you know, your sales organization. When you go to big shows, do you pay more attention to men on the floor than women on the floor? If you have a sales event where you get different customers together, is it a golf outing or is it something that's maybe a little bit more inclusive than just male? So those are the three things I think as an industry we have to focus in on, start younger, get them, you know, work on mentorships specifically in cyber, and the third thing is, look at some of the things that we're doing, as companies both in our HR and sales practices. >> That's a great, that last piece of advice, Debbie is fantastic. That's one that I hadn't thought about, but you're right. If a job description is written, for must have all of these things and a woman that goes, "I only got three out of the ten. I'm not going to even get past, you know, the recruiter here." How can we write things differently? I also loved your idea of bringing in people with diverse backgrounds. I've been in marketing for 16 years and I've met very few people that actually have marketing degrees, a lot of people. So you get that diversity of thought. Tyler, what are some of your thoughts about how we can help expand the role of women in technology? Do you agree with some of the things that Debbie said? >> I love what Debbie said. I agree 100%. And I started laughing because I was thinking about all the golf outings that I've been on and I don't play golf. (all laughing) I think that there is an untapped resource because there's a lot of women who are now interested in changing their careers and that's a big pool of people. And I think that making it more accessible and making it so that people understand what the different cyber security or cyber jobs are, because a lot of people just assume that it's coding, or it's, you know, working on AI, but that's not necessarily true. I mean, there's so many different avenues. There's marketing, there's forensics, there's incident response. I mean, I could go on and on and on. And oftentimes if people don't know that these types of jobs exist, they're not even going to look for them. So making that more well-known, what the different types of opportunities are to people, I think that that would help kind of open more doors. >> And that goes along beautifully with what Debbie was talking about with respect to mentorship. And I would even add sponsorship in there, but becoming a sponsor of a younger female, who's maybe considering tech or is already in tech to help her navigate the career. Look for the other opportunities. Tyler, as you mentioned, there's a lot to cybersecurity, that is beyond coding and AI for example. So maybe getting the awareness out there more. Did either of you have sponsors when you were early in your career? Are you a sponsor now? Debbie, let's start with you. >> So, I'll answer your first question. I guess I was really fortunate that my first job out of college, I had an internship and I happened to have a female boss. And so, although we may not have called it sponsorship or mentor, she taught me and showed me that, you know, women can be leaders. And she always believed in us and always pushed us to do things beyond what we may have thought we were capable of. Throughout the years, someone once told me that we should all have our own personal board of directors. You know, a group of people that when we're making a decision, that may be life-changing or we're unsure, rather than just having one mentor, having a group of people that you, that you know, they don't have to be in cybersecurity. Yeah, I want someone that's on my board of directors that maybe, is a specialist in cybersecurity, but having other executives in other companies, that can also give you that perspective. You know, so I've always had a personal board of directors. I think I've had three or four different mentors. Some of them, I went out and found. Some of them I have joined organizations that have been fortunate enough to become not only a mentor, but a mentee. And I've kept those relationships up over three or four years. And all those people are now on my personal board of directors, that, you know, if I have a life-changing question, I've got a group of people that I can go back on. >> That is brilliant advice. I love that having a... Isn't that great Tyler? Having a personal- >> Yes Yes! >> Board of directors, especially as we look at cybersecurity and the cybersecurity skills gap Tyler has been, I think it's in its 5th year now, which is there's so much opportunity. What we saw in the threat landscape in the last 18, 19 months during the pandemic was this explosion and the attack surface, ransomware becoming a word that even my mom knows these days. What do you advise Tyler for, you talked about really making people much more aware of all of the opportunities within cyber, but when you think about how you would get women interested in cybersecurity specifically, what are some of the key pieces of advice you would offer? >> Well, again, I think I love the board of directors. I love that. That is brilliant, but I really think that it is about finding mentors, and it is about doing the research, and really asking questions. Because if you reach out to someone on LinkedIn, you know, they may just not respond, but chances are some someone will and, you know, most people in this community are very willing to help. And, you know, I found that to be great. I mean, I've got my board of directors too. I realize that now. (Debbie laughs) But I also like to help other people as well, that are just kind of entering into the field or if they're changing their careers. And it's not necessarily just women, it's people that are interested in getting into an aspect of this industry. And this is a industry where, you know, you can jump from this, to this, to this, to this. I mean, I think that I've had six different major career shifts still within the cybersecurity realm. So, just because you start off doing one thing doesn't mean that that's what you're going to do forever. There're so many different areas. And it's really interesting. I think about my 11 year old niece and she may very well have a job someday, that doesn't even exist right now. That's how quickly cyber and everything connected is moving. And if you think about it, we are connected, there is a cyber component to every single thing that we do, and that's going to continue to expand and continue to grow. And we need more people to be interested, and to want to get into these careers. And I think also it's important for younger girls to let them know these careers are really fun and they're extremely rewarding. And I mean, I hate to use this as an incentive, but there's also a lot of money that can be made too, and that's an incentive to get, you know, women and girls into these careers as well. >> And Tyler, I think you're right. In addition to that, you're always going to have a job. And I think cyber is a great career for someone that are lifelong learners, because like you said, your 11 year old niece, the job, when she graduates from college, she may have, probably doesn't even exist today. And so I think you have to be a lifelong learner. I think one of the things that people may not be aware of is, you know, for women who may have gone the non-traditional route and got degrees later in life, or took time off to raise children and want to come back to work, cyber security is something that, you know, doesn't have to be a nine to five job. I have, it happens to be a gentlemen on my team, who has to get kids on the bus and off the bus. And so we figured out how, you know, he gets up and he works for a couple hours, puts kids on the bus, is in the office. And then he gets the kids off. And once they've had dinner and gone to bed, he puts in a couple more hours. And I think, you know, people need to be aware of, there is some flexibility, there is flexibility in cyber jobs. I mean, it's not a nine to five job, it's not like banking. Well, if you were teller, and your hours are when the bank is open, cyber is 7/24 and jobs can be flexible. And I think people need to be aware of that. >> I agree on the flexibility front, and people also need to be flexible themselves. I do want to ask you both, we're getting low on time, but I've got to ask you, how do you get the confidence, to be, like you said, back in the day, in the room, maybe the only female and I've been in that as well, even in marketing, product marketing years ago. How do you get the confidence to continue moving forward? Even as someone says, "You're only here because you're a female." Tyler, what's your advice to help young women and young men as well fight any sort of challenges that are coming their way? >> I had a mentor when I first moved to the Defense Intelligence Agency, I had an Office Chief and she said to me, "Tyler, you're a Senior Intelligence Officer, you always take a seat at the table. Do not let anyone tell you that you cannot have a seat at the table." And you know, that was good advice. And I think confidence is great. But courage is something that's much more important, because courage is what leads up to confidence. And you really have to believe in yourself and do things that you know are right for you, not because you think it's going to make other people happy. And I think, you know, as women, it's really finding that courage to be brave and to be strong and to be willing to stand out, you know, alone on something, because it's what you care about and what you believe in. And that's really what helps kind of motivate me. >> I love that courage. Debbie, what are your thoughts? >> (laughs) So I was going to say, this is going to be really hard to believe, but when I was 16 years old, I was so shy that if I went to a restaurant and someone served me stone cold food, I wouldn't say a word. I would just eat it. If I bought something in a store and I didn't like it, I'd refuse, I just couldn't bring myself to go to that customer service desk and return it. And my first job in high school, was it a fast food place. And I worked for a gentleman who was a little bit of a tyrant, but you know, I learned how to get a backbone very quickly. And I would have to say now looking back, he was probably my first mentor without even trying to do that. He mentored me on how to believe in myself and how to stand up for what's right. So, Tyler, I completely agree with you. And you know, that's something that people think when they get a mentorship, sometimes it's someone going to mentor them on, you know, something tactical, something they want to know how to do, but sometimes what you need to be mentored in, could be, "How do I believe in myself?" Or "How do I find the courage to be that the only female in the room?" And I think that is where some of that mentorship comes from and, you know, I think, you know, if we go back to mentoring at the middle school, there's lots of opportunities, career fairs, the first robotically, get the middle school level, gives all of us an opportunity to sort of mentor girls at that level. And for all the guys out there who have daughters, this is, you know, how to... It's not like you can get a parenting checklist, "Teach my kid courage." And Tyler, I love that word, but I think that's something that we all need to aspire to bring out in others. >> I love that. I love that. >> Okay with that, I think I love both of your stories, are zig-zaggy in certain ways, one in a more direct cybersecurity path, Debbie with yours. Tyler, yours, very different coming from the music industry. But you both have such great advice. It's really, I would say, I'm going to add that, open your mind to be open to, you can do anything. As Tyler said, there's a very great possibility that right now the job that your niece who's 11 is going to get in the next 10 years, doesn't exist yet. How exciting is that? To have the opportunity to be open-minded enough and flexible enough to say, "I'm going to try that." And I'm going to learn from my mentors, whether it's a fast food cook, which I wouldn't think would be a direct mentor, and recognizing years later, "Wow, what an impact that person had on me, having the courage to do what I have." And so I would ask you like each one more question in terms of just your inspiration for what you're currently doing. Debbie, as the leader of security for NETSCOUT, what inspires you to continue in your current role and seek more? >> So, I'm a lifelong learner. So, I love to learn cybersecurity. You know, every day is a different day. So, it's definitely the ability to continue to learn and to do new things. But the second thing is, is I think I've always been, I don't want to call it a fixer-upper because cybersecurity isn't a fixer-upper, I'm just always wanted to improve upon things. If I've seen something that I think can do better, or a product that could have something new or better in it, you know, that's what excites me is to give people that feedback and to improve on what we've had out there. You know, you had mentioned, we've got this block of jobs that we can't fill. We have to give feedback and how we get the tools and what we have today smarter, so that if there are less of us, we're working smarter and not harder. And so if there is some low-level tasks that we could put back into tools, and talk to vendors and have them do this for us, that's how I think we start to get our way sort of out of the hole. Tyler, any thoughts on that? >> I again, I love that answer. I mean, I think for me, you know, I do like, it's that problem solving thing too. But for me it's also about, it's about compassion. And when I see, you know, a story of some child that's been involved in some kind of cyber bullying attack, or a company that has been broken into, I want to do whatever I can to help people, and to teach people to really protect themselves, so that they feel empowered and they're not afraid of cyber security. So for me, it's also really that drive to really make a difference and really help people. >> And you've both done, I'm sure, so much of that made such a big difference in many communities in which you're involved. I thank you so much for sharing your journeys with me on the program today, and giving such great pointed advice to young men and women, and even some of the older men and women out there that might be kind of struggling about, where do I go next? Your advice is brilliant, ladies. Thank you so much. It's been a pleasure talking with you. >> Thank you. >> Thank you. >> For Debbie Briggs and Tyler Cohen Wood, I'm Lisa Martin. You've been watching this Cube Conversation. (upbeat music)

>>Welcome back to the cubes coverage of AWS public sector summit live in Washington D. C. A face to face event were on the ground here is to keep coverage. I'm john Kerry, your hosts got two great guests. Both cuba alumni Shannon Kellogg VP of public policy for the Americas and john would ceo tell us congratulations on some announcement on stage and congressional john being a public company. Last time I saw you in person, you are private. Now your I. P. O. Congratulations >>totally virtually didn't meet one investor, lawyer, accountant or banker in person. It's all done over zoom. What's amazing. >>We'll go back to that and a great great to see you had great props here earlier. You guys got some good stuff going on in the policy side, a core max on stage talking about this Virginia deal. Give us the update. >>Yeah. Hey thanks john, it's great to be back. I always like to be on the cube. Uh, so we made an announcement today regarding our economic impact study, uh, for the commonwealth of Virginia. And this is around the amazon web services business and our presence in Virginia or a WS as we all, uh, call, uh, amazon web services. And um, basically the data that we released today shows over the last decade the magnitude of investment that we're making and I think reflects just the overall investments that are going into Virginia in the data center industry of which john and I have been very involved with over the years. But the numbers are quite um, uh, >>just clever. This is not part of the whole H. 20. H. Q. Or whatever they call HQ >>To HQ two. It's so Virginia Amazon is investing uh in Virginia as part of our HQ two initiative. And so Arlington Virginia will be the second headquarters in the U. S. In addition to that, AWS has been in Virginia for now many years, investing in both data center infrastructure and also other corporate facilities where we house AWS employees uh in other parts of Virginia, particularly out in what's known as the dullest technology corridor. But our data centers are actually spread throughout three counties in Fairfax County, Loudoun County in Prince William County. >>So this is the maxim now. So it wasn't anything any kind of course this is Virginia impact. What was, what did he what did he announce? What did he say? >>Yeah. So there were a few things that we highlighted in this economic impact study. One is that over the last decade, if you can believe it, we've invested $35 billion 2020 alone. The AWS investment in construction and these data centers. uh it was actually $1.3 billion 2020. And this has created over 13,500 jobs in the Commonwealth of Virginia. So it's a really great story of investment and job creation and many people don't know John in this Sort of came through in your question too about HQ two, But aws itself has over 8000 employees in Virginia today. Uh, and so we've had this very significant presence for a number of years now in Virginia over the last, you know, 15 years has become really the cloud capital of the country, if not the world. Uh, and you see all this data center infrastructure that's going in there, >>John What's your take on this? You've been very active in the county there. Um, you've been a legend in the area and tech, you've seen this many years, you've been doing so I think the longest running company doing cyber my 31st year, 31st year. So you've been on the ground. What does this all mean to you? >>Well, you know, it goes way back to, it was roughly 2005 when I served on the Economic Development Commission, Loudon County as the chairman. And at the time we were the fastest-growing county in America in Loudon County. But our residential real property taxes were going up stratospherically because when you look at it, every dollar real property tax that came into residential, we lose $2 because we had to fund schools and police and fire departments and so forth. And we realized for every dollar of commercial real property tax that came in, We made $97 in profit, but only 13% of the money that was coming into the county was coming in commercially. So a small group got together from within the county to try and figure out what were the assets that we had to offer to companies like Amazon and we realized we had a lot of land, we had water and then we had, you know this enormous amount of dark fiber, unused fibre optic. And so basically the county made it appealing to companies like amazon to come out to Loudon County and other places in northern Virginia and the rest is history. If you look today, we're Loudon County is Loudon County generates a couple $100 million surplus every year. It's real property taxes have come down in in real dollars and the percentage of revenue that comes from commercials like 33 34%. That's really largely driven by the data center ecosystem that my friend over here Shannon was talking. So >>the formula basically is look at the assets resources available that may align with the kind of commercial entities that good. How's their domicile there >>that could benefit. >>So what about power? Because the data centers need power, fiber fiber is great. The main, the main >>power you can build power but the main point is is water for cooling. So I think I think we had an abundance of water which allowed us to build power sources and allowed companies like amazon to build their own power sources. So I think it was really a sort of a uh uh better what do they say? Better lucky than good. So we had a bunch of assets come together that helps. Made us, made us pretty lucky as a, as a region. >>Thanks area too. >>It is nice and >>john, it's really interesting because the vision that john Wood and several of his colleagues had on that economic development board has truly come through and it was reaffirmed in the numbers that we released this week. Um, aws paid $220 million 2020 alone for our data centers in those three counties, including loud >>so amazon's contribution to >>The county. $220 million 2020 alone. And that actually makes up 20% of overall property tax revenues in these counties in 2020. So, you know, the vision that they had 15 years ago, 15, 16 years ago has really come true today. And that's just reaffirmed in these numbers. >>I mean, he's for the amazon. So I'll ask you the question. I mean, there's a lot of like for misinformation going around around corporate reputation. This is clearly an example of the corporation contributing to the, to the society. >>No, no doubt. And you think >>About it like that's some good numbers, 20 million, 30 >>$5 million dollar capital investment. You know, 10, it's, what is it? 8000 9000 >>Jobs. jobs, a W. S. jobs in the Commonwealth alone. >>And then you look at the economic impact on each of those counties financially. It really benefits everybody at the end of the day. >>It's good infrastructure across the board. How do you replicate that? Not everyone's an amazon though. So how do you take the formula? What's your take on best practice? How does this rollout? And that's the amazon will continue to grow, but that, you know, this one company, is there a lesson here for the rest of us? >>I think I think all the data center companies in the cloud companies out there see value in this region. That's why so much of the internet traffic comes through northern Virginia. I mean it's I've heard 70%, I've heard much higher than that too. So I think everybody realizes this is a strategic asset at a national level. But I think the main point to bring out is that every state across America should be thinking about investments from companies like amazon. There are, there are really significant benefits that helps the entire community. So it helps build schools, police departments, fire departments, etcetera, >>jobs opportunities. What's the what's the vision though? Beyond data center gets solar sustainability. >>We do. We have actually a number of renewable energy projects, which I want to talk about. But just one other quick on the data center industry. So I also serve on the data center coalition which is a national organization of data center and cloud providers. And we look at uh states all over this country were very active in multiple states and we work with governors and state governments as they put together different frameworks and policies to incent investment in their states and Virginia is doing it right. Virginia has historically been very forward looking, very forward thinking and how they're trying to attract these data center investments. They have the right uh tax incentives in place. Um and then you know, back to your point about renewable energy over the last several years, Virginia is also really made some statutory changes and other policy changes to drive forward renewable energy in Virginia. Six years ago this week, john I was in a coma at county in Virginia, which is the eastern shore. It's a very rural area where we helped build our first solar farm amazon solar farm in Virginia in 2015 is when we made this announcement with the governor six years ago this week, it was 88 megawatts, which basically at the time quadruple the virginias solar output in one project. So since that first project we at Amazon have gone from building that one facility, quadrupling at the time, the solar output in Virginia to now we're by the end of 2023 going to be 1430 MW of solar power in Virginia with 15 projects which is the equivalent of enough power to actually Enough electricity to power 225,000 households, which is the equivalent of Prince William county Virginia. So just to give you the scale of what we're doing here in Virginia on renewable energy. >>So to me, I mean this comes down to not to put my opinion out there because I never hold back on the cube. It's a posture, we >>count on that. It's a >>posture issue of how people approach business. I mean it's the two schools of thought on the extreme true business. The government pays for everything or business friendly. So this is called, this is a modern story about friendly business kind of collaborative posture. >>Yeah, it's putting money to very specific use which has a very specific return in this case. It's for everybody that lives in the northern Virginia region benefits everybody. >>And these policies have not just attracted companies like amazon and data center building builders and renewable energy investments. These policies are also leading to rapid growth in the cybersecurity industry in Virginia as well. You know john founded his company decades ago and you have all of these cybersecurity companies now located in Virginia. Many of them are partners like >>that. I know john and I both have contributed heavily to a lot of the systems in place in America here. So congratulations on that. But I got to ask you guys, well I got you for the last minute or two cybersecurity has become the big issue. I mean there's a lot of these policies all over the place. But cyber is super critical right now. I mean, where's the red line Shannon? Where's you know, things are happening? You guys bring security to the table, businesses are out there fending for themselves. There's no militia. Where's the, where's the, where's the support for the commercial businesses. People are nervous >>so you want to try it? >>Well, I'm happy to take the first shot because this is and then we'll leave john with the last word because he is the true cyber expert. But I had the privilege of hosting a panel this morning with the director of the cybersecurity and Infrastructure Security agency at the department, Homeland Security, Jenness easterly and the agency is relatively new and she laid out a number of initiatives that the DHS organization that she runs is working on with industry and so they're leaning in their partnering with industry and a number of areas including, you know, making sure that we have the right information sharing framework and tools in place, so the government and, and we in industry can act on information that we get in real time, making sure that we're investing for the future and the workforce development and cyber skills, but also as we enter national cybersecurity month, making sure that we're all doing our part in cyber security awareness and training, for example, one of the things that are amazon ceo Andy Jassy recently announced as he was participating in a White house summit, the president biden hosted in late august was that we were going to at amazon make a tool that we've developed for information and security awareness for our employees free, available to the public. And in addition to that we announced that we were going to provide free uh strong authentication tokens for AWS customers as part of that announcement going into national cybersecurity months. So what I like about what this administration is doing is they're reaching out there looking for ways to work with industry bringing us together in these summits but also looking for actionable things that we can do together to make a difference. >>So my, my perspective echoing on some of Shannon's points are really the following. Uh the key in general is automation and there are three components to automation that are important in today's environment. One is cyber hygiene and education is a piece of that. The second is around mis attribution meaning if the bad guy can't see you, you can't be hacked. And the third one is really more or less around what's called attribution, meaning I can figure out actually who the bad guy is and then report that bad guys actions to the appropriate law enforcement and military types and then they take it from there >>unless he's not attributed either. So >>well over the basic point is we can't as industry hat back, it's illegal, but what we can do is provide the tools and methods necessary to our government counterparts at that point about information sharing, where they can take the actions necessary and try and find those bad guys. >>I just feel like we're not moving fast enough. Businesses should be able to hack back. In my opinion. I'm a hawk on this one item. So like I believe that because if people dropped on our shores with troops, the government will protect us. >>So your your point is directly taken when cyber command was formed uh before that as airlines seeing space physical domains, each of those physical domains have about 100 and $50 billion they spend per year when cyber command was formed, it was spending less than Jpmorgan chase to defend the nation. So, you know, we do have a ways to go. I do agree with you that there needs to be more uh flexibility given the industry to help help with the fight. You know, in this case. Andy Jassy has offered a couple of tools which are, I think really good strong tokens training those >>are all really good. >>We've been working with amazon for a long time, you know, ever since, uh, really, ever since the CIA embrace the cloud, which was sort of the shot heard around the world for cloud computing. We do the security compliance automation for that air gap region for amazon as well as other aspects >>were all needs more. Tell us faster, keep cranking up that software because tell you right now people are getting hit >>and people are getting scared. You know, the colonial pipeline hack that affected everybody started going wait a minute, I can't get gas. >>But again in this area of the line and jenny easterly said this this morning here at the summit is that this truly has to be about industry working with government, making sure that we're working together, you know, government has a role, but so does the private sector and I've been working cyber issues for a long time to and you know, kind of seeing where we are this year in this recent cyber summit that the president held, I really see just a tremendous commitment coming from the private sector to be an effective partner in securing the nation this >>full circle to our original conversation around the Virginia data that you guys are looking at the Loudon County amazon contribution. The success former is really commercial public sector. I mean, the government has to recognize that technology is now lingua franca for all things everything society >>well. And one quick thing here that segues into the fact that Virginia is the cloud center of the nation. Um uh the president issued a cybersecurity executive order earlier this year that really emphasizes the migration of federal systems into cloud in the modernization that jOHN has worked on, johN had a group called the Alliance for Digital Innovation and they're very active in the I. T. Modernization world and we remember as well. Um but you know, the federal government is really emphasizing this, this migration to cloud and that was reiterated in that cybersecurity executive order >>from the, well we'll definitely get you guys back on the show, we're gonna say something. >>Just all I'd say about about the executive order is that I think one of the main reasons why the president thought was important is that the legacy systems that are out there are mainly written on kobol. There aren't a lot of kids graduating with degrees in COBOL. So COBOL was designed in 1955. I think so I think it's very imperative that we move has made these workloads as we can, >>they teach it anymore. >>They don't. So from a security point of view, the amount of threats and vulnerabilities are through the >>roof awesome. Well john I want to get you on the show our next cyber security event. You have you come into a fireside chat and unpack all the awesome stuff that you're doing. But also the challenges. Yes. And there are many, you have to keep up the good work on the policy. I still say we got to remove that red line and identified new rules of engagement relative to what's on our sovereign virtual land. So a whole nother Ballgame, thanks so much for coming. I appreciate it. Thank you appreciate it. Okay, cute coverage here at eight of public sector seven Washington john ferrier. Thanks for watching. Mhm. Mhm.

>>live from Washington, D. C. It's the Cube covering Bumi World 19 Do you buy movie? >>Welcome back to the Cubes. Coverage of Bumi World 19 I'm Lisa Martin with John Ferrier. John and I have a couple of gents joining us. To my right is Jeff Emerson, the global managing director for Custom Application Engineering Ethics Center. Hey, just hey, welcome. Thank you were glad to tell you, and we've got Steve would back with us. The CPO up. Hey, Steve, >>Hayley says. Ages >>minutes. You sticking into some research about that? The history of Bumi and Ipads and just looking at how the consumer ization effect has infected by a bad word has really infiltrated has that every industry organizations went from having enterprise applications. Legacy applications, cloud applications, custom applications. Let's talk about custom applications. What are you seeing in the customer marketplace for the demand for having this level of customization, whether it's a retail or or, you know, utilities company, >>it really doesn't matter what industry it is these days. Custom applications were going through a renaissance. It is. It is truly the renaissance of custom, where there was once a swing towards enterprise applications and the packages and so on. And now it's realized that oh gosh t separate ourselves from our competition. We have two great something that doesn't exist well, that is, by its nature, a custom application. And so these air coming up, Maura and Maur across the industry, and it's really starting to dominate the value chain for software. >>You were here in D. C. And public sector is going through a modernization as well. He looked at government procurement. I mean, essentially with data, everything's instrumental. You have unlimited resource with cloud computing. So essentially personalization. Hot trend. So applications air being personalized. They're customized. So every app should be not general purpose unless it's either under the covers. So this is the country's We've been having you guys. Bumi has a platform. You enable APS? You guys are deploying it. How are customers responded to this? Because to me they might go Will custom haps me, feels expensive. It feels one off the old adage. It's a one off, but it seems to be coming back. >>It does end. Fact is, you're able to do things so much more quickly today than you ever have been able to in the fast in the past and three ability to create new experiences quickly and react in an agile fashion to how those applications are being received in the marketplace. React to the data that is generated both as the primary data and the data exhaust from those systems to determine what your customers need, what they want, how they're going to act, what they're going to buy. All of those things are things that we can pull together so much more quickly today than we could ever in the past. And so it's great. >>Steve, We were talking earlier about how the data's real big part of the equation. Now everything about the application world it used to be the infrastructure would dictate what you could build. Yeah, now you have application developers saying, This is what I want now the infrastructures so programmable it's kind of flipped around that they're dictating kind of terms. >>Well, there's suddenly being this sort of emergence of these low code platforms to kind of help manage that. I mean, and they're kind of taking care of a lot of the infrastructure so you can kind of skill them is needed, but yeah, I mean, there's been a him. It's been a huge birthday. I couldn't agree more. There's like the demand for applications. We're seeing a lot. Sure there's the mega applications. We tend to leave those to our sister company Pivotal toe code those with this whole other ecosystem of applications everywhere. The personalization sze of the line of business needs to improve. Their business processes were going after that layer. We have to do it in the right way to make it super easy to do on the infrastructure that people expected to be with the architecture they expect to see. So they're highly customizable, so get exactly what they want. >>Jeff, you know, we always talk on the industry joke on the Cube, and the game is changed, but it's still the same. And every time a new trend comes, you know it's the death of something. A meteorite media to say something's dying when something new starts right. But nothing really changes everything about applications. It's the same gain just with a different twist. Do it with cloud. How are customers were spouting this? Because obviously his benefits business benefits cost benefits lot of mount up line with how they're attacking the application development. Then they got a data tsunami happening. But they gotta build APS, right, Not anything, right? >>It was once said that absolute in the world, and now it's really that data is feeding the world right? And so the amount of data that's out there and accessible and usable within applications is absolutely incredible. And so, with the emergence of the cloud in order, Thio support those massive amounts of data and Dr Rapid Development and then lo code to make that development much easier. These things all time come together, and you talked about the death of X, y or Z. We talk now about living systems, right on living systems are things that are easy to modify, their absolutely attainable and usable and expandable for for any kind of use and ultimately adaptable. >>So John mentioned the word one off a minute ago, and it reminded me of something where, you know, whatever industry that you're in, Not too long ago it was customers got some one off. Whether it's an application or part of the infrastructure, that's expensive, and it's not something that can be monetized but down to your point it's it's really custom. Applications are a big part of a business. Is competitive advantage. So what is it about the customized app? Is it Is it the fact that it's driven by an A P I? That's programmable that allows it to be customized at scale toe, where it's not a one off from a support perspective, it's something that really a company can use as that competitive leg up. >>Right in the this livings living systems world. We really have agile engineering, agile methods and so that we're doing development quickly. And we're doing this in an engineering fashion that has micro service's and small pieces of functionality that could be grabbed and plugged and played together. Thio great, different experiences. And so that granular ization of software is something that drives his flexibility and enables us to make modifications and updates quickly. >>Actually, ive your customer example that it was something we'd done, which is absence of term it like how the oil and gas industry saved nurses in Africa are saved people in Africa, which is we built, a solution that allowed them nurses in sub Saharan Africa to visit patients out in the field. They built it on a loco pa from witches. Flow part of me connected through a P eyes connected to all the infrastructure. But a lot of the work was on, uh, android tablets offline. So with the loco PA from that could deliver this solution with all offline capabilities, all the connectivity, all the integration, all built in without writing. Really any code? The only code there rose to customize the look and feel so looked exactly what they want. They delivered that on early version of our offline framework and then latterly the oil and gas industry origin energy deployed a similar solution to their rigs. The lot of you seem really complicated things of form, validation and better validation rules and better data synchronization that really forced us to improve our offline framework to something which is a Steve a big jump ahead of where it was before. And then lo and behold, the nurses nafta came back to us and said, Well, actually went up, Did or are we gonna run on desktops as well as ipads? Funnily enough, and we're like, Well, good news. We've actually already added that support. And so literally from three days of that phone call to them going live within our laptops and ipads. That was all it took. They didn't have to write any CO. They literally We just give them access to the new you. I will find framework. They installed it, turn off the wet. And that's kind of the power of this kind of next gen of up building that for this kind of line of business applications where you just need to innovate, how you work, you don't have to spend three years rebuilding those for iPad and >>Jeff houses. That dynamic, which is pretty much, I think, consisted a lot of these new APS. How's it changed your business? Because you know the theme that we've been identifying the mega trend is that there's more project work going on fast time to value, agile. You guys been doing exceptional work there and following Madu Center's been doing talking to Paul Doherty amongst others. Get a huge data science team you guys are on. I know you guys have transformed but big project and now a bunch of little projects going on, so it's kind of have to make you guys more agile as a practice because you've got to go out and solve the business problems with the customers. How is this dynamic changed? >>You're right. We absolutely do. And we have to assume muchas anything. It's helping our customers get into that mode of thinking as well. What was once a six months of gathering and documenting requirements is now done in a handful of ours. At first to get the first small bit of what's gonna be valuable functionality to put out there. And you keep doing that irritably. Overtime is instead of in a six month period, but then gets thrown over the wall. Thio have other people do this for another build stuff for six or nine >>months. I mean, the federation and getting those winds early gets proof points, gets mo mentum validation. You're not waiting for a gestation period. >>You make good decisions about what to do next on DDE. What to not do that you were planning on doing but turns out, doesn't mean >>I want to get your thoughts on something important you mentioned humanization. We see that big trend because Avery people centric and you're thinking at Bumi and we've had this debate in the queue we? We didn't come in on either side yet, but you know it orations great, great, fast. But the old days of software was a lot of craftsmanship involved, you know, crafting the product, getting it right now it's ship be embarrassed, ship it fast and then injury, which is great for efficiency. But there's a trend coming back to crafting product. They're absolutely. What is your thoughts on this? Because craft Manship is now design thinking. Would it be calling in different names? But this is a new thing. It's happening all the time. >>That software software craftsmanship is something that is more important today than it ever has been. Because you're going fast. And because you're putting things out into the market very quickly, you can't afford to make big mistakes, right? You could make functional decision mistakes, right? Oh, that wasn't the right thing for the customer, but having it not work or creating it bad experiences, right? Very bad, right? And so that craftsmanship building in all the Dev Ops pipelines and the error check in the testing and gateways and security checking all that happens automatically every time you check in code that is critical and it drives that craftsmanship back to the developer, right? Pushing left so that you make a mistake. You fix it within minutes, as opposed to >>you. Run private engineering, Smile on your face. Come on, What's your angle on this >>time? And craftsmanship is obviously huge mean? When we thought about like Bumi, we kind of wanted to make sure that yeah, that way we used to talk a little bit. No code platforms. And I think that what they did was they left out the craftsmanship that developers could do. And I've kind of thought it was like, Hey, if you can put like the business or the person who really understands the process of the application into the beating heart of the creation process so they could be on the right side of the soft waiting the world like they could be a creator and producer as much as they could be a consumer of applications, you allow them to do that and then let developers have radiate that that out with new engage with models, coding out new experiences that really hyper specific to the EU's case of the user. That's kind of the ultimate you get the core business value, and then you get the craftsmanship of the engineers together, I think, >>and I'm glad you said that because there's so many cases where here, we want to push it so that we don't even need software engineers for our software. And that's an interesting idea. Yeah, but it's actually not a good idea. Ll know or idea, Yes, simply because you there's an important aspect of software and and how I t runs that even if you have low coach, uh, components in order to drive the functionality right, these things that have to be done. But frankly, professional software engineers know how to do. >>It's better and faster and easier to do it that way. >>I think the federation certainly makes the problem that you're trying to solve. Solvable, right? Don't take your eye off the main ball, which is saw the problem, but get it elegantly designed all right, but I think that's a good This is a big discussion. You're seeing a lot with loco. So again, this is back. The custom maps custom APS just means a targeted app that solves a specific problem because it is a unique problem and it's different than the other one, right? That's the speed game. It's a speed game to nose in it that fast, fast, fast. >>And the engineering methods have changed really over the last couple of decades. While I've been doing this. Where way talked a moment about ago about the waterfall ways and then the agile ways. And the simple fact of the matter is that you're developing small pieces of software to get out into the market quickly, and you can do this in a matter of days and weeks. A supposed to months and quarters >>right, which many businesses don't have that time for company competitors gonna get in there. I'm curious as the development methods have changed so dramatically have the customer conversations like Are you guys talking more with business leaders vs You know the Guys and Girls and Dev Ops is that is this movie business little conversation that a CEO CFO, a CEO is involved in? >>So from our perspective at Accenture that the technology is always there to drive a business need, and so that conversation is first with the business owners, and that was true 20 years ago as well. The a CZ much as we do. I t transformation. It's a business lead. I transformation and, more often, technology supported business transformation. >>Excellent. Well, guys, thank you for joining John and me on the program today. Talking about all the things that you guys are seeing out in the field. Exciting stuff. >>Thanks for having us. >>We appreciate your time. Thank you for John Ferrier. I'm Lisa Martin. You're watching the Cube from Bhumi World 19. Thanks for watching.

>>live from Washington D. C. It's the Cube covering Bumi World 19 to Bide Movie. >>Hey, welcome back to the Cubes Coverage of Bumi World 19 from Washington D. C. I'm Lisa Martin with John Ferrier and John and I have a Cube alumni sitting with us. We have the chief product officer off. Del blew me. Steve would Steve, Welcome back. >>Thank you. It's great to be back. I could see again. John. Great must meet you >>back. Wise Enjoyed your keynote this morning, Man. There were so many nuggets and there I couldn't type faster. But one of my favorite things that you said is that no one is asking for less data. Slower? >>Yes, OK did I like kind of like saying because it frames things very clearly. It's just because it's clearly a prole. Every relates to him in the audience, but it was kind of amusing, so they've really got it immediately as I get that, that's a fair statement, so >>so like, and then you kind of took us the audience back. Thio 11 months ago at Bumi World 18. Some of the things that you guys said this is what we're going to be really focused on redefining the eye and I pass to be intelligent. Give her audience who wasn't able to see your keynote A little bit of that historical from 11 months ago. So what you guys are delivering today what the Bumi platform looks like today? >>Yeah, sure. So I mean, a lot of showed last Army, we kind of owe. Then we feel like we is like craters. The industry have to kind of try lead it. Where? Where is it going next? That's our big kind of duty, I guess. And so it's been taken over when we had the founder of booming attend, which was nice, but yes, so the big thing we should Last year was kind of the next generation, which is really a unified look and feel super easy to build applications that spend all of the portfolio and art in our that we offer our customers. We wanted to make it very collaborative, so users of business or business analysts or quick technical people can work together and use. Our platform is a collaboration space of the right controls in place. Eso stuff like that was really good to show that our new solutions. Overview. We've been definitely encouraging partners to put Maur intellectual property into our platform to excel, help accelerate their customers. Helping our customers just get people on board as quickly as possible. In fact, actually owned boarding employees on boarding was the solution we showed last year. >>That was fantastic. I couldn't believe how complex that was at Bumi. And when you guys said, We've got to change this huge improvements. >>Yeah, well, it was sort of a discovery that came up from one of our cells. Engineers got Andy Tiller did a fantastic job. He didn't enjoy his, um, his own boarding experience abuse me and then sort of building a solution. And we're like, we like we can actually do this way better on the platform. But what was amazing was that even for a company the size of Bumi, which is about 1000 people, we have, like, nearly 100 integration points and systems had to be coordinated to on board a single employee 100. Yeah, it's a lot, you know. So it became a really connectivity problem, actually, on >>boarding >>bits relatively easy. It's just, like connected all these systems. That's the hard bit. So yeah, we're excited to show that I think we got a kick out of seeing you together than we give progress on how we're moving that forward with various demos >>you don't want to ask you. Last year we asked the chief operating officer and the CEO Bumi what their investment priorities were going into the next year. And they said Number one was product. So that was a key thing. First and foremost go to market and then customer equation. But a product has been a big focus. That continues to be. What >>is >>the problem? Does it mean product when your chief product officer, what do you overseeing? Talk about What is the product? What is the platform And is there a difference? >>Yeah, I mean, so we we talk about the problem because we're in the product group, but we definitely see it as a platform. The investment in product is great. It means I get to spend lots of money like about my new converse. I won't try to show them, but way, but yeah, I mean, the investment partners being that we know that as we get Maur is this is this economy keeps building of integration and connective iti wanna continue to hold our leadership. We need to invest in product to make it easier. The expectations of our users is that they get a really premium experience when they're on board it onto the platform. We have to make sure we keep up to date with all of that effort. So a lot of what we talked about, it's how one is that we break our product up into discreet service is to allow us to move faster from an engineering perspective. And there's a lot of stuff that goes on there to think about ourselves as a platform to make sure we're fully extensible on. Then providing Maura Maura service is that people can build on our platform. So a lot of that investment just driving those >>activity. Rick was on yesterday talking about the big bets they made early on that are paying off. One of them was Aussie Cloud. On seeing that as you look at the architecture of this kind of new era of clobbering cloud to point, are we calling it? There's new requirements. It's the glue layers being built out. You need data to be accessible on addressable and available in real time, and you have multiple systems to talk to hence the integration you guys are doing. But this new mega trends happening is event driven architectures, which you guys talk about. There's a P I's just going from rest ful to state. And so you have micro service is here. So these air new dynamics Can >>you take >>a minute displaying like what all this means And what is event driven infrastructure? >>Yeah, a venture of architecture. But yeah, that's well, that's what we've been calling it. But yeah, I mean, it's basically that we're going to models where we're responding in real time to things that are happening out there on that revolt that involves a whole new level of scale. But, you know, we're also getting to things like streaming soas. Data come comes in, it's coming in, not in these packets, but it's constantly being fed to you, sir, constantly having to process it. You know, before in the integration space, it was like what? You'd set up a schedule you'd say, move that data at midnight from there to there and then it got faster and booming, provided real time, which was a request response that you send it personally, require a response back. But now it's like we're not going to just send it to you as a discreet thing. We're going to send it to you constantly, so event driven architectures. But how do you handle this continuous influx of data? And it's not getting any less. So how do you kind of manage this? We're being pulled in. Both ends were being pulled. There's never been more data that you never wanted to have faster. So it's like, How do you manage that? So for Bhumi, you know, that's why we're investing so heavily. >>Used to be in the old days when things were slower, events were like a trigger in a network management software alarm notification. Now they're happening. All the time is more and more events and paying attention to what events becomes a non human thing. Yeah, it's a software thing. Is that kind of where this is going? >>Yeah, well, I >>mean, we've been thinking >>a lot about that, like we sort of feel it. One is that we're gonna grow up from being on iPods to more of a data management vendor. We think that, like where the data manager in the future will come from an I pass, that we will be managing your data across like all of these systems from the catalogue and preparation to the, you know, actually integration and surfacing it up in real time and all that kind of streaming side. So I know it's Ah yeah, it's an evolving field for sure. >>One final point on this topic of product AP eyes have been great. They really made the market. Going back to the original Web service is in early two thousands to cloud. Where does a P I go? A A p I to dot or whatever you call it. What's the next Gen Place for AP? Eyes? >>Well, so it's interesting course. So we >>have >>a slightly different view of a pie management. That may be the typical AP management space, which is one thing to declare openly. But I think I >>want to >>go with that. Were right in the sense that cause I would think that because I'm a product, >>it's a good thing for a product. I don't think so Go >>and we're more than a little opinionated. So >>it is here, >>but yeah. Is that like sure. I mean, with a p I You need a gateway you need for the proxy ap eyes. Wherever they may be, wherever they may be developed. Other you build him and Bumi or you code them yourself when you told him, Manage those and throttle and scale and add policies and, you know, have developers registered to use them and monitor their usage and cut them off and have quotas. All that kind of that is old, fantastically good stuff. You know, there's lots of understeer doing a lot of that. We're adding Maur Mork capabilities there. But for us, a p I is really about AP enabling absolutely everything like we're in this world where you got refrigerators, two autonomous vehicles to cloud infrastructure to pivotal to all these different environments. And you have to have a tool that how do you How do you manage a P I across this incredibly disparate landscape of tools, technologies, things, infrastructure and it's one thing to say. OK, we could manage a P eyes and you install our software. Well, that's not good enough because, you know, with our customer like Jack in the box. They have 2200 plus retail locations. Nice have joked in my keynote that it's like painting Golden Gate Bridge. If you had to upgrade your gateway every time there was enough grade needed. It's like pain the Golden Gate Bridge to get to the end and you start all over again. That's 2200 plus retail locations. You know, I work for Dow. Ultimately is the holy owner of our business. He put five billion P seas on the planet. What if you had a gateway on five billion peces like, How do you manage that from a single control plane in the cloud? And that's what we're after. How do you do that huge scale AP enabling literally everything. >>And this was kind of under the concept of run anywhere that waas Yes, >>yes, yeah, and that was because we wanted to emphasize that it was about running Ap eyes and a pen, enabling things wherever they may be. That's why we put it under the run anywhere Banner. >>What's the biggest thing that you guys have done this year from last movie world that you're proud of? In terms of product or technology or something that could be of some obscure something prominent. What do you do? You proud of? What's the big thing? >>Yeah, well, for a point of perspective, it would be the AP I side for sure, because that was that was a big lift. There was a lot of work involved. We kind of moved ourselves forward very, very quickly in our capabilities on a p I with Gateway portal proxy, you know, literally within the span of just over a year. So that was Ah, big left. But I would, you know, because I also run engineering. So I feel like I need to, like, geek out a little bit. I mean, one of my proud things is, actually, we started wrestling and wrangling that 30 terabytes plus of metadata and starting to see what's in there. And like, anything in data science, you know, you're kind of like looking at weaken start. We started seeing all sorts of cool new things. Now I'm not gonna talk about it the inside side, But you start to see new things. We start to see ways that that meditated can be applied. So we built the infrastructure It's huge scale, massive scale they might have meditated, were ingesting and then analyzing eyes helping us, you know, improve productivity across the platforms. We talk a lot about being more efficient, more effective, so you'll see more of that in the pub. >>Can you clear up the just the commentary around the definition around single tenant instance? And when customers do multi tenant, because the benefit of the single tenants what the main core value proposition with the data, the unification of data? That's awesome. But there's also potential opportunities with customs. Might want have a roll run through things. So you have flexibility. Is that true? Is that the definite Take us through what the difference when, when multi tenant kicks in and what's >>well, so on our platform multi tendencies s. So if you think about the build experience when you're your dragon dropping, pointing, clicking, building your work flows or your processes for managing your data, you do that in the cloud, and then you can decide where you wanna put that. So where is that actually gonna be executed? And you can put it in our cloud, which is our multi tenant cloud, and then you. Could we manage it all for you? And that's fantastic. You can point or manage. Cloud service is if you have very specific requirements, usually around security, Sometimes around hyper scale. Well may put you in a manage cloud service environment. But then, if you have very sensitive data, you may want to run that workload and then stole our little run time. Adam, you know behind your firewall so we never see the data. So it's super sensitive. We don't see it. We >>see how >>it's running and we manage it. We have grade that that infrastructure for you, but we never see your data, so it kind of gives you the best of both worlds. You could be a cloud first, cloud only vendor, and you can be a traditional on perimeter. You could be a hybrid of both >>is not a requirement. The product. It's a customer choice. >>It's a total customer choice. I think that's pretty cool. Yeah, and I think actually we're one of the few that does it the way we've been doing for a long time. And it's hard, by the way, because it's like maintaining that compatibility For 10 plus years, is quite difficult to make sure everything works every time. We have, like 9000 >>customers and 80 plus countries. But on the the 30 plus terabytes of anonymous metadata, you are very clear this morning and saying that it's just the metadata that's not the actual have any any, you know, private information from any of our customers. But in terms of leveraging that data for those insights where some of the things that from last spoon me world to this one, that that access to all that data has what some are. Some of the announcements, maybe that came out today that you guys looked at saying, It's these are some of the nuggets that were able to pull out because we have the access to this musing. Maybe it's a I or what not gonna give you >>some examples in one was the the suggested filters. And it was a simple thing. I did sort of like that joke of It's one small step for Bhumi customers, but a giant leap for booming engineering. But because we rebuild a whole bunch of infrastructure to dio but suggested filters just making it easier to query information of various systems. And it is cool because it literally is looking your system, comparing it with other customers systems based on how you've configured in this case Attilio environment and then working out actually, based on what people are doing. This is kind of what the filter might look like for you, which is very, very personalized to the user. Based on intelligence. We have more That's on the bill tight. We have more on the deployment side because you can show you, actually hey, few of built in a p. I do want to deploy it out, too. A raspberry pie will. Actually, you probably want to configure the AP. I like this where you may find you see some issues here, and that's not static information that's evolving from the metadata. We can see the performance of your systems against the Oxy. All right, In that environment, I do it a bit like this. Or if you deploy to say, I Jules, we might make recommendations based on that process of that, a p I or that data quality hub that you wantto excess just make your systems run like this. So it's kind of predicting how you deployed >>I was about to say, Are you helping customers get predicted with us? >>Yes. And there's lots we can do there. I mean, like, so we'll do Maura. Maura. But we can automatically optimize your deployment. So if it's in our cloud, that that'll happens automatically. So helps us, too. But for customers, it's also making just go. Okay, we'll deploy it. And then the leverage that community to so see what works best. The most successful deployment, the most successful architecture and the way you've deployed it is was what you'll be matched with. And then the same with the run time. With monitoring, we can start to look at things and see will. Well, not slowing down a little bit. Actually, it's Linden the string error. A little bit, actually, based on what we've seen before, that system may be about to fall over, so you might want to get all not before completely does what it's gonna do. >>Well, we got you here. I want to get your definition of cloud two point. Oh, on We've been riffing on this. Been more of a takeoff on Web two point. Oh, because cloud one daughter was anything Amazon you know storage. Compute some networking, but it's Amazon that working. But you scale up start ups will go there. It's beautiful thing, but now it's enterprise. Start to embrace cloud with hybrid on premises and deal with all these hard problems and challenges. Crazy opportunity. An operating model for on premises Cloud Club one Dato Amazon. Really easy to work with. Scales are beautiful. Cloud to point is different. I got things to deal with. Observe, abilities, a hot thing you got kubernetes containers you got. How would you define what cloud? Two pointers for Enterprise? >>We'll think because we're all about the data cloud 2.0, is really like for us. Ah, data problem. I mean, it's just like E think before I mean, I was part of cells force for a while. Is this whole idea of like earlier data in the cloud will manageable for you. But when you're getting into the kind of environments were seeing, say, there's just too much data like you, it's not feasible. I mean, give you an example. Bumi itself. We moved our infrastructure customers was transplanted customers from Rackspace to eight of us Last year it was a big engineering lift to do. You can imagine moving 9000 plus customers over on our cloud Ah, design surface that but so we did that, but actually to move the data, it was so much it was actually faster to put the disk drives in the back of a van. No mobile moving over snowball using the wheel network, you know, the engine motor e one and then put the hard drives in. And then we did our sink to bring them back up so that we have the same data in both locations. And that's just an example of the kind of customer data that customers are routinely struggling with. And cloud wasn't set up for that. But that's becoming day to day now, so you need a highly distributed architecture. It was probably why we announced the Adam Fabric, which is really a fabric of connectivity, as much as is a fabric of data, so we don't need to move your data around. You can leave it where it is. We can do some analysis on it as part of an end to end >>Program Cube alumni that I was on the cube a couple weeks ago, he said. Data is the new software, data and software. What's your reaction to that when you hear that? >>To some extent, >>I think that's a CZ, A bit of a business process geek. I think you know this process around data for sure. But But I do think I've heard similar things with, like, actually, applications come and go. Business processes come and go, but the data remains so I think maybe in some respects, your date is the new software Could be a term I I could buy into a Well, >>Steve, it's been great having you on the Cube with John and me sharing all of the things that you guys have done in the last 11 months. I can't wait to see how everything becomes a P. I enabled. Still, next Bumi World, you gotta come back. Yeah, All right. Our pleasure for John Ferrier. I'm Lisa Martin. You're watching the Cube from Bhumi World 19. Thanks for watching

>> Narrator: From San Francisco, celebrating 10 years of high-tech coverage, it's theCUBE! Covering VMworld 2019. Brought to you by VMware and its ecosystem partners. >> Hey, welcome back everyone. We're here CUBE live in San Francisco, California, VMworld 2019. We're here in Moscone north lobby. I'm John Furrier with David Vellante, my co-host. Three days of coverage. Our next guest is Steve Wood, chief product officer at Dell Boomi. Steve, thanks for joining us today. Appreciate you coming on. >> Thank you. >> So we got your event coming up in DC. theCUBE will be there covering it. >> Correct, yes. >> We've been following you guys. Interesting opportunity, you're the chief product officer, you got the keys to the kingdom. You're in charge. (laughs) >> Yes sir. Oh yeah, yes. >> Tell us, what products, roadmap, pricing, all the analysis. >> (laughs) >> Take a minute to explain Boomi real quick for the folks that might not fully understand the product idea. >> Sure, yeah, yeah, absolutely. I mean, Boomi is a platform. The goal of the platform is to solve really tough technical challenges that you often meet in order to get to a business outcome of some kind. So if kind of brought that into maybe sharper focus, if you like. So Boomi started its life as an integration vendor. And its main goal is actually making it super easy to integrate your assets across cloud and on-prem. And that was a challenge at the time. A lot of the older integration tools weren't really ready for the cloud. Boomi brought forward this awesome architecture, this distribution architecture of containers that could run anywhere, integrating everything, moving your data around as needed. >> It was visionary. >> It was super visionary. >> I mean, it was early days. I was like, almost pre-cloud. >> Yeah, yeah, yeah. And actually, what was the cool thing was that you would have the benefits of cloud computing but you still could run something, like, behind your firewall, which was a really unheard of experience. Which actually starts to sound a lot like today, with Edge. But I'll kibosh that. But then, we sort of expanded into B2B, so you can connect to like, Walmart with all the sort of traditional and sort of modern protocols, kind of stuff that's been around for a while. We launched Hub for data quality, 'cause we felt like, hey, if we're connecting all of your data together, you're probably going to find it's fairly inconsistent. So we have Hub to help you manage your data quality. And then we moved into API management. We've done a huge investment this year to API-enable your integrations, but also API-enable your enterprise. And then possibly my favorite, 'cause it's an acquisition of my company, which I joined Boomi, acquisition of a workflow business. So actually not only provides workflow for people-centric processes, so really the connecting the dots from your devices and things and your infrastructure, on-prem and the cloud, all the way up to your people, driving those end-to-end experiences, but we also use the workflow product to help extend our existing products. >> So you were building a platform in your other company, and now Boomi's also in the same ethos, API-based, DevOps, complete DevOps, kind of no-code, low-code kind of thing. >> Steve: Low-code, yeah, for sure. Absolutely yes. >> What is, so what did you guys jump on, which wave is powering you guys now? Because I look at VMware, for instance, they have all these acquisitions. Their integration's going to be challenging. And just, most enterprises that are not born in the cloud, I mean, their legacy is, they got everything under the sun. And they're not necessarily talking to each other. It's a huge problem. >> No, for sure it is. And actually, it's become more of a problem as we move into machine learning and sharing data across enterprise, given access to the data for sure, ensuring it's controlled. So there's a lot going on. I think also for us, we're seeing obviously data's getting faster, you know. So as I often joke internally, nobody's asking for less data slower. >> (laughs) >> And we don't think that the volumes of data are going down anytime soon. So for us, it continues to be about the data. That for sure is the trend, the fact that it's moving faster, it's needed faster. We're going from batch to streaming, going from, you know, request-response to real-time. >> So what problems do you guys solve? You had to be nailed down and give up the problem statement, what is the main problem statement that you guys are addressing today that's most relevant? >> Yeah, the biggest problem is actually, I would say it's just unlocking your data. But in the fastest time possible. So when Boomi kind of, I guess, does well in the market, it's because we bring kind of enterprise creds, we bring you a journey to the cloud, not a cloud-only picture. We're not lookin' on-prem, tryin' to be retrofitted to the cloud. So what customers experience is they get the agility that they expect, so they get the value very, very fast. But they're also kind of ready to kind of make that transition from bein' on-prem, legacy, big vendor type, ERP, massive system to best of breed. And we help them with that change. >> I always say that, to David and I chattin', just really DevOps is about Dev and Ops, right? You want to have a great development environment so you can build those next-gen apps, which by the way, they need data, they need machine learning, all these new things are going on within microservices. It's very compelling, and everyone kind of knows that already. Or they should know it. But the dev scene's lookin' good, CID pipeline, good scene on the dev side. It's the ops side. (laughs) So I've seen a lot of enterprises really tryin' to catch up their operations, which is why VMware is continuing to do well, because they got operators. So I get that, like, they're not going to shift overnight to the Nirvana. But the role of developing and operating that app is ultimately the core digital transformation. >> Yeah, for sure, for sure. >> John: Your thoughts on that and what you guys are doing? >> Well, part of it also, like, when we looked at, so actually with the acquisition of Flow, I think it was interesting for us because it moved us also to be able to provide apps. So for example, VMware has something called Workspace ONE, which is their onboarding, help the employees onboard within the organization, connecting you to your endpoint applications. We're actually working with them on a similar thing. We have an onboarding solution to help employees onboard faster. But part of, I think, the value that we bring is that apps have traditionally, you know, been something that's heavily coded, they take a long time to do. So from integrations being heavily coded to APIs being heavily coded, and now for us, apps being heavily coded, is we kind of solve those tough types of challenges, everything from like, mobile and offline to APIs that are scalable and robust, through connecting to all of your systems including your things, and having the ability to do that. We kind of solve all of that so you can focus on what, so the true innovation. But like any cloud vendor, even if you leave it alone, it's getting faster, richer, better. So you know, it's unlike, say, coded solutions where they kind of sort of, they're a snapshot of that point in time. And if you leave them alone, they kind of slowly fade away, whereas Boomi is, we're constantly modernizing what you build on our platform. >> So the other piece about digital transformation is the data. And then you're talkin' about your data quality and information quality initiatives. That's kind of in the tailwind for you guys. So where does it all fit in terms of digital transformation, data, some of the things you were just talking about, and then the rest of the Dell family, Dell, VMware, how does it all fit together? >> Oh, sure, okay. Yeah, that's a lot. But yeah, I'll see if I can sort of give the gist it. Well so partly actually for us is like, getting data out. It feels like if you're going to transform your business, you kind of need to know what data you have. That feels like a fairly normal thing. But also, and I can't, I'll give you a teaser. We can't say more about it. But one of the things that's been interesting about the data on our platform, our metadata, which is anonymized, we have more customers for the longest time running on our cloud service, which is a multi-tenant service, which means we see how the 9000 plus customers work with other systems. And we have the metadata of how they architect that connectivity across the board, all the way out to people, all the way down to their infrastructure. We can see what's going on. So we've been doing a lot of research. And actually, showing you more about what your business is doing. And we have some really cool announcements coming up at Boomi World. >> So the truth in the data. I'm imagining machine learning. But you get to see the patterns. >> We get to see the patterns. >> Emerging. The signals, there's signals. >> Yes. And we're seeing the patterns not only in what's being built and the structure of what's being built, but how it's operating, how it's being deployed, what's most successful, how those things work. So we have a really interesting sense. So when you're going through a digital transformation, we think we can show you things that you'll not have seen before. >> So what are you showing and to whom are you showing it? >> So it'll be at Boomi World on the first of October >> (laughs) >> In Washington. So I can't say more than that. But we're going to show them some things that our platform can extract for you that we don't think any other vendor's done before. >> And today, how do you visualize that? >> Well, today actually we don't do that much to visualize it, actually. That was actually, so we've been on a real machine learning train for the past couple of years. And as we got really good at understanding the metadata we have, and we've got the data scientists involved, they started showing us more of the art of the possible. So for that I'd say we've been probably remiss in not helping customers more, exposing more of those insights. Obviously, from a transformation perspective, we unlock your data. But we think we can do a lot more. >> So is the Dell relationship largely a go-to-market one? Same question for VMware. >> Well I'd say, like, if you think about Dell, it's like, I guess, I dunno, the sort of unofficial, so the hardware part of the triangle, VMware being the server infrastructure. >> Don't tell them that. >> Yeah, sorry. >> But it's true. (laughs) >> Yeah, sorry Michael. But it's the hardware side. And VMware you've got the kind of infrastructure, DevOps, operational side. And then Boomi brings you the data. And we think that that kind of triangle is what you need to go through a digital transformation, certainly if your title is CIO. >> And Michael Dell's bullish on you guys. He was at your last event we broadcasted. He sees you guys as modern SAAS interface for companies, certainly from a transformational standpoint, as the interface in for integration. >> Yeah, for sure. I mean, it will, I guess some of our performance speaks to that. I mean, we've been a very, very high-performing, I don't want to say we're the number one performing technology in his portfolio, but it's certainly, it's either-- >> Well, you're up and to the right. That quadrant thing. >> Yes, quadrant, yes. >> What's the winning formula? Why are you winning these deals? Why are you winning customers? Why are you keeping customers? What's the real value that they're getting out of Boomi? >> So our CMO would want me to say, business outcomes accelerated, which is, hopefully you got that. >> Check, got that down. >> Oh, yeah, yeah. (laughs) >> Gold star for you, go. >> Thank you, thank you. >> Now, the truth. (laughs) >> Now the truth. (laughs) It's actually, but it is time to value. I mean, our customers, that's the, because we've solved the challenges, sure. Other vendors can say, we've solved the challenges too. But we've solved it in a low-code way, and customers see the value very, very quickly. So when we go, you know, head-to-head with a competitor on a deal, you know, like a bake-off if you like, we win pretty much every time. >> Take a minute to explain what low-code is for the folks that are, been debating what low-code is. Been a lot of Twitter wars on this. But explain what low-code is. >> I will give my explanation, sure. So low-code fundamentally is the idea that, you know, I'd say, like, the first phase, almost, of cloud, was like, hey, you're not going to code anything. The new paradigm is it's all point and click. And Salesforce, actually I used to be at Salesforce, I sold my last company to Salesforce. It was all about kind of like, the no-code approach. But I think reality is, it's like, there's different ways in which you can be productive. Sometimes point and click is by far the most productive, but it is not always the most productive way to solve a problem. Sometimes code is by far the most productive way to solve a problem. So when you provide a low-code platform, what you're really thinking about is productivity for everybody, not just the point and click, drag and drop, ease of use, but also productivity for the developers. So when they engage and they're working together to deliver a solution, it's highly productive. >> For instance, wiring up APIs is a great example, or managing containers might be a great use case of low-code. No code would be just, you know, more automation behind the simple stuff. But low-code is really more stitching stuff together. >> Yeah. And sometimes people do associate it more with application creation side, but I often think of it as, like, a role thing. If you think about, like, your company, one solution to solve the kind of app gap, or the gap in all the stuff in your backlog that needs to be done, is to hire more IT people. The other way to solve the problem is to empower everybody you have to do more with technology. So I often think about it as like, you know, software eating the world, you know, a lot of people are on the wrong side of that equation. You know, they're-- >> You talk to people who are cloud-native, or born in the cloud, their IT is the developer. I mean, they're the ones managing the configurations, and it's all either scripted away or written code for. What was IT's job? (laughs) >> You say a lot of people on the wrong side of that equation, you mean customers? >> No, I mean, well, people inside the business are often like, you know, they've got a whole bunch of stuff they want to do with technology, but there's a gatekeeper, and that gatekeeper is the developer. And it's not that they want to be a gatekeeper, it's that you need tools to be able to do it. They want to be sure the architecture's right. So low-code platforms are all about kind of bringing more people into the conversation. So I often think about it as like, take the business, and so say, your ideas don't now get translated through a whole bunch of series of weird things, you can now be very engaged in the creation process. >> So it's domain expertise meets coding capability. >> It reminds me of the old 4GL days in the '80s. You know, you had interpreters, scripting languages, kind of higher-level of abstractions. But the underlying language is hardcore, compiler, object code, you know, all that stuff under the covers has to be there, right. That's, you're putting that abstraction on top, making it easy to code. >> Yeah, absolutely. 'Cause like, I mean, what you deploy has to be credible. So what the low-code vendors are after is something where an architect would go, love that, that thing is great, I love the way it's put together, it's well-architect, well put together, and I can code around it to finish those last small issues, and kind of, you know, add my shine to it. >> 'Cause they know what they're dealing with. >> Yeah. >> Under the covers, at least. >> Yeah. But a lot of like, you know, the no-code vendors kind of went for architecturally slightly curious routes and didn't necessarily think about the whole picture. >> So you guys are all about dealing with all this complexity, helping people manage that, at least a part. How about some of these new innovations that are comin' out. I mean, the world's crazy about ML, AI, blockchain, you know, all kinds of new automations. Where do you guys fit into that? Is that an opportunity for you? >> Yeah. I mean, well, so machine learning, we're all, oop. Sorry, I tried to spill my water. We're all crazy about machine learning as well. So we're using it a lot, as I mentioned, on our metadata. But also, we see a lot of our customers using our technology to get the data out in order to surface new insights. So for example we've got, like, actually Jack in the Box would be an interesting example of kind of emerging technology. One is that they're using our technology to get data out at the point of sale. So they have to use, our technology is running at the point of sale. They have 2200 plus locations, which means we have to be able to run out there on the edge and process it right at the point of sale. But they're trying to do things like, you know, when you drive up and your license plate is scanned, they know who you are, they go, hey do you want those, that same meal again. You know, so they can predict what you want, they can help make suggestions for you. So that's a fantastic example. So, yeah. >> Great edge use cases. I mean, that's awesome. >> And then, which is one of them, but there's also, machine learning for us, we're tied with machine learning. And we are exploring the idea of actually providing machine learning as a service to our customers. That's something we're just, we're sort of eyeing that up as we've been doing more and more internally. But blockchain's the same. And we see customers playing with blockchain all the time. And actually, I guess, our pitch to customers who are looking at emerging technology is we have a group that is looking specifically at emerging technology. And because of our time to value, and because often, emerging technology is like, so what does blockchain mean to, I dunno, well, you guys, theCUBE. >> John: Supply chain. >> Steve: You know, like, how would you use it? You might want to experiment with it. >> We have a CUBEcoin. >> You have a CUBEcoin. >> And we have a reputation protocol, and we have a community software layer. >> It's actually working. >> I would track the supply chain. >> You're going to do it? >> I already built it. (laughing) It's in tech preview right now. >> Okay, well good, good. Hopefully you did it on Boomi, that'd be nice. (laughing) >> No, but I mean like, the success or maybe failure of CUBEcoin, I don't want to call it, but you know. >> It's not a utility token. Well maybe, nah. >> Right. (laughs) But like, a lot of customers want to build to experiment, so time to value's really important. We're solving those problems in those emerging technologies. >> Yeah, rapid application development and DevOps, using containers, APIs, very friendly. >> Try it out and then see, like, does this make sense? >> All right, so you got the event coming up October first to the third in Washington DC. You get a plug for that. >> I might've mentioned it. >> theCUBE will be there. You're holdin' back on some of the good stuff. The good items. We'll wait for then. >> Yeah, otherwise, yeah. Wait for the keynote, then you'll see, yes. >> (laughs) They all want to know now. Come on. (laughing) They're all like, no, don't say anything. All right. We'll leak it on Twitter later if I find out. No, no. Steve, thanks for coming on and sharing the insight. We're looking forward to chatting more at Boomi World in Washington DC. I'm John Furrier with Dave Vellante. More live coverage here in San Francisco for VMworld 2012 after this short break. (electronic music)

>> Live from Las Vegas, it's theCUBE covering AWS re:Invent 2018, brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> And welcome back to Las Vegas. We are live here at AWS re:Invent along with Justin Moore and I'm John Wallis. I know when you travel these days, all you want is, you want it to work, right? >> Yeah. >> We just want to get there. Well, I'll tell you what, Phil Wood from EasyJet wants you to get there as well. As does Matt Leonard from CenturyLink. Gentlemen, glad to have you with us. >> Thanks very much. >> We appreciate it. >> EasyJet, a European-based carrier just north of London, so we're talking about air travel. You are, as we've just recently learned, you are a Catalyst Award winner from CenturyLink, there's a reason for that and that's a point of distinction. So Matt, if you would maybe take us through a little bit about what EasyJet did to earn that distinction. >> Sure, the Catalyst Award is an award that we give out in combination with VMware to kind of highlight customers that are doing new and exciting things with regard to digital transformation. We've been a provider of services and a partner with EasyJet for a long time and they've done some really cool things with regard to services they provide their end customers. And we play a very very small part of that. Two exciting things that are my personal favorites with regard to EasyJet is the Look and Book service. So within the application if you want to book a new trip you normally have to type in the airport that you want to go to, and you have to figure out what's the name of the airport, or the three-digit code. With the EasyJet application you can upload a picture and it has intelligence that's used to figure out that picture and what that landmark is and then what the nearest airport is. So that's pretty exciting. And the second exciting thing within the application >> is a trip in one tap. So you can basically justdial in how much money you want to spend for a trip, hit the Go button, in literally one tap it'll recommend a city, a hotel, and a fun and exciting thing that's happening during that duration of time. So for last minute travelers, my family's certainly one of those, we got a free period of time, one tap it'll tell you where to stay, how to get there with EasyJet and then what's exciting happening within that city. >> So I could put in, I say, I want to spend 300 dollars a ticket, and tap boom, and it'll say you can go to Brussels, you can go to Amsterdam but you can't make it to Dublin this weekend, right? Or whatever. I love that. So what has that done for your business in terms of, on a micro level and a macro level, what's it doing in terms of that interface and what's it mean to your business in general? >> As a business, we're 23 years old, so we started very much like a startup and we kind of came in at low-cost airline bracket. But now what we're renowned for is the convenience, and you've got two examples there where our customers love that because it's a convenient way. They don't have to do lots of searching, they can just take the photograph and they know exactly where they're going to go. And that's really what differentiates us is that convenience and the customer experience that we offer to all of our customers. We have a lot of customers. We have 90 million passengers a year. They come to us because they know not just that we give great value but that experience. So what it's done, it's made us grow. And that's literally how we continue to grow is to expand those customer services and Centurylink have been a part of that journey for over half of our tenure as an airline. >> It sounds like technology is actually right on the edge of driving that value for customers and making things easy. Like just the experience of being able to walk out and take a photo of something and say, I want to go here. I would like to go out and see if I can trick it by taking a photo of the Eiffel Tower out in the back here. >> We'll go and try it out in a bit. >> I'm confident. >> We'll see how it goes. That's making use of a whole bunch of technologies. It's got mobile technology in there, it's got image recognition, it's got machine learning. What else are you seeing at the show here at AWS, what are some of the technologies that you think will drive the next evolution of things, what's going to win you the next award? >> I think one of the things I've really been looking at is around data and around the personalization. So we talked about customer experience but our whole journey of taking a plane, taking a holiday, for example, it's from the moment you book it to the moment you get back. There's so many touch points during that and there's so much data that we can take from that. So I've been really interested in looking at how different organizations and how Amazon have been using data. I also think you can't come to a show like this without looking at machine learning and AI. We're using aspects of that in how we analyze our data, but that's certainly something I think's going to change the airline industry moving forward. >> How important is a partnership with someone like CenturyLink in making sure that you get the best use of these technologies? >> Matt talked about that they have a small part to play but you've got to understand that every single customer, every single search on our website goes through a network. In order for us to connect to our customers, be they booking a flight, be they on a flight, we've got to go through a reliable network. And the way I describe it, it needs to be effortless. It needs to just work. You mentioned that right at the beginning. But I also think as well for us to exploit technologies like the cloud, which is what we're starting to invest a lot more into, we need a partner who can help us on that journey. So again, that's where CenturyLink and the partnership we've got has been absolutely crucial. The things that we're doing with CenturyLink around making sure that we're only paying for our network for what we use. We're an airline. Our airports are seasonal so kind of traditional networks, what you'll end up doing is paying for bandwidth all year, when in the winter seasons if you're not flying there that's dead money. So it's simple things like that but that makes a huge difference towards my cost base perspective. >> And time of day, I assume that affects that as well? >> Absolutely. I mean, clearly in our summer periods we fly a lot, so time of day during the summer, there's not that many hours we don't fly. >> You get a lot of daylight over there, right? (laughter) >> But certainly in winter where we have our kind of summer destinations, it makes a big big difference. And that's cost we pass on to the customer as well which is massively important. >> What is it about the customer that you don't know? You talked about AI, what that could do for you down the road. How much information, how much data do you think you can extract from the customer to make that experience even better, and what do you need to know about them, and how will CenturyLink help you get there? >> You need to know everything. I mean, we know that we sell a hundred seventy million bacon sandwiches a year. Whether that's useful or not, but we know that. >> There's hungry people. >> That's a lot of bacon. >> It is a lot. But it means that we know the type of food that our customers want to eat, we know the top destinations, even knowing how long between booking a flight and actually flying. So we know from a price perspective and from a making sure our planes are full or making sure we're not overselling our flights. All of that information, there's just a wealth of data that you're getting out there. And it's not just customers. One of the big factors for us is safety. So we use our data now to analyze maintenance. So we have predicted maintenance around when's the right time to put in spare parts but also what's the most efficient time so that we're not disrupting the customer. So actually we may want to bring a maintenance cycle sooner so we can open up more routes for customers to fly when they want to. So it's very hard to answer that question cause every day we're coming up with new ideas or new bits of information that at the time we never thought we needed to know but that actually turns out to be an absolutely crucial part of our offer. >> That's not an unusual thing for most people in a world where there's this much dynamic, this much change going on. So what process do you run through to figure out, where should we be looking to find out the next set of optimizations? Or how do you discover what is the next thing that you should work on, like where does the idea for, maybe we should build this app. Where does that come from? >> I don't think there's one model. I think what's always been at the heart of EasyJet is innovation, and we've always focused on the customer. So we have a great loyalty scheme and our customers are very loyal. We have 75% loyalty with our customers which is phenomenal. We get a lot of feedback and that feedback drives a lot of the ideas that we push forward. So I think it's a mixture of our passion, it's a mixture of our experience, but I'd say that feedback from the customer, that drives a lot of the ideas that we do moving forward. >> From the CenturyLink perspective, you received certification for the MSP designation. >> Yup. >> Working in the travel business, what does that do, or how does that MSP certification translate over to learning about a different industry, to applying different approaches, unique approaches, because it's not one size fits all. They have very, very specific challenges that you're trying to address. >> Yeah, so on a broader sense, our mission with clients like EasyJet and customers interested in the cloud is really to connect, migrate, and then manage their workloads within the cloud. That's really what we're focused on. And there's certainly commonalities within verticals but every customer's different, and really assessing, starting with the customer, and that's a common thing that I think both EasyJet as well as CenturyLink and certainly Amazon have in common, really focused on that customer journey. One of the approaches that we take through a program called CustomerLink is put the customer right in the center of the team and we've applied the Agile methodology to that customer engagement process. So we do a standup meeting once every two weeks, we do sprints once every two weeks. A lot of our customers are part of that board that we use to activate the sprint and to define priorities and what actions are. So really pulling the whole team together across different departments, focusing on the customer first, and in many cases the customer's customer first cause a lot of your priorities are based on what your customers are after, and really making sure that we're working on the right activity in a very lean way, pulling away as much waste as possible that aren't contributing to adding value to the customer journey. >> And then from your side of the fence going forward, you've mentioned four or five general areas, you've said, we could improve here, we could look at this, we could look at that. How do you prioritize and say, okay, let's focus here now and then we'll move on. So if you had to focus now, or for the next twelve months, what would that be on? >> So we've actually just relaunched our strategy. At the heart we are an airline so our priority is about being number one or number two in all the primary airports. We've got to keep that. But we also recognize from the data that the amount of our customers who will book hotels or book further products through some of our partners that's something that we can actually capitalize on. So we're looking more into holidays now. Taking that customer centricity, and how do we make the end-to-end journey for our customers so including travel to and from airport and the whole day. So that's a priority for us. Continue building our customer loyalty. So as much as we pride ourselves on loyalty, we believe there's a lot more you can do. I think the airline loyalty schemes need to be shaken up a little bit more. If you look in the retail sector or things like that they're focusing on different things. It's no longer just the case of air miles. People want speedier boarding, or they want a better experience, better seating arrangements. So we're looking at our loyalty. And then also business. We talk about, we've got really good slots for when we fly planes. And they're slots that are competitive to a business traveler. So that's our three main areas, I would say, are business, holidays, and loyalty. >> Matt, you're going to be in business for a while. I think you're okay. If you could work on legroom, I'm sold. Matt and Phil, thank you for being with us. We appreciate the time. Join us here on theCUBE. You're watching our live coverage from Las Vegas at AWS re:Invent. (electronic music)

>> Live from Bahrain, it's theCUBE. Covering AWS Summit, Bahrain. Brought to you by Amazon Web Services. >> Welcome back everyone, we're here live in Bahrain, for exclusive Amazon coverage. It's theCUBE's first time in the region, we're excited to be here as AWS Public Sector Summit and commercial opportunities are expanding Amazon has announced and will be up and running in 2019 with a new region here in Bahrain in the middle east. It will generate a lot of activity, we expect it to create a tsunami of innovation, data information is the new oil. We're here covering it, this is going to be the beginning of more coverage here in the area for theCUBE. And we're meeting new people, and then we've run into some luminaries, CUBE alumnus, and our next guest is a CUBE alumna, John Wood is the CEO of Telos, also been on theCUBE many times as you might know, is an expert in cybersecurity, just an overall knowledgeable and visionary entrepreneur, good to see you thanks for joining us today. >> Thanks John, I really appreciate it. >> So you're part of the entourage with Teresa and the team as she comes in a cross-pollinates Amazon Web Services public sector seven, what she's done in Washington DC and beyond, here in the region, it's going to be a new formula that Bahrain and the people here have recognized. Like we were in a meeting yesterday, where you weren't pounding the table, but you looked very clearly at the Chief Executive Officer who reports to the king and the crown prince and you said, you don't really know yet, what you got, and you're a visionary, so and we've talked about this and so I want to get it out here on camera, this is a big freaking deal. >> It is. >> Can you explain why, and what your vision is and what will happen with Amazon, 'cause you've been a partner of AWS with Telos, you've been very successful, you've seen the moving parts, you've seen the impact of innovation. >> Yup, absolutely. >> What's your thoughts? >> So you know, the shot heard around the world back at the end of 2013 John was when the Central Intelligence Agency made the decision that the cloud was just secure enough for them. And that kind of made everybody around the world stand up and notice. So yesterday, when we were talking with all of the various people around economic development in Bahrain, you know I said the shot heard around the Middle East is that Amazon is located here in Bahrain. I think just like what happened in America, it's going to have a massive impact from a socio-economic point of view here in the Middle East and specifically in Bahrain. >> What are some of the things that you might expect to see, that they got to be ready for here? >> Well first of all, one thing I'll say is a marked difference from America is that the government here and the business environment here all has agreed it's important to move to the cloud. That in and of itself is a big, big difference than America. In America it's been a lot more fragmented and it's taken more time. I think here, I think the government and the industry is seeing the value of the cloud globally, and they're going to be able to move that much faster than even we did in America. >> They built a Formula 1 race track in 14 months, they don't have a lot of the baggage that America has in terms of older systems. I mean, more tech baggage, or tech legacy, older systems, older databases, kind of a clean sheet of paper. >> They have a bit of a clean sheet of paper, but they also do have legacy John. What they've also done though, is they've given themselves a two year time frame to move everything to the cloud. Now that in and of itself, having a beginning, a middle, and an end, is a really good thing because the journey's going to be relatively rapid and I think the uptick economically as a result is going to be rapid as well. >> So one of the things that you were also involved in here with Teresa and the local Bahrain government and entrepreneurs is you were here with General Keith Alexander, who had to leave last night, we had hoped to have him on theCUBE, four star general, head of the NSA, he's seen his shares of data and scale, he had a unique perspective. What are some of the things that you and General Alexander were discussing with the government here? Can you share with appropriate, some of the things you were talking about? >> I think we can apply best practices here, just like we applied back in America. I think the fact that they've gone to a cloud first policy is a really good thing, the next step I think is to find a standard that you can actually look to from a security point of view, 'cause with that standard you can then have a common lexicon. And that common lexicon allows you to share data between and amongst each other that much more quickly. >> You know, one of the things I overheard you over here and I kind of observed this, and I'm just going to throw it out there because we think the same way with theCUBE is that when you have a cloud model, the benefit of the cloud is you can just actually spin up another instance or thing. It's horizontally scalable, generally speaking. So as you run your business Telos with Amazon in the US and other areas, this is a new opportunity for you. It's almost rinse and repeat, just kind of plug in. And cloud gives you that benefit, so this kind of opens up the conversation of opportunities that Amazon will pull with them to Bahrain and the region. Do you agree with that? How do you see this pull that Amazon might have? >> I think what Amazon can do more than really any other cloud organizations is because they've been at it for such a long time, so much longer than the other cloud providers, they can bring best practices to the table, they can bring best technologies to the table, they can bring best partnerships to the table, which allows people to actually know with confidence that if they move to the cloud it's going to work, and it's going to be more secure. >> The other thing I will also point out at the end of that is then that Andy Jassy and Teresa also bring expertise. They'll do work here on behalf of citizens. >> Well absolutely, you know when Amazon makes a commitment to build a region over a 10 year period it's anywhere between a two to three billion dollar financial commitment to the region, so that in and of itself drives economic value into the region. >> So I got to ask you the tough question, which is obviously the one that's the elephant in the room, is instability in the region, potentially, how does digital disruption impact, say Bahrain and Middle East, you got Horizon, you got crypto-currency we know that markets kind of frothy and somewhat unethical in some areas, that's a red flag, but wants to be legitimate, cybersecurity, a big thing. This is your wheelhouse, cybersecurity, these new emerging areas, you got A.I. booming, you got cloud booming, got the notion these emerging tech, cybersecurity's at the center of the action. What does that mean for Amazon? What does that mean for stability in the region? What's the impact? What's your view on cybersecurity, Middle East, Bahrain, Amazon, can you share, can you unpack that? >> So John, that's an incredibly broad question, so thank you. So from my point of view, I can't deal with the political situations, what we can deal with is what we can control. And we know we can help control the security automation orchestration, we know it works. We've seen the most security conscious organization in the world adopt the security. We and Amazon are the security for the agencies cloud and we know that works. As it relates to the political situation I think here the ruling party understands that's an issue and they're working on it, and I can just leave that to them. >> But you're independent of that, you allow the scale piece on Amazon. And what do you hope to do in the region? What are some of your goals as a commercial opportunity with Bahrain announcing this partnership at the highest levels, this community here, young people want to work here. >> So I see it as a huge work force opportunity for everybody, number one. Number two, I think we can find a way to make sure that everybody can feel confident that it's going to work, so they can feel confident they can move their workload to the cloud. People in Kuwait can feel confident, people in Saudi Arabia can feel confident, and again, that confidence builds stability. With stability, with economic stability, there becomes political stability. That's the other point I'll make, is that at the end of the day, if you have the benefit of having the financial stability it helps in a lot of different ways. >> So what's your advice to the folks, if I had the king sitting here and the crown prince, we had a round table, what are some of the things that you would advise them from your experience, kind of looking back on your career and what you've done now knowing that the regions got a cultural and more of a different economic dynamic, what's your advice to the crown prince, the king, and folks trying to figure this out? >> From a cybersecurity perspective, I would want to do something similar, maybe not the same, but something similar to what the United States government did. When the US government decided to adopt a cybersecurity policy, the so called Cybersecurity Executive Order, there were two parts to it John, the first was cloud first which has been done here, and the second was to adopt the NIST Framework, the NIST Framework gave the common lexicon for all the cybersecurity professionals to be able to push their workloads to the cloud and then guys like me, what we do is, we push automation into that framework, which basically means we get out of the way of the mission and we help make the mission happen much more quickly. >> What about training and support? What's your impression of the economic development board, some of the work they're doing? Obviously they have a transition we heard, maybe some of them in a work force not yet mature, but they got programs in place. How do you see that developing? How would you put them on the progress bar vis-a-vis their aspiration? >> I think in general some of the work force issues that they have here are very similar to the work force issues we have in America. You know, in America, often when kids graduate from college there's a gap between what they get in terms of a degree and what we need in terms of a skill set, that kind of happens everywhere. I think that simple programs like apprenticeships; which have been around for a long time, can be very, very effective in terms of narrowing that gap so that when the kids come out we can actually put them to work and they don't have to be re-trained in the work force. I think that's a big opportunity. I also think there's a big opportunity to bring some of the people here into America to teach best practices, and then bring them back, that they can bring those best practices into the environments here, so they can have that work themselves here. >> What's your take on the eco-system, obviously here we heard start-ups are very active but there's a glass ceiling if you will because cloud's not yet here in full throttle, capital markets mechanics have not yet formed, but there's funds of funds they're just putting this in place, your assessment of the entrepreneurial landscape here. >> I think it's a small, but growing landscape. I think a key point to making an entrepreneurial company successful, you know I started the company back in 1991, which is many, many, many, many moons ago, but anyway, what I can remember is I worked so hard, seven days a week, the joke was it was nine to five, 9 am to 5 am, you're not here on Saturday don't bother coming on Sunday. So fundamentally there's a thing you got to do, what is it Ben Franklin used to say? It's about 99% perspiration, 1% inspiration. So hard work does help a lot. Not to say that we don't have that culture here, but I think in general-- >> They were hard working here. >> Entrepreneurial is all about making sure you do the work. >> One of my observations, they're hard working here, so I think that's a good sign. >> Absolutely. >> So let's go back and talk about this, your experience, you mentioned 1991, my first start-up was 1997, and so we've seen a few cycles, and as cycles come and go this one seems to be a bigger cycle in the sense of a lot of combining forces going on; you've got cloud scale, the role of data and now A.I. to automate, and honestly traditional stuff is kind of being moved to a whole 'nother operating model. Given that you've seen so many cycles, what have you learned from those cycles that you could apply here if you were an entrepreneur here, you're now going to do some business hopefully here I think with Amazon. And for people in government trying to get out of the way or figure out policy, given your cycle experience, these guys are jumping into a wave that's coming. >> I definitely have a point of view on this. So for years, back in the United States, I would have one customer, I'd go to this customer, and I'd say, hey, this other customer over here, they've done it this way, and this customer would say, I want to do it a different way. And I'm like, well then everybody's going to be out of sync. Well recently the CIA decided to publish a case study that talked about moving to the cloud and why they moved to the cloud. And the reason they published this case study was for something called reciprocity. I think if more governments, if more industries can work together from a standpoint of reciprocity, then we're going to be able to more quickly ascertain the threat, discover what the vulnerability is, and mitigate it. >> What specifically the reciprocity should they be working on? Data transfer, information, what are some of the specifics? >> I think a specific will be the NIST Framework as an example. The NIST Framework is made up of 1100 different controls, which are lots, and lots of different subsets of other controls around the world, whether you're talking about ISO, Gramm-Leach-Bliley, HIPAA, whatever, they're all derivations of a framework which basically is a common lexicon. So for me that's something that is very specific when I think they should consider here. >> So one of the things I wanted to get your thoughts before we end here, is your observations, as you look around here, you're seeing a cultural shift, a woman's on the supreme court in Bahrain, we went to the women's breakfast that Teresa Carlson held yesterday, packed house, they had to kick us out of our table, us guys. >> They did, they did. >> They got to make room for the workshop, great fireside chat with Mary Camarata, head of Analysts and corporate communication for Andy and Teresa, fireside chat, then they had breakouts, we didn't get kicked out, but we were asked to give up the table for the women to do the workshop. This was a robust, packed house. >> Not just packed John, it was also just positive, optimistic, happy, they see a future, they see possibilities, there was a lot of give and take, I didn't see any of the stuff that you read about, and I tell ya, this is my first time in the Middle East, my first time to come to Bahrain, and I'm so happy I've come, I'm so sad it took me almost 55 years to make it happen. >> Yeah, I feel the same way. I feel like there's an opportunity bubbling that's going to be really big and legit, and I love the diversity here, it surprised me. My daughter, 21 years old, asked me, she said, dad can you, what's the women like over there? Because there's a perception around culture, around the role of women. Packed house yesterday for the Women in Tech Breakfast, inspirational speech by Teresa Carlson, great workshop here, you see women forcing function; cultural shift. >> Cultural shift, but also don't believe everything you read in the paper, right John? So we all know that you got to go sometimes to see what things are really like, and I'm really happy I came. It's a bubbling, growing, active, really active, really cool nightlife, really cool skyline very beautiful beaches, it's a great place. >> The ground truth always trumps fake news and innuendo. Of course theCUBE is bringing you all the action, we are here with entrepreneur, visionary, John Wood, CEO of Telos, a big strategic partner with Amazon, part of the cultural sea change with AWS, Amazon Web Services, announcing a region here in Bahrain, in the Middle East. I'm John Furrier your CUBE co-host, you can reach me on twitter @furrier, F-U-R-R-I-E-R, if you want to reach out and ping me on twitter any time. More coverage live here, in Bahrain, in the Middle East after this short break. (futuristic electronic music)

live from New York it's the cube covering AWS summit New York 2018 hot GUI Amazon Web Services and its ecosystem partners hello and welcome back here live cube coverage in New York City for AWS Amazon Web Services summit 2018 I'm John Fourier with Jeff Rick here at the cube our next guest is dr. Matt wood general manager of artificial intelligence with Amazon Web Services keep alumnae been so busy for the past year and been on the cubanía thanks for coming back appreciate you spending the time so promotions keep on going on you got now general manager of the AI group AI operations ai automation machine learning offices a lot of big category of new things developing and a you guys have really taken AI and machine learning to a whole new level it's one of the key value propositions that you guys now have for not just a large enterprise but down to startups and developers so you know congratulations and what's the update oh well the update is this morning in the keynote I was lucky enough to introduce some new capabilities across our platform when it comes to machine learning our mission is that we want to be able to take machine learning and make it available to all developers we joke internally that we just want to we want to make machine learning boring we wanted to make it vanilla it's just it's another tool in the tool chest of any developer and any any data data scientist and we've done that this idea of taking technology that is traditionally only within reached a very very small number of well-funded organizations and making it as broadly distributed as possible we've done that pretty successfully with compute storage and databases and analytics and data warehousing and we want to do the exact same thing for the machine learning and to do that we have to kind of build an entirely new stack and we think of that stack in in three different tiers the bottom tier really for academics and researchers and data scientists we provide a wide range of frameworks open source programming libraries the developers and data scientists use to build neural networks and intelligence they're things like tend to flow and Apache mx9 and by torch and they're really they're very technical you can build you know arbitrarily sophisticated says most she open source to write mostly open source that's right we contribute a lot of our work back to MX net but we also contribute to buy torch and to tend to flow and there's big healthy open source projects growing up around you know all these popular frameworks plus more like chaos and gluon and horror boredom so that's a very very it's a key area for for researchers and academics the next level up we have machine learning platforms this is for developers and data scientists who have data they see in the clout although they want to move to the cloud quickly but they want to be able to use for modeling they want to be able to use it to build custom machine learning models and so here we try and remove as much of the undifferentiated heavy lifting associated with doing that as possible and this is really where sage maker fits in Cersei's maker allows developers to quickly fill train optimize and host their machine learning models and then at the top tier we have a set of AI services which are for application developers that don't want to get into the weeds they just want to get up and running really really quickly and so today we announced four new services really across those their middle tier in that top tier so for Sage maker we're very pleased to introduce a new streaming data protocol which allows you to take data straight from s3 and pump it straight into your algorithm and straight onto the computer infrastructure and what that means is you no longer have to copy data from s3 onto your computer infrastructure in order to be able to start training you just take away that step and just stream it right on there and it's an approach that we use inside sage maker for a lot of our built-in algorithms and it significantly increases the the speed of the algorithm and significantly of course decreases the cost of running the training because you pay by the second so any second you can save off it's a coffin for the customer and they also it helps the machine learn more that's right yeah you can put more data through it absolutely so you're no longer constrained by the amount of disk space you're not even constrained by the amount of memory on the instance you can just pump terabyte after terabyte after terabyte and we actually had another thing like talked about in the keynote this morning a new customer of ours snap who are routinely training on over 100 terabytes of image data using sage maker so you know the ability to be able to pump in lots of data is one of the keys to building successful machine learning applications so we brought that capability to everybody that's using tensorflow now you can just have your tensor flow model bring it to Sage maker do a little bit of wiring click a button and you were just start streaming your data to your tents upload what's the impact of the developer time speed I think it is it is the ability to be able to pump more data it is the decrease in time it takes to start the training but most importantly it decreases the training time all up so you'll see between a 10 and 25 percent decrease in training time some ways you can train more models or you can train more models per in the same unit time or you can just decrease the cost so it's a completely different way of thinking about how to train over large amounts of data we were doing it internally and now we're making it available for everybody through tej matrix that's the first thing the second thing that we're adding is the ability to be able to batch process and stage make them so stage maker used to be great at real-time predictions but there's a lot of use cases where you don't want to just make a one-off prediction you want to predict hundreds or thousands or even millions of things all at once so let's say you've got all of your sales information at the end of the month you want to use that to make a forecast for the next month you don't need to do that in real-time you need to do it once and then place the order and so we added batch transforms to Sage maker so you can pull in all of that data large amounts of data batch process it within a fully automated environment and then spin down the infrastructure and you're done it's a very very simple API anyone that uses a lambda function it's can take advantage of this again just dramatically decreasing the overhead and making it so much easier for everybody to take advantage of machine load and then at the top layer we had new capabilities for our AI services so we announced 12 new language pairs for our translation service and we announced new transcription so capability which allows us to take multi-channel audio such as might be recorded here but more commonly on contact centers just like you have a left channel on the right channel for stereo context centers often record the agent and the customer on the same track and today you can now pass that through our transcribed service long-form speech will split it up into the channels or automatically transcribe it will analyze all the timestamps and create just a single script and from there you can see what was being talked about you can check the topics automatically using comprehend or you can check the compliance did the agents say the words that they have to say for compliance reasons at some point during the conversation that's a material new capability for what's the top surface is being used obviously comprehend transcribe and barri of others you guys have put a lot of stuff out there all kinds of stuff what's the top sellers top use usage as a proxy for uptake you know I think I think we see a ton of we see a ton of adoption across all of these areas but where a lot of the momentum is growing right now is sage maker so if you look at a formula one they just chose Formula One racing they just chose AWS and sage maker as their machine learning platform the National Football League Major League Baseball today announcer they're you know re offering their relationship and their strategic partnership with AWS cream machine learning so all of these groups are using the data which just streams out of these these races all these games yeah and that can be the video or it can be the telemetry of the cars or the telemetry of the players and they're pumping that through Sage maker to drive more engaging experiences for their viewers so guys ok streaming this data is key this is a stage maker quickly this can do video yeah just get it all in all of it well you know we'd love data I would love to follow up on that so the question is is that when will sage maker overtake Aurora as the fastest growing product in history of Amazon because I predicted that reinvent that sage maker would go on err is it looking good right now I mean I sorta still on paper you guys are seeing is growing but see no eager give us an indicator well I mean I don't women breakout revenue per service but even the same excitement I'll say this the same excitement that I see Perseids maker now and the same opportunity and the same momentum it really really reminds me of AWS ten years ago it's the same sort of transformative democratizing approach to which really engages builders and I see the same level of the excitement as levels are super super high as well no super high in general reader pipe out there but I see the same level of enthusiasm and movement and the middle are building with it basically absolutely so what's this toy you have here I know we don't have a lot of time but this isn't you've got a little problem this is the world's first deep learning in April were on wireless video camera we thought it D blends we announced it and launched it at reinvent 2017 and actually hold that but they can hold it up to the camera it's a cute little device we modeled it after wall-e the Pixar movie and it is a HD video camera on the front here and in the base here we have a incredibly powerful custom piece of machine learning hardware so this can process over a billion machine learning operations per second you can take the video in real time you send it to the GPU on board and we'll just start processing the stream in real time so that's kind of interesting but the real value of this and why we designed it was we wanted to try and find a way for developers to get literally hands-on with machine learning so the way that build is a lifelong learners right they they love to learn they have an insatiable appetite for new information and new technologies and the way that they learn that is they experiment they start working and they kind of spin this flywheel where you try something out it works you fiddle with it it stops working you learn a little bit more and you want to go around around around that's been tried and tested for developers for four decades the challenge with machine learning is doing that is still very very difficult you need a label data you need to understand the algorithms it's just it's hard to do but with deep lens you can get up and running in ten minutes so it's connected back to the cloud it's good at about two stage makeup you can deploy a pre-built model down onto the device in ten minutes to do object detection we do some wacky visual effects with neural style transfer we do hot dog and no hot dog detection of course but the real value comes in that you can take any of those models tear them apart so sage maker start fiddling around with them and then immediately deploy them back down onto the camera and every developer on their desk has things that they can detect there are pens and cups and people whatever it is so they can very very quickly spin this flywheel where they're experimenting changing succeeding failing and just going round around a row that's for developers your target audience yes right okay and what are some of the things that have come out of it have you seen any cool yes evolutionary it has been incredibly gratifying and really humbling to see developers that have no machine learning experience take this out of the box and build some really wonderful projects one in really good example is exercise detection so you know when you're doing a workout they build a model which detects the exerciser there and then detects the reps of the weights that you're lifting now we saw skeletal mapping so you could map a person in 3d space using a simple camera we saw security features where you could put this on your door and then it would send you a text message if it didn't recognize who was in front of the door we saw one which was amazing which would read books aloud to kids so you would hold up the book and they would detect the text extract the text send the text to paly and then speak aloud for the kids so there's games as educational tools as little security gizmos one group even trained a dog detection model which detected individual species plug this into an enormous power pack and took it to the local dog park so they could test it out so it's all of this from from a cold start with know machine learning experience you having fun yes absolutely one of the great things about machine learning is you don't just get to work in one area you get to work in you get to work in Formula One and sports and you get to work in healthcare and you get to work in retail and and develop a tool in CTO is gonna love this chief toy officers chief toy officers I love it so I got to ask you so what's new in your world GM of AI audition intelligence what does that mean just quickly explain it for our our audience is that all the software I mean what specifically are you overseeing what's your purview within the realm of AWS yeah that's that's a totally fair question so my purview is I run the products for deep learning machine learning and artificial intelligence really across the AWS machine learning team so I get I have a lot of fingers in a lot of pies I get involved in the new products we're gonna go build out I get involved in helping grow usage of existing products I get it to do a lot of invention it spent a ton of time with customers but overall work with the rest of the team on setting the technical and pronto strategy for machine learning at AWS when what's your top priorities this year adoption uptake new product introductions and you guys don't stop it well we do sync we don't need to keep on introducing more and more things any high ground that you want to take what's what's the vision I didn't the vision is to is genuinely to continue to make it as easy as possible for developers to use Ruggiero my icon overstate the importance or the challenge so we're not at the point where you can just pull down some Python code and figure it out we're not even we don't have a JVM for machine learning where there's no there's no developer tools or debuggers there's very few visualizers so it's still very hard if you kind of think of it in computing terms we're still working in assembly language and you're seen learning so there's this wealth of opportunity ahead of us and the responsibility that I feel very strongly is to be able to continually in crew on the staff to continually bring new capabilities to mortar but well cloud has been disrupting IT operations AI ops with a calling in Silicon Valley and the venture circuit Auto ml as a term has been kicked around Auto automatic machine learning you got to train the machines with something data seems to be it strikes me about this compared to storage or compared to compute or compared to some of the core Amazon foundational products those are just better ways to do something they already existed this is not a better way to do something that are exists this is a way to get the democratization at the start of the process of the application of machine learning and artificial intelligence to a plethora of applications in these cases that is fundamentally yeah different in it just a step up in terms of totally agree the power to the hands of the people it's something which is very far as an area which is very fast moving and very fast growing but what's funny is it totally builds on top of the cloud and you really can't do machine learning in any meaningful production way unless you have a way that is cheap and easy to collect large amounts of data in a way which allows you to pull down high-performance computation at any scale that you need it and so through the cloud we've actually laid the foundations for machine learning going forwards and other things too coming oh yes that's a search as you guys announced the cloud highlights the power yet that it brings to these new capabilities solutely yeah and we get to build on them at AWS and at Amazon just like our customers do so osage make the runs on ec2 we wouldn't we won't be able to do sage maker without ec2 and you know in the fullness of time we see that you know the usage of machine learning could be as big if not bigger than the whole of the rest of AWS combined that's our aspiration dr. Matt would I wish we had more time to Chad loved shopping with you I'd love to do a whole nother segment on what you're doing with customers I know you guys are great customer focus as Andy always mentions when on the cube you guys listen to customers want to hear that maybe a reinvent will circle back sounds good congratulations on your success great to see you he showed it thanks off dr. Matt would here in the cube was dreaming all this data out to the Amazon Cloud is whether they be hosts all of our stuff of course it's the cube bringing you live action here in New York City for cube coverage of AWS summit 2018 in Manhattan we'll be back with more after this short break

>> Live from Washington DC, it's theCUBE. Covering AWS Public Sector Summit 2018. Brought to you by Amazon Web Services and it's ecosystem partners. >> Hey, welcome back everyone. This is theCUBE's exclusive coverage live in Washington DC at Amazon Web Services AWS Public Sector Summit. I mean, it's so jam-packed you can't even move. This is like the re:Invent for Public Sector even though it's a summit for Amazon Web Services. I'm here with Dave Vellante, my co-host. Our next guest is John Wood, Chairman and CEO of Telos, and Rick Tracy, Chief Security Officer and the co-inventor of Xacta, it's hot technology. John, great to see you, welcome to theCUBE. >> Thanks guys. >> Thanks for having us. >> I love to get the brain trust here, John you're, like, probably one of the most experienced cyber security gurus in the DC area still standing. (laughing) As we said last time on theCUBE. >> Always, always. >> Okay. (laughing) And you've got some patents here, with some core technology, so first of all, I want to, before we get into some of the cool features of the products, talk about the dynamic of public sector, because Amazon has these summits, and they're kind of like a recycled re:Invent. Small scale, still packed. Talk about what Public Sector Summit is, because this is a completely different ballgame in this world. >> Sure, it's a perfect age for the cloud, and what this summit does, is it provides a great venue for people to come, learn about what works, get best practices, find use cases and just see what the ecosystem's all about in terms of how to make it work with the cloud. >> Rick, so what's your take? >> Well, if there's any doubt about it, what, is it double the size of last year? I think there were 7,000 people here last year and Teresa said today 14,500. So, yeah, I mean, it suits us perfectly because this is our sweet spot. >> So, Dave and I are always amazed by Amazon in general, the slew of announcements, Teresa Carlson picking the reins up where Andy Jassy does that Amazon re:Invent which is just tons of content, so many new announcements. What's your guys take on the hot news for you guys, because you guys are a major sponsor and you're in the ecosystem, you've been doing a lot of business with Amazon. >> Sure. >> What's going on in the business? What's happening with Telos? Why is it so booming right now for you guys? >> Well, I think people realize that there is a way to use automation where security can help drive cloud adoption. So, Rick and I co-authored an article back in 2011 that talked about why the cloud was more secure and it went over kind of like a lead ballon. And then back in 2014 the agency made the decision, the CIA made the decision, arguably the most security conscious organization in the world, to go to the cloud. And so that was a big, big, big, deal. But what we do is we help drive the security automation and orchestration stuff so you can reduce the time it takes to get what's called your authority to operate. And so I think that's a big deal now. The use of automation is being used to enhance the mission, so that the mission owners can get to their mission using the cloud, much more quickly. >> And we heard from the most powerful sentence in the keynote this morning was, "The cloud on it's weakest day is more secure than Client Service Solutions." This is a practitioner saying that, a leader of an agency saying that, not Amazon or not Telos. >> Absolutely. >> And it's because of that automation, right? I mean, that's really a key factor. >> It's because of the automation. It's also because the cloud providers are making sure that they lock down their physical infrastructure. Guards, gates, guns. All of the physical infrastructure and the virtual infrastructure, they do a really good job of that. If you think about it, the US government, unfortunately, 80% of their spend is around maintaining old systems. Well, the cloud providers are keeping modern. Those old systems have a lot of weaknesses from a standpoint of cyber security flaws. So, with a modern technology like the cloud, there's a lot more you can do around automation to lock down much more quickly. >> And the standardization that you get with a cloud makes it's easier as well, because there's not so many variations of things that you have to figure out how to protect. So, the standardized services that everything's built on really helps. >> Yeah, and people are adopting cloud in kind of different ways, which makes it harder, too. But you get the benefits of scale and speed, certainly. But I got to just pick up on some big news that's happened just last night and today. Microsoft Azure suffered an 11 hour downtime across Europe. 11 hours Azure's down, Microsoft Azure. This is a huge concern. Downtime, security, these are issues, I mean, this is just like, so, what's going on with this? >> Well, the truth of the matter is, if you think about where Amazon is today, Amazon is light years ahead of the rest of the cloud guys. The reason for that is they made the decision early on to take the risk around cloud. As a result of that, they have so many lessons learned that are beyond all of the other cloud providers, that that wouldn't happen to Amazon today, because they'll be able to back up, replication and duplication if they have, and their environments. >> How big do you think that lead is? You know, there's a lot of debate in the industry that other guys are catching up. The other side of the coin is, no, actually the flywheel effect is a lot like Secretariat in the stretch run of the Belmont, you were talking about racing before. What's your sense of that lead, even subjectively. >> I think it's between 5 and 10 years. There was a, it was crickets in this world, in the public sector world for cloud up until, literally, the agency decided to adopt. So the CIA made that decision, that was, sort of, the shot heard around the world as it relates to cloud adoption. Not just for public sector but for commercial as well, 'cause if you look at Amazon's ramp up, right after that decision was made, their ramp up has been amazing. >> That was a watershed event, for sure. >> It was, and it was very well documented, I mean, I read the judges ruling on that when IBM tried to stop them and the judge eviscerated IBM. And of course IBM had no cloud at the time, they had to go out and spend two billion dollars on software. John has lots of opinions on that, but okay, so that leaves-- >> I'm on the right side of history on that call. >> I think you are, it was a pretty good call. What about, what should be practitioners be thinking about? You talked about the standardization. Where should they be focused? Is it on response, is it on analytics, is it on training? What should it be? >> Well, from our perspective it is, a lot of the focus is on analytics, right? So, a lot of data that we've helped our customers collect over time for this ATO process that John previously mentioned, our goal with IO, Xacta IO, is to help organizations leverage that data to do more through analytics, so there's this dashboard with ad hoc reporting and analytic capability that's going to allow them to blend asset data with risk-to-threat data, with other sorts of data that they're collecting for ATO, specifically for the ATO process, that they can use now for more robust cyber risk management. So, for me, analytics is huge moving forward. >> And that's a prioritization tool so they can focus on the things that matter, or maybe double-click on that? >> It could be, it could be a prioritization tool, but it could also be a tool that you use to anticipate what might happen, right? So, some analytics will help you determine this asset is vulnerable for these variety of reasons, therefore it has to go to the top of the sack for remediation. But also, using that data over time might help you understand that this plus this plus this is an indication that this bad thing is going to happen. And so, analytics, I think, falls into both categories. Probably it's more the forecasting and predictive is something that's going to come later but as you unmask more data and understand how to apply rules to that data, it will naturally come. So, Rick and I have worked together for many, many years and, over a quarter of a century, so the way I would say it is like this. Xacta 360 helps you to accelerate your authority to operate, but that's a point in time. The holy grail for us as security practitioners is all around continuous monitoring of your underlying risk. So, the data analytics that he's talking about, is where we come about and looking at Xacta IO. So, Xacta IO helps fulfill that mission of continuous compliance, which means that the ATO is no longer just relevant at that moment in time because we can do continuous monitoring now at scale, in hybrid environments, in the cloud, on prem. 'Cause our clients are huge, so they're going to be a combination of environments that they're sitting in, and they need to understand their underlying risk posture. They need to have, they're going to have all kinds of scanners, so we don't really care, we can ingest any kind of scanner that you have with Exact IO. As a result of that, the security professional can spend their time on the analysis and not the pedestrian stuff that's just kind of wasting time, like documentation and all that stuff. >> Yeah, for us, data's a means to an end, right? It's either to get an ATO or to help you understand where you need to be focusing your resources to remediate issues. So, for us, leveraging the data that's produced by many companies that are at this show. Their data is a means to help us get our job done. >> Were you able to have, one follow up, if I may, were you able to have an impact, to me, even, again, subjectively, on that number, whatever that number is, that we get infiltrated, the customer gets infiltrated, it's 300 days before they even realize it. Are you seeing an impact on that as a result of analytics, or is it too early days? >> I would say it's still early. But it's reasonable to expect that there will be benefits in terms of faster detection. And maybe it's not even detection at some point, hopefully, it's anticipating so that you're not detecting something bad already happened, it's avoiding it before it happens. >> Yeah, and let me say it this way, too. You know, if you listen to John Edwards, the CIO from the CIA, he talks about how the reason he loves the cloud is because it used to take the agency about a year to provision a server, now it's a few minutes, right? Well that's great, but if you can't get your authority to operate, 'cause that can take another 18 months, you're not going to get the benefit of the cloud, right? So what we do, is we help accelerate how fast you can get to that ATO so that guys like the agency and anybody else that wants to use the cloud can use it much more quickly, right? >> Yeah, and the continuous integration and all that monitoring is great for security but I've got to ask you a question. Analytics are super important, we all know data analysis now is in the center of the value proposition across the board, horizontally. Not just data warehousing, analytics that are used as instrumentation and variables into critical things like security. So, with that being said, if you believe that, the question is, how does that shape the architecture, if I'm in an agency or I'm a customer, I want to build a cloud architecture that's going to scale and do all those things, be up, not go down, and have security. How does the architecture change with the cloud formula for the decision maker? Because right now they're like, "Oh, should I do multi-cloud, should I just Amazon" So, the data is a critical architectural decision point. How do you guys see that shaping, what's your advice to practitioners around designing the cloud architecture for data in mind. Just use Amazon? (laughs) >> Well, yes. (laughs) Just use Amazon. I mean, all the tools that you need exist here, right, and so-- >> If all the tools you need in the cloud exist here. >> Alright, so rephrase another way. >> But John, the issue is you're not going to have all your stuff in the cloud if you're the air force or if you're the army, because you have 75 years of data that you got to push in. So over the next 10 years there's going to be this "hybrid" environment where you'll have some stuff in the cloud, some stuff in a hybrid world, some stuff on prem, right? >> How I secured that, so that's a great point. So, data's everywhere, so that means you're going to need to collect it and then measure certain things. What's the best way to secure it and then is that where Xacta fits in? I'm trying to put that together if I'm going to design my architecture and then go to procurement, whether it's on premise or multi-cloud. >> Well, there are lots of security products that people use to secure, whether you're on prem or whether you're in the cloud and our platform leverages that information to determine whether things are secure enough. So there's a distinction between cyber risk management and actually securing a database, right? So, there's so many granular point products that exist for different points along the security chain, lifecycle chain, if you will, that our objective is to ingest as much of that information and purpose it in a way that allows someone to understand whether they're actually secure or not. And so it's understanding your security posture, transforming that security information to risk so that you can prioritize, as you were talking about before. >> You're taking a platform mentality as opposed to a point product. >> We're taking an enterprise view of risk. So, the enterprise is, remember, it's on prem, and hybrid and cloud. If all your stuff is in the cloud, Amazon has the answer for you. None of our customers are in that situation. If you're a start up, Amazon's the way to go, period. But all of our customers have legacy. As a result of that it's an enterprise view of risk. That's why companies like Telos partner so well with Amazon because they're all about being close to the customer, they're all about using automation. We are as well. >> Alright, talk about the news you guys have, Xacta IO, you're the co-inventor of it, Jack. Talk about this product. What's the keys, what does it do, where's it applied to, you mentioned a little bit of getting past the authority time point there. What's the product about? The product is about ingesting massive amounts of information to facilitate the ATO process, one, but managing cyber risk more generically because not everybody has an ATO requirement. So, you asked a few seconds ago about, so you're taking a platform approach. Yes, we're blending three separate products that we currently have, taking that functionality and putting it on a very, very, robust platform that can exist on prem, it can exist in the cloud. To enable organizations to manage their cyber risk and if they choose, or they have a requirement, to deal with things like FedRAMP and risk management framework and cyber security framework and iso certification and things of that nature. The point is, not everyone has an ATO requirement but everyone has a need to manage their risk posture. So we're using our ability to ingest lots and lots of data from lots and lots of different sources. We're organizing that data in ways that allow an organization to understand compliance and/or risk and/or security, and visualize all that through some dashboard with ad hoc reporting that let's them blend that data across each other to get better insights about risk posture. >> And to visualize it in a way that makes sense to the user. >> Yes, so, if you're the CEO, you're going to want to see it a certain way. If you're the IT manager, you're going to want to see it a certain way. If you're a risk assessor, you're going to want to see it a different way. So that's kind of what we're talking about. >> I got to ask you one question, I know we got to go, but, a hardcore security practitioner once said to me that hardcore security practitioners, like you guys, when they were kids they used to dream about saving the world. So, I want to know, who's your favorite superhero? >> Superman. >> Superman? >> Spiderman. >> Alright, awesome. (laughing) >> That was a basic question for you guys. >> Thank you very much >> Yeah, that's the hardest question, see they're fast, they know. Star Trek or Star Wars? (laughing) >> Depends on the generation. >> We won't go there. theCUBE have 15 more minutes today. Okay, final question, what's this going to do for your business now you have new, opened up new windows with the new product integration. How's that going to change Telos, what does it do for you guys from a capabilities standpoint? >> Well, the big thing I'd suggest your listeners and your watchers to consider is, there's a new case study that just came out, it's published jointly by the CIA, Amazon and Telos, talking about why working together is really, really, really groundbreaking in terms of this movement to the cloud. 'Cause your public sector listeners and viewers are going to want to know about that because this ATO thing is really a problem. So this addresses a massive issue inside of the public sector. >> And final question, while you're here, just to get your thoughts, obviously there's a big change of the guard, if you will, from old guard to new guard, that's an Amazon term Andy Jassy uses. Also, we all saw the DOD deal, JEDI's right there on the table, a lot of people jockeying, kind of old school policy, lobbying, sales is changing. How is the landscape, from a vendor-supplies to the agencies changed and/or changing with this notion of how things were done in the past and the new school? So, three points, legislatively there's top cover, they understand the need to modernize, which is great. The executive branch understands the need to modernize through the IT modernization act as well as the cyber security executive order. And then lastly, there are use cases now that can show the way forward. Here's the problem. The IT infrastructure out there, the IT guys out there that do business in the government, many of them are not paid to be efficient, they're paid cost plus, they're paid time and material, that's no way to modernize. So, fundamentally, I think our customers understand that and they're going to revolutionize the move forward. >> And the rules are changing big time. Sole source, multi-source, I mean, Amazon's on record, I've got Teresa on record saying, "Look, if we don't want a sole source requirement, let everyone bid fairly." Let's see who wins. Who can bring a secret cloud to the table? No one else has that. >> In terms of past performance and customer use cases they're pretty much in the head, for sure. >> Great, Amazon kicking butt here, Telos, congratulations for a great event, thanks for coming on. >> Thanks a lot guys. >> I appreciate it. >> Alright, CUBE coverage here in DC, this is theCUBE, I'm John Furrier with Dave Vellante. Stay with us, we have more great interviews stacked up all day and all day tomorrow. Actually you have half day tomorrow until two 'o clock Eastern. Stay with us for more, we'll be right back. (upbeat music)

>> Announcer: Live from the Moscone Center it's theCUBE, covering AWS Summit San Francisco 2018. Brought to you by Amazon Web Services. >> Hello everyone, welcome to theCUBE here in San Francisco at Moscone West, theCUBE's exclusive coverage of Amazon Web Services Summit 2018. It's the first of their kickoff of their little satellite events, really about developers and training and educating people on Amazon Web Services products and services. Again theCUBE covers re:Invent, that's their big show, This is more of a, less of a sales and marketing but more of a really get down and dirty with the developers and practitioners. I'm John Furrier, with my cohost this week Stu Miniman all day today, wall to wall coverage. Stu, the keynotes just kicked off, Andy Jassy is not here, notable. Werner Vogels does all the summits so he's always been the headline. Last year Andy Jassy kind of did the keynote, fireside chat, we had that up on our YouTube channel, SiliconANGLE theCUBE, but here the story is all about SageMaker and the continued dominance of Amazon Web Services, and then again as we were speculating at re:Invent, and we've been saying on theCUBE, the maturization of Amazon Web Services is clear. Everyone knows the numbers, they're breaking out the reporting, they clearly got competitive forces for the first time in AWS's history, they have some serious competition upping their game. Microsoft nipping at their heels, Google putting out some open source tech, Oracle trying to throw FUD into the fire and say, change the rules and kind of keep the rules on their terms, so the competitive pressure. But at the end of the day there's a whole new era of modern software development, modern business applications and we're seeing it with things like cloud expansion, on-premise consolidation, hybrid-cloud, multi-cloud, decentralized infrastructure, blockchain AI, these are the themes, this is what developers want, this is what businesses are doing, let's analyze and discuss the keynotes. What's your thoughts? >> Yeah, so John, I mean, first of all, we watched the rolling thunder that is AWS just rolling through the entire industry, and now rolling all over the globe. So the AWS Summit, I think they actually had an idea about Summit in Singapore like, last night, and we're going to be covering a few of them. I was last year at the AWS New York City Summit, and I tell you, that New York City show alone was one of the best shows I went to all year. The amount of people, the excitement, what really differentiates as you said, the big re:Invent versus the summit, first of all, the summit, they tend to be a local audience, it's free for basically everybody to come in. So numbers are great, you know, we're in San Francisco, they going to 10, 15 thousand people here probably. Google Cloud Next was here last year in February and it feels almost the same amount of people here for a regional Amazon show. So the numbers are wow, the announcements, every day Amazon's running an announcement, so Doctor Werner Vogels, Doctor Matt Wood, get up stage, go through some of the usual we're dominating every industry and every service and everything there, but when you piece apart there's like, ooh, there's real announcements that are coming, things that jumped out, we talked about machine learning, Matt Wood talked about SageMaker is really growing super fast, people that I talked to that have been using it are loving it. They came out with SageMaker local, which means that I can develop it on my laptop and do it with that cool, you take ML with that cool, what was it, that deep lens, that they've got. It's how do I get these environments? Amazon isn't just about infrastructure cloud anymore, They've gone to paths, they're pushing to edge, they're doing all of these things. They had a whole ton of announcements, when they were already past the time that the keynotes were going to be done, Oh, you thought we're done, well security, security, security and secrets manager, firewall manager, there's so many services. The theme I've been looking at the past couple years, how do we keep up with all of this, even internally? You talk to Amazon people, they don't know everything that everyone's doing, because it's all those two pizza teams and how they're growing. >> And they always have to get all their sound bites in because they don't have a lot of time to get all that packed into one powerful punch. Just on a quick side note for the folks that watching knows theCUBE, we've been covering Amazon really since the beginning, since the re:Invent started, you know we've been covering data center infrastructure and big data, Hadoop and now beyond. You're starting to see coverage around blockchain and cryptocurrency. So again, we are expanding our coverage of the AWS ecosystem and cloud to include most of the major regional shows of AWS Summit, continuing to go deep into the AWS re:Invent and the community, we are also initiating coverage heavily on Google, Google Cloud Next, we'll be at their show and soon to be at Microsoft show, that's still to be determined with Microsoft that they will let us in, we're working on that, we think that's going to be good, but we'll be nailing and doubling down on the cloud coverage. So Stu, with that as a backdrop, people know we've been deep with Amazon, I've been called an Amazon fanboy many times, but the numbers are clear. I'm a Google fanboy, by the way, too, I love Google stuff. Microsoft I got to learn more about, obviously they have bundling and Office so they're a legacy player, Oracle a legacy player, so you got two legacy players, you got Amazon and Google, I would put them in two different categories, but then Alibaba in China trying to dip in as you got those, the real kind of cloud native companies, Google and Amazon on one end, you get the legacy players with Microsoft and Oracle and IBM on the other. So you have this really highly competitive environment. We're seeing for the first, or second time, Andy Jassy did it at re:Invent, but Werner Vogels put up the competitive slide. He said "This is what we're doing." And he showed the number of services that Amazon offers, vis a vis the competition, and he didn't actually call out the vendors but we kind of know, I put on my Twitter feed, you can see his number one, the second one's Microsoft. Google they put in the Google colors, that's obviously Google, and red is Oracle. Amazon is clearly dominating on the number of services available across the cloud. So when we've been squinting through the numbers on who's leading who, you've really got look at two perspectives. The broad range of available services and the number of customers using those services versus point solutions that might be one instance of the cloud. This is a new architecture, it's not the old waterfall model it's not the old six months to provision into it, mentioned that. This is like a highly competitive environment. So Stu I've got to ask you, how do you squint through that and look at the competition that Amazon has, obviously the numbers aren't great. But how should customers look at the competition, how are you looking at it, how is our team evaluating the competition? >> Well first of all John, it is not a zero sum game and it is very nuanced and complicated. And for most customers it's not a solution, it's many solutions and it's something that Amazon doesn't love, is that you talk about things like multi-cloud and they would say "Well, we have the "best service everywhere and we're the cheapest everywhere "and everyone's all in on us," well, when you get down to it, You know, I hate I have to defend a little bit, you say Microsoft and Oracle, legacy. Microsoft has business productivity applications. They are the leader in the space when you talk about... >> Yeah they're the leader in legacy applications. >> But you know, you start with the Microsoft Office Suite, and say what you will, it's still dominant out there, it's there. Microsoft gave enterprises the green light to go to SaaS, and they really helped drive that. >> John: Whoah, whoah, that's a direction. >> Yeah. >> John: But they're a legacy vendor, what you just said is that they're legacy. >> But Azure is doing quite well... >> John: Oracle's going to the cloud, are they legacy? >> Oracle's got a phenomenal team, have been building some really interesting things in cloud, but obviously no doubt about it, Amazon's leading, but when you talk to users and you say, okay, there's lots of reasons they might be using Azure for various pieces. Everybody is using AWS, except for those people, John, and you used the example, the ones that compete against Amazon and obviously that's a concern. Because today Amazon is competing against more and more companies, so that's a little bit... >> I'm not, I'm not down on the legacy, what I'm trying to point out is that IBM was clear about this, they were up front about it at IBM Think we were just at, which is, they're saying the legacy has to evolve. Doesn't mean legacy's going to die, I mean Microsoft clearly is going to the cloud, their stock's at like 90 plus, it was at 26 a few years ago so, Satya Nadella taking over from Ballmer. Clearly that's the direction Microsoft has to go, and they're doing it. Now, they're a legacy company doing cloud. Oracle, legacy company, doing cloud. IBM, legacy company, doing cloud. So that's necessarily a bad thing, I'm just saying vis a vis the competition I would put Google and I would put Amazon in a new, modern, non-legacy kind of world. >> Yeah, well okay, and you find one of the lines I love that Werner Vogels was talking about is we talked about AWS customers are builders, and he said builders have a bias for action. And I love that, because if you talk to companies, and you know, we've talked a lot on theCUBE, digital transformation, much more than a buzzword, John, I've not talked to anybody, that they're like, "Oh, kind of hogwash, you know, I'm just going to "keep doing the same thing I've been doing "for the last 10 years and I'll keep being successful." We understand that change needs to happen and it's not easy. So if you've got data scientists, if you've got, you know, understanding data, if you're embracing developers, Amazon has affinity with these groups, and that's why they build and they listen to their customers and there's new services and another thing, Amazon gets up on stage and it's not so much "Oh, here's the vision of where we're going," it's here's the stuff that we GAed that we already had you in the beta. Here's the new things, and they might give you a couple things in preview, but they iterate and move so fast. >> Yeah, checking the boxes on the product side, but... >> But much more than checking the boxes, they listen to their customers. >> Well, well of course, that's what they say, but we know they're doing that, but the thing, I mean checking the boxes, they're on the cadence of the Amazon releases, which we've talked about that. But fundamentally, Stu, I think the two big things and this is what I want to get your reaction to is, what's going on with Amazon, the consistent thing is that they lay out the preferred architecture of the modern stack and it's not the same architecture as the old way. Two, the SageMaker and machine learning and where AI is going, if you look at what Matt Wood discussed, SageMaker, my prediction, will surpass Aurora as the number one shipping service for Amazon in the history of their product. That thing is on a torrent pace, and the way they lay it out architecturally, they're not head figment, they're saying this is what we're doing, they lay out the architecture, and they're putting in the machine learning. So, to me, I love that. Now, all the other stuff that they're doing it's just the cadence of Amazon. More announcements, more services, general availability, they're moving the ball down the field, as Jeff Frick would say, matriculating the ball down the field. So your reaction to the modern architecture, and the SageMaker, machine learning for all developers. >> Yeah, absolutely, Amazon is setting the bar for how we think about architecture today. They're leaders in serverless, an area I've been hot on the last year or so. You know, Werner was up on stage talking about Ai Roba who I got the chance to interview last year. So absolutely they are the bar that everything is measured on in this industry. And if they're not, have the leading product in everything, they are close second and they have so many services that there is just this flywheel of not only services and customers and the new flywheel we talked about on theCUBE two years ago with Andy Jassy is data. John, I want to throw back at you a question. Amazon released something called AWS Secrets Manager. Do we trust Amazon with our secrets? Is the government coming after Amazon now? There's some of these macroeconomic things happening, you're hearing everything in Silicon Valley, what are you hearing lately? >> Well what I'm hearing is one, people are really kind of not happy with Amazon's success because it, you know, market share at the expense of other old guard or legacy vendors, and so that's taking it's toll. Oracle to me is the biggest company that's impacted most by Amazon. It's clear that a war of words is happening between Ellison and Jassy. Two, there's a big policy battle going on in D.C. I think Bloomberg broke a story that Oracle is trying to incite Trump to tackle Amazon proper, but and then Amazon is affected, Amazon Web Services is affected, because they have all that Department of Defense and the CIA deal, so you're seeing Amazon, Amazon Web Services for the first time dealing with competitive pressures that's old school tactics, which is policy formulation, and as they say in the policy game in D.C., Stu, the battle is won before it's even fought. This is new territory for Amazon, they really got to get their act together, and if I had to tell Andy Jassy any advice would be like look it, you got to start thinking chess game at this point, and understand that the competition is not going to roll over. We've said this on theCUBE many times. Oracle's not going to roll over, IBM's not going to roll over. Now, other companies, like Cloud Air who's down thirty percent on earnings, they're going to have to do a deal with Amazon, just like VMware did. So I think you have these big cloud players sucking the oxygen out of the room, and there are impacts. The growing startups who are pre-public companies or are public companies have to either join the ecosystem or find another partner. The major cloud players are going to fight tooth and nail for market share as stakes on the table is the future internet, it's basically everything in cloud that's going to extend to democratization around decentralization, the future of money, sovereignty, government, digital nations, internet of things, these are, it's a high stakes chess game and Amazon is now on new territory, and I think that to me is the big walkaway is that no one is going to let them take this uncontested. >> Yeah, John, look at this crowd. The expo hall is filling up, customers are still excited. The buzz that I hear is that Amazon, they listen, they still move really fast when they need to make changes, I remember a year ago when we were here for the Google event I was talking, it's like, ah, Google's got such better pricing for the small business and everything like that. A week later Amazon changed all of their pricing, billing by the microsecond, I talked back to some of my sources and they're like, "Yeah Amazon listened and totally flipped the game." >> Yeah, well Jassy, he... >> There are sustainable advantages, so difficult in the fast pace of change but Amazon is doing better than what Oracle used to do in the past, they were kind of like, we'd get the lead and kind of want the competition intact, with them with the old sailing analogy, Amazon doesn't worry about the competition, they listen to their customers, they're moving forward. >> Well, I think that they do, they don't admit it but they have to watch, they've got to look in their rear view mirror a little bit, but Stu, to end out the analysis I would say the following, my observation is this: Andy Jassy and his team are very customer-centric. He sat on theCUBE many times, so as an organization they're very process oriented, they'll listen to customers. But if you look at what's happening in the world today, is that in the old way, the way that Intuit laid it out that took months to provision the software, the old technology business model or venture architecture for a business was make a sound technology decision, and all the chits will fall in the right places. This is completely opposite now, if you look at what's going on with cloud and blockchain and cryptocurrency and decentralized applications, it's the business model that matters, the technology switching costs are now fungible with Lambda you're starting to see these sets of services that can be spun up in parallel. So the scale and flexibility of the platform, and Werner Vogels pointed this out on the keynote, this is fundamental. The decisions that are fatal to a company is the business model and the business logic, this is where the action is. That means it's not just a developer game any more, it's the CTO, it's the data scientists, and Werner Vogels laid that out and I think that to me was my big walkaway from today's keynote is that Amazon recognizes that it's not just about developers, make developers more productive, but bring all those people together to do the right for the business model, the business logic and applications. >> Yeah, John, we're always looking for what are those things that are slow down the company and the roadblocks, one thing Amazon I think did a great job they're out in front of GDPR, that are super hot topic out there, and they just say categorically, "We're ready for GDPR on all of our services," so full steam ahead, don't stop your spending, keep growing. >> Couldn't be a better time to be a theCUBE host to analyze and talk about the competition. Let's see how Amazon handles the competition, do they just keep pedal to the metal, or do they address it and play those 3D chess games? TheCUBE here in San Francisco for live coverage of AWS Summit 2018 in San Francisco, more coverage after this short break. We'll be right back. (techno music)

(dramatic music) >> Narrator: Live from Washington D.C., it's cube conversations with John Furrier. >> Hello everyone, welcome to this special cube conversation, I'm John Furrier, the host of The Cube, co-founder of SiliconANGLE media Inc. We are here in the Washington D.C. Beltway area. We're actually at Amazon web services' public sector headquarters in Arlington, Virginia. My next guest is John Wood, he's the CEO and chairman of the board at Telos, a big provider of some of the big contracts, certainly with Amazon CIA, among others, welcome. >> Thank you very much. >> Thanks for joining me. >> I'm glad to be here. >> So, you guys have been pretty instrumental and we were talking to Teresa Carlson earlier, with an exclusive interview with her, and we talked about the shot heard around the Cloud. That was the CIA, Amazon win, four years ago. >> Yes. >> Kind of infiltrated the government area. It's almost a gestation period and now you got DOD action, a ton of other opportunities, but it really is an architectural mindset changeover from the old way. >> Yes You're involved in this, with Telos. What's your take, how are you guys involved, what's going on? >> Yeah, so it was groundbreaking, when the CIA made the determination that they were going to move to the Cloud, for sure. It kind of made everybody stand up and take notice, if the most security conscience organization in the world was considering it, why aren't I? And here we are, four years later, so where is the CIA now? Well now, the CIA is able to provision a server in a couple minutes, whereas the past, it used to take them almost a year. Now, with the use of automation tools like we have with Telos and the Xacta suite, the CIA is able to get their authority to operate in less than a week, when it used to take 18 months. So, I basically think what's happening is, the Cloud is providing an access point to IT modernization and the agency is showing that there is a blueprint that the rest of the government can also follow if they want to. >> One of the things we're involved in a lot of Blockchain covers, as well as kind of kicking the tires on Blockchain. You're in the middle of a Cloud gain with identity. Identity is the secret to having good scalable systems, because when you have good identity, good things happen. In Blockchain, some people say a theory about those. In IT, it's what identity you're going to use. How does the authority to operate challenge, you mentioned, become so important, because you're talking about massive amounts of time, I mean time savings. >> Wood: Yeah, so-- >> Just tease out the nuances of why it's so important to have that identity solution. >> So, in the past, there was no common language within which our cyber security professionals could engage with each other. Now, with the signing of the President's executive order on cyber security, the White House really is mandating the adoption if the NIST framework. What's relevant there is that on the one hand it provides you with a common language, but on the other hand, it's 11 hundred controls. So, as a result, automation is going to be key, to making sure that people can work with each other and making sure that, actually, the adoption actually takes off. >> They're safe, they know the trusted party. Is trust a big part of this and how does that--? >> I think what's happening, because the intelligence community has been working so closely together, and when I say the intelligence community, it's not just the traditional CIA, NSA, NRO, et cetera, it's also the military component of the intelligence community. So, you've got almost 38 assessors that are assessing C2S and SC2S. You know, the secret, if you will, Cloud, and the top secret Cloud, and those assessors all have been working in the same community under this framework and I think that has given them the confidence that the data is protected and as a result, they're heading much closer to reciprocity than ever before. >> There's been observations certainly on the Cube, we've said this many times with the past few years in tracking IT over the years, IT transformation, digital transformation, whatever you want to call it, buzz word. The reality is you had some progressives that would move faster and kick the tires, certainly financial services, in some areas you see that. Really, no problem. Then you had the folks who have just been consolidated down, didn't have a lot of budget and were lagging, waiting to adopt. Now there's no excuses, with cyber security, top of mind, with hacking, malware, ransomware, cyber warfare from nation states, sponsored states, an open source it's out of control. >> It is. >> So the security equations is forcing IT to move. The action has to be taken. What are you guys seeing in this area, because this is a big story and it's really putting a fire under everyone to move. >> And it's long over due. I co-wrote and article with our chief security officer in 2011, talking about why the Cloud was the way to go for federal, state, local, and education customers and at the end of the day, I think what's happening from a top cover perspective, the legislative community understands that. Obviously the Executive branch understands that, and now with editions like C2S the rest of the environment, the rest of the government can see what's possible. So, I believe the leadership within the government is ready for this change. They're seeing the benefit as it relates to C2S and SC2S and ultimately, the key is, the guys who run the contracts themselves, you got to make sure that those guys want that, to embrace that change too. >> Furrier: Yeah, so you have the-- >> And right now, 80, if you look across the government, 80% IT span is going back into maintenance. If you look at all my commercial customers, it's somewhere between 20 and 25%. What does that mean? It basically means that the government has a lot of legacy systems, which means that there's a lot of threats, and, which means there's a real cyber security problem. I believe fundamentally that by moving work loads to the Cloud, you'll be eliminating a lot of those cyber security problems. >> Yeah, it just means security is going to be the driver. The other thing I wanted to bring up, especially here in D.C., in public sector, is transparency. Now everyone can see everything. We're in a data-driven world, you can't hide either. The light is on, it's right there on the table. No more hiding. How has transparency been impacted in the procurement process, in the sales motions, the overall engagements with gov and public sector customers? >> I think, truth be told, there have been a lot of ideas that were sort of short-term and not really thoughtful, but the good news, as I said, is that the policy makers are really thinking and considering, trying to figure out how to make changes. Take for example, LPTA, low price technically acceptable. When I went to the congress and talked to both the House and the Senate side, and talked about how if I have one customer whose gotten hacked and the other customer has the same hack, but one happens to be a government customer and one's a commercial customer, the resources that we have are really trained, highly skilled, highly sought-after resources. Well, my commercial customers are willing to pay three to four hundred percent more than my government customers are. So when you have scarce resources, where are you going to apply them? You're going to apply them where the people are who are going to pay you. So my point to the Congress was simply to say, hey man, you get what you pay for. So ultimately, the good news is that, both on the House and the Senate side, that they elimanted LTPA, as it relates to cyber security, goods and services. So I believe, again, that there's a lot of, not just transparency happening, but there's a lot of people realizing that there are things that we can do. Procurement is kind of the last frontier for me. I have seen recently, I saw one of our government customers, where we were subcontracted, they went with something called an OTA, which stands for an other transaction agreement. Big problem in the government these days is everybody protest everything and there's really no downside to the protesting. With an OTA it's not protest-able. So I am seeing our government customers beginning to think about other means of actually doing things like procurement, and so that you can actually acquire. >> Are they going to have instant replay? (laughter) It sounds like the NFL, that call's not reversible. I mean, this is kind of, we're getting into all these rules and regulations where you've got protest, it seems that policy injection is not healthy at some level, because that point about what cost more on the commercial side, because of demand there, they understand the consequences and resource availability. To the government you just eliminated a policy that wasn't really helping. >> Right. >> So policy is a real consideration in here. >> I think so. Again though, it's a different environment than it was five or six years ago and I do think that there are some real positive things that are happening. I agree with you that there's a ground-swell of support behind the Cloud and certainly, players like us see the benefit associated with that shared security model. >> One of the things we've been observing and tracking on Sillaconangle and the Cube is this notion of public-private collaberation. Sharing data is a huge deal. Certainly, in Cyber people realize that data is valuable. Certainly, at Scale, you see patterns you might not see, customers on workloads, here and there, need to be identified. You're not sharing the data you don't know. So data sharing is a big deal, but also, collaborations between the private and public sector. Can you comment on what's going on there, because we're seeing some movement where, you're seeing some security agencies saying, "We'll share some stuff." >> Yeah. >> Furrier: You share some stuff with me, so you're seeing a little bit of the community developing heavily around data-sharing, what's you're take on that? >> So, I think we have a ways to go to make it work right, because if it was working right, you wouldn't see the very published, publicized hacks that have gone on. One of the things that the Congress can do is to provide incentives for the private sector to share more information, more quickly. When the Yahoo hacks occurred, it wasn't discovered until two or three years later. As a result, like I said, there's really no incentive and there's a perceived amount of liability. One of the things I'm asking some of our Congress people to consider is if you do share information, maybe, there's a limitation on liability and that provides, if you will, a mechanism and that provides an incentive for the private organization to work with the public organizations. >> So not to bury it, like Yahoo tried to bury that thing. >> Exactly. There's no sense in burying it. There should be no reason to bury. >> Okay, take a minute to talk about Telos, what you guys are doing, the chief executive. What's going on with the company, talk about the successes, where you guys are winning, your challenges and opportunities. >> Sure, we're in the business of, we do cyber security, we do identity and we do secure mobility. In the area of cyber security, I'm very proud about the fact that we're the database of record for intelligence community, many department of defense agencies use us, homeland security, a whole, department of safe-- There's a whole bunch of organizations that tend to work with us. I think that the issue for me has always been around investing in things that make our customers more efficient. So whether it's cyber security, it's one thing to provide the authority to operate, but I like to provide that authority to operate on a continuous basis. When we talk about identity, it's one thing to say that I am who I say I am, but it's another thing to let you know that I'm actually somebody that's trust worthy. So, we have a special relationship with the FBI that allows us to do real-time data look-ups on their people. We're the integrator of record for the common access card, the military ID card, we have been for a long time. From that, we built a business relationship with the TSA and now we have about 70 airports around America that use our service to do identity as a service for all their employees. >> Can you get me to cut the line at Pre? (laughter) >> You know, if you want to cut the line at TSA pre-- >> Quality of service opportunity and people will pay more for that. >> Absolutely. And plus, I think TSA pre-check wants to have a lot more people in that ecosystem too. No different than when the Easy Pass came into play years and years ago. I remember just zooming through the Easy Pass and wondering why people would want to stand in line, why would you, right? And then if you think about it, we're also involved with secure mobility, so we have a capability called Telos ghost that allows you to basically hide on a network. You're familiar with the notion of signal hopping? In World War two that's how we avoided detection by the enemy, so this is what we invented here with something around IP hopping. So as a result of that, whether you're a server-facing thing or a client-facing thing or a mobile device, you can't be seen on the network and if you can't be seen on the network, you can't be hacked. >> Well, that's awesome stuff. Your relationship with Amazon Web Services, talk about that, some of the things you're involved in. >> Yeah. >> The deals, the momentum. What's the relationship look like between you guys? >> So we have an enormous relationship with Amazon, most important part that we have, it started with the agency and I was in a meeting with Teresa Carlson, one of the senior people in the agency, and we wondered whether or not we could do for, we Telos, can do for the Cloud that which we've been doing for the enterprise for the better part of 15 to 17 years now, which is basically providing that authority to operate in an automated way. So we invested together and we were able to prove that we could absolutely do that. Now, what we're doing is we're basically copying and pasting that model to our customers across the government. >> And you guys put a stake in the ground, 2011. You were early. I mean 2008 was the beginning of the DevOps movement, you were in the heart of it in 2011. >> Wood: Yep. What's the biggest thing you've learned or observed or experienced over those years, since 2011? >> The biggest thing? >> Or just the most important. >> Wood: That is an enormous question. >> It could be the most important, the most relevant, most surprising-- >> Well the most important thing was I got married in 2012. (laughter) I have a four year old and two year old and a 14-year old, those are the most important. >> Was it really you who got married, was it your identity? >> Wood: It was really me and it was my identity. I will say, I think that the government is embracing efficiency. The government is embracing change. I think it started around 2014 or 15, and now it's really moving out. I think there's a lot of top cover, both from a policy side and an executive side and I'm seeing a lot of leadership from within the government itself of people who want to make the change happen. >> And there's also the competitive fairness question we're hearing, just here in town, yesterday, rumblings of one-source Cloud, multi-Cloud. Amazon is technically a one-source Cloud, but they've got an ecosystem. Should they have multi-Cloud in their requirements? All these things almost feel like that protest model is going on, like there's a little fud going everywhere from the other vendors. Do we expect to see more of that in your mind or less of it? (laughter) >> I think at the end of the day-- >> The chips are taken off the table. >> The people who don't want change are the ones, who are, if you will, very invested in the legacy. If those people are paid, time, material or cost blessed, they're not paid to be efficient. So there's going to be push back. On the other hand we've seen by the gigantic growth of the adoption of the Cloud and by the Cloud infrastructure and the Cloud ecosystem itself, there are enomorous opportunities for organizations out there. So I think people should embrace the change, I really do. I think, fundamentally, it's going to be a really big positive to this industry and into this region. >> I always say to Dave Vellante and my co-hosts, it's like no brainer, you look at the main frame, that was the generation when I was growing in the industry. I was the young gun, like main frame co-ball, who the hell wants that? Mini computer, eh, I want the client server. It's pretty obvious when you're in it. So I got to ask you with that in mind, Cloud is pretty obvious. Folks will understand DevOps and automation and those efficiences. You mentioned authority to operate as an example. Some of these numbers are pretty significant. So let's go down the problems that are important, what are the consequences, how do you quantify it, right? So the problem that people are trying to solve is how do I get resources, computing, software, whatever. Pretty important, because now you've got security, you've got all kinds of stuff. What are some of the consequences and you mentioned some benchmarks that you've quantified. You mentioned provisioning a server in a year. Is that really true? >> Wood: That's true! >> So give me some data on some of consequences, kind of the old way and new way. >> Well the old way if you're using the traditional procurement, it's like I said, one of the big issues is whether it was the culture or it's procurement roles or just the process to get an approval, it would take a year to get a server provisioned. Now, it's literally, you push a button and one to two minutes later you have a server, a new server. So you get ultimate scale, you get ultimate throughput, you pay as you go, you pay what you use. What's not to like? So that's all good. From the standpoint of security, because it's the NIST framework we can automate about 90% of that. That's 11 hundred controls, right? So we automate about 90% of those 11 hundred controls. Now, you get a whole bunch of auto inheritance, a whole bunch of things that can be automated are, and as a result, when NIST goes from one version of NIST to another version, all that happens automatically, and more importantly, as a cyber security professional, and I've only been at it since 1994. (laughter) I've been in it for relatively a long time as a CEO. As a cyber security professional, what I see is, as long as I can show a continuous monitoring of your current status, that's very relevant to the operational security professional. That's really good. So for us, we know that our customers are going to be a combination of Cloud, hybrid, and on-prem. These large organizations are going to take years and years and years to move to the Cloud, but they got to start, because now is the time. >> So automation and having that nice stack where it automatically updates and auto-provisioning, auto scaling, but the operational provisioning piece is really where the rubber meets the road, right? Is that what you're getting at? >> Well it's that. It's also you're consolidating your data centers. You don't need lots of them anymore. You can just focus on one, that's another big area. Another big area is, you can lift and shift your legacy IT infrastructure into the Cloud and then put the big investment into the new application as it's siting in there in the Cloud. >> Awesome, John, thanks for joining us here in the cube conversation. Here at Amazon Web Services Headquarters, breaking down the trends in GovCloud public sector as Cloud computing really levels the playing field, opens up new doors, new solutions, faster time to operate, in vi of other things, here in Washington, D.C., in Arlington, Virginia, I'm John Furrier. Thanks for watching. (dramatic music)

>> Announcer: Live, from Las Vegas, it's theCUBE. Covering Veritas Vision, 2017. Brought to you by Veritas. >> Welcome back to theCUBE. This is Veritas Vision, 2017, #Vtas at theCUBE. We like to go out to the events, we extract the signal from the noise. My name is Dave Vellante and I'm here with Stuart Miniman, my cohost for the week. Alex Sakaguchi is here, he's a senior director of global Cloud solutions marketing at Veritas, and he's joined by Ian Wood who's the head of business practices and media for Veritas. Gentlemen, welcome to theCUBE. Thanks for coming on. >> Thank you. >> Thanks for having us. >> So Ian, I noticed a number of EMEA badges here at the event. It's quite a presence, come a long way. Maybe talk about that a little bit. >> Yeah, absolutely. I think we have a great customer base out in EMEA. EMEA for us is Europe, Middle East, and Africa. I know some people get a bit confused with the acronym. We've got a great deal of customers from Europe, the Middle East, and in fact a whole bunch of customers that made it all the way from South Africa and that's one heck of a flight. So showing some good commitment to come out here to our vision conference. We're excited. >> Yeah, that's excellent. What's the narrative like in Europe and how does it compare to the U.S.? Is it equivalent? Is it different? Maybe more of a focus on GDPR, maybe you could summarize. >> Absolutely. Similarities about multi-Cloud is pretty much the same but multi-Cloud or Cloud means different things to different countries. There's a ton of diversity so you can go into Germany, multi-Cloud means something different out in the Middle East as opposed to the U.K. There's a lot of diversity in multi-Cloud but multi-Cloud as a concept is resonating. Customers are understanding that they need a multi-Cloud strategy and that's bubbling up. For them it's not going to be necessarily the big multi-Cloud service providers, they'll have more local Cloud providers that they're looking to include. Spices it up. Then, as you mentioned GDPR is just taking off. It's one of the number one topics on any CIO's agenda right now is GDPR. What do I do? How do I get compliant? How do I make sure by the 25th of May next year I'm ready for GDPR? >> Alright Alex, so what is a multi-Cloud solution? What is it to you guys? >> I think before you get to solution it really takes some understanding and some discussion around what multi-Cloud is. I think we do a lot of ABCs at headquarters, having customers come in and we're kind of on the forefront of that whole multi-Cloud discussion. But many of these customers, many enterprise customers, have multi-Cloud environments meaning that they have lots of different Cloud players: private Cloud, public Cloud, open stack Clouds. Lots of different types of Clouds but they don't have strategies yet. They're in this situation where they've gotten here by virtue of circumstance. The fact that their dev team decides to deploy their resources somewhere. Some other business unit somewhere else or some other engineering team decides to spin up some resources somewhere else and they find themselves in this situation where they have multiple Clouds. Now they're trying to figure out what to do. How do I make a wrapper over that? How do I get some organization? How do I simplify the operations? How do I take a lot of this to production environments from your test dev labs? It's really about enabling those customers, no matter the mix of infrastructure they have, no matter the mix of Cloud providers they decide to employ, giving them the data management capabilities they need to stay in control. The same exact challenges have existed since the beginning of the data center. It's the same problems. >> Alex, you bring up some great points because multi-Cloud for a lot of customers it wasn't the strategy, it's where they are because they just kind of ended up there. Too often in IT it was like I have an application let's spin something up. Then, I spin something else up and I have my temples of excellence for each of them. Things like that and, unfortunately, we've ended up with a lot of that in Cloud. One of the messages I've really liked hearing this week is Veritas is helping customers kind of get their arms around it, not only how do I manage pieces but how do I understand what I have, how do I manage that visibility into a lot of that. >> I think it actually goes back to one step before that because what you're actually talking about is how do I take care of these challenges. That assumes the customer even knows that they have challenges to take care of. What we've found through research, through customer meetings there are many common misconceptions about what a customer's responsibility is from a data management standpoint and what the Cloud provider's responsibility is from an infrastructure as a service provider. That disconnect is where things can go wrong, where they're at increased risk. They think the Cloud provider is offering them some service or some protection or some level of compliance when really, they're not. Part of it is educating the customer. >> And I'd go even further not just infrastructure service but SASS. A lot of customers are like I don't need to worry about back up or security when I'm doing SASS right? That's all taken care of by the platform. >> I had a CIO once come to me it was a fantastic saying he said what I'm doing now is paying the bill for what shadow IT have created. Therefore, there's a shift that shadow IT went rogue deploying Cloud like crazy. IT are now trying to gain control and trying to sort out quite a mess that shadow IT created. >> We've been doing this Cube since 2010 and we started one of the key Cloud shows was the M world. That's where we started. I want to lay out a timeline and you guys, I'm sure I won't get it exactly right but fill in the holes. My argument is we're entering the fifth phase of Cloud. That's how fast things are moving. Phase one was like kick the tires, in 2006, 2007. During the economic downturn, it was a cap-ex to op-x thing. Then, we came out of that and it was like speed. Shadow IT go, go, go, go. Spend, spend, spend. We've got to get to market fast. It was like there was a couple years there 2013, 14, maybe 15 where it was like wow. IT said this is real, we've got to get control. Now there's still a lot of that going on, to your point Ian, but it seems like the next phase that we're about to enter is a deeper level of business integration. Where Cloud is a strategic capability and a platform for these organizations. In seven years, that many phases and they seem to be somewhat distinct. What do you guys think about that? Is that a reasonable timeline? How would you adjust that? >> I would agree generally speaking. The one difference is I think there are many organizations that haven't even gone through stage one. There are other organizations that have gone through that same set of stages multiple times. Think of especially our core set of customers these are large enterprise customers. Many of them grow by acquisition. They inherit the IT environments of whatever company they've acquired. That creates a whole new set of challenges. They might be using different platforms, different Clouds, etc. So really, they kind of go through that process over and over again. What I think is unique is in many cases I think you articulated this in phase one but also in the latter stages, many have looked at, at least in terms of the public Cloud, they've looked at the public Cloud as a way to offset cost, as a low cost alternative. I think what many people find is, it's not. That's not where the value ends. That's not to the extent that they should be looking for value there either. It's really about data agility. It's really about agility of their organizations. It's really about how they can get more from their environments, be more agile, meet their customers' needs better and as they look to accomplish those types of goals then they also realize that hey we need a different set, a different way to manage the resources, manage the applications that sit on those platforms, manage the data that's involved. I think in many cases the cycle repeats itself. I think in many cases they're starting to realize that they need to go beyond even what was typically just sort of a cost argument. I don't know what you're seeing with customers. I know you meet a lot with them. >> Yeah, I think what you mentioned made sense in the phases. I would actually rather look at it as evolution. I think what happens is in the beginning, do I buy or do I rent was the Cloud argument. What happened with that is that's now incremental to I want to drive agility or more security which is incremental to which workload should I go put to the Cloud. I see it as an evolution and I think they're gaining traction and gaining value as you go along. Giving more option and more choice, rather than distinct phases that sort of start end and reboot themselves to something else. It's definitely incremental. >> To that point though, in the earlier stages there was all this fear about the Cloud not being secure. I think we're largely past that. In many cases organizations realize that at least in terms of even SASS players but even public Cloud providers they're way more secure than you can possibly even build your own data center to. They meet all the regulations that you don't have time spin up and manage and adhere to on your own. Having said that, even a lot of the research that we see, security still comes up as the number one concern. Even though people recognize that the Cloud is much more secure than in many cases what they could do on their own. I think we're largely past that for the most part but some of the other areas maybe not so much so. >> Part of that too is this realization that and we've talked about this Stu a lot not necessarily here but on other shows. CIOs realize that they can't just reshape and reform their business and stick it in the public Cloud. Rather, they have to bring the Cloud model to their data. As a result, it creates discontinuities in security practices. I mean, Amazon, it's like here's our security and it's good but it may not be like your private Cloud security so you have to figure that out. That's a challenge for customers. Do you see that? >> Yeah, but it doesn't stop at security. It's really consistency across everything. >> All the edicts of the organization, absolutely. >> For us especially, things like service level agreements. When you're managing SLAs and as an IT organization you're expected to meet certain SLAs but yet your architecture, your environment is one that's distributed. Where you have different pieces of that environment that sit in different platforms, in different Clouds, on prev different technologies. The level of SLA consistency across that is like gone. So how do you ensure things like your business service up time like those SLAs are being met or that you're able to service that or adhere to when you have such a distributed environment and those are challenges that Veritas aims to solve. >> We talked to Mike Palmer earlier and he said a year ago we thought maybe we could just kind of put a thin layer on top and make all the Clouds look the same and when you get into it. Nope. That's not what's going to happen. There's very different reasons and different services. Some of those things, absolutely. It's heterogeneous. How do we focus on the data? How do we help customers through to get the best of why they're buying all these pieces yet get their arms around all of it? >> Yeah, it could be a world of maturity where customers look at a I would say horses for courses. It's an English statement. So look this Cloud provider is going to be just as cheap as anything. Let's go there. That Cloud provider going to be fantastic in analytics like we know who could be pretty good in analytics. That Cloud provider could be good in front office or back office applications. So it's going to be selecting the Cloud providers that provide the best service. That really I think will be the multi-Cloud world. >> So we only have a few minutes left and I want to get into the why Veritas because multi-Cloud is like there's a land grab going on. There's a big opportunity for the vendor community. It's complicated. People are trying to figure out why Veritas. >> A number of reasons. Especially in the enterprise, these are environments that, quite frankly, are too large for many of our closest competitors to even hope to address. These are very, very heterogeneous environments. Lots and lots and lots of data. Multiple types of platforms and Veritas has always been sort of that middle, that heterogeneous layer software defined, software driven provider that enables that sort of layer over all of that stuff basically that sort of disparity and sort of up-level it up to a more simple management capability. That's one. The second thing is and probably this is equally, if not more important is the fact that we're proven to do that. Not just in the multi-Cloud world that we're talking about now but where the customers have come from. What's happening is we're not seeing the customers eliminate the rest of their architecture. They're not eliminating the data centers. They're just adding to it. You can't just provide a solution that only addresses the new, forgets about the old. You have to provide a solution that covers the entirety of the customer's environment. There's not many organizations that can do that and Veritas is one of them that can and that we've built up a level of trust with these enterprise organizations. We're having done that for many, many years. >> Okay. So you just knocked off the upstarts. Well done. Check. But now you're head-to-head with guys like IBM, HPE, Dell, EMC. What's your advantage relative to those guys? Because they're big enough. They can get money, they get breadth. Why you over them? >> I don't know if the appropriate question is Why you over them? Because all of them are here at this conference and there our partners. IBM's a strategic partner for us. >> Dave: Cloud guys though. But there's other parts, okay? >> Certainly, but I think we love these partners. We compete with them in many cases. They also use our technology in other cases. They also partner with us to deliver combined value to our customers. I think it's really not about why us over them. They certainly see the value that we bring to the table and we inevitably... >> Customers have choices, right? How about the evil machine? >> Alex: You're going to press this aren't you? >> I am. I am I've got to press it. No, because people ask us all the time Why Veritas over a company with this large portfolio? I know you don't want to name them but I mean I have an answer but I would... >> I think we look at it as data management, right? Ultimately, multi-Cloud data management's where we sit. That's sort of the category I think we focus in on solving for customer problems and then you go into perhaps the key competitors. I think if I look at the breadth and scale of what we deliver, you narrow it down to a small scale of organizations that compete with us. All of them, especially the EMCs of the world, they have a hardware agenda. Ultimately, at the end of the day, their business is backed on selling hardware and they're going to struggle to get away from that whereas Veritas what we've always sold for is a true software defined or a data management layer which is really what we're going to look at which is Clouding the pages. >> My analysis I would add to that, that you wake up every day thinking about this problem. That's what your company is, old Scott McNeilly, all the wood behind one arrow. They got not only a hardware agenda, they've got a financial agenda, a got to pay off the debt service agenda, a VM ware agenda, a lot of different agendas. They're like the government. Now there's some strengths on the positive side of the ledger but it seems to me in this multi-Cloud world that the focus that you guys have is an advantage because you're designing for that. >> I think we're actually being helped in many regards. Interesting conversation I had a while back about IT. We know information technology, what IT stands for and what has become and evolved over many, many years to be almost like infrastructure technology. I think what we're seeing now is a revert back to the information first. Use any infrastructure you want, it's going to be a combination of a bunch of different things. Who's going to help me get the value out of the information? To your point, that's where Veritas is focused. >> The other thing I'd add is not only do you not have a hardware agenda but you don't have a Cloud agenda. >> Alex: No, yeah. >> Whereas, okay IBM's a partner. They've got a Cloud so that's cool. Take Delhi MC, they don't have a Cloud, a clear agenda even though they won't say it is to keep stuff on prim. You don't care. >> Yeah. >> That is a clear message that I'm hearing here. Again, I see a number of advantages. At the end of the day, it's who's got the better product, who can execute, who can service and deliver. That's what's fun about our industry and you guys have demonstrated that you can do that over a long period of time. Excellent. Good. Thanks for getting into it with me. Guys I'll give you the last word on Vision 2017, each of you a bumper sticker as the trucks are pulling away. >> Vision 2017 has been a fantastic event. It's been true that we've demonstrated that we can exercise in the multi-Cloud world and look at all the Cloud partners that are part of the Veritas world that we're in, in the Vision conference right here. >> I think last thing is you've seen a ton of innovation and product capabilities, technology announced at this conference. What you should probably look forward to in the next six to 12 months before we get to our next Vision conference is the complete maniacal focus and attention given towards a positive and an improved user experience. Across all the products, across all the 360 data management technologies, you're really going to see the UX, and in particular the UIs, improve. >> I love the fact that you guys are transparent about that and you know Mike Palmer. You guys got a spring in your step. The old Veritas mojo looks like it's coming back so congratulations. Thanks for coming to theCUBE. >> Thank you. >> Thank you very much. >> Keep right there everybody, we'll be back with our next guest right after this short break. It's theCUBE. We're live from Veritas Vision 2017. (upbeat music)

(upbeat music) >> Hello and welcome back to theCUBE. We're here in Palo Alto, California. I'm your host, John Furrier with a special guest here in the studio. As part of our Cloud Native SecurityCon Coverage we had an opportunity to bring in Jon Turow who is the partner at Madrona Venture Partners formerly with AWS and to talk about machine learning, foundational models, and how the future of AI is going to be impacted by some of the innovation around what's going on in the industry. ChatGPT has taken the world by storm. A million downloads, fastest to the million downloads there. Before some were saying it's just a gimmick. Others saying it's a game changer. Jon's here to break it down, and great to have you on. Thanks for coming in. >> Thanks John. Glad to be here. >> Thanks for coming on. So first of all, I'm glad you're here. First of all, because two things. One, you were formerly with AWS, got a lot of experience running projects at AWS. Now a partner at Madrona, a great firm doing great deals, and they had this future at modern application kind of thesis. Now you are putting out some content recently around foundational models. You're deep into computer vision. You were the IoT general manager at AWS among other things, Greengrass. So you know a lot about data. You know a lot about some of this automation, some of the edge stuff. You've been in the middle of all these kind of areas that now seem to be the next wave coming. So I wanted to ask you what your thoughts are of how the machine learning and this new automation wave is coming in, this AI tools are coming out. Is it a platform? Is it going to be smarter? What feeds AI? What's your take on this whole foundational big movement into AI? What's your general reaction to all this? >> So, thanks, Jon, again for having me here. Really excited to talk about these things. AI has been coming for a long time. It's been kind of the next big thing. Always just over the horizon for quite some time. And we've seen really compelling applications in generations before and until now. Amazon and AWS have introduced a lot of them. My firm, Madrona Venture Group has invested in some of those early players as well. But what we're seeing now is something categorically different. That's really exciting and feels like a durable change. And I can try and explain what that is. We have these really large models that are useful in a general way. They can be applied to a lot of different tasks beyond the specific task that the designers envisioned. That makes them more flexible, that makes them more useful for building applications than what we've seen before. And so that, we can talk about the depths of it, but in a nutshell, that's why I think people are really excited. >> And I think one of the things that you wrote about that jumped out at me is that this seems to be this moment where there's been a multiple decades of nerds and computer scientists and programmers and data thinkers around waiting for AI to blossom. And it's like they're scratching that itch. Every year is going to be, and it's like the bottleneck's always been compute power. And we've seen other areas, genome sequencing, all kinds of high computation things where required high forms computing. But now there's no real bottleneck to compute. You got cloud. And so you're starting to see the emergence of a massive acceleration of where AI's been and where it needs to be going. Now, it's almost like it's got a reboot. It's almost a renaissance in the AI community with a whole nother macro environmental things happening. Cloud, younger generation, applications proliferate from mobile to cloud native. It's the perfect storm for this kind of moment to switch over. Am I overreading that? Is that right? >> You're right. And it's been cooking for a cycle or two. And let me try and explain why that is. We have cloud and AWS launch in whatever it was, 2006, and offered more compute to more people than really was possible before. Initially that was about taking existing applications and running them more easily in a bigger scale. But in that period of time what's also become possible is new kinds of computation that really weren't practical or even possible without that vast amount of compute. And so one result that came of that is something called the transformer AI model architecture. And Google came out with that, published a paper in 2017. And what that says is, with a transformer model you can actually train an arbitrarily large amount of data into a model, and see what happens. That's what Google demonstrated in 2017. The what happens is the really exciting part because when you do that, what you start to see, when models exceed a certain size that we had never really seen before all of a sudden they get what we call emerging capabilities of complex reasoning and reasoning outside a domain and reasoning with data. The kinds of things that people describe as spooky when they play with something like ChatGPT. That's the underlying term. We don't as an industry quite know why it happens or how it happens, but we can measure that it does. So cloud enables new kinds of math and science. New kinds of math and science allow new kinds of experimentation. And that experimentation has led to this new generation of models. >> So one of the debates we had on theCUBE at our Supercloud event last month was, what's the barriers to entry for say OpenAI, for instance? Obviously, I weighed in aggressively and said, "The barriers for getting into cloud are high because all the CapEx." And Howie Xu formerly VMware, now at ZScaler, he's an AI machine learning guy. He was like, "Well, you can spend $100 million and replicate it." I saw a quote that set up for 180,000 I can get this other package. What's the barriers to entry? Is ChatGPT or OpenAI, does it have sustainability? Is it easy to get into? What is the market like for AI? I mean, because a lot of entrepreneurs are jumping in. I mean, I just read a story today. San Francisco's got more inbound migration because of the AI action happening, Seattle's booming, Boston with MIT's been working on neural networks for generations. That's what we've found the answer. Get off the neural network, Boston jump on the AI bus. So there's total excitement for this. People are enthusiastic around this area. >> You can think of an iPhone versus Android tension that's happening today. In the iPhone world, there are proprietary models from OpenAI who you might consider as the leader. There's Cohere, there's AI21, there's Anthropic, Google's going to have their own, and a few others. These are proprietary models that developers can build on top of, get started really quickly. They're measured to have the highest accuracy and the highest performance today. That's the proprietary side. On the other side, there is an open source part of the world. These are a proliferation of model architectures that developers and practitioners can take off the shelf and train themselves. Typically found in Hugging face. What people seem to think is that the accuracy and performance of the open source models is something like 18 to 20 months behind the accuracy and performance of the proprietary models. But on the other hand, there's infinite flexibility for teams that are capable enough. So you're going to see teams choose sides based on whether they want speed or flexibility. >> That's interesting. And that brings up a point I was talking to a startup and the debate was, do you abstract away from the hardware and be software-defined or software-led on the AI side and let the hardware side just extremely accelerate on its own, 'cause it's flywheel? So again, back to proprietary, that's with hardware kind of bundled in, bolted on. Is it accelerator or is it bolted on or is it part of it? So to me, I think that the big struggle in understanding this is that which one will end up being right. I mean, is it a beta max versus VHS kind of thing going on? Or iPhone, Android, I mean iPhone makes a lot of sense, but if you're Apple, but is there an Apple moment in the machine learning? >> In proprietary models, here does seem to be a jump ball. That there's going to be a virtuous flywheel that emerges that, for example, all these excitement about ChatGPT. What's really exciting about it is it's really easy to use. The technology isn't so different from what we've seen before even from OpenAI. You mentioned a million users in a short period of time, all providing training data for OpenAI that makes their underlying models, their next generation even better. So it's not unreasonable to guess that there's going to be power laws that emerge on the proprietary side. What I think history has shown is that iPhone, Android, Windows, Linux, there seems to be gravity towards this yin and yang. And my guess, and what other people seem to think is going to be the case is that we're going to continue to see these two poles of AI. >> So let's get into the relationship with data because I've been emerging myself with ChatGPT, fascinated by the ease of use, yes, but also the fidelity of how you query it. And I felt like when I was doing writing SQL back in the eighties and nineties where SQL was emerging. You had to be really a guru at the SQL to get the answers you wanted. It seems like the querying into ChatGPT is a good thing if you know how to talk to it. Labeling whether your input is and it does a great job if you feed it right. If you ask a generic questions like Google. It's like a Google search. It gives you great format, sounds credible, but the facts are kind of wrong. >> That's right. >> That's where general consensus is coming on. So what does that mean? That means people are on one hand saying, "Ah, it's bullshit 'cause it's wrong." But I look at, I'm like, "Wow, that's that's compelling." 'Cause if you feed it the right data, so now we're in the data modeling here, so the role of data's going to be critical. Is there a data operating system emerging? Because if this thing continues to go the way it's going you can almost imagine as you would look at companies to invest in. Who's going to be right on this? What's going to scale? What's sustainable? What could build a durable company? It might not look what like what people think it is. I mean, I remember when Google started everyone thought it was the worst search engine because it wasn't a portal. But it was the best organic search on the planet became successful. So I'm trying to figure out like, okay, how do you read this? How do you read the tea leaves? >> Yeah. There are a few different ways that companies can differentiate themselves. Teams with galactic capabilities to take an open source model and then change the architecture and retrain and go down to the silicon. They can do things that might not have been possible for other teams to do. There's a company that that we're proud to be investors in called RunwayML that provides video accelerated, sorry, AI accelerated video editing capabilities. They were used in everything, everywhere all at once and some others. In order to build RunwayML, they needed a vision of what the future was going to look like and they needed to make deep contributions to the science that was going to enable all that. But not every team has those capabilities, maybe nor should they. So as far as how other teams are going to differentiate there's a couple of things that they can do. One is called prompt engineering where they shape on behalf of their own users exactly how the prompt to get fed to the underlying model. It's not clear whether that's going to be a durable problem or whether like Google, we consumers are going to start to get more intuitive about this. That's one. The second is what's called information retrieval. How can I get information about the world outside, information from a database or a data store or whatever service into these models so they can reason about them. And the third is, this is going to sound funny, but attribution. Just like you would do in a news report or an academic paper. If you can state where your facts are coming from, the downstream consumer or the human being who has to use that information actually is going to be able to make better sense of it and rely better on it. So that's prompt engineering, that's retrieval, and that's attribution. >> So that brings me to my next point I want to dig in on is the foundational model stack that you published. And I'll start by saying that with ChatGPT, if you take out the naysayers who are like throwing cold water on it about being a gimmick or whatever, and then you got the other side, I would call the alpha nerds who are like they can see, "Wow, this is amazing." This is truly NextGen. This isn't yesterday's chatbot nonsense. They're like, they're all over it. It's that everybody's using it right now in every vertical. I heard someone using it for security logs. I heard a data center, hardware vendor using it for pushing out appsec review updates. I mean, I've heard corner cases. We're using it for theCUBE to put our metadata in. So there's a horizontal use case of value. So to me that tells me it's a market there. So when you have horizontal scalability in the use case you're going to have a stack. So you publish this stack and it has an application at the top, applications like Jasper out there. You're seeing ChatGPT. But you go after the bottom, you got silicon, cloud, foundational model operations, the foundational models themselves, tooling, sources, actions. Where'd you get this from? How'd you put this together? Did you just work backwards from the startups or was there a thesis behind this? Could you share your thoughts behind this foundational model stack? >> Sure. Well, I'm a recovering product manager and my job that I think about as a product manager is who is my customer and what problem he wants to solve. And so to put myself in the mindset of an application developer and a founder who is actually my customer as a partner at Madrona, I think about what technology and resources does she need to be really powerful, to be able to take a brilliant idea, and actually bring that to life. And if you spend time with that community, which I do and I've met with hundreds of founders now who are trying to do exactly this, you can see that the stack is emerging. In fact, we first drew it in, not in January 2023, but October 2022. And if you look at the difference between the October '22 and January '23 stacks you're going to see that holes in the stack that we identified in October around tooling and around foundation model ops and the rest are organically starting to get filled because of how much demand from the developers at the top of the stack. >> If you look at the young generation coming out and even some of the analysts, I was just reading an analyst report on who's following the whole data stacks area, Databricks, Snowflake, there's variety of analytics, realtime AI, data's hot. There's a lot of engineers coming out that were either data scientists or I would call data platform engineering folks are becoming very key resources in this area. What's the skillset emerging and what's the mindset of that entrepreneur that sees the opportunity? How does these startups come together? Is there a pattern in the formation? Is there a pattern in the competency or proficiency around the talent behind these ventures? >> Yes. I would say there's two groups. The first is a very distinct pattern, John. For the past 10 years or a little more we've seen a pattern of democratization of ML where more and more people had access to this powerful science and technology. And since about 2017, with the rise of the transformer architecture in these foundation models, that pattern has reversed. All of a sudden what has become broader access is now shrinking to a pretty small group of scientists who can actually train and manipulate the architectures of these models themselves. So that's one. And what that means is the teams who can do that have huge ability to make the future happen in ways that other people don't have access to yet. That's one. The second is there is a broader population of people who by definition has even more collective imagination 'cause there's even more people who sees what should be possible and can use things like the proprietary models, like the OpenAI models that are available off the shelf and try to create something that maybe nobody has seen before. And when they do that, Jasper AI is a great example of that. Jasper AI is a company that creates marketing copy automatically with generative models such as GPT-3. They do that and it's really useful and it's almost fun for a marketer to use that. But there are going to be questions of how they can defend that against someone else who has access to the same technology. It's a different population of founders who has to find other sources of differentiation without being able to go all the way down to the the silicon and the science. >> Yeah, and it's going to be also opportunity recognition is one thing. Building a viable venture product market fit. You got competition. And so when things get crowded you got to have some differentiation. I think that's going to be the key. And that's where I was trying to figure out and I think data with scale I think are big ones. Where's the vulnerability in the stack in terms of gaps? Where's the white space? I shouldn't say vulnerability. I should say where's the opportunity, where's the white space in the stack that you see opportunities for entrepreneurs to attack? >> I would say there's two. At the application level, there is almost infinite opportunity, John, because almost every kind of application is about to be reimagined or disrupted with a new generation that takes advantage of this really powerful new technology. And so if there is a kind of application in almost any vertical, it's hard to rule something out. Almost any vertical that a founder wishes she had created the original app in, well, now it's her time. So that's one. The second is, if you look at the tooling layer that we discussed, tooling is a really powerful way that you can provide more flexibility to app developers to get more differentiation for themselves. And the tooling layer is still forming. This is the interface between the models themselves and the applications. Tools that help bring in data, as you mentioned, connect to external actions, bring context across multiple calls, chain together multiple models. These kinds of things, there's huge opportunity there. >> Well, Jon, I really appreciate you coming in. I had a couple more questions, but I will take a minute to read some of your bios for the audience and we'll get into, I won't embarrass you, but I want to set the context. You said you were recovering product manager, 10 plus years at AWS. Obviously, recovering from AWS, which is a whole nother dimension of recovering. In all seriousness, I talked to Andy Jassy around that time and Dr. Matt Wood and it was about that time when AI was just getting on the radar when they started. So you guys started seeing the wave coming in early on. So I remember at that time as Amazon was starting to grow significantly and even just stock price and overall growth. From a tech perspective, it was pretty clear what was coming, so you were there when this tsunami hit. >> Jon: That's right. >> And you had a front row seat building tech, you were led the product teams for Computer Vision AI, Textract, AI intelligence for document processing, recognition for image and video analysis. You wrote the business product plan for AWS IoT and Greengrass, which we've covered a lot in theCUBE, which extends out to the whole edge thing. So you know a lot about AI/ML, edge computing, IOT, messaging, which I call the law of small numbers that scale become big. This is a big new thing. So as a former AWS leader who's been there and at Madrona, what's your investment thesis as you start to peruse the landscape and talk to entrepreneurs as you got the stack? What's the big picture? What are you looking for? What's the thesis? How do you see this next five years emerging? >> Five years is a really long time given some of this science is only six months out. I'll start with some, no pun intended, some foundational things. And we can talk about some implications of the technology. The basics are the same as they've always been. We want, what I like to call customers with their hair on fire. So they have problems, so urgent they'll buy half a product. The joke is if your hair is on fire you might want a bucket of cold water, but you'll take a tennis racket and you'll beat yourself over the head to put the fire out. You want those customers 'cause they'll meet you more than halfway. And when you find them, you can obsess about them and you can get better every day. So we want customers with their hair on fire. We want founders who have empathy for those customers, understand what is going to be required to serve them really well, and have what I like to call founder-market fit to be able to build the products that those customers are going to need. >> And because that's a good strategy from an emerging, not yet fully baked out requirements definition. >> Jon: That's right. >> Enough where directionally they're leaning in, more than in, they're part of the product development process. >> That's right. And when you're doing early stage development, which is where I personally spend a lot of my time at the seed and A and a little bit beyond that stage often that's going to be what you have to go on because the future is going to be so complex that you can't see the curves beyond it. But if you have customers with their hair on fire and talented founders who have the capability to serve those customers, that's got me interested. >> So if I'm an entrepreneur, I walk in and say, "I have customers that have their hair on fire." What kind of checks do you write? What's the kind of the average you're seeing for seed and series? Probably seed, seed rounds and series As. >> It can depend. I have seen seed rounds of double digit million dollars. I have seen seed rounds much smaller than that. It really depends on what is going to be the right thing for these founders to prove out the hypothesis that they're testing that says, "Look, we have this customer with her hair on fire. We think we can build at least a tennis racket that she can use to start beating herself over the head and put the fire out. And then we're going to have something really interesting that we can scale up from there and we can make the future happen. >> So it sounds like your advice to founders is go out and find some customers, show them a product, don't obsess over full completion, get some sort of vibe on fit and go from there. >> Yeah, and I think by the time founders come to me they may not have a product, they may not have a deck, but if they have a customer with her hair on fire, then I'm really interested. >> Well, I always love the professional services angle on these markets. You go in and you get some business and you understand it. Walk away if you don't like it, but you see the hair on fire, then you go in product mode. >> That's right. >> All Right, Jon, thank you for coming on theCUBE. Really appreciate you stopping by the studio and good luck on your investments. Great to see you. >> You too. >> Thanks for coming on. >> Thank you, Jon. >> CUBE coverage here at Palo Alto. I'm John Furrier, your host. More coverage with CUBE Conversations after this break. (upbeat music)