>> Live from Bahrain, it's theCUBE! Covering AWS Summit Bahrain. Brought to you by Amazon Web Services. >> Okay, welcome back everyone. We are here, live in Bahrain, for the exclusive CUBE coverage of AWS Summit here in the region. Obviously, huge news, Amazon's having a region here, a full region, that's going to create a lot of connections, new opportunities, and hopefully make the life easier for all the developers and whatnot. Great guest here, so we're just talking with Kim on camera, about all the exciting developments on Amazon. We've got Abdul Raman, who's the group EVP of tech, at the ATG, which is the Al Tayyar Travel Group, in Saudi Arabia. >> Yep. >> Thanks for joining me today. >> Thanks a lot for having me. >> So, I'll quickly fast forward, you guys started in 2015, programming in the cloud, your like, we were late. I think that's actually a good time, 'cause Amazon had a lot of mature services ready. Went from zero to billions in revenue. >> Correct. >> Really big success story, that's large scale, all cloud based right? >> Yep, correct. >> Tell your story, what do you guys do, real quick, take a minute to explain your group, what you guys do, and then, what were the architectural things you decided, how did you get the growth? >> So, we are a 40 years old company, we started in 1979, we are the largest travel and tourism company in the Middle East. We went public, through our IPO in 2012. And 2015, our new board, and new management, including myself, we started building our ten-year strategy plan. And we said, we need to diversify our investment, so it mandated that we need to have an online presence. In 2015, we had a choice to build our online presence, which is very late, either on-premise using, building a data center, or we go to the cloud. We had multiple metrics including the cost efficiency, including scalability, security and so on, and all these metrics, when we compared on-premise versus cloud, cloud always win. And we selected Amazon to build our online presence. And beginning of 2015, we had zero presence, zero revenue. Our total revenue from the classic legacy systems, for the retail was almost two billion dollars. But we had zero revenue from the online. We were able, within six weeks, to build the proof of concept, and launch it immediately, and we started heavily investing in various components, from back-end, front-end, DevOps, and so on. And this year, we anticipate, we're going to be generating more than two billion riyal of revenue, that's about 450 >> Online >> Online only. >> Via cloud. >> Exactly, only on Amazon. And for us, that has been the best success story we had for years. >> It's an amazing success story actually. >> We look backward to our decision back then. >> I'll break for you, that's like actually really amazing. This is something that I think people don't really understand, what about the cloud, and certainly Amazon, and the kind of scale that you can get, if you get something right, both on the business model side and architecturally, you can be a unicorn. You're really a unicorn in revenue, that's the word that they hear in the startup world, unicorn, but mostly that's stock value, that's not actually real cash, in how many years? This is pretty phenomenal. This is the entrepreneurial dream, that is now a reality. >> Yep, that's correct. >> This is the story here. >> Exactly, and I'm happy that you mentioned that. We actually, when we started this venture, we said, to the founders, you guys are a startup. We rented out, in 2015, a garage, literally. >> Yeah, get out of the way. >> A house, A very old warehouse, we brought like, five guys, you are the core team, we told them, you are a startup, give us whatever you want to do. And it has been very successful since then. >> It's kind of like the Steve Jobs story, you got Apple, with the Mac II, and then the little group over here, you know, doing the Macintosh. >> Yep, yep, yep. >> That's your group, because you got to get out of their way, it's a mindset, I want to ask you that, that was one of my questions, but we got there a little early, but, this is a cultural shift. Cloud is a different mindset. >> Yep. >> It's not the old way of planning, team-building. >> Yep. >> It really is a different dynamic both execution wise, but team makeup. >> Correct. >> Can you share that piece of it? >> We gave our founders complete freedom, in how they're going to make up their management style. So we have a complete agile team, we have diverse geographical locations, we have people from India, developers in Egypt, in Dubai, in Saudi, and be all work and collaborate, using DevOp tools from Amazon, so we divide the work load, our product teams, weekly launch feature list. They tell us when they would like to launch every two weeks, or three weeks, a new version of the website, or the mobile apps. So, we have a completely agile development methodology, and we give our new venture a truly startup culture. >> And the key for you, if I get this right, is to have executive leadership say, we're doing this? >> Yep. >> Was that in place, did you drive that? >> Absolutely, so when our board said, told us, the new board in 2015, guys we don't have an online, go and get it, me and the CEO said, the best way to do it, is just spin off a completely different unit, completely independent, startup mentality, intro manuals, and told them, guys, sky is limit. We need to be the number one player in the Middle East. >> So, I got to dig deeper, 'cause I love, you know, it's all sexy, and great story when you say, this is how we started, and we finished strong, but as Andy Jassy would say, the CEO of AWS, the learning's in the middle, the ups and downs, as you figure things out, 'cause a lot of things about cloud, is iteration. >> Yep. >> 'Cause you have the ability to move very fast, and you get smart people together, so there's a glorious start and a glorious outcome, but in the middle is the experimentation, that's where the real work gets done. Can you share some of the learnings? Was it a technology selection? Did you really, do you have more queuing, more database, as you start to play with Amazon, this becomes, actually, a business process. >> Our biggest, yeah. >> Playing with the different pieces and which services are right for which process. Can you share something? >> Correct. So our biggest challenge was finding the right skillset, who are people who understand how Amazon, AWS, works. In the Middle East, we don't have that many skillset, or skillful people, so we had to wait, train the people, send them to Amazon workshops, be very patient with the mistakes, we don't mind people refactoring all the old code. Every month we start from scratch. We were very aware that this is, what we are doing, is never been done before in the Middle East. And what we have developed, in terms of, for example, the big data, the big data platform we build today, is one of the largest, we are processing terrabytes of data every week. It's one of the largest in the Middle East. The number of developers we have today, more than 500, working on AWS. I don't think any company in the Middle East, have that number of developers, working on this platform. So we're very proud that we gave our developers the trust and we are aware that you need to fail fast, learn, and quickly adapt. >> And it's a contagious mindset too, when you start seeing success. >> Yep. >> So talk about some of the architectural, talk about the stack that you're using. Obviously, you must be using a variety of the Amazon goodness, EC2, that's pretty obvious, are you guys using the queuing, are you using Kinesis? How you, can you talk about some of the architectural things, if you can? >> Yep, so we have, the front-end that we have today, is completely built on Node.js and AngularJS, so it's very fast, very agile. Our back end is built on Java, most of the code built on Java. We have multiple messaging buses, that asynchronous mode, so whenever there is something that needs to be given to a certain component, we don't have to wait for serial queuing. It's all parallel. At the same time, we have a lot of Auto Scaling components. One of the examples I gave earlier today, is that, we had, the beginning of this summer, we had so many marketing campaigns, and we were surprised by how successful these marketing campaigns. We have noticed, in one marketing campaign, that our demand, from our customer, have reached 300 percent, within 24 hours, and the Auto Scaling that we have in place, have been very successful. We were able to immediately meet that demand. >> Talk about how good the Auto Scaling is. Isn't that a relief? >> Absolutely. >> I mean, explain how it works because, essentially, when the demand comes in, explain how it works. >> Yep, so, just to give an example, if we had this infrastructure on-premise, we would have needed six weeks to procure a new infrastructure, install it, configure it, and we would have lost all this six weeks of revenue. >> And then, by the way, you would have lost the first 24 hour surge, then you'd go over-billed, and then wait around, and then not know if you over-provisioned. >> Absolutely. >> This is, the old way. The new way is, you configure Auto Scaling, based on policy, and then it just spins up. >> Absolutely. >> Resources. >> Absolutely. >> While you're sleeping. >> Exactly, so in a few seconds, the Auto Scaling fires up a lot of instances, and we immediately cope with the demand. >> You know, it's funny you mentioned that. One of the comments we have inside our company is, you know you're successful online, when you're making money while you're sleeping. And, you know, if you have Auto Scaling, and things of that nature, these things are programmatic, this is what elastic is all about, this is what coders, >> Yep. >> Not system administrators do >> True. >> And once they do it, they're highly motivated not to manage it again. >> Correct, absolutely. >> Again, this is back to the culture of DevOps. >> Yep, yep. >> How have you guys innovated on that piece, can you give some other examples? >> Yes, so today we have, our big data has feeds from all the buys from the big social networks, Twitter and Facebook, and also from Google, and we have all this analytical data, into our big data, and we analyze all our customer behavior, what they're looking for, what kind of destinations, holidays, business travel, and we try to adapt every two, three weeks, our product and services to meet our customer demand. Next year, we're going to be launching our machine learning, and AI infrastructure. This way, we'll be able to do real time, predictive analysis, and we will be able to serve each customer, unique, fully personalized, customized, web page and experience. We will be able to exceed our customer expectations, and we'll be able to give our customer exactly what they're looking for. >> Abdul, I got to ask you a personal question. >> Sure. >> What are you most proud of, of this success story? What are some of the things, that you look back and say, wow, we really knocked it out of the park, we did great on this, and then an example where you had a good learning experience. Maybe a trip and a fall, that was a learning opportunity. What are you most proud of? And areas that you learned the most about from, tripping and falling, and failure. >> Yep, so I think the most thing I'm proud of, is we have gathered great minds, and we have created great culture. I think great companies have great people behind them, and this, I've learned from reading the stories of Apple or Microsoft, or Google and so on. So, I think we've been very successful in this area, in the Middle East, where the resources are very scarce, and the ability to attract very smart people is very difficult, to bring them in the Middle East. And I think, we've been very successful in that regard, we've been able to gather a lot of smart people, and create great culture. >> You know, Marc Andreessen wrote that article, book about, or maybe it was a tweet, I can't even remember, the 10x engineer. >> Yep. >> And that concept is one engineer, that does cloud and DevOps right is worth ten engineers in the old world. And so, if you can collect, a selection of these 10x multipliers, that can do architecture. >> Correct. >> Now I personally believe that the full-stack developer, might be obsoleted with the cloud, or reduce the requirement for full-stack developer, but you'll still need full-stack developers for cloud, in general, but you don't need to stockpile full-stack developers. >> True, true, I agree. >> If you have good full-stack developers, you then can hire application developers >> True. >> Because the full-stack takes care of all the scale. >> Exactly, you can always repurpose those guys, and up-skill them to do something different. Instead of being a full-stack, you really want to focus on solution developer. >> Google's proven this with their SRE, if you've seen, they have operators, and developers. And this, as you scale, you're operating infrastructure, or you're writing code for applications. >> Correct. >> Alright, so what's the learnings that have been magnified for you? In the middle of the journey here, there's always the, you know, situation were, you know, you have to take care of personnel issue, or technology selection tweak or change, iteration, I won't say pivot, 'cause people don't pivot, when they're succeeding, it's just navigating through the journey. What was something that you've experienced that was magnified in the learnings, that have helped you get better? >> Yep, I believe that the multi-culture and the multi-nationalities and multi-discipline and people coming from different backgrounds. We have people from Asia, from Europe, from the U.S., in our company, and this helped having different backgrounds, different experiences, and this has helped us to build a nice, multi-dimensional solutions. And people have been able to share this experience, in a very nice way. >> That's great, Abdul, thanks so much for sharing, taking the time. >> Thank you. >> Here on theCUBE, and sharing your insight, and amazing success story, congratulations to you and your team, really love to hear these amazing success stories, essentially building from zero start, online, to billions in revenue, that's an amazing success story. >> Thank you very much for having me. >> And it certainly is great. Exclusive coverage here, we are in Bahrain, this exclusive CUBE coverage, I'm John Furrier. You can reach me on Twitter @furrier, or just search my name, reach out to me, let me know what you think. Stay with us for more coverage, after this break. (techno music fades out)

>> Announcer: Live from San Jose, California, it's the CUBE, covering Big Data Silicon Valley 2017. (upbeat synthesizer music) >> Live with the CUBE coverage of Big Data Silicon Valley or Big Data SV, #BigDataSV in conjunction with Strata + Hadoop. I'm John Furrier with the CUBE and my co-host George Gilbert, analyst at Wikibon. I'm excited to have our next guest, Yaron Haviv, who's the founder and CTO of iguazio, just wrote a post up on SiliconANGLE, check it out. Welcome to the CUBE. >> Thanks, John. >> Great to see you. You're in a guest blog this week on SiliconANGLE, and always great on Twitter, cause Dave Alante always liked to bring you into the contentious conversations. >> Yaron: I like the controversial ones, yes. (laughter) >> And you add a lot of good color on that. So let's just get right into it. So your company's doing some really innovative things. We were just talking before we came on camera here, about some of the amazing performance improvements you guys have on many different levels. But first take a step back, and let's talk about what this continuous analytics platform is, because it's unique, it's different, and it's got impact. Take a minute to explain. >> Sure, so first a few words on iguazio. We're developing a data platform which is unified, so basically it can ingest data through many different APIs, and it's more like a cloud service. It is for on-prem and edge locations and co-location, but it's managed more like a cloud platform so very similar experience to Amazon. >> John: It's software? >> It's software. We do integrate a lot with hardware in order to achieve our performance, which is really about 10 to 100 times faster than what exists today. We've talked to a lot of customers and what we really want to focus with customers in solving business problems, Because I think a lot of the Hadoop camp started with more solving IT problems. So IT is going kicking tires, and eventually failing based on your statistics and Gardner statistics. So what we really wanted to solve is big business problems. We figured out that this notion of pipeline architecture, where you ingest data, and then curate it, and fix it, et cetera, which was very good for the early days of Hadoop, if you think about how Hadoop started, was page ranking from Google. There was no time sensitivity. You could take days to calculate it and recalibrate your search engine. Based on new research, everyone is now looking for real time insights. So there is sensory data from (mumbles), there's stock data from exchanges, there is fraud data from banks, and you need to act very quickly. So this notion of and I can give you examples from customers, this notion of taking data, creating Parquet file and log files, and storing them in S3 and then taking Redshift and analyzing them, and then maybe a few hours later having an insight, this is not going to work. And what you need to fix is, you have to put some structure into the data. Because if you need to update a single record, you cannot just create a huge file of 10 gigabyte and then analyze it. So what we did is, basically, a mechanism where you ingest data. As you ingest the data, you can run multiple different processes on the same thing. And you can also serve the data immediately, okay? And two examples that we demonstrate here in the show, one is video surveillance, very nice movie-style example, that you, basically, ingest pictures for S3 API, for object API, you analyze the picture to detect faces, to detect scenery, to extract geolocation from pictures and all that, all those through different processes. TensorFlow doing one, serverless functions that we have, do other simpler tasks. And in the same time, you can have dashboards that just show everything. And you can have Spark, that basically does queries of where was this guys last seen? Or who was he with, you know, or think about the Boston Bomber example. You could just do it in real time. Because you don't need this notion of pipeline. And this solves very hard business problems for some of the customers we work with. >> So that's the key innovation, there's no pipe lining. And what's the secret sauce? >> So first, our system does about a couple of million of transactions per second. And we are a multi-modal database. So, basically, you can ingest data as a stream, exactly the same data could be read by Spark as a table. So you could, basically, issue a query on the same data. Give me everything that has a certain pattern or something, and could also be served immediately through RESTful APIs to a dashboard running AngularJS or something like that. So that's the secret sauce, is by having this integration, and this unique data model, it allows you all those things to work together. There are other aspects, like we have transactional semantics. One of the challenges is how do you make sure that a bunch of processes don't collide when they update the same data. So first you need a very low ground alert. 'cause each one may update to different field. Like this example that I gave with GeoData, the serverless function that does the GeoData extraction only updates the GeoData fields within the records. And maybe TensorFlow updates information about the image in a different location in the record or, potentially, a different record. So you have to have that, along with transaction safety, along with security. We have very tight security at the field level, identity level. So that's re-thinking the entire architecture. And I think what many of the companies you'll see at the show, they'll say, okay, Hadoop is given, let's build some sort of convenience tools around it, let's do some scripting, let's do automation. But serve the underlying thing, I won't use dirty words, but is not well-equipped to the new challenges of real time. We basically restructured everything, we took the notions of cloud-native architectures, we took the notions of Flash and latest Flash technologies, a lot of parallelism on CPUs. We didn't take anything for granted on the underlying architecture. >> So when you found the company, take a personal story here. What was the itch you were scratching, why did you get into this? Obviously, you have a huge tech advantage, which is, will double-down with the research piece and George will have some questions. What got you going with the company? You got a unique approach, people would love to do away with the pipeline, that sounds great. And the performance, you said about 100x. So how did you get here? (laughs) Tell the story. >> So if you know my background, I ran all the data center activities in Mellanox, and you know Mellanox, I know Kevin was here. And my role was to take Mellanox technology, which is 100 gig networking and silicon, and fit it into the different applications. So I worked with SAP HANA, I worked with Teradata, I worked on Oracle Exadata, I work with all the cloud service providers on building their own object storage and NoSQL and other solutions. I also owned all the open source activities around Hadoop and Saf and all those projects, and my role was to fix many of those. If a customer says I don't need 100 gig, it's too fast for me, how do I? And my role was to convince him that yes, I can open up all the bottleneck all the way up to your stack so you can leverage those new technologies. And for that we basically sowed inefficiencies in those stacks. >> So you had a good purview of the marketplace. >> Yaron: Yes. >> You had open source on one hand, and then all the-- >> All the storage players, >> vendors, network. >> all the database players and all the cloud service providers were my customers. So you're a very unique point where you see the trajectory of cloud. Doing things totally different, and sometimes I see the trajectory of enterprise storage, SAN, NAS, you know, all Flash, all that, legacy technologies where cloud providers are all about object, key value, NoSQL. And you're trying to convince those guys that maybe they were going the wrong way. But it's pretty hard. >> Are they going the wrong way? >> I think they are going the wrong way. Everyone, for example, is running to do NVMe over Fabric now that's the new fashion. Okay, I did the first implementation of NVMe over Fabric, in my team at Mellanox. And I really loved it, at that time, but databases cannot run on top of storage area networks. Because there are serialization problems. Okay, if you use a storage area network, that mean that every node in the cluster have to go and serialize an operation against the shared media. And that's not how Google and Amazon works. >> There's a lot more databases out there too, and a lot more data sources. You've got the Edge. >> Yeah, but all the new databases, all the modern databases, they basically shared the data across the different nodes so there are no serialization problems. So that's why Oracle doesn't scale, or scale to 10 nodes at best, with a lot of RDMA as a back plane, to allow that. And that's why Amazon can scale to a thousand nodes, or Google-- >> That's the horizontally-scalable piece that's happening. >> Yeah, because, basically, the distribution has to move into the higher layers of the data, and not the lower layers of the data. And that's really the trajectory where the traditional legacy storage and system vendors are going, and we sort of followed the way the cloud guys went, just with our knowledge of the infrastructure, we sort of did it better than what the cloud guys did. 'Cause the cloud guys focused more on the higher levels of the implementation, the algorithms, the Paxos, and all that. Their implementation is not that efficient. And we did both sides extremely efficient. >> How about the Edge? 'Cause Edge is now part of cloud, and you got cloud has got the compute, all the benefits, you were saying, and still they have their own consumption opportunities and challenges that everyone else does. But Edge is now exploding. The combination of those things coming together, at the intersection of that is deep learning, machine learning, which is powering the AI hype. So how is the Edge factoring into your plan and overall architectures for the cloud? >> Yeah, so I wrote a bunch of posts that are not published yet about the Edge, But my analysis along with your analysis and Pierre Levin's analysis, is that cloud have to start distribute more. Because if you're looking at the trends. Five gig, 5G Wi-Fi in wireless networking is going to be gigabit traffic. Gigabit to the homes, they're going to buy Google, 70 bucks a month. It's going to push a lot more bend with the Edge. On the same time, a cloud provider, is in order to lower costs and deal with energy problems they're going to rural areas. The traditional way we solve cloud problems was to put CDNs, so every time you download a picture or video, you got to a CDN. When you go to Netflix, you don't really go to Amazon, you got to a Netflix pop, one of 250 locations. The new work loads are different because they're no longer pictures that need to be cashed. First, there are a lot of data going up. Sensory data, upload files, et cetera. Data is becoming a lot more structured. Censored data is structured. All this car information will be structured. And you want to (mumbles) digest or summarize the data. So you need technologies like machine learning, NNI and all those things. You need something which is like CDNs. Just mini version of cloud that sits somewhere in between the Edge and the cloud. And this is our approach. And now because we can string grab the mini cloud, the mini Amazon in a way more dense approach, then this is a play that we're going to take. We have a very good partnership with Equinox. Which has 170 something locations with very good relations. >> So you're, essentially, going to disrupt the CDN. It's something that I've been writing about and tweeting about. CDNs were based on the old Yahoo days. Cashing images, you mentioned, give me 1999 back, please. That's old school, today's standards. So it's a whole new architecture because of how things are stored. >> You have to be a lot more distributive. >> What is the architecture? >> In our innovation, we have two layers of innovation. One is on the lower layers of, we, actually, have three main innovations. One is on the lower layers of what we discussed. The other one is the security layer, where we classify everything. Layer seven at 100 gig graphic rates. And the third one is all this notion of distributed system. We can, actually, run multiple systems in multiple locations and manage them as one logical entity through high level semantics, high level policies. >> Okay, so when we take the CUBE global, we're going to have you guys on every pop. This is a legit question. >> No it's going to take time for us. We're not going to do everything in one day and we're starting with the local problems. >> Yeah but this is digital transmissions. Stay with me for a second. Stay with this scenario. So video like Netflix is, pretty much, one dimension, it's video. They use CDNs now but when you start thinking in different content types. So, I'm going to have a video with, maybe, just CGI overlayed or social graph data coming in from tweets at the same time with Instagram pictures. I might be accessing multiple data everywhere to watch a movie or something. That would require beyond a CDN thinking. >> And you have to run continuous analytics because it can not afford batch. It can not afford a pipeline. Because you ingest picture data, you may need to add some subtext with the data and feed it, directly, to the consumer. So you have to move to those two elements of moving more stuff into the Edge and running into continuous analytics versus a batch on pipeline. >> So you think, based on that scenario I just said, that there's going to be an opportunity for somebody to take over the media landscape for sure? >> Yeah, I think if you're also looking at the statistics. I seen a nice article. I told George about it. That analyzing the Intel cheap distribution. What you see is that there is a 30% growth on Intel's cheap Intel Cloud which is faster than what most analysts anticipate in terms of cloud growth. That means, actually, that cloud is going to cannibalize Enterprise faster than what most think. Enterprise is shrinking about 7%. There is another place which is growing. It's Telcos. It's not growing like cloud but part of it is because of this move towards the Edge and the move of Telcos buying white boxes. >> And 5G and access over the top too. >> Yeah but that's server chips. >> Okay. >> There's going to be more and more computation in the different Telco locations. >> John: Oh you're talking about computer, okay. >> This is an opportunity that we can capitalize on if we run fast enough. >> It sounds as though because you've implemented these industry standard APIs that come from the, largely, the open source ecosystem, that you can propagate those to areas on the network that the vendors, who are behind those APIs can't, necessarily, do. Into the Telcos, towards the Edge. And, I assume, part of that is cause of the density and the simplicity. So, essentially, your footprint's smaller in terms of hardware and the operational simplicity is greater. Is that a fair assessment? >> Yes and also, we support a lot of Amazon compatible APIs which are RESTful, typically, HTTP based. Very convenient to work with in a cloud environment. Another thing is, because we're taking all the state on ourself, the different forms of states whether it's a message queue or a table or an object, et cetera, that makes the computation layer very simple. So one of the things that we are, also, demonstrating is the integration we have with Kubernetes that, basically, now simplifies Kubernetes. Cause you don't have to build all those different data services for cloud native infrastructure. You just run Kubernetes. We're the volume driver, we're the database, we're the message queues, we're everything underneath Kubernetes and then, you just run Spark or TensorFlow or a serverless function as a Kubernetes micro service. That allows you now, elastically, to increase the number of Spark jobs that you need or, maybe, you have another tenant. You just spun a Spark job. YARN has some of those attributes but YARN is very limited, very confined to the Hadoop Ecosystem. TensorFlow is not a Hadoop player and a bunch of those new tools are not in Hadoop players and everyone is now adopting a new way of doing streaming and they just call it serverless. serverless and streaming are very similar technologies. The advantage of serverless is all this pre-packaging and all this automation of the CICD. The continuous integration, the continuous development. So we're thinking, in order to simplify the developer in an operation aspects, we're trying to integrate more and more with cloud native approach around CICD and integration with Kubernetes and cloud native technologies. >> Would it be fair to say that from a developer or admin point of view, you're pushing out from the cloud towards the Edge faster than if the existing implementations say, the Apache Ecosystem or the AWS Ecosystem where AWS has something on the edge. I forgot whether it's Snowball or Green Grass or whatever. Where they at least get the lambda function. >> They're field by the way and it's interesting to see. One of the things they allowed lambda functions in their CDS which is going the direction I mentioned just for a minimal functionality. Another thing is they have those boxes where they have a single VM and they can run lambda function as well. But I think their ability to run computation is very limited and also, their focus is on shipping the boxes through mail and we want it to be always connected. >> Our final question for you, just to get your thoughts. Great save up, by the way. This is very informative. Maybe be should do a follow up on Skype in our studio for Silocon Friday show. Google Next was interesting. They're serious about the Enterprise but you can see that they're not yet there. What is the Enterprise readiness from your perspective? Cause Google has the tech and they try to flaunt the tech. We're great, we're Google, look at us, therefore, you should buy us. It's not that easy in the Enterprise. How would you size up the different players? Because they're all not like Amazon although Amazon is winning. You got Amazon, Azure and Google. Your thoughts on the cloud players. >> The way we attack Enterprise, we don't attack it from an Enterprise perspective or IT perspective, we take it from a business use case perspective. Especially, because we're small and we have to run fast. You need to identify a real critical business problem. We're working with stock exchanges and they have a lot of issues around monitoring the daily trade activities in real time. If you compare what we do with them on this continuous analytics notion to how they work with Excel's and Hadoops, it's totally different and now, they could do things which are way different. I think that one of the things that Hadook's customer, if Google wants to succeed against Amazon, they have to find the way of how to approach those business owners and say here's a problem Mr. Customer, here's a business challenge, here's what I'm going to solve. If they're just going to say, you know what? My VM's are cheaper than Amazon, it's not going to be a-- >> Also, they're doing the whole, they're calling lift and shift which is code word for rip and replace in the Enterprise. So that's, essentially, I guess, a good opportunity if you can get people to do that but not everyone's ripping and replacing and lifting and shifting. >> But a lot of Google advantages around areas of AI and things like that. So they should try and leverage, if you think about Amazon approach to AI, this fund the university to build a project and then set it's hours where Google created TensorFlow and created a lot of other IPs and Dataflow and all those solutions and consumered it to the community. I really love Google's approach of contributing Kubernetes, to contributing TensorFlow. And this way, they're planting the seeds so the new generation this is going to work with Kubernetes and TensorFlow who are going to say, "You know what?" "Why would I mess with this thing on (mumbles) just go and. >> Regular cloud, do multi-cloud. >> Right to the cloud. But I think a lot of criticism about Google is that they're too research oriented. They don't know how to monetize and approach the-- >> Enterprise is just a whole different drum beat and I think that's the only thing on my complaint with them, they got to get that knowledge and/or buy companies. Have a quick final point on Spanner or any analysis of Spanner that went from paper, pretty quickly, from paper to product. >> So before we started iguazio, I started Spanner quite a bit. All the publication was there and all the other things like Spanner. Spanner has the underlying layer called Colossus. And our data layer is very similar to how Colossus works. So we're very familiar. We took a lot of concepts from Spanner on our platform. >> And you like Spanner, it's legit? >> Yes, again. >> Cause you copied it. (laughs) >> Yaron: We haven't copied-- >> You borrowed some best practices. >> I think I cited about 300 research papers before we did the architecture. But we, basically, took the best of each one of them. Cause there's still a lot of issues. Most of those technologies, by the way, are designed for mechanical disks and we can talk about it in a different-- >> And you have Flash. Alright, Yaron, we have gone over here. Great segment. We're here, live in Silicon Valley, breakin it down, getting under the hood. Looking a 10X, 100X performance advantages. Keep an eye on iguazio, they're looking like they got some great products. Check them out. This is the CUBE. I'm John Furrier with George Gilbert. We'll be back with more after this short break. (upbeat synthesizer music)

live from Las Vegas Nevada it's the cute covering knowledge 15 brought to you by service now okay hello everyone we are live for day two of coverage this is the cube our flagship program we go out to the events and extract the signal noise we go over here live in service now's knowledge 15 hashtag no 15 you want to join the conversation we have a back channel live chat on crowd chat new application which I'm excited Dave to show the guys from Sarah's neck as they love good software so but a crowd shot net / no 15 and see the conversation ask questions join our virtual social experience and we'll be happy to address that with your day to coverage live in Las Vegas out of three full days yesterday was a great day we had Frank sloop enough CEO opening up the day really laying down and and in clarifying the future of service now certainly they took a bath on the the stock last week on their earnings still in throwing off a lot of lot of cash great platform business great buying opportunity as Dave and I were speculating and ended the day with John Cleese famous actor writer comedian who we had some fun we try to bring a little bit of Jon Stewart a little bit of Jimmy Fallon I'm jump Road Dave vellante Dave what you think about yes that your laptop working parts of my lap water here I've lost my return key in my M so what you think John Cleese k the holy grail of our of our of our program yesterday he was great I mean we had a nice little bit going on there all ad lib just for the record folks he was not pissed he was totally happy at a great time but was all ad-lib he challenged us on the cube and it was great seeing after we were nervous and he's a pro we couldn't even hold a candle to his performance David it was great seeing him afterwards he came up to us yellow hey mr. classy came up and high-five and a smiling laughing it was great smart guy what you think of the inter very opinionated I thought the interview was great I mean it was weird but it was great I top guest top test of six years he's on a great show we had about you know 50 people behind that's all watching so it was really a lot of fun again but let's get back to the event here day two well you know another top guest coming up today is Fred ludie I think you're really going to enjoy interviewing and you heard him on the keynote John he was talking about the new development platform the new UI the new mobile app all that he was geeking out on all the technologies a lot of things that you're very familiar with borrowing from you know real-time geolocation leveraging the camera in the mobile app a lot of technologies borrow from Facebook and Twitter and a whole that whole real-time crowd a lot of stuff that that that crowd chat uses I know you talk about it all the time angularjs and all these kind of things that people don't understand our new crowd chat application go to crouch at that poke around look at the live one but what you'll notice on that app is one hundred percent as synchronous we use cutting-edge technologies like bootstrap we use angularjs and our new crowd pages coming out we have knowed Java on the backend for analytics really a cross-section of all the different language but node bootstrap angular these are the technologies that truly make it a singer's Facebook by the way is not a synchronous you've got to load the page having a synchronous communications loose from WebSockets days of web browser to fully available data real-time so near real-time is the holy grail today and basically instant is going to be defensive state-of-the-art today in software development that's what service now is showing on the stage and again a lot of it resonated because I hear you talking about all the time and I see it I see the green dot I see the presence I see the real-time nature and that's really what today's modern apps are all about and we'll talk about that today in detail what's under the hood for service now and again I can reiterate what a great software platform service now has I am super impressed the people here a passion about what they do Dave and I say you know we're going to get with Fred and here the founder story the prot chief product officer and all his folks because what they're building is the future generation Frank's Ludeman is a world-class CEO we heard the story of how he was hired you know Fred Letty said his keynote I wake up every day and I want to write code I don't want to be the CEO they hired Frank's luqman built a great business but not only do they have great business fundamentals and how they're executing their business plan Dave they have a great product leadership team the founder stays around every successful company that I talked to and i can highlight you look at them you name them all the ones that are the really sustainable companies Dave the founder stays around this is a lesson that the top VCS and Silicon Valley and around the world are now paying attention to is do not boot the founders out of the company marc andreessen with injuries Horowitz absolutely adamant founder friendly means growth and sustainability the old days of kick the founder out don't work ServiceNow is a great case study of a company that has grown from a seed idea go to market one booth at a show get some customers get some funding have a grade VC build a great product and continually to go to the next level and I think that's the story for us today what's the next level for service now what is that and you're going to see two major themes cloud born in the cloud capabilities asynchronous real-time presidents to enterprise grade enterprise-grade means you can't you can be born in the cloud and enterprise grade that's the Holy Grail Dave that is the key question people ask can you be enterprise-grade can you be agile can you have integrated stacks can you do stuff in real time and do it at a speed and at a scale that's the premise of the cloud and service now is delivering that so even my take on that so I mean you're talking about a cool tech behind it and there's a whole nother story here and Fred muddy and Dave right took us down memory lane today you know sort of the history of the company and going back to the original first knowledge and San Diego showed some pictures that was all fine and well and good but the fact is the piece that I want to add to what you just said is the customer angle I treated out yesterday Frank's lubin has made a career and identifying pain points and resolving those pain points essentially selling aspirin is what I call it and so that's what service now is doing there resolving the pain points within organizations it was interesting to note Dave right and Fred Lunney talked about how in 2008 when the economy was collapsing and Sequoia Capital you remember John put out that famous memo you better you hunker down conserve cash and Fred ludie showed the audience his counterpoint and basically it makes sense to me because what happened in 2008-2009 is people said let's let's start moving to the cloud more aggressively let's ship shift capex to op X and let's try to save money and service now is one of those technologies that really you know is all about saving money we kind of lived through that John right we were the open source version of information and so we have tons of demand around that time for our content service now in a whole different world saw uptick in demand and so they are really out solving customer problems dealing with process problems we're now seeing sort of the next wave the next evolution of that around email and how email is used as a workflow management system and is ineffective at that the hole forms business going to mobile and you saw today in the mobile apps it wasn't forms oriented it wasn't forms front and center forms is still there but it wasn't all about the forms it was all about the mobile experience so they're transitioning from this sort of forms based automation to one that's more mobile optimized that's something to talk to Fred yeah I think I think which day was your pointing out is is that the highlight of during a crisis at Fred Letty pointed out in OA at a critical inflection point of the company Sequoia Capital issued out a memo to all their portfolio come a little bit inside baseball but important to note that they said bunker down hunker down filled a bunker hoard your cash service now and this is where I love this company right they wrote a counter memo to their customers and the venture has a no no this is the winds are shifting we see an opportunity because their customers were going under or having financial problems they shifted their product value proposition to saving cash consolidation and creating an opportunity out of the crisis and I think this is the opportunity with cloud as you pointed out you seeing a transformation in workflows you're seeing a transformation in business process that is changing the game in terms of you know time to value cost structures and then the economics that's the promise of the cloud so again the companies that can take advantage of the times of the shifts and the inflection point because what's happening is the shift is happening and as an inflection point so yeah I think everybody talks about and it's so overused now seventy percent of the money that I t spends is on on keeping the lights on and and only thirty percent is on innovation I like to look it a little differently I like to break it down when i had my cio consultancy with floyer we used to consult and try to get the others to think about putting their portfolio into three categories their application portfolio in the project portfolio running the business growing the business in transforming the business and i think if you think about those things i think servicenow is very transformative and our helping companies run the business differently and grow the business as well so they're sort of fit into all three but they start with transformation and then change the way that people are running the business I think that's a much more effective way to look at that hole 7030 mix and I think service now is changing the way companies work what do you think about service now see earnings are we're out last week EMC report a little bit down VMware blew it away covering for emc you're seeing the big enterprise players service now take a big knife cut on Friday but that's Frank's lubin pointed out there in the long game and they have a platform play and they're throwing up a lot of cash so their cash flow is amazing Wall Street Journal has some articles about this kind of shift that we in a bubble is service now built for the long haul I want your opinion on this Frank subin weighed in on his and I think the software's phenomenal but let's talk about that yeah let's really his wall street not understanding about service so let's recap what happened on Friday service now announced earnings the stock had hit about a 12 billion dollar valuation which is you know sort of the highest valuation roughly that it had hit and people were getting used to service now continuingly continuously beating expectations well they met expectations actually beat by a little they had but they guided lower because of currency headwinds everybody's facing headwinds you saw EMC missed by about fifteen percent and it's you know this week and so all the companies and earnings releases are saying all right we're being more cautious because of currency fluctuations right the dollars getting stronger as a result you're translating international currency back into fewer dollars means less earnings so on an apples-to-apples basis servers now continued to blow it away they grew fifty percent plus but they guided lower they're a little bit more conservative so with the street did is they took about a billion dollars out of the valuation now since then it's come back a little bit it's not not come back to ten points to the loss but i see this john is a very very positive opportunity you said that you call it a buying opportunity i think it probably is you know who knows the markets choppy and maybe maybe you companies like service now that are high flyers you might see them you know up and down evan flow but here's the point and I think you've made this as well they are built for the long term and here's why they they started out in what everybody thought was a very small they've got a 40 to 50 billion dollar total available market that they're going after they're just scratching the surface right now they've got leading-edge technology they're killing the competition and they're growing into new places where typically these types of companies don't go the traditional IT service management folks where are they going they're automating service management not only with an IT but also within HR within finance within legal anything that's service oriented and their billet going after email if it's maybe it's be even bigger than a 40 or 50 billion dollar market so they got a big market they got great tech they got great management so I think there's a lot of room for this company to grow can they go to the collaboration space that's gonna be the question means all about email how much collaborative even ibn about competing with with this with companies like work they went all out HRM well well a CRM a Salesforce i think is a potential big competitor down the road i think they're on a collision course with force calm and Heroku and you know all those app development you know activities that those guys are doing but that's it's early there but I see that yeah damn your point about sales force this is why I think its dangers for sales forces why I think you know maybe we're kind of opening up the kimono here on service now because we're reading the tea leaves but what em what Amazon is done for the cloud and what we're doing with crouched at servicenow is doing for iit meaning they're building integrated technologies for a variety of different use cases that quite frankly it's it's enabling so sales forces cobbling together a bunch of stuff they got chatter I got this and when you put monolithic systems together and try to match them together into quote a you know fake stack that's really not going to work so I think the challenge for the incumbent companies like Salesforce and others is if you cobble together technologies and don't integrate them in there for this new real-time clouded native born in the cloud mentality and have the enterprise grade you will lose some territory so service now is doing both of those and they could take territory very quickly so they're humble saying no no we're not competing I know we got to go but last thing I'll say this frank says ITR our homies that's the Franks lupins you know so it talks about IT and the reason why I see that as a big advantages i T is the one part of the organization that has purview over the entire organization so a single cmdb with nit is very and whoever controls the data will be very interesting so real time having the data having the platform will give you a lot better horizontal platform I love what service now is doing again we're going to go this is our pep in by the way and this is not their messaging but we will probe all the guests Dave we're going to kick off date you this is our intro for day two wall-to-wall coverage when we hear all day here at in Las Vegas with service now nawlins 15 this is the cube I'm John for Dave vellante thanks for watching stay tuned and all day today thats is the cube we'll be right back after this short break