>> Voiceover: From theCUBE's Studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCUBE Conversation. >> Welcome back to theCUBE's coverage of the AWS Startup Showcase. Next Big Thing in AI, Security and Life Sciences featuring Ahana for the AI Trek. I'm your host, John Furrier. Today, we're joined by two great guests, Steven Mih, Ahana CEO, and Sachin Nayyar, Securonix CEO. Gentlemen, thanks for coming on theCUBE. We're talking about the Next-Gen technologies on AI, Open Data Lakes, et cetera. Thanks for coming on. >> Thanks for having us, John. >> Thanks, John. >> What a great line up here. >> Sachin: Thanks, Steven. >> Great, great stuff. Sachin, let's get in and talk about your company, Securonix. What do you guys do? Take us through, I know you've got a slide to help us through this, I want to introduce your stuff first then jump in with Steven. >> Absolutely. Thanks again, Steven. Ahana team for having us on the show. So Securonix, we started the company in 2010. We are the leader in security analytics and response capability for the cybermarket. So basically, this is a category of solutions called SIEM, Security Incident and Event Management. We are the quadrant leaders in Gartner, we now have about 500 customers today and have been plugging away since 2010. Started the company just really focused on analytics using machine learning and an advanced analytics to really find the needle in the haystack, then moved from there to needle in the needle stack using more algorithms, analysis of analysis. And then kind of, I evolved the company to run on cloud and become sort of the biggest security data lake on cloud and provide all the analytics to help companies with their insider threat, cyber threat, cloud solutions, application threats, emerging internally and externally, and then response and have a great partnership with Ahana as well as with AWS. So looking forward to this session, thank you. >> Awesome. I can't wait to hear the news on that Next-Gen SIEM leadership. Steven, Ahana, talk about what's going on with you guys, give us the update, a lot of stuff happening. >> Yeah. Great to be here and thanks for that such, and we appreciate the partnership as well with both Securonix and AWS. Ahana is the open source company based on PrestoDB, which is a project that came out of Facebook and is widely used, one of the fastest growing projects in data analytics today. And we make a managed service for Presto easily on AWS, all cloud native. And we'll be talking about that more during the show. Really excited to be here. We believe in open source. We believe in all the challenges of having data in the cloud and making it easy to use. So thanks for having us again. >> And looking forward to digging into that managed service and why that's been so successful. Looking forward to that. Let's get into the Securonix Next-Gen SIEM leadership first. Let's share the journey towards what you guys are doing here. As the Open Data Lakes on AWS has been a hot topic, the success of data in the cloud, no doubt is on everyone's mind especially with the edge coming. It's just, I mean, just incredible growth. Take us through Sachin, what do you guys got going on? >> Absolutely. Thanks, John. We are hearing about cyber threats every day. No question about it. So in the past, what was happening is companies, what we have done as enterprise is put all of our eggs in the basket of solutions that were evaluating the network data. With cloud, obviously there is no more network data. Now we have moved into focusing on EDR, right thing to do on endpoint detection. But with that, we also need security analytics across on-premise and cloud. And your other solutions like your OT, IOT, your mobile, bringing it all together into a security data lake and then running purpose built analytics on top of that, and then having a response so we can prevent some of these things from happening or detect them in real time versus innovating for hours or weeks and months, which is is obviously too late. So with some of the recent events happening around colonial and others, we all know cybersecurity is on top of everybody's mind. First and foremost, I also want to. >> Steven: (indistinct) slide one and that's all based off on top of the data lake, right? >> Sachin: Yes, absolutely. Absolutely. So before we go into on Securonix, I also want to congratulate everything going on with the new cyber initiatives with our government and just really excited to see some of the things that the government is also doing in this space to bring, to have stronger regulation and bring together the government and the private sector. From a Securonix perspective, today, we have one third of the fortune 500 companies using our technology. In addition, there are hundreds of small and medium sized companies that rely on Securonix for their cyber protection. So what we do is, again, we are running the solution on cloud, and that is very important. It is not just important for hosting, but in the space of cybersecurity, you need to have a solution, which is not, so where we can update the threat models and we can use the intelligence or the Intel that we gather from our customers, partners, and industry experts and roll it out to our customers within seconds and minutes, because the game is real time in cybersecurity. And that you can only do in cloud where you have the complete telemetry and access to these environments. When we go on-premise traditionally, what you will see is customers are even thinking about pushing the threat models through their standard Dev test life cycle management, and which is just completely defeating the purpose. So in any event, Securonix on the cloud brings together all the data, then runs purpose-built analytics on it. Helps you find very few, we are today pulling in several million events per second from our customers, and we provide just a very small handful of events and reduce the false positives so that people can focus on them. Their security command center can focus on that and then configure response actions on top of that. So we can take action for known issues and have intelligence in all the layers. So that's kind of what the Securonix is focused on. >> Steven, he just brought up, probably the most important story in technology right now. That's ransomware more than, first of all, cybersecurity in general, but ransomware, he mentioned some of the government efforts. Some are saying that the ransomware marketplace is bigger than some governments, nation state governments. There's a business model behind it. It's highly active. It's dominating the scene and it's a real threat. This is the new world we're living in, cloud creates the refactoring capabilities. We're hearing that story here with Securonix. How does Presto and Securonix work together? Because I'm connecting the dots here in real time. I think you're going to go there. So take us through because this is like the most important topic happening. >> Yeah. So as Sachin said, there's all this data that needs to go into the cloud and it's all moving to the cloud. And there's a massive amounts of data and hundreds of terabytes, petabytes of data that's moving into the data lakes and that's the S3-based data lakes, which are the easiest, cheapest, commodified place to put all this data. But in order to deliver the results that Sachin's company is driving, which is intelligence on when there's a ransomware or possibility, you need to have analytics on them. And so Presto is the open source project that is a open source SQL query engine for data lakes and other data sources. It was created by Facebook as part of the Linux foundation, something called Presto foundation. And it was built to replace the complicated Hadoop stack in order to then drive analytics at very lightning fast queries on large, large sets of data. And so Presto fits in with this Open Data Lake analytics movement, which has made Presto one of the fastest growing projects out there. >> What is an Open Data Lake? Real quick for the audience who wants to learn on what it means. Does is it means it's open source in the Linux foundation or open meaning it's open to multiple applications? What does that even mean? >> Yeah. Open Data Lake analytics means that you're, first of all, your data lake has open formats. So it is made up of say something called the ORC or Parquet. And these are formats that any engine can be used against. That's really great, instead of having locked in data types. Data lakes can have all different types of data. It can have unstructured, semi-structured data. It's not just the structured data, which is typically in your data warehouses. There's a lot more data going into the Open Data Lake. And then you can, based on what workload you're looking to get benefit from, the insights come from that, and actually slide two covers this pictorially. If you look on the left here on slide two, the Open Data Lake is where all the data is pulling. And Presto is the layer in between that and the insights which are driven by the visualization, reporting, dashboarding, BI tools or applications like in Securonix case. And so analytics are now being driven by every company for not just industries of security, but it's also for every industry out there, retail, e-commerce, you name it. There's a healthcare, financials, all are looking at driving more analytics for their SaaSified applications as well as for their own internal analysts, data scientists, and folks that are trying to be more data-driven. >> All right. Let's talk about the relationship now with where Presto fits in with Securonix because I get the open data layer. I see value in that. I get also what we're talking about the cloud and being faster with the datasets. So how does, Sachin' Securonix and Ahana fit in together? >> Yeah. Great question. So I'll tell you, we have two customers. I'll give you an example. We have two fortune 10 customers. One has moved most of their operations to the cloud and another customer which is in the process, early stage. The data, the amount of data that we are getting from the customer who's moved fully to the cloud is 20 times, 20 times more than the customer who's in the early stages of moving to the cloud. That is because the ability to add this level of telemetry in the cloud, in this case, it happens to be AWS, Office 365, Salesforce and several other rescalers across several other cloud technologies. But the level of logging that we are able to get the telemetry is unbelievable. So what it does is it allows us to analyze more, protect the customers better, protect them in real time, but there is a cost and scale factor to that. So like I said, when you are trying to pull in billions of events per day from a customer billions of events per day, what the customers are looking for is all of that data goes in, all of data gets enriched so that it makes sense to a normal analyst and all of that data is available for search, sometimes 90 days, sometimes 12 months. And then all of that data is available to be brought back into a searchable format for up to seven years. So think about the amount of data we are dealing with here and we have to provide a solution for this problem at a price that is affordable to the customer and that a medium-sized company as well as a large organization can afford. So after a lot of our analysis on this and again, Securonix is focused on cyber, bringing in the data, analyzing it, so after a lot of our analysis, we zeroed in on S3 as the core bucket where this data needs to be stored because the price point, the reliability, and all the other functions available on top of that. And with that, with S3, we've created a great partnership with AWS as well as with Snowflake that is providing this, from a data lake perspective, a bigger data lake, enterprise data lake perspective. So now for us to be able to provide customers the ability to search that data. So data comes in, we are enriching it. We are putting it in S3 in real time. Now, this is where Presto comes in. In our research, Presto came out as the best search engine to sit on top of S3. The engine is supported by companies like Facebook and Uber, and it is open source. So open source, like you asked the question. So for companies like us, we cannot depend on a very small technology company to offer mission critical capabilities because what if that company gets acquired, et cetera. In the case of open source, we are able to adopt it. We know there is a community behind it and it will be kind of available for us to use and we will be able to contribute in it for the longterm. Number two, from an open source perspective, we have a strong belief that customers own their own data. Traditionally, like Steven used the word locked in, it's a key term, customers have been locked in into proprietary formats in the past and those days are over. You should be, you own the data and you should be able to use it with us and with other systems of choice. So now you get into a data search engine like Presto, which scales independently of the storage. And then when we start looking at Presto, we came across Ahana. So for every open source system, you definitely need a sort of a for-profit company that invests in the community and then that takes the community forward. Because without a company like this, the community will die. So we are very excited about the partnership with Presto and Ahana. And Ahana provides us the ability to take Presto and cloudify it, or make the cloud operations work plus be our conduit to the Ahana community. Help us speed up certain items on the roadmap, help our team contribute to the community as well. And then you have to take a solution like Presto, you have to put it in the cloud, you have to make it scale, you have to put it on Kubernetes. Standard thing that you need to do in today's world to offer it as sort of a micro service into our architecture. So in all of those areas, that's where our partnership is with Ahana and Presto and S3 and we think, this is the search solution for the future. And with something like this, very soon, we will be able to offer our customers 12 months of data, searchable at extremely fast speeds at very reasonable price points and you will own your own data. So it has very significant business benefits for our customers with the technology partnership that we have set up here. So very excited about this. >> Sachin, it's very inspiring, a couple things there. One, decentralize on your own data, having a democratized, that piece is killer. Open source, great point. >> Absolutely. >> Company goes out of business, you don't want to lose the source code or get acquired or whatever. That's a key enabler. And then three, a fast managed service that has a commercial backing behind it. So, a great, and by the way, Snowflake wasn't around a couple of years ago. So like, so this is what we're talking about. This is the cloud scale. Steven, take us home with this point because this is what innovation looks like. Could you share why it's working? What's some of the things that people could walk away with and learn from as the new architecture for the new NextGen cloud is here, so this is a big part of and share how this works? >> That's right. As you heard from Sachin, every company is becoming data-driven and analytics are central to their business. There's more data and it needs to be analyzed at lower cost without the locked in and people want that flexibility. And so a slide three talks about what Ahana cloud for Presto does. It's the best Presto out of the box. It gives you very easy to use for your operations team. So it can be one or two people just managing this and they can get up to speed very quickly in 30 minutes, be up and running. And that jump starts their movement into an Open Data Lake analytics architecture. That architecture is going to be, it is the one that is at Facebook, Uber, Twitter, other large web scale, internet scale companies. And with the amount of data that's occurring, that's now becoming the standard architecture for everyone else in the future. And so just to wrap, we're really excited about making that easy, giving an open source solution because the open source data stack based off of data lake analytics is really happening. >> I got to ask you, you've seen many waves on the industry. Certainly, you've been through the big data waves, Steven. Sachin, you're on the cutting edge and just the cutting edge billions of signals from one client alone is pretty amazing scale and refactoring that value proposition is super important. What's different from 10 years ago when the Hadoop, you mentioned Hadoop earlier, which is RIP, obviously the cloud killed it. We all know that. Everyone kind of knows that. But like, what's different now? I mean, skeptics might say, I don't believe you, but it's just crazy. There's no way it works. S3 costs way too much. Why is this now so much more of an attractive proposition? What do you say the naysayers out there? With Steve, we'll start with you and then Sachin, I want you to like weigh in too. >> Yeah. Well, if you think about the Hadoop era and if you look at slide three, it was a very complicated system that was done mainly on-prem. And you'd have to go and set up a big data team and a rack and stack a bunch of servers and then try to put all this stuff together and candidly, the results and the outcomes of that were very hard to get unless you had the best possible teams and invested a lot of money in this. What you saw in this slide was that, that right hand side which shows the stack. Now you have a separate compute, which is based off of Intel based instances in the cloud. We run the best in that and they're part of the Presto foundation. And that's now data lakes. Now the distributed compute engines are the ones that have become very much easier. So the big difference in what I see is no longer called big data. It's just called data analytics because it's now become commodified as being easy and the bar is much, much lower, so everyone can get the benefit of this across industries, across organizations. I mean, that's good for the world, reduces the security threats, the ransomware, in the case of Securonix and Sachin here. But every company can benefit from this. >> Sachin, this is really as an example in my mind and you can comment too on if you'd believe or not, but replatform with the cloud, that's a no brainer. People do that. They did it. But the value is refactoring in the cloud. It's thinking differently with the assets you have and making sure you're using the right pieces. I mean, there's no brainer, you know it's good. If it costs more money to stand up something than to like get value out of something that's operating at scale, much easier equation. What's your thoughts on this? Go back 10 years and where we are now, what's different? I mean, replatforming, refactoring, all kinds of happening. What's your take on all this? >> Agreed, John. So we have been in business now for about 10 to 11 years. And when we started my hair was all black. Okay. >> John: You're so silly. >> Okay. So this, everything has happened here is the transition from Hadoop to cloud. Okay. This is what the result has been. So people can see it for themselves. So when we started off with deep partnerships with the Hadoop providers and again, Hadoop is the foundation, which has now become EMR and everything else that AWS and other companies have picked up. But when you start with some basic premise, first, the racking and stacking of hardware, companies having to project their entire data volume upfront, bringing the servers and have 50, 100, 500 servers sitting in their data centers. And then when there are spikes in data, or like I said, as you move to the cloud, your data volume will increase between five to 20x and projecting for that. And then think about the agility that it will take you three to six months to bring in new servers and then bring them into the architecture. So big issue. Number two big issue is that the backend of that was built for HDFS. So Hadoop in my mind was built to ingest large amounts of data in batches and then perform some spark jobs on it, some analytics. But we are talking in security about real time, high velocity, high variety data, which has to be available in real time. It wasn't built for that, to be honest. So what was happening is, again, even if you look at the Hadoop companies today as they have kind of figured, kind of define their next generation, they have moved from HDFS to now kind of a cloud based platform capability and have discarded the traditional HDFS architecture because it just wasn't scaling, wasn't searching fast enough, wasn't searching fast enough for hundreds of analysts at the same time. And then obviously, the servers, et cetera wasn't working. Then when we worked with the Hadoop companies, they were always two to three versions behind for the individual services that they had brought together. And again, when you're talking about this kind of a volume, you need to be on the cutting edge always of the technologies underneath that. So even while we were working with them, we had to support our own versions of Kafka, Solr, Zookeeper, et cetera to really bring it together and provide our customers this capability. So now when we have moved to the cloud with solutions like EMR behind us, AWS has invested in in solutions like EMR to make them scalable, to have scale and then scale out, which traditional Hadoop did not provide because they missed the cloud wave. And then on top of that, again, rather than throwing data in that traditional older HDFS format, we are now taking the same format, the parquet format that it supports, putting it in S3 and now making it available and using all the capabilities like you said, the refactoring of that is critical. That rather than on-prem having servers and redundancies with S3, we get built in redundancy. We get built in life cycle management, high degree of confidence data reliability. And then we get all this innovation from companies like, from groups like Presto, companies like Ahana sitting on double that S3. And the last item I would say is in the cloud we are now able to offer multiple, have multiple resilient options on our side. So for example, with us, we still have some premium searching going on with solutions like Solr and Elasticsearch, then you have Presto and Ahana providing majority of our searching, but we still have Athena as a backup in case something goes down in the architecture. Our queries will spin back up to Athena, AWS service on Presto and customers will still get served. So all of these options, but what it doesn't cost us anything, Athena, if we don't use it, but all of these options are not available on-prem. So in my mind, I mean, it's a whole new world we are living in. It is a world where now we have made it possible for companies to even enterprises to even think about having true security data lakes, which are useful and having real-time analytics. From my perspective, I don't even sign up today for a large enterprise that wants to build a data lake on-prem because I know that is not, that is going to be a very difficult project to make it successful. So we've come a long way and there are several details around this that we've kind of endured through the process, but very excited where we are today. >> Well, we certainly follow up with theCUBE on all your your endeavors. Quickly on Ahana, why them, why their solution? In your words, what would be the advice you'd give me if I'm like, okay, I'm looking at this, why do I want to use it, and what's your experience? >> Right. So the standard SQL query engine for data lake analytics, more and more people have more data, want to have something that's based on open source, based on open formats, gives you that flexibility, pay as you go. You only pay for what you use. And so it proved to be the best option for Securonix to create a self-service system that has all the speed and performance and scalability that they need, which is based off of the innovation from the large companies like Facebook, Uber, Twitter. They've all invested heavily. We contribute to the open source project. It's a vibrant community. We encourage people to join the community and even Securonix, we'll be having engineers that are contributing to the project as well. I think, is that right Sachin? Maybe you could share a little bit about your thoughts on being part of the community. >> Yeah. So also why we chose Ahana, like John said. The first reason is you see Steven is always smiling. Okay. >> That's for sure. >> That is very important. I mean, jokes apart, you need a great partner. You need a great partner. You need a partner with a great attitude because this is not a sprint, this is a marathon. So the Ahana founders, Steven, the whole team, they're world-class, they're world-class. The depth that the CTO has, his experience, the depth that Dipti has, who's running the cloud solution. These guys are world-class. They are very involved in the community. We evaluated them from a community perspective. They are very involved. They have the depth of really commercializing an open source solution without making it too commercial. The right balance, where the founding companies like Facebook and Uber, and hopefully Securonix in the future as we contribute more and more will have our say and they act like the right stewards in this journey and then contribute as well. So and then they have chosen the right niche rather than taking portions of the product and making it proprietary. They have put in the effort towards the cloud infrastructure of making that product available easily on the cloud. So I think it's sort of a no-brainer from our side. Once we chose Presto, Ahana was the no-brainer and just the partnership so far has been very exciting and I'm looking forward to great things together. >> Likewise Sachin, thanks so much for that. And we've only found your team, you're world-class as well, and working together and we look forward to working in the community also in the Presto foundation. So thanks for that. >> Guys, great partnership. Great insight and really, this is a great example of cloud scale, cloud value proposition as it unlocks new benefits. Open source, managed services, refactoring the opportunities to create more value. Stephen, Sachin, thank you so much for sharing your story here on open data lakes. Can open always wins in my mind. This is theCUBE we're always open and we're showcasing all the hot startups coming out of the AWS ecosystem for the AWS Startup Showcase. I'm John Furrier, your host. Thanks for watching. (bright music)

>> Narrator: Live, from Nice, France. It's theCUBE. Covering .NEXT Conference 2017 Europe. Brought to you by Nutanix. (techno music) >> Welcome back, I'm Stu Miniman and this is SiliconANGLE Media's production of theCUBE. Happy to have a welcome back to the program, CEO and Founder of Nutanix, Dheeraj Pandey. The keynote this morning, talking about how Nutanix really going from a traditional enterprise infrastructure company really becoming it's goal of being an iconic software company. So, Dheeraj, bring us up to speed as to you know, how Nutanix positioned itself for this future. >> Yeah, I think it's it's been a rite of passage because you can't start from AWS in day one. You have to sell books, and sell eCommerce. You know, you being in the eCommerce space. It was a 20 years journey for them before they could get into computing and people took them seriously. I mean, look at Apple with iPod, and then iPhone, and the iPad, and then iTunes and app store. And all that stuff was a journey of 15 years. You know, before they could really see that they've arrived. I think for us we had to build the form factor of an iPhone four so that people realize what this hyperconvergence thing was. Before we could go and ship an android as an operating system. 'Cause if hadn't android operating system come first... Just like Windows Mobile operating system was around for a while and nobody really understood how to really go and make money on it. I think we had to build a form factor first. And now that people grock it, now we can really go and make software out of this. And be swell software and make the android version of the iOS itself. And that's the thing. I think, as a company we're challenged to balance these paradoxes. Oh, I thought you were an appliance company and you believe in this Apple like finesse. Polish and attention to detail. How do you apply that to an android like the shboosh model where you leave it to others to go and build handsets and so on. I think that's the challenge that you've taken upon ourselves. Now inside, with the cloud service, we have a lot of control. With appliances, we have somewhat control because we at least know what our hardware is running on. But software we open it up. And opening it up, and yet not giving up on the attention to detail is the challenge that this company has to, actually, really go and undertake. We are looking at a lot of our tools and bill for certifications, and you know, passing the test. The litmus test for hardware and we're trying to figure out how to automate the heck out of it. Make them into cloud services. So that customers can now go an crowdsource certifications. So, there'll be some new paradigms that will emerge and the reason why we are well placed for those kinds of things is because our heritage is appliance. So now when we think of doing software a lot of the tooling, a lot of the automations, certifications, the attention to detail we had we'll need to go and make them into cloud services. We have some of them, like Cicer is a cloud service. X-ray is a cloud service. Foundation is a cloud service. So a lot of these services will then go and make the job of certifying an unknown piece of hardware easier, actually. I mean in fact, even day two and beyond we have what we can NCC which is a service that runs from within prism to do health checks. And every two hours you can do health checks. So if there's a new piece of hardware that we thought we just certified, we need to keep paranoid about it. Stay paranoid about it, and say, look is the hardware really the hardware we wanted it to be. So there's lots of really innovative things we can do as a company that really had the heritage of appliance to go and do software, as well. >> Yeah, absolutely people have always underestimated the interoperability required. Remember when server virtualization rolled out up the BIOS. You know, could make everything go horribly. Even, you know, containers could give you portability and run everywhere. Oh wait, networking and storage. There's considerations there. Do you think it's getting to a point from a maturation of the market that the software... You know, can you in the future take Nutanix to be a fully software company where you kind of let somebody else take care of the hardware pieces and then you just become their software. And then there's service software services. That seem like a likely future? >> Yeah, I think with the right tools, right level of automation, right level of machine learning, right level of talk-back. You know, I say talk-balk, I mean the fact that the hard beats are coming to us we understand what the customers are doing. And with the right level of paranoia day two and beyond. Which is NCC for example, it's, We call it Nutanix Cluster check. And it does like 350 odd health checks on a periodic basis. And it erases the load, and some things like that. With the right level of paranoia I think we can really go and make this work. And by the way, that's where design comes in. Like, how do you think of X-Ray as a service, and Foundation, and Cicer and NCC and so on. I think that's where the real design of a software company that is also not being callous about hardware comes in, actually. So I'm really looking forward to it. I think... it's not just about tech and products. It's also about go-to-market because go-to-market has a change too. I mean, the kind of packaging, and the kind of pricing, the kind of ELA's, sales compensation, channel programs, a lot of those things have to be revisited as well. As upstream engineering, you talk about, there's a lot of downstream go-to market engineering as well, that needs to be done. >> Now, when it comes to go-to-market, partnerships are key of course. There's the channel. You want to grow your sales channel, and grow a piece. But also from a technology standpoint, there's a comment I heard you make earlier this week. You know, Google has the opportunity to be kind of that next partner. As like Dell was a partner to give you pre-IPO credibility Dell's trusted you. Dell, you have Lenovo, you have IBM up on stage there. As a software company, who are the partners that help Nutanix kind of through this next phase? >> I think you mentioned some of them already. You know, the cloud vendors, though, obviously open up. And there will be new ones that'll open up over time as well. Where we're thinking about ways to blur the lines between public and private. Because I think the world, including the public cloud vendors have come to realize that. You know, you can't have silos. You can't have a public cloud that's separate from the private and so on. So being able to blur the lines, there'll be a lot of cloud partners for us as well. I think on the hardware side, we already talked about all of them, actually. Now, HP and Cisco are right now partners, in double quotes, because we go and make our software work on it, you know. But on some levels they'll probably also have to open up. And they're networking partners that've been working with you know, Arista is a good case in point. Lexi's another one. And security partners, like Palo Alto could be a large one over time because we think about what firewalls need to be look like in the next five years, and so on, you know. I think in every way, I look at even Apache foundation. Which is not really a company but the fact that we can really coop a lot of open source and build COM marketplace apps. Where the apps could be spun up in an on-prem environment and a single tenet on-prem environment. And you can drag and drop them into a side merchant intent environment. I think being able to go and do more with Apache. To me it's the... I would say, the biggest game changer for the company would be what else can we do with Apache? You know, 'cause we did a lot the first eight years. I mean, obviously, Linux is a big piece of our overall story, you know. Not just as hypervisor but a controller, and things like that is all Linux based. Which draws the pace of innovation of this company, actually. But beyond Linux, we've used Cassandra and ZooKeeper, RocksDB and things like that. What else can we do with Apache Spark, and Costco, and MariaDB, and things like that. I think we need to go and elevate the definition of infrastructure. To include databases and NoSQL systems, and batch processing hadoop, and things like that. All those things become a part of the overall marketplace story for us, you know. And that's where the really interesting stuff really comes in. >> How do you look at open source from a strategic standpoint from Nutanix? I think it's been phenomenal because we have then operated as a company that's bigger than we are. 'Cause otherwise, I mean, look at VMware. They don't have that goodness. Nor does Microsoft actually. I mean, Amazon is the only one that really goes and makes the best out of open source. >> Explain that, we say Microsoft had a huge push into open source. Especially, you know, kind of publicly the last two or three years. But they've been working on it, they've, you know, heavily embraced containers. You know, they've gone Kubernetes. You know, heavily. >> I'm going to give you examples. I think there's a lot of marchitecture. And what Microsoft is doing is open source. But, of course you know, Linux has to work on Hyper-V. So, that's a given. They cannot make a relevant stack without really making Linux work in Hyper-V. But they tried Hadoop on Windows. And Horton works actually on quartered Hadoop in Windows but there are not too many takers, as you see, you know. Containers will probably continue to make a lot of progress on Linux because of the LXD and LXC engines, and things like that. And there's a lot more momentum on the Linux side of containers then the LB on the Windows side containers >> And even Azure is running more Linux than they are Windows these days. >> Absolutely, now that being said, Azure Stack is still Azure Stack. It's still Hyper-V. It's still system centered, not user-centered and things like that. I think Microsoft software will really, really have to find itself. And change a lot of its thinking to really go and say we truly embrace open source like the way Amazon does. And like the way Facebook does. Like the way Nutanix does, I think. You know, it's a very different way we look at open source. We are much like Facebook and Amazon than someone else. I mean, VMware is way farther away from open source, in that sense. I mean vSphere, overall You know, I mean I would say that it probably is Linux based. ESX is Linux based from 17, 18 years ago. I am sure that curt path has been forked forever. And it's very hard for them to go and uptake from open source from overall upstream stuff actually. That we build, you know I mean, our stuff runs on a palm sized server. A palm sized server, imagine it. And that's where we put in a drone and that's the foundation of an edge cloud for us, in some sense. Our stuff runs on IBM power system because IBM was doing a lot of work with open source KVM that made it easy for us to port it to H-V, and so on. And so, I think H-V is a lot more momentum because it shares that overall core base of open source, as well. And I think, over time we'll do many more things with open source. Including in the platform space. >> Okay, how's Nutanix doing globally. You know, what more do you want to be doing. How would you rate yourself on kind of new tenent as a global company? >> I think it's a great question and it's one of those that's a double edged sword, actually. And I'll tell you what I mean by that. So when you stop growing, non-US business become 50%, 'cause that's pretty much the reflection of ID spend. Half the spend is outside the US, half the spend is within the US. Right from here is 65/35. Which is a very healthy place to be in, actually. I don't want to just think to change to like 50/50 end because that's a proxy for are we stop growing, actually. At the same time, I'd love to be shipping everywhere, because again, I've said that the definition of an enterprise cloud is even more relevant. And, you know, parts of the world that is not US, actually. In that sense, just being able to go and maintain that customer base outside the US. I mean, being able to do it. I mean, you know we recently sold a system in Myanmar, actually. And I was telling my friends that look, now I can die in piece because we have a system in Myanmar, you know. But the very fact that they are partners, and there's the channel community, and there's technology champion and their exports. There are certified people in these remote parts of the world. And the fact that we can support these customers successfully, says a lot about the overall reach of the technology. The fact that it's reliable, the fact that it's easy to use and spin up, and the fact that its easy to get certified on. I think is the core of Nutanix, so I feel good about those things, actually. >> You've reached a certain maturity of product marketed option and we've seen Nutanix starting to spread out into certain things sometimes we call adjacencies. You've talked about some of the different softer pieces. How do you manage the growth, the spread and make sure that, you know, simplicity. We were talking to Seneal this morning about absolutely you want simplicity but you also want to, you know. Where does Nutanix play and where don't they play? You know, where >> That's a great question So, there's a really good book that I was introduced to about two years ago. And it's also... There's some videos on YouTube about this book. It's called, The Founder's Mentality the YouTube video is called The Founder's Mentality, as well. And it talks about this very phenomenon that as companies grow they become complex. So they introduce a problem. It's called the Paradox of Growth. The thing that you want to do, really do, was grow. And that thing that you covered kills you. 'Cause growth creates complexity and complexity is a silent killer of growth. So the thing that you covered is the thing that kills you. And that is the Paradox of Growth, actually. You know, in very simple terms. And then it goes on to talk about what are the things you need to do because you started an insurgent company over time you started acting like you've arrived and you're incumbent now, all of a sudden. And the moment you start thinking like an incumbent you're done, in some sense. What are the headwinds, and what are the tailwinds that you can actually produce to actually stay an insurgent. I think there's some great lessons there about an insurgent mindset, and an owner's mentality and then finally, this obsessions for the front lining. How do you think about customers as the first, last thing. So, I think that's one of the guiding principles of the company. In how can we continue to imbibe the founder's mentality in there as well. Where every employee can be a founder, actually, without really having the founder's tag, and so on. And then internally, there's a lot of things we could do differently, in the way that we do engineering, in the way we do collaboration. I mean, these are all good things to revisit design. Not just the product design piece, but organizational design like what does it mean to have two PIDs a team, and microservices, and product managers, and prism developers and COM developers, assigned to two PIDs a team, and so on. QA developers and so on. So there's a lot of structure that we can put at scale. That continues to make us look small, continues to have accountability at a product manager level so that they act like GM's, as opposed to PM's. Where each of these two PIDs a team are like a quasi PNL. You know they, you can look at them very objectively and you can fund them. If they start to become too big you need to split them. If they are not doing too well, you need to go and kill them, actually. >> Alright, Dheeraj, last question I have for you. Enterprise cloud, I think, you know when it first came out as a term, we said, it was a little bit inspirational. What should we be looking for in a year to really benchmark and show as proof points that it's becoming reality. You know, from Nutanix. >> That's a great point. You know, obviously, when Gartner starts to use the term very close term, you know what I say. Used the term enterprise cloud operating system. And in one of the recent discourses I saw, enterprise cloud operating model. That's very similar to system, vs model, but the operating model of the enterprise cloud is based on the tenants of you know, web skilled engineering you know, the fact that things aren't in commodity servers. Everything is pure software and you have zero differentiation in hardware. And all those differentiation comes in pure software. Infrastructure is cold. All those things are not going away. Now how it becomes easy to use, so that you don't need PhD's to manage it is where consumer grade design comes in. And where you have this notion of prism and calmed that actually come to really help make it easy to use. I think this is the core of enterprise cloud itself, you know. I think, obviously, every layer in this overall cake needs more features, more capability, and so on. But foundationally, it's about web skilled engineering, consumer grade design. And if you're doing these two things getting more workloads, getting more geographies, getting more platforms, getting more features... All those things are basically a rite of passage. You know, you need to continue to do them all the time, actually. >> Alright, Dheeraj, I had a customer on. Said the reason he bought Nutanix was for that fullness of vision. So, always appreciate catching up with you. And we'll be back with lots more coverage here from Nutanix .NEXT, here in Nice, France. I'm Stu Miniman, and you're watching TheCUBE.

>> Live from the Julia Morgan Ballroom in San Francisco. Extracting the signal from the noise, it's TheCUBE. Covering Structure 2015. Now your host, George Gilbert. >> This is George Gilbert, we're at Structure 2015. Reborn and really healthy from the old GigaOM, and we're pleased to welcome Alex Polvi from CoreOS, everyone seems to want to talk to Alex these days. So we've got first dibs. Alex why don't you tell us a little bit about CoreOS and why it's of such relevance right now. >> Sure, so we started CoreOS a little over two years ago, about two and a half years ago now. And our mission is to fundamentally improve the security of the internet. And our approach in doing that is to help companies run infrastructure in this way that allows it to be much more serviceable and have much better security and so on. This way that we're modeling looks a lot like what we've seen from the hyperscale companies. Folks like Google. So we often call it Google's Infrastructure For Everyone Else, GIFFY for short 'cause that's kind of a mouthful. And that involves distributed systems, containers, and running on standard hardware which in 2015 can be a bare-metal server, or could be an instance in AWS. >> Okay. So help us understand though that, if CoreOS, it sounds like there's an operating system at the core. >> Yeah. >> Is this like a cut down version of Linux that gives it a small attack surface and a sort of easier deployment and patching? >> Exactly, so in our quest to run the world servers to secure the internet we start at the lowest level component possible. There's the OS, then there's the distributed system side. So CoreOS is our company name, but it's also the name of the first product that we released, CoreOS Linux. CoreOS Linux is a lightweight container-based OS that automatically updates itself, 'cause we think that updates are the key to good security. So it's a combination of the updates, the container weight, the lightweight container-based application model. As well as just stripping everything else out. I mean the last 20 years of Linux distributions have created lots of cruft so it was time to kind of rebirth a new lightweight Linux OS. >> Sticking to CoreOS >> Yeah. >> For a moment, in an earlier era, might we have called this like an embedded OS where you just sort of chopped out everything that was not necessary for the application? >> Yeah, it's very much inspired by embedded OSes. On servers you know, you really want to get everything out of the way of the resources like the memory and CPU and so on so you get as much as you want out of it. So while it's a little bit counterintuitive, you have this really monster server, you still want as light and thin of an OS on there as you possibly can like an embedded OS so you can really maximize the performance. >> So something that abstracts the hardware but gets out of the way. >> Exactly. Just focus, get on the things that matter which is running your applications and managing the actual hardware and really nothing else. >> Okay, so, presumably to provide Google's infrastructure for everyone else, and I don't remember the acronym, >> GIFFY. >> Okay. What other products did you have to fill out to make that possible? >> Sure, great question. So the next major piece that we released is a tool called ETCD. It's meant for doing shared configuration amongst servers. Whenever you have a group of servers, the first thing you need to do is they all need to know about each other, and tell each other about the configuration. This is load balancers knowing where the app servers are, the app servers knowing where the databases are and so on. And to do this in the most robust distributed systems way, you have to do this thing in computer science that's very difficult called "consensus". Consensus algorithms is an area of computing, actually speaking about here in a little bit with Eric Brewer, who is a huge academic, a very well respected engineer in the area of consenus and distributed systems. And so we built ETCD, which solves this really hard distributed systems problem in a way that's usable by many operations teams. >> So let me just interrupt you for a second, >> Yeah. >> I mean I've got this sound going off in my head that says "Zookeeper, Zookeeper". >> Exactly. It's Zookeeper for everyone else. >> It's simplified. >> It's a simplified Zookeeper and make it accessible. Areas that a lot of people wanted to use distributed systems but Zookeeper is a little bit too difficult to use as well as really oriented toward the Java and Hadoop community, and there's a whole wide array of other folks out there. >> So it couldn't make as many constraining assumptions as yours, which would simplify. >> It just couldn't be as widely adopted. And so we released ETCD around the same time we released CoreOS Linux and this point, there's been over a thousand projects if you go on GitHub that have built things around ETCD, so our bet was right. Even things like Kubernetes, itself has a hard dependency on ETCD. Without ETCD, Kupernetes will not run. So our hypothesis there was let's make the hardest part of distributed systems easier, and then we will see distributed systems overall accelerate. And that is definitely what's happened with ETCD. >> Okay so help us understand, how you've built up the rest of the infrastructure and then where you'd like to see it go. >> Sure, so the thing that we're targeting is this distributed systems approach. And again we care about this a lot because we think that the ability to manage and service your applications, is what is the key to the security. Keeping things up to date, and when we mean up to date, we don't just mean like patch a vulnerability. Of which we've fixed many of those. But it's also about company's comfort rolling out a new version of their application that they won't break something. If you run your infrastructure in a distributed system, you can roll out a version, if it breaks a little bit of the application that's okay, but you didn't take the whole thing down. And that's kind of the safety net that distributed systems give you. >> Does this require the sort of micro-service approach where there's a clean separation between this new set of bits and the rest of the app? >> It really does. And that's why we've invested so heavily in containers. It requires a container, it also requires the distributed systems components of it. So we first built CoreOS Linux, then we built ETCD, then we started building some distributed systems work very early in the market. And then things like Kubernetes came along, and we were like, "Hey, instead of us reinventing all of this stuff let's partner up with the guys from the Google" if we're monitoring Google's infrastructure for everyone else, let's partner up with the team at Google that built that and get their solution more widely adopted out in the world as well. So the whole platform comes together as this combination of Kubernetes, ETCD, CoreOS Linux, we have our own container runtime called Rocket, which we built primarily to address some security issues in Docker. And so all of these pieces come together and what we call that piece when they're all together is Tectonic. Tectonic is our product that is that Google's infrastructure in a box. >> Okay let me just drop down in the weed for a sec. Derek Collison calls, I'm sorry I'm having a senior moment. And I hope it's not early onset Alzheimer's. The Docker, he calls sort of this generation's Tarball, you know, like to distribute you know, just a sort of I guess equivalent of an executable. Are you providing something that's compatible or does what's inside the container have to change to take advantage of the additional services that's sort of Google-centric. >> Sure. So the packaging, that Tarball piece, we're compatible with. And will always remain compatible with. To even further the compatibility, we've put together standards around what that container should be so many vendors can inter-operate more widely. We've done that first through the app container project and then more recently through the open container initiative which is a joint effort between Docker and us, and the rest of the ecosystem. And so we always, we always want the user to be able to package their application once and then choose whatever system they want to run it in, and the container is what really unlocks that portability. >> Okay. So then let me ask you, does the Google compute engine folks, or the passgroup, do they view you as a way of priming the pump outside the Google ecosystem to get others using their sort of application model or their infrastructure model? Because I'm trying to understand, you know Azure sort of has its own way of looking at the world, Amazon has its own way of looking at the world, are they looking at you as a way of sort of disseminating an approach to building applications? Or managing applications. >> Sure. So the Google team and their motivations behind Kubernetes, you'd have to talk to them about it. My understanding is that they see that as a way to have a very consistent environment between different cloud providers and so on. It is a next-generation way of running infrastructure as well, and its just better than the previous way of running infrastructure. >> That's sort of the answer I was looking for which is, they don't have to either give away their stuff or manage their infrastructure elsewhere. But you're sort of the channel to deliver Google style infrastructure in other environments. >> Sure, I mean Google Cloud's motivation at the end of the day is selling cores of memory. They put all these other services on top of it to make it, to make it more attractive to use, but the end of the day anything that drives more usage of these products is how they run their business. At least that's my perception of it. I'm obviously not speaking on behalf of Google. >> So where are you in attracting showcase customers? Guys who've sort of said "okay we'll bet", if not the entire business, "we'll bet the success of this application or these set of applications on this". >> Right, so first the technology's been very, very exciting. I mean the past two years we've seen this whole space explode in interest, but the discussion around "how does this solve business problems, how does this actually get adopted to these companies and what motivates them to actually do this" outside of the tech being very cool. That's a discussion that is just getting started and in fact in about two weeks here in early December in New York we're hosting that discussion at an event called the Tectonic Summit. The Tectonic Summit is where we're bringing together all the enterprise early adopters that are using containers, using distributed systems, and talking about why did their management and their leadership decide to make investments in these technologies. And what we're seeing are use cases about multi-data center between your physical data center and your cloud environments. We're seeing folks build their next-generation web services. Many businesses that weren't traditionally in the web services businesses need to be now because of mobile, just modern product offerings. And so we're hearing from these large guys and how they're using our technologies and other companies' technologies today to do this, and it's just two weeks at our event. >> Would it be fair to say, I'm listening to this and what seems to becoming across is that your technology makes it easier to abstract not just the machine, which would be CoreOS, but hybrid infrastructure. And it doesn't even have to be hybrid, it could be this data center and that data center. >> Right. >> Or your own data center and a public cloud. >> Exactly. One of the biggest value props of all this is the consistency between environments. We just give this compute, CPUs, memory, storage, we don't care if it's on cloud or if it's a physical data center, we can allow you to manage that in an extremely consistent way. Not just between your data centers but also between development and production, and that's a really important part of all of this. >> Do you need a point of view built into the infrastructure to make it palatable to developers who want a platform? As opposed to just infrastructure. >> Sure. So one of the things that's most exciting about this space is we're splitting the difference of platform and infrastructure. Platform is typically, platform is a service, this very prescriptive way of running your server infrastructure. And there's raw infrastructure which is a like, "here is a canvas, go to town but you need to bring all your own tools". What's happening right now in this distributed systems container space is a middle category. It's still infrastructure, but it's application focused. And at the end of the day that's what a developer is trying to do, is deploy their application out into the server infrastructure. >> So it doesn't have an opinion that tells the developer "we think you should build it this way", but it does hide all the sort of, the different types of hardware and their location pretty much. >> Right, it gives you a prescriptive way to how you package and deploy that, but doesn't put on any constraints of what you can package or deploy. >> Okay. Very interesting. It's sort of like a, if platform as a service was constraining because developers didn't want a straightjacket for how they should build the app, and infrastructures, our service was too raw. You're giving them a middle ground. >> Exactly. It's still infrastructure, but it's a consistent way of running that infrastructure. And that's why companies like Google and Facebook and Twitter do this, they have millions of servers and data centers all over the world. >> And they can't prescribe. >> Well they need to be able to have a consistent way of doing it so that they don't have to have an infinitely growing operations team as they scale their infrastructure. You need to have consistency, but at the same time you need to be able to have a wide array of tools and things to deploy and interact with that infrastructure. So it's that middle ground, and that's why the hyperscale guys have adopted it because they're forced to, because they have to have that consistency to have that scale. >> Okay let me ask you then, not on the, separate from the hyperscale guys, the sort of newest distributed system that mainstream enterprises are struggling with and sort of off the record, maybe choking on, you know is Hadoop. Because they haven't had to do elastic infrastructure before and like you said the Zookeeper is not that easy, and there's 22 other projects by the way that also have to get stood up. Can you help someone who is perhaps flailing in that or if not flailing, finding the skills overhead really, really tough? >> So, Hadoop. Let's remember Hadoop's roots. Where did that come from? >> Well Yahoo!. >> Well but where did Yahoo! get the idea? >> Oh yeah, Google, sorry. >> Exactly. Yahoo! gets all the credit for it. Even though it was a Google paper that was modeled after. And so again, if Kubernetes and containers and everything is the equivalent of Google's borg, which is that raw application infrastructure, Hadoop is a certain application that consumes the spare resources on that cluster in order to do these map reducing computational jobs. >> So the next question is, how much can you simplify what mainstream enterprises do that don't have the Google infrastructure yet? >> Right, so they have to manage that as its own whole separate thing. It's its own set of infrastructure, it's its own set of servers to manage their Hadoop cluster. If you combine it with this application infrastructure, we just treat Hadoop as another application that runs on the platform. It's not its own distinct, special thing. It's just another application running out there along with your web servers and your databases, and everything else, you have your Hadoop workload in the mix. So you have this consistent pool of infrastructure and Hadoop is just another application that's monitored or managed the exact same way as everything else. >> So, for folks who are a little more familiar with Mesos, which is the opposite of a virtual machine, it makes many machines look like a single one, I assume. >> Well this is a very similar message to Mesos. Mesos is also building Google-like infrastructure for everyone else. The difference with what we're doing is really we just partnered up with the team that built that at Google, and focusing our solution around Kubernetes which is what the Google efforts are behind. So we're all modeling Google's infrastructure. >> Okay. >> Mesos took their own spin on it with Kubernetes, and CoreOS and ETCD, we're taking a different spin on it. >> So and what other products have you built out that we haven't touched on, and what do you see the roadmap looking like? >> Sure, so really, all these things we've talked about are open source projects. They're all components for building this Google-like infrastructure. Tectonic is our platform for companies that want this style of infrastructure but they don't want to have to figure out all the different pieces themselves. And we think once companies adopt Tectonic, just this general style of infrastructure, that we can give them all the benefits of this, better utilization, that consistency, easier management of lots and lots of servers and so on. But we also think we can dramatically improve the security of their infrastructure as well. And that's what we're investing in our roadmap is to leverage this kind of change, and then with that change we can do some things to the infrastructure that was never possible before. >> Okay. >> And that's the things that we're investing in as a company. >> Okay, great. We're going to break at that, this is George Gilbert, at Structure '15, with Alex Polvi of CoreOS. And we'll be back in just a few minutes. (light music)