Live from Boston, Massachusetts, extracting the signal from the noise. It's theCUBE, covering HP Big Data Conference 2015, brought to you by HP Software. Now, your hosts, John Furrier and Dave Vellante. Okay, welcome back everyone live here in Boston, Massachusetts, the Silicon Angles theCUBE, our flagship program. We go out to the events and extract the signal from the noise. I'm John Furrier, Silicon Angle. John, my coach Dave Vellante of wikibond.com. Here at the HP Big Data Conference, HP Big Data 2015 is the hashtag. Our next guest is Sudeep Venkatesh, VP of Solutions Architects at HP Security, part of the Voltage Security. Welcome to theCUBE. Thank you so much, it's great to be here. So we had the new worldwide sales guy on yesterday and he comes from the security group. Yes. And again, security is a big data problem. Waitin', I mean, just sittin' there. We can't go to a Big Data Conference without talking about it. I mean, security's headlining. Big Data is really the key weaponry right now to stop cyber attacks and other threats. Exactly, exactly. But Voltage Security and now, of course, HP Security Voltage takes a slightly different approach to this field. So what we're seeing with Big Data essentially is that deployments of Big Data are extremely hard to protect for a number of reasons. So that's the approach that we take. Some of the reasons for that include the fact that you have data from a number of disparate sources coming into your Hadoop deployments, for example. You have a number of analysts, for example, that need access to that data to make real value out of it. And the types of data that we're seeing that go into Hadoop systems are very different as well. So we work with telcos that put things like GPS data along with other personally identifiable information into it. We work with a large healthcare organization out of Connecticut, for example, that put a lot of healthcare information, things like social security numbers, prescription information, et cetera, into Hadoop as well. So our approach essentially is to protect that data at the data level itself, but still make it usable to the vast majority of consumers. So are you trapping on stuff or is it more of detection or a pattern recognition or both? Right, neither, neither. So when you think of security, security can come at it from various different angles. I mean, of course you have components like firewalls, you have components like malware detection, anti-virus detection, you can do IPS as well. But our whole value proposition is that you can build as high walls as you want, but attackers will still get beyond those. So our whole approach is to take data and move security close to the data by encrypting the data or tokenizing it, depending on what your needs are. So rather than being in IPS or malware or firewalls, of course all very essential technologies in the market, we actually go straight to the source, we could go to the data and then encrypt our token. So would it be safe to say that for companies that are looking at perimeter-less security models, this is one answer? Exactly, so it's the old cliche that the perimeter is no longer existing, data is moving into the cloud. API economy, people are accessing all kinds of variety. I mean, Stonebreaker said in the keynote here, variety of big data is a problem, which means, you believe that which is true, connecting to data sources means you're connecting. Exactly. And inside and out. Exactly, exactly. So where's the vulnerability? Is it the encryption key or do you somehow distribute the encryption key? Right. Can you talk, when I decrypt, can you talk about that? Right, that's a great point, that's a great point. So encryption is fairly easy to do with today's technology. The hard part is, how do you make sure that the keys are properly managed? So you need to make sure that the right people have access to the right keys. You need to make sure that if someone's changed their role, they no longer have access to that data by having access to the keys. So along with encryption at the data level, we also provide a key management service that's typically deployed at the customer side itself. The key management that we provide is called stateless key management. So in this case, we are not required to store keys, but we can generate keys on the fly as when required. So this can make it extremely scalable for even the largest organizations. So we solve the problem of encryption using this technology called Format Preserving Encryption. That's very interesting. And then we also solve the problem or the complexity that key management brought into an organization using the stateless key management concept. What is your take of this conference here? A lot of engineers here, it's not a security conference, it's not a developer conference, it's an engineer conference. A little bit DevOps, got a little bit of this, got a little bit of security. What's the conversation like here for the within the security paradigm that is needed out there? Is it embedded in naturally in every conversation or is it specifically brought out in certain use cases? Right, so what we are hearing a lot is that, especially when I'm talking to customers who come here. So not only the vendors obviously who come here but also customers, is that big data projects are stalling because of lack of security. Data that gives you the most value is also the most sensitive data within an organization. You can get maximum juice out of credit card number usage, out of prescription medication usage, out of people's GPS information, but that is also the most valuable information to an organization and also the most sensitive. So what we are hearing from customers, especially here, is that big data projects are being stopped by security teams because of lack of security. And that's where of course our products and our solutions come into play. So what's your take on Vertica's performance? We're hearing that's becoming a part of the reporting piece of it. Security to me seems like it needs a real time. Or can you have a slower moving layers of data, real time? You know what I'm saying? I'm trying to get at the Vertica piece of it. Where does that all fit in? Were you seeing the deployments or say the HP software in security the most? Yeah, right. So one of the problems with traditional ways of doing data level security was that the format of the data changed. So right if I took your social security number or your name and I encrypted it, then the format changed, which meant that it was extremely disruptive to the underlying Vertica deployment or to the underlying database deployment. And also you would need to constantly encrypt and decrypt that data to access it, which led to a lot of performance problems, which I think you're talking about. But what we can essentially do from the HP voltage side is we can take data elements and we can encrypt them, but retain the format. And what we're seeing is that 90 to 95% of business processes where you're running analysis, you're counting, you're doing searches, index, joins, et cetera, can happen on the protected data itself. And in that case, of course, security through encryption has zero impact on performance because you can run a lot of your queries on protected data because the format is retained and the properties are retained as well. So you preserve the format, you dynamically change the keys. We could do that, yes, yeah. So that's, is that fundamental to the architecture or not necessarily as an optional sort of? That's fundamental to the architecture. What do you make of these emerging approaches that are inspired by like the Bitcoin blockchain, like Enigma from MIT and others are trying to do that as well? Sure, so I mean, Bitcoin is obviously, you know, a slightly different topic with the currency that it tries to match. But a lot of the, you know, there are several companies out there that provide cryptography and that provide encryption, which was the equivalent of being developed in the back of a garage, right? So there's a lot of proprietary encryption out there. There's a lot of proprietary tokenization out there as well. One of the things that we've been almost fanatical about is the standardization of the encryption that we bring to the market. So what we advise customers on is that not all encryption is the same, right? You know, look for encryption technologies that are open, that have been peer reviewed, and most importantly, that have gone through the NIST certification process as well. So you're right.  But we always caution customers to really look at the provenance of that encryption and make sure it's coming from the right place and has been looked at by the right place. Yeah, well then these are more sort of whiteboard technologies now, you know, coming not so soon, right? But the idea of distributing, you know, using a blockchain type approach has been getting a lot of attention in different circles. Okay, so the other question I want to ask you is a security professional. A lot of times people say, well, security, we've failed, you know, it's a do-over, is that fair?  That's a great question actually. Obviously, you know, security at the end of the day is a control, right? It's providing a control to a business problem. What we're seeing now more and more is you're seeing an increase in attacks, you know, by folks who want to take your data and want to commercialize it illegally. You're seeing an increase in attacks by things like foreign intelligence agencies as well. So I think security has always been making steady progress in response to what technologies and what architectures it's protecting. But nowadays you're getting a lot of publicity, especially with the recent breaches that we've heard about in the enterprise space as well as with the federal government. Yeah, and I feel like, I mean, Stuxnet was a new high-water market and opened up Pandora's box. Right, exactly. So what's your take on the show here today? Give us, share with the audience out there why this show is so special. Yeah, I think it's been very interesting, talking to a lot of customers, seeing what innovations customers are doing. I know you spoke to one of our customers in Mar this morning, having good. So he is, they are a great example of where someone is really trying to monetize big data, make sense of it, but use security not as an inhibitor, but as a friend that helps you make progress there. So also I think there is a lot of desire amongst customers to move from, you know, demo or proof of concept systems of Hadoop to more production grade Hadoop. So they're sort of hungry, I would say, to look for new use cases to monetize their existing Hadoop deployments and also increase them into more production systems. So we heard from Robert Young-Johns about practicality, you know, trying to really level set the audience and the world that there's a lot of hype out there, a lot of noise. So as the solutions architect here, they're all working under the covers. How does someone prepare to kill two birds with one stone, so to speak, to where they can architect the big data platform, be scalable with large scale, whether it's bare metal, data center or cloud, enable the analytics to scale, and check the box on security. I mean, it's a tall order, but people are doing it. Can you share your thoughts on that? People are doing it, absolutely. And, you know, we are seeing a lot of customers doing it. We know that there is a lot of hype in this industry, obviously that's been obvious for the past couple of years, but we are seeing people do really big investments and big data and benefit from it as well. So for example, the healthcare organization that I was talking about in New England, they are building towards a thousand node deployment, a thousand node Hadoop deployment, and they're primarily using it to pick prescription for fraud and also catch on Medicare overpayments as soon as possible. The large telco that we spoke about is working towards a 2000 node Hadoop deployment, and they're putting all sorts of information. So they import something like 330 million records into Hadoop with 17 sensitive data elements in them that they protect with our technology, and this is everything from GPS information, location information, et cetera. We work with some large banks and they're putting a ton of credit card data into Hadoop. The marketing team obviously benefits from it to give their customers new offers, and they're also feeding that data into different fraud analysis as well. So yes, there's a lot of hype and a lot of talk about big data, but we're really seeing deployments that are of the hundreds of nodes, if not thousands, adding real business benefits and value. And speaking of John Mitchell Cloud, you got to ask to the Cloud question. So with a lot of people, and specifically as it relates to data, what a lot of the public Cloud guys are doing is trying to build data management pipelines that are integrated and deliver them as services, and you get the simplicity of that service, but maybe lack some of the functionality and maybe some of the ability to customize from a security standpoint. What's your take on the state of security for Cloud, specifically as it relates to data management? Yeah, absolutely. I mean, once data leaves an organization's parameter, then it is vulnerable to a whole different set of attacks outside as well. For example, if a Cloud provider gets breached, then that means that sensitive data from a particular enterprise would get breached as well. Sometimes we're seeing things like blind subpoenas where different governments would require a Cloud provider to supply all VMs or all hardware from a particular environment for forensic purposes. So that sort of only bears into our story of data-centric security. That if I take sensitive information like your social security number or your email address or other behavior patterns, and if I protect that using things like encryption and tokenization, it doesn't matter if that is proliferated into a thousand node Hadoop deployment. It doesn't matter if that is sent temporarily into AWS for doing an elastic map of these jobs. As you make your Hadoop more elastic, the security moves along with that data. So, you know, with large big data deployments, especially those in the Cloud, we're only seeing a validation of this data-centric approach that we have. And it doesn't matter if some government's looking at it other than the symbolic implication. Right, they only get tokenized data. Right, if a Cloud provider gets breached and they get to all the VMs, all they get is not your SSN, but a surrogate of it. Okay, well, thanks for sharing your insight on theCUBE. We really appreciate it. What do you expect to see in the next year? Last question. I think in the next year, we'll see a couple of things. So we'll see more and more organizations really figuring out what to do with their big data. So of course, everyone has gone. You know, one of the interesting terms that I heard yesterday was the data swamp, right? So we start off building a data lake, but it turned into a data swamp. So I think we will see a lot of organizations finally figuring out how to turn some of those swamps back into a very usable data lake. That's one thing that we, I hope to see in the next year. Well, we will see data oceans, that's our prediction, more dynamic, a lot more threats, a lot more currents, a lot more unpredictability. You got those rogue waves, obviously a security threat, that David couldn't help that. Again, it's live in Boston, so keep me right back up this short break.


Good afternoon. My name is Robert Askar. I'm the Prime Manager for OpenStack at NetApp. I've been working with OpenStack for about three and a half Years, so I've done this a few different times. And I thought we'd just go ahead and launch it. And we've got a total of about 15 minutes. So I just wanted to give you an overview of NetApp's Integration story with OpenStack. And a couple of the things that we have coming. Do a couple of short demos. So let's go ahead and get into it. So just to get a little bit of the groundwork and the way We think about something like an OpenStack at NetApp. We believe that we have a number of the technologies in place To create a common data fabric across endpoints. Will that be private cloud, public cloud in a hyperscale Sense or of course hosted private cloud or a number of Other boutique service providers. Of course we're familiar with some of the today's Hyperscale providers. The potential to actually host workloads that might have Actually been intended to land at an Amazon or perhaps In the future in Azure or a Google cloud platform. And of course most of this is shimmed presently in the form Of AWS and OpenStack. Any number of different OpenStack equivalents. Some of which may in over time in fact achieve some Of the same scale that you would see of a Google Of an Azure and perhaps over time even in Amazon. As I expect most folks are already aware here, there are Of course some high profile large public clouds already Based on OpenStack or at least the veiling OpenStack APIs. And of course a number of other small locales. It becomes that sort of common plane or at least Run time for infrastructure as a service above that Common data fabric that NetApp is executing upon. Just briefly on the prior slide our data on tap operating System is by most measures the single most prevalent Commercial storage operating system in the world. Of course NetApp is not the single largest provider of Storage but all of our platforms with a couple of Exceptions are based on this data on tap. And as such it's a good place to start and Building a common data fabric. To achieve the largest number of nodes possible. Familiar with metcast law and he given network as only as Useful as the number of nodes within so it's a good place to Start. A bit about open source at NetApp. That data on tap I referred to derives from BSD originally And of course we also are the primary employers of some Of the Linux maintainers around NFS. So OpenStack was an organic thing for us to settle upon. There are a number of different things that NetApp Differentiates within the market at large. No intention to go through all of these. But when we start in on something like a cinder Integration exercise we want to make sure none of it is left Behind. We're not a commodity storage device. There's a lot of differentiated capabilities. And something like a cinder is an abstraction. It allows you to write application logic to address a Single api for all block storage. But as such it's an abstraction to make sure that the things That we do differently whether it's various qualities of data Protection or storage efficiency, uptime availability, Protection security so and so forth that those are Explicitly accessible through that abstraction. So that's actually where we start when it comes to Cinder development. We've been at this for like I said a little while. I've been working with it for three and a half years. Our first integrations they viewed in the sx release And we've iterated upon it successively expanded. And in fact here in ice house we've debuted support for an Entirely new platform namely our e and e f series. An all flash version of our e series systems. Clustered on tap is a programmable capability. That's resident on many different modalities. Many different contexts whether it be on prem and a Host of private cloud sitting in front of foreign storage Meaning non adept storage or increasingly in the future As an end point at some of those hyper scale providers I mentioned earlier. So let's actually get into a little bit about open stack. And since I'm already talking at length let me speed along Here. Let's talk about glance.  Since we are talking about os bits deduplication tends To be very aggressive 90 plus percent is not uncommon. You can do that with either the object or the file back end But from a simplicity perspective file tends to be the Path of least resistance. When it comes to object storage we have an interesting Reference architecture on our e series platform which Possesses a I guess you could call it a node level Erasure coding capability. It's actually an alternative implementation of the crush Algorithm for those might be familiar. That allows you to mitigate the effect of long rebuild Times classically associated with raid. Why mention this? Well for swift by default uses a consistent hashing ring. That ring makes three copies by default within a single Site and of course more as you extend over multiple Sites. You wouldn't want to reconstitute over the WAN so you're talking about at least two copies at the Other end of it. Traditional raid or traditional parity scheme has Us long rebuild time. Since we've mitigated it with our dynamic dispools Technology I just talked about we're able to Dramatically reduce the actual consumption associated With storage of a single object. So it goes from 3x within a site to 1.3x. And of course that single site also becomes Immediately consistent. And I guess what you ultimately see is a pretty Significant reduction in cost of operation. Power cooling, floor space so and so forth Management associated. On the topic of block storage which of course where We started it goes without saying this is a Control plane activity. It's not the data path. One of the things that we work within the community on And in fact actually there's a session concurrent with This on the topic of the use of volume types within Cinder. You allow you to actually construct a catalog of Capabilities. So I earlier alluded to the fact that our Systems do things different than commodity storage That are different from them. And so how do you get at them? Well frankly you can you establish what's referred to As a volume type. It's arbitrary and then you compose it with what are Referred to as volume type extra specs. Which are the unique capabilities that a given Cinder back end can deliver. And so from that a requester of Cinder storage You know speaks to the api server and then the Cinder scheduler attempts to levy the request against The back end that's most appropriate given the Characteristics of what you of the type that You requested. So just a brief demonstration of establishing some Well actually we've already established the extra specs. This is an indication of some of them that have been Established as well as quality of service attributes. And I'm sorry I moved a little too fast with the Fingers there. What you'll see is that we've established a gold Silver and a bronze catalog if you will with Different attributes. There's quite a lot of option there in this particular Case we've aligned for example bronze to a sort of a Lowest common denominator storage option. Perhaps it's for ephemeral type use cases where you Really don't care about the qualities in your Aligned storage. And of course with a silver and a bronze we've Aligned different other things. You probably saw that we assigned quality of service Attributes a ceiling associated to a given type Such that you prevent a given tenant from exceeding That and of course there's a lot of different reasons Why you do so. You know prevent the the noisy neighbor syndrome but Also frankly don't deny yourself as a service provider If that is indeed who you are. The option of selling them something that's more Aligned to what they're actually consuming. So this is just sort of a depiction of what that Looks like with our e-Series driver. And then with our clustered on tap driver in this Case silver was composed with a replication characteristic So that when that occurs it went ahead and provisioned Into a container that has a replication policy. So there's a number of different options depending upon Which of our drivers you use. We avail both NFS and iSCSI. We help deliver NFS in the originally within the Community. Wrote the reference driver for the generic driver if You will. And you might ask well why NFS after all we are Talking about block storage service. It's simply vastly more scalable. You run out of initiators and loans well before you would Files in a given export. There's a variety of cloning advantages as well that Will get into a second. But we support paralyzed NFS for the first time in Icehouse by default if available and of course NFS has been around for a little bit. On our e-Series systems iSCSI presently and you Will look to expand upon those in the generative Time frame. So as it applies to okay creating new instances In opensack compute. Most of you may be familiar that a day in the life of a Given virtual machine exists as you know hey i'm Going to interrogate my fleet of hypervisors and Determine what's the most appropriate locale given The flavor and the image selected and once i've Done so if the image is not already there i copy it Over i have to actually curl it over htb copy it to The location which can be quite expensive now it is The case if you have a subsequent request you're Going to have the advantage of that one copy cached but It's only local to that specific hypervisor if you Have like i said a fleet of them that copy operation Occurs on the next one over and you know if you have Lots and lots of images this can be particularly Expensive so what we've delivered is a capability Where we can collate collocate glance and our Cinder backing store on the same system if it so Happens that they are not in the same system perhaps Swift is elsewhere and is actually the glance back End and senders on our systems we'll make that one Copy but that copy actually ends up being global to The entire fleet of hypervisors and i should also Point out that it's a boot from volume activity we're Looking at so it means that your volume your Your bootable volume is in fact not ephemeral By default it's persistent by default if you Have used cases that want an ephemeral instance Then select delete upon terminate you get the effect And i'd argue that it's far more effective to go from Persistent to ephemeral than it is to try to go from Ephemeral to persistent where your needs for a given Instance to have changed along the path so it's Significantly faster we clone aggressively are Being net of cloning technology no new no additional Space consumed until there's a net new writer Overwrite the effect is at least on the storage Component of the boot process of new instances is Essentially instantaneous not to say that you know the Boot process doesn't proceed and that doesn't take Time the storage component of is dramatically Sped when it comes to the array of storage services Within open stack we think there's a critical Emission in 2012 i believe it was idc Specified something like 65% of all storage sold In the market at large was for deployment of Shared file system so if you think of open stack Is the de facto open infrastructure service Capability there's a critical issue when it comes to Infrastructure as a service so shared file systems as a Service specifically so we've endeavored to create a new Service building community around it i should point out Called manila which does what for shared and distributed File systems what cinder does for block storage if you Know what cinder does then you know what manila does There's additional considerations for it and There's a little bit of additional complexity but Conceptually you're there so this is just a depiction of The addition a quick demo to show you that this is in Fact real on wednesday i believe it's a 10 a.m. We're going to have a session an hour long session that Is in fact actually community activity we have a number of Other vendors on stage with us demonstrating their Capabilities around manila so you know a net app Conceived of prototype develop you know contributed Capability but we are to be clear working with the broader Community and encourage encourage folks to join so you'll See some of those other folks on stage with us on wednesday Again not to go into the depth of manila since we don't Have the time here but it does exist those are the Horizon interfaces that's not smoking mirrors so it is Presently on the path to incubation we go in front of The technical committee well i don't have the exact date But sometime after this after the summit to get the official Not on it you can play with it you can deploy it today it's on Stack forage like i said on wednesday there's a pretty in Depth session so that's kind of a summary of what we've Done i mentioned in ice house that we debuted a couple of Capabilities support for our e-series and e-f which is An all-fresh array version thereof systems in the way of Cinder that reference architecture i talked about was Swift is in fact predicated on e-series a quality of e-series Underneath we default to paralyze nfs where available meaning The host os on the compute node the location of the Hypervisor must of course support it and of course we'll Negotiate it down to whatever version is in fact available i Talked about the the rapid instance creation efficient Creation we did an additional optimization we have a Capability that copy off loads where if in fact glance And cinder are not on the same net app systems we can actually Do an out of band copy between them directly instead of having To wash it through the host that's running the open stack Services and then we have a variety of reference Architectures and we endeavor to deliver both pop it in the Future chef automation with each of our reference Architectures so it's not just a simple exercise in Reading it it's an exercise in making it so Juno is a whole topic unto itself but more to come I've got a limited amount of time so i just wanted to get Into a little bit of some of the reasons why we see folks Deploying that app underneath open stack there's a Variety of different ones one is i've got a variety of Cloud native applications i've got a variety of like Classic posix applications and i want to deploy them on a Single highly available highly reliable infrastructure if i'm Only building like that entirely cloud native ephemeral Application then there are reasons why you might do so for Storage efficiency the total cost of operation in terms of Environmental sustainability perspective more often than not Most customers have a collection of both and to have Only one stuff pipe infrastructure for one style of Application tends to be rather expensive and we see a Lot of folks you know kind of moving towards this Hybrid cloud model when they want to repatriate from an a Ws when their workloads become more of a steady state and It's frankly do costly to keep it there or maybe to actually Like you know deploy it first on-prem and then be able to Burst out to so open stacks essential qualities of having Essential api compatibility with its equivalent a ws Services are attractive in that sense and i'm running out of Time but a variety of other reasons so we have a number Of reference architectures net app dot com slash open stack More to come we'll see you in france hopefully and follow us at Open stack net app and like i said net dot com sends you to Our deployment and operations guide or community some of the Reference architectures i discussed and there's some Other sessions this in these ensuing days that are of Relevance three of them on monday i'm sorry on wednesday And then a few of them other times in the week including net Apple feature in the nebula keynote and then likewise in the Triple-O session we address net up systems via ironic thanks Very much run over just a little bit so i greatly appreciate it Have a good day


Stevenson in the first game in the history of men's ice hockey here at Stevenson picks up a 7-1 win over Morrisville State Coach Dominic Dawes before we get to the hockey what a night what a crowd what an atmosphere what was it like just being a part of this it was obviously pretty exciting it's been kind of a long time coming I mean it was fun the guys they've worked hard to kind of start to build and establish a foundation here and I think all that hard work paid off tonight you know our goal was to go out there and just kind of work hard get pucks to the net and that's that's what we did and turned out to be pretty successful it was a dominant effort 51 13 advantage in shots goal scored early goal scored often on the power play for just about all but is there anywhere they look and say we could have done this better well I mean I think penalties were a big part of that game it seems to be the trend at in college hockey this year with kind of some new points of emphasis I think it takes a little bit of the flow out of the game but I think we responded well I think you could see how young we were at times in terms of some of the mistakes and just kind of getting stuck and slow and but I think we responded well and we kind of played a full 60 minutes which is nice seven goals six goal scores the distribution of the puck I'm sure you got to be pretty happy with yeah I know I mean it was it's hey anytime guys are putting the puck in the net is a is a good thing but it was you know good start for guys to get some confidence and see what the level of play is about and see what kind of college hockey is about I think we got quite a few that are banged up in the room there which is all part of this so it was a good you know something to build upon and then you turn around and you got to play the same team tomorrow really quick turn around 5 30 on Saturday what you know I do you have to remind the team hey don't don't think too high and mighty yourselves it's just a brand new game tomorrow I mean we talk about that every period because we're gonna face so many different situations and so many ups and downs as the year goes on we've tried to like look at every period as a as a new game and a new challenge and I think they did a pretty good job at doing that tonight so tomorrow's a new day and we'll we'll go from there it's pretty special for the first one congratulations coach thank you very much coach Dominic Dawes I'm Glenn Clark for sfm sports net