Breaking Analysis: Thinking Outside the Box...AWS signals a new era for storage
from the cube studios in palo alto in boston bringing you data-driven insights from the cube and etr this is breaking analysis with dave vellante by our estimates aws will generate around nine billion dollars in storage revenue this year and is now the second largest supplier of enterprise storage behind dell we believe aws storage revenue will hit 11 billion in 2022 and continue to outpace on-prem storage growth by more than a thousand basis points for the next three to four years at its third annual storage day event aws signaled a continued drive to think differently about data storage and transform the way customers migrate manage and add value to their data over the next decade hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we'll give you a brief overview of what we learned at aws's storage day share our assessment of the big announcement of the day a deal with netapp to run ontap natively in the cloud as a managed service and we'll share some new data on how we see the market evolving with aws executive perspectives on its strategy how it thinks about hybrid and where it fits into the emerging data mesh conversation let's start with a snapshot of the announcements made at storage day now as with most aws events this one had a number of announcements and introduced them at a pace that was predictably fast and oftentimes hard to follow here's a quick list of most of them with some comments on each the big big news is the announcement with netapp netapp and aws have engineered a solution which ports the rich netapp stack onto aws and will be delivered as a fully managed service this is a big deal because previously customers either had they had to make a trade-off they had a settle for cloud-based file service with less functionality than you could get with netapp on-prem or it had to lose the agility and elasticity of the cloud and the whole pay-by-the-drink model now customers can get access to a fully functional netapp stack with services like data reduction snaps clones the full multi-protocol support replication all the services ontap delivers in the cloud as a managed service through the aws console our estimate is that 80 of the data on-prem is stored in file format and that's not the revenue but that's the data and we all know about s3 object storage but the biggest market from a capacity standpoint is file storage you know this announcement reminds us quite a bit of the vmware cloud on aws deal but applied to storage netapp's aunt anthony lai told me dave this is bigger and we're going to come back to that in a moment aws announced s3 multi-region access points it's a service that optimizes storage performance it takes into account latency network congestion and the location of data copies to deliver data via the best route to ensure our best performance this is something we've talked about for quite some time using metadata to optimize that that access aws also announced improvements to s3 tiering where it will no longer charge for small objects of less than 128k so for example customers won't be charged for most metadata and other smaller objects remember aws years ago hired a bunch of emc engineers and those guys built a lot of tiering functionality into their boxes and we'll come back to that later in this episode aws also announced backup and monitoring tools to ensure backups are in compliance with regulations and corporate edicts this frankly is table stakes and was was overdue in my view aws also made a number of other announcements that have been well covered in the press around block storage and simplified data migration tools so we'll leave that to your perusal through other outlets i want to come back to the big picture on the market dynamics now as we've reported in previous breaking analysis segments aws storage revenue is on a path to 10 billion dollars we reported this last year this chart puts the market in context it shows our estimates for worldwide enterprise storage revenue in the calendar year 2021. this data is meant to include all storage revenue including primary secondary and archival storage and related maintenance services dell is the leader in the 60 billion market with aws now hot on its tail with 15 of the market in terms of the way we've cut it now in the pre-cloud days customers would tell us our storage strategy is the following we buy emc for block and netapp for file keeping it simple while remnants of this past habit continue the market is definitely changing as you can see here the companies highlighted in red represent the growing hyperscaler presence and you can see in the pi on the right they now account for around 25 percent of the market and they're growing much much faster than the on-prem vendors well over that thousand basis points when you combine them all a couple of other things to note in the data we're excluding kindrel from ibm's figures that's ibm spinout but including our estimates of storage software for example spectrums protect that is sold as part of the ibm cloud but not reported in ibm's income statement by the way pre-kindred spin ibm storage business we believe would approach the size of netapp's business now in the yellow we've highlighted the portion of hyper-converged that comprises storage this includes vmware nutanix cisco and others vmware and nutanix are the largest hci players but in total the storage piece of that market is less than two billion okay so the way to look at this market is changing traditional on-prem is vying for budgets with cloud storage services which are rapidly gaining presence in the market and we're seeing the on-prem piece evolve of course into as a service models with hpe's green lake dell's apex and other on-prem cloud-like models now let's come back to the netapp aws deal netapp as we know is the gold standard for file services they've been the market leader for a long long time and other than pure which is considerably smaller netapp is the one company that consistently was able to beat emc in the market emc developed its its nas business and developed on its own nasdaq and it bought isilon to compete with netapp with isilon's excellent global file system but generally netapp remains the best file storage company today now emerging disruptors like cumulo vast weka they would take issue with this statement and rightly so as they have really promising technology but netapp remains the king of the file hill you can't debate that now netapp however has had some serious headwinds as the largest independent storage player as seen in this etr chart the data shows a nine-year view of netapp's presence in the etr survey presence is referred to by etr as market share it's not traditional market share it measures the pervasiveness of responses in the etr survey over a thousand customers each quarter so the percentage of mentions essentially that netapp is getting and you can see well netapp remains a leader it has had a difficult time expanding its tam and it's become frankly less relevant in the eye in the grand scheme and the grand eyes of it buyers the company hit headwinds when it began migrating its base to ontap 8 and was late riding a number of new waves including flash but generally it is recovered from those headwinds and it's really now focused on the cloud opportunity opportunity as evidenced by this deal with aws now as i said earlier netapp evp anthony lai told me that this deal is bigger than vmware cloud on aws like me you may be wondering how can that be vmware is the leader in the data center it has half a million customers its deal with aws has been a tremendous success as seen in this etr chart the data here shows spending momentum or net score from when vmware cloud on aws was picked up in the etr surveys with a meaningful n which today is approaching 100 responses in the survey the yellow line is there for context it's vmware's overall business so repeat it buyers who responded vmware versus specifically vmware cloud on aws so you see vmware overall has a huge presence in the survey more than 600 n the red line is vmware cloud on aws and that red dotted line you see that that's that's my magic 40 mark anything above that line we consider elevated net score or spending velocity and while we saw some deceleration earlier this year in that line that top line for vmware cloud vmware cloud and aws has been consistently showing well in the survey well above that 40 percent line so could this netapp deal be bigger than vmware cloud on aws well probably not in our view but we like the strategy of netapp going cloud native on aws and aws's commitment to deliver this as a managed service now where could get interesting is across clouds in other words if netapp can take a page out of snowflake and build an abstraction layer that hides the underlying complexity of not only the aws cloud but also gcp and azure where you log into the netapp cloud netapp data cloud if you will just go ahead and steal steal it from snowflake and then netapp optimizes your on-prem your aws your azure and or your gcp file storage we see that as a winning strategy that could dramatically expand netapp's tam politically it may not sit well with aws but so what netapp has to go multi-cloud to expand that tam when the vmware deal was announced many people felt it was a one-way street where all the benefit would eventually accrue to aws in reality this has certainly been a near-term winner for aws and vmware and of course importantly vmware and aws join customers now longer term it's going to clearly be a win for aws because it gets access to vmware's customer base but we also think it will serve vmware well because it gives the company a clear and concise cloud strategy especially if it can go across clouds and eventually get to the edge so with this netapp aws deal will it be as big probably not in our view but it is big netapp in our view just leapfrogged the competition because of the deep engineering commitment aws has made this isn't a marketplace deal it's a native managed service and we think that's pretty huge okay we're going to close with a few thoughts on aws storage strategy and some other thoughts on hybrid talk about capturing mission critical workloads and where aws fits in the overall data mesh conversation which is one of our favorite topics first let's talk about aws's storage strategy overall as with other services aws approach is to give builders access to tools at a very granular level that means it does mean a lot of apis and access to primitives that are essentially building blocks while this may require greater developer skills it also allows aws to get to market quickly and add functionality faster than the competition enterprises however where they will pay up for solutions so this leaves some nice white space for partners and also competitors and especially the on-prem folks but let's hear from an aws executive i spoke to milan thompson bucheveck an aws vp on the cube and asked her to describe aws's storage strategy here's what she said play the clip we are dynamically and constantly evolving our aws storage services based on what the application and the customer want that is fundamentally what we do every day we talked a little bit about those deployments that are happening right now dave that is something that idea of constant dynamic evolution just can't be replicated by on-premises where you buy a box and it sits in your data center for three or more years and what's unique about us among the cloud services is again that perspective of the 15 years where we are building applications in ways that are unique because we have more customers and we have more customers doing more things so you know i i've said this before uh it's all about speed of innovation dave time and change wait for no one and if you're a business and you're trying to transform your business and base it on a set of technologies that change rapidly you have to use aws services i mean if you look at some of the launches that we talk about today and you think about s3's multi-region access points that's a fundamental change for customers that want to store copies of their data in any number of different regions and get a 60 performance improvement by leveraging the technology that we've built up over over time the the ability for us to route to intelligently router requests across our network that and fsx for netapp ontap nobody else has these capabilities today and it's because we are at the forefront of talking to different customers and that dynamic evolution of storage that's the core of our strategy so as you hear and can see by milan's statements how these guys think outside the box mentality at the end of the day customers want rock solid storage that's dirt cheap and lightning fast they always have and they always will but what i'm hearing from aws is they think about delivering these capabilities in the broader context of an application or a business think deeper business integration not the traditional suppliers don't think about that as well but the services mentality the cloud services mentality is different than dropping off a box at a loading dock turning it over to a professional services organization and then moving on to the next deal now i also had a chance to speak with wayne dusso he's another aws vp in the storage group wayne do so is a long time tech athlete for years he was responsible for building storage arrays at emc aws as i said hired a bunch of emcs years ago and those guys did a lot of tiered storage so i asked wayne what's the difference in mentality when you're building boxes versus cloud services here's what he said you have physical constraints you have to worry about the physical resources on that device for the life of that device which is years think about what changes in three or five years think about the last two years alone and what's changed can you imagine having being constrained by only uh having boxes available to you during this last two years versus having the cloud and being able to expand or contract based on your business needs that would be really tough right and it has been tough and that's why we've seen customers from every industry accelerate uh their use of the cloud during these last two years so i get that so what's your mindset when you're building storage services and data services so so each of the surfaces that we have in object block file movement services data services each of them provides very specific customer value in each are deeply integrated with the rest of aws so that when you need object services you start using them the integrations come along with you when if you're using traditional block we talked about ebs io2 block express when using file just the example alone today with ontap you know you get to use what you need when you need it and the way that you're used to using it without any concern so so the big difference is no constraints in the box but lots of opportunities to blend in with other services now all that said there are cases where the box is gonna win because of locality and and physics and latency issues you know particularly where latency is king that's where a box is gonna be advantageous and we'll come back to that in a bit okay but what about hybrid how does aws think about hybrid and on-prem here's my take and then let's hear from milan again the cloud is expanding it's moving out to the edge and aws looks at the data center as just another edge node and it's bringing its infrastructure as code mentality to that edge and of course to data centers so if aws is truly customer centric which we believe it is it will naturally have to accommodate on-prem use cases and it is doing just that here's how milan thompson-bucheveck explained how aws is thinking about hybrid roll the clip for us dave it always comes back to what the customer is asking for and we were talking to customers and they were talking about their edge and what they wanted to do with it we said how are we going to help and so if i just take s3 for outposts as an example or ebs and outposts you know we have customers like morningstar and morningstar wants outposts because they are using it as a step in their journey to being on the cloud if you take a customer like first adudabi bank they're using outposts because they need data residency for their compliance requirements and then we have other customers that are using outposts to help like dish networks as an example to place the storage as close as account to the applications for low latency all of those are customer driven requirements for their architecture for us dave we think in the fullness of time every customer and all applications are going to be on the cloud because it makes sense and those businesses need that speed of innovation but when we build things like our announcement today of fxs for netapp ontap we build them because customers asked us to help them with their journey to the cloud just like we built s3 and evs for outposts for the same reason so look this is a case where the box or the appliance wins latency matters as we said and aws gets that this is where matt baker of dell is right it's not a zero-sum game this is especially accurate as it pertains to the cloud versus on-prem discussion but a budget dollar is a budget dollar and the dollar can't go to two places so the battle will come down to who has the best solution the best relationships and who can deliver the most rock solid storage at the lowest cost and highest performance let's take a look at mission critical workloads for a second we're seeing aws go after these it's doing a database it's doing it with block storage we're talking about oracle sap microsoft sql server db2 that kind of stuff high volume oltp transactions mission critical work now there's no doubt that aws is picking up a lot of low hanging fruit with business critical workloads but the really hard to move work isn't going without a fight frankly it's not going that fast aws and mace has made some improvements to block storage to remove some of the challenges related but generally we see this is a very long road ahead for aws and other cloud suppliers oracle is the king of mission critical work along with ibm mainframes and those infrastructures generally it's not easy to move to the cloud it's too risky it's too expensive and the business case oftentimes isn't there because very frequently you have to freeze applications to do so what generally what people are doing is they're building an abstraction layer over that putting that abstraction layer maybe in the cloud building new apps that can connect to the back end and the into the cloud but that back end is largely cemented and fossilized look it's all in the definition no doubt there's plenty of mission critical work that is going to move but just really depends on how you define it even aws struggles to move its most critical transaction systems off of oracle but we'll continue to keep an open mind there it's just that today we define the most mission-critical workloads as we define them we don't see a lot of movement to the hyperscale clouds and we're going to close with some thoughts on data mesh so one of our favorite topics we've written extensively about this and interviewed and are collaborating with jamaa dagani who has coined the term and we've announced a media collaboration with the data mesh community and believe it's a strong direction for the industry so we wanted to understand how aws thinks about data mesh and where it fits in the conversation here's what milan had to say about that play the clip we have customers today that are taking the data mesh architectures and implementing them with aws services and dave i want to go back to the start of amazon when amazon first began we grew because the amazon technologies were built in microservices fundamentally a data match is about separation or abstraction of what individual components do and so if i look at data mesh really you're talking about two things you're talking about separating the data storage and the characteristics of data from the data services that interact and operate on that storage and with data mesh it's all about making sure that the businesses the decentralized business model can work with that data now our aws customers are putting their storage in a centralized place because it's easier to track it's easier to view compliance and it's easier to predict growth and control costs but we started with building blocks and we deliberately built our storage services separate from our data services so we have data services like lake formation and glue we have a number of these data services that our customers are using to build that customized data mesh on top of that centralized storage so really it's about at the end of the day speed it's about innovation it's about making sure that you can decentralize and separate your data services from your storage so businesses can go faster so it's very true that aws has customers that are implementing data mess data mesh data mess data mesh can be a data mess if you don't do it right jpmorgan chase is a firm that is doing that we've we've covered that they've got a great video out there check out the breaking analysis archive you'll see that hellofresh has also initiated a data mesh architecture in the cloud and several others are starting to pop up i think the point is the issues and challenges around data mesh are more organizational and process related and less focused on the technology platform look data by its very nature is decentralized so when mylan talks about customers building on centralized storage that's a logical view of the storage but not necessarily physically centralized it may be in a in a hybrid device it may be a copy that lives outside of that same physical location this is an important point as jpmorgan chase pointed out the data mesh must accommodate data products and services that are in the cloud and also on-prem it's got to be inclusive the data mesh looks at the data store as a node on the data mesh it shouldn't be confined by the technology whether it's a data warehouse a data hub a data mart or an s3 bucket so i would say this while people think of the cloud as a centralized walled garden and in many respects it is that very same cloud is expanding into a massively distributed architecture and that fits with the data mesh architectural model as i say the big challenges of data mesh are less technical and more cultural and we're super excited to see how data mesh plays out over time and we're really excited to be part of part of the the community and a media partner of the data mesh community okay that's it for now remember i publish each week on wikibon.com and siliconangle.com and these episodes they're all available as podcasts all you do is search for breaking analysis podcasts you can always connect on twitter i'm at d vellante or email me at david.velante at siliconangle.com i appreciate the comments you guys make on linkedin and don't forget to check out etr.plus for all the survey action this is dave vellante for the cube insights powered by etr be well and we'll see you next time [Music] you
SUMMARY :
and the dollar can't go to two places so
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Faizan Buzdar, Box | Google Cloud Next 2018
>> Live from San Francisco, it's theCUBE, covering Google Cloud Next 2018. Brought to you by Google Cloud and it's ecosystem partners. >> Hey, welcome back everyone. We're live in San Francisco for Google Cloud's conference Next 18, #GoogleNext18. I'm John Furrier with Dave Vellante. Our next guest is Faizan Buzdar, Senior Director at Box, box.com, collaborative file sharing in the Cloud. No stranger to Cloud. Welcome to theCUBE. >> Thank you for having me. >> So you guys have a relationship with Google. First talk about the relationship with Google, and you have some breakouts you're doing on machine learning, which I want to dig into, but. Take a step back. Take a minute to explain the relationship between Box and Google Cloud. >> So Box has partnered Google for a few years now, and we have actually two areas of key, sort of, collaboration. One is around the Google Productivity Suite that was actually announced last year. But we actually demoed it for the first time in public today. Where, if you look at a bunch of customers, like about 60% of the Fortune 500, that chose Box as their secure content layer. These guys can now go into Box and say, "Create a new Google doc, Google spreadsheet, Google slide." And it will open up. It will fire up the Google editors. You can do, get all of the benefit of the rich editing, collaboration, but your content is long-term stored in Box. So it does not leave Box. So from a security and compliance layer, if you've chosen Box, you now get to use all of the power of the Google collaboration and >> It's Google Drive inside Google Box, but natively, you guys have the control for that backend, so the user experience feels native. >> Yeah, so in this case it doesn't touch Google Drive. It's basically, it never leaves Box. So that's the key benefit if you're a Box customer. >> That's awesome. That's great for the user. Great for you guys. That's awesome. Okay, so take a step back now. What's your role there? What do you do? >> So I'm Senior Director for Product Management, and I basically look after two areas. One is our sort of best of breed integration strategies, such as the one with Google Suite or Gmail. And then the second area is machine learning, especially as machine learning relates to specific business process problems in the Enterprise. So that's one of the areas that I look after. >> So how do you use data? You talked about the integration. How are you using data to solve some of those business process problems? Maybe give some examples, and tie it back into the Google Cloud. >> So, for example, so for us, we announced a product called Box Skills last year at BoxWorks. And we're going to talk about it next month at BoxWorks, too. So, the strategy there was we will bring the best of breed machine learning to apply to your content in Box, and we will take care of all of the piping. So, I keep hearing machine learning is the new electricity. But if you talk to CIOs, it's a weird kind of electricity for them because it actually feels like I have to uproot all of my appliances in factory, and take it to where the electricity is. It doesn't feel like electricity came to my factory, right? Or appliances or whatever. So, our job, we looked at it, and we said, "Hey, we have probably one of the biggest, most valuable repositories of content, Enterprise content. How do we enable it so that companies can use that without worrying about that?" So Box Skills actually has two components to it. One is what we would call, sort of, skills that are readily available out of the box. So as an example, today we are in beta with Google Vision. And the way that the admin turns that on is literally, he goes into his admin panel and he just turns on two check boxes, chooses which folders to apply it to, maybe apply it to all of the images in the Enterprise. So if you're a marketing company, now all of your images start to show these tags, which were basically returned by Google machine learning. But to the end user, it's still Box, they're still looking at their images, it still has all of those permissioning, it's just that now, we have the capability for metadata, for humans to add metadata manually, now that metadata is being added by machine learning. But in terms of adoption for the Enterprise, we made it super simple. And then, the framework also enables you to connect with any sort of best of breed machine learning. And we look at it, if you were to sort of make a, look at it as two axis, number of users that would use it, and the amount of business value that it brings. There are some things which are horizontal, like, say, the basic Google Vision, basic Google Video, basic Google Audio. Everybody would like an audio transcript, maybe. Everybody wants some data from their images. And that's something that a bunch of users will benefit from, but it might not be immense change in business process. And then there's another example, we'll say you're a ride sharing company, and you have to scan 50,000 driving licenses in every city that you go into. And currently you have that process where people submit their photos, and then people manually add that metadata. And if now you apply Google Vision to it, and you're extracting the metadata out of that, I actually love scenarios like this. Like, enterprises often ask me like where we should start. Where we should start in terms of applying machine learning, and my sort of candid advice is don't start with curing cancer. Start with something where there is some manual data being added. It's being added at scale. And take those scenarios, such as this driving license example, and now apply machine learning to that, so where previously it would take a month for you to get the data entered for 50,000 driving licenses, now you can do it in 50 minutes. And, um, yeah. >> And what's the quality impact? I mean, presumably the machines are going to get it right more often. >> Yeah. >> But do you have any data you can share with regard to that? >> So that's, actually, that's such an awesome question. And I'll connect it to my sort of previous advice to enterprises, which is that's why I love these processes because these processes have exception handling built into them already. So humans have at minimum a 5% error rate. Sometimes a 30% error rate. So, when we looked at, you know, captioned videos and TV from like 10 years ago, we could clearly see errors in that, which humans had transcribed, right? So, most of these manual processes at scale already have two processes built in, data entry, data validation and exception handling. So the reason that I love replacing the data entry portion is that machine learning is never 100%, but to the validation process, it still looks like kind of the same thing. You still saved all of your money. Not just money, but you saved sort of the time to market. And that's also what Box does, right? Because if you use Box in combination with Google Cloud, we actually, one of the things that I didn't talk about before, we looked at all of these machine learning providers, and we came up with standard JSON formats of how to represent machine learning output. So, as an example, you could imagine that getting machine learning applied in audio is a different problem than getting machine learning applied in video, is a different problem than getting machine learning applied from images. So we actually created these visual cards, which are developer components. And you can just get, put data in that JSON format, we will take care of the end user interactivity. So as an example, if it's a video, and you have topics. Now when you click on a topic, you see a timeline, which you didn't in images because there was no timeline. >> You matched the JSON configuration for the user expectation experience. >> Exactly. So now if you're in Enterprise and you're trying to turn that on, you're now, you could already see the content preview, and now you can also see the machine learning output, but it's also interactive. So if you, if you were recording this video, and you were like, "When did he say BoxWorks?" You click on that little timeline, and you will be able to jump to those portions in the timeline. >> That's awesome. I mean, you guys doing some great work. What's next? Final question, what are you guys going to do next? You got a lot to dig in. You got the AI, machine learning, store with Google. You got the Skills with Box to merge them together. What's next? >> So I think for us, the machine learning thing is just starting, so it's sort of, you'll learn more at BoxWorks. But for us I think the biggest thing there is how do we enable companies to experience machine learning faster? Which is why when we look at this two axis image audio video, we enable organizations to experience that quickly. And it actually is like an introduction to the drug because the guy who has to process insurance claims or the car damage photos, or the drone photos, he looks at that Google Vision output, and then he says, "Oh, if I can get these ties, maybe I can get these specialized business process ties." And then now he's looking at AutoML, announced today, and, you know, the adoption of that really, really >> Autonomous driving, machine learning. It's going to happen. Great stuff. Real quick question for you. When is BoxWorks? I don't think it's on our schedule. >> Next month, yeah. >> I think it's August 28th or 29th. It's coming up, yeah, yeah. >> So I'm going to go check. I don't think theCUBE is scheduled to be there, but I'm going to make a note. Follow up. >> We'd love to have you. Check with Jeff Frick on that. I think we were talking about covering the event. It's going to be local in San Francisco area? >> Uh, Moscone, yeah. >> Moscone, okay great. Well, thanks for coming on. Machine learning, certainly the future. You got auto drive, machine learning, all kinds of new stuff happening. Machine learning changing integrations, changing software, changing operations, and building better benefits, expectations for users. Box doing a great job. Congratulations on the work you're doing. Appreciate it. >> Thanks for coming on. >> Thanks for coming on. More CUBE coverage after the short break. We're going to wrap up day one. We got a special guest. Stay with us. One more interview, and then we got all day tomorrow. Be right back. (upbeat music)
SUMMARY :
Brought to you by Google Cloud collaborative file sharing in the Cloud. So you guys have a You can do, get all of the so the user experience feels native. So that's the key benefit That's great for the user. So that's one of the So how do you use data? And we look at it, if you I mean, presumably the machines So the reason that I love You matched the JSON configuration for and now you can also see You got the Skills with or the car damage photos, It's going to happen. I think it's August 28th So I'm going to go check. about covering the event. Congratulations on the work you're doing. More CUBE coverage after the short break.
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Julian Box, Calligo & Shekhar Mishra, Lenovo - Lenovo Transform 2017
(upbeat electronic music) >> Voiceover: Live from New York City, it's theCUBE, covering Lenovo Transform 2017. Brought to you by Lenovo. >> Welcome back to theCUBE's coverage of Lenovo Transform. I'm your host, Rebecca Knight, along with my cohost, Stu Miniman, who is a senior analyst at Wikibon. We are joined today by Julian Box. He is the founder and CEO of Calligo, and Shekhar Mishra, who is the director of product management here at Lenovo. Thanks so much for coming on the show. >> Thank you. >> So Julian, I want to start with you. Tell us a little bit about Calligo and your business challenges. >> Calligo is six years old now. We're a cloud service provider, but we do things slightly differently. We were set up with data privacy at its core, which is a little bit of a paradox for cloud, of course, because you shouldn't really care where the data is, but I believed people would care where the data was, and what laws were applicable, and who could look at the data, and so forth. Fast forward to today, and we've had Edward Snowden, and now we've got the EU GDPR, which, some people would say, is a lot tougher now because of Edward Snowden's stuff that he actually showed was going on. Interestingly, a lot of that stuff, was really focused very much on the U.S. and not really about outside the U.S. We focus very much around any organization that touches EU citizens. We have a privacy play around that. We do it just slightly differently than a standard cloud service provider. >> I do want to get into that new EU regulation you were talking about, but can you tell us a little bit about why you chose Lenovo? >> There's a lot of history there. Right back in the day, I was true blue in the '80s, coding away in the midrange, and I've always had that link with IBM. Then, through the acquisition that Lenovo did, we flowed into Lenovo, and it's been actually very, very good. Some people questioned whether that was a good move, but I saw what they'd done with the ThinkPad, and the Think Range, and the PC, and I was pretty confident it was going to carry on. We've been very happy with what we've had so far. >> Shekhar, want to bring you into the discussion. You've been talking a lot about infrastructure, things like server, storage, and networking. Bring us into how cloud fits into the Lenovo portfolio with the announcements that we've been talking about today. >> Definitely. If you really look at, not the how, but why people are moving towards having cloud structure, people like as he was talking earlier, that service provider, they're looking really for the agility and simplicity that a lot of the public cloud brings, but then, as he was talking, that a lot of the regulatory issues, SLA, security concerns really prohibit them to actually put everything on a public cloud, right? They want those benefits, but they want that at their own terms, right? The best people who can provide that is one who are able to embrace openness, play with the ecosystem, like partners, like Microsoft, Nutanix, and VMware, and also provide a very solid infrastructure, to run those things, right? We, as a company, Lenovo DCG, can offer that. Those are the key values, but also going beyond that, if you think about, cloud is really simple, but once you get it deployed and working, that is a big "if" there, right? What we have done as a strategy is to simplify this, to increase the kind of value for our customers. We promote this as a pre-integrated solution, which is really a turnkey with the simple support so customers are not running around for support or having to deploy it on their own terms, things like that. >> I would actually say, the idea of cloud is simple. Once you really get into it, it's not so simple. I've been at the Amazon re:Invent show for many years. They're adding 1,000 new features every year. That's not simple. Julian, six years? I mean, that's like multiple lifetimes since you started your company. The whole service provider marketplace has changed a lot. Can you talk about what's been changing in your business? You're involved with the Microsoft Azure Stack. How do you look at the public cloud, and that hybrid layer, and envision your role going forward? >> Yeah, it has changed a lot. If someone had asked me that we would be doing a Microsoft stack cloud-based system a few years ago, I wouldn't have thought we would be, but because of the way people perceive data now, and where it is, and where it's held, there's more and more of a demand that, "I want my data, and I want it executed "in the location, the jurisdiction that I live in." Microsoft, and Amazon, and all the other places, they can't be in every single country in the world, clearly. The scale is not there. Even for them, it's not. The Azure Stack is a way, I think, that Microsoft's going to attempt to deal with some of those challenges around actually where data is processed. That gives us an opportunity because we have a lot of clients that won't put their data into the Azure cloud because of where the Azure cloud actually is right now, but when we put it into the jurisdictions we're in, we've got a lot of people wanting to use it. The sooner we get it, the better, really. >> You look at it more from a actual, physical location more than kind of control or governance? >> No, that all goes part and parcel, but the starting point is jurisdictional position in the data. With the EU, you're either in the EU, or you're not in the EU, clearly. With the GDPR law, it's switching. It's switching to become who that person actually is. At the moment, it's all around where the data is. With the GDPR, it's more focused on the individual. The individual doesn't have to live in the EU anymore, but it's still protected by these same laws. People do care, very much so, where the data is actually going to be. Businesses don't want to be caught out either, and they have the challenges of actually processing the data, or controlling the data, as it's known. As a service provider, one of the biggest changes for us, is that we're now liable for some of the processes of what actually happens to that data. Before, it was just the client that was using it. Now, it's proportionally between the two of us. We have a role as a processor, and they have a role as a control of that data. Therefore, again, it comes down to, how do we minimize the risks? How do we ensure that we are meeting the obligations that we have under these new laws? It becomes easier if you're actually doing it in a jurisdiction that has the appropriate laws, or is physically in the EU. There's a thing called a adequacy rating that the EU give to a certain set of countries. You can apply for it. Anybody can apply for it, but only about a dozen or so countries around the world actually have it. What this gives them is the ability to be seen as being in the EU, even though you're not in the EU, from a data protection perspective. >> Companies are really fundamentally rethinking how they approach data privacy. Shekhar, how are you partnering with other companies and helping them work through this? I mean, your example with Calligo, and other companies, too, that are affected? >> That is one of the biggest challenge, if you would think about this. Not only have the companies have to think about, yes, I have to go to a cloud and have a cloud strategy, but the whole deployment model, the mindset of the companies themselves are also shifting, and they need to shift. A very simple example I'll give you, for instance. We have a very prominent educational institute. They're budget right now was allocated to build three more buildings, for instance, to accommodate the influx of new students coming in. They're now talking to us, respect to Azure Stack, that, "Should I move some of that budget "to build up an Azure Stack versus building a new building?" No one thought two years back that IT will be actually competing with the construction. It's very weird to think of that way. One of the key reasons, when you ask them, is, look, Amazon is there, but I cannot just go there. I need that flexibility, but I need it on my own terms, and that this makes sense for me. We are partnering with people like Microsoft to create those. We are doing innovations on a platform itself from the compute all the way to the networking, so as you asked earlier, we own, enter, and stack, whether it is compute, storage, or networking, we have our own IP around it, so we can really create that security across the platform. We are not trying to create an island for customers where you have to work towards the propriety solution because that's totally against the whole cloud model then. That's why we partner with Microsoft. We are partners with VMware, we are partners with Nutanix, and then other networking players also, but that helps our clients to get the best of the breed solution, the software, on a best of breed infrastructure. >> Where do you see data privacy right now? I mean, famously, Europeans and Americans look at data privacy very differently, just individually, consumers, also businesses. Edward Snowden, is he a hero, is he a villain? I mean, there's so many questions, and we're still really a society wrestling with all of this. How does Lenovo approach this? You talked about the mindset. >> From a piracy perspective, you see that, we have a very strict policy around the security and, what do you call, the real vicinity of the infrastructure itself. We do unique things inside our infrastructure itself. We control our infrastructure lineup, the manufacturing and everything. We have certain features enabled which are default, like IPv6 for instance, right? It won't let us ever go in a mode where it can be compromised in any way. We bring that into our software stack all the way from the comware. Those kind of things are helping us drive and maintain that piracy issue. >> Julian, Lenovo, of course, has a long history partnering with both Intel and with Microsoft. When I look at the first generation of Azure Stack, there's not a lot of feature differentiation. Microsoft says, "This is the configuration "you're going to offer, lock it in." So why Lenovo, in your mind? Because there's another three companies, two of which have more market share and other positions. What led you down the path of Lenovo? >> For me, it was very much the history that Lenovo and the Lenovo team that they inherited from IBM have got. They led the way when virtualization first came out. I remember when the 440 was released back in 2001, 2002, something like that, people didn't understand why it was being built. It was because they were ahead of the game. They could see that virtualization was coming. I think Lenovo has the edge from a capabilities perspective. The XClarity tool, I think it's the best management tool that's out there right now. And reliability. I've been using their technology for a very long time now, in all it's forms, and you can see why they're number one, because they genuinely hardly ever ... Literally, I can hardly think, in the last six years, we've probably replaced a couple of spinning disks. That's about it. It really is that reliable, actually. >> Julian, want to get your input. You've been looking at the Azure Stack here. Azure Pack's existed for a while. We've been talking about Azure Stack for a couple of years. This'll be a 1.0 release. What does it mean for your business and your customers? Are there things that you're looking at beyond the 1.0 that will expand it even further? >> Yeah, clearly, on the first version, it's not going to have every single feature that you want it to have, but it will have a lot of the things that our clients are calling for right now. I'm speaking to them right now, and they're prepared to wait for the extra features to come along. Right now, they can't get any of it, so we're giving them a big chunk of it, and they will take the extra features as they come along. As to the point you mentioned a little bit earlier about, it is what we're given, that's true, but people want it to be exactly the same as the big one. We don't care that it's not exactly the same. That said, it will be deployed alongside our standard infrastructure and server offering, which we call CloudCore, and again, it's all Lenovo equipment, not just the Azure Stack. We're 100% Flash. We guarantee any workload. We do things very, very slightly differently in a lot of cases, and you combine these two technologies because clearly, the Azure Stack does stuff that CloudCore doesn't, and CloudCore can do stuff that Azure doesn't do, so we actually think we can give a combination there that you wouldn't typically be able to get. Of course, they're right next to each other running at super high speeds, and not different clouds going across much slower high latency links. Lots and lots of positive stuff. >> Shekhar, from your standpoint in product development, what excites you the most about Azure Stack, and what your customers expect today, and what you see in the future from Lenovo? >> You asked a question that, that it's fixed, and is that a constraint? Actually, my view, I feel that, other than minor tweaks, customers actually don't want a lot of variations because that actually simplifies an environment, right? Today, there's a lot of overhead and management. What my group is really focused on is not about so much on what infrastructure layer. It's more about what the end to end solution is, and not just from a point product, but how the customer is consuming in the entire life cycle of it. All the way from when they start thinking about Azure Stack, for instance, how do you make sure that what kind of data is right on Azure and what is not? How do you make sure that, how much of Azure do they really need? How do they make sure that it's going to audit and ship promptly? And then they can deploy it. By the way, once you deploy it, how am I going to maintain it, right? Our onsite professional go and train them. Then, once you have it deployed, how do I do ongoing management? I'm going to have issues. Who is going to help me? Because this is now built with multiple things. We think of all those entrance consumption, and that's what the whole motivation around ThinkAjile is, to make all of that simplified for our clients, all the way from deployment, to support, to management, and things like that. >> Great point on the consistency because, if you ask any customer, "What version of Azure are you running?" they'll laugh at you 'cause Microsoft takes care of that, and you would want the customer environment to be similar. >> For us, the fact that they're actually going to come and commission it for us is one less thing I have to organize, I have to resource. Literally, the rack turns up, they do the commission, and give us two cables to plug into our core switches, and away we go. The time to delivery is far quicker for us. As we want to roll these out quite quickly around the globe, with everything else that we are up to at the moment, that's another massive plus for us. We actually like the fact that it's coming in this set form, and these guys are going to look after it for us at that lower level, and we're operating, run it with our clients, and that, again, is huge benefit for us. >> Julian, Shekhar, thank you so much for joining us. It's been a pleasure. >> [Julian And Shekhar] Thank you. >> I'm Rebecca Knight for Stu Miniman. We will have more from Lenovo Transform after this. (upbeat electronic music)
SUMMARY :
Brought to you by Lenovo. He is the founder and CEO of Calligo, and your business challenges. and not really about outside the U.S. and the Think Range, and the PC, Shekhar, want to bring you into the discussion. that a lot of the public cloud brings, and that hybrid layer, Microsoft, and Amazon, and all the other places, that the EU give to a certain set of countries. Shekhar, how are you partnering with other companies One of the key reasons, when you ask them, is, You talked about the mindset. of the infrastructure itself. When I look at the first generation of Azure Stack, that Lenovo and the Lenovo team You've been looking at the Azure Stack here. We don't care that it's not exactly the same. By the way, once you deploy it, and you would want the customer environment to be similar. We actually like the fact that it's coming in this set form, Julian, Shekhar, thank you so much for joining us. We will have more from Lenovo Transform after this.
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Dave Clack, Square Box Systems | NAB Show 2017
>> Narrator: Live from Las Vegas it's the Cube covering NAB 2017. Brought to you by HGST. >> Hey, welcome back to the Cube. We are live at the NAB 2017 conference, the National Association of Broadcasters. Great event, over a hundred thousand people. Wow, amazing. I'm Lisa Martin very excited to introduce you to you to our next guest, Dave Clack, the CEO of Square Box Systems. Hi, Dave, welcome to the Cube. >> Thank you. >> Great to have you here. Now, you are a veteran of NAB. >> Yeah, afraid so. >> Yeah, this year's event really this over arching theme of the MET effect. Convergence of media, entertainment technology that used to be distinct. With that theme and all the buzz that's going on here, what are some of your observations on day, this isn't day one for you, but day one for most of us? >> Well, I think the show is far busier than I've seen it in recent years so we've been overwhelmed on our booth this morning. I think with folks being able to manage extremely complex storage landscapes has been a real theme for us in the discussion so far this morning. In addition, folks are so much moving towards the cloud that people have been talking about it for years, but suddenly it seems there's been a step change. People want to do it right now and so we're really noticing that in the discussion so far at least this morning, yeah. >> Do you think that's because cloud technology has matured so much as have cloud users? >> Yeah, I think exactly. I think exactly both. So, the technology is starting to mature and the band widths is really getting there so folks can use this stuff more effectively. People are getting more used to it in their day to day lives. So, you know, everyone's phone backs up to the cloud and everyone just gets used to it just being always on and always working. And so I think a lot of the confidence that people need to have when you're shooting content that's valuable and you need to have deadlines you're going to meet, then people are getting used to the fact that the cloud can be a reliable, even more reliable than a lot of the traditional storage and production approaches. >> And one of the themes along those lines that we've heard today on the program is speed and agility are absolutely key. We're hearing that studio will shoot something, a particular scene and then think you know what that would have been great in virtual reality and do the entire thing again and then that compounds costs and storage challenges, but needing things really quickly. Another thing that we're hearing is well all of us are content creators, right. We all have tablets and mobile devices. >> Yeah. >> We're not only consuming it in these ways we're creating it in these ways. And so it really becomes a challenge for whether it's broadcasters or film studios or even on the sports and entertainment side, of containing and kind of corralling this. Tell us a little bit about Square Box Systems. Who are what are you delivering by way of media asset management and who are some of your key constituents, key sectors that you work with? >> Yeah, so our CatDV is all about helping people to find and reuse their content, saving time, saving money, saving stress. Our whole pile of kind of workflow orchestration workflow automation and so being able to find and reuse is clearly really important when content is exploding in the way it has. And the ways that people consume content is exploding and so almost everybody has the potential need for a system like CatDV with this explosion of content. If you can't find your content you just don't have it. It's just taking up space and money on some storage somewhere. And so the main sectors in which we work are I guess we started our focus on broadcast production post, but now everybody have media. And so, we have a pile of customers, basketball, football, baseball, soccer in the sports market. Education, many universities use CatDV. Non-profits lots of houses of worship use CatDV. Lots of corporates use CatDV, training videos, outreach marketing, social media, you know a lot of agencies, advertising use CatDV. So, there's a few really interesting kind of use cases, things like Jay Piell, the history of space science in CatDV. You want to find out about the Mars rover or about all the space probe stuff look in CatDV. So, sports is a really interesting one. We have a load of ten NFL teams and they have some really interesting workflows around asset management. So, I was chatting with some folks from the Kansas City Chiefs a few weeks ago and what their workflow's done has done is really turned on their head the way that they make programming and content. And so, if you imagine they go to an away game then what they'll do is they'll shoot their content and on the plane on the way home, they'll load that content. They'll plug the camera card into laptops and they'll load that content, not just for tonight's show which is clearly important 'cause tonight's coming soon, but to become part of the history of that sports team. Could it become part of the historic record? >> Of course. >> And so then, let's imagine in a years' time we've got an athlete that's retiring or that's got an award or something, they can go into our system and they can say well CatDV, find me the five star clips for this athlete in this season wearing this number. CatDV will come back with a long list of content, be able to preview it whether it's on active storage, on cloud storage or wherever it is in this kind of complex landscape and then CatDV will be able to preview that media, put it into a rough cut and then within a few minutes you've got a rough cut for a really quality piece of programming that can then be made very cost effectively. So, for them it's really turned on their head the kind of psychology of program making, the psychology of logging. It really has become such a valuable thing that it's just part of their DNA then when they're making their content for their fans. >> Another thing that speaking of fans, that really interested me and piqued my interest when I was reading that Kansas City Chiefs' case study on your website is, what they're doing working with Square Box to really be diversifying and improve their fan experience. Because from a fan's perspective they're able to slice and dice different parts of the game and deliver it in multiple platforms. Tell us a little bit more about how you help sports teams for example really diversify engaging with their fans which presumably to them is going to drive up revenue. >> Right, exactly. And I think that kind of talks to how many end points there are where people can consume this content. That clearly folks I think I heard that there are, it's getting on so that there were more mobile phones than there are Tvs in the U.S. now. So, I always consume my content on mobile devices now. We have a TV, we watch films on it. >> Right. >> But that's about it and so I think that being able to have content and then repurpose it extremely quickly for different workflows, okay being able to broadcast to the satellite channel for the KCC, that's great. But, being able to take segments that are athlete profiles for websites, for Twitter, for social media. Just being able to get that stuff out really quickly and in an automated fashion. So, if you get people in the way mistakes are made and things are slow. So, if you can just take a few boxes and rely on content getting to the right place at the right time, then that is crucial. And so, automation, big thing for us as CatDV, that is a real key thing when trying to manage this stuff cost effectively because while there's an explosion in demand there isn't an explosion in budget so how do people cope when there's all this demand for high quality content but there isn't more money to pay for it. >> So walk us through that journey. If you're talking to a Kansas City Chiefs or another sporting organization, help us understand how you help them understand where to start, to your point budgets are constrained, but the opportunity there for them to really gain much more from their existing digital assets is huge. What is that journey that you help them go on? >> That's a really good question. And, actually it's what motivates me to be in the industry atoll because we make our submergence products, we think they're great. But, asset management doesn't exist in isolation. There's cameras and networking and storage and archiving and distribution and so the first conversation that we have when engaging with any customer sports included, is What's your problem? What are you trying to achieve? And we end up having really interesting conversations about folks businesses. How is it that they're trying to get work done? What's the content creation focus like? So, how do you shoot? What do you shoot on? And so, we have to we have to almost follow the life of a file through from when it's being created as a piece of FX or whether it's some content that's being shot on a camera, well how does that get from where it's being made to the consumer and then how does it get reused so that it becomes an asset rather than a liability? Meanwhile, making sure that it's safe. It can't get lost. It can't get stolen and all that kind of stuff. So, we end up almost doing business consulting about the creative process of making content and that is really fascinating and it's only when we have a really good view of that workflow can we recommend well how's the best way to use our stuff and how's the best way for that to work with storage? >> You brought up something about safety and security. Cyber security is a huge issue and we see it in all that we talk to a lot of different industries here on the Cube and in some industries we had Ted Harrington on the program a little bit ago who's one of the security experts and he said in some industries it's sort of nice to have. More in media and entertainment it's really starting to become part of the culture. >> Yeah. >> Is that something that you're experiencing? >> Oh, very much so. >> Absolutely. >> So and there's always this balance like, so everybody wants their content everywhere and we find out when the execs say oh I don't want to log in, I just want you to send me the video. It's like, well we can do that and we send you the video and it's enormously simple but it's not secure. And so what we try and do is have a balance. We have simple tools that are secure and we have many government agencies and military agencies that use our software so we love working with those guys. They help us to improve our product and to harden it because there's so many well publicized cases of content being stolen. So, we try and get a good balance between hyper secure lockdown and very usable and we work with customers to kind of choose how far down that path they want to get. And you know there's some simple things you can do too. If you're sharing content over the internet then, putting nice watermarks on stuff whether they be visible watermarks or invisible ones that are kind of burnt in, then that can really stop people misusing content or stop people making mistakes about where content's going to be broadcast. Because it's really clear. You're not going to put stuff up if it's got a big label over it. >> Right, you mentioned working with different types of customers, broadcasts, sports, houses of worship. From a collaboration perspective, talk to us about how Square Box facilitates collaboration. >> Yeah, absolutely. So, there are kind of three core things that CatDV does, automate, collaborate and organize. Right, so for this show one of our biggest announcements is CatDV social. And so, what CatDV social lets you do is to have a conversation realtime, a bit like a Skype or a Slack conversation either between a couple of people or group about a collaborative event. So, we're making some content. You know, I need this sound file right now. So, being able to have that realtime collaborative conversation is a new feature in CatDV. We're previewing it at the show and I have to say it's getting a huge amount of interest. It's great. >> Fantastic. Well Dave, thank you so much for being on the program. We wish you nothing but continued success at Square Box. >> Thank you very much. >> And we want to thank you for watching the Cube. Again, live from Las Vegas at NAB 2017. I'm Lisa Martin. Stick around, we'll be right back.
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Brought to you by HGST. to you to our next guest, Dave Clack, Great to have you here. that used to be distinct. in the discussion so far this morning. So, the technology is starting to mature And one of the themes along those lines key constituents, key sectors that you work with? And so the main sectors in which we work are of content, be able to preview it Tell us a little bit more about how you are, it's getting on so that there were more So, if you get people in the way What is that journey that you help them go on? and archiving and distribution and so the in all that we talk to a lot of different And you know there's some simple things From a collaboration perspective, talk to us And so, what CatDV social lets you do is to have on the program. And we want to thank you for watching the Cube.
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Breaking Analysis: Databricks faces critical strategic decisions…here’s why
>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> Spark became a top level Apache project in 2014, and then shortly thereafter, burst onto the big data scene. Spark, along with the cloud, transformed and in many ways, disrupted the big data market. Databricks optimized its tech stack for Spark and took advantage of the cloud to really cleverly deliver a managed service that has become a leading AI and data platform among data scientists and data engineers. However, emerging customer data requirements are shifting into a direction that will cause modern data platform players generally and Databricks, specifically, we think, to make some key directional decisions and perhaps even reinvent themselves. Hello and welcome to this week's wikibon theCUBE Insights, powered by ETR. In this Breaking Analysis, we're going to do a deep dive into Databricks. We'll explore its current impressive market momentum. We're going to use some ETR survey data to show that, and then we'll lay out how customer data requirements are changing and what the ideal data platform will look like in the midterm future. We'll then evaluate core elements of the Databricks portfolio against that vision, and then we'll close with some strategic decisions that we think the company faces. And to do so, we welcome in our good friend, George Gilbert, former equities analyst, market analyst, and current Principal at TechAlpha Partners. George, good to see you. Thanks for coming on. >> Good to see you, Dave. >> All right, let me set this up. We're going to start by taking a look at where Databricks sits in the market in terms of how customers perceive the company and what it's momentum looks like. And this chart that we're showing here is data from ETS, the emerging technology survey of private companies. The N is 1,421. What we did is we cut the data on three sectors, analytics, database-data warehouse, and AI/ML. The vertical axis is a measure of customer sentiment, which evaluates an IT decision maker's awareness of the firm and the likelihood of engaging and/or purchase intent. The horizontal axis shows mindshare in the dataset, and we've highlighted Databricks, which has been a consistent high performer in this survey over the last several quarters. And as we, by the way, just as aside as we previously reported, OpenAI, which burst onto the scene this past quarter, leads all names, but Databricks is still prominent. You can see that the ETR shows some open source tools for reference, but as far as firms go, Databricks is very impressively positioned. Now, let's see how they stack up to some mainstream cohorts in the data space, against some bigger companies and sometimes public companies. This chart shows net score on the vertical axis, which is a measure of spending momentum and pervasiveness in the data set is on the horizontal axis. You can see that chart insert in the upper right, that informs how the dots are plotted, and net score against shared N. And that red dotted line at 40% indicates a highly elevated net score, anything above that we think is really, really impressive. And here we're just comparing Databricks with Snowflake, Cloudera, and Oracle. And that squiggly line leading to Databricks shows their path since 2021 by quarter. And you can see it's performing extremely well, maintaining an elevated net score and net range. Now it's comparable in the vertical axis to Snowflake, and it consistently is moving to the right and gaining share. Now, why did we choose to show Cloudera and Oracle? The reason is that Cloudera got the whole big data era started and was disrupted by Spark. And of course the cloud, Spark and Databricks and Oracle in many ways, was the target of early big data players like Cloudera. Take a listen to Cloudera CEO at the time, Mike Olson. This is back in 2010, first year of theCUBE, play the clip. >> Look, back in the day, if you had a data problem, if you needed to run business analytics, you wrote the biggest check you could to Sun Microsystems, and you bought a great big, single box, central server, and any money that was left over, you handed to Oracle for a database licenses and you installed that database on that box, and that was where you went for data. That was your temple of information. >> Okay? So Mike Olson implied that monolithic model was too expensive and inflexible, and Cloudera set out to fix that. But the best laid plans, as they say, George, what do you make of the data that we just shared? >> So where Databricks has really come up out of sort of Cloudera's tailpipe was they took big data processing, made it coherent, made it a managed service so it could run in the cloud. So it relieved customers of the operational burden. Where they're really strong and where their traditional meat and potatoes or bread and butter is the predictive and prescriptive analytics that building and training and serving machine learning models. They've tried to move into traditional business intelligence, the more traditional descriptive and diagnostic analytics, but they're less mature there. So what that means is, the reason you see Databricks and Snowflake kind of side by side is there are many, many accounts that have both Snowflake for business intelligence, Databricks for AI machine learning, where Snowflake, I'm sorry, where Databricks also did really well was in core data engineering, refining the data, the old ETL process, which kind of turned into ELT, where you loaded into the analytic repository in raw form and refine it. And so people have really used both, and each is trying to get into the other. >> Yeah, absolutely. We've reported on this quite a bit. Snowflake, kind of moving into the domain of Databricks and vice versa. And the last bit of ETR evidence that we want to share in terms of the company's momentum comes from ETR's Round Tables. They're run by Erik Bradley, and now former Gartner analyst and George, your colleague back at Gartner, Daren Brabham. And what we're going to show here is some direct quotes of IT pros in those Round Tables. There's a data science head and a CIO as well. Just make a few call outs here, we won't spend too much time on it, but starting at the top, like all of us, we can't talk about Databricks without mentioning Snowflake. Those two get us excited. Second comment zeros in on the flexibility and the robustness of Databricks from a data warehouse perspective. And then the last point is, despite competition from cloud players, Databricks has reinvented itself a couple of times over the year. And George, we're going to lay out today a scenario that perhaps calls for Databricks to do that once again. >> Their big opportunity and their big challenge for every tech company, it's managing a technology transition. The transition that we're talking about is something that's been bubbling up, but it's really epical. First time in 60 years, we're moving from an application-centric view of the world to a data-centric view, because decisions are becoming more important than automating processes. So let me let you sort of develop. >> Yeah, so let's talk about that here. We going to put up some bullets on precisely that point and the changing sort of customer environment. So you got IT stacks are shifting is George just said, from application centric silos to data centric stacks where the priority is shifting from automating processes to automating decision. You know how look at RPA and there's still a lot of automation going on, but from the focus of that application centricity and the data locked into those apps, that's changing. Data has historically been on the outskirts in silos, but organizations, you think of Amazon, think Uber, Airbnb, they're putting data at the core, and logic is increasingly being embedded in the data instead of the reverse. In other words, today, the data's locked inside the app, which is why you need to extract that data is sticking it to a data warehouse. The point, George, is we're putting forth this new vision for how data is going to be used. And you've used this Uber example to underscore the future state. Please explain? >> Okay, so this is hopefully an example everyone can relate to. The idea is first, you're automating things that are happening in the real world and decisions that make those things happen autonomously without humans in the loop all the time. So to use the Uber example on your phone, you call a car, you call a driver. Automatically, the Uber app then looks at what drivers are in the vicinity, what drivers are free, matches one, calculates an ETA to you, calculates a price, calculates an ETA to your destination, and then directs the driver once they're there. The point of this is that that cannot happen in an application-centric world very easily because all these little apps, the drivers, the riders, the routes, the fares, those call on data locked up in many different apps, but they have to sit on a layer that makes it all coherent. >> But George, so if Uber's doing this, doesn't this tech already exist? Isn't there a tech platform that does this already? >> Yes, and the mission of the entire tech industry is to build services that make it possible to compose and operate similar platforms and tools, but with the skills of mainstream developers in mainstream corporations, not the rocket scientists at Uber and Amazon. >> Okay, so we're talking about horizontally scaling across the industry, and actually giving a lot more organizations access to this technology. So by way of review, let's summarize the trend that's going on today in terms of the modern data stack that is propelling the likes of Databricks and Snowflake, which we just showed you in the ETR data and is really is a tailwind form. So the trend is toward this common repository for analytic data, that could be multiple virtual data warehouses inside of Snowflake, but you're in that Snowflake environment or Lakehouses from Databricks or multiple data lakes. And we've talked about what JP Morgan Chase is doing with the data mesh and gluing data lakes together, you've got various public clouds playing in this game, and then the data is annotated to have a common meaning. In other words, there's a semantic layer that enables applications to talk to the data elements and know that they have common and coherent meaning. So George, the good news is this approach is more effective than the legacy monolithic models that Mike Olson was talking about, so what's the problem with this in your view? >> So today's data platforms added immense value 'cause they connected the data that was previously locked up in these monolithic apps or on all these different microservices, and that supported traditional BI and AI/ML use cases. But now if we want to build apps like Uber or Amazon.com, where they've got essentially an autonomously running supply chain and e-commerce app where humans only care and feed it. But the thing is figuring out what to buy, when to buy, where to deploy it, when to ship it. We needed a semantic layer on top of the data. So that, as you were saying, the data that's coming from all those apps, the different apps that's integrated, not just connected, but it means the same. And the issue is whenever you add a new layer to a stack to support new applications, there are implications for the already existing layers, like can they support the new layer and its use cases? So for instance, if you add a semantic layer that embeds app logic with the data rather than vice versa, which we been talking about and that's been the case for 60 years, then the new data layer faces challenges that the way you manage that data, the way you analyze that data, is not supported by today's tools. >> Okay, so actually Alex, bring me up that last slide if you would, I mean, you're basically saying at the bottom here, today's repositories don't really do joins at scale. The future is you're talking about hundreds or thousands or millions of data connections, and today's systems, we're talking about, I don't know, 6, 8, 10 joins and that is the fundamental problem you're saying, is a new data error coming and existing systems won't be able to handle it? >> Yeah, one way of thinking about it is that even though we call them relational databases, when we actually want to do lots of joins or when we want to analyze data from lots of different tables, we created a whole new industry for analytic databases where you sort of mung the data together into fewer tables. So you didn't have to do as many joins because the joins are difficult and slow. And when you're going to arbitrarily join thousands, hundreds of thousands or across millions of elements, you need a new type of database. We have them, they're called graph databases, but to query them, you go back to the prerelational era in terms of their usability. >> Okay, so we're going to come back to that and talk about how you get around that problem. But let's first lay out what the ideal data platform of the future we think looks like. And again, we're going to come back to use this Uber example. In this graphic that George put together, awesome. We got three layers. The application layer is where the data products reside. The example here is drivers, rides, maps, routes, ETA, et cetera. The digital version of what we were talking about in the previous slide, people, places and things. The next layer is the data layer, that breaks down the silos and connects the data elements through semantics and everything is coherent. And then the bottom layers, the legacy operational systems feed that data layer. George, explain what's different here, the graph database element, you talk about the relational query capabilities, and why can't I just throw memory at solving this problem? >> Some of the graph databases do throw memory at the problem and maybe without naming names, some of them live entirely in memory. And what you're dealing with is a prerelational in-memory database system where you navigate between elements, and the issue with that is we've had SQL for 50 years, so we don't have to navigate, we can say what we want without how to get it. That's the core of the problem. >> Okay. So if I may, I just want to drill into this a little bit. So you're talking about the expressiveness of a graph. Alex, if you'd bring that back out, the fourth bullet, expressiveness of a graph database with the relational ease of query. Can you explain what you mean by that? >> Yeah, so graphs are great because when you can describe anything with a graph, that's why they're becoming so popular. Expressive means you can represent anything easily. They're conducive to, you might say, in a world where we now want like the metaverse, like with a 3D world, and I don't mean the Facebook metaverse, I mean like the business metaverse when we want to capture data about everything, but we want it in context, we want to build a set of digital twins that represent everything going on in the world. And Uber is a tiny example of that. Uber built a graph to represent all the drivers and riders and maps and routes. But what you need out of a database isn't just a way to store stuff and update stuff. You need to be able to ask questions of it, you need to be able to query it. And if you go back to prerelational days, you had to know how to find your way to the data. It's sort of like when you give directions to someone and they didn't have a GPS system and a mapping system, you had to give them turn by turn directions. Whereas when you have a GPS and a mapping system, which is like the relational thing, you just say where you want to go, and it spits out the turn by turn directions, which let's say, the car might follow or whoever you're directing would follow. But the point is, it's much easier in a relational database to say, "I just want to get these results. You figure out how to get it." The graph database, they have not taken over the world because in some ways, it's taking a 50 year leap backwards. >> Alright, got it. Okay. Let's take a look at how the current Databricks offerings map to that ideal state that we just laid out. So to do that, we put together this chart that looks at the key elements of the Databricks portfolio, the core capability, the weakness, and the threat that may loom. Start with the Delta Lake, that's the storage layer, which is great for files and tables. It's got true separation of compute and storage, I want you to double click on that George, as independent elements, but it's weaker for the type of low latency ingest that we see coming in the future. And some of the threats highlighted here. AWS could add transactional tables to S3, Iceberg adoption is picking up and could accelerate, that could disrupt Databricks. George, add some color here please? >> Okay, so this is the sort of a classic competitive forces where you want to look at, so what are customers demanding? What's competitive pressure? What are substitutes? Even what your suppliers might be pushing. Here, Delta Lake is at its core, a set of transactional tables that sit on an object store. So think of it in a database system, this is the storage engine. So since S3 has been getting stronger for 15 years, you could see a scenario where they add transactional tables. We have an open source alternative in Iceberg, which Snowflake and others support. But at the same time, Databricks has built an ecosystem out of tools, their own and others, that read and write to Delta tables, that's what makes the Delta Lake and ecosystem. So they have a catalog, the whole machine learning tool chain talks directly to the data here. That was their great advantage because in the past with Snowflake, you had to pull all the data out of the database before the machine learning tools could work with it, that was a major shortcoming. They fixed that. But the point here is that even before we get to the semantic layer, the core foundation is under threat. >> Yep. Got it. Okay. We got a lot of ground to cover. So we're going to take a look at the Spark Execution Engine next. Think of that as the refinery that runs really efficient batch processing. That's kind of what disrupted the DOOp in a large way, but it's not Python friendly and that's an issue because the data science and the data engineering crowd are moving in that direction, and/or they're using DBT. George, we had Tristan Handy on at Supercloud, really interesting discussion that you and I did. Explain why this is an issue for Databricks? >> So once the data lake was in place, what people did was they refined their data batch, and Spark has always had streaming support and it's gotten better. The underlying storage as we've talked about is an issue. But basically they took raw data, then they refined it into tables that were like customers and products and partners. And then they refined that again into what was like gold artifacts, which might be business intelligence metrics or dashboards, which were collections of metrics. But they were running it on the Spark Execution Engine, which it's a Java-based engine or it's running on a Java-based virtual machine, which means all the data scientists and the data engineers who want to work with Python are really working in sort of oil and water. Like if you get an error in Python, you can't tell whether the problems in Python or where it's in Spark. There's just an impedance mismatch between the two. And then at the same time, the whole world is now gravitating towards DBT because it's a very nice and simple way to compose these data processing pipelines, and people are using either SQL in DBT or Python in DBT, and that kind of is a substitute for doing it all in Spark. So it's under threat even before we get to that semantic layer, it so happens that DBT itself is becoming the authoring environment for the semantic layer with business intelligent metrics. But that's again, this is the second element that's under direct substitution and competitive threat. >> Okay, let's now move down to the third element, which is the Photon. Photon is Databricks' BI Lakehouse, which has integration with the Databricks tooling, which is very rich, it's newer. And it's also not well suited for high concurrency and low latency use cases, which we think are going to increasingly become the norm over time. George, the call out threat here is customers want to connect everything to a semantic layer. Explain your thinking here and why this is a potential threat to Databricks? >> Okay, so two issues here. What you were touching on, which is the high concurrency, low latency, when people are running like thousands of dashboards and data is streaming in, that's a problem because SQL data warehouse, the query engine, something like that matures over five to 10 years. It's one of these things, the joke that Andy Jassy makes just in general, he's really talking about Azure, but there's no compression algorithm for experience. The Snowflake guy started more than five years earlier, and for a bunch of reasons, that lead is not something that Databricks can shrink. They'll always be behind. So that's why Snowflake has transactional tables now and we can get into that in another show. But the key point is, so near term, it's struggling to keep up with the use cases that are core to business intelligence, which is highly concurrent, lots of users doing interactive query. But then when you get to a semantic layer, that's when you need to be able to query data that might have thousands or tens of thousands or hundreds of thousands of joins. And that's a SQL query engine, traditional SQL query engine is just not built for that. That's the core problem of traditional relational databases. >> Now this is a quick aside. We always talk about Snowflake and Databricks in sort of the same context. We're not necessarily saying that Snowflake is in a position to tackle all these problems. We'll deal with that separately. So we don't mean to imply that, but we're just sort of laying out some of the things that Snowflake or rather Databricks customers we think, need to be thinking about and having conversations with Databricks about and we hope to have them as well. We'll come back to that in terms of sort of strategic options. But finally, when come back to the table, we have Databricks' AI/ML Tool Chain, which has been an awesome capability for the data science crowd. It's comprehensive, it's a one-stop shop solution, but the kicker here is that it's optimized for supervised model building. And the concern is that foundational models like GPT could cannibalize the current Databricks tooling, but George, can't Databricks, like other software companies, integrate foundation model capabilities into its platform? >> Okay, so the sound bite answer to that is sure, IBM 3270 terminals could call out to a graphical user interface when they're running on the XT terminal, but they're not exactly good citizens in that world. The core issue is Databricks has this wonderful end-to-end tool chain for training, deploying, monitoring, running inference on supervised models. But the paradigm there is the customer builds and trains and deploys each model for each feature or application. In a world of foundation models which are pre-trained and unsupervised, the entire tool chain is different. So it's not like Databricks can junk everything they've done and start over with all their engineers. They have to keep maintaining what they've done in the old world, but they have to build something new that's optimized for the new world. It's a classic technology transition and their mentality appears to be, "Oh, we'll support the new stuff from our old stuff." Which is suboptimal, and as we'll talk about, their biggest patron and the company that put them on the map, Microsoft, really stopped working on their old stuff three years ago so that they could build a new tool chain optimized for this new world. >> Yeah, and so let's sort of close with what we think the options are and decisions that Databricks has for its future architecture. They're smart people. I mean we've had Ali Ghodsi on many times, super impressive. I think they've got to be keenly aware of the limitations, what's going on with foundation models. But at any rate, here in this chart, we lay out sort of three scenarios. One is re-architect the platform by incrementally adopting new technologies. And example might be to layer a graph query engine on top of its stack. They could license key technologies like graph database, they could get aggressive on M&A and buy-in, relational knowledge graphs, semantic technologies, vector database technologies. George, as David Floyer always says, "A lot of ways to skin a cat." We've seen companies like, even think about EMC maintained its relevance through M&A for many, many years. George, give us your thought on each of these strategic options? >> Okay, I find this question the most challenging 'cause remember, I used to be an equity research analyst. I worked for Frank Quattrone, we were one of the top tech shops in the banking industry, although this is 20 years ago. But the M&A team was the top team in the industry and everyone wanted them on their side. And I remember going to meetings with these CEOs, where Frank and the bankers would say, "You want us for your M&A work because we can do better." And they really could do better. But in software, it's not like with EMC in hardware because with hardware, it's easier to connect different boxes. With software, the whole point of a software company is to integrate and architect the components so they fit together and reinforce each other, and that makes M&A harder. You can do it, but it takes a long time to fit the pieces together. Let me give you examples. If they put a graph query engine, let's say something like TinkerPop, on top of, I don't even know if it's possible, but let's say they put it on top of Delta Lake, then you have this graph query engine talking to their storage layer, Delta Lake. But if you want to do analysis, you got to put the data in Photon, which is not really ideal for highly connected data. If you license a graph database, then most of your data is in the Delta Lake and how do you sync it with the graph database? If you do sync it, you've got data in two places, which kind of defeats the purpose of having a unified repository. I find this semantic layer option in number three actually more promising, because that's something that you can layer on top of the storage layer that you have already. You just have to figure out then how to have your query engines talk to that. What I'm trying to highlight is, it's easy as an analyst to say, "You can buy this company or license that technology." But the really hard work is making it all work together and that is where the challenge is. >> Yeah, and well look, I thank you for laying that out. We've seen it, certainly Microsoft and Oracle. I guess you might argue that well, Microsoft had a monopoly in its desktop software and was able to throw off cash for a decade plus while it's stock was going sideways. Oracle had won the database wars and had amazing margins and cash flow to be able to do that. Databricks isn't even gone public yet, but I want to close with some of the players to watch. Alex, if you'd bring that back up, number four here. AWS, we talked about some of their options with S3 and it's not just AWS, it's blob storage, object storage. Microsoft, as you sort of alluded to, was an early go-to market channel for Databricks. We didn't address that really. So maybe in the closing comments we can. Google obviously, Snowflake of course, we're going to dissect their options in future Breaking Analysis. Dbt labs, where do they fit? Bob Muglia's company, Relational.ai, why are these players to watch George, in your opinion? >> So everyone is trying to assemble and integrate the pieces that would make building data applications, data products easy. And the critical part isn't just assembling a bunch of pieces, which is traditionally what AWS did. It's a Unix ethos, which is we give you the tools, you put 'em together, 'cause you then have the maximum choice and maximum power. So what the hyperscalers are doing is they're taking their key value stores, in the case of ASW it's DynamoDB, in the case of Azure it's Cosmos DB, and each are putting a graph query engine on top of those. So they have a unified storage and graph database engine, like all the data would be collected in the key value store. Then you have a graph database, that's how they're going to be presenting a foundation for building these data apps. Dbt labs is putting a semantic layer on top of data lakes and data warehouses and as we'll talk about, I'm sure in the future, that makes it easier to swap out the underlying data platform or swap in new ones for specialized use cases. Snowflake, what they're doing, they're so strong in data management and with their transactional tables, what they're trying to do is take in the operational data that used to be in the province of many state stores like MongoDB and say, "If you manage that data with us, it'll be connected to your analytic data without having to send it through a pipeline." And that's hugely valuable. Relational.ai is the wildcard, 'cause what they're trying to do, it's almost like a holy grail where you're trying to take the expressiveness of connecting all your data in a graph but making it as easy to query as you've always had it in a SQL database or I should say, in a relational database. And if they do that, it's sort of like, it'll be as easy to program these data apps as a spreadsheet was compared to procedural languages, like BASIC or Pascal. That's the implications of Relational.ai. >> Yeah, and again, we talked before, why can't you just throw this all in memory? We're talking in that example of really getting down to differences in how you lay the data out on disk in really, new database architecture, correct? >> Yes. And that's why it's not clear that you could take a data lake or even a Snowflake and why you can't put a relational knowledge graph on those. You could potentially put a graph database, but it'll be compromised because to really do what Relational.ai has done, which is the ease of Relational on top of the power of graph, you actually need to change how you're storing your data on disk or even in memory. So you can't, in other words, it's not like, oh we can add graph support to Snowflake, 'cause if you did that, you'd have to change, or in your data lake, you'd have to change how the data is physically laid out. And then that would break all the tools that talk to that currently. >> What in your estimation, is the timeframe where this becomes critical for a Databricks and potentially Snowflake and others? I mentioned earlier midterm, are we talking three to five years here? Are we talking end of decade? What's your radar say? >> I think something surprising is going on that's going to sort of come up the tailpipe and take everyone by storm. All the hype around business intelligence metrics, which is what we used to put in our dashboards where bookings, billings, revenue, customer, those things, those were the key artifacts that used to live in definitions in your BI tools, and DBT has basically created a standard for defining those so they live in your data pipeline or they're defined in their data pipeline and executed in the data warehouse or data lake in a shared way, so that all tools can use them. This sounds like a digression, it's not. All this stuff about data mesh, data fabric, all that's going on is we need a semantic layer and the business intelligence metrics are defining common semantics for your data. And I think we're going to find by the end of this year, that metrics are how we annotate all our analytic data to start adding common semantics to it. And we're going to find this semantic layer, it's not three to five years off, it's going to be staring us in the face by the end of this year. >> Interesting. And of course SVB today was shut down. We're seeing serious tech headwinds, and oftentimes in these sort of downturns or flat turns, which feels like this could be going on for a while, we emerge with a lot of new players and a lot of new technology. George, we got to leave it there. Thank you to George Gilbert for excellent insights and input for today's episode. I want to thank Alex Myerson who's on production and manages the podcast, of course Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our EIC over at Siliconangle.com, he does some great editing. Remember all these episodes, they're available as podcasts. Wherever you listen, all you got to do is search Breaking Analysis Podcast, we publish each week on wikibon.com and siliconangle.com, or you can email me at David.Vellante@siliconangle.com, or DM me @DVellante. Comment on our LinkedIn post, and please do check out ETR.ai, great survey data, enterprise tech focus, phenomenal. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, and we'll see you next time on Breaking Analysis.
SUMMARY :
bringing you data-driven core elements of the Databricks portfolio and pervasiveness in the data and that was where you went for data. and Cloudera set out to fix that. the reason you see and the robustness of Databricks and their big challenge and the data locked into in the real world and decisions Yes, and the mission of that is propelling the likes that the way you manage that data, is the fundamental problem because the joins are difficult and slow. and connects the data and the issue with that is the fourth bullet, expressiveness and it spits out the and the threat that may loom. because in the past with Snowflake, Think of that as the refinery So once the data lake was in place, George, the call out threat here But the key point is, in sort of the same context. and the company that put One is re-architect the platform and architect the components some of the players to watch. in the case of ASW it's DynamoDB, and why you can't put a relational and executed in the data and manages the podcast, of
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James Bryan, Dell Technologies & Heather Rahill, Dell Technologies | MWC Barcelona 2023
>> Narrator: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (bright music) >> Hey everyone! Welcome back. Good evening from Barcelona, Spain. It's theCUBE, the leader in live tech coverage. As you well know, Lisa Martin and Dave Nicholson. Day two of our coverage of MWC 23. Dave, we've been talking about sexy stuff all day. It's about to get, we're bringing sexy back. >> It's about to get hot. >> It's about to get hot. We've had two guests with us, two senior consultants from the product planning, networking and emerging server solutions group at Dell, Heather Raheel and James Bryan. Welcome guys. >> Thanks for having us. >> Thanks for having us. >> Really appreciate it. >> Lisa: Dude, you're bringing sexy back. >> I know. We are. We are. We wanted to bring it, yes. >> This is like XR8000 >> We've been talking about this all day. It's here... >> Yes. Yes. Talk to us about why this is so innovative. >> So, actually we wanted to bring this, getting a lot of attention here on site. Matter of fact, we even have a lot of our competition taking pictures of it. And why is it so innovative? So one of the things that we've done here is we've taken a lot of insights and feedback from our customers that are looking at 5G deployments and looking at how do they, basically, bring commercial off the shelf to a very proprietary industry. So what we've done is we've built a very flexible and scalable form factor in the XR8000. And so this is actually a product that we've purposely built for the telecommunications space. Specifically can be deployed for serving a virtual DU or DUC at a cell site for distributed ram. Or it can be put in a local data center, but outside a main data center to support centralized ram. We'll get into it, which is where the really excitement gets is it's sled-based in its design. And so because of that, it enables us to provide both functionality for telecommunications. Could be network, could be enterprise edge as well as being designed to be configured to whatever that workload is, and be cost-optimized for whatever that work. >> Ah, you're killing us! Let's see. Show, show it to us. >> Actually this is where I have to hand it off to my colleague Heather. But what I really want to show you here is the flexibility that we have and the scalability. So, right here what I'm going to show you first is a one U sled. So I'll set that out here, and I'll let Heather tell us all about it. >> Yeah. So XR8000. Let's talk about flexibility first. So the chassis is a two U chassis with a hot swap shared power supply on the right. Within it there are two form factors for the sleds. What James brought out here, this is the one U form factor. Each sled features one node or one CPU first sled. So we're calling the one U the highest, highest density sled right? Cause you can have up to four one node one U sleds in the chassis. The other form factor is a two U sled, on the right here. And that's just really building on top of the one U sled that adds two PCIe sleds on top. So this is really our general purpose sled. You could have up to two of these sleds within the chassis. So what's really cool about the flexibility is you can plug and play with these. So you could have two one Us, two two Us, or mix and match of each of those. >> Talk about the catalyst to build this for telco and some of the emerging trends that, that you guys have seen and said this needs to be purpose-built for the telco. There's so much challenge and complexity there, they need this. >> Want me to take this? So actually that, that's a great question by the way. It turns out that the market's growing. It's nascent right now. Different telecommunication providers have different needs. Their workloads are different. So they're looking for a form factor like this that, when we say flexible, they need to be able to configure it for theirs. They don't all configure the same way. And so they're looking for something that they can configure to their needs, but they also don't want to pay for things that they don't need. And so that's what led to the creation of, of this device the way we've created it. >> How is it specific for edge use cases, though? We think of the edge: it's emerging, it's burgeoning. What makes this so (pause) specific to edge use cases? >> Yeah, let's talk about some of the the ruggedized features of the product. So first of all, it is short depth. So only 430 millimeters. And this is designed for extreme temperatures, really for any environment. So the normal temperatures of operating are negative five to 55, but we've also developed an enhanced heat sink to get us even beyond that. >> Dave: That's Celsius? >> Celsius. Thank you. >> Lisa: Right. So this will get us all the way down to negative 20 boot in operating all the way up to 65 C. So this is one of the most extreme temperature edge offerings we've seen on the market so far. >> And so this is all outside the data center, so not your typical data center server. So not only are we getting those capabilities, but half the size when you look at a typical data center server. >> So these can go into a place where there's a rack, maybe, but definitely not, not doesn't have to be raised for... >> Could be a cell side cabinet. >> Yeah. Okay. >> Heather: Yeah. And we also have AC and DC power options that can be changed over time as well. >> So what can you pack into that one one U sled in terms of CPU cores and memory, just as an example? >> Yeah, great. So, each of the sleds will support the fourth generation of Intel Sapphire Rapids up to 32 corp. They'll also be supporting their new vRAN boost SKUs. And the benefit of those is it has an integrated FEC accelerator within the CPU. Traditionally, to get FEC acceleration, you would need a PCIe card that would take up one of the slots here. Now with it integrated, you're freeing up a PCIe slot, and there's also a power savings involved with that as well. >> So talk about the involvement of, of the telco customer here and then design, I know Dell is very tight with its customers. I imagine there was a lot of communications and collaboration with customers to, to deliver this. >> Interesting question. So it turns out that early on, we had had some initial insight, but it was actually through deep engagement with our customers that we actually redesigned the form factor to what you see here today. So we actually spent significant amount of time with various telecommunication customers from around the world, and they had a very strong influence in this form factor. Even to the point, like Lisa mentioned, we ended up redesigning it. >> Do, do you have a sense for how many of these, or in what kinds of configurations would you deploy in like the typical BBU? So if we're thinking about radio access network literally tran- tower transmitter receiver... somewhere down there (pause) in a cabinet, you have one of these, you have multiple units. I know, I know the answer is "it depends". >> You are right. >> But if, but if someone tells you, well you know, we have 20, 20 cellular sites, and we need (pause) we're we're moving to an open model, and we need the horsepower to do what we want to do. I'm trying to, I'm trying to gauge like what, one of these, what does that, what does that mean? Or is it more like four of these? >> So that, so we'll go >> It depends? >> Yeah it depends, you're absolutely right. However, we can go right there. So if you look in the two U >> Yeah. >> we have three PCIe slots, you know, as Heather mentioned. And so let's say you have a typical cell site, right? We could be able to support a cell site that could have it could have three radios in the configuration here, it could have a, multiply by three, right? It could have up to 18 radios, and we could actually support that. We could support multiple form factors or multiple deployments at a particular cell site. It really then to your point, it does depend, and that's one of the reasons that we've designed it the way we have. For example, if a customer says their initial deployment, they only need one compute node because maybe they're only going to have, you know, two or three carriers. So then, there, you've got maybe six or eight or nine radios. Well then, you put in a single node, but then they may want to scale over time. Well then, you actually have a chassis. They just come in, and they put in a new chassis. The other beauty of that is, is that maybe they wait, but then they want to do new technology. They don't even have to buy a whole new server. They can update to >> Heather: Yeah. the newest technology, same chassis put that in, connect to the radios, and keep going. >> But in this chassis, is it fair to say that most people will be shocked by how much traffic can go through something like this? In the sense that, if a tower is servicing 'n' number of conversations and data streams, going through something like this? I mean somehow blow, it blows my mind to think of thousands of people accessing something and having them all wrapped through something like this. >> It, it'll depend on what they're doing with that data. So you've probably talked a lot about a type of radios, right? Are we going to be massive MIMO or what type of radio? Is it going to be a mix of 4G or 5G? So it'll really depend on that type of radio, and then where this is located. Is it in a dense urban environment, or is it in a rural type of environment at that cell site shelter, but out in a suburban area. So will depend, but then, that's the beauty of this is then, (pause) I get the right CPU, I get the right number of adding cards to connect to the right radios. I purchase whatever, what I need. I may scale to that. I may be (pause) in a growing part of the city, like where we're from or where I'm from or in San Diego where Heather's from where she's in a new suburban, and they put out a new tower and the community grows rapidly. Well then, we may, they may put out one and then you may add another one and I can connect to more radios, more carriers. So it really just comes down to the type and what you're trying to put through that. It could edit a stadium where I may have a lot of people. I may have like, video streaming, and other things. Not only could I be a network connectivity, but I could do other functions like me, multi-axis axon point that you've heard about, talked about here. So I could have a GPU processing information on one side. I could do network on the other side. >> I do, I do. >> Go for it >> Yeah, no, no, I'm sorry. I'm sorry. I don't want to, don't want to hog all of the time. What about expansion beyond the chassis? Is there a scenario where you might load this chassis up with four of those nodes, but then because you need some type of external connectivity, you go to another chassis that has maybe some of these sleds? Or are these self-contained and independent of one another? >> They are all independent. >> Okay. >> So, and then we've done that for a reason. So one of the things that was clear from the customers, again and again and again, was cost, right? Total cost of ownership. So not only, how much does this cost when I buy it from you to what is it going to take to power and run it. And so basically we've designed that with that in mind. So we've separated the compute and isolated the compute from the chassis, from the power. So (pause) I can only deal with this. And the other thing is is it's, it's a sophisticated piece of equipment that people that would go out and service it are not used to. So they can just come out, pull it out without even bringing the system down. If they've got multiple nodes, pull it. They don't have to pull out a whole chassis or whole server. Put one in, connect it back up while the system is still running. If a power supply goes out, they can come and pull it out. We've got one, it's designed with a power infrastructure that if I lose one power supply, I'm not losing the whole system. So it's really that serviceability, total cost of ownership at the edge, which led us to do this as a configurable chassis. >> I was just going to ask you about TCO reduction but another thing that I'm curious about is: there seems to be like a sustainability angle here. Is that something that you guys talk with customers about in terms of reducing footprint and being able to pack more in with less reducing TCO, reducing storage, power consumption, that sort of thing? >> Go ahead. >> You want me to take that one as well? So yes, so it comes at me, varies by the customer, but it does come up and matter of fact one- in that vein, similar to this from a chassis perspective is, I don't, especially now with the technology changing so fast and and customers still trying to figure out well is this how we're really going to deploy it? You basically can configure, and so maybe that doesn't work. They reconfigure it, or, as I mentioned earlier, I purchased a single sled today, and I purchased a chassis. Well then the next generation comes. I don't have to purchase a new chassis. I don't have to purchase a new power supply. So we're trying to address those sustainability issues as we go, you know, again, back to the whole TCO. So they, they're kind of related to some extent. >> Right. Right, right. Definitely. We hear a lot from customers in every industry about ESG, and it's, and it's an important initiative. So Dell being able to, to help facilitate that for customers, I'm sure is part of what gives you that competitive advantage, but you talked about, James, that and, and we talked about it in an earlier segment that competitors are coming by, sniffing around your booth. What's going on? Talk about, from both of your lenses, the (pause) competitive advantage that you think this gives Dell in telco. Heather, we'll start with you. >> Heather: Yeah, I think the first one which we've really been hitting home with is the flexibility for scalability, right? This is really designed for any workload, from AI and inferencing on like a factory floor all the way to the cell site. I don't know another server that could say that. All in one box, right? And the second thing is, really, all of the TCO savings that will happen, you know, immediately at the point of sale and also throughout the life cycle of this product that is designed to have an extremely long lifetime compared to a traditional server. >> Yeah, I'll get a little geeky with you on that one. Heather mentioned that we'll be able to take this, eventually, to 65 C operating conditions. So we've even designed some of the thermal solutions enabling us to go there. We'll also help us become more power efficient. So, again, back to the flexibility even on how we cool it so it enables us to do that. >> So do, do you expect, you just mentioned maybe if I, if I heard you correctly, the idea that this might have a longer (pause) user-usable life than the average kind of refresh cycle we see in general IT. What? I mean, how often are they replacing equipment now in, kind of, legacy network environments? >> I believe the traditional life cycle of a of a server is, what? Three? Three to five years? Three to five years traditionally. And with the sled based design, like James said, we'll be designing new sleds, you know, every year two years that can just be plugged in, and swapped out. So the chassis is really designed to live much longer than, than just three to five years. >> James: We're having customers ask anywhere from seven to when it dies. So (pause) substantial increase in the life cycle as we move out because as you can, as you probably know, well, right? The further I get out on the edge, it, the more costly it is. >> Lisa: Yep. >> And, I don't want to change it if I don't have to. And so something has to justify me changing it. And so we're trying to build to support that both that longevity, but then with that longevity, things change. I mean, seven years is a long time in technology. >> Lisa: Yes it is. >> So we need to be there for those customers that are ready for that change, or something changed, and they want to still be able to, to adopt that without having to change a lot of their infrastructure. >> So customers are going to want to get their hands on this, obviously. We know, we, we can tell by your excitement. Is this GA now? Where is it GA, and where can folks go to learn more? >> Yeah, so we are here at Mobile World Congress in our booth. We've got a few featured here, and other booths throughout the venue. But if you're not here at Mobile World Congress, this will be launched live on the market at the end of May for Dell. >> Awesome. And what geographies? >> Worldwide. >> Worldwide. Get your hands on the XR8000. Worldwide in just a couple months. Guys, thank you >> James: Thank you very much. >> for the show and tell, talking to us about really why you're designing this for the telco edge, the importance there, what it's going to enable operators to achieve. We appreciate your time and your insights and your show and tell. >> Thanks! >> Thank you. >> For our guests and for Dave Nicholson, I'm Lisa Martin. You're watching theCUBE live, Spain in Mobile MWC 23. Be back with our sho- day two wrap with Dave Valente and some guests in just a minute. (bright music)
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Juan Carlos Garcia, Telefónica & Ihab Tarazi, Dell Technologies | MWC Barcelona 2023
>> Narrator: TheCUBE's live coverage is made possible by funding from Dell Technologies, creating technologies that drive human progress. (upbeat music) (logo background tingles) >> Hey everyone, it's so good to see you, welcome back to theCube's day two coverage of MWC 23. We are live in Barcelona, Lisa Martin with Dave Nicholson, Dave we have had no signage of people dropping out, this conference is absolutely jam packed. There's so much interest in the industry, you've had a lot of interviews this morning, before we introduce our guests and have a great conversation about the industry and challenges and how they're being solved, what are some of the things that stuck out to you in conversations today? >> Well, I think the interesting, kind of umbrella conversation, that seems to be overlapping you know, overlying everything is this question about Open RAN and open standards in radio access network technology and where the operators of networks and the providers of technology come together to chart a better path forward. A lot of discussion of private 5G networks, it's very interesting, I think I've said this a few times, from a consumer's perspective, we feel like 5G has been with us for a long time- >> We do. >> But it's very clear that this, that we're really at the beginning of stages of this and I'm super excited for our guests that we have here because we're going to be able to talk to an actual operator- >> Yes. >> And hear what they have to say, we've heard a lot of people talking about the cool stuff they build, but we're going to get to hear from someone who actually works with this stuff, so- >> Who actually built it, absolutely. Please welcome our two guests, we have Ihab Tarazi CTO and SVP at Dell Technologies, and Juan Carlos Garcia SVP Technology Innovation and Ecosystems at Telephonica, it's great to have you guys on the program. >> So, thank you very much. >> So the buzz around this conference is incredible, 80,000 plus people, 2000 exhibitors, it's standing room only. Lot of opportunity in the industry, a lot of challenges though, Juan Carlos we'd love to get your perspective on, what are some of the industry challenges that Telephonica has faced that your peers are probably facing as well? >> Well we have two kinds of challenges, one is a business challenge, I would say that we may find in other industries, like profitability and growth and I will talk about it. And the second challenge is our technology challenge, we need the network to be ready to embrace a new wave of technologies and applications that are, you know, very demanding in terms of network characteristics and features. On the efficiency and profitability and growth, the solution comes as a challenge from changing the way networks are built and operated, from the traditional way to make them become software platforms. And this is not just at the knowledge challenge, it's also changing the mindset of network operators from a network and service provider to a digital service provider, okay? And this means several things, your network needs to become software-based so that you can manage it digitally and on top of it, you need to be able to deliver detail services digitally, okay? So there are three aspects, making your network so (indistinct) and cloud and cloud waste and then be able to sell in a different way to our customers. >> So some pretty significant challenges, but to your point, Juan Carlos, you share some of those challenges with other industries so there's some commonality there. I wanted to bring Ihab into the conversation, from Dell's perspective, we're seeing, you know, the explosion of data. Every company has to be a data company, we expect to have access to data in real time, if it's a new app, whatever it is. What are some of the challenges that you're seeing from your seat at Dell? >> Yeah, I think Juan Carlos explained that really well, what all the operators are talking about here between new applications, think metaverse, think video streaming, going all the way to the edge, think all the automation of factories and everything that's happening. It's not only requiring a whole new model for delivery and for building networks, but it's throwing out enormous amount of data and the data needs to be acted on to get the value of it. So the challenge is how do I collect the data? How do I catalog it? How do I make it usable? And then how do I make it persistent? So you know, it's high performance data storage and then after that, how do I move it to where I want to and be able to use it. And for many applications that has to happen in milliseconds for the value to come out. So now we've seen this before with enterprise but now I would say this digital transformation is happening at very large scale for all the telcos and starting to deal with very familiar themes we've seen before. >> So Juan Carlos, Telephonica, you hear from partners, vendors that they've done this before, don't worry, you're in good hands. >> Juan Carlos: Yeah, yeah. >> But as a practical matter, when you look at the challenges that you have and you think about the things you'll do to address them as you move forward, what are the immediate short term priorities? >> Okay. >> Versus the longer term priorities? What's realistic? You have a network to operate- >> Yeah. >> You're not just building something out of nothing, so you have to keep the lights on. >> Yeah. >> And you have to innovate, we call that by the way, in the CTO trade, ambidextrous, management using both hands, so what's your order of priorities? >> Well, the first thing, new technologies you are getting into the network need to come with a detail shape, so being cloud native, working by software. On the legacies that you need to keep alive, you need to go for a program to switch (indistinct) off progressively, okay? In fact, in Spain we are going to switch up the copper network in two years, so in 2024, Telephonica will celebrate 100 years and the celebration will be switching up the copper network and we'll have on the fixed access only fiber, okay. So more than likely, the network is necessary, all this digitalization may happen only on the new technologies because the new technologies are cloud-based, cloud native, become already ready for this digitalization process. And not only that, so you need also to build new things, we need an abstraction layer on top of the physical infrastructure to be able to manage the network by software, okay. This is something that happened in the computing world, okay, where the servers, you know, were covered with a cloud stack layer and we are doing the same thing in the network. We are trained to abstract the network services and capabilities and be able to offer them digitally to our customers. And this is a process that we are ongoing with many initiatives in the market, so one was the CAMARA community that was opened in Linux Foundation and the other one was the announcement we made yesterday of the open gateway initiative here at Mobile World Congress where all telecom operators have agreed to launch in this year a set of service APIs that are common worldwide, okay. This is a similar thing to what we did with 2G 35 years ago, to agree on a standard way of delivering a service and in this case is digital services based on APIs. >> What's the net result of? What are the benefits of having those open standards? Is it a benefit that myself as a consumer would enjoy? It seems, I mean, I've been, I'm old enough to remember, you know, a time before cellular telephones and I remember a time when it was very, very difficult to travel from North America to Europe with a cell phone. Now I land and my provider says, "Hey, welcome-" >> Juan Carlos: Yes. >> "Welcome, we're going to charge you a little extra money." And I say, "Hallelujah, awesome." So is part of that interoperability a benefit to consumers or, how, what? >> Yeah, you touch the right point. So in the same way you travel anywhere and you want to still make a call and send an SMS and connect to the internet, you will like your applications in your smartphone to work being them edge applications, okay, and these applications, each application will have to work to be executed very close to where you are, in a way that if you travel abroad the visitor network is serving you, okay. So this means that we are somehow extending the current interconnection and roaming agreements between operators to be able also to deliver edge applications wherever you are, in whatever network, with whatever technology. >> We have that expectation on the consumer side, that it's just going to work no matter where we are, we want apps to be updated, whether I'm banking or I'm shopping for groceries, I want to make sure that they know who I am, the data's got to be there, it's got to be real time, it's got to be right, it's got to serve me personally, but it just has to work. You guys talked about some of the big challenges, but also the opportunities in terms of the future of networking, the data turning companies in the data companies. Walk us through the future of networking from Telephonica's lens, you talked about some of the big initiatives that you have by 2024. >> Yes. >> But if you had a crystal ball and you could look in there and go it looks like this for operators, what would you say? And I'd love to get your feedback too. >> Yeah, I liked how Juan Carlos talked about how the future is, I think I want to add one thing to it, to say, a lot of times the user is no longer a consumer, it's an automated thing, you know, AI think robots, so a lot of times, more and more the usage is happening by some autonomous thing and it needs to always connect. And more and more these things are extending to places where even cellular coverage doesn't exist today, so you have edge compute show up. So, and when you think about it, the things we have to solve as a community here and this is all the discussions is, number one, how you make it a fully open standard model, so everything plugs and play, more and more, there's so many pieces coming, software, hardware, from different components and the integration of all of that is probably one of the biggest challenges people want solved. You know, how it's no longer one box, you buy from one person and put it away, now you have a complex combination of hardware and software. Also the operational model is very important and that is one of the areas we're focused on at Dell, is that while the operational model works inside the data centers for certain application, for telcos, it looks different when you're out at the cell tower and you're going to have these extended temperature changes. And sometimes this may not be inside a cabinet, maybe outside and the person servicing it is not an IT technician. This is somebody that needs to know exactly how to plug it, to be able to place equipment quickly and add capacity, those are just two of the areas, the cloud, making it work like a cloud, where it's intuitive, automated and you can easily add capacity, you can, you know, get a lot of monitoring, a lot of metrics, those are some of the things that we're all solving in this community. >> Let's talk about exactly how you're achieving this, Telephonica and Dell have been working together for a couple of years, you said before we went live. Talk about, you're doing this, you talked about the challenges, the opportunities how are you solving them and why with Dell? >> Okay, well you need to go with the right partners, not to this kind of process of transforming your network into a digital platform. There are big challenges on creating the cloud infrastructure that you need to support the complex, functionality and network requires. And I think you need to have with you, companies that know about the processors, that know about the hardware, the server, that know about how to make an abstraction of that hardware layer so that you can manage that digitally and this is not something any company can do, so you need companies that are very specialized. Telecom operators are changing the way to work, we work in the past with traditionally, with network equipment vendors, now we need to start working with technology providers, hardware (indistinct) providers with cloud providers with an ecosystem that is probably wider than what we had in the past. >> Yes. >> So I come from a background, I call myself a "knuckle dragging hardware engineer" sort of guy, so I'm almost fascinated by the physical part of this. You have a network, part of that network includes towers that have transmitters, receivers, at the base of those towers and like you mentioned, they're not all necessarily in urban areas or easy to access. There's equipment there, let's say that, that tower has been there for 5 years, 10 years, in the traditional world of IT, we have this this concept of the "refresh cycle" >> Juan Carlos: Yeah. >> Where a server may have a useful life of 36 months before it's consuming more power than it should based on the technology. How do you move from, kind of a legacy more proprietary, all-inclusive stack to an open system? I mean, is this a, "Okay, we're planning for an outage for the tower and you're wheeling out old equipment and wheeling in new equipment?" >> Juan Carlos: Yeah. >> I mean that's not, that's what we say as a non-trivial exercise, it's something that isn't, it's not something that's just easy to do, but is that what progress looks like? Sort of, methodically one site at a time? >> Yeah, well, I mean, you have touched an important point. In the technology renewal cycles, we were taking an appliance and replacing that by another one. Now with the current technology, you have the couple, the hardware from the software and the hardware, you need to replace it only when you run out of processing capacity to do what you want, okay? So then we'll be there 2, 3, 4, 5 years, whatever, when you need additional capacity, you replace it, but on the software side you can make the replacement every hour, every week. And this is something that the new technologies are bringing, a flexibility for the telecom operator to introduce a new feature without having to be physically there in the place, okay, by software remotely and this is the kind of software network we want to build. >> Lisa Martin: You know- >> Yeah, I want to add to that if I can- >> Please. >> Yeah. >> I think this is one of the biggest benefits of the open model. If the stack is all integrated as one appliance, when a new technology, we all know how quickly selecon technology comes out and now we have GPU's coming out for AI more increasingly, in an appliance model it may take you two years to take advantage of some new selecon that just came out. In this new open model, as Juan Carlos was saying, you just swap out, you know, you have time to market CPUs launched, it can be put out there at the cell tower and it could double capacity instantly and we're going to need that in that world, that easily going to be AI enabled- >> Lisa Martin: Right. >> So- >> So my last question to you, we only got a minute left or so, is given everything that we've talked about, the challenges, the opportunities, what you're doing together, how would you Juan Carlos summarize how the business is benefiting from the Dell partnership and the technologies that you're enabling with this new future network? >> Well, as I said before, we will need to be able to cover all the characteristics and performance of our network. We will need the right kind of processing capacity, the right kind of hardware solutions. We know that the functionality of the network is a very demanding one, we need hardware acceleration, we need a synchronization, we need time-sensitive solutions and all these can only done by hardware, so you need a good hardware partner, that ensures that you have the processing capacity you need to be able then to run your software, you know, with the confidence that it will work and with the performance that you need. >> That confidence is key. Well it sounds like what Telephonica and Dell have achieved together has been quite successful. Congratulations on the first couple of years, sounds like it's really helping Telephonica's business move in the strategic direction that it wants. We appreciate you joining us on the program today, describing all this, thank you both so much for your time. >> Thank you very much. >> Thank you, this was fun. >> A pleasure. >> Good, our pleasure. For our guests and for Dave Nicholson, I'm Lisa Martin, you're watching theCUBE live day two from Barcelona, MWC 23. Don't go anywhere, Dave and I will be right back with our next guests. (cheerful bouncy music)
SUMMARY :
that drive human progress. to you in conversations today? and the providers of it's great to have you So the buzz around this and on top of it, you What are some of the and the data needs to be acted you hear from partners, so you have to keep the lights on. into the network need to What are the benefits of we're going to charge you So in the same way you travel anywhere the data's got to be there, And I'd love to get your feedback too. and that is one of the areas for a couple of years, you that know about the hardware, the server, and like you mentioned, for the tower and you're and the hardware, you need to replace it benefits of the open model. and with the performance that you need. Congratulations on the and I will be right back
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Ben Hirschberg, Armo Ltd | CloudNativeSecurityCon 23
(upbeat music) >> Hello everyone, welcome back to theCUBE's coverage of Cloud Native SecurityCon North America 2023. Obviously, CUBE's coverage with our CUBE Center Report. We're not there on the ground, but we have folks and our CUBE Alumni there. We have entrepreneurs there. Of course, we want to be there in person, but we're remote. We've got Ben Hirschberg, CTO and Co-Founder of Armo, a cloud native security startup, well positioned in this industry. He's there in Seattle. Ben, thank you for coming on and sharing what's going on with theCUBE. >> Yeah, it's great to be here, John. >> So we had written on you guys up on SiliconANGLE. Congratulations on your momentum and traction. But let's first get into what's going on there on the ground? What are some of the key trends? What's the most important story being told there? What is the vibe? What's the most important story right now? >> So I think, I would like to start here with the I think the most important thing was that I think the event is very successful. Usually, the Cloud Native Security Day usually was part of KubeCon in the previous years and now it became its own conference of its own and really kudos to all the organizers who brought this up in, actually in a short time. And it wasn't really clear how many people will turn up, but at the end, we see a really nice turn up and really great talks and keynotes around here. I think that one of the biggest trends, which haven't started like in this conference, but already we're talking for a while is supply chain. Supply chain is security. I think it's, right now, the biggest trend in the talks, in the keynotes. And I think that we start to see companies, big companies, who are adopting themselves into this direction. There is a clear industry need. There is a clear problem and I think that the cloud native security teams are coming up with tooling around it. I think for right now we see more tools than adoption, but the adoption is always following the tooling. And I think it already proves itself. So we have just a very interesting talk this morning about the OpenSSL vulnerability, which was I think around Halloween, which came out and everyone thought that it's going to be a critical issue for the whole cloud native and internet infrastructure and at the end it turned out to be a lesser problem, but the reason why I think it was understood that to be a lesser problem real soon was that because people started to use (indistinct) store software composition information in the environment so security teams could look into, look up in their systems okay, what, where they're using OpenSSL, which version they are using. It became really soon real clear that this version is not adopted by a wide array of software out there so the tech surface is relatively small and I think it already proved itself that the direction if everyone is talking about. >> Yeah, we agree, we're very bullish on this move from the Cloud Native Foundation CNCF that do the security conference. Amazon Web Services has re:Invent. That's their big show, but they also have re:Inforce, the security show, so clearly they work together. I like the decoupling, very cohesive. But you guys have Kubescape of Kubernetes security. Talk about the conversations that are there and that you're hearing around why there's different event what's different around KubeCon and CloudNativeCon than this Cloud Native SecurityCon. It's not called KubeSucSecCon, it's called Cloud Native SecurityCon. What's the difference? Are people confused? Is it clear? What's the difference between the two shows? What are you hearing? >> So I think that, you know, there is a good question. Okay, where is Cloud Native Computing Foundation came from? Obviously everyone knows that it was somewhat coupled with the adoption of Kubernetes. It was a clear understanding in the industry that there are different efforts where the industry needs to come together without looking be very vendor-specific and try to sort out a lot of issues in order to enable adoption and bring great value and I think that the main difference here between KubeCon and the Cloud Native Security Conference is really the focus, and not just on Kubernetes, but the whole ecosystem behind that. The way we are delivering software, the way we are monitoring software, and all where Kubernetes is only just, you know, maybe the biggest clog in the system, but, you know, just one of the others and it gives great overview of what you have in the whole ecosystem. >> Yeah, I think it's a good call. I would add that what I'm hearing too is that security is so critical to the business model of every company. It's so mainstream. The hackers have a great business model. They make money, their costs are lower than the revenue. So the business of hacking in breaches, ransomware all over the place is so successful that they're playing offense, everyone's playing defense, so it's about time we can get focus to really be faster and more nimble and agile on solving some of these security challenges in open source. So I think that to me is a great focus and so I give total props to the CNC. I call it the event operating system. You got the security group over here decoupled from the main kernel, but they work together. Good call and so this brings back up to some of the things that are going on so I have to ask you, as your startup as a CTO, you guys have the Kubescape platform, how do you guys fit into the landscape and what's different from your tools for Kubernetes environments versus what's out there? >> So I think that our journey is really interesting in the solution space because I think that our mode really tries to understand where security can meet the actual adoption because as you just said, somehow we have to sort out together how security is going to be automated and integrated in its best way. So Kubescape project started as a Kubernetes security posture tool. Just, you know, when people are really early in their adoption of Kubernetes systems, they want to understand whether the installation is is secure, whether the basic configurations are look okay, and giving them instant feedback on that, both in live systems and in the CICD, this is where Kubescape came from. We started as an open source project because we are big believers of open source, of the power of open source security, and I can, you know I think maybe this is my first interview when I can say that Kubescape was accepted to be a CNCF Sandbox project so Armo was actually donating the project to the CNCF, I think, which is a huge milestone and a great way to further the adoption of Kubernetes security and from now on we want to see where the users in Armo and Kubescape project want to see where the users are going, their Kubernetes security journey and help them to automatize, help them to to implement security more fast in the way the developers are using it working. >> Okay, if you don't mind, I want to just get clarification. What's the difference between the Armo platform and Kubescape because you have Kubescape Sandbox project and Armo platform. Could you talk about the differences and interaction? >> Sure, Kubescape is an open source project and Armo platform is actually a managed platform which runs Kubescape in the cloud for you because Kubescape is part, it has several parts. One part is, which is running inside the Kubernetes cluster in the CICD processes of the user, and there is another part which we call the backend where the results are stored and can be analyzed further. So Armo platform gives you managed way to run the backend, but I can tell you that backend is also, will be available within a month or two also for everyone to install on their premises as well, because again, we are an open source company and we are, we want to enable users, so the difference is that Armo platform is a managed platform behind Kubescape. >> How does Kubescape differ from closed proprietary sourced solutions? >> So I can tell you that there are closed proprietary solutions which are very good security solutions, but I think that the main difference, if I had to pick beyond the very specific technicalities is the worldview. The way we see that our user is not the CISO. Our user is not necessarily the security team. From our perspective, the user is the DevOps and the developers who are working on the Kubernetes cluster day to day and we want to enable them to improve their security. So actually our approach is more developer-friendly, if I would need to define it very shortly. >> What does this risk calculation score you guys have in Kubscape? That's come up and we cover that in our story. Can you explain to the folks how that fits in? Is it Kubescape is the platform and what's the benefit, what's the purpose? >> So the risk calculation is actually a score we are giving to clusters in order for the users to understand where they are standing in the general population, how they are faring against a perfect hardened cluster. It is based on the number of different tests we are making. And I don't want to go into, you know, the very specifics of the mathematical functions, but in general it takes into account how many functions are failing, security tests are failing inside your cluster. How many nodes you are having, how many workloads are having, and creating this number which enables you to understand where you are standing in the global, in the world. >> What's the customer value that you guys pitching? What's the pitch for the Armo platform? When you go and talk to a customer, are they like, "We need you." Do they come to you? Is it word of mouth? You guys have a strategy? What's the pitch? What's so appealing to the customers? Why are they enthusiastic about you guys? >> So John, I can tell you, maybe it's not so easy to to say the words, but I nearly 20 years in the industry and though I've been always around cyber and the defense industry and I can tell you that I never had this journey where before where I could say that the the customers are coming to us and not we are pitching to customers. Simply because people want to, this is very easy tool, very very easy to use, very understandable and it very helps the engineers to improve security posture. And they're coming to us and they're saying, "Well, awesome, okay, how we can like use it. Do you have a graphical interface?" And we are pointing them to the Armor platform and they are falling in love and coming to us even more and we can tell you that we have a big number of active users behind the platform itself. >> You know, one of the things that comes up every time at KubeCon and Cloud NativeCon when we're there, and we'll be in Amsterdam, so folks watching, you know, we'll see onsite, developer productivity is like the number one thing everyone talks about and security is so important. It's become by default a blocker or anchor or a drag on productivity. This is big, the things that you're mentioning, easy to use, engineering supporting it, developer adoption, you know we've always said on theCUBE, developers will be the de facto standards bodies by their choices 'cause developers make all the decisions. So if I can go faster and I can have security kind of programmed in, I'm not shifting left, it's just I'm just having security kind of in there. That's the dream state. Is that what you guys are trying to do here? Because that's the nirvana, everyone wants to do that. >> Yeah, I think your definition is like perfect because really we had like this, for a very long time we had this world where we decoupled security teams from developers and even for sometimes from engineering at all and I think for multiple reasons, we are more seeing a big convergence. Security teams are becoming part of the engineering and the engineering becoming part of the security and as you're saying, okay, the day-to-day world of developers are becoming very tangled up in the good way with security, so the think about it that today, one of my developers at Armo is creating a pull request. He's already, code is already scanned by security scanners for to test for different security problems. It's already, you know, before he already gets feedback on his first time where he's sharing his code and if there is an issue, he already can solve it and this is just solving issues much faster, much cheaper, and also you asked me about, you know, the wipe in the conference and we know no one can deny the current economic wipe we have and this also relates to security teams and security teams has to be much more efficient. And one of the things that everyone is talking, okay, we need more automation, we need more, better tooling and I think we are really fitting into this. >> Yeah, and I talked to venture capitalists yesterday and today, an angel investor. Best time for startup is right now and again, open source is driving a lot of value. Ben, it's been great to have you on and sharing with us what's going on on the ground there as well as talking about some of the traction you have. Just final question, how old's the company? How much funding do you have? Where you guys located? Put a plug in for the company. You guys looking to hire? Tell us about the company. Were you guys located? How much capital do you have? >> So, okay, the company's here for three years. We've passed a round last March with Tiger and Hyperwise capitals. We are located, most of the company's located today in Israel in Tel Aviv, but we have like great team also in Ukraine and also great guys are in Europe and right now also Craig Box joined us as an open source VP and he's like right now located in New Zealand, so we are a really global team, which I think it's really helps us to strengthen ourselves. >> Yeah, and I think this is the entrepreneurial equation for the future. It's really great to see that global. We heard that in Priyanka Sharma's keynote. It's a global culture, global community. >> Right. >> And so really, really props you guys. Congratulations on Armo and thanks for coming on theCUBE and sharing insights and expertise and also what's happening on the ground. Appreciate it, Ben, thanks for coming on. >> Thank you, John. >> Okay, cheers. Okay, this is CUB coverage here of the Cloud Native SecurityCon in North America 2023. I'm John Furrier for Lisa Martin, Dave Vellante. We're back with more of wrap up of the event after this short break. (gentle upbeat music)
SUMMARY :
and sharing what's going on with theCUBE. What is the vibe? and at the end it turned that do the security conference. the way we are monitoring software, I call it the event operating system. the project to the CNCF, What's the difference between in the CICD processes of the user, is the worldview. Is it Kubescape is the platform It is based on the number of What's the pitch for the Armo platform? and the defense industry This is big, the things and the engineering becoming the traction you have. So, okay, the company's Yeah, and I think this is and also what's happening on the ground. of the Cloud Native SecurityCon
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Anurag Gupta, Shoreline io | AWS re:Invent 2022 - Global Startup Program
(gentle music) >> Now welcome back to theCUBE, everyone. I'm John Walls, and once again, we're glad to have you here for AWS re:Invent 22. Our coverage continues here on Thursday, day three, of what has been a jam-packed week of tech and AWS, of course, has been the great host for this. It's now a pleasure to welcome in Anurag Gupta, who is the founder and CEO of Shoreline, joining us here as part of the AWS Global Showcase Startup Program, and Anurag, good to see you, sir. Thanks for joining us. >> Thank you so much. >> Tell us about Shoreline, about what you're up to. >> So we're a DevOps company. We're really focused on repairing issues. If you think about it, there are a ton DevOps companies and we all went to the cloud in order to gain faster innovation and by and large check. Then all of the things involved in getting things into production, artifact generation, testing, configuration management, deployment, also by and large, automated. Now pity the poor SRE who's getting the deluge of stuff on them, every week, every two days, sometimes multiple times a day, and it's complicated, right? Kubernetes, VMs, lots of services, multiple clouds, sometimes, and you know, they need to know a little bit about everything. And you know what, there are a ton of companies that actually help you with what we call Day-2 Ops. It's just that most of them help you with observability, telling you what's gone wrong, or incident management, routing something to someone. But you know, back when I was at AWS, I never got really that excited about one more dashboard to look at or one more like better ticket routing. What used to really excite me was having some issue extinguished forever. And if you think about it, like the first five minutes of an incident are detecting and routing. The next hour, two hours, is some human being going in and fixing it, so that feels like the big opportunity to reduce, so hopefully we can talk a little bit about different ways that one can do that. >> What about Day-2 Ops? Just tell me about how you define that. >> So I basically define it as once the software goes into a production, just making sure things stay up and are healthy and you're resilient and you don't get errors and all of those sorts of things because everything breaks sooner or later, you know, to a greater or lesser degree. >> Especially that SRE you're talking about, right? >> Yeah. >> So let's go back to that scenario. Yeah, you pity the poor soul because they do have to be a little expert in everything. >> Exactly. >> And that's really challenging and we all know that, that's really hard. So how do you go about trying to lighten that burden, then? >> So when you look at the numbers, about somewhere between 40% to even 95% of the alarms that fire, the alerts that fire, are false positives and that's crazy. Why is someone waking up just to deal with? >> It's a lot of wasted time, isn't it? >> A lot of wasted time. And you know, you're also training someone into what I call ClickOps, just to go in and click the button and resolve it and you don't actually know if it was the false positive or it's the rare real positive, and so that's a challenge, right? And so the first thing to do is to figure out where the false positives are. Like, let's say Datadog tells you that CPU is high and alarms. Is that a good thing or a bad thing? It's hard for them to tell, right? But you have to then introspect it into something precise like, oh, CPU is high, but response times are standard and the request rate is high. Okay, that's a good thing. I'm going to ignore this. Or CPU is high, but it kind of resolves itself, so I'm going to not wake anybody up. Or CPU is high and oh, it's the darn JVM starting to garbage collect again, so let me go and take a heap dump and give that to my dev team and then bounce the JVM and you know, without waking anybody up, or CPU is high, I have no idea what's going on. Now it's time to wake somebody up. You know, what you want to use humans for is the ability to think about novel stuff, not to do repetitive stuff, so that's the first step. The second step is, about 40% of what remains is repetitive and straightforward. So like a disk is full, I'd better clean up the garbage on the disk or maybe grow the disk. People shouldn't wake up to deal to grow a disk. And so for that, what you want to do is just have those sorts of things get automated away. One of the nice things about Shoreline is, is that we take the experience in what we build for one company, and if they're willing, provide it to everybody else. Our belief is, a central tenant is, if someone somewhere fixes something, everyone everywhere should gain the benefit because we all sit on the same three clouds, we all sit on the same set of database infrastructure, et cetera. We should all get the same benefits. Why do we have to scar our own backs rather than benefiting from somebody else's scar tissue, so that's the second thing. The third thing is, okay, let's say it's not straightforward, not something I've seen before, then in that case, what often happens is on average like eight people get involved. You know, it initially goes to L1 support or L1 ops and, but they don't necessarily know because, as you say, the environment's complex. And so, you know, they go into Slack and they say, "At here, can somebody help me with this?" And those things take a much longer time, so wouldn't it be better that if your best SRE is able to say, "Hey, check these 20 things and then run these actions." We could convert that into like a Jupyter Notebook where you could say the incident got fired I pre-populated all the diagnostics, and then I tell people very precisely, "If you see this, run this, et cetera." Like a wiki, but actually something you could run right in this product. And then, you know, last piece of the puzzle, the smaller piece, is sometimes new things happen and when something new happens, what you want is sort of the central tech of Shoreline, which is parallel distributed, real-time debugging. And so the ability to do, you know, execute a command across your fleet rather than individual boxes so that you can say something like, "I'm hearing that my credit card app is slow. For everything tagged as being part of my credit card app, please run for everything that's running over 90% CPU, please run a top command." And so, you know, then you can run in the same time on one host as you can on 30,000 and that helps a lot. So that's the core of what we do. People use us for all sorts of things, also preventative maintenance, you know, just the proactive regular things. You know, like your car, you do an oil change, well, you know, you need to rotate your certs, certificates. You need to make sure that, you know, there isn't drift in your configurations, there isn't drift in your software. There's also security elements to it, right? You want to make sure that you aren't getting weird inbound/outbound traffic across to ports you don't expect to be open. You don't want to have these processes running, you know, maybe something's bad. And so that's all the kind of weird anomaly detection that's easy to do if you run things in a distributed parallel way across everything. That's super hard to do if you have to go and Whac-A-Mole across one box after the next. >> Well, which leads to a question just in terms of setting priorities then, which is what you're talking about helping companies establish priorities, this hierarchy of level one warning, level two, level three, level four. Sounds like that should be a basic, right? But you're saying that's not, that's not really happening in the enterprise. >> Well, you know, I would say that if you hadn't automated deployments, you should do that first. If you haven't automated your testing pipeline, shame on you, you should do that like a year ago. But now it's time to help people in production because you've done that other work and people are suffering. You know, the crazy thing about the cloud is, is that companies spend about three times more on the human beings to operate their cloud infrastructure as on the cloud infrastructure itself. I've yet to hear anybody say that their cloud bill is too low, you know, so, you know, there's a clearer savings also available. And you know, back when I was at AWS, obviously I had to keep the lights on too, but you know, I had to do that, but it's kind of a tax on my engineers and I'd really spend, prefer to spend the head count on innovation, on doing things that delight my customers. You never delight your customers by keeping the lights on, you just avoid irritating them by turning 'em off, right? >> So why are companies so fixed in on spending so much time on manually repairing things and not looking for these kinds of little, much more elegant solution and cost-efficient, time-saving, so on so forth. >> Yeah, I think there just hasn't been very much in this space as yet because it's a hard, hard problem to solve. You know, automation's a little bit scary and that's the reality of it and the way you make it less scary is by proving it out, by doing the simple things first, like reducing the alert fatigue, you know, that's easy. You know, providing notebooks to people so that they can click things and do things in a straightforward way. That's pretty easy. The full automation, that's kind of the North Star, that's what we aspire to do. But you know, people get there over time and one of our customers had 700 instances of this particular incident solved for them last week. You imagine how many human beings would've been doing it otherwise, you know? >> Right. >> That's just one thing, you know? >> How many did it take the build a pyramid? How many decades did that take, right? You had an announcement this week. I don't think we've talked about that. >> No, yeah, so we just announced Incident Insights, which is a free product that lets people plug into initially PagerDuty and pretty soon the Opsgenie ServiceNow, et cetera. And what you can do is, is you give us an API key read-only and we will suck your PagerDuty data out. We apply some lightweight ML unsupervised learning, and in a couple of minutes, we categorize all of your incidents so that you can understand which are the ones that happen most often and are getting resolved really quickly. That's ClickOps, right? Those alarms shouldn't fire. Which are the ones that involve a lot of people? Those are good candidates to build a notebook. Which are the ones that happen again and again and again? Those are good candidates for automation. And so, I think one of the challenges people have is, is that they don't actually know what their teams are doing and so this is intended to provide them that visibility. One of our very first customers was doing the beta test for us on it. He used to tell us he had about 100 tickets, incidents a week. You know, he brought this tool in and he had 2,100 last week and was all, you know, like these false alarms, so while he's giving us- >> That was eye opening for him to see that, sure. >> And why he's, you know, looking at it, you know, he's just like filing Jiras to say, "Oh, change this threshold, cancel this alarm forever." You know, all of that kind of stuff. Before you get to do the fancy work, you got to clean your room before you get to do anything else, right? >> Right, right, dinner before dessert, basically. >> There you go. >> Hey, thanks for the insights on this and again the name of the new product, by the way, is... >> Incident Insights. >> Incident Insights. >> Totally free. >> Free. >> Yeah, it takes a couple of minutes to set up. Go to the website, Shoreline.io/insight and you can be up and running in a couple of minutes. >> Outstanding, again, the company is Shoreline. This is Anurag Gupta, and thank you for being with us. We appreciate it. >> Appreciate it, thank you. >> Glad to have to here on theCUBE. Back with more from AWA re:Invent 22. You're watching theCUBE, the leader in high-tech coverage. (gentle music)
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of the AWS Global Showcase about what you're up to. But you know, back when I was at AWS, Just tell me about how you define that. and you don't get errors Yeah, you pity the poor soul So how do you go about trying So when you look at the numbers, And so the ability to do, you know, in the enterprise. And you know, back when I was at AWS, and not looking for these kinds of little, and the way you make it less the build a pyramid? and was all, you know, for him to see that, sure. And why he's, you know, before dessert, basically. and again the name of the new and you can be up and running thank you for being with us. Glad to have to here on theCUBE.
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Omri Gazitt, Aserto | KubeCon + CloudNative Con NA 2022
>>Hey guys and girls, welcome back to Motor City, Lisa Martin here with John Furrier on the Cube's third day of coverage of Coon Cloud Native Con North America. John, we've had some great conversations over the last two and a half days. We've been talking about identity and security management as a critical need for enterprises within the cloud native space. We're gonna have another quick conversation >>On that. Yeah, we got a great segment coming up from someone who's been in the industry, a long time expert, running a great company. Now it's gonna be one of those pieces that fits into what we call super cloud. Others are calling cloud operating system. Some are calling just Cloud 2.0, 3.0. But there's definitely a major trend happening around how cloud is going Next generation. We've been covering it. So this segment should be >>Great. Let's unpack those trends. One of our alumni is back with us, O Rika Zi, co-founder and CEO of Aerio. Omri. Great to have you back on the >>Cube. Thank you. Great to be here. >>So identity move to the cloud, Access authorization did not talk to us about why you found it assertive, what you guys are doing and how you're flipping that script. >>Yeah, so back 15 years ago, I helped start Azure at Microsoft. You know, one of the first few folks that you know, really focused on enterprise services within the Azure family. And at the time I was working for the guy who ran all of Windows server and you know, active directory. He called it the linchpin workload for the Windows Server franchise, like big words. But what he meant was we had 95% market share and all of these new SAS applications like ServiceNow and you know, Workday and salesforce.com, they had to invent login and they had to invent access control. And so we were like, well, we're gonna lose it unless we figure out how to replace active directory. And that's how Azure Active Directory was born. And the first thing that we had to do as an industry was fix identity, right? Yeah. So, you know, we worked on things like oof Two and Open, Id Connect and SAML and Jot as an industry and now 15 years later, no one has to go build login if you don't want to, right? You have companies like Odd Zero and Okta and one login Ping ID that solve that problem solve single sign-on, on the web. But access Control hasn't really moved forward at all in the last 15 years. And so my co-founder and I who were both involved in the early beginnings of Azure Active directory, wanted to go back to that problem. And that problem is even bigger than identity and it's far from >>Solved. Yeah, this is huge. I think, you know, self-service has been a developer thing that's, everyone knows developer productivity, we've all experienced click sign in with your LinkedIn or Twitter or Google or Apple handle. So that's single sign on check. Now the security conversation kicks in. If you look at with this no perimeter and cloud, now you've got multi-cloud or super cloud on the horizon. You've got all kinds of opportunities to innovate on the security paradigm. I think this is kind of where I'm hearing the most conversation around access control as well as operationally eliminating a lot of potential problems. So there's one clean up the siloed or fragmented access and two streamlined for security. What's your reaction to that? Do you agree? And if not, where, where am I missing that? >>Yeah, absolutely. If you look at the life of an IT pro, you know, back in the two thousands they had, you know, l d or active directory, they add in one place to configure groups and they'd map users to groups. And groups typically corresponded to roles and business applications. And it was clunky, but life was pretty simple. And now they live in dozens or hundreds of different admin consoles. So misconfigurations are rampant and over provisioning is a real problem. If you look at zero trust and the principle of lease privilege, you know, all these applications have these course grained permissions. And so when you have a breach, and it's not a matter of if, it's a matter of when you wanna limit the blast radius of you know what happened, and you can't do that unless you have fine grained access control. So all those, you know, all those reasons together are forcing us as an industry to come to terms with the fact that we really need to revisit access control and bring it to the age of cloud. >>You guys recently, just this week I saw the blog on Topaz. Congratulations. Thank you. Talk to us about what that is and some of the gaps that's gonna help sarto to fill for what's out there in the marketplace. >>Yeah, so right now there really isn't a way to go build fine grains policy based real time access control based on open source, right? We have the open policy agent, which is a great decision engine, but really optimized for infrastructure scenarios like Kubernetes admission control. And then on the other hand, you have this new, you know, generation of access control ideas. This model called relationship based access control that was popularized by Google Zanzibar system. So Zanzibar is how they do access control for Google Docs and Google Drive. If you've ever kind of looked at a Google Doc and you know you're a viewer or an owner or a commenter, Zanzibar is the system behind it. And so what we've done is we've married these two things together. We have a policy based system, OPPA based system, and at the same time we've brought together a directory, an embedded directory in Topaz that allows you to answer questions like, does this user have this permission on this object? And bringing it all together, making it open sources a real game changer from our perspective, real >>Game changer. That's good to hear. What are some of the key use cases that it's gonna help your customers address? >>So a lot of our customers really like the idea of policy based access management, but they don't know how to bring data to that decision engine. And so we basically have a, you know, a, a very opinionated way of how to model that data. So you import data out of your identity providers. So you connect us to Okta or oze or Azure, Azure Active directory. And so now you have the user data, you can define groups and then you can define, you know, your object hierarchy, your domain model. So let's say you have an applicant tracking system, you have nouns like job, you know, know job descriptions or candidates. And so you wanna model these things and you want to be able to say who has access to, you know, the candidates for this job, for example. Those are the kinds of rules that people can express really easily in Topaz and in assertive. >>What are some of the challenges that are happening right now that dissolve? What, what are you looking at to solve? Is it complexity, sprawl, logic problems? What's the main problem set you guys >>See? Yeah, so as organizations grow and they have more and more microservices, each one of these microservices does authorization differently. And so it's impossible to reason about the full surface area of, you know, permissions in your application. And more and more of these organizations are saying, You know what, we need a standard layer for this. So it's not just Google with Zanzibar, it's Intuit with Oddy, it's Carta with their own oddy system, it's Netflix, you know, it's Airbnb with heed. All of them are now talking about how they solve access control extracted into its own service to basically manage complexity and regain agility. The other thing is all about, you know, time to market and, and tco. >>So, so how do you work with those services? Do you replace them, you unify them? What is the approach that you're taking? >>So basically these organizations are saying, you know what? We want one access control service. We want all of our microservices to call that thing instead of having to roll out our own. And so we, you know, give you the guts for that service, right? Topaz is basically the way that you're gonna go implement an access control service without having to go build it the same way that you know, large companies like Airbnb or Google or, or a car to >>Have. What's the competition look like for you guys? I'm not really seeing a lot of competition out there. Are there competitors? Are there different approaches? What makes you different? >>Yeah, so I would say that, you know, the biggest competitor is roll your own. So a lot of these companies that find us, they say, We're sick and tired of investing 2, 3, 4 engineers, five engineers on this thing. You know, it's the gift that keeps on giving. We have to maintain this thing and so we can, we can use your solution at a fraction of the cost a, a fifth, a 10th of what it would cost us to maintain it locally. There are others like Sty for example, you know, they are in the space, but more in on the infrastructure side. So they solve the problem of Kubernetes submission control or things like that. So >>Rolling your own, there's a couple problems there. One is do they get all the corner cases who built a they still, it's a company. Exactly. It's heavy lifting, it's undifferentiated, you just gotta check the box. So probably will be not optimized. >>That's right. As Bezo says, only focus on the things that make your beer taste better. And access control is one of those things. It's part of your security, you know, posture, it's a critical thing to get right, but you know, I wanna work on access control, said no developer ever, right? So it's kind of like this boring, you know, like back office thing that you need to do. And so we give you the mechanisms to be able to build it securely and robustly. >>Do you have a, a customer story example that is one of your go-tos that really highlights how you're improving developer productivity? >>Yeah, so we have a couple of them actually. So there's the largest third party B2B marketplace in the us. Free retail. Instead of building their own, they actually brought in aer. And what they wanted to do with AER was be the authorization layer for both their externally facing applications as well as their internal apps. So basically every one of their applications now hooks up to AER to do authorization. They define users and groups and roles and permissions in one place and then every application can actually plug into that instead of having to roll out their own. >>I'd like to switch gears if you don't mind. I get first of all, great update on the company and progress. I'd like to get your thoughts on the cloud computing market. Obviously you were your legendary position, Azure, I mean look at the, look at the progress over the past few years. Just been spectacular from Microsoft and you set the table there. Amazon web service is still, you know, thundering away even though earnings came out, the market's kind of soft still. You know, you see the cloud hyperscalers just continuing to differentiate from software to chips. Yep. Across the board. So the hyperscalers kicking ass taking names, doing great Microsoft right up there. What's the future? Cuz you now have the conversation where, okay, we're calling it super cloud, somebody calling multi-cloud, somebody calling it distributed computing, whatever you wanna call it. The old is now new again, it just looks different as cloud becomes now the next computer industry, >>You got an operating system, you got applications, you got hardware, I mean it's all kind of playing out just on a massive global scale, but you got regions, you got all kinds of connected systems edge. What's your vision on how this plays out? Because things are starting to fall into place. Web assembly to me just points to, you know, app servers are coming back, middleware, Kubernetes containers, VMs are gonna still be there. So you got the progression. What's your, what's your take on this? How would you share, share your thoughts to a friend or the industry, the audience? So what's going on? What's, what's happening right now? What's, what's going on? >>Yeah, it's funny because you know, I remember doing this quite a few years ago with you probably in, you know, 2015 and we were talking about, back then we called it hybrid cloud, right? And it was a vision, but it is actually what's going on. It just took longer for it to get here, right? So back then, you know, the big debate was public cloud or private cloud and you know, back when we were, you know, talking about these ideas, you know, we said, well you know, some applications will always stay on-prem and some applications will move to the cloud. I was just talking to a big bank and they basically said, look, our stated objective now is to move everything we can to the public cloud and we still have a large private cloud investment that will never go away. And so now we have essentially this big operating system that can, you know, abstract all of this stuff. So we have developer platforms that can, you know, sit on top of all these different pieces of infrastructure and you know, kind of based on policy decide where these applications are gonna be scheduled. So, you know, the >>Operating schedule shows like an operating system function. >>Exactly. I mean like we now, we used to have schedulers for one CPU or you know, one box, then we had schedulers for, you know, kind of like a whole cluster and now we have schedulers across the world. >>Yeah. My final question before we kind of get run outta time is what's your thoughts on web assembly? Cuz that's getting a lot of hype here again to kind of look at this next evolution again that's lighter weight kind of feels like an app server kind of direction. What's your, what's your, it's hyped up now, what's your take on that? >>Yeah, it's interesting. I mean back, you know, what's, what's old is new again, right? So, you know, I remember back in the late nineties we got really excited about, you know, JVMs and you know, this notion of right once run anywhere and yeah, you know, I would say that web assembly provides a pretty exciting, you know, window into that where you can take the, you know, sandboxing technology from the JavaScript world, from the browser essentially. And you can, you know, compile an application down to web assembly and have it real, really truly portable. So, you know, we see for example, policies in our world, you know, with opa, one of the hottest things is to take these policies and can compile them to web assemblies so you can actually execute them at the edge, you know, wherever it is that you have a web assembly runtime. >>And so, you know, I was just talking to Scott over at Docker and you know, they're excited about kind of bringing Docker packaging, OCI packaging to web assemblies. So we're gonna see a convergence of all these technologies right now. They're kind of each, each of our, each of them are in a silo, but you know, like we'll see a lot of the patterns, like for example, OCI is gonna become the packaging format for web assemblies as it is becoming the packaging format for policies. So we did the same thing. We basically said, you know what, we want these policies to be packaged as OCI assembly so that you can sign them with cosign and bring the entire ecosystem of tools to bear on OCI packages. So convergence is I think what >>We're, and love, I love your attitude too because it's the open source community and the developers who are actually voting on the quote defacto standard. Yes. You know, if it doesn't work, right, know people know about it. Exactly. It's actually a great new production system. >>So great momentum going on to the press released earlier this week, clearly filling the gaps there that, that you and your, your co-founder saw a long time ago. What's next for the assertive business? Are you hiring? What's going on there? >>Yeah, we are really excited about launching commercially at the end of this year. So one of the things that we were, we wanted to do that we had a promise around and we delivered on our promise was open sourcing our edge authorizer. That was a huge thing for us. And we've now completed, you know, pretty much all the big pieces for AER and now it's time to commercially launch launch. We already have customers in production, you know, design partners, and you know, next year is gonna be the year to really drive commercialization. >>All right. We will be watching this space ery. Thank you so much for joining John and me on the keep. Great to have you back on the program. >>Thank you so much. It was a pleasure. >>Our pleasure as well For our guest and John Furrier, I'm Lisa Martin, you're watching The Cube Live. Michelle floor of Con Cloud Native Con 22. This is day three of our coverage. We will be back with more coverage after a short break. See that.
SUMMARY :
We're gonna have another quick conversation So this segment should be Great to have you back on the Great to be here. talk to us about why you found it assertive, what you guys are doing and how you're flipping that script. You know, one of the first few folks that you know, really focused on enterprise services within I think, you know, self-service has been a developer thing that's, If you look at the life of an IT pro, you know, back in the two thousands they that is and some of the gaps that's gonna help sarto to fill for what's out there in the marketplace. you have this new, you know, generation of access control ideas. What are some of the key use cases that it's gonna help your customers address? to say who has access to, you know, the candidates for this job, area of, you know, permissions in your application. And so we, you know, give you the guts for that service, right? What makes you different? Yeah, so I would say that, you know, the biggest competitor is roll your own. It's heavy lifting, it's undifferentiated, you just gotta check the box. So it's kind of like this boring, you know, Yeah, so we have a couple of them actually. you know, thundering away even though earnings came out, the market's kind of soft still. So you got the progression. So we have developer platforms that can, you know, sit on top of all these different pieces know, one box, then we had schedulers for, you know, kind of like a whole cluster and now we Cuz that's getting a lot of hype here again to kind of look at this next evolution again that's lighter weight kind the edge, you know, wherever it is that you have a web assembly runtime. And so, you know, I was just talking to Scott over at Docker and you know, on the quote defacto standard. that you and your, your co-founder saw a long time ago. And we've now completed, you know, pretty much all the big pieces for AER and now it's time to commercially Great to have you back on the program. Thank you so much. We will be back with more coverage after a short break.
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Eric Herzog, Infinidat | CUBEConversation
>>Hey everyone, welcome to this cube conversation. I'm your host Lisa Martin, and I have the pleasure of welcoming back our most prolific guest on the cube in its history, the CMO of Fin Ad, Eric Herzog. Eric, it's great to see you. Welcome back, >>Lisa. It's great to be here. Love being on the cube. I think this might be number 55 or 56. Been doing 'em a long time with the Cube. You guys are great. >>You, you have, and we always recognize you lately with the Hawaiian shirts. It's your brand that's, that's the Eric Hizo brand. We love it. But I like the pin, the infin nut pin on brand. Thank you. >>Yeah. Oh, gotta be on brand. >>Exactly. So talk about the current IT landscape. So much change we've seen in the last couple of years. Specifically, what are some of the big challenges that you are talking with enterprise customers and cloud service providers? About what, what are some of those major things on their minds? >>So there's a couple things. First of all is obviously with the Rocky economy and even before covid, just for storage in particular, CIOs hate storage. I've been doing this now since 1986. I have never, ever, ever met a CIO at any company I've bid with. And I've been with four of the biggest storage companies on this planet. Never met a cio. Used to be a storage guy. So they know they need it, but boy, they really don't like it. So the storage admins have to manage more and more storage. Exabytes, exabytes, it just ballooning for what a storage admin has to do. Then you then have the covid and is it recession? No. Is it a growth? And then clearly what's happened in the last year with what's going on in Europe and the, is it a recession, the inflation. So they're always looking to, how do we cut money on storage yet still get what we need for our applications, workloads, and use cases. So that's definitely the biggest, the first topic. >>So never met a CIO that was a storage admin or as a fan, but as you point out, they need it. And we've seen needs changing in customer landscapes, especially as the threat landscape has changed so dramatically the last couple of years. Ransomware, you've said it before, I say it too. It's no longer if it's when it's how often. It's the frequency. We've gotta be able to recover. Backups are being targeted. Talk to me about some of, in that landscape, some of the evolutions of customer challenges and maybe those CIOs going, We've gotta make sure that our, our storage data is protected. >>So it's starting to change. However, historically with the cio and then when they started hiring CISOs or security directors, whatever they had, depending on the company size, it was very much about protecting the edge. Okay, if you will, the moat and the wall of the castle. Then it was the network in between. So keep the streets inside the castle clean. Then it was tracking down the bad guy. So if they did get over, the issue is, if I remember correctly, the sheriff of Nottingham never really caught Robinhood. So the problem is the dwell time where the ransomware malware's hidden on storage could be as much as 200 days. So I think they're starting to realize at the security level now, forget, forget the guys on the storage side, the security guys, the cso, the CIO, are starting to realize that if you're gonna have a comprehensive cybersecurity strategy, must include storage. And that is new >>That, well, that's promising then. That's new. I mean obviously promising given the, the challenges and the circumstances. So then from a storage perspective, customers that are in this multi-cloud hybrid cloud environment, you talked about the the edge cloud on-prem. What are some of the key things from a storage perspective that customers have to achieve these days to be secure as data volumes continue to grow and spread? >>So what we've done is implement on both primary storage and secondary storage and technology called infin safe. So Infin Safe has the four legs of the storage cyber security stool. So first of all is creating an air gap. In this case, a logical air gap can be local or remote. We create an immutable snapshot, which means it can't be changed, it can't be altered, so you can't change it. We have a fenced forensic environment to check out the storage because you don't wanna recover. Again, malware and rans square can is hidden. So you could be making amenable snapshots of actually malware, ransomware, and never know you're doing it right. So you have to check it out. Then you need to do a rapid recovery. The most important thing if you have an attack is how fast can you be up and going with recovery? So we have actually instituted now a number of cyber storage security guarantees. >>We will guarantee the SLAs on a, the snapshot is absolutely immutable. So they know that what they're getting is what they were supposed to be getting. And then also we are guaranteeing recovery times on primary storage. We're guaranteeing recovery of under one minute. We'll make the snapshot available under one minute and on secondary storage under 20 minutes. So those are things you gotta look for from a security perspective. And then the other thing you gotta practice, in my world, ransomware, malware, cyber tech is basically a disaster. So yes, you got the hurricane, yes, you got the flood, yes, you got the earthquake. Yes, you got the fire in the building. Yes you got whatever it may be. But if you don't practice malware, ransomware, recoveries and protection, then it might as well be a hurricane or earthquake. It will take your data, >>It will take your data on the numbers of customers that pay ransom is pretty high, isn't it? And and not necessarily able to recover their data. So it's a huge risk. >>So if you think about it, the government documented that last year, roughly $6 trillion was spent either protecting against ransomware and malware or paying ransomware attacks. And there's been several famous ones. There was one in Korea, 72 million ransom. It was one of the Korea's largest companies. So, and those are only the ones that make the news. Most of 'em don't make the news. Right. >>So talk to me then, speaking and making the news. Nobody wants to do that. We, we know every industry is vulnerable to this. Some of the ones that might be more vulnerable, healthcare, government, public sector education. I think the Los Angeles Unified School district was just hit as well in September. They >>Were >>What, talk to me about how infin out is helping customers really dial down the risk when the threat actors are becoming more and more sophisticated? >>Well, there's a couple things. First of all, our infin safe software comes free on our main product. So we have a product called infin Guard for Secondary Storage and it comes for free on that. And then our primary storage product's called the Infin Box. It also comes for free. So they don't have to use it, but we embed it. And then we have reference architectures that we give them our ses, our solutions architects and our technical advisors all up to speed on why they should do it, how they should do it. We have a number of customers doing it. You know, we're heavily concentrated the global Fortune 2000, for example, we publicly announced that 26% of the Fortune 50 use our technology, even though we're a small company. So we go to extra lengths to a B, educated on our own front, our own teams, and then B, make sure they portray that to the end users and our channel partners. But the end users don't pay a dime for the software that does what I just described, it's free, it's included when you get you're Infin box or you're ingar, it's included at no charge. >>That's pretty differentiating from a competitive standpoint. I might, I would guess >>It is. And also the guarantee. So for example, on primary storage, okay, whether you'd put your Oracle or put your SAP or I Mongo or your sequel or your highly transactional workloads, right? Your business finance workload, all your business critical stuff. We are the first and only storage company that offers a primary guarantee on cyber storage resilience. And we offer two of them on primary storage. No other vendor offers a guarantee, which we do on primary storage. Whether you the first and right now as of here we are sitting in the middle of October. We are still the only vendor that offers anything on primary storage from a guaranteed SLA on primary storage for cyber storage resilience. >>Let's talk about those guarantees. Walk me through what you just announced. There's been a a very, a lot of productivity at Infin DAT in 2022. A lot of things that you've announced but on crack some of the things you're announcing. Sure. Talk to me specifically about those guarantees and what's in it for me as a customer. It sounds pretty obvious, but I'd love to hear it from you. >>Okay, so we've done really three different types of guarantees. The first one is we have a hundred percent availability guarantee on our primary storage. And we've actually had that for the last, since 2019. So it's a hundred percent availability. We're guaranteed no downtime, a hundred percent availability, which for our customer base being heavily concentrated, the global Fortune 2000 large government enterprises, big universities and even smaller companies, we do a lot of business with CSPs and MSPs. In fact, at the Flash Memory Summit are Infin Box ssa All Flash was named the best product for hyperscaler deployment. Hyperscaler basically means cloud servers provider. So they need a hundred percent availability. So we have a guarantee on that. Second guarantee we have is a performance guarantee. We'll do an analysis, we look at all their workloads and then we will guarantee in writing what the performance should be based on which, which of our products they want to buy are Infin Box or Infin Box ssa, which is all flash. >>Then we have the third one is all about cyber resilience. So we have two on our Infin box, our Infin box SSA for primary storage, which is a one the immutability of the snapshot and immediately means you can't erase the data. Right? Camp tamper with it. Second one is on the recovery time, which is under a minute. We just announced in the middle of October that we are doing a similar cyber storage resilience guarantee on our ARD secondary product, which is designed for backup recovery, et cetera. We will also offer the immutably snapshot guarantee and also one on the recoverability of that data in under 20 minutes. In fact, we just did a demo at our live launch earlier this week and we demoed 20 petabytes of Veeam backup data recovered in 12 minutes. 12 >>Minutes 2012. >>20 petabytes In >>12 bytes in 12 minutes. Yes. That's massive. That's massively differentiating. But that's essential for customers cuz you know, in terms of backups and protecting the data, it's all about recovery >>A and once they've had the attack, it's how fast you get back online, right? That that's what happens if they've, if they can't stop the attack, can't stop the threat and it happens. They need to get that back as fast as they can. So we have the speed of recovery on primary stores, the first in the industry and we have speed on the backup software and we'll do the same thing for a backup data set recovery as well. Talk >>To me about the, the what's in it for me, For the cloud service providers, they're obviously the ones that you work with are competing with the hyperscalers. How does the guarantees and the differentiators that Fin out is bringing to market? How do you help those cloud SPS dial up their competitiveness against the big cheeses? >>Well, what we do is we provide that underlying infrastructure. We, first of all, we only sell things that are petabyte in scale. That's like always sell. So for example, on our in fitter guard product, the raw capacity is over four petabytes. And the effective capacity, cuz you do data reduction is over 85 petabytes on our newest announced product, on our primary storage product, we now can do up to 17 petabytes of effective capacity in a single rack. So the value to the service rider is they can save on what slots? Power and floor. A greener data center. Yeah, right. Which by the way is not just about environmentals, but guess what? It also translate into operational expense. >>Exactly. CapEx office, >>With a lot of these very large systems that we offer, you can consolidate multiple products from our competitors. So for example, with one of the competitors, we had a deal that we did last quarter 18 competitive arrays into one of ours. So talk about saving, not just on all of the operational expense, including operational manpower, but actually dramatically on the CapEx. In fact, one of our Fortune 500 customers in the telco space over the last five years have told us on CapEx alone, we've saved them $104 million on CapEx by consolidating smaller technology into our larger systems. And one of the key things we do is everything is automated. So we call it autonomous automation use AI based technology. So once you install it, we've got several public references who said, I haven't touched this thing in three or four years. It automatically configures itself. It automatically adjusts to changes in performance and new apps. When I put in point a new app at it automatically. So in the old days the storage admin would optimize performance for a new application. We don't do that, we automatically do it and autonomously the admin doesn't even click a button. We just sense there's new applications and we automate ourselves and configure ourselves without the admin having to do anything. So that's about saving operational expense as well as operational manpower. >>Absolutely. I was, one of the things that was ringing in my ear was workforce productivity and obviously those storage admins being able to to focus on more strategic projects. Can't believe the CIOs aren't coming around yet. But you said there's, there's a change, there's a wave coming. But if we think about the the, the what's in it for me as a customer, the positive business outcomes that I'm hearing, lower tco, your greener it, which is key. So many customers that we talk to are so focused on sustainability and becoming greener, especially with an on-prem footprint, workforce productivity. Talk about some of the other key business outcomes that you're helping customers achieve and how it helps them to be more competitive. >>Sure. So we've got a, a couple different things. First of all, storage can't go down. When the storage goes down, everyone gets blamed. Mission. When an app goes down, no one really thinks about it. It's always the storage guy's fault. So you want to be a hundred percent available. And that's today's businesses, and I'd actually argue it's been this way for 20 years are 24 by seven by 365. So that's one thing that we deliver. Second thing is performance. So we have public references talk about their SAP workload that used to take two hours, now takes 20 minutes, okay? We have another customer that was doing SAP queries. They improved their performance three times, Not 3%, not 3%, three times. So 300% better performance just by using our storages. They didn't touch the sap, they didn't touch the servers. All they do is to put our storage in there. >>So performance relates basically to applications, workloads and use cases and productivity beyond it. So think the productivity of supply chain guys, logistics guys, the shipping guys, the finance guys, right? All these applications that run today's enterprises. So we can automate all that. And then clearly the cyber threat. Yeah, that is a huge issue. And every CIO is concerned about the cyber threat. And in fact, it was interesting, Fortune magazine did a survey of CEOs, and this was last May, the number one concern, 66% in that may survey was cyber security number one concern. So this is not just a CIO thing, this is a CEO thing and a board level >>Thing. I was gonna say it's at at the board level that the cyber security threats are so real, they're so common. No one wants to be the next headline, like the colonial pipeline, right? Or the school districts or whatnot. And everybody is at risk. So then what you're enabling with what you've just announced, the all the guarantees on the SLAs, the massively fast recovery times, which is critical in cyber recovery. Obviously resilience is is key there. Modern data protection it sounds like to me. How do you define that and and what are customers looking for with respect to modern cyber resilience versus data protection? >>Yeah, so we've got normal data protection because we work with all the backup vendors. Our in ARD is what's known as a purpose built backup appliance. So that allows you to back at a much faster rate. And we work all the big back backup vendors, IBM spectrum Protect, we work with veritas vem com vault, oracle arm, anybody who does backup. So that's more about the regular side, the traditional backup. But the other part of modern data protection is infusing that with the cyber resilience. Cuz cyber resilience is a new thing. Yes, from a storage guy perspective, it hasn't been around a long time. Many of our competitors have almost nothing. One or two of our competitors have a pretty robust, but they don't guarantee it the way we guarantee it. So they're pretty good at it. But the fact that we're willing to put our money where our mouth is, we think says we price stand above and then most of the other guys in the storage industry are just starting to get on the bandwagon of having cyber resilience. >>So that changes what you do from data protection, what would call modern data protection is a combination of traditional backup recovery, et cetera. Now with this influence and this infusion of cybersecurity cyber resilience into a storage environment. And then of course we've also happened to add it on primary storage as well. So whether it's primary storage or backup and archive storage, we make sure you have that right cyber resilience to make it, if you will, modern data protection and diff different from what it, you know, the old backup of your grandfather, father, son backup in tape or however you used to do it. We're well beyond that now we adding this cyber resilience aspect. Well, >>From a cyber resilience perspective, ransomware, malware, cyber attacks are, that's a disaster, right? But traditional disaster recovery tools aren't really built to be able to pull back that data as quickly as it sounds like in Trinidad is able to facilitate. >>Yeah. So one of the things we do is in our reference architectures and written documentation as well as when we do the training, we'd sell the customers you need to practice, if you practice when there's a fire, a flood, a hurricane, an earthquake or whatever is the natural disaster you're practicing that you need to practice malware and ran somewhere. And because our recovery is so rapid and the case of our ingar, our fenced environment to do the testing is actually embedded in it. Several of our competitors, if you want the fenced environment, you have to buy a second product with us. It's all embedded in the one item. So A, that makes it more effective from a CapEx and opex perspective, but it also makes it easier. So we recommend that they do the practice recoveries monthly. Now whether they do it or not separate issue, but at least that's what we're recommending and say, you should be doing this on a monthly basis just like you would practice a disaster, like a hurricane or fire or a flood or an earthquake. Need to be practicing. And I think people are starting to hear it, but they don't still think more about, you know, the flood. Yeah. Or about >>The H, the hurricane. >>Yeah. That's what they think about. They not yet thinking about cybersecurity as really a disaster model. And it is. >>Absolutely. It is. Is is the theme of cyber resilience, as you said, this is a new concept, A lot of folks are talking about it, applying it differently. Is that gonna help dial up those folks just really being much more prepared for that type of cyber disaster? >>Well, we've made it so it's automated. Once you set up the immutable snapshots, it just does its thing. You don't set it and forget it. We create the logical air back. Once you do it, same thing. Set it and forget it. The fence forensic environment, easy to deploy. You do have to just configure it once and then obviously the recovery is almost instantaneous. It's under a minute guaranteed on primary storage and under 20 minutes, like I told you when we did our launch this week, we did 20 petabytes of Veeam backup data in 12 minutes. So that's pretty incredible. That's a lot of data to have recovered in 12 minutes. So the more automated we make it, which is what our real forte is, is this autonomous automation and automating as much as possible and make it easy to configure when you do have to configure. That's what differentiates what we do from our perspective. But overall in the storage industry, it's the recognition finally by the CISOs and the CIOs that, wait a second, maybe storage might be an essential part of my corporate cybersecurity strategy. Yes. Which it has not been historically, >>But you're seeing that change. Yes. >>We're starting to see that change. >>Excellent. So talk to me a little bit before we wrap here about the go to market one. Can folks get their hands on the updates to in kindergar and Finn and Safe and Penta box? >>So all these are available right now. They're available now either through our teams or through our, our channel partners globally. We do about 80% of our business globally through the channel. So whether you talk to us or talk to our channel partners, we're there to help. And again, we put our money where your mouth is with those guarantees, make sure we stand behind our products. >>That's awesome. Eric, thank you so much for joining me on the program. Congratulations on the launch. The the year of productivity just continues for infinit out is basically what I'm hearing. But you're really going in the extra mile for customers to help them ensure that the inevitable cyber attacks, that they, that they're complete storage environment on prem will be protected and more importantly, recoverable Very quickly. We appreciate your insights and your input. >>Great. Absolutely love being on the cube. Thank you very much for having us. Of >>Course. It's great to have you back. We appreciate it. For Eric Herzog, I'm Lisa Martin. You're watching this cube conversation live from Palo Alto.
SUMMARY :
and I have the pleasure of welcoming back our most prolific guest on the cube in Love being on the cube. But I like the pin, the infin nut pin on brand. So talk about the current IT landscape. So the storage admins have to manage more and more So never met a CIO that was a storage admin or as a fan, but as you point out, they need it. So the problem is the dwell time where the ransomware malware's hidden on storage could be as much as 200 days. So then from a storage perspective, customers that are in this multi-cloud hybrid cloud environment, So Infin Safe has the four legs of the storage cyber security stool. So yes, you got the hurricane, yes, you got the flood, yes, you got the earthquake. And and not necessarily able to recover their data. So if you think about it, the government documented that last year, So talk to me then, speaking and making the news. So we have a product called infin Guard for Secondary Storage and it comes for free I might, I would guess We are the first and only storage company that offers a primary guarantee on cyber on crack some of the things you're announcing. So we have a guarantee on that. in the middle of October that we are doing a similar cyber cuz you know, in terms of backups and protecting the data, it's all about recovery of recovery on primary stores, the first in the industry and we have speed on the backup software How does the guarantees and the differentiators that Fin And the effective capacity, cuz you do data reduction Exactly. So in the old days the storage admin would optimize performance for a new application. So many customers that we talk to are so focused on sustainability So that's one thing that we deliver. So performance relates basically to applications, workloads and use cases and productivity beyond it. So then what you're enabling with what you've just announced, So that's more about the regular side, the traditional backup. So that changes what you do from data protection, what would call modern data protection is a combination of traditional built to be able to pull back that data as quickly as it sounds like in Trinidad is able to facilitate. And because our recovery is so rapid and the case And it is. Is is the theme of cyber resilience, as you said, So the more automated we make it, which is what our real forte is, But you're seeing that change. So talk to me a little bit before we wrap here about the go to market one. So whether you talk to us or talk to our channel partners, we're there to help. Congratulations on the launch. Absolutely love being on the cube. It's great to have you back.
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George Kurtz, CrowdStrike | CrowdStrike Fal.Con 2022
(upbeat music) >> Welcome back to The Cube's coverage of Fal.Con 22. I'm Dave Vellante with Dave Nicholson. This is day one of our coverage. We had the big keynotes this morning. Derek Jeter was one of the keynotes. We have a big Yankee fan here: George Kurtz is the co-founder and CEO of CrowdStrike. George, thanks for coming on The Cube. >> It's great to be here. >> Boston fan, you know, I tweeted out Derek Jeter. He broke my heart many times, but I can't hate on Jeter. You got to have respect for the guy. >> Well, I still remember I was in Japan when Boston was down you know, by three games and came back to win. So I've got my own heartbreak as well. >> It did heal some wounds, but it almost changed the rivalry, you know? I mean, >> Yeah. >> Once, it's kind of neutralized it, you know? It's just not as interesting. I mean, I'm a season ticket holder. I go to all the games and Yankee games are great. A lot of it used to be, you would never walk into Fenway park with, you know pin stripes, when today there's as many Yankee fans as there are... >> I know. >> Boston fans. Anyway, at Fenway, I mean. >> Yeah. >> Why did you start CrowdStrike? >> Biggest thing for me was to really change the game in how people were looking at security. And at my previous company, I think a lot of people were buying security and not getting the outcome that they wanted. Not- I got acquired by a company, not my first company. So, to be clear, and before I started CrowdStrike, I was in the antivirus world, and they were spending a lot of money with antivirus vendors but not getting the outcome I thought they should achieve, which is to stop the breach, not just stop malware. And for me, security should be outcome based not sort of product based. And the biggest thing for us was how could we create the sales force of security that was focused on getting the right outcome: stopping the breach. >> And the premise, I've seen it, the unstoppable breach is a myth. No CSOs don't live by that mantra, but you do. How are you doing on that journey? >> Well I think, look, there's no 100% of anything in security, but what we've done is really created a platform that's focused on identifying and stopping breaches as well as now, extending that out into helping IT identify assets and their hygiene and basically providing more visibility into IT assets. So, we talked about the convergence of that. Maybe we'll get into it, but. >> Dave Vellante: Sure. >> We're doing pretty well. And from our standpoint, we've got a lot of customers, almost 20,000, that rely on us day to day to help stop the breach. >> Well, and when you dig into the CrowdStrike architecture, what's so fascinating is, you know, Dave, we've talked about this: agent bad. Well, not necessarily, if you can have a lightweight agent that can scale and support a number of modules, then you can consolidate all these point tools out there. You talked about in your keynote, your pillars, workloads, which really end points >> Right. >> ID, which we're going to talk about. Identity data and network security. You're not a network security specialist, >> Right. >> But the other three, >> Yes. >> You're knocking down. >> Yeah. >> You guys went deep into that today. Talk about that. >> We did, most folks are going to know us for endpoint and Cloud workload protection and visibility. We did an acquisition almost two years to the day on preempt. And that was our identity play, identity threat protection and detection. And that really turned out to be a smart move, because it's the hottest topic right now. If you look at all the breaches over the last couple years, it's all identity based. Big, big talking points in our keynotes today. >> Dave Vellante: Right. >> And then the third area is on data, and data is really the you know, the new currency that people trade in. So how do you identify and protect endpoints and workloads? How do you tie that together with identity, as well as understanding how you connect the dots and the data and where data flows? And that's really been our focus and we continue to deliver on that for customers. >> And you've had a real dogma, I'll call it, about Cloud Native. I've had this conversation with Frank Slootman, "No we're not going to do a halfway house." You, I think, said it really well today. I think it was you who said it. If you've got On-Prem and Cloud, you got two code bases, >> George Kurtz: Right. >> That you got to maintain. >> That's it, yeah. >> And that means you're taking away resources from one or the other. >> That's exactly right. And what a lot of our competitors have done is they started On-Prem as an AV vendor, and then they took what they had and they basically put it in a Cloud instance called a Cloud, which doesn't really scale. And then, you know, where they need to, they basically still keep their On-Prem, and that just diffuses your engineering team. And most of the On-Prem stuff doesn't even have the features of what they're trying to offer from the Cloud. So either you're Cloud Native or you're not. You can't be halfway. >> But it doesn't mean that you can't include and ingest On-Prem data- >> Well, absolutely. >> into your platform, and that's what I think most people just some reason don't seem to understand. >> Well our agents run wherever. They certainly run On-Prem. >> Dave Vellante: Right. Right. >> And they run in the Cloud, they run wherever. But the crowd in the CrowdStrike is the fact that we can crowdsource this threat information at scale into our threat graph, which gives us unique insight, 7 trillion events per week. And you can't do that if you're not Cloud Native. And that crowd gives the, we call, community immunity. We see all kinds of attacks across 176 different countries. That benefit accrues to all of our customers. >> But how do you envision and maintain and preserve a lightweight agent that can support so many modules? As you do more acquisitions and you knock down new areas and bring in new functionality, go after things like operations technology, how is it that you're able to keep that agent lightweight? >> Well, we started as a platform company, meaning that the whole idea was we're going to build a lightweight agent. First iteration had no security capabilities. It was collect data, get it into a common data architecture or threat graph, in one spot. And then once we had the data then we applied AI to it and we created different workflows. So, the first incarnation was get data into the Cloud at scale. And that still holds true today. So if you think about why we can actually have all these different modules without an impact on the performance, it's we collect data one time. It's a threat data, you know? We're not collecting user data, but threat data collection mechanism. Once we have all that data, then we can slice and dice and create other modules. So the new modules never have to even touch the agent 'cause we've already collected the data. >> I'm going to just keep going, Dave, unless you shove your way in. >> No, no, go ahead. No, no, no. I'm waiting to pounce. >> But okay, so, I think, George, but George, I need to ask you about a comment that you made about we're not just shoving it into a data lake. But you are collecting all the data. Can you explain that nuance? >> Yeah. So there's a difference between a collect and forward agent. It means they just collect a bunch of data. They'll probably store it in a lot of space on the endpoint. It's slow and cumbersome, and then they'll forward it up into another data lake. So you have no context going into no context. Our agent is a smart agent, which actually allows us to always track the context of all these processes in what's happening on the endpoint. And it's a mini graph, meaning we keep track of the relationships. And as we ship that contextual information to the Cloud, we never lose that context. And then it goes into the bigger graph database, always with the same level of context. So, we keep the context of each individual workload or endpoint, and then across the Cloud, we have the context of all of those put together. It's massive. And that allows us to create different insights rather than a data lake, which is, you know, you're looking for, you're creating a bigger needle stack looking for needles. >> And I'm envisioning almost an index that is super, super fast. I mean, you're talking about sub, well second kind of near real time responses, correct? >> Absolutely. So a lot of what we do in terms of protection is already pushed down to the endpoint , 'cause it has intelligence and the AI model. And then again, the Cloud is always looking for different anomalies, not only on each individual endpoint or workload, but across the entire spectrum of our customer base. And that's all real time. It continually self-learns from all the data we collect. >> So when, yeah, when you've made these architectural decisions over time, there was a time when saying that you needed to run an agent could be a deal killer somewhere for people who argued against that. >> George Kurtz: Right. >> You've made the right decision there, clearly. Having everything be crowdsourced into Cloud makes perfect sense. Has that, though, posed a challenge from a sovereignty perspective? If you were deploying stuff On-Prem all over the place, you don't need to worry about that. Everything is here >> George Kurtz: Yeah. >> in a given country. How do you address the challenges of sovereignty when these agents are sending data into some sort of centralized Cloud space that crosses boundaries? >> Well, yeah, I guess what we would, let me go back to the beginning. So I started company in 2011 and I had to convince people that delivering endpoint security from the Cloud was going to be a good thing. >> Dave Vellante: Right. (chuckles) >> You know, you go into a Swiss bank and a bunch of other places and they're like, you're crazy. Right? >> Dave Nicholson: Right. >> They all became customers afterwards, right? And you have to just look at what they're doing. And the question I would have in the early days is, well, let me ask you are you using Dropbox, Box? Are you using a Microsoft? You know, what are you using? Well, they're all sending data to the Cloud. So good news! You already have a model, you've already approved that, right? So let's talk about our benefit. And you know, you can either have an adversary steal your data or you can send threat data to our Cloud, which by the way is in a lot of sovereign Clouds that are out there. And when you actually break it down to what we're sending to the Cloud, it's threat data, right? It isn't user files and documents and stuff. It's threat data. So, we work through all of that. And the Cloud is bigger than CrowdStrike. So you look at Sales Force, Service Now, Workday, et cetera. That's being used all over the place, Box, Dropbox. We just tagged onto it. Like why shouldn't security be the platform of record, and why shouldn't CrowdStrike be the platform of record and be the pillar of Cloud security? >> Explain your observability strategy, 'cause you acquired Humio for, I mean, I think it was $400 million, which is a song. >> Yeah. >> And then Reposify is the latest acquisition. I see that as an extension, 'cause it gives you visibility. Is that part of your security, of your observability play? Explain where you do play and don't play. >> Sure. Well observability is a big, you know, fluffy word. Where we play is in probably the first two areas of observability, right? There's five, kind of, pillars. We're focused on event collection. Let's get events from the endpoints. Let's get events from really anywhere in the network. And we can do that with Humio is now log scale. And then the second piece is with our agents, let's get an understanding of their, the asset itself. What is the asset? What state is it in? Does it have vulnerabilities? Does it have, you know, is it running out of disc space? Is it have, does it have a performance issue? Those are really the first two, kind of, areas of observability. We're not in application performance, we're in let's collect data from the endpoint and other sources, and let's understand if the thing is working, right? And that's a huge value for customers. And we can do that because we already have a privileged spot on the endpoint with our agent. >> Got it. Question on the TAM. Like I look at your TAMs, your charts, I love it. You know, generally do. Were you taking known data from you know, firms like IDC >> George Kurtz: Yeah. >> and saying, okay we're going to play there, now we're made this acquisition. We're new modules, now we're playing there. Awesome. I think you got a big TAM. And I guess that's, that's the point. There's no lack of market for you. >> George Kurtz: Right. >> But I do feel like there's this unknown unquantifiable piece of your TAM. IDC can't see it, 'cause they're kind of looking back >> George Kurtz: Right. >> seein' what the market do last year and we'll forecast it out. It's almost, you got to be a futurist to see it. How do you think about your total available market and the opportunity that's out there? >> Well, it's well in excess of 120 billion and we've actually updated that recently. So it's even beyond that. But if you look at all the modules each module has a discreet TAM and again, for what, you know, what we're focused on is how do you give an outcome to a customer? So a lot of the modules map back into specific TAM and product categories. When you add 'em all up and when you look at, you know, some of the new things that we're coming out with, again, it's well in excess of 120 billion. So that's why we like to say like, you know, we're not an endpoint company. We're really, truly a security platform company that was born in the Cloud. And I think if you see the growth rates, and one of the things that we've talked about, and I think you might have pointed out in prior podcasts, is we're the second fastest company to 2 billion dollars in annual recurring revenue, only behind Zoom. And you know I would argue- great company, by the way, a customer- but that was a black Swan event in a pandemic, right? >> Dave Vellante: I'll say! >> Yeah. >> So we are rarefied air when you think about the capabilities that we have and the performance and the TAM that's available to us. >> The other thing I said in my breaking analysis was 'cause you guys aspire to be a generational company. And I think you got a really good shot at being one, but to be a generational company, you have to have an ecosystem. So I'd love you to talk about the ecosystem, but where you want to see it in five years. >> Well, it really is a good point and we are a partner first company. Ecosystem is really important. Cameras probably can't see all the vendors that are here that are our partners, right? It's a big part of this show that we're at. You see a lot of, well, you see some vendors behind us. >> Yep. >> We have to realize in 2022, and I think this is something that we did well and it's my philosophy, is we are not the only game in town. We like to be, and we are, for many companies the security platform on record, but we don't do everything. We talked about network in other areas. We can't do everything. You can't be good and try to do everything. So, for customers today, what they're looking at is best of platform. And in the early days of security, I've been in it over 30 years, it used to be best of breed products, then it was best of suite, now it's best of platform. So what do I mean by that? It means that customers don't want to engineer their own solution. They, like Lego blocks, they want to pull the platforms, and they want to stitch 'em together via API. And they want to say, okay, CrowdStrike works with Okta, works with Zscaler, works with Proofpoint, et cetera. And that's what customers want. So, ecosystem is incredibly important for us. >> Explain that. You mentioned Okta, I had another question for you. I was at Reinforce, and I saw this better together presentation, CrowdStrike and Okta talking about identity. You've got an identity module. Explain to people how you're not competing with Okta. You guys complement each other, there. >> Well, an identity kind of broker, if you will, is basically what Okta does in others, right? So you log in single sign on and you get access. They broker access to all these other applications. >> Dave Vellante: Right. >> That's not what we do. What we do is we look at those endpoints and workloads and domain controllers and directory services and we figure out, are there vulnerabilities and are there threats associated with them? And we call that out. The second piece, which is critical, is we prevent lateral movement. So if credentials are stolen we can prevent those credentials from being laundered or used and moved laterally, which is a key part of how breaches happen. We then create a trust score on those endpoints and workloads. And we basically say, okay, do we think the trust on the endpoint and workload is high or low? Do we think the identity, you know, is it George on the endpoint, or not? We give that a score. And we pass that along to Okta or Ping or whoever, and they then use that as part of their calculus in how they broker access to other resources. So it really is better together. >> So your execution has been stellar. This is my competition question. You obviously have competition out there. I think architecturally, you've got some advantages. You have a great relationship with AWS. I don't know what's going on with Google, but Kevin's up on stage. >> George Kurtz: Yeah. >> They're now part of Google. >> George Kurtz: We have a great relationship with them. >> Microsoft obviously, a competitor. You obviously do some things in, >> Right. >> in Azure. Are you building the security Cloud? >> We are. We think we are, because when you look at the amount of data that we actually ingest, when you look at companies using us for critical decisions and critical protection, not only on their On-Prem, but also in their Cloud environment, and the knowledge we have, we think it is a security Cloud. You know, you had, you had Salesforce and Workday and ServiceNow and each of them had their respective Clouds. When I started the company, there was no security Cloud. You know, it wasn't any of the companies that you know. It wasn't the firewall companies, wasn't the AV companies. And I think we really defined ourselves as the security Cloud. And the level of knowledge and insights we have in our Cloud, I think, are world class. >> But you know, it's a difference of being those- 'cause you mentioned those other, you know, seminal Clouds. They, like Salesforce, Workday, they're building their own Clouds. Maybe not so much Workday, but certainly Salesforce and ServiceNow built their own >> Yeah. >> Clouds, their own data centers. You're building on top of hyperscalers, correct? >> Well, >> Well you have your own data centers, too. >> We have our own data centers, yeah. So when we first started, we started in AWS as many do, and we have a great relationship there. We continue to build out. We are a huge customer and we also have, you know, with data sovereignty and those sort of things, we've got a lot of our sort of data that sits in our private Cloud. So it's a hybrid approach and we think it's the best of both worlds. >> Okay. And you mean you can manage those costs and it's, how do you make the decision? Is it just sovereignty or is it cost as well? >> Well, there's an operational element. There's cost. There's everything. There's a lot that goes into it. >> Right. >> And at the end of the day we want to make sure that we're using the right technology in the right Clouds to solve the right problem. >> Well, George, congratulations on being back in person. That's got to feel good. >> It feels really good. >> Got a really good audience here. I don't know what the numbers are but there's many thousands here, >> Thousands, yeah. >> at the ARIA. Really appreciate your time. And thanks for having The Cube here. You guys built a great set for us. >> Well, we appreciate all you do. I enjoy your programs. And I think hopefully we've given the audience a good idea of what CrowdStrike's all about, the impact we have and certainly the growth trajectory that we're on. So thank you. >> Fantastic. All right, George Kurtz, Dave Vellante for Dave Nicholson. We're going to wrap up day one. We'll be back tomorrow, first thing in the morning, live from the ARIA. We'll see you then. (calm music)
SUMMARY :
George Kurtz is the co-founder Boston fan, you know, you know, by three games neutralized it, you know? Anyway, at Fenway, I mean. And the biggest thing for us was that mantra, but you do. So, we talked about the And from our standpoint, Well, and when you dig into You're not a network security specialist, that today. If you look at all the breaches and data is really the I think it was you who said it. And that means you're And most of the On-Prem stuff doesn't even and that's what I think most people Well our agents run wherever. Dave Vellante: Right. And you can't do that if So if you think about why we can actually going, Dave, unless you shove No, no, go ahead. that you made about So you have no context And I'm envisioning almost from all the data we collect. when saying that you you don't need to worry about that. How do you address the and I had to convince people Dave Vellante: Right. You know, you go into a Swiss bank And you know, you can 'cause you acquired Humio for, I mean, 'cause it gives you visibility. And we can do that with you know, firms like IDC And I guess that's, that's the point. But I do feel like there's this unknown and the opportunity that's out there? And I think if you see the growth rates, the capabilities that we have And I think you got a really You see a lot of, well, you And in the early days of security, CrowdStrike and Okta of broker, if you will, Do we think the identity, you know, You have a great relationship with AWS. George Kurtz: We have a You obviously do some things in, Are you building the security Cloud? and the knowledge we have, But you know, it's a of hyperscalers, correct? Well you have your we also have, you know, how do you make the decision? There's a lot that goes into it. And at the end of the day That's got to feel good. I don't know what the numbers are at the ARIA. Well, we appreciate all you do. We'll see you then.
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Anthony Cunha, Mercury Financial & Alex Arango, Mercury Financial | CrowdStrike Fal.Con 2022
(upbeat music) >> Welcome back to Fal.Con 22. We're here at the ARIA hotel in Las Vegas. We're here in Las Vegas, a lot. Dave Nicholson, Dave Alante. Fal.Con 22, wall to wall coverage, you're watching theCUBE. Anthony Kunya is here. He's the chief information security officer at Mercury Financial. And he's joined by his deputy CISO, Alex Arengo. Welcome, gentlemen. >> Good to see you. >> Thank you very much. Good to be here. Thank you for the opportunity to speak. >> Yeah, so this is a great event. This is our first time being at the, a CrowdStrike customer event. We do a lot of security shows, but this is really intimate. We got a high flying company. Tell us first about, of Mercury Financial. What are you guys all about? >> Oh, that's a fantastic question. Let's leeway into that. So Mercury Financial is a credit card company that serves people who are near prime. So be it some kind of hardship in their life. They had something impacted, be a financial impact, maybe a medical impact, an emergency, something, a death family where somehow their credit was impacted. We give 'em the opportunity through our motto, better credit, better life, to build up that credit score to add livelihood to their ability to be financially stable. >> I mean, I think this is huge because you know, so many people it's like, okay, one strike and you're out. >> Right. >> You know, that's just not right. You got- >> No, not at all. >> You got to give people another chance. And so there's so much talent out there. I think about some of the mistakes I made, Dave, when I was a younger man, but- >> No comment. >> Right. So I heard a stat today that I thought was great. Did you guys see the keynote? >> Yes. >> Of course. >> So in the keynote, the, they did the thing at Black Hat but they said what's XDR and I thought- Anthony] Oh goodness. >> My favorite, and I'm not going to ask you what XDR is. >> Okay, good, thank God. >> But my favorite answer was a holistic approach to endpoint security. And, you know, I think as a CISO you have to take a holistic approach to a security- >> Of course. >> Okay. >> Maybe talk about, a little bit about how you do that. >> Wow, a holistic approach I would say and I could, I'll give you an opportunity to speak as well, but a holistic approach it's people processes in technology. So a holistic approach would be, it isn't one box that you check. It's not a technology that is a silver bullet that fixes anything. Those technologies, those services are implemented by people. So good training, our human firewall, the forefront of implementing those technologies to build those processes and incorporate people and a level of sincerity and integrity that we build. So I feel like a holistic approach is both cyber culture to build the cyber resilience program that we so dearly need. >> And I could spend all day talking about security organizations, SecOps, DevSecOps, data SecOps, et cetera, but, but Alex, how, what is your role as the deputy CISO? How do you compliment what Anthony does? >> I got to bring it all together, right? So technically, what are we putting in place? What are the requirements that these stakeholders have? Their needs, their wants. We all have something that we need and want in our environment as an employee, as a customer, as a stakeholder. How do do we get that to market? How can we get it there quickly? You know, and it's really about finding the partners that can get us there, right? That can leverage us, that can force multiply us. >> Yes. >> You know, give my people more time to get the work done, the good work. >> Right, the hard work, of course. >> So paint a picture. You know, we hear a lot about all the different, the bevy of tools, the, how complicated CISOs tell us all the time, that we just don't have enough talent. We're looking for partners to help us compromise, but paint a picture of your environment and how you guys use CrowdStrike. >> Oh, that's a good one. Do you want to take this one? >> Great one, right? I mean, we leverage CrowdStrike at every way we can. We're a Fal.Con complete customer. So they're an extension of our team. They're an extension of our SOC right? >> Yeah. >> We leverage them for many things. We leverage them to understand the risk in our environment. Where we're at in zero trust. How we can really bring a lot of the new processes that the business wants to market, right? How can we get there as fast as possible? Can we make it secure, right? I'm a Mercury card customer also. So I'm, I have a vested interested in that. And I like to drive that, that's, so it comes down to can you align your holistic approach, or your organizational goals and bring that to a really good security product that is world class? >> And I can add a little bit to that as well. So I look at it as a triangle. So we leverage Fal.Con complete as that first level, tier one triage, people who do and understand the product extremely well, we leverage them quite a bit. We also have a VSOC service that we have this like, consider tier two or the middle of the triangle, by Verse, right? >> Yeah. >> Fantastic boutique security company that just has been working with us year over year, innovation, strategic initiatives, always there to play. And then Alex Arengo, and the threat management team, is our top tier, that's tier three, that's the top of the pyramid. By the time it bubbles up to Alex, that's when the real work happens, everyone's triaging, collecting data, putting together pieces. And then Alex and his teammates, and people that he's trained, fantastic, comes and puts it all together and paints a picture so we can then take that information and describe it in layman's terms, simple terms, to the business, to make them understand the level of risk, what we have to do to get to, and through that attack, or that indication of compromise, et cetera, so that we can remediate it, rectify it. >> Right, it's building that security culture foundation, right? It's getting everyone to buy into that. >> Yeah. >> It's a holistic approach and it's really the best way to do it, right? You get bought in from the stakeholders understand what they need to do, and what the goals of the business are. And it really works really well >> We journey together. >> We build a program together. >> Dave, I think that that cultural aspect is critical. Cause I've said many times, bad user behavior trumps good security every time. >> Yeah, absolutely. >> Oh goodness. >> Every time. >> Nicely put, I like that. >> So, I know we're early in the week still, but we did have the keynote. Is there anything that you are hearing, in terms of vision, that peaks your interest specifically, and then also sort of the follow up question is, are you guys kind of like lifeguards who can't ever relax at the beach? >> That's why I have a deputy CISO. Well, nobody can take time off, we have to share this. Of course we do. Most definitely. What would you say would be the next, most innovative thing that were looking for? >> Yeah, what's the next big thing, as far as you're concerned? >> The next biggest thing is definitely building the relationships we have. As we bring in new technologies, we go even more Cloud native. How do we leverage that expertise, that of the partners that we're bringing on board like Zscaler, CrowdStrike, Verse, right? How do we make them a part of the team, and make them perform, bring that world class quality talent across the spectrum, you know, from DevOps to that security analyst, picking up the phone and saying, I'm not really sure what's going on, but there's a culture that's built there where everybody comes to the table to feed, right? We all eat together. >> The ecosystem. >> Yes. >> That is the tooling that we leverage day in and day out. That's how we sleep at night. We have to pick our partners. >> You know, we talked about the ecosystem up front, and you look around, you can see the ecosystem and it's growing. >> Yes. >> And I predict it's going to grow a lot more. >> Yes. >> That's, and it has to, right? I mean, exactly what you're saying is that no one company can do it alone. And we heard, you know, we heard, it is confusing. You hear CrowdStrike's doing Identity, but then they partner with Okta. Right, and they're here out on the floor. So that's what you guys need. Talk a little bit more about the importance of ecosystem and partnerships from your perspective. >> Oh I got a good one for this. So I use the metaphor of having a restaurant. So we run a restaurant really well. We know what we want in the menu. We have a chef, we know how we want to put together, but we need excellent ingredients. You make muffins well. Bring your muffin into the restaurant. That brings and builds that rapport. That I want the menu to be rich and empower people to come in and say, you know, I've never had scallops or octopus before, I hear you guys make it better than anyone else, well, our ingredients are fantastic. Therefore, no matter what we do when we present it, it's perfect, it's palatable. >> Yeah. That's great. You're not making ice cream, but you're serving it. >> I can't, if you ever want to show us. >> We're just converging our bakery, you know? >> Yeah, yeah, yeah, salt, salt is the key. >> We're just working the bakery part out, yeah. >> Okay, I want to ask you about Cloud because you know, in 2010, 2011, when you talk to a financial services firm, Cloud, no, that's an evil word, now everybody's Cloud first. George Kurts talks about how, I mean essentially CrowdStrike is dogmatic. We are Cloud native. We have a Cloud native architecture. I know Gartner has this term CNAP or Cloud native application platform. So what does the Cloud mean to you guys? How does it fit in? What does Cloud native architecture do for you? >> It lets us converge everything we've been talking about. How do we, you know, that's a really big struggle that all security teams are having at, having today. How do I converge threat intelligence? How do I converge the environment that I'm in? How do I converge the threat intel that's coming in, right? All this, you're getting, security teams are constantly on a swivel, right? They're looking left, they're looking right. They're trying to identify what to do first. And you bring in the right partners. >> Yes. >> And you get in, you build the right program. You cement that culture internally. And it really provides dividends. >> You know what I think as well, Dave, is in the past, everyone was more data center based. >> Right. >> The Cloud was like a thing we'd forklift, we'd move over, we were born in the Cloud. So Cloud native Application protection is something that we need and will drive innovation. Will align with our strategic initiatives. We need people to think like the Cloud is what's happening. Super Cloud, some of the things that we spoke about. >> Yeah, so I was at, when we were at reinforced, I had this new mental model emerge, and it sort of hit me in the face. And you tell me, I'd love to talk to practitioners to say, yeah, that makes sense or, no, that's crap. So it seems like the Cloud has become the first line of defense for CISOs. Now you're Cloud first or Cloud native, so, okay. But then now you've got the shared responsibility model. And I don't know if you use multiple Clouds. Do you use multiple Clouds? >> We cannot say. >> Cannot say, okay, let's assume for a second, your, some of your colleagues, CISO colleagues, use multiple Clouds. >> They should, okay, sure. >> Now they've got multiple shared responsibility models. Now you've got also the application development team. They're being asked to be the pivot point to actually execute, they got to secure the platform. They got to secure the containers, their run time. >> Workloads, yes. >> And then you got audit behind you is kind of the last line of defense. So things are shifting. Describe sort of the organizational dynamic that you see, not necessarily specific to Mercury Financial, or that would be cool, but generally in the industry. >> Oh, I would say, I could say this, that having Cloud, multitenancy Cloud or the super Cloud model where we could abstract our services our protection, the different levels of security tooling, being able to abstract and speak a common language where you could run in Azure, GCP or AWS, and still have a common language that you can interpret and leverage between all the tooling would be something I would love to see. >> That's Super Cloud >> A magical, that is that. >> That is a Cloud interpreter essentially. >> I think we use different words, but yes. >> A PAs layer, super PAs layer, sorry to take it too far. >> Yeah, like, I want to be able to abstract it and speak a language that would work in any of the- >> What does that do for you as a technology practitioner? >> Well, imagine if you had to speak three different languages with three different people, get lost in translation. If we could speak a common language across all the different platforms and all the different footprints, it would be easier to define our security posture. Where are we? Are we secure? You might say security groups in AWS, it might be, mean something else, but it's still a level of protection that surrounds the end point, right? Something that would abstract that level would be very fun. Very good for me. >> It's, you know, it's pretty easy to understand your use case for this. When you're talking about here we are, Mercury Financial, you have the most sensitive financial information about people, right? >> Right, absolutely. >> A data breach where all of the information about your customers getting out there on the dark web. Right? Heart attack time. >> Instantly. >> What are some things that people might not think about though, that are going on in your world? What would surprise someone who maybe isn't a security specialist in terms of the things that you're dealing with as far as threats are concerned? >> I'm going to leave that on you. >> Can you think of some examples of things that you could, you know, obviously generic examples. >> Right. >> Yes. >> I'm going to point to the number one and two most common ways that applications and businesses are getting owned right now. And that's misconfigurations on your web app or a vulnerable application or phishing. And those are both very important things, right? A lot of development teams, they want to get things to market as soon as possible. And maybe security's on the back foot. It's about building that culture and to, you know, being Cloud native helps you have a, you can provide different tool sets to your organization that helps you understand that posture and makes you help those business decisions. Are we in a good posture to go forward right now? That's a big question that I think most security organizations need to ask themselves and the need to hold other stakeholders accountable. >> So phishing and the concept of social engineering, still alive and well? >> Oh, goodness. >> Always. >> Everything starts with people. The human firewall has to be front of mind. Security can't be an afterthought or a bolt on, that's something that you think about, well, I guess if I have to meet our compliance, it doesn't work with us. >> Comes back to the culture that you're actually talking about before. >> 100%, yeah, cyber resiliency starts with cyber culture. >> Kevin Mandy has said it today. I, never underestimate the adversary. The adversary- >> Of course. >> Is highly capable, motivated, big ROI and it just keeps getting bigger. The more technology gets embedded into our lives. The more lucrative hacking becomes. >> And more attack vectors. We have more areas that we could be potentially penetrated. >> They have a lot of time. Those threat actors have a lot of time. >> They do have a lot of time, yeah. >> Right. >> Right and to your point, you're constantly on the swivel. Right, you don't have time. >> Right. >> No, we don't. >> So do your responsibilities touch on things like fraud detection as well? >> Yeah, oh, that- >> Is that a silly question? I'm thinking- >> Yeah, no, it really is, so- >> No, not at all. >> Or there isn't segregation between what we would think of as IT and the credit card transaction that fires up a red flag. >> Those are integrated. >> It's definitely important. And in any business, right? Is to, like I mentioned, I use this word a lot converge, right? It's converging that intel, that fraud intelligence and making it into a process where we're reducing the risk and the losses that the business is incurring. >> Yes. >> It's so important, right? That we build that culture within the fraud teams, the operational teams, the, you know really anybody who has a really large stake in whatever the business product is. And, you know, being Cloud native, bringing in the right partners, building that security culture. I mean, that's the biggest one. >> Yeah, we've flown. >> It's last and definitely not least, it is, the culture's where you need to be. >> Absolutely. >> You know, you guys, I'm sure, you know, work with a lot of different vendors, a lot of tools, or sometimes the tools are point tools, they're best to breed. CrowdStrike says it wants to be a generational company. >> Oh, yeah. >> It says this notion of an unstoppable breach is a myth. You guys can't live that way. You have to assume you're going to breach but can CrowdStrike be a generational company? >> I think they've proven themselves. They've been around over a decade now. it's 11 years. They just had their birthday yesterday, right? >> Yeah. >> Or anniversary, the company started? >> Yeah. 11 years, yeah. >> I absolutely, and I also agree to add it a little bit part, from the fraud part. I think CrowdStrike would be an integral piece of the overall solution that we have. It hits so many different aspects and looks at so many different potential attack vectors. I keep using that word, but I think integrating fraud in other parts and other functions of the business will start to see that they can leverage CrowdStrike. That there's tooling within CrowdStrike innovatively, like ahead of the game. And I always like that about CrowdStrike, being way ahead of the game and thinking in front of our adversaries. I think other departments will be like, what tools do you have, how can we use them? This is fantastic, this makes us feel better. We don't have to worry about that. We can focus in on what we're good at and build that best of breed solution. So fraud can focus on fraud and you can leverage the tooling and the infrastructure that we provide them together holistically to build a security program that's beyond reproach. >> Guys, we got to go, great perspectives. Always love having the practitioners on. >> Yeah, thank you. >> I really appreciate your time, thank you. >> Yeah, absolutely, always a pleasure. Thank you so much for your time. >> Anthony, Alex, Dave and Dave will be right back, right after this short break. You're watching theCUBE from Fal.Con 2022 from the ARIA in Las Vegas. >> Cheers my friend. >> Yeah, of course. (cheerful music)
SUMMARY :
We're here at the ARIA hotel in Las Vegas. Thank you for the opportunity to speak. What are you guys all about? We give 'em the opportunity is huge because you know, You know, that's just not right. You got to give people another chance. Did you guys see the keynote? So in the keynote, the, going to ask you what XDR is. And, you know, I think as a CISO bit about how you do that. it isn't one box that you check. We all have something that we need more time to get the work done, all the time, that we just Do you want to take this one? I mean, we leverage CrowdStrike that the business wants to market, right? that we have this like, so that we can remediate it, rectify it. It's getting everyone to buy into that. and it's really the best Dave, I think that that early in the week still, What would you say would be the next, across the spectrum, you know, from DevOps That is the tooling that we and you look around, you going to grow a lot more. And we heard, you know, to come in and say, you but you're serving it. salt, salt is the key. We're just working the So what does the Cloud mean to you guys? How do I converge the threat And you get in, is in the past, everyone is something that we need and it sort of hit me in the face. some of your colleagues, CISO colleagues, They got to secure the dynamic that you see, that you can interpret and leverage That is a Cloud I think we use layer, sorry to take it too far. that surrounds the end point, right? It's, you know, it's all of the information of things that you could, you know, and the need to hold other that's something that you think about, Comes back to the starts with cyber culture. The adversary- and it just keeps getting bigger. We have more areas that we They have a lot of time. They do have a lot of time, Right and to your point, and the credit card transaction and the losses that the the operational teams, the, you know it is, the culture's where you need to be. You know, you guys, I'm sure, you know, You have to assume you're going to breach I think they've proven themselves. of the overall solution that we have. Always love having the practitioners on. I really appreciate Thank you so much for your time. the ARIA in Las Vegas. Yeah, of course.
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Scott Baker, IBM Infrastructure | VMware Explore 2022
(upbeat music) >> Welcome back everyone to theCUBEs live coverage in San Francisco for VMware Explorer. I'm John Furrier with my host, Dave Vellante. Two sets, three days of wall to wall coverage. This is day two. We got a great guest, Scott Baker, CMO at IBM, VP of Infrastructure at IBM. Great to see you. Thanks for coming on. >> Hey, good to see you guys as well. It's always a pleasure. >> ()Good time last night at your event? >> Great time last night. >> It was really well-attended. IBM always has the best food so that was good and great props, magicians, and it was really a lot of fun, comedians. Good job. >> Yeah, I'm really glad you came on. One of the things we were chatting, before we came on camera was, how much changed. We've been covering IBM storage days, back on the Edge days, and they had the event. Storage is the center of all the conversations, cyber security- >> ()Right? >> ... But it's not just pure cyber. It's still important there. And just data and the role of multi-cloud and hybrid cloud and data and security are the two hottest areas, that I won't say unresolved, but are resolving themselves. And people are talking. It's the most highly discussed topics. >> Right. >> ()Those two areas. And it's just all on storage. >> Yeah, it sure does. And in fact, what I would even go so far as to say is, people are beginning to realize the importance that storage plays, as the data custodian for the organization. Right? Certainly you have humans that are involved in setting strategies, but ultimately whatever those policies are that get applied, have to be applied to a device that must act as a responsible custodian for the data it holds. >> So what's your role at IBM and the infrastructure team? Storage is one only one of the areas. >> ()Right. >> You're here at VMware Explore. What's going on here with IBM? Take us through what you're doing there at IBM, and then here at VMware. What's the conversations? >> Sure thing. I have the distinct pleasure to run both product marketing and strategy for our storage line. That's my primary focus, but I also have responsibility for the mainframe software, so the Z System line, as well as our Power server line, and our technical support organization, or at least the services side of our technical support organization. >> And one of the things that's going on here, lot of noise going on- >> Is that a bird flying around? >> Yeah >> We got fire trucks. What's changed? 'Cause right now with VMware, you're seeing what they're doing. They got the Platform, Under the Hood, Developer focus. It's still an OPS game. What's the relationship with VMware? What are you guys talking about here? What are some of the conversations you're having here in San Francisco? >> Right. Well, IBM has been a partner with VMware for at least the last 20 years. And VMware does, I think, a really good job about trying to create a working space for everyone to be an equal partner with them. It can be challenging too, if you want to sort of throw out your unique value to a customer. So one of the things that we've really been working on is, how do we partner much stronger? When we look at the customers that we support today, what they're looking for isn't just a solid product. They're looking for a solid ecosystem partnership. So we really lean in on that 20 years of partnership experience that we have with IBM. So one of the things that we announced was actually being one of the first VMware partners to bring both a technical innovation delivery mechanism, as well as technical services, alongside VMware technologies. I would say that was one of the first things that we really leaned in on, as we looked out at what customers are expecting from us. >> So I want to zoom out a little bit and talk about the industry. I've been following IBM since the early 1980s. It's trained in the mainframe market, and so we've seen, a lot of things you see come back to the mainframe, but we won't go there. But prior to Arvind coming on, it seemed like, okay, storage, infrastructure, yeah it's good business, and we'll let it throw off some margin. That's fine. But it's all about services and software. Okay, great. With Arvind, and obviously Red Hat, the whole focus shift to hybrid. We were talking, I think yesterday, about okay, where did we first hear hybrid? Obviously we heard that a lot from VMware. I heard it actually first, early on anyway, from IBM, talking hybrid. Some of the storage guys at the time. Okay, so now all of a sudden there's the realization that to make hybrid work, you need software and hardware working together. >> () Right. So it's now a much more fundamental part of the conversation. So when you look out, Scott, at the trends you're seeing in the market, when you talk to customers, what are you seeing and how is that informing your strategy, and how are you bringing together all the pieces? >> That's a really awesome question because it always depends on who, within the organization, you're speaking to. When you're inside the data center, when you're talking to the architects and the administrators, they understand the value in the necessity for a hybrid-cloud architecture. Something that's consistent. On The Edge, On-Prem, in the cloud. Something that allows them to expand the level of control that they have, without having to specialize on equipment and having to redo things as you move from one medium to the next. As you go upstack in that conversation, what I find really interesting is how leaders are beginning to realize that private cloud or on-prem, multi cloud, super cloud, whatever you call it, whatever's in the middle, those are just deployment mechanisms. What they're coming to understand is it's the applications and the data that's hybrid. And so what they're looking for IBM to deliver, and something that we've really invested in on the infrastructure side is, how do we create bidirectional application mobility? Making it easy for organizations, whether they're using containers, virtual machines, just bare metal, how do they move that data back and forth as they need to, and not just back and forth from on-prem to the cloud, but effectively, how do they go from cloud to cloud? >> Yeah. One of the things I noticed is your pin, says I love AI, with the I next to IBM and get all these (indistinct) in there. AI, remember the quote from IBM is, "You can't have AI without IA." Information architect. >> () Right. >> () Rob Thomas. >> Rob Thomas (indistinct) the sound bites. But that brings up the point about machine learning and some of these things that are coming down the like, how is your area devolving the smarts and the brains around leveraging the AI in the systems itself? We're hearing more and more softwares being coded into the hardware. You see Silicon advances. All this is kind of, not changing it, but bringing back the urgency of, hardware matters. >> That's right. >> () At the same time, it's still software too. >> That's right. So let's connect a couple of dots here. We talked a little bit about the importance of cyber resiliency, and let's talk about a little bit on how we use AI in that matter. So, if you look at the direct flash modules that are in the market today, or the SSDs that are in the market today, just standard-capacity drives. If you look at the flash core modules that IBM produces, we actually treat that as a computational storage offering, where you store the data, but it's got intelligence built into the processor, to offload some of the responsibilities of the controller head. The ability to do compression, single (indistinct), deduplication, you name it. But what if you can apply AI at the controller level, so that signals that are being derived by the flash core module itself, that look anomalous, can be handed up to an intelligence to say, "Hey, I'm all of a sudden getting encrypted rights from a host that I've never gotten encrypted rights for. Maybe this could be a problem." And then imagine if you connect that inferencing engine to the rest of the IBM portfolio, "Hey, Qradar. Hey IBM Guardian. What's going on on the network? Can we see some correlation here?" So what you're going to see IBM infrastructure continue to do is invest heavily into entropy and the ability to measure IO characteristics with respect to anomalous behavior and be able to report against that. And the trick here, because the array technically doesn't know if it's under attack or if the host just decided to turn on encryption, the trick here is using the IBM product relationships, and ecosystem relationships, to do correlation of data to determine what's actually happening, to reduce your false positives. >> And have that pattern of data too. It's all access to data too. Big time. >> That's right. >> And that innovation comes out of IBM R&D? Does it come out of the product group? Is it IBM research that then trickles its way in? Is it the storage innovation? Where's that come from? Where's that bubble up? That partnership? >> Well, I got to tell you, it doesn't take very long in this industry before your counterpart, your competitor, has a similar feature. Right? So we're always looking for, what's the next leg? What's the next advancement that we can make? We knew going into this process, that we had plenty of computational power that was untapped on the FPGA, the processor running on the flash core module. Right? So we thought, okay, well, what should we do next? And we thought, "Hey, why not just set this thing up to start watching IO patterns, do calculations, do trending, and report that back?" And what's great about what you brought up too, John, is that it doesn't stay on the box. We push that upstack through the AIOPS architecture. So if you're using Turbonomic, and you want to look applications stack down, to know if you've got threat potential, or your attack surface is open, you can make some changes there. If you want to look at it across your infrastructure landscape with a storage insight, you could do that. But our goal here is to begin to make the machine smarter and aware of impacts on the data, not just on the data they hold onto, but usage, to move it into the appropriate tier, different write activities or read activities or delete activities that could indicate malicious efforts that are underway, and then begin to start making more autonomous, how about managed autonomous responses? I don't want to turn this into a, oh, it's smart, just turn it on and walk away and it's good. I don't know that we'll ever get there just yet, but the important thing here is, what we're looking at is, how do we continually safeguard and protect that data? And how do we drive features in the box that remove more and more of the day to day responsibility from the administrative staff, who are technically hired really, to service and solve for bigger problems in the enterprise, not to be a specialist and have to manage one box at a time. >> Dave mentioned Arvind coming on, the new CEO of IBM, and the Red Hat acquisition and that change, I'd like to get your personal perspective, or industry perspective, so take your IBM-hat off for a second and put the Scott-experience-in-the-industry hat on, the transformation at the customer level right now is more robust, to use that word. I don't want to say chaotic, but it is chaotic. They say chaos in the cloud here at VM, a big part of their messaging, but it's changing the business model, how things are consumed. You're seeing new business models emerge. So IBM has this lot of storage old systems, you're transforming, the company's transforming. Customers are also transforming, so that's going to change how people market products. >> () Right. >> For example, we know that developers and DevOps love self-service. Why? Because they don't want to install it. Let me go faster. And they want to get rid of it, doesn't work. Storage is infrastructure and still software, so how do you see, in your mind's eye, with all your experience, the vision of how to market products that are super important, that are infrastructure products, that have to be put into play, for really new architectures that are going to transform businesses? It's not as easy as saying, "Oh, we're going to go to market and sell something." The old way. >> () Right. >> This shifting happening is, I don't think there's an answer yet, but I want to get your perspective on that. Customers want to hear the storage message, but it might not be speeds and fees. Maybe it is. Maybe it's not. Maybe it's solutions. Maybe it's security. There's multiple touch points now, that you're dealing with at IBM for the customer, without becoming just a storage thing or just- >> () Right. >> ... or just hardware. I mean, hardware does matter, but what's- >> Yeah, no, you're absolutely right, and I think what complicates that too is, if you look at the buying centers around a purchase decision, that's expanded as well, and so as you engage with a customer, you have to be sensitive to the message that you're telling, so that it touches the needs or the desires of the people that are all sitting around the table. Generally what we like to do when we step in and we engage, isn't so much to talk about the product. At some point, maybe later in the engagements, the importance of speeds, feeds, interconnectivity, et cetera, those do come up. Those are a part of the final decision, but early on it's really about outcomes. What outcomes are you delivering? This idea of being able to deliver, if you use the term zero trust or cyber-resilient storage capability as a part of a broader security architecture that you're putting into place, to help that organization, that certainly comes up. We also hear conversations with customers about, or requests from customers about, how do the parts of IBM themselves work together? Right? And I think a lot of that, again, continues to speak to what kind of outcome are you going to give to me? Here's a challenge that I have. How are you helping me overcome it? And that's a combination of IBM hardware, software, and the services side, where we really have an opportunity to stand out. But the thing that I would tell you, that's probably most important is, the engagement that we have up and down the stack in the market perspective, always starts with, what's the outcome that you're going to deliver for me? And then that drags with it the story that would be specific to the gear. >> Okay, so let's say I'm a customer, and I'm buying it to zero trust architecture, but it's going to be somewhat of a long term plan, but I have a tactical need. I'm really nervous about Ransomware, and I don't feel as though I'm prepared, and I want an outcome that protects me. What are you seeing? Are you seeing any patterns? I know it's going to vary, but are you seeing any patterns, in terms of best practice to protect me? >> Man, the first thing that we wanted to do at IBM is divorce ourselves from the company as we thought through this. And what I mean by that is, we wanted to do what's right, on day zero, for the customer. So we set back using the experience that we've been able to amass, going through various recovery operations, and helping customers get through a Ransomware attack. And we realized, "Hey. What we should offer is a free cyber resilience assessment." So we like to, from the storage side, we'd like to look at what we offer to the customer as following the NIST framework. And most vendors will really lean in hard on the response and the recovery side of that, as you should. But that means that there's four other steps that need to be addressed, and that free cyber-resilience assessment, it's a consultative engagement that we offer. What we're really looking at doing is helping you assess how vulnerable you are, how big is that attack surface? And coming out of that, we're going to give you a Vendor Agnostic Report that says here's your situation, here's your grade or your level of risk and vulnerability, and then here's a prioritized roadmap of where we would recommend that you go off and start solving to close up whatever the gaps or the risks are. Now you could say, "Hey, thanks, IBM. I appreciate that. I'm good with my storage vendor today. I'm going to go off and use it." Now, we may not get some kind of commission check. We may not sell the box. But what I do know is that you're going to walk away knowing the risks that you're in, and we're going to give you the recommendations to get started on closing those up. And that helps me sleep at night. >> That's a nice freebie. >> Yeah. >> Yeah, it really is, 'cause you guys got deep expertise in that area. So take advantage of that. >> Scott, great to have you on. Thanks for spending time out of your busy day. Final question, put a plug in for your group. What are you communicating to customers? Share with the audience here. You're here at VMware Explorer, the new rebranded- >> () Right? >> ... multi-cloud, hybrid cloud, steady state. There are three levels of transformation, virtualization, hybrid cloud, DevOps, now- >> Right? >> ... multi-cloud, so they're in chapter three of their journey- >> That's right. >> Really innovative company, like IBM, so put the plugin. What's going on in your world? Take a minute to explain what you want. >> Right on. So here we are at VMware Explorer, really excited to be here. We're showcasing two aspects of the IBM portfolio, all of the releases and announcements that we're making around the IBM cloud. In fact, you should come check out the product demonstration for the IBM Cloud Satellite. And I don't think they've coined it this, but I like to call it the VMware edition, because it has all of the VMware services and tools built into it, to make it easier to move your workloads around. We certainly have the infrastructure side on the storage, talking about how we can help organizations, not only accelerate their deployments in, let's say Tanzu or Containers, but even how we help them transform the application stack that's running on top of their virtualized environment in the most consistent and secure way possible. >> Multiple years of relationships with VMware. IBM, VMware together. Congratulations. >> () That's right. >> () Thanks for coming on. >> Hey, thanks (indistinct). Thank you very much. >> A lot more live coverage here at Moscone west. This is theCUBE. I'm John Furrier with Dave Vellante. Thanks for watching. Two more days of wall-to-wall coverage continuing here. Stay tuned. (soothing music)
SUMMARY :
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Sam Kassoumeh, SecurityScorecard | CUBE Conversation
(upbeat music) >> Hey everyone, welcome to this CUBE conversation. I'm John Furrier, your host of theCUBE here in Palo Alto, California. We've got Sam Kassoumeh, co-founder and chief operating office at SecurityScorecard here remotely coming in. Thanks for coming on Sam. Security, Sam. Thanks for coming on. >> Thank you, John. Thanks for having me. >> Love the security conversations. I love what you guys are doing. I think this idea of managed services, SaaS. Developers love it. Operation teams love getting into tools easily and having values what you guys got with SecurityScorecard. So let's get into what we were talking before we came on. You guys have a unique solution around ratings, but also it's not your grandfather's pen test want to be security app. Take us through what you guys are doing at SecurityScorecard. >> Yeah. So just like you said, it's not a point in time assessment and it's similar to a traditional credit rating, but also a little bit different. You can really think about it in three steps. In step one, what we're doing is we're doing threat intelligence data collection. We invest really heavily into R&D function. We never stop investing in R&D. We collect all of our own data across the entire IPV force space. All of the different layers. Some of the data we collect is pretty straightforward. We might crawl a website like the example I was giving. We might crawl a website and see that the website says copyright 2005, but we know it's 2022. Now, while that signal isn't enough to go hack and break into the company, it's definitely a signal that someone might not be keeping things up to date. And if a hacker saw that it might encourage them to dig deeper. To more complex signals where we're running one of the largest DNS single infrastructures in the world. We're monitoring command and control malware and its behaviors. We're essentially collecting signals and vulnerabilities from the entire IPV force space, the entire network layer, the entire web app player, leaked credentials. Everything that we think about when we talk about the security onion, we collect data at each one of those layers of the onion. That's step one. And we can do all sorts of interesting insights and information and reports just out of that thread intel. Now, step two is really interesting. What we do is we go identify the attack surface area or what we call the digital footprint of any company in the world. So as a customer, you can simply type in the name of a company and we identify all of the domains, sub domains, subsidiaries, organizations that are identified on the internet that belong to that organization. So every digital asset of every company we go out and we identify that and we update that every 24 hours. And step three is the rating. The rating is probabilistic and it's deterministic. The rating is a benchmark. We're looking at companies compared to their peers of similar size within the same industry and we're looking at how they're performing. And it's probabilistic in the sense that companies that have an F are about seven to eight times more likely to experience a breach. We're an A through F scale, universally understood. Ds and Fs, more likely to experience a breach. A's we see less breaches now. Like I was mentioning before, it doesn't mean that an F is always going to get hacked or an A can never get hacked. If a nation state targets an A, they're going to eventually get in with enough persistence and budget. If the pizza shop on the corner has an F, they may never get hacked because no one cares, but natural correlation, more doors open to the house equals higher likelihood someone unauthorized is going to walk in. So it's really those three steps. The collection, we map it to the surface area of the company and then we produce a rating. Today we're rating about 12 million companies every single day. >> And how many people do you have as customers? >> We have 50,000 organizations using us, both free and paid. We have a freemium tier where just like Yelp or a LinkedIn business profile. Any company in the world has a right to go claim the score. We never extort companies to fix the score. We never charge a company to see the score or fix it. Any company in a world without paying us a cent can go in. They can understand what we're seeing about them, what a hacker could see about their environment. And then we empower them with the tools to fix it and they can fix it and the score will go up. Now companies pay us because they want enterprise capabilities. They want additional modules, insights, which we can talk about. But in total, there's about 50,000 companies that at any given point in time, they're monitoring about a million and a half organizations of the 12 million that we're rating. It sounds like Google. >> If you want to look at it. >> Sounds like Google Search you got going on there. You got a lot of search and then you create relevance, a score, like a ranking. >> That's precisely it. And that's exactly why Google ventures invested in us in our Series B round. And they're on our board. They looked and they said, wow, you guys are building like a Google Search engine over some really impressive threat intelligence. And then you're distilling it into a score which anybody in the world can easily understand. >> Yeah. You obviously have page rank, which changed the organic search business in the late 90s, early 2000s and the rest is history. AdWords. >> Yeah. >> So you got a lot of customer growth there potentially with the opt-in customer view, but you're looking at this from the outside in. You're looking at companies and saying, what's your security posture? Getting a feel for what they got going on and giving them scores. It sounds like it's not like a hacker proof. It's just more of a indicator for management and the team. >> It's an indicator. It's an indicator. Because today, when we go look at our vendors, business partners, third parties were flying blind. We have no idea how they're doing, how they're performing. So the status quo for the last 20 years has been perform a risk assessments, send a questionnaire, ask for a pen test and an audit evidence. We're trying to break that cycle. Nobody enjoys it. They're long tail. It's a trust without verification. We don't really like that. So we think we can evolve beyond this point in time assessment and give a continuous view. Now, today, historically, we've been outside in. Not intrusive, and we'll show you what a hacker can see about an environment, but we have some cool things percolating under the hood that give more of a 360 view outside, inside, and also a regulatory compliance view as well. >> Why is the compliance of the whole third party thing that you're engaging with important? Because I mean, obviously having some sort of way to say, who am I dealing with is important. I mean, we hear all kinds of things in the security landscape, oh, zero trust, and then we hear trust, supply chain, software risk, for example. There's a huge trust factor there. I need to trust this tool or this container. And then you got the zero trust, don't trust anything. And then you've got trust and verify. So you have all these different models and postures, and it just seems hard to keep up with. >> Sam: It's so hard. >> Take us through what that means 'cause pen tests, SOC reports. I mean the clouds help with the SOC report, but if you're doing agile, anything DevOps, you basically would need to do a pen test like every minute. >> It's impossible. The market shifted to the cloud. We watched and it still is. And that created a lot of complexity, not to date myself. But when I was starting off as a security practitioner, the data center used to be in the basement and I would have lunch with the database administrator and we talk about how we were protecting the data. Those days are long gone. We outsource a lot of our key business practices. We might use, for example, ADP for a payroll provider or Dropbox to store our data. But we've shifted and we no longer no who that person is that's protecting our data. They're sitting in another company in another area unknown. And I think about 10, 15 years ago, CISOs had the realization, Hey, wait a second. I'm relying on that third party to function and operate and protect my data, but I don't have any insight, visibility or control of their program. And we were recommended to use questionnaires and audit forms, and those are great. It's good hygiene. It's good practice. Get to know the people that are protecting your data, ask them the questions, get the evidence. The challenge is it's point in time, it's limited. Sometimes the information is inaccurate. Not intentionally, I don't think people intentionally want to go lie, but Hey, if there's a $50 million deal we're trying to close and it's dependent on checking this one box, someone might bend a rule a little bit. >> And I said on theCUBE publicly that I think pen test reports are probably being fudged and dates being replicated because it's just too fast. And again, today's world is about velocity on developers, trust on the code. So you got all kinds of trust issues. So I think verification, the blue check mark on Twitter kind of thing going on, you're going to see a lot more of that and I think this is just the beginning. I think what you guys are doing is scratching the surface. I think this outside in is a good first step, but that's not going to solve the internal problem that still coming and have big surface areas. So you got more surface area expanding. I mean, IOT's coming in, the Edge is coming fast. Never mind hybrid on-premise cloud. What's your organizations do to evaluate the risk and the third party? Hands shaking, verification, scorecards. Is it like a free look here or is it more depth to it? Do you double click on it? Take us through how this evolves. >> John it's become so disparate and so complex, Because in addition to the market moving to the cloud, we're now completely decentralized. People are working from home or working hybrid, which adds more endpoints. Then what we've learned over time is that it's not just a third party problem, because guess what? My third parties behind the scenes are also using third parties. So while I might be relying on them to process my customer's payment information, they're relying on 20 vendors behind the scene that I don't even know about. I might have an A, they might have an A. It's really important that we expand beyond that. So coming out of our innovation hub, we've developed a number of key capabilities that allow us to expand the value for the customer. One, you mentioned, outside in is great, but it's limited. We can see what a hacker sees and that's helpful. It gives us pointers where to maybe go ask double click, get comfort, but there's a whole nother world going on behind the firewall inside of an organization. And there might be a lot of good things going on that CISO security teams need to be rewarded for. So we built an inside module and component that allows teams to start plugging in the tools, the capabilities, keys to their cloud environments. And that can show anybody who's looking at the scorecard. It's less like a credit score and more like a social platform where we can go and look at someone's profile and say, Hey, how are things going on the inside? Do they have two-factor off? Are there cloud instances configured correctly? And it's not a point in time. This is a live connection that's being made. This is any point in time, we can validate that. The other component that we created is called an evidence locker. And an evidence locker, it's like a secure vault in my scorecard and it allows me to upload things that you don't really stand for or check for. Collateral, compliance paperwork, SOC 2 reports. Those things that I always begrudgingly email. I don't want to share with people my trade secrets, my security policies, and have it sit on their exchange server. So instead of having to email the same documents out, 300 times a month, I just upload them to my evidence locker. And what's great is now anybody following my scorecard can proactively see all the great things I'm doing. They see the outside view. They see the inside view. They see the compliance view. And now they have the holy grail view of my environment and can have a more intelligent conversation. >> Access to data and access methods are an interesting innovation area around data lineage. Tracing is becoming a big thing. We're seeing that. I was just talking with the Snowflake co-founder the other day here in theCUBE about data access and they're building a proprietary mesh on top of the clouds to figure out, Hey, I don't want to give just some tool access to data because I don't know what's on the other side of those tools. Now they had a robust ecosystem. So I can see this whole vendor risk supply chain challenge around integration as a huge problem space that you guys are attacking. What's your reaction to that? >> Yeah. Integration is tricky because we want to be really particular about who we allow access into our environment or where we're punching holes in the firewall and piping data out out of the environment. And that can quickly become unwieldy just with the control that we have. Now, if we give access to a third party, we then don't have any control over who they're sharing our information with. When I talk to CISOs today about this challenge, a lot of folks are scratching their head, a lot of folks treat this as a pet project. Like how do I control the larger span beyond just the third parties? How do I know that their software partners, their contractors that they're working with building their tools are doing a good job? And even if I know, meaning, John, you might send me a list of all of your vendors. I don't want to be the bad guy. I don't really have the right to go reach out to my vendors' vendors knocking on their door saying, hi, I'm Sam. I'm working with John and he's your customer. And I need to make sure that you're protecting my data. It's an awkward chain of conversation. So we're building some tools that help the security teams hold the entire ecosystem accountable. We actually have a capability called automatic vendor discovery. We can go detect who are the vendors of a company based on the connections that we see, the inbound and outbound connections. And what often ends up happening John is we're bringing to the attention to our customers, awareness about inbound and outbound connections. They had no idea existed. There were the shadow IT and the ghost vendors that were signed without going through an assessment. We detect those connections and then they can go triage and reduce the risk accordingly. >> I think that risk assessment of vendors is key. I was just reading a story about this, about how a percentage, I forget the number. It was pretty large of applications that aren't even being used that are still on in companies. And that becomes a safe haven for bad actors to hang out and penetrate 'cause they get overlooked 'cause no one's using them, but they're still online. And so there's a whole, I called cleaning up the old dead applications that are still connected. >> That happens all the time. Those applications also have applications that are dead and applications that are alive may also have users that are dead as well. So you have that problem at the application level, at the user level. We also see a permutation of what you describe, which is leftover artifacts due to configuration mistakes. So a company just put up a new data center, a satellite office in Singapore and they hired a team to go install all the hardware. Somebody accidentally left an administrative portal exposed to the public internet and nobody knew the internet works, the lights are on, the office is up and running, but there was something that was supposed to be turned off that was left turned on. So sometimes we bring to company's attention and they say, that's not mine. That doesn't belong to me. And we're like, oh, well, we see some reason why. >> It's his fault. >> Yeah and they're like, oh, that was the contractor set up the thing. They forgot to turn off the administrative portal with the default login credentials. So we shut off those doors. >> Yeah. Sam, this is really something that's not talked about a lot in the industry that we've become so reliant on managed services and other people, CISOs, CIOs, and even all departments that have applications, even marketing departments, they become reliant on agencies and other parties to do stuff for them which inherently just increases the risk here of what they have. So there inherently could be as secure as they could be, but yet exposed completely on the other side. >> That's right. We have so many virtual touch points with our partners, our vendors, our managed service providers, suppliers, other third parties, and all the humans that are involved in that mix. It creates just a massive ripple effect. So everybody in a chain can be doing things right. And if there's one bad link, the whole chain breaks. I know it's like the cliche analogy, but it rings true. >> Supply chain trust again. Trust who you trust. Let's see how those all reconcile. So Sam, I have to ask you, okay, you're a former CISO. You've seen many movies in the industry. Co-founded this company. You're in the front lines. You've got some cool things happening. I can almost imagine the vision is a lot more than just providing a rating and score. I'm sure there's more vision around intelligence, automation. You mentioned vault, wallet capabilities, exchanging keys. We heard at re:Inforce automated reasoning, metadata reasoning. You got all kinds of crypto and quantum. I mean, there's a lot going on that you can tap into. What's your vision where you see SecurityScorecard going? >> When we started the company, the rating was the thing that we sold and it was a language that helped technical and non-technical folks alike level the playing field and talk about risk and use it to drive their strategy. Today, the rating just opens the door to that discussion and there's so much additional value. I think in the next one to two years, we're going to see the rating becomes standardized. It's going to be more frequently asked or even required or leveraged by key decision makers. When we're doing business, it's going to be like, Hey, show me your scorecard. So I'm seeing the rating get baked more and more the lexicon of risk. But beyond the rating, the goal is really to make a world a safer place. Help transform and rise the tide. So all ships can lift. In order to do that, we have to help companies, not only identify the risk, but also rectify the risk. So there's tools we build to really understand the full risk. Like we talked about the inside, the outside, the fourth parties, fifth parties, the real ecosystem. Once we identified where are all the Fs and bad things, will then what? So couple things that we're doing. We've launched a pro serve arm to help companies. Now companies don't have to pay to fix the score. Anybody, like I said, can fix the score completely free of charge, but some companies need help. They ask us and they say, Hey, I'm looking for a trusted advisor. A Sherpa, a guide to get me to a better place or they'll say, Hey, I need some pen testing services. So we've augmented a service arm to help accelerate the remediation efforts. We're also partnered with different industries that use the rating as part of a larger picture. The cyber rating isn't the end all be all. When companies are assessing risk, they may be looking at a financial ratings, ESG ratings, KYC AML, cyber security, and they're trying to form a complete risk profile. So we go and we integrate into those decision points. Insurance companies, all the top insurers, re-insurers, brokers are leveraging SecurityScorecard as an ingredient to help underwrite for cyber liability insurance. It's not the only ingredient, but it helps them underwrite and identify the help and price the risk so they can push out a policy faster. First policy is usually the one that's signed. So time to quote is an important metric. We help to accelerate that. We partner with credit rating agencies like Fitch, who are talking to board members, who are asking, Hey, I need a third party, independent verification of what my CISO is saying. So the CISO is presenting the rating, but so are the proxy advisors and the ratings companies to the board. So we're helping to inform the boards and evolve how they're thinking about cyber risk. We're helping with the insurance space. I think that, like you said, we're only scratching the surface. I can see, today we have about 50,000 companies that are engaging a rating and there's no reason why it's not going to be in the millions in just the next couple years here. >> And you got the capability to bring in more telemetry and see the new things, bring that into the index, bring that into the scorecard and then map that to potential any vulnerabilities. >> Bingo. >> But like you said, the old days, when you were dating yourself, you were in a glass room with a door lock and key and you can see who's two folks in there having lunch, talking database. No one's going to get hurt. Now that's gone, right? So now you don't know who's out there and machines. So you got humans that you don't know and you got machines that are turning on and off services, putting containers out there. Who knows what's in those payloads. So a ton of surface area and complexity to weave through. I mean only is going to get done with automation. >> It's the only way. Part of our vision includes not attempting to make a faster questionnaire, but rid ourselves of the process all altogether and get more into the continuous assessment mindset. Now look, as a former CISO myself, I don't want another tool to log into. We already have 50 tools we log into every day. Folks don't need a 51st and that's not the intent. So what we've done is we've created today, an automation suite, I call it, set it and forget it. Like I'm probably dating myself, but like those old infomercials. And look, and you've got what? 50,000 vendors business partners. Then behind there, there's another a hundred thousand that they're using. How are you going to keep track of all those folks? You're not going to log in every day. You're going to set rules and parameters about the things that you care about and you care depending on the nature of the engagement. If we're exchanging sensitive data on the network layer, you might care about exposed database. If we're doing it on the app layer, you're going to look at application security vulnerabilities. So what our customers do is they go create rules that say, Hey, if any of these companies in my tier one critical vendor watch list, if they have any of these parameters, if the score drops, if they drop below a B, if they have these issues, pick these actions and the actions could be, send them a questionnaire. We can send the questionnaire for you. You don't have to send pen and paper, forget about it. You're going to open your email and drag the Excel spreadsheet. Those days are over. We're done with that. We automate that. You don't want to send a questionnaire, send a report. We have integrations, notify Slack, create a Jira ticket, pipe it to ServiceNow. Whatever system of record, system of intelligence, workflow tools companies are using, we write in and allow them to expedite the whole. We're trying to close the window. We want to close the window of the attack. And in order to do that, we have to bring the attention to the people as quickly as possible. That's not going to happen if someone logs in every day. So we've got the platform and then that automation capability on top of it. >> I love the vision. I love the utility of a scorecard, a verification mark, something that could be presented, credential, an image, social proof. To security and an ongoing way to monitor it, observe it, update it, add value. I think this is only going to be the beginning of what I would see as much more of a new way to think about credentialing companies. >> I think we're going to reach a point, John, where and some of our customers are already doing this. They're publishing their scorecard in the public domain, not with the technical details, but an abstracted view. And thought leaders, what they're doing is they're saying, Hey, before you send me anything, look at my scorecard securityscorecard.com/securityrating, and then the name of their company, and it's there. It's in the public domain. If somebody Googles scorecard for certain companies, it's going to show up in the Google Search results. They can mitigate probably 30, 40% of inbound requests by just pointing to that thing. So we want to give more of those tools, turn security from a reactive to a proactive motion. >> Great stuff, Sam. I love it. I'm going to make sure when you hit our site, our company, we've got camouflage sites so we can make sure you get the right ones. I'm sure we got some copyright dates. >> We can navigate the decoys. We can navigate the decoys sites. >> Sam, thanks for coming on. And looking forward to speaking more in depth on showcase that we have upcoming Amazon Startup Showcase where you guys are going to be presenting. But I really appreciate this conversation. Thanks for sharing what you guys are working on. We really appreciate. Thanks for coming on. >> Thank you so much, John. Thank you for having me. >> Okay. This is theCUBE conversation here in Palo Alto, California. Coming in from New York city is the co-founder, chief operating officer of securityscorecard.com. I'm John Furrier. Thanks for watching. (gentle music)
SUMMARY :
to this CUBE conversation. Thanks for having me. and having values what you guys and see that the website of the 12 million that we're rating. then you create relevance, wow, you guys are building and the rest is history. for management and the team. So the status quo for the and it just seems hard to keep up with. I mean the clouds help Sometimes the information is inaccurate. and the third party? the capabilities, keys to the other day here in IT and the ghost vendors I forget the number. and nobody knew the internet works, the administrative portal the risk here of what they have. and all the humans that You're in the front lines. and the ratings companies to the board. and see the new things, I mean only is going to and get more into the I love the vision. It's in the public domain. I'm going to make sure when We can navigate the decoys. And looking forward to speaking Thank you so much, John. city is the co-founder,
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AWS Storage Day 2022 Intro
(upbeat music) >> Welcome to theCUBE's coverage of AWS Storage Day 2022. My name is Dave Vellante. In 2021, theCUBE team was in Seattle covering Storage Day. And after that event, I wrote a breaking analysis piece on Wikibon and SiliconANGLE called "Thinking Outside The Box, "AWS Signals A New Era For Storage." And the point of that post was that the cloud's impact was clearly moving into the storage realm in a big way. And the days of consuming storage as a box were numbered. And I projected, AWS doesn't share these numbers but I projected that AWS's storage business was on track to hit $10 billion, making it the second largest purveyor of storage with a gross trajectory that by mid-decade would make AWS the number one storage player in the market. Now, a lot of people didn't like that post, particularly the fact that I was mixing AWS storage service, OpEx, with what generally were CapEx purchases. But I didn't really care to argue the nuance of CapEx versus OpEx. Rather, the point I was really making was, and I was looking at the spending data from ETR and estimating the revenue for the players, and the message was clear. Data was moving to and being created in the cloud much faster than on-prem and the spending patterns were following data growth. Now, fast forward almost 12 months and the picture is even more clear to me. The number of cloud storage services from AWS is expanding as is their consequent adoption. The pace of delivery is accelerating. And very importantly, the optionality of the ecosystem is exploding. Virtually every storage company, primary, secondary, data protection, archival, is partnering with AWS to run their services in the cloud and in many cases connect to their on-prem installations, expanding the cloud as we've talked about and written about extensively. Despite the narrative from some about repatriation and people moving out of the cloud back on-prem, such activity is a rounding error in the grand scheme of enterprise tech spending. The data is clear, cloud and cloud storage spending continues to grow at 30% plus per year, far ahead of any other markets. Now, the edge presents new opportunities and likely will bring novel architectures as we've predicted many times covering what AWS is doing with the Arm-based Graviton and others. Now, this is especially important at the far edge, like real-time AI inferencing and new workloads. You know, there's questions that remain about how much storage is going to persist at the edge, how much is going to go back into the cloud, and what requirements exist across the board. But in many respects, the edge is all incremental in terms of data growth and data creation. So the challenge is how do we harness the power of that data? So what can we expect going forward in storage? Well, the pace of service delivery from hyperscale providers generally and AWS specifically is going to continue to accelerate. AWS is likely going to lead the way. We've seen this, started with S3, expand storage portfolio into block and file, and then bringing cohort services like new compute architectures, we've talked about Nitro and Graviton and others, and a portfolio of database options and new machine intelligence, machine learning, and AI solutions. Storage in the cloud is moving from being a bit bucket to being a platform that is evolving as part of an emerging data mesh architecture where business users, those with context, gain secure, governed, and facile self-service access to data that they need when they need it so they can make better decisions and importantly create new data products and services. This is the vision for data generally in the 2020s and cloud storage specifically will be an underpinning of this new era. Thanks for watching theCUBE's coverage of AWS Storage Day. This is Dave Vellante. (upbeat music)
SUMMARY :
and the message was clear.
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Rashmi Kumar, HPE | HPE Discover 2022
>> Announcer: theCUBE presents HPE Discover 2022, brought to you by HPE. >> We're back at the formerly the Sands Convention Center, it's called the Venetian Convention Center now, Dave Vellante and John Furrier here covering day three, HPE Discover 2022, it's hot outside, it's cool in here, and we're going to heat it up with Rashmi Kumar, who's the Senior Vice President and CIO of Hewlett Packard Enterprise, great to see you face to face, it's been a while. >> Same here, last couple of years, we were all virtual. >> Yeah, that's right. So we've talked before about sort of your internal as-a-service transformation, you know, we do call it dog fooding, everybody likes to course correct and say, no, no, it's drinking your own champagne, is it really that pretty? >> It is, and the way I put it is, no pressure to my product teams, it's being customer zero. >> Right, take us through the acceleration on how everything's been going with you guys, obviously, the pandemic was an impact to certainly the CIO role and your team but now you've got GreenLake coming in and Antonio's big statement before the pandemic, by 2022 everything will be as a service and then everything went remote, VPNs and all this new stuff, how's it going? >> Yeah, so from business perspective, that's a great point to start that, right? Antonio promised in 2019 that HPE will be Everything-as-a-Service company and he had no view of what's going to happen with COVID. But guess what? So many businesses became digital and as-a-service during those two years, right? And now we came back this year, it was so exciting to be part of Discover when now we are Everything-as-a-Service. So great from business perspective but, when I look at our own transformation, behind the scene, what IT has been busy with and we haven't caught a breadth because of pandemic, we have taken care of all that change, but at the same time have driven our transformation to make HPE, edge to cloud platform as a service company. >> You know, I saw a survey, I referenced it earlier today, it was a survey, I think it was been by Couchbase, it was a CIO survey, so they asked, who was responsible at your organization for the digital transformation? And overwhelming, like 75% said, CIO, which surprised me 'cause, you know, in line with the business and so forth but in fact I thought, well, maybe, because of the forced march to digital that's what was top of their mind, so who is responsible for, and I know it's not just one person, for the digital transformation? Describe that dynamic. >> Yeah, so definitely it's not one person, but you do need that whole accountable, responsible, informed, right, in the context of digital transformation. And you call them CIO, you call them CDIO or CDO and whatnot but, end of the day, technology is becoming an imperative for a business to be successful and COVID alone has accelerated it, I'm repeating this maybe millions time if you Google it but, CIOs are best positioned because they connect the dots across organization. In my organization at HPE, we embarked upon this large transformation where we were consolidating 10 different ERPs, multiple master data system into one and it wasn't about doing digital which is e-commerce website or one technology, it was creating that digital foundation for the company then to transform that entire organization to be a physical product company to a digital product company. And we needed that foundation for us to get that code to cash experience, not only in our traditional business, but in our as-a-service company. >> So maybe that wasn't confirmation bias, I want to ask you about, we've been talking a lot about sustainability and I've made the comment that, if you go back, you know, 10, 12 years and you were CIO IT at that time, CIO really didn't care about the energy bill, that was paid for by facilities, they really didn't talk to each other much and that's completely changed, why has it changed? How should a CIO, how do your your peers think about energy costs today? >> Yeah, so, at some point look, ESG is the biggest agenda for companies, regulators, even kind of the watchers of ISS and Glass Lewis type thing and boards are becoming aware of it. If you look at 2-4% of greenhouse emission comes from infrastructure, specifically technology infrastructure, as part of this transformation within HPE, I also did what I call private cloud transformation. Remember, it's not data center transformation, it's private cloud transformation. And if you can take your traditional workload and cloudify it which runs on a GreenLake type platform, it's currently 30% more efficient than traditional way of handling the workload and the infrastructure but, we recently published our green living progress report and we talk about efficiency, by 2020 if you have achieved three times, the plan is to get to 30 times by 2050 where, infrastructure will not contribute to energy bill in turn the greenhouse emission as well. I think CIOs are responsible multifold on the sustainability piece. One is how they run their data center, make it efficient with GreenLake type implementations, demand from your hyperscaler to provide that, what Fidelma just launched, sustainability scorecard of the infrastructure, second piece is, we are the data gods in the company, right? We have access to all kinds of data, provide that to the product teams and have them, if we cannot measure, we cannot improve. So if you work with your product team, work with your BU leader, provide them data around greenhouse gas and how they're impacting a mission through their products and how can they make it better going forward, and that can be done through technology, right? All the measurements come from technology. So what technology we need to provide to our manufacturing lines so that they can monitor and improve on the sustainability front as well. >> You mentioned data, I wanted to bring that up 'cause I was going to bring that up in another top track here, data as an asset now is at play, so I get the data on the sustainability, feed that in, but as companies go to the cloud operating model, they go, hey, I got the hyperscalers, you call microscale, Amazon for instance, and you got on-premises data center, which is a large edge and you got the edge, the data control plane, and then the control plane and the data plane are always seem to be like the battle ground, I want to control the data plane, will customers own the data plane or will the infrastructure providers control that data plane? And how do you see that? Because we want to power the machine learning, so data plane control plane, it seems to be like the new middleware, what's your view on that? How do you look at that holistically? >> Yeah, so I'll start based on the hyperscaler conversation, right? And I had this conversation with one of the very big ones recently, or even our partner, SAP, when they talk about RISE, data center and how I host my application infrastructure, that's the lowest common denominator of our job. When I talk about CIOs being responsible for digital transformation, that means how do I make my business process more innovative? How do I make my data more accessible, right? So, if you look at data as an asset for the company, it's again, they're responsible, accountable. As CIO, I'm responsible to have it managed, have it on a technology platform, which makes it accessible by it and our business leader accountable to define the right metrics, right kind of KPIs, drive outcome from that data. IT organization, we are also too busy driving a lot of activities and today's world is going to bad business outcome. So with the data that I'm collecting, how do I enable my business leader to be able to drive business outcome through the use of the data? That's extremely important, and at HPE, we have achieved it, there are two ways, right? Now I have one single ERP, so all the data that I need for what I call operational reporting, get hindsight and insight is available at one place and they can drive their day to day business with that, but longer term, what's going to happen based on what happened, which I call insight to foresight comes from a integrated data platform, which I have control of, and you know, we are fragmenting it because companies now have Databox, Snowflake, AWS data analytics tool, Azure data analytics tool, I call it data torture. CIOs should get control of common set of data and enable their businesses to define better measurements and KPIs to be able to drive the data. >> So data's a crown jewel then, it's crown jewel not-- >> Can we double-click on that because, okay, so you take your ERP system, the consumers of data in the ERP system, they have the context that we've kind of operationalized those systems. We haven't operationalized our analytics systems in the same way, which is kind of a weird dynamic, and so you, right, I think correctly noted Rashmi that, we are creating all these stove pipes. Now, think I heard from you, you're gaining control of those stove pipes, but then how do you put data back in the hands of those line of business users without having to go through a hyper specialized analytics team? And that's a real challenge I think for data. >> It is challenge and I'll tell you, it's messy even in my world but, I have dealt with data long enough, the value lies in how do I take control of all stove pipes, bring it all together, but don't make it a data lake which is built out of multiple puddles, that data lake promise hasn't delivered, right? So the value lies in the conformed layer which then it's easier for businesses to access and run their analytics from, because they need a playground because all the answers they don't have, on the operation side, as you mentioned, we got it, right? It'll happen, but on the fore site side and deeper insight side based on driving the key metrics, two challenges; understanding what's the key metrics in KPI, but the second is, how to drive visibility and understanding of it. So we need to get technology out of the conversation, bring in understanding of the data into the conversation and we need to drive towards that path. >> As a business, you know, line of business person putting that hat on, I would love to have this conversation with my CIO because I would say, I just want self-service infrastructure and I want to have access to the data that I need, I know what metrics I need to run my business so now I want the technology to be just a technical detail, you take care of that and then somebody in the organization, probably not the line of business person wants to make sure that that data is governed and secure. So there's somebody else and that maybe is your responsibility, so how do you handle that real problem? So I think you're well on the track with GreenLake for self-serve infrastructure, right, how do you handle the sort of automated governance piece of it, make that computational? Yeah, so one thing is technology is important because that's bringing all the data together at one place with single version of truth. And then, that's why I say my sons are data scientist, by the way, I tell them that the magic happens at the intersection of technology knowledge, data knowledge, and business knowledge, and that's where the talent, which is very hard to find who can connect dots across these three kind of circles and focus on that middle where the value lies and pushing businesses to, because, you know, business is messy, I've worked on pharma companies, utilities, now technology, order does not mean revenue, right? There's a lot more that happen and pricing or chargeback, rebates, all that things, if somebody can kind of make sense out of it through incremental innovation, it's not like a big bang I know it all, but finding those areas and applying what you said, I call it the G word, governance, to make sure your source is right and then creating that conform layer then makes into the dashboard the right information about those types of metrics is extreme. >> And then bringing that to the ecosystem, now I just made it 10 times more complicated. >> Yeah, this is a great conversation, we on theCUBE interview one time we're talking about the old software days where shrink-wrap software be on the shelf, you wouldn't know if was successful until you looked at the sales data, well after the fact, now everything's instrumented, SaaS companies, you know exactly what the adoption is, either people like it or they don't, the data doesn't lie. So now companies are realizing, okay, I got data, I can instrument everything, your customers are now saying, I can get to the value fast now. So knowing what that value is is what everyone's talking about. How do you see that changing the data equation? >> Yeah, that's so true even for our business, right? If you talk to Fidelma today, who is our CTO, she's bringing together the platform and multiple platforms that we had so far to go to as-a-service business, right? Infosite, Aruba Central, GLCP, or now we call it it's all HPE GreenLake, but now this gives us the opportunity to really be a alongside customer. It's no more, I sold a box, I'll come back to you three years later for a refresh, now we are in touch with our customer real time through Telemetry data that's coming from our products and really understanding how our customers are reacting with that, right? And that's where we instantiated what we call is a federated data lake where, marketing, product, sales, all teams can come together and look at what's going on. Customer360, right? Data is locked in Salesforce from opportunity, leads, codes perspective, and then real time orders are locked in S4. The challenge is, how do we bring both together so that our sales people have on their fingertip whats the install base look like, how much business that we did and the traditional side and the GreenLake side and what are the opportunities here to support our customers? >> Real quick, I know we don't have a lot of time left, but I want to touch on machine learning, which basically feeds AI, machine learning, AI go together, it's only as good as the data you can provide to it. So to your point about exposing the data while having the stove pipes for compliance and governance, how do you architect that properly? You mentioned federated data lake and earlier you said the data lake promise hasn't come back, is it data meshes? What is the architecture to have as much available data to be addressed by applications while preserving the protection? >> Yeah, so, machine learning and AI, I will also add chatbots and conversational AI, right? Because that becomes the front end of it. And that's kind of the automation process promise in the data space, right? So, the point is that, if we talk about federated data lake around one capability which I'm talking about GreenLake consumption, right? So one piece is around, how do I get data cleanly? How do I relate it across various products? How do I create metrics out of it? But how do I make it more accessible for our users? And that's where the conversational AI and chatbot comes in. And then the opportunity comes in is around not only real time, but analytics, I believe Salesforce had a pitch called customer insight few years ago, where they said, we have so many of you on our platform, now I can combine all the data that I can access and want to give you a view of how every company is interacting with their customer and how you can improve it, that's where we want to go. And I completely agree, it ends up being clean data, governed data, secure data, but having that understanding of what we want to project out and how do I make it accessible for our users very seamlessly. >> Last question, what's your number one challenge right now in this post isolation world? >> Talent, we haven't talked about that, right? >> Got to get that out there. >> All these promises, right, the entire end to end foundational transformation, as-a-service transformation, talking about the promise of data analytics, we talked about governance and security, all that is possible because of the talent we have or we will have, and our ability to attract and retain them. So as CIO, I personally spend a lot of time, CEO, John Schultz, Antonio, very, very focused on creating that employee experience and what we call everything is edge for us, so edge to office initiative where we are giving them hybrid work capabilities, people are very passionate about purpose, so sustainability, quality, all these are big deal for them, making sure that senior leadership is focused on the right thing, so, hybrid working capability, hiring the right set of people with the right skill set and keeping them excited about the work we are doing, having a purpose, and being honest about it means I haven't seen a more authentic leader than Antonio, who opens up his keynote for this type of convention, with the purpose that he's very passionate about in current environment. >> Awesome, Rashmi, always great to have you on, wonderful to have you face to face, such a clear thinker in bringing your experience to our audience, really appreciate it. >> Thank you, I'm a big consumer of CUBE and look forward to having-- >> All right, and keep it right there, John and I will be back to wrap up with Norm Follett, from HPE discover 2022, you're watching theCUBE. (gentle music)
SUMMARY :
brought to you by HPE. great to see you face to Same here, last couple of is it really that pretty? It is, and the way I put it is, behind the scene, what because of the forced march to digital foundation for the company then and improve on the and KPIs to be able to drive the data. in the same way, which is but the second is, how to drive visibility and applying what you that to the ecosystem, don't, the data doesn't lie. and the traditional side What is the architecture to and how you can improve it, the entire end to end great to have you on, John and I will be back to
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Alexey Surkov, Deloitte | Amazon re:MARS 2022
(upbeat music) >> Okay, welcome back everyone to theCube's coverage of AWS re:Mars here in Las Vegas. I'm John Furrier, host of theCube. Got Alexey Surkov, Partner at Deloitte joining me today. We're going to talk about AI biased AI trust, trust in the AI for the, to save the planet to save us from the technology. Alexey thanks for coming on. >> Thank you for having me. >> So you had a line before you came on camera that describe the show, and I want you to say it if you don't mind because it was the best line that for me, at least from my generation. >> Alexey: Sure. >> That describes the show and then your role at Deloitte in it. >> Alexey: Sure. Listen, I mean, I, you know, it may sound a little corny, but to me, like I look at this entire show, at this whole building really, and like everybody here is trying to build a better Skynet, you know, better, faster, stronger, more potent, you know, and it's like, we are the only ones, like we're in this corner of like Deloitte trustworthy AI. We're trying to make sure that it doesn't take over the world. So that's, you know, that's the gist of it. How do you make sure that AI serves the good and not evil? How do you make sure that it doesn't have the risk? It doesn't, you know, it's well controlled that it does what we're, what we're asking it to do. >> And of course for all the young folks out there the Terminator is the movie and it's highly referenced in the nerd circles Skynet's evil and helps humanity goes away and lives underground and fights for justice and I think wins at the end. The Terminate three, I don't, I can't remember what happened there, but anyway. >> Alexey: I thought the good guys win, but, you know, that's. >> I think they do win at the end. >> Maybe. >> So that brings up the whole point because what we're seeing here is a lot of futuristic positive messages. I mean, three areas solve a lot of problems in the daily lives. You know, machine learning day to day hard problems. Then you have this new kind of economy emerging, you know, machine learning, driving new economic models, new industrial capabilities. And then you have this whole space save the world vibe, you know, like we discover the moon, new water sources maybe save climate change. So very positive future vibe here at re:Mars. >> Alexey: Absolutely. Yeah, and it was really exciting just watching, you know, watching the speakers talk about the future, and conquering space, and mining on the moon like it's happening already. It's really exciting and amazing. Yeah. >> Let's talk about what you guys are working at Deloitte because I think it's fascinating. You starting to see the digital transformation get to the edge. And when I say edge, I mean back office is done with cloud and you still have the old, you know, stuff that the old models that peoples will use, but now new innovative things are happening. Pushing software out there that's driving you with the FinTech, these verticals, and the trust is a huge factor. Not only do the consumers have a trust issues, who owns my data, there's also trust in the actual algorithms. >> Exactly. >> You guys are in the middle of this. What's your advice to clients, 'cause they want to push the envelope hard be cutting edge, >> Alexey: Right. >> But they don't want to pull back and get caught with their, you know, data out there that might been a misfire or hack. >> Absolutely. Well, I mean the simple truth is that, you know, with great power comes great responsibility, right? So AI brings a lot of promise, but there are a lot of risks, you know. You want to make sure that it's fair, that it's not biased. You want to make sure that it's explainable, that you can figure out and tell others what it's doing. You might want to make sure that it's well controlled, that it's responsible, that it's robust, that, you know, if somebody feeds it bad data, it doesn't produce results that don't make sense. If somebody's trying to provoke it, to do something wrong, that it's robust to those types of interactions. You want to make sure that it preserves privacy. You know, you want to make sure that it's secure, that nobody can hack into it. And so all of those risks are somewhat new. Not all of them are entirely new. As you said, the concept of model risk management has existed for many years. We want to make sure that each black box does what it's supposed to do. Just AI machine learning just raises it to the next level. And we're just trying to keep up with that and make sure that we develop processes, you know, controls that we look at technology that can orchestrate all this de-risking of transition to AI. >> Deloitte's a big firm. You guys saw you in the US open sponsorship was all over the TV. So that you're here at re:Mars show that's all about building up this next infrastructure in space and machine learning, what's the role you have with AWS and this re:Mars. And what's that in context of your overall relationship to the cloud players? >> Alexey: Well, we are, we're one of the largest strategic alliances for AWS, and AWS is one of the largest ones for Deloitte. We do a ton of work with AWS related to cloud, related to AI machine learning, a lot of these new areas. We did a presentation here just the other day on conversational AI, really cutting edge stuff. So we do all of that. So in some ways we participate in that part of the, the part of the room that I mentioned that is trying to kind of push the envelope and get the new technologies out there, but at the same time, Deloitte is a brand that carries a lot of, you know, history of trust, and responsibility, and controls, and compliance, and all of that comes, >> John: You get a lot of clients. I mean, you have big names. Get a lot of big name enterprises >> Right. >> That relied on you. >> Right, and so >> They rely on you now. >> Exactly, yeah. And so, it is natural for us to be in the marketplace, not only with the message of, you know, let's get to the better mouse trap in AI and machine learning, but also let's make sure that it's safe, and secure, and robust, and reliable, and trustworthy at the end of the day. And so, so this trustworthy message is intertwined with everything that we do in AI. We encourage companies to consider trustworthiness from the start. >> Yeah. >> It shouldn't be an afterthought, you know. Like I always say, you know, if you have deployed a bot and it's been deciding whether to issue loans to people, you don't want to find out that it was like, you know, biased against a certain type of (indistinct) >> I can just see in the boardroom, the bot went rogue. >> Right, yeah. >> Through all those loans you know. >> And you don't want to find out about it like six months later, right? That's too late, right? So you want to build in these controls from the beginning, right? You want to make sure that, you know, you are encouraging innovation, you're not stifling any development, and allowing your- >> There's a lot of security challenges too. I mean, it's like, this is the digital transformation sweet spot you're in right now. So I have to ask you, what's the use case, obviously call center's obvious, and bots, and having, you know, self-service capabilities. Where is the customers at right now on psychology and their appetite to push the envelope? And what do you guys see as areas that are most important for your customers to pay attention to? And then where do you guys ultimately deliver the value? >> Sure. Well, our clients are, I think, are aware of the risks of AI. They are not, that's not the first thing that they're thinking about for the most part. So when we come to them with this message they listen, they're very interested. And a lot of them have begun this journey of putting in kind of governance, compliance, controls, to make sure that as they are proceeding down this path of building out AI, that they're doing it responsibly. So it is in a nascent stage. >> John: What defines responsibility? >> Well, you want to, okay, so responsibility is really having governance. Like you have a, you build a robot dog, right? So, but you want to make sure that it has a leash, right? That it doesn't hurt anybody, right? That you have processes in place that at the end of the day, humans are in control, right? I don't want to go back to the Skynet analogy, right? >> John: Yeah. >> But humans should always be in control. There should always be somebody responsible for the functioning of the algorithm that can throw the switch at the right time, that can tweak it at the right time, that can make sure that you nudge it in the right direction that at no point should somebody be able to say, oh, well, it's not my fault. The algorithm did it, and that's why we're in the papers today, right? So that's the piece that's really complex, and what we try to do for our clients as Deloitte always does is kind of demystify that, right? >> John: Yeah. >> So what does it actually mean from a procedures, policies, >> John: Yeah, I mean, I think, >> Tools, technology, people. >> John: Yeah, I mean, this is like the classic operationalizing a new technology, managing it, making sure it doesn't get out of control if you will. >> Alexey: Exactly. >> Stay on the leash if you will. >> Alexey: Exactly. Yeah. And I guess one piece that I always like to mention is that, it's not to put breaks on these new technologies, right? It's not to try to kind of slow people down in developing new things. I actually think that making AI trustworthy is enabling the development of these technologies, right? The way to think about it is that, we have, you know, seat belts, and abs brakes, and, you know, airbags today. And those are all things that didn't exist like 100 years ago, but our cars go a lot faster, and we're a lot safer driving them. So, you know, when people say, oh, I hate seatbelts, you know, you're like, okay, yes, but first of all, there are some safety technologies that you don't even notice, which is how a lot of AI controls work. They blend into the background. And more importantly, the idea is for you to go faster, not slower. And that's what we're trying to enable our clients to do. >> Well, Alexey, great to have you on theCube. We love Deloitte come on to share their expertise. Final question for you is, where do you see this show going? Where do you guys, obviously you here, you're participating, you got a big booth here, where's this going? And what's next, where's the next dots that connect? Share your vision for this show, and kind of how it, or the ecosystem, and this ecosystem, and where you're going to intersect that? >> Wow. I mean, this show is already kind of pushing the boundaries. You know, we're talking about machine learning, artificial intelligence, you know, robotics, space. You know, I guess next thing I think, you know, we'll be probably spending a lot of time in the metaverse, right? So I can see like next time we come here, you know, half of us are wearing VR headsets and walking around and in meta worlds, but, you know, it's been an exciting adventure and, you know I'm really excited to partner and spend, you know spend time with AWS folks, and everybody here because they're really pushing the envelope on the future, and I look forward to next year >> The show is small, so it feels very intimate, which is actually a good feeling. And I think the other thing in metaverse I heard that too. I heard quantum. I said next, I heard, I've heard both those next year quantum and metaverse. >> Okay. >> Well, why not? >> Why not? Exactly, yeah. >> Thanks for coming on theCube. Appreciate it. >> Thank you. >> All right. It's theCube coverage here on the ground. Very casual Cube. Two days of live coverage. It's not as hot and and heavy as re:Invent, but it's a great show bringing all the best smart people together, really figure out the future, you know, solving problems day to day problems, and setting the new economy, the new industrial economy. And of course, a lot of the world problems are going to be helped and solved, very positive message space among other things here at re:Mars. I'm John furrier. Stay with us for more coverage after this short break. (upbeat music)
SUMMARY :
the, to save the planet and I want you to say it That describes the show So that's, you know, in the nerd circles Skynet's evil but, you know, that's. of economy emerging, you know, just watching, you know, and you still have the old, you know, You guys are in the middle of this. with their, you know, that it's robust, that, you know, You guys saw you in carries a lot of, you know, I mean, you have big names. not only with the message of, you know, Like I always say, you know, I can just see in the boardroom, and having, you know, that's not the first thing that at the end of the day, that can make sure that you out of control if you will. the idea is for you to and kind of how it, or the we come here, you know, in metaverse I heard that too. Exactly, yeah. Thanks for coming on theCube. you know, solving problems
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Joe Nolte, Allegis Group & Torsten Grabs, Snowflake | Snowflake Summit 2022
>>Hey everyone. Welcome back to the cube. Lisa Martin, with Dave ante. We're here in Las Vegas with snowflake at the snowflake summit 22. This is the fourth annual there's close to 10,000 people here. Lots going on. Customers, partners, analysts, cross media, everyone talking about all of this news. We've got a couple of guests joining us. We're gonna unpack snow park. Torston grabs the director of product management at snowflake and Joe. No NTY AI and MDM architect at Allegis group. Guys. Welcome to the program. Thank >>You so much for having >>Us. Isn't it great to be back in person? It is. >>Oh, wonderful. Yes, it >>Is. Indeed. Joe, talk to us a little bit about Allegis group. What do you do? And then tell us a little bit about your role specifically. >>Well, Allegis group is a collection of OPCA operating companies that do staffing. We're one of the biggest staffing companies in north America. We have a presence in AMEA and in the APAC region. So we work to find people jobs, and we help get 'em staffed and we help companies find people and we help individuals find >>People incredibly important these days, excuse me, incredibly important. These days. It is >>Very, it very is right >>There. Tell me a little bit about your role. You are the AI and MDM architect. You wear a lot of hats. >>Okay. So I'm a architect and I support both of those verticals within the company. So I work, I have a set of engineers and data scientists that work with me on the AI side, and we build data science models and solutions that help support what the company wants to do, right? So we build it to make business business processes faster and more streamlined. And we really see snow park and Python helping us to accelerate that and accelerate that delivery. So we're very excited about it. >>Explain snow park for, for people. I mean, I look at it as this, this wonderful sandbox. You can bring your own developer tools in, but, but explain in your words what it >>Is. Yeah. So we got interested in, in snow park because increasingly the feedback was that everybody wants to interact with snowflake through SQL. There are other languages that they would prefer to use, including Java Scala and of course, Python. Right? So then this led down to the, our, our work into snow park where we're building an infrastructure that allows us to host other languages natively on the snowflake compute platform. And now here, what we're, what we just announced is snow park for Python in public preview. So now you have the ability to natively run Python code on snowflake and benefit from the thousands of packages and libraries that the open source community around Python has contributed over the years. And that's a huge benefit for data scientists. It is ML practitioners and data engineers, because those are the, the languages and packages that are popular with them. So yeah, we very much look forward to working with the likes of you and other data scientists and, and data engineers around the Python ecosystem. >>Yeah. And, and snow park helps reduce the architectural footprint and it makes the data pipelines a little easier and less complex. We have a, we had a pipeline and it works on DMV data. And we converted that entire pipeline from Python, running on a VM to directly running down on snowflake. Right. We were able to eliminate code because you don't have to worry about multi threading, right? Because we can just set the warehouse size through a task, no more multi threading, throw that code away. Don't need to do it anymore. Right. We get the same results, but the architecture to run that pipeline gets immensely easier because it's a store procedure that's already there. And implementing that calling to that store procedure is very easy. The architecture that we use today uses six different components just to be able to run that Python code on a VM within our ecosystem to make sure that it runs on time and is scheduled and all of that. Right. But with snowflake, with snowflake and snow park and snowflake Python, it's two components. It's the store procedure and our ETL tool calling it. >>Okay. So you've simplified that, that stack. Yes. And, and eliminated all the other stuff that you had to do that now Snowflake's doing, am I correct? That you're actually taking the application development stack and the analytics stack and bringing them together? Are they merging? >>I don't know. I think in a way I'm not real sure how I would answer that question to be quite honest. I think with stream lit, there's a little bit of application that's gonna be down there. So you could maybe start to say that I'd have to see how that carries out and what we do and what we produce to really give you an answer to that. But yeah, maybe in a >>Little bit. Well, the reason I asked you is because you talk, we always talk about injecting data into apps, injecting machine intelligence and ML and AI into apps, but there are two separate stacks today. Aren't they >>Certainly the two are getting closer >>To Python Python. It gets a little better. Explain that, >>Explain, explain how >>That I just like in the keynote, right? The other day was SRE. When she showed her sample application, you can start to see that cuz you can do some data pipelining and data building and then throw that into a training module within Python, right down inside a snowflake and have it sitting there. Then you can use something like stream lit to, to expose it to your users. Right? We were talking about that the other day, about how do you get an ML and AI, after you have it running in front of people, we have a model right now that is a Mo a predictive and prescriptive model of one of our top KPIs. Right. And right now we can show it to everybody in the company, but it's through a Jupyter notebook. How do I deliver it? How do I get it in the front of people? So they can use it well with what we saw was streamlet, right? It's a perfect match. And then we can compile it. It's right down there on snowflake. And it's completely easier time to delivery to production because since it's already part of snowflake, there's no architectural review, right. As long as the code passes code review, and it's not poorly written code and isn't using a library that's dangerous, right. It's a simple deployment to production. So because it's encapsulated inside of that snowflake environment, we have approval to just use it. However we see fit. >>It's very, so that code delivery, that code review has to occur irrespective of, you know, not always whatever you're running it on. Okay. So I get that. And, and, but you, it's a frictionless environment you're saying, right. What would you have had to do prior to snowflake that you don't have to do now? >>Well, one, it's a longer review process to allow me to push the solution into production, right. Because I have to explain to my InfoSec people, right? My other it's not >>Trusted. >>Well, well don't use that word. No. Right? It got, there are checks and balances in everything that we do, >>It has to be verified. And >>That's all, it's, it's part of the, the, what I like to call the good bureaucracy, right? Those processes are in place to help all of us stay protected. >>It's the checklist. Yeah. That you >>Gotta go to. >>That's all it is. It's like fly on a plane. You, >>But that checklist gets smaller. And sometimes it's just one box now with, with Python through snow park, running down on the snowflake platform. And that's, that's the real advantage because we can do things faster. Right? We can do things easier, right? We're doing some mathematical data science right now and we're doing it through SQL, but Python will open that up much easier and allow us to deliver faster and more accurate results and easier not to mention, we're gonna try to bolt on the hybrid tables to that afterwards. >>Oh, we had talk about that. So can you, and I don't, I don't need an exact metric, but when you say faster talking 10% faster, 20% faster, 50% path >>Faster, it really depends on the solution. >>Well, gimme a range of, of the worst case, best case. >>I, I really don't have that. I don't, I wish I did. I wish I had that for you, but I really don't have >>It. I mean, obviously it's meaningful. I mean, if >>It is meaningful, it >>Has a business impact. It'll >>Be FA I think what it will do is it will speed up our work inside of our iterations. So we can then, you know, look at the code sooner. Right. And evaluate it sooner, measure it sooner, measure it faster. >>So is it fair to say that as a result, you can do more. Yeah. That's to, >>We be able do more well, and it will enable more of our people because they're used to working in Python. >>Can you talk a little bit about, from an enablement perspective, let's go up the stack to the folks at Allegis who are on the front lines, helping people get jobs. What are some of the benefits that having snow park for Python under the hood, how does it facilitate them being able to get access to data, to deliver what they need to, to their clients? >>Well, I think what we would use snowflake for a Python for there is when we're building them tools to let them know whether or not a user or a piece of talent is already within our system. Right. Things like that. Right. That's how we would leverage that. But again, it's also new. We're still figuring out what solutions we would move to Python. We are, we have some targeted, like we're, I have developers that are waiting for this and they're, and they're in private preview. Now they're playing around with it. They're ready to start using it. They're ready to start doing some analytical work on it, to get some of our analytical work out of, out of GCP. Right. Because that's where it is right now. Right. But all the data's in snowflake and it just, but we need to move that down now and take the data outta the data wasn't in snowflake before. So there, so the dashboards are up in GCP, but now that we've moved all of that data down in, down in the snowflake, the team that did that, those analytical dashboards, they want to use Python because that's the way it's written right now. So it's an easier transformation, an easier migration off of GCP and get us into snow, doing everything in snowflake, which is what we want. >>So you're saying you're doing the visualization in GCP. Is that righting? >>It's just some dashboarding. That's all, >>Not even visualization. You won't even give for. You won't even give me that. Okay. Okay. But >>Cause it's not visualization. It's just some D boardings of numbers and percentages and things like that. It's no graphic >>And it doesn't make sense to run that in snowflake, in GCP, you could just move it into AWS or, or >>No, we, what we'll be able to do now is all that data before was in GCP and all that Python code was running in GCP. We've moved all that data outta GCP, and now it's in snowflake and now we're gonna work on taking those Python scripts that we thought we were gonna have to rewrite differently. Right. Because Python, wasn't available now that Python's available, we have an easier way of getting those dashboards back out to our people. >>Okay. But you're taking it outta GCP, putting it to snowflake where anywhere, >>Well, the, so we'll build the, we'll build those, those, those dashboards. And they'll actually be, they'll be displayed through Tableau, which is our enterprise >>Tool for that. Yeah. Sure. Okay. And then when you operationalize it it'll go. >>But the idea is it's an easier pathway for us to migrate our code, our existing code it's in Python, down into snowflake, have it run against snowflake. Right. And because all the data's there >>Because it's not a, not a going out and coming back in, it's all integrated. >>We want, we, we want our people working on the data in snowflake. We want, that's our data platform. That's where we want our analytics done. Right. We don't want, we don't want, 'em done in other places. We when get all that data down and we've, we've over our data cloud journey, we've worked really hard to move all of that data. We use out of existing systems on prem, and now we're attacking our, the data that's in GCP and making sure it's down. And it's not a lot of data. And we, we fixed it with one data. Pipeline exposes all that data down on, down in snowflake now. And we're just migrating our code down to work against the snowflake platform, which is what we want. >>Why are you excited about hybrid tables? What's what, what, what's the >>Potential hybrid tables I'm excited about? Because we, so some of the data science that we do inside of snowflake produces a set of results and there recommendations, well, we have to get those recommendations back to our people back into our, our talent management system. And there's just some delays. There's about an hour delay of delivering that data back to that team. Well, with hybrid tables, I can just write it to the hybrid table. And that hybrid table can be directly accessed from our talent management system, be for the recruiters and for the hiring managers, to be able to see those recommendations and near real time. And that that's the value. >>Yep. We learned that access to real time. Data it in recent years is no longer a nice to have. It's like a huge competitive differentiator for every industry, including yours guys. Thank you for joining David me on the program, talking about snow park for Python. What that announcement means, how Allegis is leveraging the technology. We look forward to hearing what comes when it's GA >>Yeah. We're looking forward to, to it. Nice >>Guys. Great. All right guys. Thank you for our guests and Dave ante. I'm Lisa Martin. You're watching the cubes coverage of snowflake summit 22 stick around. We'll be right back with our next guest.
SUMMARY :
This is the fourth annual there's close to Us. Isn't it great to be back in person? Yes, it Joe, talk to us a little bit about Allegis group. So we work to find people jobs, and we help get 'em staffed and we help companies find people and we help It is You are the AI and MDM architect. on the AI side, and we build data science models and solutions I mean, I look at it as this, this wonderful sandbox. and libraries that the open source community around Python has contributed over the years. And implementing that calling to that store procedure is very easy. And, and eliminated all the other stuff that you had to do that now Snowflake's doing, am I correct? we produce to really give you an answer to that. Well, the reason I asked you is because you talk, we always talk about injecting data into apps, It gets a little better. And it's completely easier time to delivery to production because since to snowflake that you don't have to do now? Because I have to explain to my InfoSec we do, It has to be verified. Those processes are in place to help all of us stay protected. It's the checklist. That's all it is. And that's, that's the real advantage because we can do things faster. I don't need an exact metric, but when you say faster talking 10% faster, I wish I had that for you, but I really don't have I mean, if Has a business impact. So we can then, you know, look at the code sooner. So is it fair to say that as a result, you can do more. We be able do more well, and it will enable more of our people because they're used to working What are some of the benefits that having snow park of that data down in, down in the snowflake, the team that did that, those analytical dashboards, So you're saying you're doing the visualization in GCP. It's just some dashboarding. You won't even give for. It's just some D boardings of numbers and percentages and things like that. gonna have to rewrite differently. And they'll actually be, they'll be displayed through Tableau, which is our enterprise And then when you operationalize it it'll go. And because all the data's there And it's not a lot of data. so some of the data science that we do inside of snowflake produces a set of results and We look forward to hearing what comes when it's GA Thank you for our guests and Dave ante.
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Samuel Niemi, Dell Technologies | CUBE Conversation
(upbeat music) >> Okay, welcome to the special CUBE conversation. I'm John Furrier, host of theCUBE. We're here talking about the evolving capabilities of VCF on VxRail. VCF being VMware Cloud Foundation. as VxRail from Dell Technologies. Samuel Niemi is their Product Manager of VCF on VxRail. He's got the keys to the kingdom. He is going to give us the update on what's going on, obviously with all the major IT operational conversations going on with cloud native, how to get the best excellence out of the organization as we come through the pandemic, big stuff happening. Welcome to theCUBE. >> Thank you, happy to be here. >> In June, you guys announced some major updates that's coming on to VMware Cloud Foundation on VxRail that would allow customers to extend their capabilities and their ability to innovate in the landscape and with external storage. Can you take us through what's new what's the situation and tell us what's happening? >> Yeah, absolutely. So, first off if you're, for those who might be watching who are not familiar with VCF on VxRail, VxRail is our hyperconverged infrastructure system that allows for massive data centers scaling at, from node to node to node. VCF on VxRail specifically is the VMware SDDC software suite that allows us to create a private cloud with VxRail deployments. So instead of saying, I want to manage this cluster and this cluster, and this cluster VCF allows us to manage VxRail clusters and deployments at a big scale. So VCF on VxRail, we've gone from in the last two and a half years or so that we have been available as a product we've gone from nothing to tens of thousands of nodes deployed across the world. And it has been a rollercoaster of a ride. And we're just thrilled with the success that we've had so far. >> And what's been new since the release in June but what's new? >> Absolutely. So, one thing that we've realized from a VxRail perspective is that, as we grow and as our data center and enterprise scale customers continue to grow their VCF on the VxRail environments VCF on VxRail has to evolve as well. And in June we announced an ability for VCF on VxRail to consume external storage. Now, hyper-converged means no storage, networking, network virtualization I should say and your server all in one box. External storage gives us the ability to utilize your existing Dell EMC storage arrays and use that data centric kind of storage deployment with your existing or net new VCF on VxRail deployments. It's really exciting stuff. And we're really looking forward to be able to even better provide solutions for our customers at that big enterprise scale. >> So a lot of change happening scale is a big word here, right? We're seeing scale, modern applications looking for environment. You talk about hybrid private cloud. I mean, essentially cloud operations is private cloud if you will. I got to ask you on this big product that you have VCF on VxRail, what are the drivers behind making this option viable for customers, what are they looking for? Why are they consuming it this way? What are the key aspects of drive in this force? >> Absolutely. So, what we found is that with vSAN which has been wildly successful on the VxRail, it's fantastic for general purpose workloads. And we don't see that changing. What we see is an ability for our customers to leverage the extreme speed of our PowerStore T, our PowerMax and our Unity XT storage arrays so that you can get that sub millisecond latency that you're used to out of those storage arrays and have the same benefits in say another workload domain of your existing vSAN deployment. Now, my favorite example of a use case for that is when you have sub millisecond latency, that's something like a PowerMax can provide. Let's say you're standing at the gas pump. It's cold, I'm here in Minnesota it was three degrees here yesterday. When I'm standing at the gas pump, swipe my card. I don't want to wait and wait and wait for that database kit. Put my card to go through I want it now. PowerMax and our PowerStore T, unity XT with those crazy low latencies, they allow our VCF on VxRail customers to not have to wait at the pump. So when our enterprise customers have those things deployed with that crazy low latency for database hits, you're not standing at the pump. You're not waiting awkwardly at the grocery store for your card to go through. You really get that extreme speed that those big storage arrays can provide. >> Yeah, so the weather in Minnesota, and so my brother lives in that area too. He was complaining about it on the family text, but this is an edge case, whether you're swiping your credit card on the pump, this latency discussion, the edge is really a key conversation because that's what you're, you're going to get cold waiting, but still you could be, key data store for say some equipment in a manufacturing operation, or on a farm or somewhere. So again, this brings up the whole edge. >> True. >> That an area is that the driver, one of the drivers, or is it also just in general the performance? >> You know I would say it depends on what you need out of your storage array. If you need that performance at the edge, VCF can deploy remote clusters in a metro distance within 50 milliseconds. So you can have your center and you can have your edges, you can put storage arrays behind those edges. You can have that kind of, speed from place to place, to place to place, or you can use traditional vSAN storage. So it really comes down to what your storage use case is. Maybe you have a need of the data replication that PowerMax can provide from one site to the other, and that's your backup for your edges. Those kinds of things can all be utilized with VCF on VxRail and remote clusters at the edge. >> What a similar customer use case? Can you just walk me through some examples of customers that you have and what they're interested in, what kind of advantages they're seeing with the capability? >> Certainly. So we have a number of customers who have high level of data resiliency requirements that we have that 99 point lots of nines resiliency that the PowerMax, and it's forebears, VMX have provided for 20 something years now, those customers say at our financial institutions where they have to have massive levels of resiliency. We have customers who frankly have separate buying cycles, where they buy their compute one year, and then maybe two years later, that's when their storage comes up for renewal. So those customers are able to leverage both VCF on VxRail and their external storage. I'm not going to drop customer names. I've got a couple that come to mind, but I'll say in the financial institution and in healthcare especially is where we see. >> What problem are they solving? You don't have to name names because I know it's probably the company, everything, but you know what all the reference stuff, but what's the anecdotal, what's the main problem, let's say kind of the use cases that jump out and people, if people are watching might think that they should be using this. What signals and signs should they be looking for? >> Absolutely. I would say first off data resiliency, and I'm just in love with PowerMax. So that's the first thing that jumps to mind. I'm extreme performance, whether it's databases or having a need to get data out to their customers as quickly as possible. Replication comes to mind. Those are the big three. And then of course, where you maybe need a little bit of compute and a lot of storage are dynamic nodes and VCF on VxRail means that we can sell our nodes without any storage. And that really gives us an ability to just say, I need a lot of compute, I need a little compute, whatever it might be, I'm going to scale my nodes and my storage independently of one another. >> Where can people get more information to find out? >> Sure, absolutely. So for more information, you can always go to dell.com. You can reach out to your sales team and talk to your VMware sales team as well, who are well-versed in VCF on VxRail deployments, but we're always here dell.com and we're always just an email away. >> So while I've got your here, say, I want to ask you about this notion of simplifying the IT operational experience. >> Sure. >> In your view, as you look out on the horizon from your perspective, being the product leader on this area, what's on the mind of the customer. What's the psychology out there? What's some of the environmental conditions that they're facing (indistinct) their landscape. Is it do more with less, the classic cliche? Is it actually a replatformin, is it refactoring? Is it application developers? what's some of the big drivers there in terms of the customers that you're seeing? >> So as a customer today, I have so many options for where to put my data and where to put my VMs and my development. I want to look at what is the best route for my business? Is it a hybrid cloud offering? And if yes, what's the easiest way to manage that because at the end of the day, if I'm spending money on maintenance spending money on staff who are not accelerating the business, but just keeping the thing going, what's the best way to do that? And VCF on VxRail today really allows our customers to deploy a private or a hybrid cloud rather, and maintain the entire thing through one interface. That interface being SDDC Manager. When we look at the benefits of it, VCF for on VxRail today provides Tanzu. So for customers who need to have a development platform in their hybrid cloud Tanzu is that the easy option or the easy answer for that. So, it is a big answer. What's driving this, lots of things, but really it's data center modernization. It's moving from a traditional servers with virtual machines on them into the hybrid cloud. >> Yeah, you were missing resilience here on the data. I think that's awesome because I mean, at the end of the day it's data driven. Everyone wants more data. Database has been around for a while. So making that go faster is really critical. Awesome, awesome conversation. And now on the VCF on VxRail, what's the bottom line, if you had to summarize the evolution capabilities that are coming on, they're evolving, you're the Product Manager, you got the keys to the kingdom, what's next, what's happening? >> If I'm looking at VCF and what's next and what's on the way, really lifecycle management. So, when our customers talk about what it looks like to lifecycle their systems without VCF on VxRail and the complexity of doing that without VCF it's lifecycle management is the reason for being. We look at the, from everything we lifecycle from the hardware of the VxRail nodes, including disc firmware, HPAs, NIC drivers, etc to the VCF SDDC software suite, all of those components they're in vSphere, VCenter ESXi. I'm going through the checklist in my head here. The V realized components, getting all of that lifecycle to a good continuous revalidated state is really, really tough. And then your add storage, that's one more thing. So I want to be able to just have a single click that will go through LCM my entire hybrid cloud environment from hardware to software stack, so that I can manage that external storage that I just added to my system without adding more pain. So really with VCF on VxRail, it's the only jointly engineered solution from an HCI vendor like VxRail and VMware to deliver that single click soup to nuts hardware to software suite LCM. LCM is the name of the game. And we're going to continue to make that innovate on that and new ways that I can't even say yet. >> I can't wait to hear the innovation is a great model. Putting that out there, getting the environmental all scaled up. Sam Niemi, Product Manager, VCF VMware Cloud Foundation on VxRail with Dell Technologies. Thanks for coming on this CUBE conversation. >> Absolutely thanks, John. >> Okay, it's theCUBE here in Palo Alto. I'm John for your host, thanks for watching. (upbeat music)
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Nick Barcet, Red Hat | KubeCon + CloudNativeCon NA 2021
(bright music) >> Welcome to this Kube Conversation. I'm Dave Nicholson. And today we have a very special guest from Red Hat, Nick Barcet. Nick is the Senior Director of Technology, Technology Strategy at Red Hat. Nick, welcome back to theCUBE. >> Thank you. It's always a pleasure to be visiting you here virtually. >> It's fantastic to have you here. I see a new office surroundings at Red Hat. Have they taken a kind of a nautical theme at the office there? Where are you joining us from? >> I'm joining from my boat now, I've been living on my boat for the past few years, and that's where you'll find me most of the time. >> So would you consider your boat to be on the Edge? >> It's certainly one form of Edge. You know, there are multiple forms of Edge and a boat is one of those forms. >> Let's talk about Edge now. We're having this conversation in anticipation of KubeCon CloudNativeCon that's coming up North America 2021, coming up in Los Angeles. Let's talk about specifically the Edge, where the Edge, Edge computing and Kubernetes come together from a Red Hat perspective. Walk us through that, talk about some of the challenges that people are having at the Edge, why Kubernetes is something that would be considered at the edge. Walk us through that. >> Let's start from the premises that people have been doing stuff at the Edge for ages. I mean, nobody has been waiting for Kubernetes or any other technology to start implementing some form of computing that is happening in their stores, in their factories, wherever. What's really new today is when we talk about Edge computing, it's reusing the same technology we've been using to deploy inside of the data center and expand that all the way to the Edge. And that's what, from my perspective, constituents, Edge computing or the revolution it bring. So that means that the same GitOps, DevSecOps methodology that we were using into that center are now expandable all the way to those devices that leaves in where locations and that we can reuse the same methodology, the same tooling, and that includes Kubernetes. And all the efforts we've been doing over the past couple of years has been to make Kubernetes even more accessible for the various Edge typologies that we are encountering when discussing with our customer that have Edge projects. >> So typically when we think of a Kubernetes environment, you're talking about containers that are contained in pods, that live on physical clusters, despite all of the talk of a no-code and serverless, we still live in a world where applications and microservices run on physical servers. Are there practical limitations in terms of just how small you can scale Kubernetes? How far, how close to the Edge can you get with the Kubernetes deployment? >> So in theory, there is really no limit. As the smallest devices are always bigger than Kubernetes itself. But the reality is you never use just Kubernetes, you use Kubernetes with a series of other projects that makes it complete, or for example, stuff that is going to be reporting telemetry, components that are going to help you automatically scale, et cetera. And the further you go into the Edge, the less of these competence you can afford. So you have to make trade-offs when you reduce the size of the device. Today, what Red Hat offers, is really concentrated to where we can deliver a full OpenShift experience. So the smallest environments on which we would recommend to run OpenShift at the Edge is a single node is roughly 24 gigabytes of RAM, which is you could buy it, sorry, which is already a relatively big Edge device. And when you go a step lower then, that's where we would recommend using a standard rail for Edge configuration or something similar. Not Kubernetes anymore. >> So you said single node, are you let's double click on that for a second. Is that a single physical node that is abstracted in a way to create some level of logical redundancy? When you say single node, walk us through that. We've got containers that are in pods, so what are we talking about? >> You have, based on your requirements, you can have different way of addressing your compute need at the Edge. You can have those smallest of clusters. And this would be three nodes that are delivered, with is the control plane and the worker nodes integrated into one. When you want to go a step further, you could use worker nodes that are controlled remotely via a central control plane that is at a central site. And when you want to go, even one step further deploy Kubernetes on a very small machine, but that remains fully functional even if disconnected that's when you would use the thing that is not anymore a cluster, which is a single note, Kubernetes where you still have access to the full Kubernetes API, regardless of the connectivity of your site, whether it's active or not, whether you're at sea or in the air or not. And that's where we still offer some form of software high vulnerability, because Kubernetes, even on a single node, it'll still detect if a container dies and restarted and provide similar functionality like this, but it won't provide hardware availability since we are a single node. >> And that makes sense. Yeah, that makes, yeah, it makes perfect sense. And I would suggest that we refer to that as a single node cluster, just because we like to mix it up with terminology in our business and sometimes confuse people with it. >> Technically, that was the choice we made, actually. You like to call it a cluster because it's not a cluster >> Exactly. No, I appreciate that. Absolutely. So what's be explicit about what the trade-offs are there. Let's say that I'm thinking of deploying something at the Edge, and I'm going use Kubernetes to orchestrate my container environment and pretend for a moment that space and cost aren't huge limiting factors. I could put a three node cluster in, but the idea of putting in a single node is very, it's attractive. Where does, where's the line drawn in terms of what you would recommend from, you know, what are the trade offs? What am I losing, going to the single node cluster? See I just called that. >> Well, in a nutshell, you're losing hardware high availability. Meaning if one of your server fails since you only have one server, you lose everything. And there is no way around that. That's the biggest trade-off. Then you have also a trade-off on the memory used by the control plane, which you won't be able to use to do something else. So if I have a site with excellent connectivity and the biggest loss of connectivity might be counted in hours, maybe a remote worker use a better solution because this way, I have a single central-side that carries my control plane, and I can use all the RAM and all the CPU's on my local site to deploy my workloads, not to carries a control plane. To give you an example of these trade-off in the telco space, for example, if you're deploying an antenna in a city, you have plenty of antennas covering that city. And therefore, the loss of one antenna is not a big deal. So in that case, you will be tempted to use a remote worker because you will be maximizing your use of the RAM on the sites for the workload, which is let's have people establish communication using their phones. But now, we take another antenna that we are getting to locate in a very remote location. There, if this antenna fail, everybody fails. There's nobody that is able to make calls, even emergency vehicles cannot discuss together very often. So in that case, it's a lot better to have an autonomous deployment, something where the control plane and the workload itself are being run in one box. And this one box in fact can be duplicated. There could be a another box that is either seating in a truck in case of emergency or off, but on the antenna site, so that in case of a major failure, you have a possibility to re to restore it. So it really depends on what's your sets of constraints in terms of availability in SIM of efficiency of your RAM use is going to be that it's going to make you choose between one or the other of the deployment models. >> No, that's a great example. And so it sounds like it's not a one size fits all world, obviously. Now, from the perspective of the marketplace, looking in at Red Hat, participating in this business, some think of Red Hat as the company that deployed Linux 20 years ago. Help us make that connection between Red Hat today and what you've been doing for the last 20 years and this topic of Edge computing, 'cause some people don't automatically think of Red Hat an Edge computing. I do, I think they should, (chuckles) but help us understand that. >> Yeah, obviously a lot of people consider that Red Hat is Red Hat, Linux, and that's it. The Red Hat Enterprise Linux is what we've been known since our beginnings 25 years ago, and what has made our early success. But we consider ourselves more of an infrastructure company. We have been offering for the past 20 years, the various component that you need to deploy server, run and manage your workloads across data centers and make sure that you can store your data, and that you can automate your operations on top of this infrastructure. So we really consider ourselves much more of a company that offers everything that enables you to run your servers and run your workloads on top of your server. And that includes a tool to do virtualization, that includes tool to do continuous deployment of containers. And that's where Kubernetes entered in play about 10 years ago. Well, first it was OPAs that then became Kubernetes and the OpenShift offering that we have today. >> Yeah. Thanks for that. So I have, I've got a final question for you. It's a little bit off topic, but it's related, this is in the category of Nick predicts. So when does Nick predict that we will get to a point where we tip beyond the 50/50 point cloud versus on-premises IT spending, if you accept today that we're still in the neighborhood of 75 to 80% on-premises. When will we hit the 50/50 mark? I'm not asking you for the hundred percent cloud date, but give us a date, you give us a month and a year for 50/50. >> Given the progression of cloud, if there was no Edge, we could said two to three years from now, we would be at this 50/50 mark. But the funny thing is that at the same time, as the cloud progresses, people start realizing that they have needs that needs to be solved locally. And this is why we are deploying Edge-based solution, solution which reliably can provide answers, regardless of the connectivity to the cloud, regardless of the bandwidth. There are things that I would never want to do, like feeding a size on feeds from 4K cameras, into my cloud environment that won't scale, I won't have the bandwidth to do so. And therefore, maybe the answer to your question is, it's going to be asymptotic, and it's almost impossible to predict. >> So that is a much better answer than giving me an exact date and time, because (chuckles) because it reveals exactly the reality that we're living in. Again, there is, you know, it's fit for function. It's not cloud for cloud's sake, compute resources, data, resources have a place that they naturally belong oftentimes. And oftentimes that is on the Edge, whether it's on the edge of the edge of the world in a sailboat or out in a single server, not node, or I keep wanting to single node cluster, it's killing me. I dunno why, I think it's so funny, but a single node implementation of OpenShift where you can run Kubernetes on the Edge, it's a fascinating subject. Anything else that you want to share with us that we didn't get? >> I think one aspect that we never talk enough is how do you manage at the scale of Edge? Because even though each Edge site is very small, you can have thousands, even hundreds of thousands of these single node something that are running all over the place. And I think that what you're seeing in advent cluster management for Kubernetes, and particularly the 2.4 version that we are going to be announcing this week and actually releasing in November is I think a pretty good answer to that problem on how do I deploy with zero touch these devices? How do I update them, upgrade them? How do I deploy the workloads on top of that? How do I ensure to have the right tooling to deploy that at the scale? And we've done the testing now of ACM with up to 2,000 clusters, connected to a single ACMs. And in the future, we are planning on building federation of those, which really gives us the possibility to provide the tooling needed to manage at its scale. >> Excellent. Excellent. Yeah. That's whenever we start talking about anything in the realm of containerization and Kubernetes scale starts to become an issue. It's no longer a question of a human being managing 10 servers and 50 applications. We start talking about tens of thousands and hundreds of thousands of instances where it's beyond human scale. So that's obviously something that's very, very important. Well, Nick, I want to thank you for becoming a Kube veteran once again. Thanks for joining this Kube Conversation from Dave Nicholson, this has been a Kube Conversation in anticipation of KubeCon and CloudNativeCon North America 2021. Thanks for tuning in. (bright music)
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Nick is the Senior Director of Technology, to be visiting you here virtually. It's fantastic to have you here. find me most of the time. and a boat is one of those forms. Let's talk about specifically the Edge, So that means that the same How far, how close to the Edge can you get And the further you go into the Edge, on that for a second. and the worker nodes And that makes sense. Technically, that was the but the idea of putting in a single node So in that case, you will be of the marketplace, and that you can automate your operations in the neighborhood of that at the same time, And oftentimes that is on the Edge, that are running all over the place. in the realm of containerization
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Jagjit Dhaliwal, UiPath & Jim Petrassi, Blue Cross Blue Shield, IL, TX, MT, OK, & NM | UiPath FORWAR
>>from the bellagio Hotel >>in Las Vegas. >>It's the >>cube covering >>Ui Path forward. >>Four brought to >>you by Ui Path. >>Welcome back to Las Vegas. The cube is here. We've been here for two days covering Ui Path Forward for lisa martin here with David Monty. We've talked about automation and many industries. Now this segment is going to focus on automation and healthcare. We've got two guests joining us Jim Petrosea Cto of Blue Cross, Blue Shield and Gadget. Dhaliwal. The global C. I. O. Industry lead at you. I pass guys welcome to the program. Thank you. So let's start unpacking from the CTO level and the ceo level the agenda for automation. Jim let's start with you. What does that look like >>for us. It's actually pretty strategic and part of as we think about digital and what digital transformation means, it actually plays a pretty key role. Um There are a lot of processes that can be very manual within a big organization like Blue cross and Blue shield and to be able to streamline that and take away kind of what I would call the mundane work. Right? The the you know, going through a spreadsheet and then typing it into the screen, there are a lot of processes like that that are legacy. But what if you could take that away um and actually create a better work experience for the people that work there right? And and focus on higher value type uh type things and it's really key. And it really It goes down to our our business folks right? There are a lot of things we can drive with automation. We started a program um in 2019. Um that's been quite successful. We now have 250 box, we measure what we call annualized efficiency gains. So how much efficiency are we getting by these bots? So the bots are doing um this repetitive work that people would do. Um And what we're finding is, you know, we've got about $11 million in any wise efficiency gain through the process and we're just getting started. Um But we're all we're not stopping there too though, we're enabling citizen developers. So we're saying, hey business, if you want to automate, you know, parts of your job, we're gonna help you do that. So we've got about 60 people that were training. Um We run bad Ethan's where they come together and they actually create bots uh And it's really really creating some some impact and buzz in our business >>anywhere from your lens, where does automation fit within the C. I. O. S. Agenda? And how do you work together in unison with the C. T. O. To help roll this out across the enterprise? >>Yeah, no, definitely. And in fact as a part of introduction, I can actually share that. How I'm wearing a Ceo had within your path since I'm just joining join path and I'm actually now helping a client ceos in their automation strategy but I was a deputy ceo in my prior role at L. A. County where actually I ran the automation strategy. So if we look at from our organization perspective B complex as L. A County which is such a Federated organization. From a Ceo perspective, the way we look at the strategy is it's always driven by the business goals of the city or a county and we typically drive into three different areas. One is how we can transform our operational processes so that we can save the tax dollars. It's all about doing more with the less dollars. And then second is about how we can transform our residents experience because end of the day it is all about how we can improve the quality of life for our residents. So we've got 10 million people for L. A. County, the largest populous county in us. So it was an uphill task to serve that such a diverse population need and that the third area is about how to transform the new business models because as we are moving away from a government centric approach to the residents centric approach, you really need to come up with a new digital solutions. And Ceo is in the center of all these three elements when you look at it. So it's a very appear to us to keep keep improving your efficiency and then at a time keep adding the new digital solutions and that's where automation strategy is kind of a horizontal strategy which enables all these components. So what I hear from >>that is alignment with the business. Yeah. Right. Change management. Absolutely. That's like really fundamental and then see IOS this this agent of transformation uh you can see or she has a horizontal purview across the organization now now jim the cto role is the automation at blue cross blue shield lead by you or you there to make sure the technology plugs into your enterprise architecture. What's your shoulder? >>You know? Uh my my role is really to drive uh what I'll call technology enabled business change. Right. So I actually uh started our our automation journey uh at hc sc and I did that by partnering with our business. Um There was actually a lot of buzz around automation and there were actually some small pockets of it, none of it was enterprise scale. Um Right. And we really wanted to go big in this and and working with the business sponsors, they saw value in it. Um and we've you know, we've generated um a lot of uh efficiency, better quality of work because of it but but I very closely had a partner with our business, we have a committee that is lead of business folks that I facilitate. So I view my role as an enabler, um we have to communicate the change management pieces is huge. Uh the education just having a common vernacular on what is automation mean, Right, because everybody interpreted it differently um and then being able to do it at an enterprise scale is quite challenging. Um You know, I I really enjoyed um one of the key notes, I don't know if you had a chance to see shankar by Duncan from the hidden brain, right? But he talked a lot about the brain aspect and how do you get people to change? And and that's a large part of it. There's a lot about technology, but there's really a lot about being a change agent um and and really working very closely with your business, >>how does one measure? I'm hearing a lot time saved. Our saved. How does one measure that and quantify the dollar impact, which by the way, I'm on record as saying the soft dollars are way bigger. And but when you're talking to the, you know, the bottom line CFO and it's all about, you know, the cash flow, whatever is, how do you measure that? >>I can take it. So we, what we do is as we define these use cases right? We we go through an actual structure product process where we we gather them. Um we then rate them and we actually prioritize them based on those that are going to have the greatest impact. Um and we can tell based on, you know, what is the manual effort today. So we understand there are X number of people that do this X number of days and we think this body can take that some load off of them. Right? Um So we we go in with the business case. Um And then the Ui Path platform actually allows us to measure well, how much is that pot running? Right. So we can actually sit there and say, well we wanted that thing to run 10 hours a day and it did and it's generated this kind of efficiency because otherwise the human would have had to do that work. >>So the business case is kind of redeploying >>human. It really is is really maximizing human capital and make and and you know really using because the bots do repetitive stuff really well. They don't do higher level thinking and and we don't view it as replacing people, we view it as augmenting and actually making them more efficient and more effective at what, how do you get the dollars out of that? Well, a couple of ways. Right. And so one of the things we've we've done is we we create and measure the efficiency our business users and financed by the way is one of our bigger ones. And the CFO is one of the sponsors of the program, um can decide how to reinvest it in a lot of cases it is actually cost avoidance as we grow, literally being able to grow without adding staff. I mean that's very measurable. Um in some cases it is actually taking, you know cost out um in in certain cases, but a lot of times that's just through attrition, right? You don't back fill positions, you let it happen naturally. Um and and then there's just things that happen to your business that you have to respond to give you a great example, state of texas, um passes what's the equivalent of the no surprise attack. But they did it there before the federal government did it. Um but it requires a lot of processes to be put in place, because now you have providers and payers having to deal with disputes, right? It actually generates a boatload of work. And we thought there might be, you know, 5000 of these in the first year, where there were 21,000 in the first year. And so far this year we're doubling that amount, right. We were able to use automation to respond to that without having to add a bunch of stuff. If we had to add staff for that, it would have literally been, you know, maybe hundreds of people, right? And but now, you know, there's, you can clearly put a value on it and it's millions of dollars a year, that we would have otherwise had to expect. >>The reason I'm harping on this lease is because I've been through a lot of cycles, as you know, and after the dot com boom, the the cost avoidance meant not writing the check to the software company, right? And that's what nick Carr wrote this, i. T matter. And then, and then, you know, post the financial crisis, we've entered uh a decade plus of awareness on the impact of technology. And I wonder if it's, I think this, I think this the cycle is changing I think. And I wonder if you have an opinion here where people, I think organizations are going to look at Technology completely different than they did like in the early 2000s when it was just easy to cut. >>No, I think the other point I will add to it. I agree with the gym. So we typically look at our away but it doesn't always have to be the cost. Right? If you look from the outcomes of the value, there are other measures also right? If you look at the how automation was able to help in the Covid generate. It was never about costs at that time. It was about a human lives. So you always may not be able to quantify it what you look at. Okay. What how are we maximizing the value or what kind of situations where we are and where we may not even have a human power to do that work. And we are running against the time. It could be the compliance needs. I'll give example of our covid use case which was pretty big success uh within L. A. County we deployed bots for the covid contact tracing program. So we were actually interviewing all the people who were testing positive so that we actually can keep track of them and then bring back that data within our HR so that our criminologists actually can look at the trends and see how we are doing as a county as compared to other counties and nationally. And we were in the peak, we were interviewing about 5000 people a day And we had to process that data manually into our nature and we deployed 15 members to do that. And they were doing like about 600 interviews a day. So every day we had a backlog of 2500 interviews. So it is not about a cost saving or a dollar value here because nobody planned for these unplanned events and now we don't have a time and money to find more data entry operators and parts were able to actually clear up all the backlog. So the value which we were able to bring it is way beyond the cost element. >>I I believe that 100% and I've been fighting this battle for a long time and it's easier to fight now because we're in this economic cycle even despite the pandemic, but I think it can be quantified. I honestly believe it can be tied to the income statement or in the case of a public sector, it could be tied to the budget and the mission how that budget supports the mission of the company. But I really believe it. And and I've always said that those soft factors are dwarf the cost savings, but sometimes, you know, sometimes the CFO doesn't listen, you know, because he or she has to cut. I think automation could change that >>for public sector. We look at how we can do more about it. So it's because we don't look at bottom line, it's about the tax dollars, we have limited dollars, but how we can maximize the value which we are giving to residents, it is not about a profit for us. We look at the different lens when it comes to the commercial >>Side, it's similar for us. So as a as a health care pair, because we're a mutual right? Our members and we have 17 million of them are really the folks that own the company and we're very purpose driven. Our our purpose is to do everything in our power to stand by members in sickness and in health. So how do you get the highest quality, cost effective health care for them? So if automation allows you to be more effective and actually keep that cost down, that means you can cover more people and provide higher quality care to our members. So that's really the driver for mission driven, >>I was gonna ask you as a member as one of your 17 million members, what are some of the ways in which automation is benefiting me? >>Um you know, a number of different ways. First off, you know, um it lowers our administrative costs, right? So that means we can actually lower our rights as as we go out and and and work with folks? That's probably the the the the bottom line impact, but we're also automating processes uh to to make it easier for the member. Right? Uh the example I used earlier was the equivalent of no surprises. Right. How do we take the member out of the middle of this dispute between, you know, out of network providers and the payer and just make it go away. Right, and we take care of it. Um but that that creates potentially administrative burden on our side, but we want to keep their costs down and we do it efficiently using it. So there's a number of use cases that we've we've done across, you know, different parts of our business. We automate a lot of our customer service, right? When you call um there's bots in the background that are helping that that agent do their job. And what that means is you're on the show, you're on the phone a lot shorter of a period of time. And that agent can be more concise and more accurate in answering your question. >>So your employee experience is dramatically improved, as is the member experience? >>Yes, they go hand in hand. They do go hand, unhappy members means unhappy employees, 100% >>mentioned scale before, you said you can't scale in this particular, the departmental pockets. Talk about scale a little bit. I'm curious as to how important cloud is to scale. Is it not matter. Can you scale without cloud? What are the other dimensions of scale? >>Well, you know, especially with my CTO had, we're we're pushing very heavily to cloud. We view ourselves as a cloud first. We want to do things in a cloud versus our own data centers, partially because of the scale that it gives us. But because we're healthcare, we have to do it very securely. So. We are very meticulous about guarding our data, how we encrypt information um, not only in our data center but in the cloud and controlling the keys and having all the controls in place. You know, the C. So and I are probably the best friends right now in the company because we have to do it together and you have to take that that security mind set up front. Right cloud first. Put security first with it. Um, so we're moving what we can to the cloud because we think it's just going to give us better scale as we grow and better economics overall, >>Any thoughts on that? I think a similar thoughts but if we look from L. A. county because of the sheer volume itself because the data which we are talking about. We had 40 departments within the county. Each department is serving a different business purpose for the resident beit voting or B justice or being social services and all and the amount of data which we are generating for 10 million residents and the amount of duplicate asi which it comes out because it's a very government centering model. You have a different systems and they may not be talking to each other. The amount of diplomacy and identity delicacy which we are creating and as we are enabling the interoperability between these functions to give us seamless experience keeping security in mind so fully agree on that because the end of the day we have to ensure that customer guarantee but it's a sheer volume that as and when we are adding these data sets and the patient's data as well as the residents data and now we have started adding a machine data because we have deployed so many IOT solutions so the data which is coming from those machines, the logs and all its exponential so that's where the scale comes into picture and how we can ensure that we are future ready for the upscale which we need and that's where cloud ability definitely helps a lot. >>What do you mean by future ready? >>So if you look at from a future smart city or a smart community perspective, imagine when machines are everywhere machines and IOT solutions are deployed, beat even healthcare, your bad information, you're even patient information, everything is interconnected and amount of data which is getting generated in that your automobile they're going to start talking to entertainment or we have to potentially track a single resident might be going same person going to the justice or maybe same person might be having a mental health issues, A same person might be looking for a social services, how we're going to connect those dots and what all systems they are touching. So all that interconnections needs to happen. So that exponential increase of data is a future readiness, which I'm talking about. Are we future ready from a technology perspective? Are we future ready from the other ecosystem perspective and how and how we're gonna manage those situations? Uh, so those are the things which we >>look at it and it's a it's a multiplier to, right? We all have this influx of information and you need to figure out what to do with it. Right. This is where artificial intelligence, machine learning is so important. But you also have interoperability standards that are coming. So now we're we have this massive data that each of our organizations have. But now you have interoperability which is a good thing for the member saying now I need to be able to share that data. Yeah, I wanted to ask you about >>that because a lot of changes in health care, um, are meaningful use. You have to show that to get paid but the standards weren't mature. Right? And so now that's changing what role does automation play in facilitating those standards. >>So, you know, we're big, big supporters of the fire standard that's out there um to in order to be able to support the standards and and create a P. I. S. And and pull together the information. What what will happen sometimes in the background is there's actually um artificial intelligence, machine learning models that create algorithms right? The output of that though often has to be active. Now a person can do something with that information or a vodka. Right? So when you start taking the ideal of artificial intelligence and now you have a robotic process that can use that to pull together the information and assimilated in a way to make it higher quality. But now it's available. It's kind of in the background. You don't see it but it's there helping. >>What are some of the things that you see? I know we're out of time but I just have a couple more questions. Some of the things that you see here we are you I path forward for we're in person. This is a bold company that's growing very quickly. Some of the announcements that were made, what are what are some of your reaction to that? And how do you see it helping move blue crush blue shield forward even >>faster. Well you know a lot of the announcements in terms of some of the features that that they've added around their robotics processing are great right? The fact that they're in the cloud and and some of the capabilities and and and better ability to to support that the process mining is key. Right. In order for abouts to be effective, you have to understand your process and you just don't want to necessarily automate the bad practices. Right? So you want to take a look at those processes to figure out how you can automate things smartly. Um and some of their capabilities around that are very interesting. We're going to explore that quite a bit but but I think they're the ambition here is beyond robotics. Right. It's actually creating um you know, applications that actually are using bots in the background which is very intriguing and has a lot of potential potentially to drive even more digital transformation. This can really affect all of our workers and allow us to take digital solutions out to the market a lot faster >>and to see what was going to ask you, you are here for four weeks at UI Path, you got to meet a lot of your colleagues, which is great. But what about this company attracted you to leave your former role and come over here to the technology vendor side. >>Well, I think I was able to achieve the similar role within L. A. County, able to establish the automation practice and achieve the maturity, able to stand up things and I feel that this is the same practitioner activity which I can actually take it back to the other clients ceos because of one thing which I really like about your hypothesis. RP is just a small component of it. I really want to change that mindset that we have to start looking ui path as an end to end full automation enterprise solution and it is not only the business automation, it's the idea automation and it's a plus combination and whether we are developing a new industry solutions with our partners to help the different industry segments and we actually helping Ceo in the center of it because Ceo is the one who is driving the automation, enabling the business automation and actually managing the automation ceo and the governess. So CEO is in left and center of it and my role is to ensure that I actually help those Ceos to make successful and get that maturity and you will path as a platform is giving that ability of length and breath and that's what is really fascinating me and I'm really looking forward that how that spectrum is changing that we are getting matured in a process mining area and how we are expanding our horizons to look at the whole automation suit, not just the R. P. Product and that's something which I'm really looking forward and seeing that how we're going to continue expanding other magic quadrants and we're actually going to give the seamless experience so the client doesn't have to worry about okay for this, I have to pick this and further, I have to pick something else >>that's seamless experience is absolutely table stakes these days. Guys, we're out of time. But thank you so much for joining. David me, talking about automation and health care. Your recommendations for best practices, how to go about doing that and and the change management piece. That's a critical piece. We appreciate your time. >>Thanks for having. Thank >>you. Our pleasure for day Volonte. I'm lisa martin live in las Vegas. The cubes coverage of you a path forward for continues next. Mhm. Mhm mm.
SUMMARY :
Now this segment is going to focus on automation and healthcare. So we're saying, hey business, if you want to automate, you know, parts of your job, And how do you work together in unison with the C. T. And Ceo is in the center of all these three elements when you look at it. uh you can see or she has a horizontal purview across the organization now the brain aspect and how do you get people to change? you know, the cash flow, whatever is, how do you measure that? Um and we can tell based on, you know, what is the manual effort today. of processes to be put in place, because now you have providers and payers having to deal with disputes, And then, and then, you know, post the financial crisis, we've entered uh a not be able to quantify it what you look at. sometimes the CFO doesn't listen, you know, because he or she has to cut. don't look at bottom line, it's about the tax dollars, we have limited dollars, So how do you get the highest quality, cost effective health care for them? out of the middle of this dispute between, you know, out of network providers and the payer and Yes, they go hand in hand. mentioned scale before, you said you can't scale in this particular, So and I are probably the best friends right now in the company because we have to do it together mind so fully agree on that because the end of the day we have to ensure that customer guarantee but they're going to start talking to entertainment or we have to potentially track a single resident We all have this influx of information and you need You have to show that to get paid but the standards weren't mature. So when you start taking the ideal of artificial intelligence and now you have a Some of the things that you see here we are you I path forward for we're in person. In order for abouts to be effective, you have to understand your process and you just But what about this company attracted you to leave that we are getting matured in a process mining area and how we are expanding our horizons to But thank you so much for joining. Thanks for having. The cubes coverage of you a path forward for continues next.
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Mai Lan Tomsen Bukovec | AWS Storage Day 2021
(pensive music) >> Thank you, Jenna, it's great to see you guys and thank you for watching theCUBE's continuous coverage of AWS Storage Day. We're here at The Spheres, it's amazing venue. My name is Dave Vellante. I'm here with Mai-Lan Tomsen Bukovec who's Vice President of Block and Object Storage. Mai-Lan, always a pleasure to see you. Thanks for coming on. >> Nice to see you, Dave. >> It's pretty crazy, you know, this is kind of a hybrid event. We were in Barcelona a while ago, big hybrid event. And now it's, you know, it's hard to tell. It's almost like day-to-day what's happening with COVID and some things are permanent. I think a lot of things are becoming permanent. What are you seeing out there in terms of when you talk to customers, how are they thinking about their business, building resiliency and agility into their business in the context of COVID and beyond? >> Well, Dave, I think what we've learned today is that this is a new normal. These fluctuations that companies are having and supply and demand, in all industries all over the world. That's the new normal. And that has what, is what has driven so much more adoption of cloud in the last 12 to 18 months. And we're going to continue to see that rapid migration to the cloud because companies now know that in the course of days and months, you're, the whole world of your expectations of where your business is going and where, what your customers are going to do, that can change. And that can change not just for a year, but maybe longer than that. That's the new normal. And I think companies are realizing it and our AWS customers are seeing how important it is to accelerate moving everything to the cloud, to continue to adapt to this new normal. >> So storage historically has been, I'm going to drop a box off at the loading dock and, you know, have a nice day. And then maybe the services team is involved in, in a more intimate way, but you're involved every day. So I'm curious as to what that permanence, that new normal, some people call it the new abnormal, but it's the new normal now, what does that mean for storage? >> Dave, in the course of us sitting here over the next few minutes, we're going to have dozens of deployments go out all across our AWS storage services. That means our customers that are using our file services, our transfer services, block and object services, they're all getting improvements as we sit here and talk. That is such a fundamentally different model than the one that you talked about, which is the appliance gets dropped off at the loading dock. It takes a couple months for it to get scheduled for setup and then you have to do data migration to get the data on the new appliance. Meanwhile, we're sitting here and customers storage is just improving, under the hood and in major announcements, like what we're doing today. >> So take us through the sort of, let's go back, 'cause I remember vividly when, when S3 was announced that launched this cloud era and people would, you know, they would do a lot of experimentation of, we were storing, you know, maybe gigabytes, maybe even some terabytes back then. And, and that's evolved. What are you seeing in terms of how people are using data? What are the patterns that you're seeing today? How is that different than maybe 10 years ago? >> I think what's really unique about AWS is that we are the only provider that has been operating at scale for 15 years. And what that means is that we have customers of all sizes, terabytes, petabytes, exabytes, that are running their storage on AWS and running their applications using that storage. And so we have this really unique position of being able to observe and work with customers to develop what they need for storage. And it really breaks down to three main patterns. The first one is what I call the crown jewels, the crown jewels in the cloud. And that pattern is adopted by customers who are looking at the core mission of their business and they're saying to themselves, I actually can't scale this core mission on on-premises. And they're choosing to go to the cloud on the most important thing that their business does because they must, they have to. And so, a great example of that is FINRA, the regulatory body of the US stock exchanges, where, you know, a number of years ago, they took a look at all the data silos that were popping up across their data centers. They were looking at the rate of stock transactions going up and they're saying, we just can't keep up. Not if we want to follow the mission of being the watchdog for consumers, for transactions, for stock transactions. And so they moved that crown jewel of their application to AWS. And what's really interesting Dave, is, as you know, 'cause you've talked to many different companies, it's not technology that stops people from moving to the cloud as quick as they want to, it's culture, it's people, it's processes, it's how businesses work. And when you move the crown jewels into the cloud, you are accelerating that cultural change and that's certainly what FINRA saw. Second thing we see, is where a company will pick a few cloud pilots. We'll take a couple of applications, maybe one or a several across the organization and they'll move that as sort of a reference implementation to the cloud. And then the goal is to try to get the people who did that to generalize all the learning across the company. That is actually a really slow way to change culture. Because, as many of us know, in large organizations, you know, you have, you have some resistance to other organizations changing culture. And so that cloud pilot, while it seems like it would work, it seems logical, it's actually counter-productive to a lot of companies that want to move quickly to the cloud. And the third example is what I think of as new applications or cloud first, net new. And that pattern is where a company or a startup says all new technology initiatives are on the cloud. And we see that for companies like McDonald's, which has transformed their drive up experience by dynamically looking at location orders and providing recommendations. And we see it for the Digital Athlete, which is what the NFL has put together to dynamically take data sources and build these models that help them programmatically simulate risks to player health and put in place some ways to predict and prevent that. But those are the three patterns that we see so many customers falling into depending on what their business wants. >> I like that term, Digital Athlete, my business partner, John Furrier, coined the term tech athlete, you know, years ago on theCUBE. That third pattern seems to me, because you're right, you almost have to shock the system. If you just put your toe in the water, it's going to take too long. But it seems like that third pattern really actually de-risks it in a lot of cases, it's so it's said, people, who's going to argue, oh, the new stuff should be in the cloud. And so, that seems to me to be a very sensible way to approach that, that blocker, if you will, what are your thoughts on that? >> I think you're right, Dave. I think what it does is it allows a company to be able to see the ideas and the technology and the cultural change of cloud in different parts of the organization. And so rather than having a, one group that's supposed to generalize it across an organization, you get it decentralized and adopted by different groups and the culture change just goes faster. >> So you, you bring up decentralization and there's a, there's an emerging trend referred to as a data mesh. It was, it was coined, the term coined by Zhamak Dehghani, a very thought-provoking individual. And the concept is basically the, you know, data is decentralized, and yet we have this tendency to sort of shove it all into, you know, one box or one container, or you could say one cloud, well, the cloud is expanding, it's the cloud is, is decentralizing in many ways. So how do you see data mesh fitting in to those patterns? >> We have customers today that are taking the data mesh architectures and implementing them with AWS services. And Dave, I want to go back to the start of Amazon, when Amazon first began, we grew because the Amazon technologies were built in microservices. Fundamentally, a data mesh is about separation or abstraction of what individual components do. And so if I look at data mesh, really, you're talking about two things, you're talking about separating the data storage and the characteristics of data from the data services that interact and operate on that storage. And with data mesh, it's all about making sure that the businesses, the decentralized business model can work with that data. Now our AWS customers are putting their storage in a centralized place because it's easier to track, it's easier to view compliance and it's easier to predict growth and control costs. But, we started with building blocks and we deliberately built our storage services separate from our data services. So we have data services like Lake Formation and Glue. We have a number of these data services that our customers are using to build that customized data mesh on top of that centralized storage. So really, it's about at the end of the day, speed, it's about innovation. It's about making sure that you can decentralize and separate your data services from your storage so businesses can go faster. >> But that centralized storage is logically centralized. It might not be physically centralized, I mean, we put storage all over the world, >> Mai-Lan: That's correct. >> right? But, but we, to the developer, it looks like it's in one place. >> Mai-Lan: That's right. >> Right? And so, so that's not antithetical to the concept of a data mesh. In fact, it fits in perfectly to the point you were making. I wonder if we could talk a little bit about AWS's storage strategy and it started of course, with, with S3, and that was the focus for years and now of course EBS as well. But now we're seeing, we heard from Wayne this morning, the portfolio is expanding. The innovation is, is accelerating that flywheel that we always talk about. How would you characterize and how do you think about AWS's storage strategy per se? >> We are a dynamically and constantly evolving our AWS storage services based on what the application and the customer want. That is fundamentally what we do every day. We talked a little bit about those deployments that are happening right now, Dave. That is something, that idea of constant dynamic evolution just can't be replicated by on-premises where you buy a box and it sits in your data center for three or more years. And what's unique about us among the cloud services, is again that perspective of the 15 years where we are building applications in ways that are unique because we have more customers and we have more customers doing more things. So, you know, I've said this before. It's all about speed of innovation Dave, time and change wait for no one. And if you're a business and you're trying to transform your business and base it on a set of technologies that change rapidly, you have to use AWS services. Let's, I mean, if you look at some of the launches that we talk about today, and you think about S3's multi-region access points, that's a fundamental change for customers that want to store copies of their data in any number of different regions and get a 60% performance improvement by leveraging the technology that we've built up over, over time, leveraging the, the ability for us to route, to intelligently route a request across our network. That, and FSx for NetApp ONTAP, nobody else has these capabilities today. And it's because we are at the forefront of talking to different customers and that dynamic evolution of storage, that's the core of our strategy. >> So Andy Jassy used to say, oftentimes, AWS is misunderstood and you, you comfortable with that. So help me square this circle 'cause you talked about things you couldn't do on on-prem, and yet you mentioned the relationship with NetApp. You think, look at things like Outposts and Local Zones. So you're actually moving the cloud out to the edge, including on-prem data centers. So, so how do you think about hybrid in that context? >> For us, Dave, it always comes back to what the customer's asking for. And we were talking to customers and they were talking about their edge and what they wanted to do with it. We said, how are we going to help? And so if I just take S3 for Outposts, as an example, or EBS and Outposts, you know, we have customers like Morningstar and Morningstar wants Outposts because they are using it as a step in their journey to being on the cloud. If you take a customer like First Abu Dhabi Bank, they're using Outposts because they need data residency for their compliance requirements. And then we have other customers that are using Outposts to help, like Dish, Dish Networks, as an example, to place the storage as close as account to the applications for low latency. All of those are customer driven requirements for their architecture. For us, Dave, we think in the fullness of time, every customer and all applications are going to be on the cloud, because it makes sense and those businesses need that speed of innovation. But when we build things like our announcement today of FSx for NetApp ONTAP, we build them because customers asked us to help them with their journey to the cloud, just like we built S3 and EBS for Outposts for the same reason. >> Well, when you say over time, you're, you believe that all workloads will be on the cloud, but the cloud is, it's like the universe. I mean, it's expanding. So what's not cloud in the future? When you say on the cloud, you mean wherever you meet customers with that cloud, that includes Outposts, just the programming, it's the programmability of that model, is that correct? That's it, >> That's right. that's what you're talking about? >> In fact, our S3 and EBS Outposts customers, the way that they look at how they use Outposts, it's either as part of developing applications where they'll eventually go the cloud or taking applications that are in the cloud today in AWS regions and running them locally. And so, as you say, this definition of the cloud, you know, it, it's going to evolve over time. But the one thing that we know for sure, is that AWS storage and AWS in general is going to be there one or two steps ahead of where customers are, and deliver on what they need. >> I want to talk about block storage for a moment, if I can, you know, you guys are making some moves in that space. We heard some announcements earlier today. Some of the hardest stuff to move, whether it's cultural or maybe it's just hardened tops, maybe it's, you know, governance edicts, or those really hardcore mission critical apps and workloads, whether it's SAP stuff, Oracle, Microsoft, et cetera. You're clearly seeing that as an opportunity for your customers and in storage in some respects was a blocker previously because of whatever, latency, et cetera, then there's still some, some considerations there. How do you see those workloads eventually moving to the cloud? >> Well, they can move now. With io2 Block Express, we have the performance that those high-end applications need and it's available today. We have customers using them and they're very excited about that technology. And, you know, again, it goes back to what I just said, Dave, we had customers saying, I would like to move my highest performing applications to the cloud and this is what I need from the, from the, the storage underneath them. And that's why we built io2 Block Express and that's how we'll continue to evolve io2 Block Express. It is the first SAN technology in the cloud, but it's built on those core principles that we talked about a few minutes ago, which is dynamically evolving and capabilities that we can add on the fly and customers just get the benefit of it without the cost of migration. >> I want to ask you about, about just the storage, how you think about storage in general, because typically it's been a bucket, you know, it's a container, but it seems, I always say the next 10 years aren't going to be like the last, it seems like, you're really in the data business and you're bringing in machine intelligence, you're bringing in other database technology, this rich set of other services to apply to the data. That's now, there's a lot of data in the cloud and so we can now, whether it's build data products, build data services. So how do you think about the business in that sense? It's no longer just a place to store stuff. It's actually a place to accelerate innovation and build and monetize for your customers. How do you think about that? >> Our customers use the word foundational. Every time they talk about storage, they say for us, it's foundational, and Dave, that's because every business is a data business. Every business is making decisions now on this changing landscape in a world where the new normal means you cannot predict what's going to happen in six months, in a year. And the way that they're making those smart decisions is through data. And so they're taking the data that they have in our storage services and they're using SageMaker to build models. They're, they're using all kinds of different applications like Lake Formation and Glue to build some of the services that you're talking about around authorization and data discovery, to sit on top of the data. And they're able to leverage the data in a way that they have never been able to do before, because they have to. That's what the business world demands today, and that's what we need in the new normal. We need the flexibility and the dynamic foundational storage that we provide in AWS. >> And you think about the great data companies, those were the, you know, trillions in the market cap, their data companies, they put data at their core, but that doesn't mean they shove all the data into a centralized location. It means they have the identity access capabilities, the governance capabilities to, to enable data to be used wherever it needs to be used and, and build that future. That, exciting times we're entering here, Mai-Lan. >> We're just set the start, Dave, we're just at the start. >> Really, what ending do you think we have? So, how do you think about Amazon? It was, it's not a baby anymore. It's not even an adolescent, right? You guys are obviously major player, early adulthood, day one, day zero? (chuckles) >> Dave, we don't age ourself. I think if I look at where we're going for AWS, we are just at the start. So many companies are moving to the cloud, but we're really just at the start. And what's really exciting for us who work on AWS storage, is that when we build these storage services and these data services, we are seeing customers do things that they never thought they could do before. And it's just the beginning. >> I think the potential is unlimited. You mentioned Dish before, I mean, I see what they're doing in the cloud for Telco. I mean, Telco Transformation, that's an industry, every industry, there's a transformation scenario, a disruption scenario. Healthcare has been so reluctant for years and that's happening so quickly, I mean, COVID's certainly accelerating that. Obviously financial services have been super tech savvy, but they're looking at the Fintech saying, okay, how do we play? I mean, there isn't manufacturing with EV. >> Mai-Lan: Government. >> Government, totally. >> It's everywhere, oil and gas. >> There isn't a single industry that's not a digital industry. >> That's right. >> And there's implications for everyone. And it's not just bits and atoms anymore, the old Negroponte, although Nicholas, I think was prescient because he's, he saw this coming, it really is fundamental. Data is fundamental to every business. >> And I think you want, for all of those in different industries, you want to pick the provider where innovation and invention is in our DNA. And that is true, not just for storage, but AWS, and that is driving a lot of the changes you have today, but really what's coming in the future. >> You're right. It's the common editorial factors. It's not just the, the storage of the data. It's the ability to apply other technologies that map into your business process, that map into your organizational skill sets that drive innovation in whatever industry you're in. It's great Mai-Lan, awesome to see you. Thanks so much for coming on theCUBE. >> Great seeing you Dave, take care. >> All right, you too. And keep it right there for more action. We're going to now toss it back to Jenna, Canal and Darko in the studio. Guys, over to you. (pensive music)
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it's great to see you guys And now it's, you know, it's hard to tell. in the last 12 to 18 months. the loading dock and, you know, than the one that you talked about, and people would, you know, and they're saying to themselves, coined the term tech athlete, you know, and the cultural change of cloud And the concept is and it's easier to predict But that centralized storage it looks like it's in one place. to the point you were making. is again that perspective of the 15 years the cloud out to the edge, in the fullness of time, it's the programmability of that's what you're talking about? definition of the cloud, you know, Some of the hardest stuff to move, and customers just get the benefit of it lot of data in the cloud and the dynamic foundational and build that future. We're just set the start, Dave, So, how do you think about Amazon? And it's just the beginning. doing in the cloud for Telco. It's everywhere, that's not a digital industry. Data is fundamental to every business. the changes you have today, It's the ability to Great seeing you Dave, Jenna, Canal and Darko in the studio.
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James Wynia, Dell Technologies | CUBE Conversation, July 2021
(smooth music) >> Hi, welcome to this CUBE Conversation. I'm Lisa Martin. We've got James Wynia here with me, the Director of Product Management at Dell. We're going to be talking about modern data center networks. Jim, welcome to the program. >> Thank you, Lisa. Great to be here. >> So let's talk about this. We've had so many dynamics going on in the last 15, 16 months, I've lost count. A lot of dynamics in play that are contributing to IT complexity. There's new sources of data. We had this massive shift to work from home, work from anywhere, that's now kind of this hybrid environment. Talk to me about some of the core requirements of a modern network infrastructure that organizations need to deploy. >> Absolutely, and thanks for teeing that up. The modern networking requirements these days, so many people have moved home, and so as a result, then the infrastructure back on the farm, back in the data center have to be beefier. You have to have more capacity. You have to be able to handle more scaling operations. And so things like the ability to radically increase your backbone just by swapping in some different transceivers, possibly some different switches to support those faster transceivers, allow for us to multiply that bandwidth very quickly. So that's been a big result of what we have seen coming out of all this, the COVID madness. >> Yeah. (chuckles) Madness is a great description for it, and there's going to be that hybrid as we go forward. There's going to be that need to, for any industry, I imagine, to enable work from anywhere. But talk to me about where customers are from a speed perspective. 100 Gig, that's really mature at this point. Is that where most businesses are? And then what's the next step from there? >> Another great question. (chuckles) I mean, 100 Gig is pretty much the de facto standard at this point. It has really become very cost-competitive and very stable. I mean, we've really been shipping QSFP28 at the latest 100 Gig for five years, and it has become the de facto standard for many, many different scenarios. As we move forward, though of course, we just need to move more data is what it comes down to, and so the next logical jump from 100 is 400. And so 400 started rolling out about the time that COVID came on, a couple months before that. And so honestly, there was a slight kind of delay in the industry as COVID kind of made everybody take a step back and say, "Whoa, hold on." But now it's really come back in full force. >> So what does an organization, and we'll kind of just leave this as any industry, need to do to be able to prepare to go from 100 to 400, because as you mentioned, the data sources aren't diminishing. It's only going to continue to increase. >> Absolutely. And so one of the things is to make sure that the backbone infrastructure can handle 400 Gig. Ironically enough, the actual optical cable trunks, those are pretty much the same. And so if you were running single-mode fiber to go a long distance, you would use that same cable. So you don't have to rip out all your cable infrastructure. What you have to look at closely is when you plug that transceiver into a switch, what is it capable of running at? In olden days, that was probably 100 Gig. Now you have a 400 Gig, so you have to make sure that you have just the right hardware to go with that. And then as you go down the chain, down the stack, rather, from those, the switch from the cord, or the switch all the way to your server, on the servers we see a lot of interest in 100 Gig, even up to 200 Gig today. And so it's the same discussion. You're taking a close look at your NIC or your adapter. What is it rated at? Is it going to be able to handle a faster speed? >> So it's not a rip and replace. Can you give us an idea of the migration path that a customer would take, and how Dell would facilitate that? >> Absolutely. And so we have some great customers who have really stepped out in different ways. You have the Greenfield customers who, they're building out a whole additional data center, say. And so they would just, from the ground up, replace it with the latest and greatest equipment that's just already ready to go. Other customers that are just extending, maybe they're tapping a couple data centers together and replacing those 100 Gig links to aggregate them with 400 Gig links. And then they would maybe migrate, adding in an additional 400 Gig links down through the stack as it makes sense. So ethernet is ethernet, right? Whether you have 100 Gig on one link, 400 Gig on another link, it all plugs and plays nicely. And so you don't have to have this big step where you have to forklift everything out and then move all new equipment in. It's as it makes sense. >> As organizations have pivoted multiple times in the last 15, 16 months, as we've all seen, and there will continue to be that I mentioned, there's this sort of work from anywhere hybrid model, what are some of the benefits that a business could expect going from 100 Gig to 400 besides just quadrupling the speed? Talk to me about some of the business impact that can be made here. >> So business impact as is can be tremendous. Certainly, the capacity is the biggest one that jumps out at us here, as we can just combine, add on more services. Another area where we see this impact, and which, again, boils down to capacity, is IoT and edge. We have these new edge devices coming left and right. I mean, every time you turn around in the consumer world, there's some new thing that we never thought was possible, or we thought was 20 years down the road, and well, there it is. All of those cute little gadgets are just creating these streams of data, okay? So you just have so much more data that has to be processed. And so some of that gets processed at the edge, and that's kind of a cool new thing, but you still have more data that has to come back to the home base, either for storage, or for analytics, or for number-crunching, and so you have to be able to manage that. Bigger, fatter pipes going long distances, going short distances, going just in the same rank. >> Have you noticed, Jim, in the last year or so any industries in particular that are really prime candidates for this upgrade? As you mentioned, IoT, the explosion at the edge, sensors, sensors everywhere. Any industries that you saw that really are benefiting from doing this migration? >> Well, certainly the hyperscalers. The big companies that we all use social networking on. They're just moving around just piles of data, and everyone's working from home, and so they just have a little extra time to do the clicking and searching and stuff. And so that, and as well as entertainment. From home, people are just... They're just using up more bandwidth, and so the tier one, tier two providers certainly... We've seen just tremendous interest and growth as they have stepped out and adopted. >> Jim, can we do a double-click now on some deployment options and capabilities, maybe helping us understand it by industry segment? >> Yes, absolutely. And so some of the segments that we've been working closely with over the last 18 months here is like cloud service providers. Also large enterprise companies who have the large data centers. And then thirdly, federal is moving along very quickly. Federal's got all the security stuff that's been in the news of late. They have more calculation and just data transfer needs than ever, and so those are a couple of good ones. >> Got it, yeah. Ransomware is now, unfortunately, one of those common household words, as is pandemic and Pfizer, right? Talk to me about where automation comes into play as organizations look to migrate to become faster, to be able to manage more data coming in faster from more sources, where does automation factor in the mix? >> One of my favorite questions, actually, because in the networking industry, it has changed so much in the last five years. It used to be that when you were talking about large data centers, and just massive amounts of data, that the entire discussion revolved around these large modular chassis. And the reality is that nowadays, yeah, large modular chassis still exist, and they have a place, but they're not mandatory in all circumstances. And one of the big changes is that you can get building blocks that push out tremendous amounts of data within a single box. And you can use like a claw structure that allows you to do more data safer because you have higher availability than these really expensive modular chassis. And so when you come with kind of more switches, the reality is that now you have a bigger automation requirement. And so the tools to be able to automatically set that up, automatically maintain, and automatically monitor it, those are critical. And especially when we're talking about high capacity environments where you have millions of people watching the video being on the screen right now. It better be there no matter what blip happens on the backend. >> Yep. There's always that demanding consumer, (chuckles) no matter what you do. What about automating day one and day two operations? How does it play into managing this infrastructure, this modern data network infrastructure, with on-prem and in the cloud? >> Yes. So I work for Dell, and I forgot to mention upfront, I apologize, I'm a Dell employee, but I'm actually speaking from my opinion. I'm not representing Dell in terms of their viewpoint of all of these things we're talking about today. But one of the big things is that, as we have gone from those modular chassis to more individual units to get this cleaner deployment, the day one has to do with how do you design that. How do you, when you have more fiber cables connecting things up, how do you make sure that you don't oops, plug one into the wrong place? And so tools such as in Dell, we have tools like the Fabric Design Center that automatically generate all of those wiring diagrams for you, all of the testing. When you plug it in for the first time, it actually verifies that everything's clean. And then day two is monitoring what's happening. Are you getting issues, subtle issues that are maybe not noticed but are building up? And so things like the Smart Fabric Director can allow us to monitor those types of things and make recommendations for, "Hey, there's something happening we need to be aware of and watch it," or "Here's some corrective action." And so those kinds of tools really are the lifeblood to make sure that the team doesn't just get overwhelmed. And the reality is we all know as time goes on, we need, or we're given the opportunity to have fewer people working on maintaining stuff. And so you need more equipment that's more complex, but you have less number of eyes on what's going on, and so the tools just have to be locked in. >> So tools you mentioned. What about operating systems? Anything that you would recommend that customers looking into? >> That's another great question. So operating systems have changed. If you look back on the server world, you go back 20, 25 years ago, every server company, they made their own CPU, they made their own operating system, and then it evolved so that there was, now you buy a CPU from either maybe Intel, maybe AMD. But it's not like Dell goes out and makes its own CPU. We buy from other established leaders. When it comes to operating systems on the server side, the same thing happened. Well, the networking world has been catching up for quite a while, and so four years ago, we started talking about open networking, and the fact that there are options. You're not locked into just what is our primary operating system. And so there are opensource operating systems that you can run. There are things like SONiC, which has just really been taking the networking world by storm. And so we certainly support Dell Enterprise SONiC on our platforms. And that is another fantastic option. >> Excellent. Last question, Jim, for you. If you had a crystal ball, given the dynamics of the world today and how quickly things are changing, and how organizations need to be competitive, what are some of the things that you think we're going to see in the networking world in the next 12 to 18 months? >> Well, it doesn't take a whole lot of a crystal ball. We just follow the standards, bodies. We see that 400 Gig has really come on strong. And honestly, we played catch up in that industry, having all of the optics that we needed. We needed all the breakout optics to go from 400 to four by 100. Those took a good, well, six to eight months before those really came on board. And so now we're finally at the place where we're in a good place, but the next thing clearly is everything doubles. And so now we'll jump to 800 Gig over the same infrastructure, and so that's, again, everything doubles. And then there's a lot of talk about, "Well, what happens after that?" Well, then you go everything from 800 to 1.6T over that same infrastructure, and so it's just kind of mind-boggling capacity, but it's coming at us like a freight train. >> It is like a freight train. We'll say a good freight train. Jim, thank you so much for joining me on theCUBE today, talking to me about modern data center networks, what's going on there, the opportunities for businesses in any industry to take advantage of the latest and greatest. We appreciate your time. >> You bet. Thank you for inviting me. >> For Jim Wynia, I'm Lisa Martin. You're watching this CUBE Conversation. (smooth music)
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the Director of Product in the last 15, 16 back in the data center and there's going to be that and so the next logical the data sources aren't diminishing. And so one of the things is to make sure of the migration path And so you don't have in the last 15, 16 and so you have to be able to manage that. in the last year or so any and so the tier one, tier And so some of the to be able to manage more data And so the tools to be able (chuckles) no matter what you do. and so the tools just Anything that you would recommend and the fact that there are options. the next 12 to 18 months? having all of the optics that we needed. the latest and greatest. Thank you for inviting me. You're watching this CUBE Conversation.
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Christian Craft, Oracle | CUBE Conversation
(upbeat music) >> Hello everyone, and welcome to this Cube conversation. We're going to dig into some of the more specific and sometimes gory details of managing the nuances of database, database management systems. You know, it's a lot of fun to get it to the daily buzz of cloud and database competition and get a little snarky on Twitter, but there are a lot of mundane issues that you have to address to really do proper database sizing, capacity planning, and you know whether or not database consolidation makes sense. These are not trivial issues. And decades ago they spawned an entire role around the database administrator. They had to do the dirty work of database management so that users and customers would be satisfied. And while automation and cloud are changing that role, at the end of the day, somebody actually has to make the databases work in the cloud and make sure that the business doesn't feel any impact on the transition along the way. So on that note, we have with us Oracle senior director of product management for mission critical databases. He works in Juan Loaiza's group, Chris Craft, and Steve Zivanic whom we know well on the cube says this guy is the Jedi master when it comes to consolidating databases in the cloud. Nobody knows more on the face of the planet Earth. So we're really excited Chris, to have you inside the Cube. Welcome. >> Thanks, thanks Dave. >> That's a very humble thanks. So when it comes to running databases in the cloud can you explain the difference between sizing and capacity planning? Aren't they two sides of the same coin? >> Yeah, you know, they really are. It's like, you know sizing is really part of capacity to planning. It's really, I look at sizing as a one-time effort whereas capacity planning is more your ongoing. You perform sizing initially when the application is deployed. And then, then when you're changing platforms, like going from on-prem to the Cloud you're going to go through a sizing exercise 'cause you're looking at going to a new platform. That's more of a one-time effort, and then ongoing, you're looking at your capacity management over time. So yeah, they are very related so. >> Okay, thank you. So we're going to talk about database consolidation. A lot of people would say, look the cloud makes consolidating databases maybe not irrelevant, but maybe not the best strategy because I got all these different purpose-built databases. Why consolidate databases if they're already going to consolidate it in the cloud in one location? >> Yeah. So, so we're really talking about in in the cloud, you're running virtual machines but consolidation still applies on the virtual machines. So if you have a virtual machine that's dedicated to a database that database is that server, that virtual machine is going to be under utilized over time. So what we're doing with consolidation is running multiple databases within a virtual machine or what it, Oracle virtual cluster. We do everything on clusters. So multiple machines multiple databases within that will drive up the utilization and improve your cost structure. So it's a sizing it's it's absolutely critical on even in the cloud. >> Okay. But, but wouldn't it, I might say to that, wouldn't it be better to have each database have a dedicated VM? I mean, from a performance perspective, it doesn't try to make the database do too much affect performance. >> Yeah. It, so whenever, so we know historically that a database on a dedicated server back in the day that was a physical server, today it's a virtual machine. When you do that, your utilization will be in the range of 15 to 20%. And that's, you know very highly under utilized systems when you do that. So we don't need to isolate things onto dedicated virtual machines for a performance perspective. There are other ways that we can manage that we have resource management built into Oracle and the Oracle database. And then on Exadata we have an integrated IO resource management as well so we can deal with that different ways. >> Okay. So you're basically proposing that you're putting these databases onto a single VM and managing it accordingly. Is there additional details you can provide on that? >> So, you know, we don't put everything into you know, literally one, one VM. You want to have some isolation built in there, but see and take a more pragmatic approach. You know, like every single database in one VM that's the wrong way to go. Each database in a dedicated VM is also the other extreme, also the wrong way to go. So we're kind of right down the middle and be more pragmatic about it, and do some level of consolidation to drive up utilization. >> I remember when I first started following tech I was studying up on, you know kind of how disc drives work and so forth. And there was probably like I can't even remember what it was. It was like probably like 10 megabytes under an actuator. And people were saying, Oh my God, that's so much data. You, you got your blast radius is, is so big. You got to split that up. So it's the same concept, apply with availability. Some would say, there's a problem because you're consolidating all this data and you've got this blast radius that increases. How do you address that? >> And so, you know, redundancy. So we have redundancy at all levels. So if you look at a single, so we're talking about Exadata here, taught in an Exadata machine we can lose up to 24 disc drives out of 30. 30 machines with 36 disc drives, we can use 24 of those. So that'd be 12 per storage cell. You can lose two storage cells as 24 out of 36 drives so we can lose and keep on running. We can also, we also cluster, we also do clustering. So the database servers are clustered together for high availability. So we can take, we can suffer multiple simultaneous failures and keep on running without performance impact either. So it's, so recovery, we handle that in different ways. So it's, look at blast radius from a standpoint, you want some, some isolation for blast radius but we have physical failures is just not something that we're concerned with. >> Why do you deal with taking down a VM? Doesn't that normally mean there's going to be some kind of disruption? >> Oh, so you know, the, so Oracle database, you're talking about real application clusters on on Oracle database, on Exadata. We've got, we have a very fast detection of of failures and then resolution of the failure. So we're looking at a small blip in performance, you know we're looking at a few milliseconds to detect failure and then maybe up around three seconds to actually affect the failover. So the applications that are not getting disconnected, they continue operating in the, in that kind of condition. So that's kind of unique to the Exadata platform. And so, you know, in our cloud, we're running Exadata. We have this built in there. So we're, we're resilient to that type of failure, so. >> And sorry, you mentioned real application clusters. You're saying because you're running real application clusters that's how you're able to become more resilient? >> So yeah, so we have, so Oracle database real application clusters runs on top of a clustered virtual machines on Exadata. We have integration then optimizes the fail over times of that clustering. So it's, it's not the cluster same, it's the optimizations are only built into Exadata. So we have much much faster, much better tighter integration, so much more scalability because of that, that integration that we have. >> Can I run rack in other clouds? Can I put that into Amazon's cloud? >> So, so real application clusters requires two things. It's a, you require shared storage in a fast interconnect, a fast networking interconnecting. And those things just don't exist in the other clouds. We have those built into Exadata in our cloud. And we also, we also allow real application clusters in our relational database, our database cloud service offering as well. But it's, really the highest implementation of that is in Exadata. >> Well, of course I was tongue in cheek joking but this is, this is why, you know, I was listening to Arvind Krishna the other day in IBM Think. And he was saying only 25% of mission critical applications have moved into the cloud. I didn't think it's that high. I mean, but, but what you're doing is basically building a mission critical, you know, cloud or a cloud for mission critical databases. And that's, that's unique. I mean, I would expect other cloud vendors that eventually you know, are going to get there, but you're kind of starting with the hard stuff and working backwards. But, that is what I've always interpreted is unique to Oracle, but how does that affect cost? Isn't that more expensive? >> Actually, no. We're taking services that that start out at a very similar price point. And then we drive. So what we've seen from other customers that are running in like Amazon, for example, we see databases on dedicated virtual machines that run anywhere from 15 to 20% utilization. So what we do is, that low, low utilization, what we do is take that and triple that. So we run, so we run maybe 50% utilization. At that point we still have full redundancy, but we've now made the service one third of the cost. So we're starting at a third, we're starting at a very similar cost. And then we drive it to, you know three times a utilization. This is not crazy numbers. This is, you know, 50% is, is fine and retain the redundancy at that level as well. >> Got it, well so. >> What we've seen is about a third the cost. >> Really? Okay. Well, so, but, what about, like for instance, on AWS, couldn't I run this in a multi availability zone, running RDS or some other cloud database? >> So, so you can run a Multi-AZ environment like in in Amazon, for example, you can run locals. That's what we call local standby. If you do that, you're now instead of being one third, instead of being three times more expensive, you're now six times more expensive. Because that is another copy of the entire platform, the entire instance, the storage, everything on the other availability zone instead of being three times more, it's now six. >> Because you're essentially replicating everything in a brute force mode, right? >> Yeah. It's a data guard standby, local standby in another AZ, or what we call availability domain in our cloud. >> So let's maybe geek out a little bit. So, let's talk more about availability. You know, for years, I mean, I remember going back to reading about this stuff with tandem computers, you know, coincident failures. How are you dealing with those in today's modern world? >> So what we call simultaneous failures is, so we, we deal with that with redundancy in the system. So we have redundancy at all layers in the storage. Like I said earlier, we can take across, you know, two storage cells and each storage cell has a dozen drives. So that's 24 disc drives. That's eight flashcard failures simultaneously. And we keep on running no data loss, no loss of service. That's at the storage layer. We have multiple, multiple redundant networking switches at that, at the networking layer, the internal network. Then we go up into the database server. We then have redundancy across the nodes of a cluster. You have multiple virtual machines that comprise a virtual cluster. So it's at each and every level, we have redundancy. And then we drive the redundancy into the application using what's called application continuity. So the application connections have knowledge of the failure, failure modes of the database. They can follow to the surviving node, and continue operating. >> And you do this with math, you're doing some kind of magic bit slicing, or how do you do that? >> That, so that is that particular thing, application continuity, so technology that's been built into Oracle database since, since 12c, and that it's been around for quite a long time. And it allows the application to follow the rack cluster, any kind of issues with the rack cluster. We can drain connections off. It's very well-proven technology in, you know, prior to to proactive maintenance, we can drain connections over and then it will also handle a failure of a connection as well. And the application following that, yes. >> I learned from my old mainframe days and hanging around with David Floyer. It's always ask, what happens when something goes wrong and it's all about recovery. And you guys have the gold standard there. I mean, we've talked about this a lot. So you got Exadata. That's what is behind your Exadata cloud service, X8M I think you call it, and you've got autonomous database. I'm not great with model numbers, but, but talk about the way you can handle simultaneous failures. I mean, are there like triple redundancies that you've built in? >> Yeah. So everything what we do in our cloud is everything is triple redundancy by default. So we, you can suffer, that way we can suffer two failures and continue operating. So the, the other thing, so recovery, if you look at transaction recovery, when a failure occurs a transaction will flip that session, will flip to the machine that keeps running. It'll reposition all in the work that's in flight, any kind of inflight transactions, any in flight queries that are going on, reposition and continue operating. >> So you've essentially created like the old three site data centers, but you're in a single platform because you're synchronous. But, that same concept in a package. >> It's, you know, it's a lot of times you show a picture of an Exadata. It looks like a single box, but in the box there's some redundancy built in the box. And in fact, in the cloud it's actually across an entire aisle. So it's, we kind of obscure that a little bit, from your provisioning, you know, our database nodes and our storage cells and in the cloud but it's actually across an entire aisle of a dataset. >> Okay, and of course, that's within a synchronous location. Let's talk about disaster recovery, and what you're doing in that area, around Oracle Cloud What are my options there? What's different from other cloud providers we were talking earlier about, AZs, how are you different and what are you doing there? >> Yeah, so we, we talked earlier about the Multi-AZ deployment, what we call it availability domain, AD, so a little different terminology. But we can deploy another, another copy of the database into another availability domain, if you like. It's not often that you lose an entire AZ or AD, it's more, we're protecting from regional failures. So across another region. And that's where we look at, we really look at that as that technology, as a standby, as a data, disaster recovery solution not for HA. HA, we build HA into the machine itself. >> So you're saying, we were talking earlier about AZ, you're saying that's for HA versus DR. Is that, is that what you're contending? >> Yeah, like, you know again, pick on Amazon for a second here. Amazon uses a standby database. What we would normally use for disaster recovery, they're using that for availability. And you're looking at a few minutes of time to flip over to another AZ, whereas within an Exadata frame, we can flip over in milliseconds. We keep continue running. There is no loss of conductivity. And then we use the standby in another region for disaster. That's a true disaster solution. >> As opposed to incurring that penalty of latency, or whatever, to spin up the other resource. >> Right, right. >> Okay, so that's clear how kind of you guys address that, that challenge. Last question, maybe you could give us your take, again folks, coming out of Oracle's mouth, but what's the bottom line cost Delta based on your experience between your service and competitive services? I love these conversations because you're not afraid to talk about the competition, so bring it on. >> I've seen, so we've just based on what we've seen with customers deploying databases in Amazon, versus what, you know we've replaced that within, in our cloud service. We're seeing from just a list price perspective. Now, you know, we discount, I know Amazon discounts, but the only thing I can really speak to is list price perspective. It's about a third the cost. So we're talking about a more powerful platform, runs faster. We get these incredible, we haven't even talked about performance here. Talk about availability, performance where we're getting IO rates, IO latencies in the 19 microsecond range. Now with Exadata, that's going to be 50 times faster than what you get with these traditional cloud vendors. So much, much faster, and a third the cost. >> So talk about discounts, I mean, I know Oracle discounts, Oracle from list price, Oracle provides significant discounts. I'm not as familiar with your cloud pricing but I mean, Amazon's discounts are really in the form of like reserved instances. Is your pricing similar in that regard or different? I mean, if I'm just paying on demand, I'm paying through the nose. I presume it's same with you. If I, but if I buy in bulk getting a discount, is that what you mean by discount? Or is it more similar to the way you've traditionally discounted, you know large customers, the more you spend, the more you you get kind of thing. >> It's a, there's a discount structure. So it's, we don't have the same kind of lock-in like with reserved instance structure, but yeah, it's, there are discounts and that's going to be very customer specific. >> Right. >> So, but I think that the end result we're starting at, a three X differential on the price. >> But the reason I'm asking the question is that the stats you gave me are for list price, right? >> Yeah, yes, yeah. >> Okay, and sure, you're saying that at list price you're, you're less expensive. I, and again, my contention would be just by experiences that your discounts would be more aggressive traditionally in Oracle's traditional business. You know, I've done a lot of Oracle negotiation in my days. And if you're, you know, if you're a big customer you can get good deals. And again, I'm not as familiar with the cloud pricing, but still that's, that's good. If you're doing it on a list price basis, to me, that's a conservative statement if that makes any sense. >> Right, that's where it starts. We know that's where it's starting out. So I, you know, once you get into discounts, it's very customer specific. >> Right. >> We know the starting point is at three X differential. Before you do something in the Multi-AZ would be a six X differential, by the way, so. >> Yeah, okay. All right, Chris. Well, Hey, I appreciate you taking us through this, good stuff, and best of luck, good work. You know, you guys keep, I always say Oracle invest you guys spend a lot of money in RD and, and, you know you're quiet for a while in the cloud and all of a sudden you came out like you invented it. So good job! >> All right. >> All right, thanks. Thanks for coming on. All right. >> Thanks. >> Thank you for watching everybody. This is Dave Vellante for Cube conversations. We'll see you next time. (upbeat music)
SUMMARY :
So on that note, we have with databases in the cloud Yeah, you know, they really are. maybe not the best strategy So if you have a virtual I might say to that, in the range of 15 to 20%. you can provide on that? So, you know, we So it's the same concept, So if you look at a So the applications that are And sorry, you mentioned So it's, it's not the cluster exist in the other clouds. building a mission critical, you know, And then we drive it to, you know about a third the cost. Well, so, but, what If you do that, you're now or what we call availability you know, coincident failures. So the application And it allows the application about the way you can handle So we, you can suffer, like the old three site data And in fact, in the cloud what are you doing there? It's not often that you So you're saying, we were Yeah, like, you know again, that penalty of latency, kind of you guys address that, but the only thing I can really speak to is that what you mean by discount? So it's, we don't have the So, but I think that the you can get good deals. So I, you know, once We know the starting point and all of a sudden you came Thanks for coming on. Thank you for watching everybody.
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