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Juan Loaiza, Oracle | Building the Mission Critical Supercloud


 

(upbeat music) >> Welcome back to Supercloud two where we're gathering a number of industry luminaries to discuss the future of cloud services. And we'll be focusing on various real world practitioners today, their challenges, their opportunities with an emphasis on data, self-service infrastructure and how organizations are evolving their data and cloud strategies to prepare for that next era of digital innovation. And we really believe that support for multiple cloud estates is a first step of any Supercloud. And in that regard Oracle surprise some folks with its Azure collaboration the Oracle database and exit database services. And to discuss the challenges of developing a mission critical Supercloud we welcome Juan Loaiza, who's the executive vice president of Mission Critical Database Technologies at Oracle. Juan, you're many time CUBE alums so welcome back to the show. Great to see you. >> Great to see you, and happy to be here with you. >> Yeah, thank you. So a lot of people felt that Oracle was resistant to multicloud strategies and preferred to really have everything run just on the Oracle cloud infrastructure, OCI and maybe that was a misperception maybe you guys were misunderstood or maybe you had to change your heart. Take us through the decision to support multiple cloud platforms >> Now we've supported multiple cloud platforms for many years, so I think that was probably a misperception. Oracle database, we partnered up with Amazon very early on in their cloud when they had kind of the the first cloud out there. And we had Oracle database running on their cloud. We have backup, we have a lot of stuff running. So, yeah, part of the philosophy of Oracle has always been we partner with every platform. We're very open we started with SQL and APIs. As we develop new technologies we push them into the SQL standard. So that's always been part of the ecosystem at Oracle. That's how we think we get an advantage by being more open. I think if we try to create this isolated little world it actually hurts us and hurts customers. So for us it's a win-win to be open across the clouds. >> So Supercloud is this concept that we put forth to describe a platform or some people think it's an architecture if you have an opinion, and I'd love to hear it but it provides a programmatically consistent set of services that hosted on heterogeneous cloud providers. And so we look at the Oracle database service for Azure as fitting within this definition. In your view, is this accurate? >> Yeah, I would broaden it. I'd see a little bit more than that. We just think that services should be available from everywhere, right? So, I mean, it's a little bit like if you go back to the pre-internet world, there was things like AOL and CompuServe and those were kind of islands. And if you were on AOL, you really didn't have access to anything on CompuServe and vice versa. And the cloud world has evolved a little bit like that. And we just think that's the wrong model. They shouldn't these clouds are part of the world and they need to be interconnected like all the rest of the world. It's been a long time with telephones internet, everything, everything's interconnected. Everything should work seamlessly together. So that's how we believe if you're running in one cloud and you're running let's say an application, one cloud you want to use a service from another cloud should be completely simple to do that. It shouldn't be, I can only use what's in AOL or CompuServe or whatever else. It should not be isolated. >> Well, we got a long way to go before that Nirvana exists but one example is the Oracle database service with Azure. So what exactly does that service provide? I'm interested in how consistent the service experience is across clouds. Did you create a purpose-built PaaS layer to achieve this common experience? Or is it off the shelf Terraform? Is there unique value in the PaaS layer? Let's dig into some of those questions. I know I just threw six at you. >> Yeah, I mean, so what this is, is what we're trying to do is very simple. Which is, for example, starting with the Oracle database we want to make that seamless to use from anywhere you're running. Whether it's on-prem, on some other cloud, anywhere else you should be able to seamlessly use the Oracle database and it should look like the internet. There's no friction. There's not a lot of hoops you got to jump just because you're trying to use a database that isn't local to you. So it's pretty straightforward. And in terms of things like Azure, it's not easy to do because all these clouds have a lot of kind of very unique technologies. So what we've done is at Oracle is we've said, "Okay we're going to make Oracle database look exactly like if it was running on Azure." That means we'll use the Azure security systems, the identity management systems, the networking, there's things like monitoring and management. So we'll push all these technologies. For example, when we have monitoring event or we have alerts we'll push those into the Azure console. So as a user, it looks to you exactly as if that Oracle database was running inside Azure. Also, the networking is a big challenge across these clouds. So we've basically made that whole thing seamless. So we create the super high bandwidth network between Azure and Oracle. We make sure that's extremely low latency, under two milliseconds round trip. It's all within the local metro region. So it's very fast, very high bandwidth, very low latency. And we take care establishing the links and making sure that it's secure and all that kind of stuff. So at a high level, it looks to you like the database is--even the look and feel of the screens. It's the Azure colors, it's the Azure buttons it's the Azure layout of the screens so it looks like you're running there and we take care of all the technical details underlying that which there's a lot which has taken a lot of work to make it work seamlessly. >> In the magic of that abstraction. Juan, does it happen at the PaaS layer? Could you take us inside that a little bit? Is there intelligence in there that helps you deal with latency or are there any kind of purpose-built functions for this service? >> You could think of it as... I mean it happens at a lot of different layers. It happens at the identity management layer, it happens at the networking layer, it happens at the database layer, it happens at the monitoring layer, at the management layer. So all those things have been integrated. So it's not one thing that you just go and do. You have to integrate all these different services together. You can access files in Azure from the Oracle database. Again, that's completely seamless. You, it's just like if it was local to our cloud you get your Azure files in your kind of S3 equivalent. So yeah, the, it's not one thing. There's a whole lot of pieces to the ecosystem. And what we've done is we've worked on each piece separately to make sure that it's completely seamless and transparent so you don't have to think about it, it just works. >> So you kind of answered my next question which is one of the technical hurdles. It sounds like the technical hurdles are that integration across the entire stack. That's the sort of architecture that you've built. What was the catalyst for this service? >> Yeah, the catalyst is just fulfilling our vision of an open cloud world. It's really like I said, Oracle, from the very beginning has been believed in open standards. Customers should be able to have choice customers should be able to use whatever they want from wherever they want. And we saw that, you know in the new world of cloud that had broken down everybody had their own authentication system management system, monitoring system networking system, configuration system. And it became very difficult. There was a lot of friction to using services across cloud. So we said, "Well, okay we can fix that." It's work, it's significant amount of work but we know how to do it and let's just go do it and make it easy for customers. >> So given Oracle is really your main focus is on mission critical workloads. You talked about this low latency network, I mean but you still have physical distances, so how are you managing that latency? What's the experience been for customers across Azure and OCI? >> Yeah, so it, it's a good point. I mean, latency can be an issue. So the good thing about clouds is we have a lot of cloud data centers. We have dozens and dozens of cloud data centers around the world. And Azure has dozens and dozens of cloud data centers. And in most cases, they're in the same metro region because there's kind of natural metro regions within each country that you want to put your cloud data centers in. So most of our data centers are actually very close to the Azure data centers. There's the kind of northern Virginia, there's London, there's Tokyo I mean, there's natural places where everybody puts their data centers Seoul et cetera. And so that's the real key. So that allows us to put a very high bandwidth and low latency network. The real problems with latency come when you're trying to go along physical distance. If you're trying to connect, you know across the Pacific or you know across the country or something like that, then you can get in trouble with latency within the same metro region. It's extremely fast. It tends to be around one, you know the highest two millisecond that's roundtrip through all the routers and connections and gateways and everything else. With everything taken into consideration, what we guarantee is it's always less than two millisecond which is a very low latency time. So that tends to not be a problem because it's extremely low latency. >> I was going to ask you less than two milliseconds. So, earlier in the program we had Jack Greenfield who runs architecture for Walmart, and he was explaining what we call their Supercloud, and it's runs across Azure, GCP, and they're on-prem. They have this thing called the triplet model. So my question to you is, are you in situations where you guaranteeing that less than two milliseconds do you have situations where you're bringing, you know Exadata Cloud, a customer on-prem to achieve that? Or is this just across clouds? >> Yeah, in this case, we're talking public cloud data center to public cloud data center. >> Oh okay. >> So add your public cloud data center to Oracle Public Cloud data center. They're in the same metro region. We set up the connections, we do all the technology to make it seamless. And from a customer point of view they don't really see the network. Also, remember that SQL is actually designed to have very low bandwidth and latency requirements. So it is a language. So you don't go to the database and say do this one little thing for me. You send it a SQL statement that can actually access lots of data while in the database. So the real latency requirement of a SQL database is within the database. So I need to access all that data fast. So I need very fast access to storage very fast access across node. That's what exit data gives you. But you send one request and that request can do a huge amount of work and then return one answer. And that's kind of the design point of SQL. So SQL is inherently low bandwidth requirements, it was used back in the eighties when we used to have 10 megabit networks and the the biggest companies in the world ran back then. So right now we're talking over hundred hundreds of gigabits. So it's really not much of a challenge. When you're designed to run on 10 megabit to say, okay I'm going to give you 10,000 times what you were designed for it's really, it's a pretty low hurdle jump. >> What about the deployment models? How do you handle this? Is it a single global instance across clouds or do you sort of instantiate in each you got exudate in Azure and exudates in OCI? What's the deployment model look like? >> It's pretty straightforward. So customer decides where they want to run their application and database. So there's natural places where people go. If you're in Tokyo, you're going to choose the local Tokyo data centers for both, you know Microsoft and Oracle. If you're in London, you're going to do that. If you're in California you're going to choose maybe San Jose, something like that. So a customer just chooses. We both have data centers in that metro region. So they create their service on Azure and then they go to our console which looks just like an Azure console and say all right create me a database. And then we choose the closest Oracle data center which is generally a few miles away, and then it it all gets created. So from a customer point of view, it's very straightforward. >> I'm always in awe about how simple you make things sound. All right what about security? You talked a little bit before about identity access how you sort of abstracting the Azure capabilities away so that you've simplified it for your customers but are there any other specific security things that you need to do? How much did you have to abstract the underlying primitives of Azure or OCI to present that common experience to customers? >> Yeah, so there's really two big things. One is the identity management. Like my name is X on Azure and I have this set of privileges. Oracle has its own identity management system, right? So what we didn't want is that you have to kind of like bridge these things yourself. It's a giant pain to do that. So we actually what we call federate across these identity managements. So you put your credentials into Azure and then they automatically get to use the exact same credentials and identity in the Oracle cloud. So again, you don't have to think about it, it just works. And then the second part is that the whole bridging the network. So within a cloud you generally have virtual network that's private to your company. And so at Oracle, we bridge the private network that you created in, for example, Azure to the private network that we create for you in Oracle. So it is still a private network without you having to do a whole bunch of work. So it's just like if you were in your own data center other people can't get into your network. So it's secured at the network level, it's secured at the identity management, and encryption level. And again we did a lot of work to make that seamless for customers and they don't have to worry about it because we did the work. That's really as simple as it gets. >> That's what's Supercloud's supposed to be all about. Alright, we were talking earlier about sort of the misperception around multicloud, your view of Open I think, which is you run the Oracle database, wherever the customer wants to run it. So you got this database service across OCI and Azure customers today, they run Oracle database in AWS. You got heat wave, MySQL, heat wave that you announced on AWS, Google touts a bare metal offering where you can run Oracle on GCP. Do you see a day when you extend an OCI Azure like situation across multiple clouds? Would that bring benefits to customers or will the world of database generally remain largely fenced with maybe a few exceptions like what you're doing with OCI and Azure? I'm particularly interested in your thoughts on egress fees as maybe one of the reasons that there is a barrier to this happening and why maybe these stove pipes, exist today and in the future. What are your thoughts on that? >> Yeah, we're very open to working with everyone else out there. Like I said, we've always been, big believers in customers should have choice and you should be able to run wherever you want. So that's been kind of a founding principle of Oracle. We have the Azure, we did a partnership with them, we're open to doing other partnerships and you're going to see other things coming down the pipe on the topic of egress. Yeah, the large egress fees, it's pretty obvious what goes on with that. Various vendors like to have large egress fees because they want to keep things kind of locked into their cloud. So it's not a very customer friendly thing to do. And I think everybody recognizes that it's really trying to kind of course or put a lot of friction on moving data out of a particular cloud. And that's not what we do. We have very, very low egress fees. So we don't really do that and we don't think anybody else should do that. But I think customers at the end of the day, will win that battle. They're going to have to go back to their vendor and say, well I have choice in clouds and if you're going to impose these limits on me, maybe I'll make a different choice. So that's ultimately how these things get resolved. >> So do you think other cloud providers are going to take a page out of what you're doing with Azure and provide similar solutions? >> Yeah, well I think customers want, I mean, I've talked to a lot of customers, this is what they want, right? I mean, there's really no doubt no customer wants to be locked into a single ecosystem. There's nobody out there that wants that. And as the competition, when they start seeing an open ecosystem evolving they're going to be like, okay, I'd rather go there than the closed ecosystem, and that's going to put pressure on the closed ecosystems. So that's the nature of competition. That's what ultimately will tip the balance on these things. >> So Juan, even though you have this capability of distributing a workload across multiple clouds as in our Supercloud premise it's still something that's relatively new. It's a big decision that maybe many people might consider somewhat of a risk. So I'm curious who's driving the decisions for your initial customers? What do they want to get out of it? What's the decision point there? >> Yeah, I mean, this is generally driven by customers that want a specific technology in a cloud. I think the risk, I haven't seen a lot of people worry too much about the risk. Everybody involved in this is a very well known, very reputable firm. I mean, Oracle's been around for 40 years. We run most of the world's largest companies. I think customers understand we're not going to build a solution that's going to put their technology and their business at risk. And the same thing with Azure and others. So I don't see customers too worried about this is a risky move because it's really not. And you know, everybody understands networking at the end the day networking works. I mean, how does the internet work? It's a known quantity. It's not like it's some brand new invention. What we're really doing is breaking down the barriers to interconnecting things. Automating 'em, making 'em easy. So there's not a whole lot of risk here for customers. And like I said, every single customer in the world loves an open ecosystem. It's just not a question. If you go to a customer would you rather put your technology or your business to run on a closed ecosystem or an open system? It's kind of not even worth asking a question. It's a no-brainer. >> All right, so we got to go. My last question. What do you think of the term "Supercloud"? You think it'll stick? >> We'll see. There's a lot of terms out there and it's always fun to see which terms stick. It's a cool term. I like it, but the decision makers are actually the public, what sticks and what doesn't. It's very hard to predict. >> Yeah well, it's been a lot of fun having you on, Juan. Really appreciate your time and always good to see you. >> All right, Dave, thanks a lot. It's always fun to talk to you. >> You bet. All right, keep it right there. More Supercloud two content from theCUBE Community Dave Vellante for John Furrier. We'll be right back. (upbeat music)

Published Date : Jan 12 2023

SUMMARY :

and cloud strategies to prepare happy to be here with you. just on the Oracle cloud of the ecosystem at Oracle. and I'd love to hear it And the cloud world has Or is it off the shelf Terraform? So at a high level, it looks to you Juan, does it happen at the PaaS layer? it happens at the database layer, So you kind of And we saw that, you know What's the experience been for customers across the Pacific or you know So my question to you is, to public cloud data center. So the real latency requirement and then they go to our console the Azure capabilities away So it's secured at the network level, So you got this database We have the Azure, we did So that's the nature of competition. What's the decision point there? down the barriers to the term "Supercloud"? and it's always fun to and always good to see you. It's always fun to talk to you. Vellante for John Furrier.

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Harveer Singh, Western Union | Western Union When Data Moves Money Moves


 

(upbeat music) >> Welcome back to Supercloud 2, which is an open industry collaboration between technologists, consultants, analysts, and of course, practitioners, to help shape the future of cloud. And at this event, one of the key areas we're exploring is the intersection of cloud and data, and how building value on top of hyperscale clouds and across clouds is evolving, a concept we call supercloud. And we're pleased to welcome Harvir Singh, who's the chief data architect and global head of data at Western Union. Harvir, it's good to see you again. Thanks for coming on the program. >> Thanks, David, it's always a pleasure to talk to you. >> So many things stand out from when we first met, and one of the most gripping for me was when you said to me, "When data moves, money moves." And that's the world we live in today, and really have for a long time. Money has moved as bits, and when it has to move, we want it to move quickly, securely, and in a governed manner. And the pressure to do so is only growing. So tell us how that trend is evolved over the past decade in the context of your industry generally, and Western Union, specifically. Look, I always say to people that we are probably the first ones to introduce digital currency around the world because, hey, somebody around the world needs money, we move data to make that happen. That trend has actually accelerated quite a bit. If you look at the last 10 years, and you look at all these payment companies, digital companies, credit card companies that have evolved, majority of them are working on the same principle. When data moves, money moves. When data is stale, the money goes away, right? I think that trend is continuing, and it's not just the trend is in this space, it's also continuing in other spaces, specifically around, you know, acquisition of customers, communication with customers. It's all becoming digital, and it's, at the end of the day, it's all data being moved from one place or another. At the end of the day, you're not seeing the customer, but you're looking at, you know, the data that he's consuming, and you're making actionable items on it, and be able to respond to what they need. So I think 10 years, it's really, really evolved. >> Hmm, you operate, Western Union operates in more than 200 countries, and you you have what I would call a pseudo federated organization. You're trying to standardize wherever possible on the infrastructure, and you're curating the tooling and doing the heavy lifting in the data stack, which of course lessens the burden on the developers and the line of business consumers, so my question is, in operating in 200 countries, how do you deal with all the diversity of laws and regulations across those regions? I know you're heavily involved in AWS, but AWS isn't everywhere, you still have some on-prem infrastructure. Can you paint a picture of, you know, what that looks like? >> Yeah, a few years ago , we were primarily mostly on-prem, and one of the biggest pain points has been managing that infrastructure around the world in those countries. Yes, we operate in 200 countries, but we don't have infrastructure in 200 countries, but we do have agent locations in 200 countries. United Nations says we only have like 183 are countries, but there are countries which, you know, declare themselves countries, and we are there as well because somebody wants to send money there, right? Somebody has an agent location down there as well. So that infrastructure is obviously very hard to manage and maintain. We have to comply by numerous laws, you know. And the last few years, specifically with GDPR, CCPA, data localization laws in different countries, it's been a challenge, right? And one of the things that we did a few years ago, we decided that we want to be in the business of helping our customers move money faster, security, and with complete trust in us. We don't want to be able to, we don't want to be in the business of managing infrastructure. And that's one of the reasons we started to, you know, migrate and move our journey to the cloud. AWS, obviously chosen first because of its, you know, first in the game, has more locations, and more data centers around the world where we operate. But we still have, you know, existing infrastructure, which is in some countries, which is still localized because AWS hasn't reached there, or we don't have a comparable provider there. We still manage those. And we have to comply by those laws. Our data privacy and our data localization tech stack is pretty good, I would say. We manage our data very well, we manage our customer data very well, but it comes with a lot of complexity. You know, we get a lot of requests from European Union, we get a lot of requests from Asia Pacific every pretty much on a weekly basis to explain, you know, how we are taking controls and putting measures in place to make sure that the data is secured and is in the right place. So it's a complex environment. We do have exposure to other clouds as well, like Google and Azure. And as much as we would love to be completely, you know, very, very hybrid kind of an organization, it's still at a stage where we are still very heavily focused on AWS yet, but at some point, you know, we would love to see a world which is not reliant on a single provider, but it's more a little bit more democratized, you know, as and when what I want to use, I should be able to use, and pay-per-use. And the concept started like that, but it's obviously it's now, again, there are like three big players in the market, and, you know, they're doing their own thing. Would love to see them come collaborate at some point. >> Yeah, wouldn't we all. I want to double-click on the whole multi-cloud strategy, but if I understand it correctly, and in a perfect world, everything on-premises would be in the cloud is, first of all, is that a correct statement? Is that nirvana for you or not necessarily? >> I would say it is nirvana for us, but I would also put a caveat, is it's very tricky because from a regulatory perspective, we are a regulated entity in many countries. The regulators would want to see some control if something happens with a relationship with AWS in one country, or with Google in another country, and it keeps happening, right? For example, Russia was a good example where we had to switch things off. We should be able to do that. But if let's say somewhere in Asia, this country decides that they don't want to partner with AWS, and majority of our stuff is on AWS, where do I go from there? So we have to have some level of confidence in our own infrastructure, so we do maintain some to be able to fail back into and move things it needs to be. So it's a tricky question. Yes, it's nirvana state that I don't have to manage infrastructure, but I think it's far less practical than it said. We will still own something that we call it our own where we have complete control, being a financial entity. >> And so do you try to, I'm sure you do, standardize between all the different on-premise, and in this case, the AWS cloud or maybe even other clouds. How do you do that? Do you work with, you know, different vendors at the various places of the stack to try to do that? Some of the vendors, you know, like a Snowflake is only in the cloud. You know, others, you know, whether it's whatever, analytics, or storage, or database, might be hybrid. What's your strategy with regard to creating as common an experience as possible between your on-prem and your clouds? >> You asked a question which I asked when I joined as well, right? Which question, this is one of the most important questions is how soon when I fail back, if I need to fail back? And how quickly can I, because not everything that is sitting on the cloud is comparable to on-prem or is backward compatible. And the reason I say backward compatible is, you know, there are, our on-prem cloud is obviously behind. We haven't taken enough time to kind of put it to a state where, because we started to migrate and now we have access to infrastructure on the cloud, most of the new things are being built there. But for critical application, I would say we have chronology that could be used to move back if need to be. So, you know, technologies like Couchbase, technologies like PostgreSQL, technologies like Db2, et cetera. We still have and maintain a fairly large portion of it on-prem where critical applications could potentially be serviced. We'll give you one example. We use Neo4j very heavily for our AML use cases. And that's an important one because if Neo4j on the cloud goes down, and it's happened in the past, again, even with three clusters, having all three clusters going down with a DR, we still need some accessibility of that because that's one of the biggest, you know, fraud and risk application it supports. So we do still maintain some comparable technology. Snowflake is an odd one. It's obviously there is none on-prem. But then, you know, Snowflake, I also feel it's more analytical based technology, not a transactional-based technology, at least in our ecosystem. So for me to replicate that, yes, it'll probably take time, but I can live with that. But my business will not stop because our transactional applications can potentially move over if need to. >> Yeah, and of course, you know, all these big market cap companies, so the Snowflake or Databricks, which is not public yet, but they've got big aspirations. And so, you know, we've seen things like Snowflake do a deal with Dell for on-prem object store. I think they do the same thing with Pure. And so over time, you see, Mongo, you know, extending its estate. And so over time all these things are coming together. I want to step out of this conversation for a second. I just ask you, given the current macroeconomic climate, what are the priorities? You know, obviously, people are, CIOs are tapping the breaks on spending, we've reported on that, but what is it? Is it security? Is it analytics? Is it modernization of the on-prem stack, which you were saying a little bit behind. Where are the priorities today given the economic headwinds? >> So the most important priority right now is growing the business, I would say. It's a different, I know this is more, this is not a very techy or a tech answer that, you know, you would expect, but it's growing the business. We want to acquire more customers and be able to service them as best needed. So the majority of our investment is going in the space where tech can support that initiative. During our earnings call, we released the new pillars of our organization where we will focus on, you know, omnichannel digital experience, and then one experience for customer, whether it's retail, whether it's digital. We want to open up our own experience stores, et cetera. So we are investing in technology where it's going to support those pillars. But the spend is in a way that we are obviously taking away from the things that do not support those. So it's, I would say it's flat for us. We are not like in heavily investing or aggressively increasing our tech budget, but it's more like, hey, switch this off because it doesn't make us money, but now switch this on because this is going to support what we can do with money, right? So that's kind of where we are heading towards. So it's not not driven by technology, but it's driven by business and how it supports our customers and our ability to compete in the market. >> You know, I think Harvir, that's consistent with what we heard in some other work that we've done, our ETR partner who does these types of surveys. We're hearing the same thing, is that, you know, we might not be spending on modernizing our on-prem stack. Yeah, we want to get to the cloud at some point and modernize that. But if it supports revenue, you know, we'll invest in that, and get the, you know, instant ROI. I want to ask you about, you know, this concept of supercloud, this abstracted layer of value on top of hyperscale infrastructure, and maybe on-prem. But we were talking about the integration, for instance, between Snowflake and Salesforce, where you got different data sources and you were explaining that you had great interest in being able to, you know, have a kind of, I'll say seamless, sorry, I know it's an overused word, but integration between the data sources and those two different platforms. Can you explain that and why that's attractive to you? >> Yeah, I'm a big supporter of action where the data is, right? Because the minute you start to move, things are already lost in translation. The time is lost, you can't get to it fast enough. So if, for example, for us, Snowflake, Salesforce, is our actionable platform where we action, we send marketing campaigns, we send customer communication via SMS, in app, as well as via email. Now, we would like to be able to interact with our customers pretty much on a, I would say near real time, but the concept of real time doesn't work well with me because I always feel that if you're observing something, it's not real time, it's already happened. But how soon can I react? That's the question. And given that I have to move that data all the way from our, let's say, engagement platforms like Adobe, and particles of the world into Snowflake first, and then do my modeling in some way, and be able to then put it back into Salesforce, it takes time. Yes, you know, I can do it in a few hours, but that few hours makes a lot of difference. Somebody sitting on my website, you know, couldn't find something, walked away, how soon do you think he will lose interest? Three hours, four hours, he'll probably gone, he will never come back. I think if I can react to that as fast as possible without too much data movement, I think that's a lot of good benefit that this kind of integration will bring. Yes, I can potentially take data directly into Salesforce, but I then now have two copies of data, which is, again, something that I'm not a big (indistinct) of. Let's keep the source of the data simple, clean, and a single source. I think this kind of integration will help a lot if the actions can be brought very close to where the data resides. >> Thank you for that. And so, you know, it's funny, we sometimes try to define real time as before you lose the customer, so that's kind of real time. But I want to come back to this idea of governed data sharing. You mentioned some other clouds, a little bit of Azure, a little bit of Google. In a world where, let's say you go more aggressively, and we know that for instance, if you want to use Google's AI tools, you got to use BigQuery. You know, today, anyway, they're not sort of so friendly with Snowflake, maybe different for the AWS, maybe Microsoft's going to be different as well. But in an ideal world, what I'm hearing is you want to keep the data in place. You don't want to move the data. Moving data is expensive, making copies is badness. It's expensive, and it's also, you know, changes the state, right? So you got governance issues. So this idea of supercloud is that you can leave the data in place and actually have a common experience across clouds. Let's just say, let's assume for a minute Google kind of wakes up, my words, not yours, and says, "Hey, maybe, you know what, partnering with a Snowflake or a Databricks is better for our business. It's better for the customers," how would that affect your business and the value that you can bring to your customers? >> Again, I would say that would be the nirvana state that, you know, we want to get to. Because I would say not everyone's perfect. They have great engineers and great products that they're developing, but that's where they compete as well, right? I would like to use the best of breed as much as possible. And I've been a person who has done this in the past as well. I've used, you know, tools to integrate. And the reason why this integration has worked is primarily because sometimes you do pick the best thing for that job. And Google's AI products are definitely doing really well, but, you know, that accessibility, if it's a problem, then I really can't depend on them, right? I would love to move some of that down there, but they have to make it possible for us. Azure is doing really, really good at investing, so I think they're a little bit more and more closer to getting to that state, and I know seeking our attention than Google at this point of time. But I think there will be a revelation moment because more and more people that I talk to like myself, they're also talking about the same thing. I'd like to be able to use Google's AdSense, I would like to be able to use Google's advertising platform, but you know what? I already have all this data, why do I need to move it? Can't they just go and access it? That question will keep haunting them (indistinct). >> You know, I think, obviously, Microsoft has always known, you know, understood ecosystems. I mean, AWS is nailing it, when you go to re:Invent, it's all about the ecosystem. And they think they realized they can make a lot more money, you know, together, than trying to have, and Google's got to figure that out. I think Google thinks, "All right, hey, we got to have the best tech." And that tech, they do have the great tech, and that's our competitive advantage. They got to wake up to the ecosystem and what's happening in the field and the go-to-market. I want to ask you about how you see data and cloud evolving in the future. You mentioned that things that are driving revenue are the priorities, and maybe you're already doing this today, but my question is, do you see a day when companies like yours are increasingly offering data and software services? You've been around for a long time as a company, you've got, you know, first party data, you've got proprietary knowledge, and maybe tooling that you've developed, and you're becoming more, you're already a technology company. Do you see someday pointing that at customers, or again, maybe you're doing it already, or is that not practical in your view? >> So data monetization has always been on the charts. The reason why it hasn't seen the light is regulatory pressure at this point of time. We are partnering up with certain agencies, again, you know, some pilots are happening to see the value of that and be able to offer that. But I think, you know, eventually, we'll get to a state where our, because we are trying to build accessible financial services, we will be in a state that we will be offering those to partners, which could then extended to their customers as well. So we are definitely exploring that. We are definitely exploring how to enrich our data with other data, and be able to complete a super set of data that can be used. Because frankly speaking, the data that we have is very interesting. We have trends of people migrating, we have trends of people migrating within the US, right? So if a new, let's say there's a new, like, I'll give you an example. Let's say New York City, I can tell you, at any given point of time, with my data, what is, you know, a dominant population in that area from migrant perspective. And if I see a change in that data, I can tell you where that is moving towards. I think it's going to be very interesting. We're a little bit, obviously, sometimes, you know, you're scared of sharing too much detail because there's too much data. So, but at the end of the day, I think at some point, we'll get to a state where we are confident that the data can be used for good. One simple example is, you know, pharmacies. They would love to get, you know, we've been talking to CVS and we are talking to Walgreens, and trying to figure out, if they would get access to this kind of data demographic information, what could they do be better? Because, you know, from a gene pool perspective, there are diseases and stuff that are very prevalent in one community versus the other. We could probably equip them with this information to be able to better, you know, let's say, staff their pharmacies or keep better inventory of products that could be used for the population in that area. Similarly, the likes of Walmarts and Krogers, they would like to have more, let's say, ethnic products in their aisles, right? How do you enable that? That data is primarily, I think we are the biggest source of that data. So we do take pride in it, but you know, with caution, we are obviously exploring that as well. >> My last question for you, Harvir, is I'm going to ask you to do a thought exercise. So in that vein, that whole monetization piece, imagine that now, Harvir, you are running a P&L that is going to monetize that data. And my question to you is a there's a business vector and a technology vector. So from a business standpoint, the more distribution channels you have, the better. So running on AWS cloud, partnering with Microsoft, partnering with Google, going to market with them, going to give you more revenue. Okay, so there's a motivation for multi-cloud or supercloud. That's indisputable. But from a technical standpoint, is there an advantage to running on multiple clouds or is that a disadvantage for you? >> It's, I would say it's a disadvantage because if my data is distributed, I have to combine it at some place. So the very first step that we had taken was obviously we brought in Snowflake. The reason, we wanted our analytical data and we want our historical data in the same place. So we are already there and ready to share. And we are actually participating in the data share, but in a private setting at the moment. So we are technically enabled to share, unless there is a significant, I would say, upside to moving that data to another cloud. I don't see any reason because I can enable anyone to come and get it from Snowflake. It's already enabled for us. >> Yeah, or if somehow, magically, several years down the road, some standard developed so you don't have to move the data. Maybe there's a new, Mogli is talking about a new data architecture, and, you know, that's probably years away, but, Harvir, you're an awesome guest. I love having you on, and really appreciate you participating in the program. >> I appreciate it. Thank you, and good luck (indistinct) >> Ah, thank you very much. This is Dave Vellante for John Furrier and the entire Cube community. Keep it right there for more great coverage from Supercloud 2. (uplifting music)

Published Date : Jan 6 2023

SUMMARY :

Harvir, it's good to see you again. a pleasure to talk to you. And the pressure to do so is only growing. and you you have what I would call But we still have, you know, you or not necessarily? that I don't have to Some of the vendors, you and it's happened in the past, And so, you know, we've and our ability to compete in the market. and get the, you know, instant ROI. Because the minute you start to move, and the value that you can that, you know, we want to get to. and cloud evolving in the future. But I think, you know, And my question to you So the very first step that we had taken and really appreciate you I appreciate it. Ah, thank you very much.

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Breaking Analysis: Cloudflare’s Supercloud…What Multi Cloud Could Have Been


 

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 over the past decade cloudflare has built a Global Network that has the potential to become the fourth us-based hyperscale class cloud in our view the company is building a durable Revenue model with hooks into many important markets these include the more mature DDOS protection space to other growth sectors such as zero trust a serverless platform for application development and an increasing number of services such as database and object storage and other network services in essence cloudflare could be thought of as a giant distributed supercomputer that can connect multiple clouds and act as a highly efficient scheduling engine at scale its disruptive DNA is increasingly attracting novel startups and established Global firms alike looking for Reliable secure high performance low latency and more cost-effective alternatives to AWS and Legacy infrastructure Solutions hello and welcome to this week's wikibon Cube insights powered by ETR in this breaking analysis we initiate our deeper coverage of cloudflare we'll briefly explain our take on the company and its unique business model we'll then share some peer comparisons with both the financial snapshot and some fresh ETR survey data finally we'll share some examples of how we think cloudflare could be a disruptive force with a super cloud-like offering that in many respects is what multi-cloud should have been cloudflare has been on our peripheral radar Ben Thompson and many others have written about their disruptive business model and recently a breaking analysis follower who will remain anonymous emailed with some excellent insights on cloudflare that prompted us to initiate more detailed coverage let's first take a look at how cloudflare seize the world in terms of its view of a modern stack this is a graphic from cloudflare that shows a simple three-layer Stack comprising Storage and compute the lower level and application layer and the network and their key message is basically that the big four hyperscalers have replaced the on-prem leaders apps have been satisfied and that mess of network that you see and Security in the upper left can now be handled all by cloudflare and the stack can be rented via Opex versus requiring heavy capex investment so okay somewhat of a simplified view is those companies on the the left are you know not standing still and we're going to come back to that but cloudflare has done something quite amazing I mean it's been a while since we've invoked Russ hanneman of Silicon Valley Fame on breaking analysis but remember when he was in a meeting one of his first meetings if not the first with Richard Hendricks it was the whiz kid on the show Silicon Valley and hanneman said something like if you had a blank check and you could build anything in the world what would it be and Richard's answer was basically a new internet and that led to Pied Piper this peer-to-peer Network powered by decentralized devices and and iPhones and this amazing compression algorithm that enabled high-speed data movement and low latency uh up to no low latency access across the network well in a way that's what cloudflare has built its founding premise reimagined how the internet should be built with a consistent set of server infrastructure where each server had lots of cores lots of dram lots of cash fast ssds and plenty of network connectivity and bandwidth and well this picture makes it look like a bunch of dots and points of presence on a map which of course it is there's a software layer that enables cloudflare to efficiently allocate resources across this Global Network the company claims that it's Network utilization is in the 70 percent range and it has used its build out to enter the technology space from the bottoms up offering for example free tiers of services to users with multiple entry points on different services and selling then more services over time to a customer which of course drives up its average contract value and its lifetime value at the same time the company continues to innovate and add new services at a very rapid cloud-like Pace you can think of cloudflare's initial Market entry as like a lightweight Cisco as a service the company's CFO actually he uses that term he calls it that which really must tick off Cisco who of course has a massive portfolio and a dominant Market position now because it owns the network cloudflare is a marginal cost of adding new Services is very small and goes towards zero so it's able to get software like economics at scale despite all this infrastructure that's building out so it doesn't have to constantly face the increasing infrastructure tax snowflake for example doesn't own its own network infrastructure as it grows it relies on AWS or Azure gcp and and while it gives the company obvious advantages it doesn't have to build out its own network it also requires them to constantly pay the tax and negotiate with hyperscalers for better rental rates now as previously mentioned Cloud Fair cloudflare claims that its utilization is very high probably higher than the hyperscalers who can spin up servers that they can charge for underutilized customer capacity cloudflare also has excellent Network traffic data that it can use to its Advantage with its Analytics the company has been rapidly innovating Beyond its original Core Business adding as I said before serverless zero trust offerings it has announced a database it calls its database D1 that's pretty creative and it's announced an object store called R2 that is S3 minus one both from the alphabet and the numeric I.E minus the egress cost saying no egress cost that's their big claim to fame and they've made a lot of marketing noise around about that and of course they've promised in our a D2 database which of course is R2D2 RR they've launched a developer platform cloudflare can be thought of kind of like first of all a modern CDN they've got a simpler security model that's how they compete for example with z-scaler that brings uh they also bring VPN sd-wan and DDOS protection services that are that are part of the network and they're less expensive than AWS that's kind of their sort of go to market and messaging and value proposition and they're positioning themselves as a neutral Network that can connect across multiple clouds now to be clear unlike AWS in particular cloudflare is not well suited to lift and shift your traditional apps like for instance sap Hana you're not going to run that in on cloudflare's platform rather the company started by making websites more secure and faster and it flew under the radar and much in the same way that clay Christensen described the disruption in the steel industry if you've seen that where new entrants picked off the low margin rebar business then moved up the stack we've used that analogy in the semiconductor business with arm and and even China cloudflare is running a similar playbook in the cloud and in the network so in the early part of the last decade as aws's ascendancy was becoming more clear many of us started thinking about how and where firms could compete and add value as AWS is becoming so dominant so for instance take an industry Focus you could do things like data sharing with snowflake eventually you know uh popularized you could build on top of clouds again snowflake is doing that as are others you could build private clouds and of course connect to hybrid clouds but not many had the wherewithal and or the hutzpah to build out a Global Network that could serve as a connecting platform for cloud services cloudflare has traction in the market as it adds new services like zero trust and object store or database its Tam continues to grow here's a quick snapshot of cloudflare's financials relative to Z scalar which is both a competitor and a customer fastly which is a smaller CDN and Akamai a more mature CDN slash Edge platform cloudflare and fastly both reported earnings this past week Cloud Fair Cloud flare surpassed a billion dollar Revenue run rate but they gave tepid guidance and the stock got absolutely crushed today which is Friday but the company's business model is sound it's growing close to 50 annually it has sas-like gross margins in the mid to high 70s and it's it it's got a very strong balance sheet and a 13x revenue run rate multiple in fact it's Financial snapshot is quite close to that of z-scaler which is kind of interesting which zinc sailor of course doesn't own its own network that's a pure play software company fastly is much smaller and growing more slowly than cloudflare hence its lower multiple well Akamai as you can see is a more mature company but it's got a nice business now on its earnings call this week cloudflare announced that its head of sales was stepping down and the company has brought in a new leader to take the firm to five billion dollars in sales I think actually its current sales leader felt like hey you know my work is done here bring on somebody else to take it to the next level the company is promising to be free cash flow positive by the end of the year and is working hard toward its long-term financial model or so working towards sorry it's a long-term financial model with gross margin Targets in the mid 70s it's targeting 20 non-gaap operating margins so so solid you know very solid not like completely off the charts but you know very good and to our knowledge it has not committed to a long-term growth rate but at that sort of operating profit level you would like to see growth be consistently at least in the 20 range so they could at least be a rule of 40 company or perhaps even even five even higher if they're going to continue to command a premium valuation okay let's take a look at the ETR data ETR is very positive on cloudflare and has recently published a report on the company like many companies cloudflare is seeing an across the board slowdown in spending velocity we've reported on this quite extensively using the ETR data to quantify the degree to that Slowdown and on the data set with ETR we see that many customers they're shifting their spend to Flat spend you know plus or minus let's say you know single digits you know two three percent or even zero or in the market we're seeing a shift from paid to free tiers remember cloudflare offers a lot of free services as you're seeing customers maybe turn off the pay for a while and going with the freebie but we're also seeing some larger customers in the data and the fortune 1000 specifically they're actually spending more which was confirmed on cloudflare's earnings call they did say everything across the board was softer but they did also indicate that some of their larger customers are actually growing faster than their smaller customers and their churn is very very low here's a two-dimensional graphic we'd like to share this view a lot it's got Net score or spending momentum on the vertical axis and overlap or pervasiveness in the survey on the horizontal axis and this cut isolates three segments in the etrs taxonomy that cloudflare plays in Cloud security and networking now the table inserted in that upper left there shows the raw data which informs the position of each company in the dots with Net score in the ends listed in that rightmost column the red dotted line indicates a highly elevated Net score and finally we posted the breakdown those colors in the bottom right of cloudflare's Net score the lime green that's new adoptions the forest green is we're spending more six percent or more the gray is flat plus or minus uh five percent and you can see that the majority of customers you can see that's the majority of the customers that gray area the pink is we're spending Less in other words down six percent or worse and the bright red is churn which is minimal one percent very good indicator for for cloudflare what you do to get etr's proprietary Net score and they've done this for many many quarters so we have that time series data you subtract the Reds from the greens and that's Net score cloudflare is at 39 just under that magic red line now note that cloudflare and zscaler are right on top of each other Cisco has a dominant position on the x-axis that cloudflare and others are eyeing AWS is also dominant but note that its Net score is well above the red dotted line it's incredible Palo Alto networks is also very impressive it's got both a strong presence on the horizontal axis and it's got a Net score that's pretty comparable to cloudflare and z-scaler to much smaller companies Akamai is actually well positioned for a reasonably mature company and you can see fastly ATT Juniper and F5 have far less spending momentum on their platforms than does cloudflare but at least they are in positive Net score territory so what's going to be really interesting to see is whether cloudflare can continue to hold this momentum or even accelerate it as we've seen with some other clouds as it scales its Network and keeps adding more and more services cloudflare has a couple of potential strategic vectors that we want to talk about and it'll be going to be interesting to see how that plays out Now One path is to compete more directly as a Cloud Player offering secure access Edge services like firewall as a service and zero Trust Services like data loss prevention email security from its area one acquisition and other zero trust offerings as well as Network Services like routing and network connectivity this is The Sweet Spot of the company load balancing many others and then add in things like Object Store and database Services more Edge services in the future it might be telecom like services such as Network switching for offices so that's one route and cloudflare is clearly on that path more services more cohorts at innovating and and growing the company and bringing in more Revenue increasing acvs and and increasing long-term value and keeping retention high now the other Vector is what we're just going to refer to as super cloud as an enabler of cross-cloud infrastructure this is new value uh relative to the former Vector that we were just talking about now the title of this episode is what multi-cloud should have been meaning cloudflare could be the control plane providing a consistent experience across clouds one that is fast and secure at global scale now to give you Insight on this let's take a look at some of the comments made by Matthew Prince the CEO and co-founder of cloudflare cloudflare put its R2 Object Store into public beta this past May and I believe it's storing around a petabyte of data today I think that's what they said in their call here's what Prince said about that quote we are talking to very large companies about moving more and more of their stored objects to where we can store that with R2 and one of the benefits is not only can we help them save money on the egress fees but it allows them to then use those object stores or objects across any of the different Cloud platforms they're that they're using so by being that neutral third party we can let people adopt a little bit of Amazon a little bit of Microsoft a little bit of Google a little bit of SAS vendors and share that data across all those different places so what's interesting about this in the super cloud context is it suggests that customers could take the best of each Cloud to power their digital businesses I might like AWS for in redshift for my analytic database or I love Google's machine learning Microsoft's collaboration and I'd like a consistent way to connect those resources but of course he's strongly hinting and has made many public statements that aws's egress fees are a blocker to that vision now at a recent investor event Matthew Prince added some color to this concept when he talked about one metric of success being how much R2 capacity was consumed and how much they sold but perhaps a more interesting Benchmark is highlighted by the following statement that he made he said a completely different measure of success for R2 is Andy jassy says I'm sick and tired of these guys meaning cloudflare taking our objects away we're dropping our egress fees to zero I would be so excited because we've then unlocked the ability to be the network that interconnects the cloud together now of course it would be Adam solipski who would be saying that or maybe Andy Jesse you know still watching over AWS and I think it's highly unlikely that that's going to happen anytime soon and that of course but but in theory gets us closer to the super cloud value proposition and to further drive that point home and we're paraphrasing a little bit his comments here he said something the effect of quote customers need one consistent control plane across clouds and we are the neutral Network that can be consistent no matter which Cloud you're using interesting right that Prince sees the world that's similar to if not nearly identical to the concepts that the cube Community has been putting forth around supercloud now this vision is a ways off let's be real Prince even suggested that his initial vision of an application running across multiple clouds you know that's like super cloud Nirvana isn't what customers are doing today that's that's really hard to do and perhaps you know it's never going to happen but there's a little doubt that cloudflare could be and is positioning itself as that cross-cloud control plane it has the network economics and the business model levers to pull it's got an edge up on the competition at the edge pun intended cloudflare is the definition of Edge and it's distributed platform it's decentralized platform is much better suited for Edge workloads than these giant data centers that are you know set up to to try and handle that today the the hyperscalers are building out you know their Edge networks things like outposts you know going out to the edge and other local zones Etc now cloudflare is increasingly competitive to the hyperscalers and those traditional Stacks that it depositioned on an earlier slide that we showed but you know the likes of AWS and Dell and hpe and Cisco and those others they're not sitting in their hands they have a huge huge customer install bases and they are definitely a moving Target they're investing and they're building out their own Super clouds with really robust stacks as well let's face it it's going to take a decade or more for Enterprises to adopt a developer platform or a new database Cloud plus cloudflare's capabilities when compared to incumbent stacks and the hyperscalers is much less robust in these areas and even in storage you know despite all the great conversation that R2 generated and the buzz you take a specialist like Wasabi they're more mature they're more functional and they're way cheaper even than cloudflare so you know it's not a fake a complete that cloudflare is going to win in those markets but we love the disruption and if cloudflare wants to be the fourth us-based hyperscaler or join the the big four as the as the fifth if we put Alibaba in the mix it's got a lot of work to do in the ecosystem by its own admission as much to learn and is part of the value by the way that it sees in its area one acquisition it's email security company that it bought but even in that case much of the emphasis has been on reseller channels compare that to the AWS ecosystem which is not only a channel play but is as much an innovation flywheel filling gaps where companies like snowflake Thrive side by side with aws's data stores as well all the on-prem stacks are building hybrid connections to AWS and other clouds as a means of providing consistent experiences across clouds indeed many of them see what they call cross-cloud services or what we call super cloud hyper cloud or whatever you know Mega Cloud you want to call it we use super cloud they are really eyeing that opportunity so very few companies frankly are not going after that space but we're going to close with this cloudflare is one of those companies that's in a position to wake up each morning and ask who can we disrupt today and very few companies are in a position to disrupt the hyperscalers to the degree that cloudflare is and that my friends is going to be fascinating to watch unfold all right let's call it a wrap I want to thank Alex Meyerson who's on production and manages the podcast as well as Ken schiffman who's our newest addition to the Boston Studio Kristen Martin and Cheryl Knight help us get the word out on social media and in our newsletters and Rob Hof is our editor-in-chief over at silicon angle thank you to all remember all these episodes are available as podcasts wherever you listen all you're going to do is search breaking analysis podcasts I publish each week on wikibon.com and siliconangle.com you can email me at david.velante at siliconangle.com or DM me at divalante if you comment on my LinkedIn posts and please do check out etr.ai they got the best survey data in the Enterprise Tech business this is Dave vellante for the cube insights powered by ETR thank you very much for watching and we'll see you next time on breaking analysis

Published Date : Nov 5 2022

SUMMARY :

that the majority of customers you can

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Keith Townsend, The CTO Advisor & James Urquhart, VMware | VMware Explore 2022


 

>>Okay, welcome back everyone. Day three of the cube coverage here at VMware VMware Explorer, not world 12 years. The Cube's been covering VMware is end user conference this year. It's called explore previously world. We got two great guests, friends of the cube friend, cube, alumni and cloud rod, Keith Townson, principal CTO advisor, air streaming his way into world this year in a big way. Congratulations. And course James Erhard principal technology, a at tan zoo cloud ARA. He's been in cloud game for a long time. We've known each other for a long, long time, even before cloud was cloud. So great to see you guys. Thanks for coming on. >>Ah, it's a pleasure, always happy to >>Be here. So day threes are kind of like riff. I'll throw out super cloud. You guys will, will trash it. We'll debate. It'll be controversial and say this damage done by the over rotation of developer experience. We'll defend Tansu, but really the end of the game is, is that guys, we have been on the cloud thing for a long time. We're we're totally into it. And we've been saying infrastructure is code as the end state. We want to get there. Right? DevOps and infrastructure is code has always been the, the, the underlying fire burning in, in all the innovation, but it's now getting legitimately enterprised it's adopted in, in, in large scale, Amazon web services. We saw that rise. It feels we're in another level right now. And I think we're looking at this new wave coming. And I gotta say, you know, the Broadcom thing has put like an electric shock syndrome into this ecosystem cuz they don't know what's gonna happen next. So as a result, everyone's kind of gotta spring in their step a little, whether it's nervous, energy or excitement around something happening, it's all cloud native. So, you know, as VMware's got such a great investment in cloud native, but yet multi cloud's the story. Right? So, so messaging's okay. So what's happening here? Like guys let's, let's break it down. You're on the show floor of the Airstream you're on the inside, but with the seeing the industry, James will start with you what's happening this year with cloud next level and VMware's future. >>Yeah, I think the big thing that is happening is that we are beginning to see the true separation of capacity delivery from capacity consumption in computing. And what I mean by that is the, the abstractions that sort of bled between the idea of a server and the idea of an application have sort of become separated much better. And I think Kubernetes is, is the strong evidence of that. But also all of the public cloud APIs are strong evidence of that. And VMware's APIs, frankly, before that we're strong evidence of that. So I think what's, what's starting to happen now then is, is developers have really kind of pulled very far away from, from anything other than saying, I need compute, I need network. I need storage. And so now you're seeing the technologies that say, well, we've figured out how to do that at a team level, like one team can automate an application to an environment, but another team will, you know, other teams, if I have hundreds of teams or, or thousands of applications, how do I handle that? And that's what the excitement I think is right >>Now. I mean the, the developer we talking, we're going on camera before you came on camera Keith around, you know, your contr statement around the developer experience. Now we, I mean, I believe that the cloud native development environment is doing extremely well right now. You talk to, you know, look around the industry. It's, it's at an all time high and relative to euphoria, you know, sit on the beach with sunglasses. You couldn't be better if you were a developer open source, booming, everything's driving to their doorstep, self service. They're at the center of the security conversation, which shift left. Yeah. There's some things there, but it's, it's a good time. If you're a developer now is VMware gonna be changing that and, and you know, are they gonna meet the developers where they are? Are they gonna try to bring something new? So these are conversations that are super important. Now VMware has a great install base and there's developers there too. So I think I see their point, but, but you have a take on this, Keith, what's your, what's your position on this? How do the developer experience core and tangential played? >>Yeah, we're I think we're doing a disservice to the industry and I think it's hurting and, or D I think I'm gonna stand by my statement. It's damaging the in industry to, to an extent VMware >>What's damaging to the >>Industry. The focusing over focusing on developer experience developer experience is super important, but we're focusing on developer experience the, the detriment of infrastructure, the infrastructure to deliver that developer experience across the industry isn't there. So we're asking VMware, who's a infrastructure company at core to meet the developer where the developer, the developer is at today with an infrastructure that's not ready to deliver on the promise. So when we're, when NetApp is coming out with cool innovations, like adding block storage to VMC on AWS, we collectively yawn. It's an amazing innovation, but we're focused on, well, what does that mean for the developer down the road? >>It should mean nothing because if it's infrastructure's code, it should just work, right. >>It should just work, but it doesn't. Okay. >>I see the damage there. The, >>The, when you're thinking, oh, well I should be able to just simply provide Dr. Service for my on-prem service to this new block level stores, because I can do that in a enterprise today. Non-cloud, we're not there. We're not at a point where we can just write code infrastructure code and that happens. VMware needs the latitude to do that work while doing stuff like innovating on tap and we're, you know, and then I think we, we, when buyers look at what we say, and we, we say VMware, isn't meeting developers where they're at, but they're doing the hard work of normalizing across clouds. I got off a conversation with a multi-cloud customer, John, the, the, the, the unicorn we all talk about. And at the end I tried to wrap up and he said, no, no, no way. I gotta talk about vRealize. Whoa, you're the first customer I heard here talk about vRealize and, and the importance of normalizing that underlay. And we just don't give these companies in this space, the right >>Latitude. So I'm trying to, I'm trying to rock a little bit what you're saying. So from my standpoint, generically speaking, okay. If I'm a, if the developers are key to the, to the cloud native role, which I, I would say they are, then if I'm a developer and I want, and I want infrastructure as code, I'm not under the hood, I'm not getting the weeds in which some lot people love to do. I wanna just make things work. So meet me where I'm at, which means self-service, I don't care about locking someone else should figure that problem out, but I'm gonna just accelerate my velocity, making sure it's secure. And I'm moving on being creative and doing my thing, building apps. Okay. That's the kind of the generic, generic statement. So what has to happen in your mind to >>Get there? Yeah. Someone, someone has to do the dirty work of making the world move as 400, still propagate the data center. They're still H P X running SAP, E there's still, you know, 75% of the world's transactions happen through SAP. And most of that happens on bare metal. Someone needs to do the plumbing to give that infrastructure's cold world. Yeah. Someone needs to say, okay, when I want to do Dr. Between my on premises edge solution and the public cloud, someone needs to make it invisible to the Kubernetes, the, the Kubernetes consuming that, that work isn't done. Yeah. It >>Is. It's an >>Opportunity. It's on paper. >>It's an opportunity though. It's not, I mean, we're not in a bad spot. So I mean, I think what you're getting at is that there's a lot of fix a lot of gaps. All right. I want Jay, I wanna bring you in, because we had a panel at super cloud event. Chris Hoff, you know, beaker was on here. Yeah. He's always snarky, but he's building, he's been building clouds lately. So he's been getting his, his hands dirty, rolling up his sleeves. The title of panel was originally called the innovators dilemma with a question, mark, you know, haha you know, innovators, dilemma, little goof on that. Cuz you know, there's challenges and trade offs like, like he's talking about, he says we should call it the integrator's dilemma because I think a lot of people are talking about, okay, it's not as seamless as it can be or should be in the Nirvana state. >>But there's a lot of integration going on. A lot of APIs are, are key to this API security. One of the most talked about things. I mean I interviewed six companies on API security in the past couple months. So yeah. I mean I never talked to anybody about API security before this year. Yeah. APIs are critical. So these key things of cloud are being attacked. And so there's more complexity as we're getting more successful. And so, so I think this is mucking up some of the conversations, what's your read on this to make the complexity go away. You guys have the, the chaos rain here, which I actually like that Dave does too, but you know, Andy Grove once said let chaos rain and then rain in the chaos. So we're in that reign in the chaos mode. Now what's your take on what Keith was saying around. Yeah. >>So I think that the one piece of the puzzle that's missing a little bit from Keith's narrative that I think is important is it's really not just infrastructure and developers. Right? It's it's there's in fact, and, and I, I wrote a blog post about this a long time ago, right? There's there's really sort of three layers of operations that come out of the cloud model in long term and that's applications and infrastructure at the bottom and in the middle is platform and services. And so I think one of the, this is where VMware is making its play right now is in terms of providing the platform and service capability that does that integration at a lower level works with VMs works with bare metal, works with the public cloud services that are available, makes it easy to access things like database services and messaging services and things along those lines. >>It makes it easy to turn code that you write into a service that can be consumed by other applications, but ultimately creates an in environment that begins to pull away from having to know, to write code about infrastructure. Right. And so infrastructure's, code's great. But if you have a right platform, you don't have to write code about infrastructure. You can actually D declare what basic needs of the application are. And then that platform will say, okay, well I will interpret that. And that's really, that's what Kubernetes strength is. Yeah. And that's what VMware's taking advantage of with what we're doing >>With. Yeah. I remember when we first Lou Tucker and I, and I think you might have been in the room during those OpenStack days and when Kubernetes was just starting and literally just happened, the paper was written, gonna go out and a couple companies formed around it. We said that could be the interoperability layer between clouds and our, our dream at that time was Hey. And, and we, we mentioned and Stratus in our, our super cloud, but the days of spanning clouds, a dream, we thought that now look at Kubernetes. Now it's kind of become that defacto rallying moment for, I won't say middleware, but this abstraction that we've been talking about allows for right once run anywhere. I think to me, that's not nowhere in the market today. Nobody has that. Nobody has anything that could write once, read one, write once and then run on multiple clouds. >>It's more true than ever. We had one customer that just was, was using AKs for a while and then decided to try the application on EKS. And they said it took them a couple of hours to, to get through the few issues they ran into. >>Yeah. I talked to a customer who who's going from, who went from VMC on AWS to Oracle cloud on Oracle cloud's VMware solution. And he raved about now he has a inherent backup Dr. For his O CVS solution because there's a shim between the two. And >>How did he do >>That? The, there there's a solution. And this is where the white space is. James talked about in the past exists. When, when I go to a conference like Cuban, the cube will be there in, in Detroit, in, in, in about 45 days or so. I talk to platform group at the platform group. That's doing the work that VMware red had hash Corp all should be doing. I shouldn't have to build that shim while we rave and, and talk about the power Kubernetes. That's great, but Kubernetes might get me 60 to 65% of their, for the platform right now there's groups of developers within that sit in between infrastructure and sit in between application development that all they do is build platforms. There's a lot of opportunity to build that platform. VMware announced tap one, 1.3. And the thing that I'm surprised, the one on Twitter is talking about is this API discovery piece. If you've ever had to use an API and you don't know how to integrate with it or whatever, and now it, it just magically happens. The marketing at the end of developing the application. Think if you're in you're, you're in a shop that develops hundreds of applications, there's thousands or tens of thousands of APIs that have to be documented. That's beating the developer where it's at and it's also infrastructure. >>Well guys, thanks for coming on the cube. I really appreciate we're on a time deadline, which we're gonna do more. We'll follow up on a power panel after VMware Explorer. Thanks for coming on the cube. Appreciate it. No problem. See you pleasure. Yeah. Okay. We'll be back with more live coverage. You, after this short break, stay with us.

Published Date : Sep 1 2022

SUMMARY :

So great to see you guys. And I gotta say, you know, the Broadcom thing has put like an electric shock syndrome into this ecosystem And I think Kubernetes is, It's, it's at an all time high and relative to euphoria, you know, sit on the beach with sunglasses. It's damaging the in industry the detriment of infrastructure, the infrastructure to deliver that developer It should just work, but it doesn't. I see the damage there. VMware needs the latitude to If I'm a, if the developers are key to the, to the cloud native role, Between my on premises edge solution and the public cloud, It's on paper. it the integrator's dilemma because I think a lot of people are talking about, okay, I mean I interviewed six companies on API security in the past couple months. that come out of the cloud model in long term and that's applications and infrastructure It makes it easy to turn code that you write into a service that can be consumed by other applications, We said that could be the interoperability layer between clouds and our, our dream at that time was Hey. And they said it took them a couple of hours to, to get through the few issues they ran into. And he raved about now And the thing that I'm surprised, Thanks for coming on the cube.

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Chris Wolf, VMware | VMware Explore 2022


 

>>Hey guys. Good morning. And welcome back to the cube. Lisa Martin here with John furrier. This is the Cube's third day of Wal Dal coverage of VMware Explorer. We're very pleased to welcome one of our alumni back to the program. Chris Wolf joins us chief research and innovation officer at VMware. Chris, welcome back to the >>Cube. Yeah. Thanks Lisa. It's always a pleasure. >>This has been a great event. We, we, the key note was standing room only on Tuesday morning. We've had great conversations with VMware's ecosystem and VMware of course, what are some of the, the hot things going on from an R and D perspective? >>Yeah, there's, there's a lot. I mean, we're, we have about four or five different priorities. And these look at this is looking at sovereign clouds and multi-cloud edge computing, modern applications and data services. We're doing quite a bit of work in machine learning as well as insecurity. So we're, we're relatively large organization, but at the same time, we really look to pick our bets. So when we're doing something in ML or security, then we wanna make sure that it's high quality and it's differentiated and adds value for VMware, our partners and our customers. >>Where are our customers in the mix in terms of being influential in the roadmap? >>Very, very much in the mix. What we, what we like to do is in early stage R and D, we want to have five to 10 customers as design partners. And that really helps. And in addition to that, as we get closer to go to market, we look to a lineup between one and three of our SI partners as well, to really help us, you know, in a large company, sometimes your organic innovations can get lost in the shuffle. Yeah. And when we have passionate SI that are like, yes, we want to take this forward with you together. That's just awesome. And it also helps us to understand at a very early stage, what are the integration requirements? So we're not just thinking about the, the core product itself, but how would it play in the ecosystem equally important? >>We had hit Culbert on CTO, great work. He's dealing with the white paper and cross cloud, obviously vSphere, big release, lot of this stuff. Dave ante had mentioned that in the analyst session, you had a lot of good stuff you were talking about. That's coming around the corner. That's shipping coming outta the oven and a big theme this year is multi-cloud cloud native. The relationship what's one's ahead. Bleed dog. No one, you kinda get a feel for multi-cloud. It's kind of out front right now, but now cloud native's got the most history what's coming out of the oven right now in terms of hitting the market. That's not yet in this, in the, in the, in the numbers, in terms of sales, like there's, there's some key cloud native stuff coming out. Where's the action. Can you share what you've shared at the analyst meeting? >>Yeah. So at the analyst meeting, what I was going through was a number of our new innovation projects or projects. And, and these are things that are typically close to being product or service at VMware, you know, somewhere in the year out timeframe. Some, some of these are just a few months out. So let me just go through some of them, I'll start with project keek. So keek is super exciting because when you think about edge, what we're hearing from customers is the, the notion of a single platform, a single piece of hardware that can run their cloud services, their containers, their VMs, their network, and security functions. Doing all of this on one platform, gives them the flexibility that as changes happen, it's a software update. They don't have to buy another piece of hardware, but if we step back, what's the management experience you want, right? >>Simple get ops oriented, simple life cycle and configuration management, very low touch. I don't need technical skills to deploy these types of devices. So this is where keek comes in. So what keek is doing is exposing a Kubernetes API above the ESXi hypervisor and taking a complete, get op style of management. So imagine now, when you need to do an update for infrastructure, you're logging into GitHub, you're editing a YAML file and pushing the update. We're doing the same thing for the applications that reside. I can do all of this through GitHub. So this is very, I would say, even internally disruptive to VMware, but super exciting for our customers and partners that we've shared this with. >>What else is happening? What else on the cloud native side Tansu Monterey those lot areas. >>Oh, there's so much. So if we look at project Monterey, I had a presentation within Invidia yesterday. We're really talking through this. And what I'm seeing now is there's a couple of really interesting inflection points with DPU. The first thing is the performance that you're getting and the number of cores that you can save on an X 86 host is actually providing a very strong business case now to bring DPU into the servers, into the data center. So that's one. So now you have a positive ROI. Number two, you start to decouple core services now from the X 86 host itself. So think about a distributed firewall that I can run on a PCI adapter. Now that's DEC coupled, physically from the server, and it really allows me to scale out east west security in a way that I could not do before. So again, I think that's really exciting and that's where we're seeing a lot of buzz from customers. >>So that DPU, which got a lot of buzz, by the way, Lisa, I never, you had trouble interviews on this. I had to the Dell folks too, V X RS taking the advantage of it, the performances, I see the performance angle on that and deep user hot. Can you talk about that security east west thing? Cuz Tom Gillis was on yesterday talking about that's a killer advantage for the security side. Can you touch on that real >>Quick? Yeah. A hundred percent. So what I can now do is take a, a firewall and run it isolated from the X 86 host that it's trying to protect. So it's right next to the host. I can get line rate speeds in terms of analytics and processing of my network and security traffic. So that's also huge. So I'm running line rate on the host and I'm able to run one of these firewall instances on every host in my data center, you cannot do that. You can never afford it with physical appliances. So to me, this is an inflection point because this is the start of network and security functions moving off of hardware appliances and onto DPU. And if you're the ecosystem vendors, this is how they're going to be able to scale some of their services and offerings into the public >>Cloud. So a lot of good stuff happening within the VMware kind of the hardware, low level atoms and the bits as well as the software. The other thing I wanna get your thoughts on relative to the next question is that takes to the next level is the super cloud world we're living in is about cloud native developers, which is DevOps dev security ops and data ops are now big parts of the, the challenges that the people are reigning in the chaos that that's being reigned in. How does VMware look at the relationship to the cloud providers? Cause we heard cloud universal. We had the cloud. If you believe in multi-cloud, which you guys are saying, people are agreeing with, then you gotta have good tight couple coupled relationships with the cloud services, >>A hundred percent. >>We can be decoupled, but highly cohesive, but you gotta connect in via APIs. What's the vision for the VMware customers who want to connect say AWS, for instance, is that seamless? What makes that happen? What's that roadmap look like for taking that VMware on premises hybrid and making it like turbo charging it to be like public cloud hybrid together? >>Yeah, I think there's some lessons that can be learned here. You know, an analogy I've been using lately is look at the early days of virtualization when VMware had vCenter, right? What was happening was you saw the enterprise management vendors try to do this overlay above virtualization management and say, we can manage all hypervisors. And at the end of the day, these multi hypervisor managers, no one bought 'em because they can do 20% of the functionality of a tool from VMware or Microsoft. And that's the lesson that we have to take to multi-cloud. We don't have to overlay every functionality. There's really good capabilities that the cloud providers are offering through their own tooling and APIs. Right? But you, you, if you step back, you say, well, what do I wanna centralize? I wanna have a centralized, secure software supply chain and I can get that through VMware tan zoo and, and where we're going with Kubernetes. When you're going with native cloud services, you might say, you know what, I wanna have a central view of, of visibility for compliance. So that's what we're doing with secure state or a central view of cost management. And we're doing that with cloud health. So you can have some brokering and governance, but then you also have to look from a surgical perspective as to what are the things that I really need to centralize versus what do I not need to centralize? >>One of the themes that we heard on the keynote on Tuesday was the, the different phases and that a lot of customers are still in the cloud chaos phase. We talked a lot about that in the last couple days with VMware, with its partner ecosystem. And, but the goal of getting to cloud smart, how does the R and D organization, how do, how are you helping customers really navigate that journey from the chaos that they're in, maybe they've inherited multi-cloud environment to getting to cloud smart. And what does cloud smart mean from your perspective >>Cloud? Smartt from my perspective means pragmatism. It means really thinking about what should I do here first, right? I don't want to just go somewhere because I can, right. I want to be really mindful of the steps I'm going to take. So one ex one example of this is I've met with a customer this morning and we were talking about using our vRealize network insight tool, because what that allows 'em to do is get a map of all of their application dependencies in their data center. And they can learn like, well, I can move this to the cloud or maybe I can't move this cuz it has all these other dependencies and it would be really difficult. So that's that's one example. It also means really thinking through issues around data sovereignty, you know, what do I wanna hold onto a customer? I just met with yesterday. They were talking about how valuable their data is and their services that they want to use via SA in the cloud. But then there's also services, which is their core research. They wanna make sure that they can maintain that in their data centers and maintain full control because they see researchers will leave. And now all of a sudden, so that intellectual property has actually gone with the person and they need to, they need to have, you know, better accountability there. >>Yeah. One of the things about that we discovered at our super cloud event was is that, you know, we kind didn't really kind of put too much structure on other than our, our vision. It's, it's not just SaaS on cloud and it's not just, multi-cloud, it's a new kind of application end state or reality that if you believe in digital transformation, then technology is everywhere. And like it in the old days, it powered the back office and then terminals and PCs and whatnot, wasn't powering the boardroom obviously or other business. But if, if it happens like that digital transformation, the company is the app, the app is the company. So you're all digital. So that means the operating expenses has to drive an income statement and the CapEx handled by the cloud provides a lot of goodness. So I think everyone's gonna realize that AWS and the hyperscalers are providing great CapEx gifts. They do all the work and you only pay when you've made your success. So that's a great business model. >>Absolutely >>That's and then combine that with open source, which is now growing so fast, going next level, the software industry's open source. That's not even a debate Mo in some circles, maybe like telco, cloud's got the CapEx. The new operating model is this cloud layer. That's going to transform the companies finally in a hundred percent. Okay. That's super cloud. If that's the case, does it really matter who provides the electricity or the power? It's the coders that are in charge. It's the developers that have to make the calls because if the application is the core, the developers are, are not only the front lines, they are the company. This is really kind of where the sea change is. So if, if we believe that, I'm sure you, you agree with that generally? >>Yeah, of >>Course. Okay. So then what's the VMware customer roadmap here. So to me, that's the big story here at the show is that we're at this point in time where the VMware customers are, have to go there >>A hundred percent, >>What's that path. What is the path for the VMware customer to go from here to there? And what's this order of operations or is there a roadmap? Can, can you share your thoughts on >>That? Yeah, I think part of it is, is with these disruptive technologies, you have to start small, you know, whether it's in your data center, into cloud, you have to build the own institutional knowledge of your team members in the organization. It's much easier than trying to attract outside talent, for least for many of our customers. So I think that's important. The other part of this when with the developer and control, like in my organization, I want my innovators to innovate any other noise around them. I don't want them to have to worry about it. And it's the same thing with our customers. So if your developers are building the technologies that is really differentiating your company, then things like security and cryptography shouldn't have to be things they worry about. So we've been doing a lot of work. Like one of the projects we announced this week was around being able to decouple cryptography from the applications themselves. And we can expose that through a proxy through service mesh. And that's really exciting because now it ops can make these changes. Our SecOps teams can make these changes without having to impact the application. So that's really key is focusing the developers on innovation and then really being mindful about how you can build the right automation around everything else. And certainly open source is key to all >>That. So that's so, so then if you, if that's happening, which I'm, I'm not gonna debate that then in essence, what's really going on here is that the companies are decomposing their entire businesses down to levels that are manageable completely different than the way they did them 20, 30 years ago. >>Absolutely. You, you, you could take a modular approach to how you're solving business problems. And we do the same thing with technology, where there might be a ML algorithms that we've developed that we're exposing as SA service, but then all of the interconnects around that service are open source and very flexible so that the businesses and the customers and the VMware partners can decide what's the right way to build a puzzle for a given problem. >>We were talking on day one, I was riffing with an executives. It was Ragu and Victoria. And the concept around cross cloud was if you get to this Nirvana state, which is we, people want to get to this or composability mode, you're not coding, you're composing cuz coding's kinda happening open source and not the old classic, write some code and write that app. It's more orchestrate, compose and orchestrate. Do you, what's your thoughts on >>That? Yeah, yeah. Yeah. I, I agree. And it's it's I would add one more part to it too, which is scope. You know, I think sometimes we see projects fail because the, the initial scope is just too big. You know, what is the problem that you need to solve, scope it properly and then continuously calibrate. So even like our customers have to listen to their customers and we have to be thinking about our customers' customers, right? Because that's really how we innovate because then we can really be mindful of a holistic solution for them. >>You know, Lisa, when we had a super cloud event, you know, one of the panels was called the innovators dilemma with a question mark. And of course everyone kinds of quotes that book innovators dilemma, but one of the panelists, Chris ho beaker on Twitter said, let's change the name from the innovator's dilemma to the integrator's dilemma. And we all kind of got chuckled. We all kind of paused and said, Hey, that's actually a good point. Yeah. If you're now in a cloud and you're seeing some of the ecosystem floor vendors out there talking in this game too, they're all kind of fitting in snapping in almost like modular, like you said, so this is a Lego game. Now it feels like, it feels like, you know, let's compose, let's orchestrate, let's integrate. Now I integrations API driven. Now you're seeing a lot more about API security in the news and we've been covering at least I've probably interviewed six companies in the past, you know, six months that are doing API security, who would've thought API, that's the link, frankly, with the web. Now that's now a target area for hackers. >>Oh. And that's such an innovation area for VMware, John. Okay. >>There it is. So, I mean, this is, again, this means the connected tissue is being attacked yet. We need it to grow. No one's debating that is wrong, but it's under siege. >>Yes. Yes. So something else we introduced this week was a project. We called project Trinidad. And the way, the way you can think about it is a lot of the anomaly detection software today is looking at point based anomalies. Like this API header looks funny where we, where we've gone further is we can look at full sequence based anomalies so we can learn the sequences of transactions at an application takes and really understand what is expected behavior within those API calls within the headers, within the payloads. And we can model legitimate application behavior based on what those expectations are. So like a, like a common sequence might be doing an e-commerce checkout, right? There's lots of operations that happen logging into the site, searching, finding a product, going through the cart. Right. All of those things. Right. So if something's out of sequence, like all of a sudden somebody's just trying to do a checkout, but they haven't actually added to the cart. Right. This just seems odd. Right. So we can start to, and that's a simplistic example, but we're able now to use our algorithms to model legitimate application behavior through the entire sequence of how applications behave and then we can start to trap on anomalies. That's very differentiating IP and, and we think it's gonna be really important for the industry. Yeah. >>Because a lot of the hacks, sometimes on the API side, even as a example, are not necessarily on the API, it's the business logic in them. That's what you're getting at here. Yes. The APIs are hard. Oh our APIs are secure. Right. Well, yeah, but you're not actually securing the business logic internally. That's what you're getting at. If I read >>That right. Or exactly. Exactly. Yeah. Yeah. And it, it's the thing it's right. It's great that you can, you can look at a header, but what's the payload, right? What is what's, what's the actual data flow, right. That's associated with the call and that's what we want to really hone in on. And that's just a, it's, it's a, it's a far different level of sophistication in being able to understand east west vulnerabilities, you know, log for JX voice and these kind of things. So we have some real, it's interesting technology >>There. Security conversations now are not about security there about defense ability because security's a state of time, your secure here, you're not secure or someone might be in the network or in the app, but can you defend yourself from, and in >>That's it, you know, our, our, our malware software, right. That we're building to prevent and respond has to be more dynamic than the threats we face. Right. And this is why machine learning is so essential in, in these types of applications. >>Let me ask you a question. So just now zooming out riffing here since day, three's our conversational day where we debate and just riff more like a podcast style. If you had to do a super cloud or build a NextGen cloud multi-cloud with abstraction layer, that's, you know, all singing and dancing and open everyone's happy hardware below it's working ISAs and then apps are killed. Can ass what's in that. What does it look like to you if you had to architect the, the ultimate super cloud enabler, that something that would disrupt the next 10 years, what would it look like and how does, and assuming, and trying to do where everybody wins go, you have 10 seconds. No, >>Yeah, yeah. So the, you know, first of all, there has to be open source at all of the intersections. I think that's really important. And, and this is, this goes from networking constructs to our database, as a service layers, you know, everything in between, you know, the, the, the participants should be able to win on merit there. The other part of super cloud though, that hasn't happened that I probably is the most important area of innovation is going to be decoupled control planes. We have a number of organizations building sovereign cloud initiatives. They wanna have flexibility in where their services physically run. And you're not going to have that with a limited number of control planes that live in very specific public cloud data centers. So that's an area, give >>An example of what a, a, a, a narrowly defined control plane is. >>Yeah, sure. So my database as a service layer, so the, the, the actual portal that the customer is going into to provision databases, right. Rep managed replication, et cetera. Right. I should be able to run that in a colo. I should be able to run that somewhere in region that is guaranteed, that I'm going to have data stay physically in region. You know, we still have some of these challenges in networking in terms of being able to constrain traffic flows and be able to predict and audit them within a particular region as well. >>It's interesting. You bring up region again, more complexity. You know, you got catalogs here, catalogs different. I mean, this is where the chaos really comes down. I mean, it's, it's advancing, but it's advancing the state of functionality, but making it hella complex, I mean, come on. Don't you think it's like pretty amazingly hard to reign in that? Well, or is it maybe you guys making it easier? I just think I just, my mind just went, oh my God, I gotta, I gotta provision to that region, but then it's gotta be the same over there. And >>When you go back to modular architecture constructs, it gets far easier. This has been really key for how VMware is even building our own clouds internally is so that we have a, a shared services platform for the different apps and services that we're building, so that you do have that modularized approach. Like I said, the, the examples of innovation projects I've shared have been really driven by the fact that, you know, what, I don't know how customers are gonna consume it, and I don't have to know. And if you have the right modular architecture, the right APIs around it, you don't have to limit a particular project or technology's future at the time you build >>It. Okay. So your super would have multiple control planes that you can move, manage with that within one place. I get that. What about the data control plane? That seems to be something that used to be the land grab in, in conversations from vendors. But that seems to be much more of a customer side, cuz if I'm a customer, I want my control plane data plane to be, you know, mine. Like I don't want to have anyone cuz data's gotta move around, gotta be secure. >>Oh exactly. >>And that's gonna be complicated. How does, how do you see the data planes emerging? >>Yeah. Yeah. We, we see an opportunity really around having a, a centralized view that can give me consistent indexing and consistent awareness of data, no matter where it resides. And then being able to have that level of integration now between my data services and my applications, because you're right, you know, right now we have data in different places, but we could have a future where data's more perpetually in motion. You know, we're already looking at time sensitive fabrics where we're expecting microservices to sometimes run in different cell towers depending on the SLA that they need to achieve. So then you have data parts that's going to follow, right? That may not always be in the same cloud data center. So there's, this is enormously complicated, not just in terms of meeting application SLAs, but auditing and security. Right. That makes it even further. So having these types of data layers that can give me a consistent purview of data, regardless of where it is, allow me to manage and life cycle data globally, that's going to be super important, I believe going forward. >>Yeah. Awesome. Well, my one last question, Lisa, gonna get a question in here. It's hard. Went for her. I'm getting all the, all the questions in, sorry, Lisa that's okay. What's your favorite, most exciting thing that you think's going on right now that people should pay attention to of all the things you're looking at, the most important thing that that's happening and maybe something that's super important that people aren't talking about or it could be the same thing. So the, the most important thing that you think that's happening in the industry for cloud next today and, and maybe something that you think people should look at and pay more attention to. >>Okay. Yeah, those are good questions. And that's hard to answer because there's, there's probably so much happening. I I've been on here before I've talked about edge. I still think that's really important. I think the value of edge soft of edge velocity being defined by software updates, I think is quite powerful. And that's, that's what we're building towards. And I would say the industry is as well. If you look at AWS and Azure, when they're packaging a service to go out to the edge it's package as a container. So it's already quite flexible and being able to think about how can I have a single platform that can give me all of this flexibility, I think is really, really essential. We're building these capabilities into cars. We have a version of our Velo cloud edge device. That's able to run on a ruggedized hardware in a police car today. We're piloting that with a customer. So there is a shift happening where you can have a core platform that can now allow you to layer on applications that you're not thinking about in the future. So I think that's probably obvious. A lot of people are like, yeah. Okay. Yes. Let's talk about edge, big deal. >>Oh it's, it's, it's big. Yes. It's >>Exploding, but >>It's complicated too. It's not easy. It's not obvious. Right. And it's merging >>There's new things coming every day. Yeah. Yeah. And related to that though, there is this kind of tension that's existing between machine learning and privacy and that's really important. So an area of investment that I don't think enough people are paying attention to today is federated machine learning. There's really good projects in open source that are having tangible impact on, in a lot of industries in VMware. We are, we're investing in a, in a couple of those projects, namely fate in the Linux foundation and open FFL. And in these use cases like the security product I mentioned to you that is looking at analyzing API sequence API call sequences. We architected that originally so that it can run in public cloud, but we're also leveraging now federated machine learning so that we can ensure that those API calls and metadata associated with that is staying on premises for the customers to ensure privacy. So I think those intersections are really important. Federated learning, I think is a, an area not getting enough attention. All right. All >>Right, Chris, thanks so much for coming on. Unfortunately we are out of time. I know you guys could keep going. Yeah. Good stuff. But thank you for sharing. What's going on in R and D the customer impact the outcomes that you're enabling customers to achieve. We appreciate your >>Insights. We're just getting started >>In, in early innings, right? Yeah. Awesome. Good stuff for guest and John furrier. I'm Lisa Martin. You're watching the cube live from VMware Explorer, 2022. Our next guest joins us momentarily. >>Okay.

Published Date : Sep 1 2022

SUMMARY :

This is the Cube's third day of Wal Dal coverage of VMware Explorer. We've had great conversations with VMware's ecosystem and VMware of course, And these look at this is looking at sovereign clouds and multi-cloud edge computing, And in addition to that, as we get closer to go to market, we look to a It's kind of out front right now, but now cloud native's got the most history what's coming out So keek is super exciting because when you think So imagine now, when you need to do an update for infrastructure, you're logging into GitHub, you're editing a YAML What else on the cloud native side Tansu Monterey those Now that's DEC coupled, physically from the server, and it really allows me to scale out east west security So that DPU, which got a lot of buzz, by the way, Lisa, I never, you had trouble interviews on this. So I'm running line rate on the How does VMware look at the relationship to the cloud providers? We can be decoupled, but highly cohesive, but you gotta connect in via APIs. And that's the lesson that we have to take to multi-cloud. but the goal of getting to cloud smart, how does the R and D organization, how do, how are you helping customers they need to have, you know, better accountability there. They do all the work and you only pay when you've made your It's the developers that have to make the calls because if the application is the core, So to me, that's the big story here at the show What is the path for the VMware customer to go from here to there? So that's really key is focusing the developers on innovation to levels that are manageable completely different than the way they did them 20, so that the businesses and the customers and the VMware partners can decide what's the right way to build And the concept around cross cloud was if So even like our customers have to listen to their customers and we have to be thinking about And of course everyone kinds of quotes that book innovators dilemma, but one of the Oh. And that's such an innovation area for VMware, John. We need it to grow. And the way, the way you can think about it is a lot of the anomaly detection software today is looking at point Because a lot of the hacks, sometimes on the API side, even as a example, are not necessarily on And it, it's the thing it's right. but can you defend yourself from, and in That's it, you know, our, our, our malware software, right. What does it look like to you if you had to architect the, the ultimate super cloud enabler, So the, you know, first of all, there has to be open the customer is going into to provision databases, right. Don't you think it's like pretty amazingly hard to reign in the right APIs around it, you don't have to limit a particular project or technology's future customer, I want my control plane data plane to be, you know, mine. How does, how do you see the data planes emerging? So then you have data parts that's going to follow, right? in the industry for cloud next today and, and maybe something that you think people should look So there is a shift happening where you can have a core platform that can now allow It's And it's merging So an area of investment that I don't think enough people are paying attention to today is federated What's going on in R and D the customer impact the outcomes We're just getting started Yeah.

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Keith Norbie, NetApp & Brandon Jackson, CDW | VMware Explore 2022


 

>>Hey everyone. Welcome back to San Francisco. Lisa Martin and Dave Nicholson here. The cube is covering VMware Explorer, 2022 first year with the new name, there's about seven to 10,000 people here. So folks are excited to be back. I was in the keynote this morning. You probably were two David. It was standing room, only lots of excitement, lots of news. We're gonna be unpacking some news. Next. We have Brandon Jackson joining us S DDC architect at CDW and Keith normy is back one of our alumni head of worldwide partner solution sales at NetApp guys. Welcome back to the program. Hey, thank >>You, reunion week. >>So let's talk about what's going on, obviously, lots of news this morning, lots of momentum at VMware, lots of momentum at NetApp CDW. Keith, we'll start with you talk about what was announced yesterday, NetApp, VMware, AWS, and what's in it for customers and partners. >>Yeah, it's a new day. I talked about this in a blog that I wrote that, you know, for me, I started out with VMware and NetApp about 15 years ago when the ecosystem was still kind of emerging back in the ESX three days, for those that remember those days and, and NetApp had a really real dominant position because some of the things that they had delivered with VMware, and we're kind of at that same venture now where everyone needs to have as they talk about today. Multi-cloud, and, and there's been some things that people try to get through as they talk about cloud chaos today. It also is in the, some of the realms, the barriers that you don't often see. So releasing this new FSX capability with the metal data store within VMware cloud, and AWS is a real big opportunity. And it's not just a big opportunity for NetApp. It's a big opportunity for the people that actually deliver this for the customers, which is our partner. So for me, it's full circle. I started with a partner I come back around and I'm now in a great position to kind of work with our partners. And they're the real story here with us. Yeah. >>Brandon, talk about the value in this from CDWs perspective, what is the momentum that your you and the company are excited to carry forward? >>Yeah, this is super exciting. I've been close to the VMware cloud AWS story since its inception. So, you know, almost four years building that practice out at CDW and it's a great solution, but we spent all this time prior driving people to that HCI type of mentality where, Hey, you can just scale the portions that you need and that wasn't available in the cloud. And although it's a great solution, there's pain points there where it just can become cost prohibitive because customers see what they need. But that storage piece is a heavy component. And when that adds to what that cluster size needs to be, that's a real problem with this announcement, right? We can now use those supplemental data stores and be able to shrink that size. So it saves the customer massive amounts of money. I mean, we have like 25, 50% in savings while without sacrificing anything, they're getting the operational efficiency that they know and love from NetApp. They get that control and that experience that they've been using or want to use in VMware cloud. And they're just combining the two in a very cost friendly package. >>So I have one comment and that is finally >>Right. Absolutely. I, >>We used to refer to it as the devil's triangle of CPU, memory and storage. And if those are, if those are inextricably linked to one another, you want a little bit more storage. Okay. Here's your CPU and memory that you can pay for and power and cool that you don't need? No, no, no, no, no, no. I just need, I just need some storage over here. And in the VMware context, think of the affinity that VMware has had with NetApp forever. The irony being that EMC of course, owned VMware for a period of time, kind of owned their stock. Yeah. So you have this thing that is fundamentally built around VMFS that just fits perfectly into the filer methodology. Yeah. And now they're back together in the cloud. And, and the thing is if, if we were, if we were sitting here talking about this 5, 6, 7 years ago, an AWS person would've said we were all crazy. Yeah, yeah. AWS at the time would've said, nah, no, no, no, no. We're gonna figure that out. You, you, you, you guys are just gonna have to go away. It's >>Not lost on me that, you know, it was great seeing and hearing of NetApp in a day, one VMware keynote. >>It's amazing. >>That was great. And so we built off that because the, the, the great thing about kind of where this comes from is, you know, you built that whole HCI or converged infrastructure for simplicity and everyone is simplicity. And so this is just another evolution of the story. And as you do, so, you know, you've, you've freed up for all the workloads, all the scenarios, all the, all the operational situations that you've wanted to kind of get into. Now, if you can save anywhere from 25 to 50% of the costs of previous, you can unleash a whole nother set of workloads and do so by the way, with same consistent operational consistency from NetApp, in terms of the data that you have on-prem to cloud, or even if you don't have NetApp, on-prem, you know, we have the ways to get it to the cloud and VMware cloud and AWS, and, and, and basically give you that data simplicity for management. >>And, but again, it isn't just a NetApp part of this. There is, as everyone knows with cloud, a whole layer of infrastructure around the security networking, there's a ton of work that gets from the partner side to look at applications and workloads and understand sort of what's the composition of those, which ones are ready for the cloud. First, you know, seeing, you know, the AWS person with the SAP title, that's a big workload. Obviously that's making this journey to the cloud, along with all the rest of them. That's what the partners deliver. NetApp has done everything they can do to make that as frictionless as possible in the marketplace as a first party service, and now through VMware cloud. So we've done all we can do on, on that factor. Now it's the partners that could take it. And by the way, the reaction that we've seen kind of in some of, of the private previews are working, has been incredible. These guys bring really the true superhero muscle to what organizations are gonna need to have to take those workloads to VMware cloud and, and evolve it into this new cloud era that they're talking about at the keynote today. >>Yeah, don't get us wrong. We love vSphere eight and vs a, a and VSAN aid in particular, but there's a huge market need for this, for what you guys are delivering. >>Talk to us, Brandon, from your perspective about being able to, to part, to, to have the powerhouses of NetApp, VMware and AWS, and in terms of being able to meet your customers where they are and what they want. >>And I, that's huge, right? That the solution allows these things to come together in a seamless way, right? So we get the, the flexibility of cloud. We get the scalability of easy storage now, in a way we didn't have before, and we get the power that's VMware, right. And in that, in the virtualization platform, and that makes it easy for a customer to say, I need to be somewhere else. And maybe that's not, that's not a colo anymore. That's not a secondary data center. I want to be in the cloud, but I wanna do it on my terms. I wanna do it. So it works for me as a customer. This solution has that, right? And, and we come in as a partner and we look at, we kind of call it the full stack approach, where we really look at the entire, you know, ecosystem that we're talking. >>So from the application all the way down to the infrastructure and even below, and figure out how that's gonna work best for our customers and putting things together with the native cloud services, then with their VMware environment, living on VMware cloud, AWS, leveraging storage with a, you know, with the, the FSX in. So they can easily grow their storage and use all those operational efficiencies and the things that they love about NetApp already. And from a Dr. Use case, we can replicate from a NetApp to NetApp. And it's just, it makes it so easy to have that conversation with the customers and just, it clicks. And like, this is what I need. This is what I've been looking for. And all wrapped up in a really easy package. >>No wonder Dave's comment was finally right. >>Oh, absolutely. I mean, we've been, again, you know, we talked about the HCI, like that made sense. And three or four years ago, maybe even a little bit longer, right. That click, same thing was like, oh my gosh, this is the way infrastructure should work. And we're just having that same Nirvana moment that this is how easy cloud infrastructure can work and that I can have that storage without sacrificing the cost, throw more nodes into my cluster to be able to do so. >>Yeah. I I've just worked with so many customers who struggle to get to where they want to be BEC, and this is something that just feels like a nice worn in pair of shoes or jeans to folks who right now, you know, look, the majority of it spend is still on premises, right? So the typical deployment of VMware today is often VMware with NetApp appliances providing file storage. So this is something that I imagine will help accelerate some of your customers' moves. >>It absolutely will. And in fact, I have three customers off the hand that I know that I've been like, not wanting to say anything like let's talk next week. Right? There's this, there may be something we can talk about when, on, after Explorer waiting for the announcement, because we've been working with NetApp and, and doing some of the private preview stuff. Yeah. And our engineering teams, working with your engineering teams to build this out so that when the announcement came out yesterday, we can go back and say, okay, now let's have that conversation. Now let's talk about what this looks like, >>Where are you having customer conversation? So this is strictly an it conversation has this elevated up the stack, especially as we've seen the massive, I call it cloud migration adoption of the last couple of years. >>I, I I'll speak fairly from the partner level. It is an elevated conversation. So we're not only talking, at least I'm not only talking to it. Administrators, directors, C levels like this is a story that resonates because it's about business value, right? I have an initiative, I have a goal. And that goal is wrapped into that it solution. And typically has some sort of resource or financial cost to it. We want to hear that story. And so it resonates when we can talk about how you can achieve your goals, do it in a way with a specific solution that encompasses everything at a price point that you'll like, and then that can flow down to the directors and the it administrators. And we can start talking about, you know, turning the screws and the knobs. >>Yeah. And for us, it does start with a partner because the reality is that's who the that's, who the customers all engage. And the reality is there's not just one partner type there's many, you know, we, in fact, what the biggest thing that we've been really modernizing is how to address the different partner types. Cuz you obviously have the Accentures of the world that are the big GSIs, the big SI you have folks that are hosting providers, you have Equinox X in the middle of that. You've got partners that just do services that might be only influenced partners that are influencing the, the design. And so if you look up and down between, you know, VMware's partner ecosystem and NetApp's partner ecosystem overlap pretty well, but there's this factor with AWS about, you know, both born and the cloud partners and partners, you know, like CW that have really, you know, taken the step forward to be relevant in that phase going forward. >>And that's, what's exciting to us is to see that kind of come forward. So when something like a FSX end comes forward in this VMware cloud and AWS scenario, they can take and, and just have instant ignition with it. And for us, that's what it's about. Our job is really just to remove friction back what they do and get outta the way, help them win. And last week we were in Chicago at the AWS reinvent thing and seeing AWS with another partner in their whole briefing and how they came to life with the, with this whole anticipation for this week, you know, it's, it's all the partners are very excited for it. So we're just gonna fuel that. And you know, I often wonder we got the, the t-shirt that says, you know, two's company three is a cloud maybe should have been four because it takes the, the partner for the, the completion. >>We appreciate that for sure. >>It does. It sounds like there's tremendous momentum in the market, an appetite across all three companies, four, if you include CDW. So in terms of, of the selling motion, it sounds like you've got folks that are gonna be eating out of eating out of your pocket. Who've been waiting for this for quite a while. Yeah. >>I think you, the analogy used earlier, it's nice when the tires are already on the Ferrari, right. This thing could just go, yes. And we've got people that we're already talking to that this fits, we've got some great go to market strategies. As we start doing partner in sales enablement to make sure that our people behind the scenes are telling the story and the way that we want it to jointly so that all of us can, you know, come together and have that aligned common message to really, you know, make this win and make this pop >>One correction though is technically we sponsor Aston Martin. So it's not a fry. It's an Aston Martin. There >>You go. >>That's right. Quite taken, not a car guy. Can >>You, can you talk a little bit Brendan about the, the routes to market and the, the GTM that you guys are working on together, even at a high level? Yeah. >>At a high level, we've already had some meetings talking about how we can get this message out. The nice thing about this is it's not relegated to a single industry vertical. It's not a single type of customer. We see this across the board and, and certainly with any of our cloud infrastructure solutions, it seems very, even from a regional standpoint and an industry vertical standpoint. So really it's just about how to get our sellers, you know, that get that message to them. So we had meetings here this week. We've been talking to your teams, oh, for probably six weeks now on what's that gonna look like? You know, what type of events are we gonna hold? Do we wanna do some type of road show? Yeah. We've done that with FlexPod very successfully, a few years ago where our teams working with your teams and VMware, we all came out and, and showed this to the world and doing something similar with this to show how easy it is to add supplemental storage to VMC. And just get that out to the masses through events, maybe through sales webinars. I mean, we're still in this world where maybe it's more virtual than on person, but we're starting to shift back, but it's just about telling the message and, and showing, Hey, here's how you do it. Come talk to us. We can help you. And we want to help >>Talk about the messaging from a, a multi-cloud perspective. Here we are at VMware Explorer, the theme, the center of the multi-cloud universe, how is this solution from NetApp's perspective? And then CDWs, how does it an enabler of customers that so many are living in the multi-cloud world by default? >>Yeah. And I think the big subtlety there that, that maybe was MIS missed was the private cloud being just so their cloud. The reality of that is probably a little bit short of, you know, of what people kind of deal with with their on on-prem data centers, just because of some of the applications, data sets they're trying to work through for AI ML and analytics. But that's what the partner's great at is, is helping them kind of leap forward and actually realize the on-prem to become the private cloud and really operate in this multi-cloud scenario and, and get beyond this cloud chaos factor. So again, you know, the beautiful part about all this is that, you know, the, the, the never ending sort of options, the optionality that you have on security, on networking, on applications, data sets, locations, governance, these are all factors that the partner deals with way better than we could even think of. So for us, it's really about just trying to connect with them, get their feedback and actually design in from the partner to take something like this and make it something that works for them >>Back to your shirt. What does it say? Two's company, three's a cloud that's right. But if you want rain, you need a fourth. Yeah. Right. We're here in California. I don't care about clouds. We need it to rain. All >>Right. So >>It's all well and good that yeah. If you know, a couple of you get together and offer something up, but where the rubber meets the road, you know, the customer relationship, the strategic seat at the customer table, there, aren't more of those than there have been in the past. And, and, and ecosystems have obviously gotten more complicated. I can't help thinking back as I think back on the history of, of NetApp and VMware and CDW, there was a time when, when things were bad, you get rid of marketing. And then, and then after that, it was definitely alliances and partnerships cuz who the heck are those people right now? Everything is an ecosystem. Yeah. Everything is an ecosystem. So talk about how CW CDW has changed through its history in terms of where CDW has come from. >>Sure. And you >>Know, not everybody knows that CDW is involved in as sophisticated in area as you are. >>And, and that's true. I mean, sometimes it's tongue in cheek, but you know, we've fulfilled a lot of needs throughout the years and, and maybe at times just a fulfillment or a box pusher, but we're really so much more that, and we've been so much more than that for years. And through some of our acquisitions, you know, Sirius last year I G N w our international arm with Kway when it became CDW, K we have a, you know, a premier experience around consultative services. And that we talk about that full stack, right? Yeah. From the application to the cloud, to the infrastructure, to the security around it, to the networking, we can help out with all of that. And we've got experts and, and, you know, on the presales and postsales that, that's what they live for. It's their passion. And working with partners close in hand, that that's, we've had great relationships with, with NetApp. And again, I've been with CDW for over 12 years. And in all 12 of those years, I've been very close to NetApp in one way, shape or form, and to see how we work together to solve our customers' challenges. It's less about what we want to do. It's more about what we're doing to help the customer. And, and I've seen that day in and day out from our relationship and, you know, kind of our partnership. >>So say we're back here in six months, or maybe we're back here at reinvent, talking with you guys and a customer. What are some of the outcomes that at this stage you were expecting customers to be able to achieve, >>Be able to do more, put more out there, right. To not be limited by the construct of, I only have X amount of space. And so maybe the use case or the initiative is, is wrapped around that. Let's turn that around and say, that's, you're limitless, let's have move what you need. And you're not gonna have to worry so much about the cost, the way you did six months ago or seven months ago, or six months in a day ago that you can do more with it. And if we have an X amount in our bucket in, in July, we could do 200 VMs. You know, and now six months later, we've done 500 VMs because of those efficiency savings because of that cost savings and using supplemental storage. So I, I see that being a growth factor and being say, Hey, this was easy. We always knew this was a solution we liked, but now it's easy and bigger. >>Yeah. I think on our end, the spectrum, I'll just say what Phil Brons would say. I said previously, he was in the previous segment, which is, this could go pretty quick, folks that have wanted to do this now that they know this is something to do and that they can go at it. The part we already know, the partners are very much in like ready to go mode. They've been waiting for this day to just get the announcement out so they can get kind of get going. And it's funny because you know, when we've presented, we've kind of presented some of the tech behind what we're doing and then the ROI T C calculator last, and everyone's feedback is the same. They said you should just lead to the calculator. So then yeah, you can see exactly how much money you save. In fact, one of the jokes is there's not many times you've saved this much money in it before. And so it's, it's a big, wow. Factor, >>Big, wow. Factor, big differentiator, guys. Thank you so much for joining David, me talking about what NetApp, VMware, AWS are doing, how it's being delivered through CDW, the evolution of all these companies. We're excited to watch the solution. We better let you go because you probably have a ton of meeting. People are just chopping at the bit to get this. Yeah. >>It's, it's exciting times. I'm loving it being here and being able to talk about this finally, in a public setting. So this has been great. >>Awesome guys. Thank you again for your time. We appreciate it. Yep. For our guests and Dave Nicholson, I'm Lisa Martin. You're watching the cube live from VMware Explorer, 2022. We'll be back after a short break, stick around.

Published Date : Aug 31 2022

SUMMARY :

So folks are excited to be back. we'll start with you talk about what was announced yesterday, NetApp, VMware, I talked about this in a blog that I wrote that, you know, for me, type of mentality where, Hey, you can just scale the portions that you need and that wasn't available in I, And in the VMware context, think of the affinity that VMware has had with NetApp forever. Not lost on me that, you know, it was great seeing and hearing of NetApp in a day, And as you do, so, you know, you've, you've freed up for all the workloads, And by the way, the reaction that we've seen kind of in some of, of the private previews are working, a and VSAN aid in particular, but there's a huge market need for this, for what you guys are delivering. and in terms of being able to meet your customers where they are and what they want. And in that, in the virtualization platform, and that makes it easy for a with a, you know, with the, the FSX in. I mean, we've been, again, you know, we talked about the HCI, like that made sense. now, you know, look, the majority of it spend is still on premises, right? And our engineering teams, working with your engineering teams to build this out Where are you having customer conversation? And we can start talking about, you know, turning the screws and the knobs. And so if you look up and down between, you know, VMware's partner ecosystem and NetApp's partner ecosystem overlap to life with the, with this whole anticipation for this week, you know, it's, So in terms of, of the selling motion, it sounds like you've got folks that you know, come together and have that aligned common message to really, you know, So it's not a fry. That's right. You, can you talk a little bit Brendan about the, the routes to market and the, the GTM that you guys are And just get that out to the masses through events, And then CDWs, how does it an enabler of customers that so many are living in the multi-cloud world The reality of that is probably a little bit short of, you know, of what people But if you want rain, you need a fourth. So but where the rubber meets the road, you know, the customer relationship, the strategic seat at the customer table, I mean, sometimes it's tongue in cheek, but you know, we've fulfilled What are some of the outcomes that at this stage you were expecting customers to be able to achieve, the cost, the way you did six months ago or seven months ago, or six months in a day ago that you So then yeah, you can see exactly how much money you save. We better let you go because you probably have a ton of meeting. So this has been great. Thank you again for your time.

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Mohit Aron & Sanjay Poonen, Cohesity | Supercloud22


 

>>Hello. Welcome back to our super cloud 22 event. I'm John F host the cue with my co-host Dave ante. Extracting the signal from noise. We're proud to have two amazing cube alumnis here. We got Sanja Putin. Who's now the CEO of cohesive the emo Aaron who's the CTO. Co-founder also former CEO Cub alumni. The father of hyper-converged welcome back to the cube I endorsed the >>Cloud. Absolutely. Is the father. Great >>To see you guys. Thank thanks for coming on and perfect timing. The new job taking over that. The helm Mo it at cohesive big news, but part of super cloud, we wanna dig into it. Thanks for coming on. >>Thank you for having >>Us here. So first of all, we'll get into super before we get into the Supercloud. I want to just get the thoughts on the move Sanjay. We've been following your career since 2010. You've been a cube alumni from that point, we followed that your career. Why cohesive? Why now? >>Yeah, John David, thank you first and all for having us here, and it's great to be at your event. You know, when I left VMware last year, I took some time off just really primarily. I hadn't had a sabbatical in probably 18 years. I joined two boards, Phillips and sneak, and then, you know, started just invest and help entrepreneurs. Most of them were, you know, Indian Americans like me who were had great tech, were looking for the kind of go to market connections. And it was just a wonderful year to just de to unwind a bit. And along the, the way came CEO calls. And I'd asked myself, the question is the tech the best in the industry? Could you see value creation that was signi significant and you know, three, four months ago, Mohit and Carl Eschenbach and a few of the board members of cohesive called me and walk me through Mo's decision, which he'll talk about in a second. And we spent the last few months getting to know him, and he's everything you describe. He's not just the father of hyperconverge. And he wrote the Google file system, wicked smart, built a tech platform better than that second time. But we had to really kind of walk through the chemistry between us, which we did in long walks in, in, you know, discrete places so that people wouldn't find us in a Starbucks and start gossiping. So >>Why Sanjay? There you go. >>Actually, I should say it's a combination of two different decisions. The first one was to, for me to take a different role and I run the company as a CEO for, for nine years. And, you know, as a, as a technologist, I always like, you know, going deep into technology at the same time, the CEO duties require a lot of breadth, right? You're talking to customers, you're talking to partners, you're doing so much. And with the way we've been growing the with, you know, we've been fortunate, it was becoming hard to balance both. It's really also not fair to the company. Yeah. So I opted to do the depth job, you know, be the visionary, be the technologist. And that was the first decision to bring a CEO, a great CEO from outside. >>And I saw your video on the site. You said it was your decision. Yes. Go ahead. I have to ask you, cuz this is a real big transition for founders and you know, I have founder artists cuz everyone, you know, calls me that. But being the founder of a company, it's always hard to let go. I mean nine years as CEO, it's not like you had a, you had a great run. So this was it timing for you? Was it, was it a structural shift, like at super cloud, we're talking about a major shift that's happening right now in the industry. Was it a balance issue? Was it more if you wanted to get back in and in the tech >>Look, I, I also wanna answer, you know, why Sanja, but, but I'll address your question first. I always put the company first what's right for the company. Is it for me to start get stuck the co seat and try to juggle this depth and Brad simultaneously. I mean, I can stroke my ego a little bit there, but it's not good for the company. What's best for the company. You know, I'm a technologist. How about I oversee the technology part in partnership with so many great people I have in the company and I bring someone kick ass to be the CEO. And so then that was the second decision. Why Sanja when Sanjay, you know, is a very well known figure. He's managed billions of dollars of business in VMware. You know, been there, done that has, you know, some of the biggest, you know, people in the industry on his speed dial, you know, we were really fortunate to have someone like that, come in and accept the role of the CEO of cohesive. I think we can take the company to new Heights and I'm looking forward to my partnership with, with Sanja on this. >>It it's we, we called it the splash brothers and >>The, >>In the vernacular. It doesn't matter who gets the ball, whether it's step clay, we shoot. And I think if you look at some of the great partnerships, whether it was gates bomber, there, plenty of history of this, where a founder and a someone who was, it has to be complimentary skills. If I was a technologist myself and wanted to code we'd clash. Yeah. But I think this was really a match me in heaven because he, he can, I want him to keep innovating and building the best platform for today in the future. And our customers tell one customer told me, this is the best tech they've seen since VMware, 20 years ago, AWS, 10 years ago. And most recently this was a global 100 big customers. So I feel like this combination, now we have to show that it works. It's, you know, it's been three, four months. My getting to know him, you know, I'm day eight on the job, but I'm loving it. >>Well, it's a sluman model too. It's more modern example. You saw, he did it with Fred Ludy at service now. Yes. And, and of course at, at snowflake, yeah. And his book, you read his book. I dunno if you've read his book, amp it up, but app it up. And he says, I always you'll love this. Give great deference to the founder. Always show great respect. Right. And for good reason. So >>In fact, I mean you could talk to him, you actually met to >>Frank. I actually, you know, a month or so back, I actually had dinner with him in his ranch in Moana. And I posed the question. There was a number of CEOs that went there and I posed him the question. So Frank, you know, many of us, we grow being deaf guys, you know? And eventually when we take on the home of our CEO, we have to do breadth. How do you do it? And he's like, well, let me tell you, I was never a death guy. I'm a breath guy. >>I'm like, >>That's my answer. Yeah. >>So, so I >>Want the short story. So the day I got the job, I, I got a text from Frank and I said, what's your advice the first time CEO, three words, amp it up, >>Amp it up. Right? Yeah. >>And so you're always on brand, man. >>So you're an amazing operator. You've proven that time and time again at SAP, VMware, et cetera, you feel like now you, you, you wanna do both of those skills. You got the board and you got the operations cuz you look, you know, look at sloop when he's got Scarelli wherever he goes, he brings Scarelli with him as sort of the operator. How, how do you, how are you thinking >>About that? I mean it's early days, but yeah. Yeah. Small. I mean I've, you know, when I was, you know, it was 35,000 people at VMware, 80, 90,000 people at SAP, a really good run. The SAP run was 10 to 20 billion innovative products, especially in analytics and VMware six to 12 end user computing cloud. So I learned a lot. I think the company, you know, being about 2000 employees plus not to mayor tomorrow, but over the course next year I can meet everybody. Right? So first off the executive team, 10 of us, we're, we're building more and more cohesiveness if I could use that word between us, which is great, the next, you know, layers of VPs and every manager, I think that's possible. So I I'm a people person and a customer person. So I think when you take that sort of extroverted mindset, we'll bring energy to the workforce to, to retain the best and then recruit the best. >>And you know, even just the week we, we were announced that this announcement happened. Our website traffic went through the roof, the highest it's ever been, lots of resumes coming in. So, and then lots of customer engagement. So I think we'll take this, but I, I feel very good about the possibilities, because see, for me, I didn't wanna walk into the company to a company where the technology risk was high. Okay. I feel like that I can go to bed at night and the technology risk is low. This guy's gonna run a machine at the current and the future. And I'm hearing that from customers. Now, what I gotta do is get the, the amp it up part on the go to market. I know a little thing or too about >>That. You've got that down. I think the partnership is really key here. And again, nine use the CEO and then Sanja points to our super cloud trend that we've been looking at, which is there's another wave happening. There's a structural change in real time happening now, cloud one was done. We saw that transition, AWS cloud native now cloud native with an kind of operating system kind of vibe going on with on-premise hybrid edge. People say multi-cloud, but we're looking at this as an opportunity for companies like cohesive to go to the next level. So I gotta ask you guys, what do you see as structural change right now in the industry? That's disruptive. People are using cloud and scale and data to refactor their business models, change modern cases with cloud native. How are you guys looking at this next structural change that's happening right now? Yeah, >>I'll take that. So, so I'll start by saying that. Number one, data is the new oil and number two data is exploding, right? Every year data just grows like crazy managing data is becoming harder and harder. You mentioned some of those, right? There's so many cloud options available. Cloud one different vendors have different clouds. There is still on-prem there's edge infrastructure. And the number one problem that happens is our data is getting fragmented all over the place and managing so many fragments of data is getting harder and harder even within a cloud or within on-prem or within edge data is fragmented. Right? Number two, I think the hackers out there have realized that, you know, to make money, it's no longer necessary to Rob banks. They can actually see steal the data. So ransomware attacks on the rise it's become a boardroom level discussion. They say there's a ransomware attack happening every 11 seconds or so. Right? So protecting your data has become very important security data. Security has become very important. Compliance is important, right? So people are looking for data management solutions, the next gen data management platform that can really provide all this stuff. And that's what cohesive is about. >>What's the difference between data management and backup. Explain that >>Backup is just an entry point. That's one use case. I wanna draw an analogy. Let's draw an analogy to my former company, Google right? Google started by doing Google search, but is Google really just a search engine. They've built a platform that can do multiple things. You know, they might have started with search, but then they went down to roll out Google maps and Gmail and YouTube and so many other things on that platform. So similarly backups might be just the first use case, but it's really about that platform on which you can do more with the data that's next gen data management. >>But, but you am, I correct. You don't consider yourself a security company. One of your competitors is actually pivoting and in positioning themselves as a security company, I've always felt like data management, backup and recovery data protection is an adjacency to security, but those two worlds are coming together. How do you see >>It? Yeah. The way I see it is that security is part of data management. You start maybe by backing with data, but then you secure it and then you do more with that data. If you're only doing security, then you're just securing the data. You, you gotta do more with the data. So data management is much bigger. So >>It's a security is a subset of data. I mean, there you go. Big TA Sanjay. >>Well, I mean I've, and I, I, I I'd agree. And I actually, we don't get into that debate. You know, I've told the company, listen, we'll figure that out. Cuz who cares about the positioning at the bottom? My email, I say we are data management and data security company. Okay. Now what's the best word that describes three nouns, which I think we're gonna do management security and analytics. Okay. He showed me a beautiful diagram, went to his home in the course of one of these, you know, discrete conversations. And this was, I mean, he's done this before. Many, if you watch on YouTube, he showed me a picture of an ice big iceberg. And he said, listen, you know, if you look at companies like snowflake and data bricks, they're doing the management security and mostly analytics of data. That's the top of the iceberg, the stuff you see. >>But a lot of the stuff that's get backed archive is the bottom of the iceberg that you don't see. And you try to, if you try to ask a question on age data, the it guy will say, get a ticket. I'll come back with three days. I'll UNIV the data rehydrate and then you'll put it into a database. And you can think now imagine that you could do live searches analytics on, on age data that's analytics. So I think the management, the security, the analytics of, you know, if you wanna call it secondary data or backed up data or data, that's not hot and live warm, colder is a huge opportunity. Now, what do you wanna call one phrase that describes all of it. Do you call that superpower management security? Okay, whatever you wanna call it. I view it as saying, listen, let's build a platform. >>Some people call Google, a search company. People, some people call Google and information company and we just have to go and pursue every CIO and every CSO that has a management and a security and do course analytics problem. And that's what we're doing. And when I talk to the, you know, I didn't talk to all the 3000 customers, but the biggest customers and I was doing diligence. They're like this thing has got enormous potential. Okay. And we just have to now go focus, get every fortune 1000 company to pick us because this problem, even the first use case you talk back up is a little bit like, you know, razor blades and soap you've needed. You needed it 30 years ago and you'll need it for 30 years. It's just that the tools that were built in the last generation that were companies formed in 1990s, one of them I worked for years ago are aids are not built for the cloud. So I think this is a tremendous opportunity where many of those, those, those nos management security analytics will become part of what we do. And we'll come up with the right phrase for what the companies and do course >>Sanjay. So ma and Sanja. So given that given that's this Google transition, I like that example search was a data problem. They got sequenced to a broader market opportunity. What super cloud we trying to tease out is what does that change over from a data standpoint, cuz now the operating environments change has become more complex and the enterprises are savvy. Developers are savvy. Now they want, they want SAS solutions. They want freemium and expanding. They're gonna drive the operations agenda with DevOps. So what is the complexity that needs to be abstracted away? How do you see that moment? Because this is what people are talking about. They're saying security's built in, driven by developers. Developers are driving operations behavior. So what is the shift? Where do you guys see this new? Yeah. Expansive for cohesive. How do you fit into super cloud? >>So let me build up from that entry point. Maybe back up to what you're saying is the super cloud, right? Let me draw that journey. So let's say the legacy players are just doing backups. How, how sad is it that you have one silo sitting there just for peace of mind as an insurance policy and you do nothing with the data. If you have to do something with the data, you have to build another silo, you have to build another copy. You have to manage it separately. Right. So clearly that's a little bit brain damaged. Right. So, okay. So now you take a little bit of, you know, newer vendors who may take that backup platform and do a little bit more with that. Maybe they provide security, but your problem still remains. How do you do more with the data? How do you do some analytics? >>Like he's saying, right. How do you test development on that? How do you migrate the data to the cloud? How do you manage it? The data at scale? How do you do you provide a unified experience across, across multiple cloud, which you're calling the super cloud. That's where cohesive goes. So what we do, we provide a platform, right? We have tentacles in on-prem in each of the clouds. And on top of that, it looks like one platform that you manage. We have a single control plane, a UI. If you may, a single pin of glass, if, if you may, that our customers can use to manage all of it. And now it looks, starts looking like one platform. You mentioned Google, do you, when you go to, you know, kind Google search or a URL, do you really care? What happens behind the scenes mean behind the scenes? Google's built a platform that spans the whole world. No, >>But it's interesting. What's behind the scenes. It's a beautiful now. And I would say, listen, one other thing to pull on Dave, on the security part, I saw a lot of vendors this day in this space, white washing a security message on top of backup. Okay. And CSO, see through that, they'll offer warranties and guarantees or whatever, have you of X million dollars with a lot of caveats, which will never paid because it's like escape clause here. We won't pay it. Yeah. And, and what people really want is a scalable solution that works. And you know, we can match every warranty that's easy. And what I heard was this was the most scalable solution at scale. And that's why you have to approach this with a Google type mindset. I love the fact that every time you listen to sun pitch, I would, what, what I like about him, the most common word to use is scale. >>We do things at scale. So I found that him and AUR and some of the early Google people who come into the company had thought about scale. And, and even me it's like day eight. I found even the non-tech pieces of it. The processes that, you know, these guys are built for simple things in some cases were better than some of the things I saw are bigger companies I'd been used to. So we just have to continue, you know, building a scale platform with the enterprise. And then our cloud product is gonna be the simple solution for the masses. And my view of the world is there's 5,000 big companies and 5 million small companies we'll push the 5 million small companies as the cloud. Okay. Amazon's an investor in the company. AWS is a big partner. We'll talk about I'm sure knowing John's interest in that area, but that's a cloud play and that's gonna go to the cloud really fast. You not build you're in the marketplace, you're in the marketplace. I mean, maybe talk about the history of the Amazon relationship investing and all that. >>Yeah, absolutely. So in two years back late 2020, we, you know, in collaboration with AWS who also by the way is an investor now. And in cohesive, we rolled out what we call data management as a service. It's our SaaS service where we run our software in the cloud. And literally all customers have to do is just go there and sign on, right? They don't have to manage any infrastructure and stuff. What's nice is they can then combine that with, you know, software that they might have bought from cohesive. And it still looks like one platform. So what I'm trying to say is that they get a choice of the, of the way they wanna consume our software. They can consume it as a SAS service in the cloud. They can buy our software, manage it themselves, offload it to a partner on premises or what have you. But it still looks like that one platform, what you're calling a Supercloud >>Yeah. And developers are saying, they want the bag of Legos to compose their solutions. That's the Nirvana they want to get there. So that's, it has to look the same. >>Well, what is it? What we're calling a Superlo can we, can we test that for a second? So data management and service could span AWS and on-prem with the identical experience. So I guess I would call that a Supercloud I presume it's not gonna through AWS span multiple clouds, but, but >>Why not? >>Well, well interesting cuz we had this, I mean, so, okay. So we could in the future, it doesn't today. Well, >>David enough kind of pause for a second. Everything that we do there, if we do it will be customer driven. So there might be some customers I'll give you one Walmart that may want to store the data in a non AWS cloud risk cuz they're competitors. Right. So, but the control plane could still be in, in, in the way we built it, but the data might be stored somewhere else. >>What about, what about a on-prem customer? Who says, Hey, I, I like cohesive. I've now got multiple clouds. I want the identical experience across clouds. Yeah. Okay. So, so can you do that today? How do you do that today? Can we talk >>About that? Yeah. So basically think roughly about the split between the data plane and the control plane, the data plane is, you know, our cohesive clusters that could be sitting on premises that could be sitting in multiple data centers or you can run an instance of that cluster in the cloud, whichever cloud you choose. Right. That's what he was referring to as the data plane. So collectively all these clusters from the data plane, right? They stored the data, but it can all be managed using the control plane. So you still get that single image, the single experience across all clouds. And by the way, the, the, the, the cloud vendor does actually benefit because here's a customer. He mentioned a customer that may not wanna go to AWS, but when they get the data plane on a different cloud, whether it's Azure, whether it's the Google cloud, they then get data management services. Maybe they're able to replicate the data over to AWS. So AWS also gains. >>And your deployment model is you instantiate the cohesive stack on each of the regions and clouds, is that correct? And you building essentially, >>It all happens behind the scenes. That's right. You know, just like Google probably has their tentacles all over the world. We will instantiate and then make it all look like one platform. >>I mean, you should really think it's like a human body, right? The control planes, the head. Okay. And that controls everything. The data plane is large because it's a lot of the data, right? It's the rest of the body, that data plane could be wherever you want it to be. Traditionally, the part the old days was tape. Then you got disk. Now you got multiple clouds. So that's the way we think about it. And there on that piece of it will be neutral, right? We should be multi-cloud to the data plane being every single place. Cause it's customer demand. Where do you want your store data? Air gapped. On-prem no problem. We'll work with Dell. Okay. You wanna be in a particular cloud, AWS we'll work then optimized with S3 and glacier. So this is where I think the, the path to a multi-cloud or Supercloud is to be customer driven, but the control plane sits in Amazon. So >>We're blessed to have a number of, you know, technical geniuses in here. So earlier we were speaking to Ben wa deja VI, and what they do is different. They don't instantiate an individual, you know, regions. What they do is of a single global. Is there a, is there an advantage of doing it the way the cohesive does it in terms of simplicity or how do you see that? Is that a future direction for you from a technology standpoint? What are the trade offs there? >>So you want to be where the data is when you said single global, I take it that they run somewhere and the data has to go there. And in this day age, correct >>Said that. He said, you gotta move that in this >>Day and >>Age query that's, you know, across regions, look >>In this day and age with the way the data is growing, the way it is, it's hard to move around the data. It's much easier to move around the competition. And in these instances, what have you, so let the data be where it is and you manage it right there. >>So that's the advantage of instantiating in multiple regions. As you don't have to move the >>Data cost, we have the philosophy we call it. Let's bring the, the computation to the data rather than the data to >>The competition and the same security model, same governance model, same. How do you, how do you federate that? >>So it's all based on policies. You know, this overarching platform controlled by, by the control plane, you just, our customers just put in the policies and then the underlying nuts and bolts just take care >>Of, you know, it's when I first heard and start, I started watching some of his old videos, ACE really like hyperconverged brought to secondary storage. In fact, he said, oh yeah, that's great. You got it. Because I first called this idea, hyperconverged secondary storage, because the idea of him inventing hyperconverge was bringing compute to storage. It had never been done. I mean, you had the kind of big VC stuff, but these guys were the first to bring that hyperconverge at, at Nutanix. So I think this is that same idea of bringing computer storage, but now applied not to the warm data, but to the rest of the data, including a >>Lot of, what about developers? What's, what's your relationship with developers? >>Maybe you talk about the marketplace and everything >>He's yeah. And I'm, I'm curious as to do you have a PAs layer, what we call super PAs layer to create an identical developer experience across your Supercloud. I'm gonna my >>Term. So we want our customers not just to benefit from the software that we write. We also want them to benefit from, you know, software that's written by developers by third party people and so on and so forth. So we also support a marketplace on the platform where you can download apps from third party developers and run them on this platform. There's a, a number of successful apps. There's one, you know, look like I said, our entry point might be backups, but even when backups, we don't do everything. Look, for instance, we don't backup mainframes. There is a, a company we partner with, you know, and their software can run in our marketplace. And it's actually used by many, many of our financial customers. So our customers don't get, just get the benefit of what we build, but they also get the benefit of what third parties build. Another analogy I like to draw. You can tell. And front of analogy is I drew an analogy to hyperscale is like Google. Yeah. The second analogy I like to draw is that to a simple smartphone, right? A smartphone starts off by being a great phone. But beyond that, it's also a GPS player. It's a, it's a, it's a music player. It's a camera, it's a flashlight. And it also has a marketplace from where you can download apps and extend the power of that platform. >>Is that a, can we think of that as a PAs layer or no? Is it really not? You can, okay. You can say, is it purpose built for what you're the problem that you're trying to solve? >>So we, we just built APIs. Yeah. Right. We have an SDK that developers can use. And through those APIs, they get to leverage the underlying services that exist on the platform. And now developers can use that to take advantage of all that stuff. >>And it was, that was a key factor for me too. Cause I, what I, you know, I've studied all the six, seven players that sort of so-called leaders. Nobody had a developer ecosystem, nobody. Right? The old folks were built for the hardware era, but anyones were built for the cloud to it didn't have any partners were building on their platform. So I felt for me listen, and that the example of, you know, model nine rights, the name of the company that does back up. So there's, there's companies that are built on and there's a number of others. So our goal is to have a big tent, David, to everybody in the ecosystem to partner with us, to build on this platform. And, and that may take over time, but that's the way we're build >>It. And you have a metadata layer too, that has the intelligence >>To correct. It's all abstract. That that's right. So it's a combination of data and metadata. We have lots of metadata that keeps track of where the data is. You know, it allows you to index the data you can do quick searches. You can actually, you, we talking about the control plan from that >>Tracing, >>You can inject a search that'll through search throughout your multi-cloud environment, right? The super cloud that you call it. We have all that, all that goodness sounds >>Like a Supercloud John. >>Yeah. I mean, data tracing involved can trace the data lineage. >>You, you can trace the data lineage. So we, you know, provide, you know, compliance and stuff. So you can, >>All right. So my final question to wrap up, we guys, first of all, thanks for coming on. I know you're super busy, San Jose. We, we know what you're gonna do. You're gonna amp it up and, you know, knock all your numbers out. Think you always do. But what I'm interested in, what you're gonna jump into, cuz now you're gonna have the creative license to jump in to the product, the platform there has to be the next level in your mind. Can you share your thoughts on where this goes next? Love the control plane, separate out from the data plane. I think that plays well for super. How >>Much time do you have John? This guy's got, he's got a wealth. Ditis keep >>Going. Mark. Give us the most important thing you're gonna focus on. That kind of brings the super cloud and vision together. >>Yeah. Right away. I'm gonna, perhaps I, I can ion into two things. The first one is I like to call it building the, the machine, the system, right. Just to draw an analogy. Look, I draw an analogy to the us traffic system. People from all walks of life, rich, poor Democrats, Republicans, you know, different states. They all work in the, the traffic system and we drive well, right. It's a system that just works. Whereas in some other countries, you know, the system doesn't work. >>We know, >>We know a few of those. >>It's not about works. It's not about the people. It's the same people who would go from here to those countries and, and not dry. Well, so it's all about the system. So the first thing I, I have my sights on is to really strengthen the system that we have in our research development to make it a machine. I mean, it functions quite well even today, but wanna take it to the next level. Right. So that I wanna get to a point where innovation just happens in the grassroots. And it just, just like >>We automations scale optic brings all, >>Just happens without anyone overseeing it. Anyone there's no single point of bottleneck. I don't have to go take any diving catches or have you, there are people just working, you know, in a decentralized fashion and innovation just happens. Yeah. The second thing I work on of course is, you know, my heart and soul is in, you know, driving the vision, you know, the next level. And that of course is part of it. So those are the two things >>We heard from all day in our super cloud event that there's a need for an, an operating system. Yeah. Whether that's defacto standard or open. Correct. Do you see a consortium around the corner potentially to bring people together so that things could work together? Cuz there really isn't no stand there. Isn't a standards bodies. Now we have great hyperscale growth. We have on-prem we got the super cloud thing happening >>And it's a, it's kind of like what is an operating system? Operating system exposes some APIs that the applications can then use. And if you think about what we've been trying to do with the marketplace, right, we've built a huge platform and that platform is exposed through APIs. That third party developers can use. Right? And even we, when we, you know, built more and more services on top, you know, we rolled our D as we rolled out, backup as a service and a ready for thing security as a service governance, as a service, they're using those APIs. So we are building a distributor, putting systems of sorts. >>Well, congratulations on a great journey. Sanja. Congratulations on taking the hem. Thank you've got ball control. Now you're gonna be calling the ball cohesive as they say, it's, >>It's a team. It's, you know, I think I like that African phrase. If you want to go fast, you go alone. If you wanna go far, you go together. So I've always operated with the best deal. I'm so fortunate. This is to me like a dream come true because I always thought I wanted to work with a technologist that frees me up to do what I like. I mean, I started as an engineer, but that's not what I am today. Right? Yeah. So I do understand the product and this category I think is right for disruption. So I feel excited, you know, it's changing growing. Yeah. No. And it's a, it requires innovation with a cloud scale mindset and you guys have been great friends through the years. >>We'll be, we'll be watching you. >>I think it's not only disruption. It's creation. Yeah. There's a lot of white space that just hasn't been created yet. >>You're gonna have to, and you know, the proof, isn't the pudding. Yeah. You already have five of the biggest 10 financial institutions in the us and our customers. 25% of the fortune 500 users, us two of the biggest five pharmaceutical companies in the world use us. Probably, you know, some of the biggest companies, you know, the cars you have, you know, out there probably are customers. So it's already happening. >>I know you got an IPO filed confidentially. I know you can't talk numbers, but I can tell by your confidence, you're feeling good right now we are >>Feeling >>Good. Yeah. One day, one week, one month at a time. I mean, you just, you know, I like the, you know, Jeff Bezos, Andy jazzy expression, which is, it's always day one, you know, just because you've had success, even, you know, if, if a and when an IPO O makes sense, you just have to stay humble and hungry because you realize, okay, we've had a lot of success in the fortune 1000, but there's a lot of white space that hasn't picked USS yet. So let's go, yeah, there's lots of midmarket account >>Product opportunities are still, >>You know, I just stay humble and hungry and if you've got the team and then, you know, I'm really gonna be working also in the ecosystem. I think there's a lot of very good partners. So lots of ideas brew through >>The head. Okay. Well, thank you so much for coming on our super cloud event and, and, and also doubling up on the news of the new appointment and congratulations on the success guys. Coverage super cloud 22, I'm sure. Dave ante, thanks for watching. Stay tuned for more segments after this break.

Published Date : Aug 10 2022

SUMMARY :

Who's now the CEO of cohesive the emo Aaron who's the CTO. Is the father. To see you guys. So first of all, we'll get into super before we get into the Supercloud. Most of them were, you know, There you go. So I opted to do the depth job, you know, be the visionary, cuz this is a real big transition for founders and you know, I have founder artists cuz everyone, some of the biggest, you know, people in the industry on his speed dial, you And I think if you look at And his book, you read his book. So Frank, you know, many of us, we grow being Yeah. So the day I got the job, I, I got a text from Frank and I said, Yeah. You got the board and you got the operations cuz you look, you know, look at sloop when he's got Scarelli wherever he goes, I think the company, you know, being about 2000 employees And you know, even just the week we, we were announced that this announcement happened. So I gotta ask you guys, what do you see as structural change right now in the industry? Number two, I think the hackers out there have realized that, you know, What's the difference between data management and backup. just the first use case, but it's really about that platform on which you can How do you see You start maybe by backing with data, but then you secure it and then you do more with that data. I mean, there you go. And he said, listen, you know, if you look at companies like snowflake and data bricks, the analytics of, you know, if you wanna call it secondary data or backed up data or data, you know, I didn't talk to all the 3000 customers, but the biggest customers and I was doing diligence. How do you see that moment? So now you take a little bit of, And on top of that, it looks like one platform that you I love the fact that every time you have to continue, you know, building a scale platform with the enterprise. we, you know, in collaboration with AWS who also by the way is an investor So that's, it has to look the same. So I guess I would call that a Supercloud So we could in the future, So there might be some customers I'll give you one Walmart that may want to store the data in a non How do you do that today? the data plane is, you know, our cohesive clusters that could be sitting on premises that could be sitting It all happens behind the scenes. So that's the way we think about it. We're blessed to have a number of, you know, technical geniuses in here. So you want to be where the data is when you said single global, He said, you gotta move that in this so let the data be where it is and you manage it right there. So that's the advantage of instantiating in multiple regions. to the data rather than the data to The competition and the same security model, same governance model, same. by the control plane, you just, our customers just put in the policies and then the underlying nuts and bolts just I mean, you had the kind of big VC stuff, but these guys were the first to bring layer to create an identical developer experience across your Supercloud. So we also support a marketplace on the platform where you can download apps from Is that a, can we think of that as a PAs layer or no? And through those APIs, they get to leverage the underlying services that So I felt for me listen, and that the example of, you know, model nine rights, You know, it allows you to index the data you can do quick searches. The super cloud that you call it. So we, you know, provide, you know, compliance and stuff. You're gonna amp it up and, you know, knock all your numbers out. Much time do you have John? That kind of brings the super cloud and vision together. you know, the system doesn't work. I have my sights on is to really strengthen the system that we have in our research you know, driving the vision, you know, the next level. Do you see a consortium around the corner potentially to bring people together so that things could work together? And even we, when we, you know, built more and more services on top, you know, Congratulations on taking the hem. So I feel excited, you know, it's changing growing. I think it's not only disruption. Probably, you know, some of the biggest companies, you know, the cars you have, you know, I know you can't talk numbers, but I can tell by your confidence, I mean, you just, you know, I like the, you know, you know, I'm really gonna be working also in the ecosystem. the news of the new appointment and congratulations on the success guys.

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Supercloud – Real or Hype? | Supercloud22


 

>>Okay, welcome back everyone to super cloud 22 here in our live studio performance. You're on stage in Palo Alto. I'm Sean fur. You're host with the queue with Dave ante. My co it's got a great industry ecosystem panel to discuss whether it's realer hype, David MC Janet CEO of Hashi Corp, hugely successful company as will LA forest field CTO, Colu and Victoria over yourgo from VMware guys. Thanks for coming on the queue. Appreciate it. Thanks for having us. So realer, hype, super cloud David. >>Well, I think it depends on the definition. >>Okay. How do you define super cloud start there? So I think we have a, >>I think we have a, like an inherently pragmatic view of super cloud of the idea of super cloud as you talk about it, which is, you know, for those of us that have been in the infrastructure world for a long time, we know there are really only six or seven categories of infrastructure. There's sort of the infrastructure security, networking databases, middleware, and, and, and, and really the message queuing aspects. And I think our view is that if the steady state of the world is multi-cloud, what you've seen is sort of some modicum of standardization across those different elements, you know, take, you know, take confluent. You know, I, I worked in the middleware world years ago, MQ series, and typical multicast was how you did message queuing. Well, you don't do that anymore. All the different cloud providers have their own message, queuing tech, there's, Google pub sub, and the equivalents across the different, different clouds. Kafka has provided a consistent way to do that. And they're not trying to project that. You can run everything connected. They're saying, Hey, you should standardize on Kafka for message cuing is that way you can have operational consistency. So I think to me, that's more how we think about it is sort of, there is sort of layer by layer of sort of de facto standardization for the lingo Franco. >>So a streaming super cloud is how you would think of it, or no, I just, or a component of >>Cloud that could be a super cloud. >>I just, I just think that there are like, if I'm gonna build an application message, queuing is gonna be a necessary element of it. I'm gonna use Kafka, not, you know, a native pub sub engine on one of the clouds, because operationally that's just the only way I can do it. So I think that's more, our view's much more pragmatic rather than trying to create like a single platform that you can run everywhere and deal with the networking realities of like network, you know, hops missing across those different worlds and have that be our responsibility. It's much more around, Hey, let's standardize each layer, operational >>Standardized layer that you can use to build a super cloud if that's in your, your intent or, yeah. Okay. >>And it reminds me of the web services days. You kind of go throwback there. I mean, we're kind of living the next gen of web services, the dream of that next level, because DevOps dev SecOps now is now gone mainstream. That's the big challenge we're hearing devs are doing great. Yep. But the ops teams and screen, they gotta go faster. This seems to be a core, I won't say blocker, but more of a drag to the innovation. >>Well, I I'll just get off, I'll hand it off to, to you guys. But I think the idea that like, you know, if I'm gonna have an app that's running on Amazon that needs to connect to a database that's running on, on the private data center, that's essentially the SOA notion, you know, w large that we're all trying to solve 20 years ago, but is much more complicated because you're brokering different identity models, different networking models. They're just much more complex. So that's where the ops bit is the constraint, you know, for me to build that app, not that complicated for the ops person to let it see traffic is another thing altogether. I think that's, that's the break point for so much of what looks easier to a developer is the operational reality of how you do that. And the good news is those are actually really well solved problems. They're just not broadly understood. >>Well, what's your take, you talk to customers all the time, field CTO, confluent, really doing well, streaming data. I mean, everyone's doing it now. They have to, yeah. These are new things that pop up that need solutions. You guys step up and doing more. What's your take on super cloud? >>Well, I mean, the way we address it honestly is we don't, it's gonna be honest. We don't think about super cloud much less is the fact that SAS is really being pushed down. Like if we rely on seven years ago and you took a look at SAS, like it was obvious if you were gonna build a product for an end consumer or business user, you'd do SAS. You'd be crazy not to. Right. But seven years ago, if you look at your average software company producing something for a developer that people building those apps, chances are you had an open source model. Yeah. Or, you know, self-managed, I think with the success of a lot of the companies that are here today, you know, snowflake data, bricks, Colu, it's, it's obvious that SaaS is the way to deliver software to the developers as well. And as such, because our product is provided that way to the developers across the clouds. That's, that's how they have a unifying data layer, right. They don't necessarily, you know, developers like many people don't necessarily wanna deal with the infrastructure. They just wanna consume cloud data services. Right. So that's how we help our customers span cloud. >>So we evenly that SAS was gonna be either built on a single cloud or in the case of service. Now they built their own cloud. Right. So increasingly we're seeing opportunities to build a Salesforce as well across clouds tap different, different, different services. So, so how does that evolve? Do you, some clouds have, you know, better capabilities in other clouds. So how does that all get sort of adjudicated, do you, do you devolve to the lowest common denominator? Or can you take the best of all of each? >>The whole point to that I think is that when you move from the business user and the personal consumer to the developer, you, you can no longer be on a cloud, right. There has to be locality to where applications are being developed. So we can't just deploy on a single cloud and have people send their data to that cloud. We have to be where the developer is. And our job is to make the most of each, an individual cloud to provide the same experience to them. Right. So yes, we're using the capabilities of each cloud, but we're hiding that to the developer. They don't shouldn't need to know or care. Right. >>Okay. And you're hiding that with the abstraction layer. We talked about this before Victoria, and that, that layer has what, some intelligence that has metadata knowledge that can adjudicate what, what, the best, where the best, you know, service is, or function of latency or data sovereignty. How do you see that? >>Well, I think as the, you need to instrument these applications so that you, you, you can get that data and then make the intelligent decision of where, where, where this, the deploy application. I think what Dave said is, is right. You know, the level of super cloud that they talking about is the standardization across messaging. And, and are you what's happening within the application, right? So you don't, you are not too dependent on the underlying, but then the application say that it takes the form of a, of a microservice, right. And you deploy that. There has to be a way for operator to say, okay, I see all these microservices running across clouds, and I can factor out how they're performing, how I, I, life lifecycle managed and all that. And so I think there is, there is, to me, there's the next level of the super cloud is how you factor this out. So an operator can actually keep up with the developers and make sense of all that and manage it. Like >>You guys that's time. Like its also like that's what Datadog does. So Datadog basically in allows you to instrument all those services, on-prem private data center, you know, all the different clouds to have a consistent view. I think that that's not a good example of a vendor that's created a, a sort of a level of standardization across a layer. And I think that's, that's more how we think about it. I think the notion of like a developer building an application, they can deploy and not have to worry where it exists. Yeah. Is more of a PAs kind of construct, you know, things like cloud Foundry have done a great job of, of doing that. But underneath that there's still infrastructure. There's still security. There's still networking underneath it. And I think that's where, you know, things like confluent and perhaps at the infrastructure layer have standardized, but >>You have off the shelf PAs, if I can call it that. Yeah. Kind of plain. And then, and then you have PAs and I think about, you mentioned snowflake, snowflake is with snow park, seems to be developing a PAs layer that's purpose built for their specific purpose of sharing data and governing data across multiple clouds call super paths. Is, is that a prerequisite of a super cloud you're building blocks. I'm hearing yeah. For super cloud. Is that a prerequisite for super cloud? That's different than PAs of 10 years ago. No, but I, >>But I think this is, there's just different layers. So it's like, I don't know how that the, the snowflake offering is built built, but I would guess it's probably built on Terraform and vault and cons underneath it. Cuz those are the ingredients with respect to how you would build a composite application that runs across multiple. And >>That's how Oracle that town that's how Oracle with the Microsoft announcement. They just, they just made if you saw that that was built on Terraform. Right. But, but they would claim that they, they did some special things within their past that were purpose built for, for sure. Low latency, for example, they're not gonna build that on, you know, open shift as an, as an example, they're gonna, you know, do their own little, you know, >>For sure, for sure. So I think what you're, you're pointing at and what Victoria was talking about is, Hey, can a vendor provided consistent experience across the application layer across these multiple clouds? And I would say, sure, just like, you know, you might build a mobile banking application that has a front end on Amazon in the back end running on vSphere on your private data center. Sure. But the ingredients you use to do that have to be, they can't be the cloud native aspects for how you do that. How do you think about, you know, the connectivity of, of like networking between that thing to this thing? Is it different on Amazon? Is it different on Azure? Is it different on, on Google? And so the, the, the, the companies that we all serve, that's what they're building, they're building composited applications. Snowflake is just an example of a company that we serve this building >>Composite. And, but, but, but don't those don't, you have to hide the complexity of that, those, those cloud native primitives that's your job, right. Is to actually it creates simplicity across clouds. Is it not? >>Why? Go ahead. You. >>Yeah, absolutely. I mean that in fact is what we're doing for developers that need to do event streaming, right. That need to process this data in real time. Now we're, we're doing the sort of things that Victoria was just talking about, like underneath the covers, of course, you know, we're using Kubernetes and we're managing the differences between the clouds, but we're hiding the, that, and we've become sort of a defacto standard across the cloud. So if I'm developing an app in any of those cloud, and I think we all know, and you were mentioning earlier every significant company's multi-cloud now all the large enterprises, I just got back from Brazil and like every single one of 'em have multiple clouds and on-prem right. So they need something that can span those. >>What's the challenge there. If you talk to those customers, because we're seeing the same thing, they have multiple clouds. Yeah. But it was kind of by default or they had some use case, either.net developers there with Azure, they'll do whatever cloud. And it kind of seems specialty relative to the cloud native that they're on what problems do they have because the complexity to run infrastructure risk code across clouds is hard. Right? So the trade up between native cloud and have better integration to complexity of multiple clouds seems to be a topic around super cloud. What are you seeing for, for issues that they might have or concerns? >>Yeah. I mean, honestly it is, it is hard to actually, so here's the thing that I think is kind of interesting though, by the way, is that I, I think we tend to, you know, if you're, if you're from a technical background, you tend to think of multicloud as a problem for the it organization. Like how do we solve this? How do we save money? But actually it's a business problem now, too, because every single one of these companies that have multiple clouds, they want to integrate their data, their products across these, and it it's inhibiting their innovation. It's hard to do, but that's where something like, you know, Hatchie Corp comes in right. Is to help solve that. So you can instrument it. It has to happen at each of these layers. And I suppose if it does happen at every single layer, then voila, we organically have something that amounts to Supercloud. Right. >>I love how you guys are representing each other's firms. And, but, but, and they also correct me if I'm a very similar, your customers want to, it is very similar, but your customers want to monetize, right. They want bring their tools, their software, their particular IP and their data and create, you know, every, every company's a software company, as you know, Andreesen says every company's becoming a cloud company to, to monetize in, in the future. Is that, is that a reasonable premise of super cloud? >>Yeah. I think, think everyone's trying to build composite applications to, to generate revenue. Like that's, that's why they're building applications. So yeah. One, 100%. I'm just gonna make it point cuz we see it as well. Like it's actually quite different by geography weirdly. So if you go to like different geographies, you see actually different cloud providers, more represented than others. So like in north America, Amazon's pretty dominant Japan. Amazon's pretty dominant. You go to Southeast Asia actually. It's not necessarily that way. Like it might be Google for, for whatever reason more hourly Bob. So this notion of multi's just the reality of one's everybody's dealing with. But yeah, I think everyone, everyone goes through the same process. What we've observed, they kind of go, there's like there's cloud V one and there's cloud V two. Yeah. Cloud V one is sort of the very tactical let's go build something on cloud cloud V two is like, whoa, whoa, whoa, whoa. And I have some stuff on Amazon, some stuff on Azure, some stuff on, on vSphere and I need some operational consistency. How do I think about zero trust across that way in a consistent way. And that's where this conversation comes into being. It's sort of, it's not like the first version of cloud it's actually when people step back and say, Hey, Hey, I wanna build composite applications to monetize. How am I gonna do that in an industrialized way? And that's the problem that you were for. It's >>Not, it's not as, it's not a no brainer like it was with cloud, go to the cloud, write an app. You're good here. It's architectural systems thinking, you gotta think about regions. What's the latency, you know, >>It's step back and go. Like, how are we gonna do this, this exactly. Like it's wanted to do one app, but how we do this at scale >>Zero trust is a great example. I mean, Amazon kind of had, was forced to get into the zero trust, you know, discussion that, that wasn't, you know, even a term that they used and now sort of, they're starting to talk about it, but within their domain. And so how do you do zero trust trust across cost to your point? >>I, I wonder if we're limiting our conversation too much to the, the very technical set of developers, cuz I'm thinking back at again, my example of C plus plus libraries C plus plus libraries makes it easier. And then visual BA visual basic. Right. And right now we don't have enough developers to build the software that we want to build. And so I want, and we are like now debating, oh, can we, do we hide that AI API from Google versus that SQL server API from, from Microsoft. I wonder at some point who cares? Right. You know, we, I think if we want to get really economy scale, we need to get to a level of abstraction for developers that really allows them to say, I don't need, for most of most of the procedural application that I need to build as a developer, as a, as a procedural developer, I don't care about this. Some, some propeller had, has done that for me. I just like plug it in my ID and, and I use it. And so I don't, I don't know how far we are from that, but if we don't get to that level, it fits me that we never gonna get really the, the economy or the cost of building application to the level. >>I was gonna ask you in the previous segment about low code, no code expanding the number of developers out there and you talking about propel heads. That's, that's what you guys all do. Yeah. You're the technical geniuses, right. To solve that problem so that, so you can have low code development is that I >>Don't think we have the right here. Cause I, we, we are still, you know, trying to solve that problem at that level. But, but >>That problem has to be solved first, right before we can address what you're talking about. >>Yeah. I, I worked very closely with one of my biggest mentors was Adam Bosworth that built, you know, all the APIs for visual basics and, and the SQL API to visual basic and all that stuff. And he always was on that front. In fact that his last job was at my, at AWS building that no code environment. So I'm a little detached from that. It just hit me as we were discussing this. It's like, maybe we're just like >>Creating, but I would, I would argue that you kind of gotta separate the two layers. So you think about the application platform layer that a developer interfaces to, you know, Victoria and I worked together years ago and one of the products we created was cloud Foundry, right? So this is the idea of like just, you know, CF push, just push this app artifact and I don't care. That's how you get the developer community written large to adopt something complicated by hiding all the complexity. And I think that that is one model. Yeah. Turns out Kubernetes is actually become a peer to that and perhaps become more popular. And that's what folks like Tanza are trying to do. But there's another layer underneath that, which is the infrastructure that supports it. Right? Yeah. Cause that's only needs to run on something. And I think that's, that's the separation we have to do. Yes. We're talking a little bit about the plumbing, but you know, we just easily be talking about the app layer. You need, both of them. Our point of view is you need to standardize at this layer just like you need standardize at this layer. >>Well, this is, this is infrastructure. This is DevOps V two >>Dev >>Ops. Yeah. And this is where I think the ops piece with open source, I would argue that open source is blooming more than ever. So I think there's plenty of developers coming. The automation question becomes interesting because I think what we're seeing is shift left is proving that there's app developers out there that wanna stay in their pipelining. They don't want to get in under the hood. They just want infrastructure as code, but then you got supply chain software issues there. We talked about the Docker on big time. So developers at the top, I think are gonna be fine. The question is what's the blocker. What's holding them back. And I don't see the devs piece Victoria as much. What do you guys think? Is it, is the, is the blocker ops or is it the developer experience? That's the blocker. >>It's both. There are enough people truthfully. >>That's true. Yeah. I mean, I think I sort of view the developer as sort of the engine of the digital innovation. So, you know, if you talk about creative destruction, that's, that was the economic equivalent of softwares, eating the world. The developers are the ones that are doing that innovation. It's absolutely essential that you make it super easy for them to consume. Right. So I think, you know, they're nerds, they want to deal with infrastructure to some degree, but I think they understand the value of getting a bag of Legos that they can construct something new around. And I think that's the key because honestly, I mean, no code may help for some things. Maybe I'm just old >>School, >>But I, I went through this before with like Delphy and there were some other ones and, and I hated it. Like I just wanted a code. Yeah. Right. So I think making them more efficient is, is absolutely good. >>But I think what, where you're going with that question is that the, the developers, they tend to stay ahead. They, they just, they're just gear, you know, wired that way. Right. So I think right now where there is a big bottleneck in developers, I think the operation team needs to catch up. Cuz I, I talk to these, these, these people like our customers all the time and I see them still stuck in the old world. Right. Gimme a bunch of VMs and I'll, I know how to manage well that world, you know, although as lag is gonna be there forever, so managing mainframe. But so if they, the world is all about microservices and containers and if the operation team doesn't get on top of it and the security team that then that they're gonna be a bottleneck. >>Okay. I want to ask you guys if the, if the companies can get through that knothole of having their ops teams and the dev teams work well together, what's the benefits of a Supercloud. How do you see the, the outcome if you kind of architect it, right? You think the big picture you zoom as saying what's the end game look like for Supercloud? Is that >>What I would >>Say? Or what's the Nirvana >>To me Nirvana is that you don't care. You just don't don't care. You know, you just think when you running building application, let's go back to the on-prem days. You don't care if it runs on HP or Dell or, you know, I'm gonna make some enemies here with my old, old family, but you know, you don't really care, right. What you want is the application is up and running and people can use it. Right. And so I think that Nirvana is that, you know, there is some, some computing power out there, some pass layer that allows me to deploy, build application. And I just like build code and I deploy it and I get value at a reasonable cost. I think one of the things that the super cloud for as far as we're concerned is cost. How do you manage monitor the cost across all this cloud? >>Make sure that you don't, the economics don't get outta whack. Right? How many companies we know that have gone to the cloud only to realize that holy crap, now I, I got the bill and, and you know, I, as a vendor, when I was in my previous company, you know, we had a whole team figuring out how to lower our cost on the one hyperscaler that we were using. So these are, you know, the, once you have in the super cloud, you don't care just you, you, you go with the path of least the best economics is. >>So what about the open versus closed debate will you were mentioning that we had snowflake here and data bricks is both ends of the spectrum. Yeah. You guys are building open standards across clouds. Clearly even the CLO, the walled gardens are using O open standards, but historically de facto standards have emerged and solved these problems. So the super cloud as a defacto standard, versus what data bricks is trying to do super cloud kind of as an, as an open platform, what are you, what are your thoughts on that? Can you actually have an, an open set of standards that can be a super cloud for a specific purpose, or will it just be built on open source technologies? >>Well, I mean, I, I think open source continues to be an important part of innovation, but I will say from a business model perspective, like the days, like when we started off, we were an open source company. I think that's really done in my opinion, because if you wanna be successful nowadays, you need to provide a cloud native SAS oriented product. It doesn't matter. What's running underneath the covers could be commercial closed source, open source. They just wanna service and they want to use it quite frankly. Now it's nice to have open source cuz the developers can download it and run on their laptop. But I, I can imagine in 10 years time actually, and you see most companies that are in the cloud providing SAS, you know, free $500 credit, they may not even be doing that. They'll just, you know, go whatever cloud provider that their company is telling them to use. They'll spin up their SAS product, they'll start playing with it. And that's how adoption will grow. Right? >>Yeah. I, I think, I mean my personal view is that it's, that it's infrastructure is pervasive enough. It exists at the bottom of everything that the standards emerge out of open source in my view. And you think about how something like Terraform is built, just, just pick one of the layers there's Terraform core. And then there's a plugin for everything you integrate with all of those are open source. There are over 2000 of these. We don't build them. Right. That's and it's the same way that drove Linux standardization years ago, like someone had to build the drivers for every piece of hardware in the world. The market does not do that twice. The market does that once. And so I, I I'm deeply convicted that opensource is the only way that this works at the infrastructure layer, because everybody relies on it at the application layer, you may have different kinds of databases. You may have different kind of runtime environments. And that's just the nature of it. You can't to have two different ways of doing network, >>Right? Because the stakes are so high, basically. >>Yeah. Cuz there's, there's an infinite number of the surface areas are so large. So I actually worked in product development years ago for middleware. And the biggest challenge was how do you keep the adapter ecosystem up to date to integrate with everything in the world? And the only way to do it in our view is through open source. And I think that's a fundamental philosophical view that it we're just, you know, grounded in. I think when people are making infrastructure decisions that span 20 years at the customer base, this is what they think about. They go which standard it will emerge based on the model of the vendor. And I don't think my personal view is, is it's not possible to do in a, in >>A, do you think that's a defacto standard kind of psychological perspective or is there actual material work being done or both in >>There it's, it's, it's a network effect thing. Right? So, so, you know, before Google releases a new service service on Google cloud, as part of the release checklist is does it support Terraform? They do that work, not us. Why? Because every one of their customers uses Terraform to interface with them and that's how it works. So see, so the philosophical view of, of the customers, okay, what am I making a standardize on for this layer for the next 30 years? It's kind of a no brainer. Philosophically. >>I tend, >>I think the standards are organically created based upon adoption. I mean, for instance, Terraform, we have a provider we're again, we're at the data layer that we created for you. So like, I don't think there's a board out there. I mean there are that creating standards. I think those days are kind of done to be honest, >>The, the Terraform provider for vSphere has been downloaded five and a half million times this year. Yeah. Right. Like, so, I >>Mean, these are unifying moments. This are like the de facto standards are really important process in these structural changes. I think that's something that we're looking at here at Supercloud is what's next? What has to unify look what Kubernetes has done? I mean, that's essentially the easy thing to orchestra, but people get behind it. So I see this is a big part of this next, the two. Totally. What do you guys see that's needed? What's the rallying unification point? Is it the past layer? Is it more infrastructure? I guess that's the question we're trying to, >>I think every layer will need that open source or a major traction from one of the proprietary vendor. But I, I agree with David, it's gonna be open source for the most part, but you know, going back to the original question of the whole panel, if I may, if this is reality of hype, look at the roster of companies that are presenting or participating today, these are all companies that have some sort of multi-cloud cross cloud, super cloud play. They're either public have real revenue or about to go public. So the answer to the question. Yeah, it's real. Yeah. >>And so, and there's more too, we had couldn't fit him in, but we, >>We chose super cloud on purpose cuz it kind of fun, John and I kind came up with it and, and but, but do you think it's, it hurts the industry to have this, try to put forth this new term or is it helpful to actually try to push the industry to define this new term? Or should it just be multi-cloud 2.0, >>I mean, conceptually it's different than multi-cloud right. I mean, in my opinion, right? So in that, in that respect, it has value, right? Because it's talking about something greater than just multi-cloud everyone's got multi-cloud well, >>To me multi-cloud is the, the problem I should say the opportunity. Yeah. Super cloud or we call it cross cloud is the solution to that channel. Let's >>Not call again. And we're debating that we're debating that in our cloud already panel where we're talking about is multi-cloud a problem yet that needs to get solved or is it not yet ready for a market to your point? Is it, are we, are we in the front end of coming into the true problem set, >>Give you definitely answer to that. The answer is yes. If you look at the customers that are there, they won, they have gone through the euphoria phase. They're all like, holy something, what, what are we gonna do about this? Right. >>And, but they don't know what to do. >>Yeah. And the more advanced ones as the vendor look at the end of the day, markets are created by vendors that build ed that customers wanna buy. Yeah. Because they get value >>And it's nuance. David, we were sort talking about before, but Goldman Sachs has announced they're analysis software vendor, right? Capital one is a software vendor. I've been really interested Liberty what Cerner does with what Oracle does with Cerner and in terms of them becoming super cloud vendors and monetizing that to me is that is their digital transformation. Do you guys, do you guys see that in the customer base? Am I way too far out of my, of my skis there or >>I think it's two different things. I think, I think basically it's the idea of building applications. If they monetize yeah. There and Cerner's gonna build those. And you know, I think about like, you know, IOT companies that sell that sell or, or you think people that sell like, you know, thermostats, they sell an application that monetizes those thermostats. Some of that runs on Amazon. Some of that runs a private data center. So they're basically in composite applications and monetize monetizing them for the particular vertical. I think that's what we ation every day. That's what, >>Yeah. You can, you can argue. That's not, not anything new, but what's new is they're doing that on the cloud and taking across multiple clouds. Multiple. Exactly. That's what makes >>Edge. And I think what we all participate in is, Hey, in order to do that, you need to drive standardization of how you do provisioning, how you do networking, how you do security to underpin those applications. I think that's what we're all >>Talking about, guys. It's great stuff. And I really appreciate you taking the time outta your day to help us continue the conversation to put out in the open. We wanna keep it out in the open. So in the last minute we have left, let's go down the line from a hash core perspective, confluent and VMware. What's your position on super cloud? What's the outcome that you would like to see from your standpoint, going out five years, what's it look like they will start with you? >>I just think people like sort under understanding that there is a layer by layer of view of how to interact across cloud, to provide operational consistency and decomposing it that way. Thinking about that way is the best way to enable people to build and run apps. >>We wanna help our customers work with their data in real time, regardless of where they're on primer in the cloud and super cloud can enable them to build applications that do that more effectively. That's that's great for us >>For tour you. >>I, my Niana for us is customers don't care, just that's computing out there. And it's a, it's a, it's a tool that allows me to grow my business and we make it all, all the differences and all the, the challenges, you know, >>Disappear, dial up, compute utility infrastructure, ISN >>Code. I open up the thought there's this water coming out? Yeah, I don't care. I got how I got here. I don't wanna care. Well, >>Thank you guys so much and congratulations on all your success in the marketplace, both of you guys and VMware and your new journey, and it's gonna be great to watch. Thanks for participating. Really appreciate it. Thank you, sir. Okay. This is super cloud 22, our events, a pilot. We're gonna get it out there in the open. We're gonna get the data we're gonna share with everyone out in the open on Silicon angle.com in the cube.net. We'll be back with more live coverage here in Palo Alto. After this short break.

Published Date : Aug 9 2022

SUMMARY :

Thanks for coming on the queue. So I think we have a, So I think to me, that's more how we think about it is sort of, there is sort of layer by layer of it. I'm gonna use Kafka, not, you know, a native pub sub engine on one of the clouds, Standardized layer that you can use to build a super cloud if that's in your, your intent or, yeah. And it reminds me of the web services days. But I think the idea that like, you know, I mean, everyone's doing it now. a lot of the companies that are here today, you know, snowflake data, bricks, Or can you take the make the most of each, an individual cloud to provide the same experience to them. what, what, the best, where the best, you know, service is, or function of latency And so I think there is, there is, to me, there's the next level of the super cloud is how you factor this And I think that's where, you know, things like confluent and perhaps And then, and then you have PAs and I think about, it. Cuz those are the ingredients with respect to how you would build a composite application that runs across multiple. as an example, they're gonna, you know, do their own little, you know, And I would say, sure, just like, you know, you might build a mobile banking application that has a front end And, but, but, but don't those don't, you have to hide the complexity of that, those, Why? just talking about, like underneath the covers, of course, you know, we're using Kubernetes and we're managing the differences between And it kind of seems specialty relative to the cloud native that It's hard to do, but that's where something like, you know, Hatchie Corp comes in right. and create, you know, every, every company's a software company, as you know, Andreesen says every company's becoming a cloud And that's the problem that you were for. you know, Like it's wanted to do one app, but how we do this at scale you know, discussion that, that wasn't, you know, even a term that they used and now sort of, they're starting to talk about I don't need, for most of most of the procedural application that I need to build as a I was gonna ask you in the previous segment about low code, no code expanding the number of developers out there and you talking Cause I, we, we are still, you know, trying to solve that problem at that level. you know, all the APIs for visual basics and, and the We're talking a little bit about the plumbing, but you know, Well, this is, this is infrastructure. And I don't see the devs There are enough people truthfully. So I think, you know, they're nerds, they want to deal with infrastructure to some degree, So I think making them more efficient is, I know how to manage well that world, you know, although as lag is gonna be there forever, the outcome if you kind of architect it, right? And so I think that Nirvana is that, you know, there is some, some computing power out only to realize that holy crap, now I, I got the bill and, and you know, So what about the open versus closed debate will you were mentioning that we had snowflake here and data bricks I think that's really done in my opinion, because if you wanna be successful nowadays, And you think about how something like Terraform is built, just, just pick one of the layers there's Terraform Because the stakes are so high, basically. And the biggest challenge was how do you keep the adapter ecosystem up to date to integrate with everything in So, so, you know, before Google releases I think the standards are organically created based upon adoption. The, the Terraform provider for vSphere has been downloaded five and a half million times this year. I mean, that's essentially the easy thing to orchestra, but you know, going back to the original question of the whole panel, if I may, but do you think it's, it hurts the industry to have this, try to put forth this new term or is it I mean, conceptually it's different than multi-cloud right. Super cloud or we call it cross cloud is the solution to that channel. that needs to get solved or is it not yet ready for a market to your point? If you look at the customers that are there, that build ed that customers wanna buy. Do you guys, do you guys see that in the customer base? And you know, I think about like, you know, IOT companies that That's what makes in order to do that, you need to drive standardization of how you do provisioning, how you do networking, And I really appreciate you taking the time outta your day to help us continue the I just think people like sort under understanding that there is a layer by layer of view super cloud can enable them to build applications that do that more effectively. you know, I don't wanna care. Thank you guys so much and congratulations on all your success in the marketplace, both of you guys and VMware and your new

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Winning Cloud Models - De facto Standards or Open Clouds | Supercloud22


 

(bright upbeat music) >> Welcome back, everyone, to the "Supercloud 22." I'm John Furrier, host of "The Cube." This is the Cloud-erati panel, the distinguished experts who have been there from day one, watching the cloud grow, from building clouds, and all open source stuff as well. Just great stuff. Good friends of "The Cube," and great to introduce back on "The Cube," Adrian Cockcroft, formerly with Netflix, formerly AWS, retired, now commentating here in "The Cube," as well as other events. Great to see you back out there, Adrian. Lori MacVittie, Cloud Evangelist with F5, also wrote a great blog post on supercloud, as well as Dave Vellante as well, setting up the supercloud conversation, which we're going to get into, and Chris Hoff, who's the CTO and CSO of LastPass who's been building clouds, and we know him from "The Cube" before with security and cloud commentary. Welcome, all, back to "The Cube" and supercloud. >> Thanks, John. >> Hi. >> All right, Lori, we'll start with you to get things going. I want to try to sit back, as you guys are awesome experts, and involved from building, and in the trenches, on the front lines, and Adrian's coming out of retirement, but Lori, you wrote the post setting the table on supercloud. Let's start with you. What is supercloud? What is it evolving into? What is the north star, from your perspective? >> Well, I don't think there's a north star yet. I think that's one of the reasons I wrote it, because I had a clear picture of this in my mind, but over the past, I don't know, three, four years, I keep seeing, in research, my own and others', complexity, multi-cloud. "We can't manage it. They're all different. "We have trouble. What's going on? "We can't do anything right." And so digging into it, you start looking into, "Well, what do you mean by complexity?" Well, security. Migration, visibility, performance. The same old problems we've always had. And so, supercloud is a concept that is supposed to overlay all of the clouds and normalize it. That's really what we're talking about, is yet another abstraction layer that would provide some consistency that would allow you to do the same security and monitor things correctly. Cornell University actually put out a definition way back in 2016. And they said, "It's an architecture that enables migration "across different zones or providers," and I think that's important, "and provides interfaces to everything, "makes it consistent, and normalizes the network," basically brings it all together, but it also extends to private clouds. Sometimes we forget about that piece of it, and I think that's important in this, so that all your clouds look the same. So supercloud, big layer on top, makes everything wonderful. It's unicorns again. >> It's interesting. We had multiple perspectives. (mumbles) was like Snowflake, who built on top of AWS. Jerry Chan, who we heard from earlier today, Greylock Penn's "Castles in the Cloud" saying, "Hey, you can have a moat, "you can build an advantage and have differentiation," so startups are starting to build on clouds, that's the native cloud view, and then, of course, they get success and they go to all the other clouds 'cause they got customers in the ecosystem, but it seems that all the cloud players, Chris, you commented before we came on today, is that they're all fighting for the customer's workloads on their infrastructure. "Come bring your stuff over to here, "and we'll make it run better." And all your developers are going to be good. Is there a problem? I mean, or is this something else happening here? Is there a real problem? >> Well, I think the north star's over there, by the way, Lori. (laughing) >> Oh, there it is. >> Right there. The supercloud north star. So indeed I think there are opportunities. Whether you call them problems or not, John, I think is to be determined. Most companies have, especially if they're a large enterprise, whether or not they've got an investment in private cloud or not, have spent time really trying to optimize their engineering and workload placement on a single cloud. And that, regardless of your choice, as we take the big three, whether it's Amazon, Google, or Microsoft, each of them have their pros and cons for various types of workloads. And so you'll see a lot of folks optimizing for a particular cloud, and it takes a huge effort up and down the stack to just get a single cloud right. That doesn't take into consideration integrations with software as a service, instantiated, oftentimes, on top of infrastructure of the service that you need to supplement where the obstruction layer ends in infrastructure of the service. You've seen most IS players starting to now move up-chain, as we predicted years ago, to platform as a service, but platforms of various types. So I definitely see it as an opportunity. Previous employers have had multiple clouds, but they were very specifically optimized for the types of workloads, for example, in, let's say, AWS versus GCP, based on the need for different types and optimized compute platforms that each of those providers ran. We never, in that particular case, thought about necessarily running the same workloads across both clouds, because they had different pricing models, different security models, et cetera. And so the challenge is really coming down to the fact that, what is the cost benefit analysis of thinking about multi-cloud when you can potentially engineer the resiliency or redundancy, all the in-season "ilities" that you might need to factor into your deployments on a single cloud, if they are investing at the pace in which they are? So I think it's an opportunity, and it's one that continues to evolve, but this just reminds me, your comments remind me, of when we were talking about OpenStack versus AWS. "Oh, if there were only APIs that existed "that everybody could use," and you saw how that went. So I think that the challenge there is, what is the impetus for a singular cloud provider, any of the big three, deciding that they're going to abstract to a single abstraction layer and not be able to differentiate from the competitors? >> Yeah, and that differentiation's going to be big. I mean, assume that the clouds aren't going to stay still like AWS and just not stop innovating. We see the devs are doing great, Adrian, open source is bigger and better than ever, but now that's been commercialized into enterprise. It's an ops problem. So to Chris's point, the cost benefit analysis is interesting, because do companies have to spin up multiple operations teams, each with specialized training and tooling for the clouds that they're using, and does that open up a can of worms, or is that a good thing? I mean, can you design for this? I mean, is there an architecture or taxonomy that makes it work, or is it just the cart before the horse, the solution before the problem? >> Yeah, well, I think that if you look at any large vendor... Sorry, large customer, they've got a bit of everything already. If you're big enough, you've bought something from everybody at some point. So then you're trying to rationalize that, and trying to make it make sense. And I think there's two ways of looking at multi-cloud or supercloud, and one is that the... And practically, people go best of breed. They say, "Okay, I'm going to get my email "from Google or Microsoft. "I'm going to run my applications on AWS. "Maybe I'm going to do some AI machine learning on Google, "'cause those are the strengths of the platforms." So people tend to go where the strength is. So that's multi-cloud, 'cause you're using multiple clouds, and you still have to move data and make sure they're all working together. But then what Lori's talking about is trying to make them all look the same and trying to get all the security architectures to be the same and put this magical layer, this unicorn magical layer that, "Let's make them all look the same." And this is something that the CIOs have wanted for years, and they keep trying to buy it, and you can sell it, but the trouble is it's really hard to deliver. And I think, when I go back to some old friends of ours at Enstratius who had... And back in the early days of cloud, said, "Well, we'll just do an API that abstracts "all the cloud APIs into one layer." Enstratius ended up being sold to Dell a few years ago, and the problem they had was that... They didn't have any problem selling it. The problem they had was, a year later, when it came up for renewal, the developers all done end runs around it were ignoring it, and the CIOs weren't seeing usage. So you can sell it, but can you actually implement it and make it work well enough that it actually becomes part of your core architecture without, from an operations point of view, without having the developers going directly to their favorite APIs around them? And I'm not sure that you can really lock an organization down enough to get them onto a layer like that. So that's the way I see it. >> You just defined- >> You just defined shadow shadow IT. (laughing) That's pretty- (crosstalk) >> Shadow shadow IT, yeah. >> Yeah, shadow shadow it. >> Yeah. >> Yeah. >> I mean, this brings up the question, I mean, is there really a problem? I mean, I guess we'll just jump to it. What is supercloud? If you can have the magic outcome, what is it? Enstratius rendered in with automation? The security issues? Kubernetes is hot. What is the supercloud dream? I guess that's the question. >> I think it's got easier than it was five, 10 years ago. Kubernetes gives you a bunch of APIs that are common across lots of different areas, things like Snowflake or MongoDB Atlas. There are SaaS-based services, which are across multiple clouds from vendors that you've picked. So it's easier to build things which are more portable, but I still don't think it's easy to build this magic API that makes them all look the same. And I think that you're going to have leaky abstractions and security being... Getting the security right's going to be really much more complex than people think. >> What about specialty superclouds, Chris? What's your view on that? >> Yeah, I think what Adrian is alluding to, those leaky abstractions, are interesting, especially from the security perspective, 'cause I think what you see is if you were to happen to be able to thin slice across a set of specific types of workloads, there is a high probability given today that, at least on two of the three major clouds, you could get SaaS providers that sit on those same infrastructure of the service clouds for you, string them together, and have a service that technically is abstracted enough from the things you care about to work on one, two, or three, maybe not all of them, but most SaaS providers in the security space, or identity space, data space, for example, coexist on at least Microsoft and AWS, if not all three, with Google. And so you could technically abstract a service to the point that you let that level of abstract... Like Lori said, no computer science problem could not be... So, no computer science problem can't be solved with more layers of abstraction or misdirection... Or redirection. And in that particular case, if you happen to pick the right vendors that run on all three clouds, you could possibly get close. But then what that really talks about is then, if you built your seven-layer dip model, then you really have specialty superclouds spanning across infrastructure of the service clouds. One for your identity apps, one for data and data layers, to normalize that, one for security, but at what cost? Because you're going to be charged not for that service as a whole, but based on compute resources, based on how these vendors charge across each cloud. So again, that cost-benefit ratio might start being something that is rather imposing from a budgetary perspective. >> Lori, weigh in on this, because the enterprise people love to solve complexity with more complexity. Here, we need to go the other way. It's a commodity. So there has to be a better way. >> I think I'm hearing two fundamental assumptions. One, that a supercloud would force the existing big three to implement some sort of equal API. Don't agree with that. There's no business case for that. There's no reason that could compel them to do that. Otherwise, we would've convinced them to do that, what? 10, 15 years ago when we said we need to be interoperable. So it's not going to happen there. They don't have a good reason to do that. There's no business justification for that. The other presumption, I think, is that we would... That it's more about the services, the differentiated services, that are offered by all of these particular providers, as opposed to treating the core IaaS as the commodity it is. It's compute, it's some storage, it's some networking. Look at that piece. Now, pull those together by... And it's not OpenStack. That's not the answer, it wasn't the answer, it's not the answer now, but something that can actually pull those together and abstract it at a different layer. So cloud providers don't have to change, 'cause they're not going to change, but if someone else were to build that architecture to say, "all right, I'm going to treat all of this compute "so you can run your workloads," as Chris pointed out, "in the best place possible. "And we'll help you do that "by being able to provide those cost benefit analysis, "'What's the best performance, what are you doing,' "And then provide that as a layer." So I think that's really where supercloud is going, 'cause I think that's what a lot of the market actually wants in terms of where they want to run their workloads, because we're seeing that they want to run workloads at the edge, "a lot closer to me," which is yet another factor that we have to consider, and how are you going to be moving individual workloads around? That's the holy grail. Let's move individual workloads to where they're the best performance, the security, cost optimized, and then one layer up. >> Yeah, I think so- >> John Considine, who ultimately ran CloudSwitch, that sold to Verizon, as well as Tom Gillis, who built Bracket, are both rolling in their graves, 'cause what you just described was exactly that. (Lori laughing) Well, they're not even dead yet, so I can't say they're rolling in their graves. Sorry, Tom. Sorry, John. >> Well, how do hyperscalers keep their advantage with all this? I mean, to that point. >> Native services and managed services on top of it. Look how many flavors of managed Kubernetes you have. So you have a choice. Roll your own, or go with a managed service, and then differentiate based on the ability to take away and simplify some of that complexity. Doesn't mean it's more secure necessarily, but I do think we're seeing opportunities where those guys are fighting tooth and nail to keep you on a singular cloud, even though, to Lori's point, I agree, I don't think it's about standardized APIs, 'cause I think that's never going to happen. I do think, though, that SaaS-y supercloud model that we were talking about, layering SaaS that happens to span all the three infrastructure of the service are probably more in line with what Lori was talking about. But I do think that portability of workload is given to you today within lots of ways. But again, how much do you manage, and how much performance do you give up by running additional abstraction layers? And how much security do you give up by having to roll your own and manage that? Because the whole point was, in many cases... Cloud is using other people's computers, so in many cases, I want to manage as little of it as I possibly can. >> I like this whole SaaS angle, because if you had the old days, you're on Amazon Web Services, hey, if you build a SaaS application that runs on Amazon, you're all great, you're born in the cloud, just like that generations of startups. Great. Now when you have this super pass layer, as Dave Vellante was riffing on his analysis, and Lori, you were getting into this pass layer that's kind of like SaaS-y, what's the SaaS equation look like? Because that, to me, sounds like a supercloud version of saying, "I have a workload that runs on all the clouds equally." I just don't think that's ever going to happen. I agree with you, Chris, on that one. But I do see that you can have an abstraction that says, "Hey, I don't really want to get in the weeds. "I don't want to spend a lot of ops time on this. "I just want it to run effectively, and magic happens," or, as you said, some layer there. How does that work? How do you see this super pass layer, if anything, enabling a different SaaS game? >> I think you hit on it there. The last like 10 or so years, we've been all focused on developers and developer productivity, and it's all about the developer experience, and it's got to be good for them, 'cause they're the kings. And I think the next 10 years are going to be very focused on operations, because once you start scaling out, it's not about developers. They can deliver fast or slow, it doesn't matter, but if you can't scale it out, then you've got a real problem. So I think that's an important part of it, is really, what is the ops experience, and what is the best way to get those costs down? And this would serve that purpose if it was done right, which, we can argue about whether that's possible or not, but I don't have to implement it, so I can say it's possible. >> Well, are we going to be getting into infrastructure as code moves into "everything is code," security, data, (laughs) applications is code? I mean, "blank" is code, fill in the blank. (Lori laughing) >> Yeah, we're seeing more of that with things like CDK and Pulumi, where you are actually coding up using a real language rather than the death by YAML or whatever. How much YAML can you take? But actually having a real language so you're not trying to do things in parsing languages. So I think that's an interesting trend. You're getting some interesting templates, and I like what... I mean, the counterexample is that if you just go deep on one vendor, then maybe you can go faster and it is simpler. And one of my favorite vendor... Favorite customers right now that I've been talking to is Liberty Mutual. Went very deep and serverless first on AWS. They're just doing everything there, and they're using CDK Patterns to do it, and they're going extremely fast. There's a book coming out called "The Value Flywheel" by Dave Anderson, it's coming out in a few months, to just detail what they're doing, but that's the counterargument. If you could pick one vendor, you can go faster, you can get that vendor to do more for you, and maybe get a bigger discount so you're not splitting your discounts across vendors. So that's one aspect of it. But I think, fundamentally, you're going to find the CIOs and the ops people generally don't like sitting on one vendor. And if that single vendor is a horizontal platform that's trying to make all the clouds look the same, now you're locked into whatever that platform was. You've still got a platform there. There's still something. So I think that's always going to be something that the CIOs want, but the developers are always going to just pick whatever the best tool for building the thing is. And a analogy here is that the developers are dating and getting married, and then the operations people are running the family and getting divorced. And all the bad parts of that cycle are in the divorce end of it. You're trying to get out of a vendor, there's lawyers, it's just a big mess. >> Who's the lawyer in this example? (crosstalk) >> Well... (laughing) >> Great example. (crosstalk) >> That's why ops people don't like lock-in, because they're the ones trying to unlock. They aren't the ones doing the lock-in. They're the ones unlocking, when developers, if you separate the two, are the ones who are going, picking, having the fun part of it, going, trying a new thing. So they're chasing a shiny object, and then the ops people are trying to untangle themselves from the remains of that shiny object a few years later. So- >> Aren't we- >> One way of fixing that is to push it all together and make it more DevOps-y. >> Yeah, that's right. >> But that's trying to put all the responsibilities in one place, like more continuous improvement, but... >> Chris, what's your reaction to that? Because you're- >> No, that's exactly what I was going to bring up, yeah, John. And 'cause we keep saying "devs," "dev," and "ops" and I've heard somewhere you can glue those two things together. Heck, you could even include "sec" in the middle of it, and "DevSecOps." So what's interesting about what Adrian's saying though, too, is I think this has a lot to do with how you structure your engineering teams and how you think about development versus operations and security. So I'm building out a team now that very much makes use of, thanks to my brilliant VP of Engineering, a "Team Topologies" approach, which is a very streamlined and product oriented way of thinking about, for example, in engineering, if you think about team structures, you might have people that build the front end, build the middle tier, and the back end, and then you have a product that needs to make use of all three components in some form. So just from getting stuff done, their ability then has to tie to three different groups, versus building a team that's streamlined that ends up having front end, middleware, and backend folks that understand and share standards but are able to uncork the velocity that's required to do that. So if you think about that, and not just from an engineering development perspective, but then you couple in operations as a foundational layer that services them with embedded capabilities, we're putting engineers and operations teams embedded in those streamlined teams so that they can run at the velocity that they need to, they can do continuous integration, they can do continuous deployment. And then we added CS, which is continuously secure, continuous security. So instead of having giant, centralized teams, we're thinking there's a core team, for example, a foundational team, that services platform, makes sure all the trains are running on time, that we're doing what we need to do foundationally to make the environments fully dev and operator and security people functional. But then ultimately, we don't have these big, monolithic teams that get into turf wars. So, to Adrian's point about, the operators don't like to be paned in, well, they actually have a say, ultimately, in how they architect, deploy, manage, plan, build, and operate those systems. But at the same point in time, we're all looking at that problem across those teams and go... Like if one streamline team says, "I really want to go run on Azure, "because I like their services better," the reality is the foundational team has a larger vote versus opinion on whether or not, functionally, we can satisfy all of the requirements of the other team. Now, they may make a fantastic business case and we play rock, paper, scissors, and we do that. Right now, that hasn't really happened. We look at the balance of AWS, we are picking SaaS-y, supercloud vendors that will, by the way, happen to run on three platforms, if we so choose to expand there. So we have a similar interface, similar capability, similar processes, but we've made the choice at LastPass to go all in on AWS currently, with respect to how we deliver our products, for all the reasons we just talked about. But I do think that operations model and how you build your teams is extremely important. >> Yeah, and to that point- >> And has the- (crosstalk) >> The vendors themselves need optionality to the customer, what you're saying. So, "I'm going to go fast, "but I need to have that optionality." I guess the question I have for you guys is, what is today's trade-off? So if the decision point today is... First of all, I love the go-fast model on one cloud. I think that's my favorite when I look at all this, and then with the option, knowing that I'm going to have the option to go to multiple clouds. But everybody wants lock-in on the vendor side. Is that scale, is that data advantage? I mean, so the lock-in's a good question, and then also the trade-offs. What do people have to do today to go on a supercloud journey to have an ideal architecture and taxonomy, and what's the right trade-offs today? >> I think that the- Sorry, just put a comment and then let Lori get a word in, but there's a lot of... A lot of the market here is you're building a product, and that product is a SaaS product, and it needs to run somewhere. And the customers that you're going to... To get the full market, you need to go across multiple suppliers, most people doing AWS and Azure, and then with Google occasionally for some people. But that, I think, has become the pattern that most of the large SaaS platforms that you'd want to build out of, 'cause that's the fast way of getting something that's going to be stable at scale, it's got functionality, you'd have to go invest in building it and running it. Those platforms are just multi-cloud platforms, they're running across them. So Snowflake, for example, has to figure out how to make their stuff work on more than one cloud. I mean, they started on one, but they're going across clouds. And I think that that is just the way it's going to be, because you're not going to get a broad enough view into the market, because there isn't a single... AWS doesn't have 100% of the market. It's maybe a bit more than them, but Azure has got a pretty solid set of markets where it is strong, and it's market by market. So in some areas, different people in some places in the world, and different vertical markets, you'll find different preferences. And if you want to be across all of them with your data product, or whatever your SaaS product is, you're just going to have to figure this out. So in some sense, the supercloud story plays best with those SaaS providers like the Snowflakes of this world, I think. >> Lori? >> Yeah, I think the SaaS product... Identity, whatever, you're going to have specialized. SaaS, superclouds. We already see that emerging. Identity is becoming like this big SaaS play that crosses all clouds. It's not just for one. So you get an evolution going on where, yes, I mean, every vendor who provides some kind of specific functionality is going to have to build out and be multi-cloud, as it were. It's got to work equally across them. And the challenge, then, for them is to make it simple for both operators and, if required, dev. And maybe that's the other lesson moving forward. You can build something that is heaven for ops, but if the developers won't use it, well, then you're not going to get it adopted. But if you make it heaven for the developers, the ops team may not be able to keep it secure, keep everything. So maybe we have to start focusing on both, make it friendly for both, at least. Maybe it won't be the perfect experience, but gee, at least make it usable for both sides of the equation so that everyone can actually work in concert, like Chris was saying. A more comprehensive, cohesive approach to delivery and deployment. >> All right, well, wrapping up here, I want to just get one final comment from you guys, if you don't mind. What does supercloud look like in five years? What's the Nirvana, what's the steady state of supercloud in five to 10 years? Or say 10 years, make it easier. (crosstalk) Five to 10 years. Chris, we'll start with you. >> Wow. >> Supercloud, what's it look like? >> Geez. A magic pane, a single pane of glass. (laughs) >> Yeah, I think- >> Single glass of pain. >> Yeah, a single glass of pain. Thank you. You stole my line. Well, not mine, but that's the one I was going to use. Yeah, I think what is really fascinating is ultimately, to answer that question, I would reflect on market consolidation and market dynamics that happens even in the SaaS space. So we will see SaaS companies combining in focal areas to be able to leverage the positions, let's say, in the identity space that somebody has built to provide a set of compelling services that help abstract that identity problem or that security problem or that instrumentation and observability problem. So take your favorite vendors today. I think what we'll end up seeing is more consolidation in SaaS offerings that run on top of infrastructure of the service offerings to where a supercloud might look like something I described before. You have the combination of your favorite interoperable identity, observability, security, orchestration platforms run across them. They're sold as a stack, whether it be co-branded by an enterprise vendor that sells all of that and manages it for you or not. But I do think that... You talked about, I think you said, "Is this an innovator's dilemma?" No, I think it's an integrator's dilemma, as it has always ultimately been. As soon as you get from Genesis to Bespoke Build to product to then commoditization, the cycle starts anew. And I think we've gotten past commoditization, and we're looking at niche areas. So I see just the evolution, not necessarily a revolution, of what we're dealing with today as we see more consolidation in the marketplace. >> Lori, what's your take? Five years, 10 years, what does supercloud look like? >> Part of me wants to take the pie in the sky unicorn approach. "No, it will be beautiful. "One button, and things will happen," but I've seen this cycle many times before, and that's not going to happen. And I think Chris has got it pretty close to what I see already evolving. Those different kinds of super services, basically. And that's really what we're talking about. We call them SaaS, but they're... X is a service. Everything is a service, and it's really a supercloud that can run anywhere, but it presents a different interface, because, well, it's easier. And I think that's where we're going to go, and that's just going to get more refined. And yes, a lot of consolidation, especially on the observability side, but that's also starting to consume the security side, which is really interesting to watch. So that could be a little different supercloud coming on there that's really focused on specific types of security, at least, that we'll layer across, and then we'll just hook them all together. It's an API first world, and it seems like that's going to be our standard for the next while of how we integrate everything. So superclouds or APIs. >> Awesome. Adrian... Adrian, take us home. >> Yeah, sure. >> What's your- I think, and just picking up on Lori's point that these are web services, meaning that you can just call them from anywhere, they don't have to run everything in one place, they can stitch it together, and that's really meant... It's somewhat composable. So in practice, people are going to be composable. Can they compose their applications on multiple platforms? But I think the interesting thing here is what the vendors do, and what I'm seeing is vendors running software on other vendors. So you have Google building platforms that, then, they will support on AWS and Azure and vice versa. You've got AWS's distro of Kubernetes, which they now give you as a distro so you can run it on another platform. So I think that trend's going to continue, and it's going to be, possibly, you pick, say, an AWS or a Google software stack, but you don't run it all on AWS, you run it in multiple places. Yeah, and then the other thing is the third tier, second, third tier vendors, like, I mean, what's IBM doing? I think in five years time, IBM is going to be a SaaS vendor running on the other clouds. I mean, they're already halfway there. To be a bit more controversial, I guess it's always fun to... Like I don't work for a corporate entity now. No one tells me what I can say. >> Bring it on. >> How long can Google keep losing a billion dollars a quarter? They've either got to figure out how to make money out of this thing, or they'll end up basically being a software stack on another cloud platform as their, likely, actual way they can make money on it. Because you've got to... And maybe Oracle, is that a viable cloud platform that... You've got to get to some level of viability. And I think the second, third tier of vendors in five, 10 years are going to be running on the primary platform. And I think, just the other final thing that's really driving this right now. If you try and place an order right now for a piece of equipment for your data center, key pieces of equipment are a year out. It's like trying to buy a new fridge from like Sub-Zero or something like that. And it's like, it's a year. You got to wait for these things. Any high quality piece of equipment. So you go to deploy in your data center, and it's like, "I can't get stuff in my data center. "Like, the key pieces I need, I can't deploy a whole system. "We didn't get bits and pieces of it." So people are going to be cobbling together, or they're going, "No, this is going to cloud, because the cloud vendors "have a much stronger supply chain to just be able "to give you the system you need. "They've got the capacity." So I think we're going to see some pandemic and supply chain induced forced cloud migrations, just because you can't build stuff anymore outside the- >> We got to accelerate supercloud, 'cause they have the supply. They are the chain. >> That's super smart. That's the benefit of going last. So I'm going to scoop in real quick. I can't believe we can call this "Web3 Supercloud," because none of us said "Web3." Don't forget DAO. (crosstalk) (indistinct) You have blockchain, blockchain superclouds. I mean, there's some very interesting distributed computing stuff there, but we'll have to do- >> (crosstalk) We're going to call that the "Cubeverse." The "Cubeverse" is coming. >> Oh, the "Cubeverse." All right. >> We will be... >> That's very meta. >> In the metaverse, Cubeverse soon. >> "Stupor cloud," perhaps. But anyway, great points, Adrian and Lori. Loved it. >> Chris, great to see you. Adrian, Lori, thanks for coming on. We've known each other for a long time. You guys are part of the cloud-erati, the group that has been in there from day one, and watched it evolve, and you get the scar tissue to prove it, and the experience. So thank you so much for sharing your commentary. We'll roll this up and make it open to everybody as additional content. We'll call this the "outtakes," the longer version. But really appreciate your time, thank you. >> Thank you. >> Thanks so much. >> Okay, we'll be back with more "Supercloud 22" right after this. (bright upbeat music)

Published Date : Aug 7 2022

SUMMARY :

Great to see you back out there, Adrian. and in the trenches, some consistency that would allow you are going to be good. by the way, Lori. and it's one that continues to evolve, I mean, assume that the and the problem they had was that... You just defined shadow I guess that's the question. Getting the security right's going to be the things you care about So there has to be a better way. build that architecture to say, that sold to Verizon, I mean, to that point. is given to you today within lots of ways. But I do see that you can and it's got to be good for code, fill in the blank. And a analogy here is that the developers (crosstalk) are the ones who are going, is to push it all together all the responsibilities the operators don't like to be paned in, the option to go to multiple clouds. and it needs to run somewhere. And maybe that's the other of supercloud in five to 10 years? A magic pane, a single that happens even in the SaaS space. and that's just going to get more refined. Adrian, take us home. and it's going to be, So people are going to be cobbling They are the chain. So I'm going to scoop in real quick. call that the "Cubeverse." Oh, the "Cubeverse." In the metaverse, But anyway, great points, Adrian and Lori. and you get the scar tissue to with more "Supercloud

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Priya Rajagopal | Supercloud22


 

(upbeat music) >> Okay, we're now going to try and stretch our minds a little bit and stretch Supercloud to the edge. Supercloud, as we've been discussing today and reporting through various breaking analyses, is a term we use to describe a continuous experience across clouds, or even on-prem, that adds new value on top of hyperscale infrastructure. Priya Rajagopal is the director of product management at Couchbase. She's a developer, a software architect, co-creator on a number of patents as well as being an expert on edge, IoT, and mobile computing technologies. And we're going to talk about edge requirements. Priya, you've been around software engineering and mobile and edge technologies your entire career, and now you're responsible for bringing enterprise class database technology to the edge and IoT environments, synchronizing. So, when you think about the edge, the near edge, the far edge, what are the fundamental assumptions that you have to make with regards to things like connectivity, bandwidth, security, and any other technical considerations when you think about software architecture for these environments? >> Sure, sure. First off, Dave, thanks for having me here. It's really exciting to be here again, my second time. And thank you for that kind introduction. So, quickly to get back to your question. When it comes to architecting for the edge our principle is prepare for the worst and hope for the best. Because, really, when it comes to edge computing, it's sort of the edge cases that come to bite you. You mentioned connectivity, bandwidth, security. I have a few more. Starting with connectivity, as you import on low network connectivity, think offshore oil rigs, cruise ships, or even retail settings, when you want to have business continuity, most of the time you've got an internet connection, but then when there is disruption, then you lose business continuity. Then when it comes to bandwidth, the notion or the approach we take is that bandwidth is always limited or it's at a premium. Data plans can go up through the roof, depending on the volume of data. Think medical clinics in rural areas. When it comes to security, edge poses unique challenges because you're moving away from this world garden, central cloud-based environment, and now everything is accessible over the internet. And the internet really is inherently untrustworthy. Every bit of data that is written or read by an application needs to be authenticated, needs to be authorized. The entire path needs to be secured end-to-end. It needs to be encrypted. That's confidentiality. Also the persistence of data itself. It needs to be encrypted on disk. Now, one of the advantages of edge computing or distributing data is that the impacted edge environment can be isolated away without impacting the other edge location. Looking at the classic retail architecture, if you've got retail use case, if you've got a a retail store where there's a security breach, you need to have a provision of isolating that store so that you don't bring down services for the other stores. When it comes to edge computing, you have to think about those aspects of security. Any of these locations could be breached. And if one of them is breached, how do you control that? So, that's to answer those three key topics that you brought up. But there are other considerations. One is data governance. That's a huge challenge. Because we are a database company at Couchbase, we think of database, data governance, compliance, privacy. All that is very paramount to our customers. It's not just about enforcing policies right now. We are talking about not enforcing policies in a central location, but you have to do it in a distributed fashion because one of the benefits of edge computing is, as you probably very well know, is the benefits it brings when it comes to data privacy, governance policies. You can enforce that at a granular scale because data doesn't have to ever leave the edge. But again, I talked about this in the context of security, there needs to be a way to control this data at the edge. You have to govern the data when it is at the edge remotely. Some of the other challenges when thinking about the edge is, of course, volume, scale, think IoT, mobile devices, classic far edge type scenarios. And I think the other criteria that we have to keep in mind when we are architecting a platform for this kind of computing paradigm is the heterogeneity of the edge itself. It's no longer a uniform set of compute and storage resources that are available at your disposal. You've got a variety of IoT devices. You've got mobile devices, different processing capabilities, different storage capabilities. When it comes to edge data centers, it's not uniform in terms of what services are available. Do they have a load balancer? Do they have a firewall? Can I deploy a firewall? These are all some key architectural considerations when it comes to actually architecting a solution for the edge. >> Great. Thank you for that awesome setup. Talking about stretching to the edge this idea of Supercloud that connote that single logical layer that spans across multiple clouds. It can include on on-prem, but a critical criterion is that the developer, and, of course, the user experience, is identical or substantially similar. Let's say identical. Let's say identical, irrespective of physical location. Priya, is that vision technically achievable today in the world of database. And if so, can you describe the architectural elements that make it possible to perform well and have low latency and the security and other criteria that you just mentioned? What's the technical enablers? Is it just good software. Is it architecture? Help us understand that. >> Sure. You brought up two aspects. You mentioned user experience, and then you mentioned from a developer standpoint, what does it take? And I'd like to address the two separately. They are very tightly related, but I'd like to address them separately. Just focusing on the easier of the two when it comes to user experience, what are the factors that impact user experience? You're talking about reliability of service. Always on, always available applications. It doesn't matter where the data is coming from. Whether the data is coming from my device, it's sourced from an on-prem data center, or if it is from the edge of the cloud, it's from a central cloud data center, from an end-user perspective, all they care about is that their application is available. The next is, of course, responsiveness. Users are getting increasingly impatient. Do you want to reduce wait times to service? You want something which is extremely fast. They're looking for immersive applications or immersive experiences, AR, VR, mixed reality use cases. Then something which is very critical, and what you just touched upon, is this sort of seamless experience. Like this omnichannel, as we talk about in the context of retail kind of experience, Or what I like to refer to as park and pick up reference. You park, you start your application, running your application, you start a transaction on one device, you park it, pick it up on another device. Or in case of retail, you walk into a store, you pick it up from there. So, there's a park and pick up. Seamless mobility of data is extremely critical. In the context of a database, when we talk about responsiveness, two key, the KPIs are latency, bandwidth. And latency is really the round trip time from the time it takes to make a request for data, and the response comes back. The factors that impact latency are, of course, the type of the network itself, but also the proximity of the data source to the point of consumption. And so the more number of hubs that the data packets have to take to reach from the source to its destination, then you're going to incur a lot of latency. And when it comes to bandwidth, we are talking about the capacity of the network. How much data can be shot through the pipe? And, of course, when edge computing, large number of clients. I talked about scale, the volume of devices. And when you're talking about all of them concurrently connected, then you're going to have network congestion which impacts bandwidth which, in turn, impacts performance. And so when it comes to how do you architect a solution for that, if you completely remove the reliance on network to the extent possible, then you get the highest guarantees when it comes to responsiveness, availability, reliability. Because your application is always going to be on. In order to do that, if you have the database and the data processing components co-located with the application that needs it, that would give you the best experience. But, of course, you want to bring it as close. A lot of times, it's not possible to end with that data within your application itself. And that's where you have options of your an on-prem data center, the edge of the cloud, max end and so on. So the closer you bring the data, you're going to get the better experience. Now, that's all great. But then when it comes to something to achieve a vision of Supercloud, when we talked about, "Hey, one way from a developer standpoint, I have one API to set up this connection to a server, but then behind the scenes, my data could be resident anywhere." How do you achieve something like that? And so, a critical aspect of the solution is data synchronization. I talked about data storage as a database, data storage database, that's a critical aspect of what database is really where the data is persisted, data processing, the APIs to access and query the data. But another really critical aspect of distributing a database is the data synchronization technology. And so once all the islands of data, whether it is on the device, whether it's an on-prem data center, whether it's the edge of the cloud, or whether it is a regional data center, once all those databases are kept in sync, then it's a question of when connectivity to one of those data centers goes down, then there needs to be a seamless switch to another data center. And today, at least when it comes to Couchbase, a lot of our customers do employ global load balancers which can automatically detect. So, from a perspective of an application, it's just one URL end point. But then when one of those services goes down or data centers goes down, we have active failover and standby. And so the load balance automatically redirects all the traffic to the backup data center. And of course, for that to happen, those two data centers need to be in sync. And that's critical. Did that answer your question? >> Yeah, let me jump in here. Thank you again for that. I want to unpack some of those, and I want use the example of Couchbase Light, which, as the name implies, a mobile version of Couchbase. I'm interested in a number of things that you said. You talked about, in some cases, you want to get data from the most proximate location. Is there a some kind of metadata intelligence that you have access to? I'm interested in how you do the synchronization. How do you deal with conflict resolution and recovery if something goes wrong? You're talking about distributed database challenges. How do you approach all that? >> Wow, great question. And probably one that I could occupy the entire session for, but I'll try and keep it brief and try and answer most of the points that you touched upon. So, we talked about distributed database and data sync. But here's the other challenge. A lot of these distributed locations can actually be disconnected. So, we've just exacerbated this whole notion of data sync. And that's what we call offline first, not just we call, what is typically referred to as offline first sync. But the ability for an application to run in a completely disconnected mode, but then when there is network connectivity, the data is synced back to the backend data servers. In order for this to happen, you need a sync protocol (indistinct). Since you asked in the context of Couchbase, our sync protocol, it's a web sockets, extremely lightweight data synchronization protocol that's resilient to network disruption. So, what this means is I could have hundreds of thousands of clients that are connected to a data center, and they could be at various stages of disconnect. And you have a field application, and then you are veering in and out of pockets of network connectivity, so network is disrupted, and then network connectivity is restored. Our sync protocol has got a built-in checkpoint mechanism that allows the two replicating points to have a handshake of what is the previous sync point, and only data from that previous sync point is sent to that specific client. And in order to achieve that you mentioned Couchbase Light, which is, of course, our embedded database for mobile, desktop and any embedded platform. But the one that handles the data synchronization is our Sync Gateway. So, we got a component, Sync Gateway, that sits with our Couchbase server, and that's responsible for securely syncing the data and implementing this protocol with Couchbase Light. You talked about conflict resolution. And it's great that you mentioned that. Because when it comes to data sync, a lot of times folks think, "Oh well, how hard can that be?" I mean, you request for some data, and you pull down the a data, and that's great. And that's the happy path. When all of the clients are connected, when there is reliable network connectivity, that's great. But we are, of course, talking about unreliable network connectivity and resiliency to network disruptions. And also the fact that you have lots of concurrently connected clients, all of them potentially updating the same piece of data. That's when you have a conflict, When two or more clients are updating the same, clients or writers. You could have the writes coming in from the clients. You could have the writes coming in from the backend systems. Either way, multiple writers do the same piece of data. That's when you have conflicts. Now, when it comes to, so, a little bit to explain how conflict resolution is handled within our data sync protocol in Couchbase, it would help to understand a little bit about what kind of database we are, how is data itself stored within our database. So, Couchbase Light is a NoSql JSON document store, which means everything is stored as JSON documents. And so every time there is a write, an update to a document, let's say you start with an initial version of the document, the document is created. Every time there is a mutation to a document, you have a new revision to that document. So, as you build in more rights or more mutations to that document, you build out what's called a revision tree. And so when does a conflict happen? Conflict happens when there is a branch in the tree. So, you've got two writers, writing to the same revision, then you get a branch, and that's what is a conflict. We have a way of detecting those conflicts automatically. That's conflict detection. So, now we know there's a conflict, but we have to resolve it. And within Couchbase, you have two options. You don't have to do anything about it. The system has built-in automatic conflict resolution heuristics built in. So, it's going to check, pick a winning revision. And so we use a bunch of criteria, and we pick a winning revision. So, if two writers are updating the same revision of the document, version of the document, we pick a winner. But then that seemed to work from our experience, 80% of the use cases. But then for the remaining 20%, applications would like to have more control over how the winner of the conflict is picked. And for that, applications can implement a custom conflict resolver. So, we'll automatically detect the conflicting revisions and send these conflicting revisions over to the application via a callback, and the application has access to the entire document body of the two revisions and can use whatever criteria needs to merge >> So, that's policy based in that example? >> Yes. >> Yeah, yeah, okay. >> So you can have user policy based, or you can have the automatic heuristics. >> Okay, I got to wrap because we're out of time, but I want to run this scenario by you. One of the risks to the Supercloud Nirvana that we always talk about is this notion of a new architecture emerging at the edge, far edge really, 'cause they're highly-distributed environments. They're low power, tons of data. And this idea of AI inferencing at the edge, a lot of the AI today is done in modeling in the cloud. You think about ARM processors in these new low-cost devices and massive processing power eventually overwhelming the economics. And then that's seeping back into the enterprise and disrupting it. Now, you still get the problem of federated governance and security, and that's probably going to be more centralized slash federated. But, in one minute, do you see that AI inferencing real-time taking off at the edge? Where is that on the S-curve? >> Oh, absolutely right. When it comes to IoT applications, it's all about massive volumes of data generated at the edge. You talked about the economics doesn't add up. Now you need to actually, the data needs to be actioned at some point. And if you have to transfer all of that over the internet for analysis, the responsiveness, you're going to lose that. You're not going to get that real-time responsiveness and availability. The edge is the perfect location. And a lot of this data is temporal in nature. So, you don't want that to be sent back to the cloud for long-term persistence, but instead you want that to be actioned close as possible to the source itself. And when you talk about, there are, of course, the really small microcontrollers and so on. Even there, you can actually have some local processing done, like tiny ML models, but then mobile devices, when you talk about those, as you're very well aware, these are extremely capable. They're capable of running neural, they have neural network processors. And so they can do a lot of processing locally itself. But then when you want to have an aggregated view within the edge, you want to process that data in an IoT gateway and only send the aggregated data back to the cloud for long-term analytics and persistence. >> Yeah, this is something we're watching, and I think could be highly disruptive, and it's hard to predict. Priya, I got to go. Thanks so much for coming on the "theCube." Really appreciate your time. >> Yeah, thank you. >> All right, you're watching "Supercloud 22." We'll be right back right after this short break. (upbeat music)

Published Date : Jul 25 2022

SUMMARY :

Priya Rajagopal is the most of the time you've is that the developer, that the data packets have to take that you have access to? most of the points that you touched upon. or you can have the automatic heuristics. One of the risks to the Supercloud Nirvana the data needs to be and it's hard to predict. after this short break.

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Rachel Obstler, Heap | CUBE Conversation


 

(upbeat music) >> Hello everyone, welcome to this CUBE conversation. I'm John Furrier, your host of theCUBE here in Palo Alto, California in our studios. Got a great guest here, Rachel Obstler, Vice President, Head of Product at heap.io or Heap is the company name, heap.io is URL. Rachel, thanks for coming on. >> Thanks for having me, John. Great to be here. >> So you guys are as a company is heavily backed with some big time VCs and funders. The momentum is pretty significant. You see the accolades in the industry. It's a hot market for anyone who can collect data easily and make sense of it relative to everything being measured, which is the Nirvana. You can measure everything, but then what do you do with it? So you're at the center of it. You're heading up product for heap. This is what you guys do. And there's a lot of solutions, so let's get into it. Describe the company. What's your mission and what you guys do? >> Yeah, so let me start maybe with how Heap was even started and where the idea came from. So Heap was started by Matin Movassate, someone who was working at Facebook. And this is important 'cause it gets right at the problem that we are trying to solve, which is that he was a product manager at Facebook and he was spending a lot of money on pizza. The reason why he was spending a lot of money on pizza is because he wanted to be able to measure what the users were doing in the product that he was responsible for, and he couldn't get the data. And in order to get the data, he would have to go beg his engineers to put in all sorts of tracking code to collect data. And every time he did so, he had to bribe him with pizza because it's no one's favorite work, number one, and then people want to build new things. They don't want to just constantly be adding tracking code. And then the other thing he found is that even when he did that then it took a couple weeks to get it done. And then he had to wait to collect the data to see what data is. It takes a while to build up the data, and he just thought there must be a better way. And so he founded, he with a couple other co-founders, and the idea was that we could automatically collect data all the time. So it didn't matter if you launched something new, you didn't have to do anything. The data would be automatically collected. And so Heap's mission is really to make it easy to create amazing digital experiences. And we do that by firstly, just making sure you have all the data of what your users are doing because you would think you want to create a new digital experience. You could just do that and it would be perfect the first time, but that's not how it works and users are not predictable. >> Yeah, remember back in the day, big data, Hadoop and that kind of fell flap, but the idea of a data lake started there. You saw the rise of Databricks, the Snowflakes. So this idea that you can collect is there. It's here now, state of the art. Now I see that market. Now the business model comes in. Okay, I can collect everything. How fast can I turn around the insights becomes the next question. So what is the business model of the company? What does the product do? Is it SaaS? Is it a as a package software? How do you guys deploy? How do your customers consume and pay for the service? >> Yeah, so we are a SaaS company and we sell largely to, it could be a product manager. It could be someone in marketing, but it's someone who is responsible for a digital service or a digital product. So they're responsible for making sure that that they're hitting whatever targets they have. It could be revenue, it could be just usage, getting more users adopted, making sure they stay in the product. So that's who we sell to. And so basically our model is just around sessions. So how many sessions do you have? How much data are you collecting? How much traffic do you have? And that's how we charge. I think you were getting at something else though that was really interesting, which is this proliferation of data and then how do you get to an insight. And so one of the things that we've done is first of all, okay, collecting all the data and making sure that you have everything that you need, but then you have a lot of data. So that is indeed an issue. And so we've also built on top of Heap a data science layer that will automatically surface interesting points. So for instance, let's say that you have a very common user flow. Maybe it's your checkout flow. Maybe it's a signup flow and you know exactly what the major milestones are. Like you first fill out a form, you sign up, like maybe you get to do the first thing in the trial. You configure it, you get some value. So we're collecting not only those major milestones, we're collecting every single thing that happens in between. And then we'll automatically surface when there is an important drop off point, for instance, between two milestones so that you know exactly where things are going wrong. >> So you have these indicators. So it's a data driven business. I can see that clearly. And the value proposition in the pitch to the customer is ease of use. Is it accelerated time to value for insights? Is it eliminating IT? Is it the 10X marketer? Or all of those things? What is the core contract with the customer, the brand promise? >> That's exactly. So it's the ability to get to insight. First of all, that you may never have found on your own, or that would take you a long time to keep trialing an error of collecting data until you found something interesting. So getting to that insight faster and being able to understand very quickly, how you can drive impact with your business. And the other thing that we've done recently that adds a lot to this is we recently joined forces with a company named Auryc so we just announced this on Monday. So now on top of having all the data and automatically surfacing points of interest, like this is where you're having drop off, this is where you have an opportunity, we now allow you to watch it. So not only just see it analytically, see it in the numbers, but immediately click a show me button, and then just watch examples of users getting stuck in that place. And it really gives you a much better or clearer context for exactly what's happening. And it gives you a much better way to come up with ideas as to how to fix it as one of those digital builders or digital owners. >> You know, kind of dating myself when I mention this movie "Contact" where Jodie foster finds that one little nugget that opens up so much more insight. This is what you're getting at where if you can find that one piece that you didn't see before and bring it in and open it up and bring in that new data, it could change the landscape and lens of the entire data. >> Yeah. I can give you an example. So we have a customer, Casper. Most are familiar with that they sell mattresses online. So they're really a digital innovator for selling something online that previously you had to like go into a store to do. And they have a whole checkout flow. And what they discovered was that users that at the very end of the flow chose same day delivery were much more likely to convert and ultimately buy a mattress. They would not necessarily have looked at this. They wouldn't necessarily have looked at or decided to track like delivery mechanism. Like that's just not the most front and center thing, but because he collects all the data, they could look at it and say, oh, people who are choosing this converted a much higher rate. And so then they thought, well, okay, this is happening at the very end of the process. Like they've already gone through choosing what they want and putting it in their card and then it's like the very last thing they do. What if we made the fact that you could get same day delivery obvious at the beginning of the whole funnel. And so they tried that and it improved their conversion rate considerably. And so these are the types of things that you wouldn't necessarily anticipate. >> I got to have a mattress to sleep on. I want it today. Come on. >> Yeah, exactly. Like there's a whole market of people who are like, oh no, I need a mattress right now. >> This is exactly the point. I think this is why I love this opportunity that you guys are in. Every company now is digitalizing their business, aka digital transformation. But now they're going to have applications, they're going to have cloud native developers, they're going to be building modern applications. And they have to think like an eCommerce company, but it's not about brick and mortars anymore. It's just digital. So this is the new normal. This is an imperative. This is a fact. And so a lot of them don't know what to do. So like, wait a minute, who do we call? This is like a new problem for the mainstream. >> Yeah, and think about it too. Actually e-commerce has been doing this for quite a while, but think about all the B2B companies and B2B SaaS, like all the things that today, you do online. And that they're really having to start thinking more like e-commerce companies and really think about how do we drive conversion, even if conversion isn't the same thing or doesn't mean the same thing, but it means like a successful retained user. It's still important to understand what their journey is and where you going to help them. >> Recently, the pandemic has pulled forward this digital gap that every company's seeing, especially the B2B, which is virtual events, which is just an indicator of the convergence of physical and online. But it brings up billions of signals and I know we have an event software that people do as well. But when you're measuring everything, someone's in a chat, someone hit a web page, I mean there are billions of signals that need to get stored, and this is what you guys do. So I want to ask you, you run the product team. What's under the covers? What's the secret sauce for you guys at Heap? Because you got to store everything. That's one challenge. That's one problem you got to solve. Then you got to make it fast because most of the databases can't actually roll up data fast enough. So you're waiting for the graph forever when some people say. What's under the covers? What's the secret sauce? >> Well, it's a couple different things. So one is we designed the system from the very beginning for that purpose. For the purpose of bringing in all those different signals and then being able to cut the data lots of different ways. And then also to be able to apply data science to it in real time to be able to surface these important points that you should be looking at. So a lot of it is just about designing the system for the very beginning for that purpose. It was also designed to be easy for everyone to use. So what was a really important principle for us is a democratization of data. So in the past, you have these central data teams. You still have them today. Central data teams that are responsible for doing complex analysis. Well, we want to bring as much of that functionality to the digital builders, the product managers, the marketers, the ones that are making decisions about how to drive impact for their digital products and make it super easy for them to find these insights without having to go through a central team that could again take weeks and months to get an answer back from. >> Well, that's what brings up a good point. I want to dig into, if you don't mind, Rachel, this data engineering challenge. There's not enough talent out there. When I call data engineer, I'm talking about like the specialist person. She could be a unique engineer, but not a data scientist. We're talking about like hardcore data engineering, pipelining, streaming data, hardcore. There's not many people that fit that bill. So how do you scale that? Is that what you guys help do? >> We can help with that. Because, again, like if you put the power in the hands of the product people or the marketers or the people that are making those decisions, they can do their own analysis. Then you can really offload some of those central teams and they can do some of the much more complex work, but they don't have to spend their time constantly serving maybe the easier questions to answer. You have data that's self-service for everyone. >> Okay, before I get into the quick customer side of it, quickly while I have you on the product side. What are some of your priorities? You look at the roadmap, probably got tons of people calling. I can only imagine the customer base is diverse in its feature requests. Everyone has the same need, but they all have different businesses. So they want a feature here. They want a feature there. What's the priorities? How do you prioritize? What are some of your priorities for how you're going to build out and keep continuing the momentum? >> Yeah, so I mentioned earlier that we just joined forces with a company name Auryc that has session replay capabilities, as well as voice of customer. So one of our priorities is that we've noticed in this market, there's a real, it's very broken up in a strange way. I shouldn't say it's strange. It's probably because this is the way markets form, startups start, and they pick a technology and they build on top of it. So as a result, the way the market has formed is that you have analytics tools like Heap, and they look at very quantitative data, collecting all sorts of data and doing all sorts of quantitative cuts on it. And then you have tools that do things like session replay. So I just want to record sessions and watch and see exactly what the user's doing and follow their path through one at a time. And so one is aggregating data and the other one is looking at individual user journeys, but they're solving similar jobs and they're used by the same people. So a product manager, for example, wants to find a point of friction, wants to find an opportunity in their product that is significant, that is happening to a lot of people, that if they make a change will drive impact like a large impact for the business. So they'll identify that using the quant, but then to figure out how to fix it, they need the qual. They need to be able to watch it and really understand where people are getting stuck. They know where, but what does that really look like? Like, let me visualize this. And so our priority is really to bring these things together to have one platform where someone can just, in seconds, find this point of opportunity and then really understand it with a show me button so that they can watch examples of it and be like, I see exactly what's happening here and I have ideas of how to fix this. >> Yeah, something's happening at that intersection. Let's put some cameras on. Let's get some eyes on that. Let's look at it. >> Exactly. >> Oh, hey, let's put something. Let's fix that. So it makes a lot of sense. Now, customer attraction has been strong. I know it's been a lot of press and accolades online with when you guys are getting review wise. I mean, I can see DevOps and app people just using this easily, like signing up and I can collect all the data and seeing value, so I get that. What are some of the customer value propositions that are coming out of that, that you can share? And for the folks watching that don't know Heap, what's their problem that they're facing that you can solve, and what pain are they in or what problem do they solve? So example of some success that's coming out of the platform, enablement, the disruptive enablement, and then what's the problem, what's the customer's pain point, and when they know to call you guys or sign up. >> Yeah, so there's a couple different ways to look at it. When I was talking about is really for the user. There's this individual person who owns an outcome and this is where the market is going that the product managers, the marketers, they're not just there to build new features, they're there to drive outcomes for the business. And so in order to drive these outcomes, they need to figure out what are the most impactful things to do? Where are the investments that they need to make? And so Heap really helps them narrow down on those high impact areas and then be able to understand quickly as I was mentioning how to fix them. So that's one way to look at it. Another use case is coming from the other side. So talking in about session replay, you may have a singular problem. You may have a single support ticket. You may have someone complaining about something and you want to really understand, not only what is the problem, like what were they experiencing that caused them to file this ticket, but is this a singular problem, or is this something that is happening to many different people? And therefore, like we should prioritize fixing it very quickly. And so that's the other use case is let's start, not with the group, like the biggest impact and go to like exactly some examples, let's start with the singular and figure out if that gives you a path to the group. But the other use case that I think is really interesting is if you think about it from a macro point of view or from a product leader or a marketing leader's point of view, they're not just trying to drive impact. They're trying to make it easy for their team to drive that impact. So they're thinking about how do they make their whole organization a lot more data driven or insights driven? How do they change the culture, the process, not just the tool, but all of those things together so that they can have a bigger business impact and enable their team to be able to do this on their own? >> You guys are like a data department for developers and product managers. >> Essentially, like we are the complete dataset and the easy analysis that really helps you figure out, where do I invest? How do I justify my investments? And how do I measure how well my investments are doing? >> And this is where the iteration comes in. This is the model everyone's doing. You see a problem, you keep iterating. Got to look at the data, get some insight and keep looking back and making that product, get that flywheel going. Rachel, great stuff. Coming out here, real quick question for you to end the segment. What's the culture like over at Heap? If people are interested in joining the company or working with you guys. Every company has their own kind of DNA. What's the Heap culture like? >> That's a great question. So Heap is definitely a unique company that I've worked at and in a really good way. We find it really important to be respectful to each other. So one of our values is respectful candor. So you may be familiar with radical candor. We've kind of softened it a bit and said, look, it's good to be truthful and have candor, but let's do it in a respectful way. We really find important that everyone has a growth mindset. So we're always thinking about how do we improve? How do we get better? How do we grow faster? How do we learn? And then the other thing that I'll mention, another one of our values that I love, we call it, "taste the soup". Some people use to call it dogfooding, but we are in Heap all the time. We call it Heap on Heap. We really want to experience what our customers experience and constantly use our product to also get better and make our product better. >> A little more salt on the sauce, keep the soup, taste it a little bit. Good stuff. Rachel, thanks for coming on. Great insights and congratulations on a great product opportunity. Again, as world goes digital transformation, developers, product, all people want to instrument everything to then start figuring out how to improve their offering. So really hot market and hot company. Thanks for coming on. >> Thanks, John. Thanks for having me. >> This is theCUBE conversation. I'm John Furrier here in Palo Alto, California. Thanks for watching. (gentle music)

Published Date : Jun 6 2022

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Alan Flower, HCL Technologies & Ramón Nissen, Red Hat | Kubecon + Cloudnativecon EU 2022


 

>>The queue presents Coon and cloud native con Europe, 2022, brought to you by red hat, the cloud native computing foundation and its ecosystem partners. >>Welcome to Valencia Spain and Coon cloud native con Europe, 2022. I'm Keith towns, along with Paul Gillon, senior editor, enterprise architecture, Silicon angle. We are going to talk to some amazing folks, especially in today's segment. Paul there's a lot of companies here, like what what's been the, the consistent theme you've heard so far in the show. >>Well, you know, one thing that's different from this show, it seems to me than others I've attended is it's all around open source. We're not seeing a lot of companies bringing new proprietary technology to market. We are seeing them try to piece together, open source components with some kind of, perhaps there's a proprietary element to it, but to create some kind of a, a common management interface or control plane, and that's quite different from what I think we've seen in the past and open source business models have been difficult to make work historically. And these companies are all taking their, their own approaches to it. But I think the, the degree to which this, the people here of coalesced around the importance of open source is building blocks to the future of, of applications is something I've not seen quite this way before. >>Well, with our current segment guests, we're gonna go deep into kind of these challenges and how enterprises are addressing, and their partners are addressing with those challenges we have with us, a flower head of cloud native HCL technologies. We'll get into how a system integrator is helping with this transition to Ramon neon, senior product manager, redhead. Welcome to the show. You're now cute. Alum. Welcome. >>Thanks for having us. >>So we're gonna get right off, off the bat. We're gonna talk about this. What are some of the trends you're seeing when it comes to application migration? You've done, I'm assuming at this point, thousands of them, what are some of the common trends? >>Well, it's a very good question. And clearly a C we've helped thousands of clients move tens of thousands of applications to what we would call a cloud native, you know, environment. I think the overwhelming trend that we're seeing of course is clients realize it's a particularly complex, sophisticated journey. It requires a certain set of skills and capability clients increasingly asking us for anything that we can do to simplify and accelerate the journey, cuz what's really important to clients. If you're on a transformation journey to cloud is you wanna see some value very quickly. So I don't wanna wait three to five years to transform my applications portfolio. If you can do something in three to five days, that would be perfect. Thank you. >>Well, three to five days, that sounds more akin to when we were doing P to V or V to V migrations, I'm sure HCL is at this point done in the millions of those types of migrations. What are some of the challenges or the nuance in doing a traditional migration from a traditional MI monolithic application to a cloud native? >>Well, it's another good question. Of course you notice that there's a general trend in the industry. Clients don't really want to lift and shift anymore. Lift and shift doesn't really bring any transformational value to my, to my company. So clients are looking for increasingly what we could call cloud native modernization. I want my applications to really take advantage of the cloud native environment. They need to be elastic and kind of more robust than maybe before now in particular, I think a lot of clients have realized that this state of Nirvana, which was we're gonna modernize everything to be a cloud native microservices based application. That is a tremendous journey, but no client really has the time patient or resources to fully refactor or rearchitect all of their applications. They're looking for more immediate kind of impact. So a key trend that we've seen of course is clients still want to refactor and modernize applications, but they're focusing those resources on those applications that will bring greater impact to their business. >>What they now see as a better replacement for lift and shift is probably what we would call replatforming, where they want all of the advantages of a cloud native environment, but they haven't necessarily got the time to modernize the code base. They wanna refactor to Kubernetes and re replatform to Kubernetes in particular, and they want us to take them there quickly. And that's why, for example, this week at cuon eight sellers announced a new set of tools called KMP based on conveyor, an open source project supported by red hat. And the key attraction of KMP is it lets me replatform my applications to Kubernetes immediately, right? Within two or three minutes, I can bring an application from a legacy platform directly onto Kubernetes and I can take it straight into production. That's the kind of acceleration that clients are looking for today. Isn't >>That just a form of lift and shift though? >>Well, no lift and shift typically of course, was moving virtual machines from one place to another. You know, the focus of Kubernetes of course is containerization of solutions. And it's not just about containerizing the solution and movement. It it's the DevOps tool chain around the solution as well. And of course, when I take that application into production in a Kubernetes based environment, I'm expecting to operate it in a different way as well. So that's where we see tremendous focus on what we would call cloud native operations clients expecting to use practices like site reliability engineering, to run these replatformed applications in a different way to, >>It sounds like you're saying, I mean, replatforming has been a, a spectrum of options. I think Gartner has seven different types of platforming. Are you seeing clients take more mature attitude now to replatforming? Are they looking more carefully at the characteristics of their legacy applications and, and try to try to make maybe more nuanced choices about what to replatform, what to just leave >>Alone? I think clients and I I'm sure Ramon's got some comments on this too, but clients have a lot more insight now in terms of what works for them. They they've realized that this, this promise of maybe a microservices based applications estate is a good one, but I can't do that for every application. If I am a large enterprise with several thousand applications in my portfolio, I can't refactor everything to become microservices based. So clients see replatforming possibly it's a middle ground. I, I get a lot of the advantages from a cloud native environment. My applications are inherently more efficient, hopefully a lot more performance. >>Yeah. It's, it's a matter of software delivery performance. Yeah. So legacy workloads will definitely benefit from being brought into Kubernetes in the software delivery per performance department. So it's a matter of somehow revamping your, your legacy applications and getting the benefits in, in life's application, life cycle management, a full tolerance and all that stuff. It's about leveraging the, what Kubernetes offers. >>When you say bringing legacy applications into Kubernetes. It's not that simple, right? I mean, what's involved in doing that. >>It, it, isn't, it's just a matter of taking a holistic view at your application portfolio and understanding the nuance sets of each application type within your organization and trying to come up with a suitable migration strategy for each one of these application types. And for that, what we're trying to do is provide a series of standardized tools and methodologies from a community perspective, we created this conveyor community. It, it was kick started by red hat and IBM, but we are trying to bring as many vendors and GSI as possible to try to set up these standards to make these road towards Kubernetes as easy as >>Possible. So we've done a little bit of app modernization in the CTO advisor hybrid infrastructure. And one of the things that we've found is there's plenty of Avan advantages. If I take a monolithic application that has that I've traditionally had to scale off to game performance, I can take selective parts of that, and now I can add autoscaling to it. Exactly. However, as I look at a landscape Allen of thousands of applications, I need to dedicate developer resources to get that done in my traditional environment. But my traditional environment is busy building new. My traditional or my developers are building new applications and new capabilities. I just don't have the resources to do that. How does HCL and red hat team together to kind of fast track that capability? >>Well, I'll comment on two things in particular, actually the, the first thing when it comes to skilling, I think the thing that's really surprised us at HCL is so many of our clients around the world have said, we are desperately short of skills. We cannot hire ourselves out of this problem. We need to get our existing developer community reskilled around platforms like OpenShift, conveyor, and other projects too. So the first thing that's happened to us at eight seal is we've been incredibly busy undertaken, probably what we would call developer workforce modernization, right? Where we have to help the client reskill their entire technical and developer community to give them the skills, right. So we will help the clients develop a community, build the cloud native understanding, help them understand how to modernize tools for example, or applications. But the second thing I mention is, and this comes back to a comment the Ram made around around conveyor. >>It's been really encouraging to see the open source community, start to invest in building the supporting frameworks around my kind of modernization journey, because if I'm a developer that's reskilling and I'm attempting to maybe modernize an application, being able to dip into an opensource project, I mean, a good example would be tackled part of the conveyor project. Exactly. You now have open source based tools that will help you analyze your applications. They will go into the source code and they will give the developer guidance in terms of what would be effective treatments to undertake. So perhaps a development team that are new to this modernization journey, they would benefit from a project like conveyor, for example, exactly because I need to know where can I safely modernize my application now for experience organizations like HCL that comes naturally to us, but for people who are just starting this journey, if I can take an open source tool like tackle or the rest of conveyor, for example, and use that to accelerate my journey, it takes a lot of pressure off, off my organization, but it also accelerates the journey too. And >>It's not just a matter of, of tooling. We we're also, opensourcing the, the modernization methodology that we've been using in red hat consulting for years. So this whole conveyor communities, it's all about knowledge sharing on one hand and building a set of tools together based on that knowledge that we are sharing to make it as easy as possible. >>And what role does red hat play in all that, I mean is your, your, you you've carved out this position for yourself as the, as the true open source company. Is that, does that position you for a leadership role in helping or companies make this >>Transition? I wouldn't say we should be leading the whole thing. We, we kick started it, but we want to get other vendors on board for this thing. One cool thing about the Camra community is that IBM is opensourcing a lot of their IP. So IBM research is on board. In this thing, we have some really crazy stuff related to a AI being applied to application analysis. We have some machine learning in place. We have very cool stuff that has been sitting on a, on a corner in IBM research for quite some years that now it's being open sourced and integrated in a unified user experience to streamline the modernization process as much as possible. >>So let's talk about the elephant of the room. HCL was leading the conversation around cloud Foundry circa five plus years ago. And as customers are thinking about their journey to cloud native, how should they think about that cloud Foundry to cloud native or Kubernetes replatform? >>Well with within the cloud Foundry community, we've, we've been quite staunched supporters of Kubernetes for quite some time, right? It's, it's quite a, a stated intent of the cloud Foundry foundation to, to move across to Kubernetes platform right now that is a significant engineering journey for cloud Foundry to take. Now we're in this position where a lot of large users of cloud Foundry have a certain urgency to their journey. They, they want to consolidate on a single Kubernetes based infrastructure. We, we see a lot of traction around OpenShift, for example, from red hat in terms of its market leadership. So a lot of clients are saying we would like to consolidate all of our platforms around a single kind of Kubernetes vendor, whether that's red hat or anyone else, you know, quite frankly. So what HCL is doing right now with the tools and the solutions we've announced this week is we're simply accelerating that journey for clients. If I've got a large installed base of applications running in my cloud Foundry environment, and I've also started to invest in standardize on Kubernetes place platforms like OpenShift, most clients would see it as quite a sensible choice to now try and consolidate those two environments into one. And that's simply what we're doing at HCL. We're making it very, very easy. In fact, we fully automated the journey so I can move all of my applications from cloud Foundry into for example, OpenShift pretty much immediately, and it just simplifies the entire journey. >>So the, as we start to wrap up the segment, I like to know customer stories. What, what, how customers either surprised or challenged when they get into, even with the help of an ACL in redhead, why are they seeing the most difficult parts of their migrations? >>Well, my, my simple comment would be maybe complexity, right? And the, the associated requirement for skilled people to undertake this modernization work, right? We spoke about this, of course, in terms of clients now are a lot more realistic. They understand that their ambition now needs to be somewhat tempered by their ability to sort of drive modernization quickly. So we see a lot of clients when they look at their very large global portfolios of applications, they're trying to invest their resources in the higher priority applications, the revenue generative applications in particular, but they have to bring everything else with them as well. Now, a common kind of separation point was we see a lot of clients who might say I'm gonna properly modernize and refactor, maybe five to 10% of my portfolio, but the other 90% also needs to come on the journey as well. And that's really where replatforming in particular kicks in. So, so the key trend again, is, is clients send to us, I've gotta take the entire journey. All right, I've got the resources and the skills to really focus on this much of my application base. Can someone simplify the overall journey so I can afford to bring everything on a cloud native journey? >>So the key to success here is having a holistic view at the application portfolio, segmenting the application portfolio in different application types and ordering the, the priorities of these application types and come up with suitable migration strategies for each one of them is >>Really necessary to move everything though. >>Not necessarily, no. Yeah. Or not necessarily. Yeah, absolutely not everything, but it would make sense. As we were saying before, it will definitely move, make sense to move legacy applications towards Kubernetes, to leverage all the software delivery. >>That's, that's a big project, right? >>It is. >>If you're gonna restructure the application around eight API and microservices, >>That it should be taken the way I've seen organizations succeeding the most in these road towards cloud native and Kubernetes in general is trying to address the whole portfolio. Maybe not move everything, but try to have this holistic view and not leave anything behind. Because if you try to do this isolated initiatives of bringing these or that application in, in isolation, you're Def you, you will miss part of the picture and you might be doomed to fail >>There. Yeah. It's been my experience that if you don't have a plan to migrate your applications to a cloud native operating model, then you're doomed to follow lift and shift examples to the public cloud. Yeah. Whether you're going to any other clouds, if you don't make that, that operational transition. Last question on operational transition, we've talked a lot about the replatforming process itself. What about day two at the I've landed to the cloud? What are some of the top considerations for, for compliance op observability? Just making sure my apps stay up in transitioning my workforce to that model. >>I think the over, you know, the overarching trend or theme that, that I see is clients now are, are asking for what I would call cloud native operations. Now in particular, there's a very solid theme around what we would call reliability engineering. So think about site reliability, engineering, SRE platform, reliability engineering, PR E. These are the dominant topics that clients now want to engage HCL on in particular, because the point you make is a valid one. I've modernized my application. Now I need to modernize the way that I operate the application in production. Otherwise I won't see those benefits. So that general theme of SRE is keeping us really busy. We're busy, re-skilling all of those operations teams around the world as well, because they need to know how to run these environments appropriately >>Too. And also being able to measure your progress while your transitioning is important. And that's one of the concerns that we are addressing as well in the community with a called polars to, to measure and to effectively measure the software delivery performance of, of the organization after the transition has been done. >>And this is a really good point by the way, cuz most, most people think it's a bit of a black art. How do I understand how I modernize my application? How do I understand how I've improved my kind of value chain around software creation and many people thought you needed to bring in very expensive consultants to advise you on these, on these black lives? No, >>Definitely >>Not. But in open source projects like conveyor from, from red hat, the availability of these tools available on an open source model means exactly any engineer, any developer can get these tools off the shelf and get that immediate benefit. >>Well, a flower head of creative labs at HCL at Ramon neon, senior product manager, redhead. Thank you for joining the Q you now cube alum. You'll have a nice profile like the profile pictures on here. Awesome. Absolutely. Thank you. From Valencia Spain. I'm Keith towns, along with Paul Gillon and you're watching the cue, the leader in high tech coverage.

Published Date : May 19 2022

SUMMARY :

The queue presents Coon and cloud native con Europe, 2022, brought to you by red hat, We are going to of open source is building blocks to the future of, of applications is Welcome to the show. of the trends you're seeing when it comes to application migration? to what we would call a cloud native, you know, environment. Well, three to five days, that sounds more akin to when we were doing P has the time patient or resources to fully refactor or rearchitect all the time to modernize the code base. environment, I'm expecting to operate it in a different way as well. attitude now to replatforming? I get a lot of the advantages from a cloud native environment. So it's a matter of somehow revamping your, your legacy applications and It's not that simple, right? as possible to try to set up these standards to make these road towards Kubernetes I just don't have the resources to do that. So the first thing that's happened to us at eight seal is we've been incredibly busy undertaken, So perhaps a development team that are new to this modernization journey, they would benefit from a project like So this whole conveyor communities, it's all about knowledge And what role does red hat play in all that, I mean is your, your, you you've carved out this position being applied to application analysis. And as customers are thinking about their journey to cloud native, how should they think about that cloud Foundry So a lot of clients are saying we would like to consolidate all of our platforms around a single kind So the, as we start to wrap up the segment, I like to know customer stories. the revenue generative applications in particular, but they have to bring everything else with them as make sense to move legacy applications towards Kubernetes, to leverage all the software delivery. to fail to any other clouds, if you don't make that, that operational transition. Now I need to modernize the way that I operate the application in production. And that's one of the concerns that we are addressing as well in the community with a called polars to, And this is a really good point by the way, cuz most, most people think it's a bit of a black art. the shelf and get that immediate benefit. You'll have a nice profile like the profile pictures on here.

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Alan Flower, HCL Technologies & Ramón Nissen, Red Hat | Kubecon + Cloudnativecon EU 2022


 

>>The cube presents, Coon and cloud native con Europe 22, brought to you by the cloud native computing foundation. >>Welcome to Valencia Spain and Coon cloud native con Europe, 2022. I'm Keith towns, along with Paul Gillon, senior editor, enterprise architecture and Silicon angle. We are going to talk to some amazing folks, especially in today's segment. Paul, uh, there's a lot of companies here, like what what's been the, the consistent theme you've heard so far in the show. >>Well, you know, one thing that's different from this show, it seems to me than others I've attended is it's all around open source. We're not seeing a lot of companies bringing new proprietary technology to market. We are seeing them try to piece together, open source components with some kind of, perhaps there's a proprietary element to it, but to create some kind of a, a common management interface or control plane, and that's quite different from what I think we've seen in the past open source business models have been difficult to make work historically. Uh, and these companies are all taking their, their own approaches to it. But I think the, the degree to which this, the people here of coalesced around the importance of open source is building blocks to the future of, of applications is something I've not seen quite this way before. >>Well, with our current segment, guess we're gonna go deep into kind of these challenges and how enterprises are addressing, and their partners are addressing with those challenges we have with us, a flower head of cloud native HCL technologies. We'll get into how a system integrator is helping with this transition to Ramon neon, senior product manager, redhead. Welcome to the show. You're now cube alum. Welcome. Thanks for having us. So we're gonna get right off, uh, off the bat. We're gonna talk about this. What are some of the trends you're seeing when it comes to application migration? You've done, I'm assuming at this point, thousands of them, what are some of the common trends? >>Well, it's a very good question. And clearly ACL we've helped thousands of clients move tens of thousands of applications to what we would call a cloud native, um, you know, environment. I think the overwhelming trend that we're seeing of course is clients realize it's a particularly complex, sophisticated journey. It requires a certain set of skills and capability clients increasingly us for anything that we can do to simplify and accelerate the journey, cuz what's really important to clients. If you're on a transformation journey to cloud is you wanna see some value very quickly. So I don't wanna wait three to five years to transform my applications portfolio. If you can do something in three to five days, that would be perfect. Thank you. >>Well, three to five days, that sounds more akin to when we were doing, uh, P to V or V to V migrations. I'm sure. Uh, HCL is at this point done in the millions of those types of migrations. What are some of the challenges or the nuance in doing a traditional migration from a traditional MI monolithic application to a cloud native? >>Well, it's another good question. Of course you notice that there's a general trend in the industry. Clients don't really want to lift and shift anymore. Lift and shift doesn't really bring any transformational value to my, to my company. So clients are looking for increasingly what we could recall, cloud native modernization. I want my applications to really take advantage of the cloud native environment. They need to be elastic and kind of more robust than maybe before now in particular, I think a lot of clients have realized that this state of Nirvana, which was we're gonna modernize everything to be a cloud native microservices based application. That is a tremendous journey, but no client really has the time patient or resources to fully refactor or rearchitect all of their applications. They're looking for more immediate kind of impact. So a key trend that we've seen of course is clients still want to refactor and modernize applications, but they're focusing those resources on those applications that will bring greater impact to their business. >>What they now see as a better replacement for lift and shift is probably what we would call replatforming, where they want all of the advantages of a cloud native environment, but they haven't necessarily got the time to modernize the code base. They wanna refactor to Kubernetes in re replatform to Kubernetes in particular, and they want us to take them there quickly. And that's why, for example, this week at cuon eight sellers announced a new set of tools called KMP based on conveyor, an open source project supported by red hat. And the key attraction of KMP is it lets me replatform my applications to Kubernetes immediately, right? Within two or three minutes, I can bring an application from a legacy platform directly onto Kubernetes and I can take it straight into production. That's the kind of acceleration that clients are looking for today. Isn't >>That just a form of lift and shift though? >>Well, no lift and shift typically of course, was moving virtual machines from one place to another. You know, the focus of Kubernetes of course is containerization of solutions. And it's not just about containerizing the solution and moving it. It's the DevOps tool chain around the solution as well. And of course, when I take that application into production in a Kubernetes based environment, I'm expecting to operate it in a different way as well. So that's where we see tremendous focus on what we would call cloud native operations clients expecting to use practices like site reliability engineering, to run these replatformed applications in a different way to, so >>It sounds like you're saying, I, I mean, replatforming has been a, a spectrum of options. I think Gartner has seven different types of re-platforming. Uh, are you seeing clients take more mature attitude now toward replatforming? Are they looking more carefully at the characteristics of their legacy applications and, and trying to try to make maybe more nuanced choices about what to replatform, what to just leave >>Alone? I think clients and I I'm sure Ramon's got some comments on this too, but clients have a lot more insight now in terms of what works for them. They they've realized that this, this promise of maybe a microservices based applications estate is a good one, but I can't do that for every application. If I am a large enterprise with several thousand applications in my portfolio, I can't refactor everything to become microservices based. So clients see replatforming possibly is a middle ground. I, I get a lot of the advantages from a cloud native environment. My applications are inherently more efficient, hopefully a lot more performance. >>Yeah. It's, it's a matter of software delivery performance. Yeah. So, uh, legacy workloads will definitely benefit from, uh, being brought into Kubernetes in the software delivery per performance department. So, uh, it's a matter of, uh, somehow Rebump your, your legacy applications and getting the benefits in, in life's application, life cycle management, a, uh, full tolerance and all that stuff. It's about leveraging the, what Kubernetes offers. >>When you say bringing legacy applications into Kubernetes. It's not that simple, right? I mean, what's involved in doing that. >>It, it, isn't, it's just a matter of taking a holistic view at your application portfolio and understanding the nuances of each application type within your organization and trying to come up with a suitable migration strategy for each one of these application types. And for that, what we're trying to do is provide a series of standardized, um, tools and methodologies, uh, from a community perspective, uh, we created this conveyor community. Uh, it, it was kick started by red hat and IBM, but we are trying to bring as many vendors and GSI, uh, as possible to try to set up these standards to make these, uh, road towards Kubernetes as easy as >>Possible. So we've done a little bit of, uh, app modernization in the CTO advisor hybrid infrastructure. And one of the things that we've found, there's plenty of Avan advantages. If I take a monolithic application that has, uh, that I've traditionally had to scale off to, uh, game performance, I can take selective parts of that, and now I can add auto-scaling to it. Exactly. However, as I look at a landscape Allen of thousands of applications, uh, I need to dedicate developer resources to get that done and my traditional environment, but my traditional environment is busy building new. My traditional or my developers are building new applications and new capabilities. I just don't have the resources to do that. How does HCL and red hat team together to kind of fast track that capability? >>Well, um, I'll comment on two things in particular, actually the, the first thing when it comes to skilling, I think the thing that's really surprised us at HCL is so many of our clients around the world have said, we are desperately short of skills. We cannot hire ourselves out of this problem. We need to get our existing developer community re-skilled around platforms like OpenShift, conveyor, and other projects too. So the first thing that's happened to us at eight still is we've been incredibly busy undertaken, probably what we would call developer workforce modernization, right, where we have to help the client reskill their entire technical and developer community to give them the skills, right. So we will help the clients develop a community, build the cloud native understanding, help them understand how to modernize tools for example, uh, or applications. But the second thing I mention is, and this comes back to a comment that Ramon made around around conveyor. >>It's been really encouraging to see the open source community start to invest in building the supporting frameworks around my kind of modernization journey, because if I'm a developer that's re-skilling and I'm attempting to maybe modernize an application, being able to dip into an open source project, I mean, a good example would be tackled part of the conveyor project. Exactly. You now have open source based tools that will help you analyze your applications. They will go into the source code and they will give the developer guidance in terms of what would be effective treatments to undertake. So perhaps a development team that are new to this modernization journey, they would benefit from a project like conveyor, for example, because I need to know where can I safely modernize my application now for experience organizations like HCL that comes naturally to us, but for people who are just starting this journey, if I can take an open source tool like tackle or the rest of the conveyor, for example, and use that to accelerate my journey, it takes a lot of pressure off, off my organization, but it also accelerates the journey too. >>And it's not just a matter of, of tooling. We we're also opensourcing, uh, the, the modernization methodology that we've been using in red hat consulting for years. So this whole conveyor communities, it's all about knowledge sharing on one hand and building a set of tools together, based on that knowledge that we are sharing to make it as easy as possible. >>And what role does red hat play in all that, I mean, is your you've carved out this position for yourself as the, as the true open source company. Is that, does that position you for a leadership role in helping companies make this >>Transition? I wouldn't say we should be leading the whole thing. Uh, we, we kick started it, but we want to get other vendors on board for this thing. One cool thing about the Camira community is that IBM is, uh, opensourcing a lot of their IP. So IBM research is on board. In this thing, we have some really crazy stuff related to a AI being applied to application analysis. We have some machine learning in place. We have very cool stuff that has been sitting on a, on a corner in IBM research for quite some years that now it's being open sourced and integrated in a, uh, unified user experience to streamline the, uh, modernization process as much as >>Possible. So let's talk about the elephant of the room. Uh, HCL was leading the conversation around cloud Foundry circa five plus years ago. And as customers are thinking about their journey to cloud native, how should they think about that cloud Foundry to cloud native or Kubernetes, uh, replatforming? >>Well within the cloud Foundry community, we've, we've been quite staunched supporters of Kubernetes for quite some time, right? It's, it's quite a, a stated intent of the cloud Foundry foundation to, to move across to Kubernetes platform right now that is a significant engineering journey for cloud Foundry to take. Now we're in this position where a lot of large users of cloud Foundry have a certain urgency to their journey. They, they want to consolidate on a single Kubernetes based, okay. Um, infrastructure. We, we see a lot of traction around OpenShift, for example, from red hat in terms of its market leadership. So a lot of clients are saying we would like to consolidate all of our platforms around a single kind of Kubernetes vendor, whether that's red hat or anyone else, you know, quite frankly. So what ATL is doing right now with the tools and the solutions we've announced this week is we're simply accelerating that journey for clients. If I've got a large installed base of applications running in my cloud Foundry environment, and I've also started to invest in standardize on Kubernetes based platforms like OpenShift, most clients would see it as quite a sensible choice to now try and consolidate those two environments into one. And that's simply what we're doing at HCL. We're making it very, very easy. In fact, we fully automated the journey so I can move all of my applications from cloud Foundry into for example, OpenShift pretty much immediately. And it just simplifies the entire journey. >>So the, as we start to wrap up the segment, I like to know customer stories. What, what, how customers either surprised or challenged when they get into, even with the help of an ACL in redhead, why are they seeing the most difficult parts of their migrations? >>Well, my, my simple comment would be maybe complexity, right? And the, the associated requirement for skilled people to undertake this modernization work, right? We spoke about this, of course, in terms of clients now are a lot more realistic. They understand that their ambition now needs to be somewhat tempered by their ability to sort of drive modernization quickly. So we see a lot of clients when they look at their very large global portfolios of applications, they're trying to invest their resources in the higher priority applications, the revenue generative applications in particular, but they have to bring everything else with them as well. Now, a common kind of separation point was we see a lot of clients who might say I'm gonna properly modernize and refactor, maybe five to 10% of my portfolio, but the other 90% also needs to come on the journey as well. And that's really where replatforming in particular kicks in. So, so the key trend again, is, is clients send to us, I've gotta take the entire journey. All right, I've got the resources and the skills to really focus on this much of my application base. Can someone simplify the overall journey so I can afford to bring everything on a cloud native journey? >>So the key to success here is having a holistic view at the application portfolio, segmenting the application portfolio in different application types and ordering the, the priorities of these application types and come up with suitable migration strategies for each one of them is >>Really necess necessary to move everything though. >>Not necessarily no, or, uh, not necessarily. Yeah, absolutely not everything. But, uh, it would make sense. Uh, as we were saying before, it will definitely move, make sense to move legacy applications towards Kubernetes, to leverage all the, uh, software delivery >>That's >>That's project, right? >>It is. If >>You're gonna restructure the application around APIs and microservices, >>That it should be taken the, the way I've seen, uh, organizations succeeding the most in this, uh, road towards cloud native and Kubernetes in general is trying to address the whole portfolio. Maybe not move everything, but try, try to have this holistic view and not leave anything behind, because if you try to do this isolated, uh, initiatives of bringing this or that applications in a, in isolation, you're Def you, you will miss part of the picture and you might be, uh, doomed to fail >>There. Yeah. It's been my experience that if you don't have a plan to migrate your applications to a cloud native operating model, then you're doomed to follow lift and shift examples to the public cloud. Yeah. Whether you're, uh, going to any other clouds, if you don't make that, that operational transition. Last question on operational transition, we've talked a lot about the replatforming process itself. What about day two, uh, at the I've landed to the cloud? What are some of the top considerations for, for compliance, uh, op op observability, just making sure my apps stay up and transitioning my workforce to that model. >>I, I, I think the over, you know, the overarching trend or theme that, that I see is clients now are, are asking for what I would call cloud native operations. Now in particular, there's a very solid theme around what we would call reliability engineering. So think about site reliability, engineering, SRE platform, reliability engineering, PR E. These are the dominant topics that clients and I want to engage, uh, HCL on in particular, because the point you make is a valid one. I've modernized my application. Now I need to modernize the way that I operate the application in production. Otherwise I won't see those benefits. So that general theme of SRE is keeping us really busy. We're busy, re-skilling all of those operations teams around the world as well, because they need to know how to run these environments appropriately too. >>And also being able to measure your progress while your transitioning is important. And that's one of the concerns that we are addressing as well in the premier community with a tool called polars to, to measure, to effectively measure the software delivery performance of, of the organization after the transition has been done. >>And this is a really good point by the way, cuz most, most people think it's a bit of a black art. How do I understand how I modernize my application? How do I understand how I've improved my kind of value chain around software creation and many people thought you needed to bring in very expensive consultants to advise you on these, on these black lives? No, >>Definitely >>Not. But in open source projects like conveyor from, from red hat, the availability of these tools available on an open source model means exactly any engineer, any developer can get these tools off the shelf and get that immediate benefit. >>Well, a flower head of creative labs at HCL at Ramon neon, senior product manager, redhead. Thank you for joining the QPI. Now Cuba alum, uh, you'll have a nice profile like the profile picture on here. Awesome. >>Absolutely. Thank you. >>From Valencia Spain. I'm Keith towns, along with Paul Gillon and you're watching the cue, the leader in high tech coverage.

Published Date : May 18 2022

SUMMARY :

brought to you by the cloud native computing foundation. We are going to of open source is building blocks to the future of, of applications is Welcome to the show. to what we would call a cloud native, um, you know, environment. Well, three to five days, that sounds more akin to when we were doing, has the time patient or resources to fully refactor or rearchitect all the time to modernize the code base. environment, I'm expecting to operate it in a different way as well. Uh, are you seeing clients take more mature I get a lot of the advantages from a cloud native environment. getting the benefits in, in life's application, life cycle management, a, It's not that simple, right? the nuances of each application type within your organization and trying to come up with a I just don't have the resources to do that. So the first thing that's happened to us at eight still is we've been incredibly busy undertaken, So perhaps a development team that are new to this modernization journey, they would benefit from a project like based on that knowledge that we are sharing to make it as easy as possible. And what role does red hat play in all that, I mean, is your you've carved out this position for being applied to application analysis. to cloud native or Kubernetes, uh, replatforming? So a lot of clients are saying we would like to So the, as we start to wrap up the segment, I like to know customer stories. of my portfolio, but the other 90% also needs to come on the journey as well. make sense to move legacy applications towards Kubernetes, to leverage all the, If uh, doomed to fail applications to a cloud native operating model, then you're doomed Now I need to modernize the way that I operate the application And that's one of the concerns that we are addressing as well in the premier community with a tool called polars to, And this is a really good point by the way, cuz most, most people think it's a bit of a black art. on an open source model means exactly any engineer, any developer can get these tools off the shelf Well, a flower head of creative labs at HCL at Ramon neon, Thank you.

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AWS Heroes Panel | AWS Startup Showcase S2 E2 | Data as Code


 

>>Hi, everyone. Welcome to the cubes presentation of the AWS startup showcase the theme. This episode is data as code, and this is season two, episode two of the ongoing series covering exciting startups from the ecosystem in cloud and the future of data analytics. I'm your host, John furry. You're getting great featured panel here with AWS heroes, Lynn blankets, the CEO of Lindbergh Lega consulting, Peter Hanson's, founder of cloud Cedar and Alex debris, principal of debris advisory. Great to see all of you here and, uh, remotely and look forward to see you in person at the next re-invent or other event. >>Thanks for having us. >>So Lynn, you're doing a lot of work in healthcare, Peter you're in the middle of all the action as data as code Alex. You're in deep on the databases. We've got a good round up of, of topics here ranging from healthcare to getting under the hood on databases. So as we'll start with you, what are you working on right now? What trends do you see in the database space? >>Yeah, sure. So I do, uh, I do a lot of consulting work working with different people and, you know, often with, with dynamo DB or, or just general serverless technology type stuff. Um, if you want to talk about trends that I'm seeing right now, I would say trends you're seeing as a lot, just more serverless native databases or cloud native databases where you're seeing these cool databases come out that really take advantage of, uh, this new cloud environment, right? Where you have scalability, you have plasticity of the clouds. So you're not having, you know, instant space environments anymore. You're paying for capacity, you're paying for throughput. You're able to scale up and down. You're not managing individual instances. So a lot of cool stuff that we're seeing, you know, um, with this new generation of, of infrastructure and in particular database is taking advantage of this, this new cloud world >>And really lot deep into the database side in terms of like cloud native impact, diversity of database types, when to use certain databases that also a big deal. >>Yeah, absolutely. I like, I totally agree. I love seeing the different types of databases and, you know, AWS has this whole, uh, purpose-built database strategy. And I think that, that makes a lot of sense. Um, you know, I want to go too far with it. I would, I would more think about purpose-built categories and things like that, you know, specialize in an OLTB database within your, within your organization, whether that's dynamo DB or document DB or relational database Aurora or something like that. But then also choose some sort of analytics database, you know, if it's drew it or Redshift or Athena, and then, you know, if you have some specialized needs, you want to show some real time stuff to your users, check out rock site. If you want to, uh, you know, do some graph analytics, fraud detection, checkout tiger graph, a lot of cool stuff that we're seeing from the startup showcase here. >>Looking forward to unpacking that Lynn you've been in love now, a healthcare action with cloud ops, the pandemic pushes hard core on everybody. What are you working on? >>Yeah, it's all COVID data all the time. Uh, before the pandemic, I was supporting research groups for cancer genomics, which I still do, but, um, what's, uh, impactful is the explosive data volumes. You know, when you there's big data and there's genomic data, you know, I've worked with clients that have broken data centers, broken public cloud provider data centers because of the daily volume they're putting in. So there's this volume aspect. And then there's a collaboration, particularly around COVID research because of pandemic. And so you have this explosive volume, you have this, um, need for, uh, computational complexity. And that means cloud the challenge is it, you know, put the pedal to the metal. So you've got all these bioinformatics researchers that are used to single machine. Suddenly they have to deal with distributed compute. So it's a wild time to be in this space. >>What was the big change that you've seen with the, uh, the pandemic and in genomic cloud genomic specifically what's the big change has happened. >>The amount of data that is being put into the public cloud, um, previously people would have their data on their local, uh, capacity, and then they would publish their paper and the data may or may not become available for, uh, reproducing the research, uh, to accelerate for drug discovery and even variant identification. The data sets are being pushed to public cloud repositories, which is a whole new set of concerns. You have not only dealing with the volume and cost, but security, you know, there's federated security is non-trivial and not well understood by this domain. So there's so much work available here. >>Awesome. Peter, you're doing a lot with the data as a platform kind of view and platform engineering data as code is, is something that's being kicked around. What are you working on and how does platform engineering change as data becomes so much more prevalent in its value proposition? >>Yeah. So I'm the founder of cloud Cedar and, um, we sort of built this company out, this consultancy all around the challenges that a lot of companies have got with getting their data sorted, getting it organized, getting it ready for other use cases, such as analytics and machine learning, um, AI workloads and the like. So typically a platform engineering team will look after the organization of a company infrastructure, making sure that it's coherent across the company and a data platform, engineering teams doing something similar in that sense where they're, they're looking at making sure that, uh, data teams have a solid foundation to build upon, uh, that everything's quite predictable and what that enables is a faster velocity and the ability to use data as code as a way of specifying and onboarding data, building that, translating it, transforming it out into its specific domains and then on to data products. >>I have to ask you while you're here. Um, there's a big trend around data meshes right now. You're hearing, we've had a lot of stuff on the cube. Um, what are practical that people are using data mesh, first of all, is it relevant and how are people looking at this data mesh conversation? >>I think it becomes more and more relevant, uh, the bigger the organization that you're dealing with. So, you know, often times in the enterprise, you've got, uh, projects with timelines of five to 10 years often outlasting technology life cycles. The technology that you're building on is probably irrelevant by the time that you complete it. And what we're seeing is that data engineering teams and data teams more broadly, this organizational bottleneck and data mesh is all about, uh, breaking down that, um, bottleneck and decentralizing the work, shifting that work back onto, uh, development teams who oftentimes have got more of the context and a centralized data engineering team. And we're seeing a lot of, uh, Philocity increases as a result of that. >>It's interesting. There's so many different aspects of how data is changing the world. Lynn talks about the volume with the cloud and genomics. We're hearing data engineering at a platform level. You're talking about slicing and dicing and real-time information. You mentioned rock set, Alex. So I'd like to ask each of you to answer this next question, which is how has the team dynamics changed with data engineering because every single company's impacted. So if you're researchers, Lynn, you're pumping more data into the cloud, that's got a little bit of data engineering to it. Do they even understand that is that impacting them? So how has data changed the responsibilities or roles in this new emerging area of data engineering or whatever you want to call it? Lynn, we'll start with you. What do you, what do you see this impact? >>Well, you know, I mean, dev ops becomes data ops and ML ops and, uh, you know, this is a whole emergent area of work and it starts with an understanding of container technologies, which, you know, in different verticals like FinTech, that's a given, right, but in bioinformatics building an appropriately optimized Docker container is something I'm still working with customers now on because they have the concept of a Docker container is just a virtual machine, which obviously it isn't, or shouldn't be. So, um, you have, again, as I mentioned previously, this humongous skill gap, um, concepts like D, which are prevalent in ad tech FinTech, that's not available yet for most of my customers. So those are the things that I'm building. So the whole ops space is, um, this a wide open area. And really it's a question of practicality. Um, you know, I have, uh, a lot of experience with data lakes and, you know, containerizing and using the data lake platform. But a lot of my customers are going to move to like an interim pass based solutions. If they're using spark, for example, they might use to use a managed spark solution as an interim, um, step up to the cloud before they build their own containers. Because the amount of knowledge to do that effectively is non-trivial >>Peter, you mentioned data, you mentioned data lakes, onboarding data into lake house architectures, for instance, something that you're familiar with. Um, this is not obvious to some verticals obvious to others. What do you see this data engineering impact from a personnel standpoint? And then ultimately how things get built, >>You know, are you directing that to me, >>Peter? >>Yeah. So I think, um, first and foremost, you know, the workload that data engineering teams are dealing with is ever increasing. Usually there's a 10 X ratio of, um, software engineers to data engineers within a business and usually double the amount of analysts to data engineers again. And so they're, they're fighting it ever increasing backload. And, uh, so they're fighting an ever increasing backlog of, of, uh, tasks to do and tickets to, to, to churn through. And so what we're seeing is that data engineering teams are becoming data platform engineering teams where they're building capability instead of constantly hamster wheels spinning if you will. And so with that in mind, with onboarding data into, uh, a Lakehouse architecture or a data lake where data engineering teams, uh, uh, getting wins is developing a very good baseline of structure where they're getting the categorization, the data tagging, whether this data is of a particular domain, does it contain some, um, PII data, for instance, uh, and, and, and, and then the security aspects, and also, you know, the mechanisms on which to do the data transformations, >>Alex, on the database side, those are known personas in an enterprise, a them, the database team, but now the scale is so big. Um, and there's so much going on in databases. How does the data engineering impact organizations from your standpoint? >>Yeah, absolutely. I think definitely, you know, gone are the days where you have a single relational database that is serving operational queries for your users, and you can also serve analytics queries, you know, for your internal teams. It's, it's now split up into those purpose-built databases, like we've said. Uh, but now you've got two different teams managing it and they're, they're designing their data model for different things. You know? So L LLTP might have a more de-normalized model, something that works for very fast operations and it's optimized for that, but now you need to suck that data out and get it elsewhere so that your, your PM or your business analyst, or whoever can crunch through some of that. And, you know, now it needs to be in a more normalized format. How do you sort of bridge that gap? That's a tough one. I think you need to, you know, build empathy on each side of, of what each side is doing and, and build the tools to say, Hey, this is going to help you, uh, you know, LLTP team, if we know what, what users are actually doing, and, and if you can get us into the right format there, so that then I can, you know, we can analyze it, um, on the backend. >>So I think, I think building empathy across those teams is helpful. >>When I left to come back to, you mentioned a health and informatics is coming back. Um, but it's interesting, you know, I look at a database world and you look at the solutions that are out there. A lot of companies that build data solutions don't have a data problem. They've never, they're not swimming in a lot of data, but then you look at like the field that you're working in right now with the genomics and health and, and quantum, they're always, they're dealing with data all the time. So you have people who deal with a lot of data all the time are breaking through New Zealand. People who are don't have that experience are now becoming data full, right? So people are now either it's a first time problem, or they've always been swimming in a ton of data. So it's more of what's the new playbook. And then, wow, I've never had to deal with a lot of data before. What's your take? >>It's interesting. Cause they know, uh, bioinformatics hires, um, uh, grad students. So grad students, you know, use their, our scripts with their file on their laptop. And so, um, to get those folks to understand distributed container-based computing is like I said, a not non-trivial problem. What's been really interesting with the money pouring in to COVID research is when I first started, some of the workflows would take, you know, literally 500 hours and that was just okay. And coming out of FinTech, I was, uh, I could, I was blown away like FinTech is like, could that please take a millisecond rather than a second? Right. And so what has now happened, which makes it, you know, like I said, even more fun to work in this domain is, uh, the research dollars have really gone up because of the pandemic. And so there are, there are, there's this blending of people like me with more of a big data background coming into bioinformatics and working side by side. >>So it's this interesting sort of translation because you have the whole taxonomy of bioinformatics with genomics and sequencers and all the weird file types that you get. And then you have the whole taxonomy of dev ops data ops, you know, containers and Kubernetes and all that. And trying to get that into pipelines that can actually, you know, be efficient, given the constraints. Of course, we, on the tech side, we always want to make it super optimized. I had a customer that we got it down from 500 hours to minutes, but they wanted to stay with the past solution because it was easier for them to go from 500 hours to five hours was good enough, but you know, the techies want to get it down to five minutes. >>This is, this is, we've seen this movie before dev ops, um, edge and op operations, you know, IOT, world scenes, the convergence of cultures. Now you have data and then old, old school operations kind of coming up. So this kind of supports the thesis. That data as code is the next infrastructure as code. What do you guys, what's the reaction there for you guys? What do you think about that? What does data's code mean? If infrastructure's code was cloud and dev ops, what is data as code? What does that mean? >>I could take it if you like. I think, um, data teams, organizations, um, have been long been this bottleneck within the organization and there's like this dark matter of untapped energy and potential waiting to be unleashed a data with the advent of open source projects like DBT, um, have been slowly sort of embracing software development, lifecycle practices. And this is really sort of seeing a, a big steep increase in, um, in their velocity. And, and this is only going to increase and improve as we're seeing data teams, um, embrace starter as code. I think it's, uh, the future is bright for data. So I'm very excited. >>Lynn Peter reaction. I mean, agility data is code is developer concept CICB pipeline. You mentioned it new operational workflows coming into traditional operations reaction. >>Yeah. I mean, I think Peter's right on there. I'd say, you know, some of those tools we're seeing come in from, from software, like, like DBT, basically giving you that infrastructure as code, but applied to that data realm. Also there have been a few, like get for data type things, pack a derm, I believe is one and a few other ones where you bring that in and you also see a lot of immutability concepts flowing into the data realm. So I think just seeing some of those software engineering concepts come over to the data world has, has been pretty interesting >>What we'll literally just versioning datasets and the identification of what's in a data set. What's not in a data set. Some of this is around ethical AI as well, um, is a whole, uh, area that has come out of research groups. Um, mostly AI research groups, but is being applied to medical data and needs to be obviously, um, so this, this, this, um, metadata and versioning around data sets is really, I think, a very of the moment area. >>Yeah, I think we, we, you guys are bringing up a really good kind of direction that's happening in data. And that is something that you're seeing on the software side, open source and now dev ops. And now going to data is that the supply chain challenges of we've been talking about it here on the cube and this, this, um, this episode is, you know, we've seen Ukraine war, but some open source, you know, malware hitting datasets is data secure. What is that going to look like? So you starting to get into this what's the supply chain, is it verified data sets if data sets have to be managed a whole nother level of data supply chain comes up, what do you guys think about that? >>I'll jump in. Oh, sorry. I'll jump in again. I think that, you know, there's, there's, um, some, some of the compliance requirements, um, around financial data are going to be applied to other types of data, probably health data. So immutability reproducibility, um, that is, uh, legally required. Um, also some of the privacy requirements that originated in Europe with GDPR are going to be replicated as more and more, um, types of data. And again, I'm always going to speak for health, but there's other types as well coming out of personal devices and that kind of stuff. So I think, you know, this idea of data as code is it's, it goes down to versioning and controlling and, um, that's, uh, that's sort of a real succinct way to say it that we didn't used to think about that. We just put it in our, you know, relational database and we were good to go, but, um, versioning and controlling in the global ecosystem is kind of, uh, where I'm focusing my efforts. >>It brings up a good question. If databases, if data is going to be part of the development process has to be addressable, which means horizontally scalable. That means it has to be accessible and open. How do you make that work and not foreclose it with a lot of restrictions? >>I think the use of data catalogs and appropriate tagging and categorization, you know, I think, you know, everyone's heard of the term data swamp, and I think that just came about because that everyone saw like, oh, wow, S3, you know, infinite storage. We just, you know, throw whatever in there for as long as we want. And I think at times, you know, the proliferation of S3 buckets, um, and the like, you know, we've just seen, uh, perhaps security, not maintained as well as it could have been. And I think that's kind of where data platform engineering teams have really sort of, uh, come into the, for, you know, creating a governance set of buckets like formation on top. But I think that's kind of where we need to see a lot more work with appropriate tags and also the automatic publishing of metadata into data catalogs so that, um, folks can easily search and address particular data sets and also control the access. You know, for instance, you've got some PII data, perhaps really only your marketing folks should be looking at email addresses and the like not perhaps your finance folks. So I think, you know, there's, there's a lot to be leveraged there in formation and other solutions, >>Alex, let's back up and talk about what's in it for the customer, right. Let's zoom back and saying reality is I just got to get my data to make sure it's secure always on and not going to be hackable. And I just got to get my data available on river performance. So then, then I got to start thinking about, okay, how do I intersect it? So what should teams be thinking about right now as I look up all their data options or databases across their enterprise? >>Yeah, it's, it's a, it's a good question. I just, you know, I think Peter made some good points there and you can think of history as sort of ebbing and flowing between centralization and decentralization a lot of times. And you know, when storage was expensive, data was going to be sort of centralized and Maine maintained, sort of a, you know, by the, uh, the people that are in charge of it. But then when, when S3 comes along, it really decreases storage. Now we can do a lot more experiments on it. We can store a lot more of our data, keep it around and do different things on it. You know, now we've got regulations again, we were, we gotta, we gotta be more realistic about, about keeping that data secure and make sure we're, we're doing the right things with it. So it's, we're gonna probably go through a period of, of centralization as we work out some of this tooling around, you know, tagging and, and ethical AI that, that both Peter. And when we're talking about here and maybe get us into that, that next wearable world of de-centralization again. But I, I think that ebb and flow is going to be natural in response to, you know, the problems of the, the other extreme, >>Where are we in the market right now from progress standpoint, because data lakes don't want to be data swamps. You seeing lake formation as a data architecture, as an example, where are we with customers? What are they doing right now? Where would you put them in the progress bar of, of evolution towards the Nirvana of having this data sovereignty? And this data is code environment. Are they just now in the data lake store, everything real-time and historical? >>Well, I can jump in there. Um, SQL on files is the, is the driver. And so we know when Amazon got Athena, um, that really drove a lot of the customers to really realistically look at data lake technologies, but data warehouses are not going away. And the integration between the two is not seamless. No, we, we are partners with AWS, but we don't work for them. So we can tell you the truth here. Um, there's, there's work to it, but it really, for my customers, it really upped the ante around data lake, uh, because Athena and technologies like that, the serverless, um, SQL queries or the familiar quarry, um, uh, libraries really drove a movement away from either OLTB or OLAP, more expensive, more cumbersome structures, >>But they still need that. Oh, LTP, like if they have high latency issues, they want to be low latency. Can they have the best of both worlds? That's the question. >>I mean, I w I would say we're getting, you know, we're getting closer. We're always going to be, uh, you know, that technology is going to be moving forward, and then we'll just move the goalpost again, in terms of, of what we're asking from it. But I think, you know, the technology that's getting out there, you can get, get really well. And then, you know, just what I work in the dynamo DB world. So you can get really great low latency. So, you know, single digit millisecond LLTP response times on that. I think some of the analytics stuff has been a problem with that. And there, there are different solutions out there to where you can export dynamo to S3, and then you can be doing SQL on your FA your files with Athena Lakeland's talking about, or now you see, you know, rock set of partner here that that'll just ingest your dynamo, DB data, you know, make all those changes. So if you're doing a lot of, uh, changes to your data and dynamo is going to reflect in Roxanna, and then you can do analytics queries, you can do complex filters, different things like that. So, you know, I, I think we continue to push the envelope and then we moved the goalpost again. But, um, you know, I think we're in a, a lot better place than we were a few years ago, for sure. >>Where do you guys see this going relative to the next level? If data as code becomes that next agile, um, software defined environment with open source? Well, all of these new tools with serverless things happening with data lakes are built in with nice architectures with data warehouses, where does it go next? What happens next? If this becomes an agile environment, what's the impact? >>Well, I don't want to be so dominant, but I have, I feel strongly, so I'm going to jump in here. So, so I, um, I feel like, you know, now for my, my, my most computationally intensive workloads, I'm using GPS, I'm bursting to GPU for TensorFlow neural networks. So I've been doing quite a bit of exploration around Amazon bracket for QPS and it's early. Um, and it's specialty. It's not, you know, for everybody. And the learning curve again is pretty daunting, but, um, there are some use cases out there. I mean, I got ahold of a paper where some people did some, um, it was a Q CNN, um, quantum convolutional neural network for lung cancer images, um, from COVID patients and the, the, uh, the QP Hugh, um, algorithm pipeline performed more accurately and faster. So I think, um, bursting to quantum is something to pay attention to. >>Awesome. Peter, what's your take on what's next? >>Well, I think there's still, um, that, that was absolutely fascinating from Lynn, but I think also there's, there's, uh, you know, some more sort of low-level, uh, low-hanging fruit available in, in the data stack. I think there's a lot of, there's still a lot of challenges around the transformation there, getting our data from sort of raw landed data into business domains, and that sort of talks to a lot of what data mesh is all about. I think if we can somehow make that a little more frictionless, because that that's really where the like labor intensive work is. That's, that's kinda dominating, uh, data engineering teams and where we're sort of trying to push that, that workload back onto, um, you know, software engineering teams. >>Alice will give you the final word. What's the impact. What's the next step? What's it look like in the future? >>Yeah, for sure. I mean, I've never had the, uh, breaking a data center problem that wind's had, or the bursting the quantum problem, for sure. But, you know, if you're in that, you know, the pool I swim and of terabytes of data and below and things like that, I think it's a good time. It just like we saw, you know, like we were talking about dev ops and, and pushing, uh, you know, allowing software engineers to handle more of, of the operation stuff. I think the same thing with data can happen where, you know, software engineering teams can handle not just their code, not just, you know, deploying and operating it, but also thinking about their data around the code. And that doesn't mean you won't have people assist you within your organization. You won't have some specialists in there, but I think pushing more stuff, even onto the individual development teams where they have ownership of that. And they're thinking about it through all this different life cycle. I mean, I'm pretty bullish on that. And I think that's an exciting development >>Was that shift, what left with left is security. What does that mean to >>Shipped so much stuff left, but now, you know, the things that were at the end are back at the end again, but, uh, you know, at least we think we can think about that stuff early in the process, which is good, >>Great conversation, very provocative, very realistic and great impact on the future data as code is real, the developers I do believe will have a great operational role and the data stack concept and impacting things like quantum, it's all kind of lining up nicely. Um, and it's a great opportunity to be in this field from a science and policy standpoint. Um, data engineering is legit. It's going to continue to grow and thanks for unpacking that here on the queue. Appreciate it. Okay. Great panel D AWS heroes. They work with AWS and the ecosystem independently out there. They're in the trenches doing the front lines, cracking the code here with data as code season two, episode two of the ongoing series of the 80, but startups I'm John for your host. Thanks for watching.

Published Date : Apr 5 2022

SUMMARY :

remotely and look forward to see you in person at the next re-invent or other event. What trends do you see in the database space? So I do, uh, I do a lot of consulting work working with different people and, you know, often with, And really lot deep into the database side in terms of like cloud native impact, diversity of database and then, you know, if you have some specialized needs, you want to show some real time stuff to your users, check out rock site. What are you working on? you know, put the pedal to the metal. What was the big change that you've seen with the, uh, the pandemic and in genomic cloud genomic specifically but security, you know, there's federated security is non-trivial and not well understood What are you working on and how does making sure that it's coherent across the company and a data platform, I have to ask you while you're here. So, you know, often times in the enterprise, you've got, uh, projects with So I'd like to ask each of you to answer this next question, which is how has the team dynamics Um, you know, I have, uh, a lot of experience with data lakes and, you know, containerizing and using What do you see this data engineering impact from a personnel standpoint? and then the security aspects, and also, you know, the mechanisms How does the data engineering impact organizations from your standpoint? I think definitely, you know, gone are the days where you have a single relational database that is serving but it's interesting, you know, I look at a database world and you look at the solutions that are out there. which makes it, you know, like I said, even more fun to work in this domain is, uh, the research dollars have really for them to go from 500 hours to five hours was good enough, but you know, edge and op operations, you know, IOT, world scenes, I could take it if you like. I mean, agility data is code is developer concept CICB I'd say, you know, some of those tools we're seeing come in from, from software, to be obviously, um, so this, this, this, um, metadata and versioning around you know, we've seen Ukraine war, but some open source, you know, malware hitting datasets I think that, you know, there's, there's, um, How do you make that work and not foreclose it with a lot of restrictions? So I think, you know, there's, there's a lot to be leveraged there in formation And I just got to get my data available on river performance. But I, I think that ebb and flow is going to be natural in response to, you know, the problems of the, Where would you put them in the progress bar of, of evolution towards the So we can tell you the truth here. the question. We're always going to be, uh, you know, that technology is going to be moving forward, so I, um, I feel like, you know, now for my, my, my most computationally intensive Peter, what's your take on what's next? but I think also there's, there's, uh, you know, some more sort of low-level, Alice will give you the final word. I think the same thing with data can happen where, you know, software engineering teams can handle What does that mean to Um, and it's a great opportunity to be

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>>Okay. We're here with the rest of the child who was the chief product officer at Altryx and Adam Wilson, the CEO of Trifacta. Now of course, part of Altryx just closed this quarter. Gentlemen. Welcome. >>Great to be here. >>Okay. So rest, let me start with you. In my opening remarks, I talked about Altrix is traditional position serving business analysts and how the hyper Anna acquisition brought you deeper into the business user space. What does Trifacta bring to your portfolio? Why'd you buy the company? >>Yeah. Thank you. Thank you for the question. Um, you know, we see, uh, we see a massive opportunity of helping, um, brands, um, democratize the use of analytics across their business. Um, every knowledge worker, every individual in the company should have access to analytics. It's no longer optional, um, as they navigate, uh, their businesses with that in mind, you know, we know designer and are the products that Ultrix has been selling the past decade or so do a really great job, um, addressing the business analysts, uh, with, um, hyperaware, um, now kind of renamed, um, Altrix auto insights. Uh, we even speak with the, uh, business owner of the line of business owner. Who's looking for insights that aren't real in traditional dashboards and so on. Um, but we see this opportunity of really helping the data engineering teams and it organizations, um, to also make better use of analytics. Um, and that's where the drive factor comes in for us. Um, drive factor has the best data engineering cloud in the planet. Um, they have an established track record of working across multiple cloud platforms and helping data engineers, um, do better data pipelining and work better with, uh, this massive kind of cloud transformation that's happening in every business. Um, and so Trifacta made so much sense for us. >>Yeah. Thank you for that. I mean, look, you could have built it yourself. Would've taken, you know, who knows how long, but, uh, so definitely a great time to market move, Adam. I wonder if we could dig into Trifacta some more, I mean, I remember interviewing Joe Hellerstein in the early days. You've talked about this as well, uh, on the cube coming at the problem of taking data from raw refined to an experience point of view. And Joe in the early days, talked about flipping the model and starting with data visualization, something Jeff, her was expert at. So maybe explain how we got here. We used to have this cumbersome process of ETL and you may be in some others changed that model with ELL and then T explain how Trifacta really changed the data engineering game. >>Yeah, that's exactly right. Uh, David, it's been a really interesting journey for us because I think the original hypothesis coming out of the campus research, uh, at Berkeley and Stanford that really birthed Trifacta was, you know, why is it that the people who know the data best can't do the work? You know, why is this become the exclusive purview of the highly technical and, you know, can we rethink this and make this a user experience, problem powered by machine learning that will take some of the more complicated things that people want to do with data and really helped to automate those. So, so a, a broader set of users can, um, can really see for themselves and help themselves. And, and I think that, um, there was a lot of pent up frustration out there because people have been told for, you know, for a decade now to be more data-driven and then the whole time they're saying, well, then give me the data, you know, in the shape that I can use it with the right level of quality and I'm happy to be, but don't tell me to be more data driven and then, and, and not empower me, um, to, to get in there and to actually start to work with the data in meaningful ways. >>And so, um, that was really, you know, what, you know, the origin story of the company. And I think as, as we, um, you know, saw over the course of the last 5, 6, 7 years that, um, you know, a real, uh, excitement to embrace this idea of, of trying to think about data engineering differently, trying to democratize the, the ETL process and to also leverage all of these exciting new, uh, engines and platforms that are out there that allow for processing, you know, ever more diverse data sets, ever larger data sets and new and interesting ways. And that's where a lot of the push down or the ELT approaches that, you know, I think it could really won the day. Um, and that, and that for us was a hallmark of the solution from the very beginning. >>Yeah, this is a huge point that you're making. This is first of all, there's a large business, it's probably about a hundred billion dollar Tam. Uh, and the, the point you're making is we've looked, we've contextualized most of our operational systems, but the big data pipelines hasn't gotten there. And maybe we could talk about that a little bit because democratizing data is Nirvana, but it's been historically very difficult. You've got a number of companies it's very fragmented and they're all trying to attack their little piece of the problem to achieve an outcome, but it's been hard. And so what's going to be different about Altryx as you bring these puzzle pieces together, how is this going to impact your customers who would like to take that one? >>Yeah, maybe, maybe I'll take a crack at it. And Adam will, um, add on, um, you know, there hasn't been a single platform, uh, for analytics automation in the enterprise, right? People have relied on, uh, different products, um, to solve kind of, uh, smaller problems, um, across this analytics, automation, data transformation domain. Um, and, um, I think uniquely altereds has that opportunity. Uh, we've got 7,000 plus customers who rely on analytics for, um, data management, for analytics or AI and ML, uh, for transformations, uh, for reporting and visualization for automated insights and so on. And so by bringing drive factor, we have the opportunity to scale this even further and solve for more use cases, expand the scenarios where it's gets applied and so multiple personas. Um, and now we just talked about the data engineers. They are really a growing stakeholder in this transformation of data and analytics. >>Yeah, good. Maybe we can stay on this for a minute cause you, you you're right. You bring it together. Now that at least 3% is the business analyst, the end user slash business user. And now the data engineer, which is really out of an it role in a lot of companies, and you've used this term, the data engineering cloud, what is that, how is it going to integrate in with, or support these other personas? And, and how's it going to integrate into the broader ecosystem of clouds and cloud data warehouses or any other data stores? >>Yeah, no, that's great. Uh, yeah, I think for us, we really looked at this and said, you know, we want to build an open and interactive cloud platform for data engineers, you know, to collaboratively profile pipeline, um, and prepare data for analysis. And that really meant collaborating with the analysts that were in the line of business. And so this is why a big reason why this combination is so magic because ultimately if we can get the data engineers that are creating the data products together with the analysts that are, uh, in the line of business that are driving a lot of the decision-making and allow for that, what I would describe as collaborative curation of the data together, so that you're starting to see, um, uh, you know, increasing returns to scale as this, uh, as this rolls out. I just think that is an incredibly powerful combination and, and frankly, something that the market has not cracked the code on yet. And so, um, I think when we, when I sat down with Suresh and with mark and the team at Ultrix, that was really part of the, the, the big idea, the big vision that that was painted and, and got us really energized about the acquisition and about the potential of the combination. >>Yeah. And you're really, you're obviously riding the cloud and the cloud native wave. Um, and, but specifically we're seeing, you know, I almost don't even want to call it a data warehouse anyway, because when you look at what's, for instance, snowflake is doing, of course their marketing is around the data cloud, but I actually think there's real justification for that because it's not like the traditional data warehouse, right. It's, it's simplified get there fast, don't necessarily have to go through the central organization to share data. Uh, and, and, and, but it's really all about simplification, right? Isn't that really what the democratization comes down to. >>Yeah. It's simplification and collaboration. Right. I don't want to, I want to kind of just, um, what Adam said resonates with me deeply, um, analytics is one of those, um, massive disciplines, an enterprise that's really had the weakest of tools. Um, and we just have interfaces to collaborate with, and I think truly this was Alteryx's and a superpower was helping the analysts get more out of their data, get more out of the analytics, like imagine a world where these people are collaborating and sharing insights in real time and sharing workflows and getting access to new data sources, um, understanding data models better, I think, um, uh, curating those insights. I boring Adam's phrase again. Um, I think that creates a real value inside the organization, uh, because frankly in scaling analytics and democratizing analytics and data, we're still in such early phases of this journey. >>So how should we think about designer cloud, which is from Altryx it's really been the on-prem and the server desktop offering. And of course Trifacta is with cloud cloud data warehouses. Right. Uh, how, how should we think about those two products? >>Yeah, I think, I think you should think about them and, uh, um, as, as very complimentary right design a cloud really shares a lot of DNA and heritage with, uh, designer desktop, um, the low code tooling and that interface, uh, that really appeals to the business analysts, um, and gets a lot of the things that they do well, we've also built it with interoperability in mind, right. So if you started building your workflows in designer desktop, you want to share that with design and cloud, we want to make it super easy for you to do that. Um, and I think over time now we're only a week into, um, this Alliance with, um, with Trifacta. Um, I think we have to get deeper inside to think about what does the data engineer really need what's business analysts really need and how to design a cloud, and Trifacta really support both of those requirements, uh, while kind of continue to build on the tri-factor on the amazing tri-factor cloud platform. >>You know, >>I was just going to say, I think that's one of the things that, um, you know, creates a lot of, uh, opportunity as we go forward, because ultimately, you know, Trifacta took a platform, uh, first mentality to everything that we built. So thinking about openness and extensibility and, um, and how over time people could build things on top of, by factor that are a variety of analytic tool chain, or analytic applications. And so, uh, when you think about, um, Ultrix now starting to, uh, to move some of its capabilities or to provide additional capabilities, uh, in the cloud, um, you know, Trifacta becomes a platform that can accelerate, you know, all of that work and create, uh, uh, a cohesive set of, of cloud-based services that, um, share a common platform. And that maintains independence because both companies, um, have been, uh, you know, fiercely independent, uh, and really giving people choice. >>Um, so making sure that whether you're, uh, you know, picking one cloud platform and other, whether you're running things on the desktop, uh, whether you're running in hybrid environments, that, um, no matter what your decision, um, you're always in a position to be able to get out your data. You're always in a position to be able to cleanse transform shape structure, that data, and ultimately to deliver, uh, the analytics that you need. And so I think in that sense, um, uh, you know, this, this again is another reason why the combination, you know, fits so well together, giving people, um, the choice. Um, and as they, as they think about their analytics strategy and their platform strategy going forward, >>Yeah. I make a chuckle, but I, one of the reasons I always liked Altryx is cause you kinda did the little end run on it. It can be a blocker sometimes, but that created problems, right? Because the current organization said, wow, there's big data stuff is taken off, but we need security. We need governance. And, and it was interesting because he got, you know, ETTL has been complex, whereas the visualization tools, they really, you know, really weren't great at governance and security. It took some time there. So that's not, not their heritage. You're bringing those worlds together. And I'm interested, you guys just had your sales kickoff, you know, what was their reaction like, uh, maybe Suresh, you could start off and maybe Adam, you could bring us home. >>Yeah. Um, thanks for asking about our sales kickoff. So we met for the first time and kind of two years, right. For, as, as it is for many of us, um, in person, uh, um, which I think was, uh, was a real breakthrough as Qualtrics has been on its transformation journey. Uh, we had a Trifacta to, um, the, the party such as the tour, um, and getting all of our sales teams and product organizations, um, to meet in person in one location. I thought that was very powerful for us, the company. Uh, but then I tell you, um, um, the reception for Trifacta was beyond anything I could have imagined. Uh, we were working Adam and I were working so hard on, on the deal and the core hypothesis and so on. And then you step back and you kind of share the vision, uh, with the field organization and it blows you away, the energy that it creates among our sellers, our partners, and I'm sure Adam will, and his team were mocked every single day with questions and opportunities to bring them in. >>But Adam, maybe he's chair. Yeah, I know it was, uh, it was through the roof. I mean, uh, uh, the, uh, the amount of energy, the, uh, certainly how welcoming everybody was, uh, uh, you know, just, I think the story makes so much sense together. I think culturally, the company is, are very aligned. Um, and, uh, it was a real, uh, real capstone moment, uh, to be able to complete the acquisition and to, and to close and announced, you know, at the kickoff event. And, um, I think, you know, for us, when we really thought about it, you know, when we ended the story, that we was just, you have this opportunity to really cater to what the end-users, you know, care about, which is a lot about interactivity and self-service, and at the same time. And that's, and that's a lot of the goodness that, um, that Ultrix has brought, you know, through, you know, you know, years and years of, of building a very vibrant community of, you know, thousands, hundreds of thousands of users. >>And on the other side, you know, Trifacta bringing in this data engineering focus, that's really about, uh, the governance things that you mentioned and the openness, um, that, that it cares deeply about. And all of a sudden, now you have a chance to put that together into a complete story where the data engineering cloud and analytics, automation, you know, coming together. And, um, and I just think, you know, the lights went on, um, you know, for people instantaneously and, you know, this is a story that, um, that I think the market is really hungry for. And certainly the reception we got from, uh, from the broader team at kickoff was, uh, was a great indication of that. >>Well, I think the story hangs together really well, you know, one of the better ones I've seen in, in this space, um, and, and you guys coming off a really, really strong quarter. So congratulations on that Jensen. We have to leave it there. I really appreciate your time today. Yeah. Take a look at this short video. And when we come back, we're going to dig into the ecosystem and the integration into cloud data warehouses and how leading organizations are creating modern data teams and accelerating their digital businesses. You're watching the cube, your leader in enterprise tech coverage.

Published Date : Mar 1 2022

SUMMARY :

the CEO of Trifacta. serving business analysts and how the hyper Anna acquisition brought you deeper into the Um, you know, we see, uh, we see a massive opportunity Would've taken, you know, who knows how long, um, there was a lot of pent up frustration out there because people have been told for, you know, And so, um, that was really, you know, what, you know, the origin story of the company. about Altryx as you bring these puzzle pieces together, how is this going to impact your customers who um, you know, there hasn't been a single platform, And now the data engineer, which is really Uh, yeah, I think for us, we really looked at this and said, you know, and, but specifically we're seeing, you know, I almost don't even want to call it a data warehouse Um, and we just have interfaces to collaborate And of course Trifacta is with cloud cloud data warehouses. Yeah, I think, I think you should think about them and, uh, um, as, as very complimentary in the cloud, um, you know, Trifacta becomes a platform that can you know, this, this again is another reason why the combination, you know, fits so well together, and it was interesting because he got, you know, ETTL has been complex, And then you step back and you kind of share the vision, uh, And, um, I think, you know, for us, when we really thought about it, you know, when we ended the story, And on the other side, you know, Trifacta bringing in this data engineering focus, Well, I think the story hangs together really well, you know, one of the better ones I've seen in, in this space,

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Accelerating Automated Analytics in the Cloud with Alteryx


 

>>Alteryx is a company with a long history that goes all the way back to the late 1990s. Now the one consistent theme over 20 plus years has been that Ultrix has always been a data company early in the big data and Hadoop cycle. It saw the need to combine and prep different data types so that organizations could analyze data and take action Altrix and similar companies played a critical role in helping companies become data-driven. The problem was the decade of big data, brought a lot of complexities and required immense skills just to get the technology to work as advertised this in turn limited, the pace of adoption and the number of companies that could really lean in and take advantage of the cloud began to change all that and set the foundation for today's theme to Zuora of digital transformation. We hear that phrase a ton digital transformation. >>People used to think it was a buzzword, but of course we learned from the pandemic that if you're not a digital business, you're out of business and a key tenant of digital transformation is democratizing data, meaning enabling, not just hypo hyper specialized experts, but anyone business users to put data to work. Now back to Ultrix, the company has embarked on a major transformation of its own. Over the past couple of years, brought in new management, they've changed the way in which it engaged with customers with the new subscription model and it's topgraded its talent pool. 2021 was even more significant because of two acquisitions that Altrix made hyper Ana and trifecta. Why are these acquisitions important? Well, traditionally Altryx sold to business analysts that were part of the data pipeline. These were fairly technical people who had certain skills and were trained in things like writing Python code with hyper Ana Altryx has added a new persona, the business user, anyone in the business who wanted to gain insights from data and, or let's say use AI without having to be a deep technical expert. >>And then Trifacta a company started in the early days of big data by cube alum, Joe Hellerstein and his colleagues at Berkeley. They knocked down the data engineering persona, and this gives Altryx a complimentary extension into it where things like governance and security are paramount. So as we enter 2022, the post isolation economy is here and we do so with a digital foundation built on the confluence of cloud native technologies, data democratization and machine intelligence or AI, if you prefer. And Altryx is entering that new era with an expanded portfolio, new go-to market vectors, a recurring revenue business model, and a brand new outlook on how to solve customer problems and scale a company. My name is Dave Vellante with the cube and I'll be your host today. And the next hour, we're going to explore the opportunities in this new data market. And we have three segments where we dig into these trends and themes. First we'll talk to Jay Henderson, vice president of product management at Ultrix about cloud acceleration and simplifying complex data operations. Then we'll bring in Suresh Vetol who's the chief product officer at Altrix and Adam Wilson, the CEO of Trifacta, which of course is now part of Altrix. And finally, we'll hear about how Altryx is partnering with snowflake and the ecosystem and how they're integrating with data platforms like snowflake and what this means for customers. And we may have a few surprises sprinkled in as well into the conversation let's get started. >>We're kicking off the program with our first segment. Jay Henderson is the vice president of product management Altryx and we're going to talk about the trends and data, where we came from, how we got here, where we're going. We get some launch news. Well, Jay, welcome to the cube. >>Great to be here, really excited to share some of the things we're working on. >>Yeah. Thank you. So look, you have a deep product background, product management, product marketing, you've done strategy work. You've been around software and data, your entire career, and we're seeing the collision of software data cloud machine intelligence. Let's start with the customer and maybe we can work back from there. So if you're an analytics or data executive in an organization, w J what's your north star, where are you trying to take your company from a data and analytics point of view? >>Yeah, I mean, you know, look, I think all organizations are really struggling to get insights out of their data. I think one of the things that we see is you've got digital exhaust, creating large volumes of data storage is really cheap, so it doesn't cost them much to keep it. And that results in a situation where the organization's, you know, drowning in data, but somehow still starving for insights. And so I think, uh, you know, when I talk to customers, they're really excited to figure out how they can put analytics in the hands of every single person in their organization, and really start to democratize the analytics, um, and, you know, let the, the business users and the whole organization get value out of all that data they have. >>And we're going to dig into that throughout this program data, I like to say is plentiful insights, not always so much. Tell us about your launch today, Jay, and thinking about the trends that you just highlighted, the direction that your customers want to go and the problems that you're solving, what role does the cloud play in? What is what you're launching? How does that fit in? >>Yeah, we're, we're really excited today. We're launching the Altryx analytics cloud. That's really a portfolio of cloud-based solutions that have all been built from the ground up to be cloud native, um, and to take advantage of things like based access. So that it's really easy to give anyone access, including folks on a Mac. Um, it, you know, it also lets you take advantage of elastic compute so that you can do, you know, in database processing and cloud native, um, solutions that are gonna scale to solve the most complex problems. So we've got a portfolio of solutions, things like designer cloud, which is our flagship designer product in a browser and on the cloud, but we've got ultra to machine learning, which helps up-skill regular old analysts with advanced machine learning capabilities. We've got auto insights, which brings a business users into the fold and automatically unearths insights using AI and machine learning. And we've got our latest edition, which is Trifacta that helps data engineers do data pipelining and really, um, you know, create a lot of the underlying data sets that are used in some of this, uh, downstream analytics. >>Let's dig into some of those roles if we could a little bit, I mean, you've traditionally Altryx has served the business analysts and that's what designer cloud is fit for, I believe. And you've explained, you know, kind of the scope, sorry, you've expanded that scope into the, to the business user with hyper Anna. And we're in a moment we're going to talk to Adam Wilson and Suresh, uh, about Trifacta and that recent acquisition takes you, as you said, into the data engineering space in it. But in thinking about the business analyst role, what's unique about designer cloud cloud, and how does it help these individuals? >>Yeah, I mean, you know, really, I go back to some of the feedback we've had from our customers, which is, um, you know, they oftentimes have dozens or hundreds of seats of our designer desktop product, you know, really, as they look to take the next step, they're trying to figure out how do I give access to that? Those types of analytics to thousands of people within the organization and designer cloud is, is really great for that. You've got the browser-based interface. So if folks are on a Mac, they can really easily just pop, open the browser and get access to all of those, uh, prep and blend capabilities to a lot of the analysis we're doing. Um, it's a great way to scale up access to the analytics and then start to put it in the hands of really anyone in the organization, not just those highly skilled power users. >>Okay, great. So now then you add in the hyper Anna acquisition. So now you're targeting the business user Trifacta comes into the mix that deeper it angle that we talked about, how does this all fit together? How should we be thinking about the new Altryx portfolio? >>Yeah, I mean, I think it's pretty exciting. Um, you know, when you think about democratizing analytics and providing access to all these different groups of people, um, you've not been able to do it through one platform before. Um, you know, it's not going to be one interface that meets the, of all these different groups within the organization. You really do need purpose built specialized capabilities for each group. And finally, today with the announcement of the alternates analytics cloud, we brought together all of those different capabilities, all of those different interfaces into a single in the end application. So really finally delivering on the promise of providing analytics to all, >>How much of this you've been able to share with your customers and maybe your partners. I mean, I know OD is fairly new, but if you've been able to get any feedback from them, what are they saying about it? >>Uh, I mean, it's, it's pretty amazing. Um, we ran a early access, limited availability program that led us put a lot of this technology in the hands of over 600 customers, um, over the last few months. So we have gotten a lot of feedback. I tell you, um, it's been overwhelmingly positive. I think organizations are really excited to unlock the insights that have been hidden in all this data. They've got, they're excited to be able to use analytics in every decision that they're making so that the decisions they have or more informed and produce better business outcomes. Um, and, and this idea that they're going to move from, you know, dozens to hundreds or thousands of people who have access to these kinds of capabilities, I think has been a really exciting thing that is going to accelerate the transformation that these customers are on. >>Yeah, those are good. Good, good numbers for, for preview mode. Let's, let's talk a little bit about vision. So it's democratizing data is the ultimate goal, which frankly has been elusive for most organizations over time. How's your cloud going to address the challenges of putting data to work across the entire enterprise? >>Yeah, I mean, I tend to think about the future and some of the investments we're making in our products and our roadmap across four big themes, you know, in the, and these are really kind of enduring themes that you're going to see us making investments in over the next few years, the first is having cloud centricity. You know, the data gravity has been moving to the cloud. We need to be able to provide access, to be able to ingest and manipulate that data, to be able to write back to it, to provide cloud solution. So the first one is really around cloud centricity. The second is around big data fluency. Once you have all of the data, you need to be able to manipulate it in a performant manner. So having the elastic cloud infrastructure and in database processing is so important, the third is around making AI a strategic advantage. >>So, uh, you know, getting everyone involved and accessing AI and machine learning to unlock those insights, getting it out of the hands of the small group of data scientists, putting it in the hands of analysts and business users. Um, and then the fourth thing is really providing access across the entire organization. You know, it and data engineers, uh, as well as business owners and analysts. So, um, cloud centricity, big data fluency, um, AI is a strategic advantage and, uh, personas across the organization are really the four big themes you're going to see us, uh, working on over the next few months and, uh, coming coming year. >>That's good. Thank you for that. So, so on a related question, how do you see the data organizations evolving? I mean, traditionally you've had, you know, monolithic organizations, uh, very specialized or I might even say hyper specialized roles and, and your, your mission of course is the customer. You, you, you, you and your customers, they want to democratize the data. And so it seems logical that domain leaders are going to take more responsibility for data, life cycles, data ownerships, low code becomes more important. And perhaps this kind of challenges, the historically highly centralized and really specialized roles that I just talked about. How do you see that evolving and, and, and what role will Altryx play? >>Yeah. Um, you know, I think we'll see sort of a more federated systems start to emerge. Those centralized groups are going to continue to exist. Um, but they're going to start to empower, you know, in a much more de-centralized way, the people who are closer to the business problems and have better business understanding. I think that's going to let the centralized highly skilled teams work on, uh, problems that are of higher value to the organization. The kinds of problems where one or 2% lift in the model results in millions of dollars a day for the business. And then by pushing some of the analytics out to, uh, closer to the edge and closer to the business, you'll be able to apply those analytics in every single decision. So I think you're going to see, you know, both the decentralized and centralized models start to work in harmony and a little bit more about almost a federated sort of a way. And I think, you know, the exciting thing for us at Altryx is, you know, we want to facilitate that. We want to give analytic capabilities and solutions to both groups and types of people. We want to help them collaborate better, um, and drive business outcomes with the analytics they're using. >>Yeah. I mean, I think my take on another one, if you could comment is to me, the technology should be an operational detail and it has been the, the, the dog that wags the tail, or maybe the other way around, you mentioned digital exhaust before. I mean, essentially it's digital exhaust coming out of operationals systems that then somehow, eventually end up in the hand of the domain users. And I wonder if increasingly we're going to see those domain users, users, those, those line of business experts get more access. That's your goal. And then even go beyond analytics, start to build data products that could be monetized, and that maybe it's going to take a decade to play out, but that is sort of a new era of data. Do you see it that way? >>Absolutely. We're actually making big investments in our products and capabilities to be able to create analytic applications and to enable somebody who's an analyst or business user to create an application on top of the data and analytics layers that they have, um, really to help democratize the analytics, to help prepackage some of the analytics that can drive more insights. So I think that's definitely a trend we're going to see more. >>Yeah. And to your point, if you can federate the governance and automate that, then that can happen. I mean, that's a key part of it, obviously. So, all right, Jay, we have to leave it there up next. We take a deep dive into the Altryx recent acquisition of Trifacta with Adam Wilson who led Trifacta for more than seven years. It's the recipe. Tyler is the chief product officer at Altryx to explain the rationale behind the acquisition and how it's going to impact customers. Keep it right there. You're watching the cube. You're a leader in enterprise tech coverage. >>It's go time, get ready to accelerate your data analytics journey with a unified cloud native platform. That's accessible for everyone on the go from home to office and everywhere in between effortless analytics to help you go from ideas to outcomes and no time. It's your time to shine. It's Altryx analytics cloud time. >>Okay. We're here with. Who's the chief product officer at Altryx and Adam Wilson, the CEO of Trifacta. Now of course, part of Altryx just closed this quarter. Gentlemen. Welcome. >>Great to be here. >>Okay. So let me start with you. In my opening remarks, I talked about Altrix is traditional position serving business analysts and how the hyper Anna acquisition brought you deeper into the business user space. What does Trifacta bring to your portfolio? Why'd you buy the company? >>Yeah. Thank you. Thank you for the question. Um, you know, we see, uh, we see a massive opportunity of helping, um, brands, um, democratize the use of analytics across their business. Um, every knowledge worker, every individual in the company should have access to analytics. It's no longer optional, um, as they navigate their businesses with that in mind, you know, we know designer and are the products that Altrix has been selling the past decade or so do a really great job, um, addressing the business analysts, uh, with, um, hyper Rana now kind of renamed, um, Altrix auto. We even speak with the business owner and the line of business owner. Who's looking for insights that aren't real in traditional dashboards and so on. Um, but we see this opportunity of really helping the data engineering teams and it organizations, um, to also make better use of analytics. Um, and that's where the drive factor comes in for us. Um, drive factor has the best data engineering cloud in the planet. Um, they have an established track record of working across multiple cloud platforms and helping data engineers, um, do better data pipelining and work better with, uh, this massive kind of cloud transformation that's happening in every business. Um, and so fact made so much sense for us. >>Yeah. Thank you for that. I mean, you, look, you could have built it yourself would have taken, you know, who knows how long, you know, but, uh, so definitely a great time to market move, Adam. I wonder if we could dig into Trifacta some more, I mean, I remember interviewing Joe Hellerstein in the early days. You've talked about this as well, uh, on the cube coming at the problem of taking data from raw refined to an experience point of view. And Joe in the early days, talked about flipping the model and starting with data visualization, something Jeff, her was expert at. So maybe explain how we got here. We used to have this cumbersome process of ETL and you may be in some others changed that model with ELL and then T explain how Trifacta really changed the data engineering game. >>Yeah, that's exactly right. Uh, David, it's been a really interesting journey for us because I think the original hypothesis coming out of the campus research, uh, at Berkeley and Stanford that really birth Trifacta was, you know, why is it that the people who know the data best can't do the work? You know, why is this become the exclusive purview of the highly technical? And, you know, can we rethink this and make this a user experience, problem powered by machine learning that will take some of the more complicated things that people want to do with data and really help to automate those. So, so a broader set of, of users can, um, can really see for themselves and help themselves. And, and I think that, um, there was a lot of pent up frustration out there because people have been told for, you know, for a decade now to be more data-driven and then the whole time they're saying, well, then give me the data, you know, in the shape that I could use it with the right level of quality and I'm happy to be, but don't tell me to be more data-driven and then, and, and not empower me, um, to, to get in there and to actually start to work with the data in meaningful ways. >>And so, um, that was really, you know, what, you know, the origin story of the company and I think is, as we, um, saw over the course of the last 5, 6, 7 years that, um, you know, uh, real, uh, excitement to embrace this idea of, of trying to think about data engineering differently, trying to democratize the, the ETL process and to also leverage all these exciting new, uh, engines and platforms that are out there that allow for processing, you know, ever more diverse data sets, ever larger data sets and new and interesting ways. And that's where a lot of the push-down or the ELT approaches that, you know, I think it could really won the day. Um, and that, and that for us was a hallmark of the solution from the very beginning. >>Yeah, this is a huge point that you're making is, is first of all, there's a large business, it's probably about a hundred billion dollar Tam. Uh, and the, the point you're making, because we've looked, we've contextualized most of our operational systems, but the big data pipeline is hasn't gotten there. But, and maybe we could talk about that a little bit because democratizing data is Nirvana, but it's been historically very difficult. You've got a number of companies it's very fragmented and they're all trying to attack their little piece of the problem to achieve an outcome, but it's been hard. And so what's going to be different about Altryx as you bring these puzzle pieces together, how is this going to impact your customers who would like to take that one? >>Yeah, maybe, maybe I'll take a crack at it. And Adam will, um, add on, um, you know, there hasn't been a single platform for analytics, automation in the enterprise, right? People have relied on, uh, different products, um, to solve kind of, uh, smaller problems, um, across this analytics, automation, data transformation domain. Um, and, um, I think uniquely Alcon's has that opportunity. Uh, we've got 7,000 plus customers who rely on analytics for, um, data management, for analytics, for AI and ML, uh, for transformations, uh, for reporting and visualization for automated insights and so on. Um, and so by bringing drive factor, we have the opportunity to scale this even further and solve for more use cases, expand the scenarios where it's applied and so multiple personas. Um, and we just talked about the data engineers. They are really a growing stakeholder in this transformation of data and analytics. >>Yeah, good. Maybe we can stay on this for a minute cause you, you you're right. You bring it together. Now at least three personas the business analyst, the end user slash business user. And now the data engineer, which is really out of an it role in a lot of companies, and you've used this term, the data engineering cloud, what is that? How is it going to integrate in with, or support these other personas? And, and how's it going to integrate into the broader ecosystem of clouds and cloud data warehouses or any other data stores? >>Yeah, no, that's great. Uh, yeah, I think for us, we really looked at this and said, you know, we want to build an open and interactive cloud platform for data engineers, you know, to collaboratively profile pipeline, um, and prepare data for analysis. And that really meant collaborating with the analysts that were in the line of business. And so this is why a big reason why this combination is so magic because ultimately if we can get the data engineers that are creating the data products together with the analysts that are in the line of business that are driving a lot of the decision making and allow for that, what I would describe as collaborative curation of the data together, so that you're starting to see, um, uh, you know, increasing returns to scale as this, uh, as this rolls out. I just think that is an incredibly powerful combination and, and frankly, something that the market is not crack the code on yet. And so, um, I think when we, when I sat down with Suresh and with mark and the team at Ultrix, that was really part of the, the, the big idea, the big vision that was painted and got us really energized about the acquisition and about the potential of the combination. >>And you're really, you're obviously writing the cloud and the cloud native wave. Um, and, but specifically we're seeing, you know, I almost don't even want to call it a data warehouse anyway, because when you look at what's, for instance, Snowflake's doing, of course their marketing is around the data cloud, but I actually think there's real justification for that because it's not like the traditional data warehouse, right. It's, it's simplified get there fast, don't necessarily have to go through the central organization to share data. Uh, and, and, and, but it's really all about simplification, right? Isn't that really what the democratization comes down to. >>Yeah. It's simplification and collaboration. Right. I don't want to, I want to kind of just what Adam said resonates with me deeply. Um, analytics is one of those, um, massive disciplines inside an enterprise that's really had the weakest of tools. Um, and we just have interfaces to collaborate with, and I think truly this was all drinks and a superpower was helping the analysts get more out of their data, get more out of the analytics, like imagine a world where these people are collaborating and sharing insights in real time and sharing workflows and getting access to new data sources, um, understanding data models better, I think, um, uh, curating those insights. I boring Adam's phrase again. Um, I think that creates a real value inside the organization because frankly in scaling analytics and democratizing analytics and data, we're still in such early phases of this journey. >>So how should we think about designer cloud, which is from Altrix it's really been the on-prem and the server desktop offering. And of course Trifacta is with cloud cloud data warehouses. Right. Uh, how, how should we think about those two products? Yeah, >>I think, I think you should think about them. And, uh, um, as, as very complimentary right designer cloud really shares a lot of DNA and heritage with, uh, designer desktop, um, the low code tooling and that interface, uh, the really appeals to the business analysts, um, and gets a lot of the things that they do well, we've also built it with interoperability in mind, right. So if you started building your workflows in designer desktop, you want to share that with design and cloud, we want to make it super easy for you to do that. Um, and I think over time now we're only a week into, um, this Alliance with, um, with, um, Trifacta, um, I think we have to get deeper inside to think about what does the data engineer really need? What's the business analysts really need and how to design a cloud, and Trifacta really support both of those requirements, uh, while kind of continue to build on the trifecta on the amazing Trifacta cloud platform. >>You know, >>I think we're just going to say, I think that's one of the things that, um, you know, creates a lot of, uh, opportunity as we go forward, because ultimately, you know, Trifacta took a platform, uh, first mentality to everything that we built. So thinking about openness and extensibility and, um, and how over time people could build things on top of factor that are a variety of analytic tool chain, or analytic applications. And so, uh, when you think about, um, Ultrix now starting to, uh, to move some of its capabilities or to provide additional capabilities, uh, in the cloud, um, you know, Trifacta becomes a platform that can accelerate, you know, all of that work and create, uh, uh, a cohesive set of, of cloud-based services that, um, share a common platform. And that maintains independence because both companies, um, have been, uh, you know, fiercely independent, uh, and, and really giving people choice. >>Um, so making sure that whether you're, uh, you know, picking one cloud platform and other, whether you're running things on the desktop, uh, whether you're running in hybrid environments, that, um, no matter what your decision, um, you're always in a position to be able to get out your data. You're always in a position to be able to cleanse transform shape structure, that data, and ultimately to deliver, uh, the analytics that you need. And so I think in that sense, um, uh, you know, this, this again is another reason why the combination, you know, fits so well together, giving people, um, the choice. Um, and as they, as they think about their analytics strategy and their platform strategy going forward, >>Yeah. I make a chuckle, but one of the reasons I always liked Altrix is cause you kinda did the little end run on it. It can be a blocker sometimes, but that created problems, right? Because the organization said, wow, this big data stuff has taken off, but we need security. We need governance. And it's interesting because you've got, you know, ETL has been complex, whereas the visualization tools, they really, you know, really weren't great at governance and security. It took some time there. So that's not, not their heritage. You're bringing those worlds together. And I'm interested, you guys just had your sales kickoff, you know, what was their reaction like? Uh, maybe Suresh, you could start off and maybe Adam, you could bring us home. >>Um, thanks for asking about our sales kickoff. So we met for the first time and you've got a two years, right. For, as, as it is for many of us, um, in person, uh, um, which I think was a, was a real breakthrough as Qualtrics has been on its transformation journey. Uh, we added a Trifacta to, um, the, the potty such as the tour, um, and getting all of our sales teams and product organizations, um, to meet in person in one location. I thought that was very powerful for other the company. Uh, but then I tell you, um, um, the reception for Trifacta was beyond anything I could have imagined. Uh, we were working out him and I will, when he's so hot on, on the deal and the core hypotheses and so on. And then you step back and you're going to share the vision with the field organization, and it blows you away, the energy that it creates among our sellers out of partners. >>And I'm sure Madam will and his team were mocked, um, every single day, uh, with questions and opportunities to bring them in. But Adam, maybe you should share. Yeah, no, it was, uh, it was through the roof. I mean, uh, uh, the, uh, the amount of energy, the, uh, certainly how welcoming everybody was, uh, uh, you know, just, I think the story makes so much sense together. I think culturally, the company is, are very aligned. Um, and, uh, it was a real, uh, real capstone moment, uh, to be able to complete the acquisition and to, and to close and announced, you know, at the kickoff event. And, um, I think, you know, for us, when we really thought about it, you know, when we ended, the story that we told was just, you have this opportunity to really cater to what the end users care about, which is a lot about interactivity and self-service, and at the same time. >>And that's, and that's a lot of the goodness that, um, that Altryx is, has brought, you know, through, you know, you know, years and years of, of building a very vibrant community of, you know, thousands, hundreds of thousands of users. And on the other side, you know, Trifacta bringing in this data engineering focus, that's really about, uh, the governance things that you mentioned and the openness, um, that, that it cares deeply about. And all of a sudden, now you have a chance to put that together into a complete story where the data engineering cloud and analytics, automation, you know, coming together. And, um, and I just think, you know, the lights went on, um, you know, for people instantaneously and, you know, this is a story that, um, that I think the market is really hungry for. And certainly the reception we got from, uh, from the broader team at kickoff was, uh, was a great indication. >>Well, I think the story hangs together really well, you know, one of the better ones I've seen in, in this space, um, and, and you guys coming off a really, really strong quarter. So congratulations on that jets. We have to leave it there. I really appreciate your time today. Yeah. Take a look at this short video. And when we come back, we're going to dig into the ecosystem and the integration into cloud data warehouses and how leading organizations are creating modern data teams and accelerating their digital businesses. You're watching the cube you're leader in enterprise tech coverage. >>This is your data housed neatly insecurely in the snowflake data cloud. And all of it has potential the potential to solve complex business problems, deliver personalized financial offerings, protect supply chains from disruption, cut costs, forecast, grow and innovate. All you need to do is put your data in the hands of the right people and give it an opportunity. Luckily for you. That's the easy part because snowflake works with Alteryx and Alteryx turns data into breakthroughs with just a click. Your organization can automate analytics with drag and drop building blocks, easily access snowflake data with both sequel and no SQL options, share insights, powered by Alteryx data science and push processing to snowflake for lightning, fast performance, you get answers you can put to work in your teams, get repeatable processes they can share in that's exciting because not only is your data no longer sitting around in silos, it's also mobilized for the next opportunity. Turn your data into a breakthrough Alteryx and snowflake >>Okay. We're back here in the queue, focusing on the business promise of the cloud democratizing data, making it accessible and enabling everyone to get value from analytics, insights, and data. We're now moving into the eco systems segment the power of many versus the resources of one. And we're pleased to welcome. Barb Hills camp was the senior vice president partners and alliances at Ultrix and a special guest Terek do week head of technology alliances at snowflake folks. Welcome. Good to see you. >>Thank you. Thanks for having me. Good to see >>Dave. Great to see you guys. So cloud migration, it's one of the hottest topics. It's the top one of the top initiatives of senior technology leaders. We have survey data with our partner ETR it's number two behind security, and just ahead of analytics. So we're hovering around all the hot topics here. Barb, what are you seeing with respect to customer, you know, cloud migration momentum, and how does the Ultrix partner strategy fit? >>Yeah, sure. Partners are central company's strategy. They always have been. We recognize that our partners have deep customer relationships. And when you connect that with their domain expertise, they're really helping customers on their cloud and business transformation journey. We've been helping customers achieve their desired outcomes with our partner community for quite some time. And our partner base has been growing an average of 30% year over year, that partner community and strategy now addresses several kinds of partners, spanning solution providers to global SIS and technology partners, such as snowflake and together, we help our customers realize the business promise of their journey to the cloud. Snowflake provides a scalable storage system altereds provides the business user friendly front end. So for example, it departments depend on snowflake to consolidate data across systems into one data cloud with Altryx business users can easily unlock that data in snowflake solving real business outcomes. Our GSI and solution provider partners are instrumental in providing that end to end benefit of a modern analytic stack in the cloud providing platform, guidance, deployment, support, and other professional services. >>Great. Let's get a little bit more into the relationship between Altrix and S in snowflake, the partnership, maybe a little bit about the history, you know, what are the critical aspects that we should really focus on? Barb? Maybe you could start an Interra kindly way in as well. >>Yeah, so the relationship started in 2020 and all shirts made a big bag deep with snowflake co-innovating and optimizing cloud use cases together. We are supporting customers who are looking for that modern analytic stack to replace an old one or to implement their first analytic strategy. And our joint customers want to self-serve with data-driven analytics, leveraging all the benefits of the cloud, scalability, accessibility, governance, and optimizing their costs. Um, Altrix proudly achieved. Snowflake's highest elite tier in their partner program last year. And to do that, we completed a rigorous third party testing process, which also helped us make some recommended improvements to our joint stack. We wanted customers to have confidence. They would benefit from high quality and performance in their investment with us then to help customers get the most value out of the destroyed solution. We developed two great assets. One is the officer starter kit for snowflake, and we coauthored a joint best practices guide. >>The starter kit contains documentation, business workflows, and videos, helping customers to get going more easily with an altered since snowflake solution. And the best practices guide is more of a technical document, bringing together experiences and guidance on how Altryx and snowflake can be deployed together. Internally. We also built a full enablement catalog resources, right? We wanted to provide our account executives more about the value of the snowflake relationship. How do we engage and some best practices. And now we have hundreds of joint customers such as Juniper and Sainsbury who are actively using our joint solution, solving big business problems much faster. >>Cool. Kara, can you give us your perspective on the partnership? >>Yeah, definitely. Dave, so as Barb mentioned, we've got this standing very successful partnership going back years with hundreds of happy joint customers. And when I look at the beginning, Altrix has helped pioneer the concept of self-service analytics, especially with use cases that we worked on with for, for data prep for BI users like Tableau and as Altryx has evolved to now becoming from data prep to now becoming a full end to end data science platform. It's really opened up a lot more opportunities for our partnership. Altryx has invested heavily over the last two years in areas of deep integration for customers to fully be able to expand their investment, both technologies. And those investments include things like in database pushed down, right? So customers can, can leverage that elastic platform, that being the snowflake data cloud, uh, with Alteryx orchestrating the end to end machine learning workflows Alteryx also invested heavily in snow park, a feature we released last year around this concept of data programmability. So all users were regardless of their business analysts, regardless of their data, scientists can use their tools of choice in order to consume and get at data. And now with Altryx cloud, we think it's going to open up even more opportunities. It's going to be a big year for the partnership. >>Yeah. So, you know, Terike, we we've covered snowflake pretty extensively and you initially solve what I used to call the, I still call the snake swallowing the basketball problem and cloud data warehouse changed all that because you had virtually infinite resources, but so that's obviously one of the problems that you guys solved early on, but what are some of the common challenges or patterns or trends that you see with snowflake customers and where does Altryx come in? >>Sure. Dave there's there's handful, um, that I can come up with today, the big challenges or trends for us, and Altrix really helps us across all of them. Um, there are three particular ones I'm going to talk about the first one being self-service analytics. If we think about it, every organization is trying to democratize data. Every organization wants to empower all their users, business users, um, you know, the, the technology users, but the business users, right? I think every organization has realized that if everyone has access to data and everyone can do something with data, it's going to make them competitively, give them a competitive advantage with Altrix is something we share that vision of putting that power in the hands of everyday users, regardless of the skillsets. So, um, with self-service analytics, with Ultrix designer they've they started out with self-service analytics as the forefront, and we're just scratching the surface. >>I think there was an analyst, um, report that shows that less than 20% of organizations are truly getting self-service analytics to their end users. Now, with Altryx going to Ultrix cloud, we think that's going to be a huge opportunity for us. Um, and then that opens up the second challenge, which is machine learning and AI, every organization is trying to get predictive analytics into every application that they have in order to be competitive in order to be competitive. Um, and with Altryx creating this platform so they can cater to both the everyday business user, the quote unquote, citizen data scientists, and making a code friendly for data scientists to be able to get at their notebooks and all the different tools that they want to use. Um, they fully integrated in our snow park platform, which I talked about before, so that now we get an end to end solution caring to all, all lines of business. >>And then finally this concept of data marketplaces, right? We, we created snowflake from the ground up to be able to solve the data sharing problem, the big data problem, the data sharing problem. And Altryx um, if we look at mobilizing your data, getting access to third-party datasets, to enrich with your own data sets, to enrich with, um, with your suppliers and with your partners, data sets, that's what all customers are trying to do in order to get a more comprehensive 360 view, um, within their, their data applications. And so with Altryx alterations, we're working on third-party data sets and marketplaces for quite some time. Now we're working on how do we integrate what Altrix is providing with the snowflake data marketplace so that we can enrich these workflows, these great, great workflows that Altrix writing provides. Now we can add third party data into that workflow. So that opens up a ton of opportunities, Dave. So those are three I see, uh, easily that we're going to be able to solve a lot of customer challenges with. >>So thank you for that. Terrick so let's stay on cloud a little bit. I mean, Altrix is undergoing a major transformation, big focus on the cloud. How does this cloud launch impact the partnership Terike from snowflakes perspective and then Barb, maybe, please add some color. >>Yeah, sure. Dave snowflake started as a cloud data platform. We saw our founders really saw the challenges that customers are having with becoming data-driven. And the biggest challenge was the complexity of having imagine infrastructure to even be able to do it, to get applications off the ground. And so we created something to be cloud-native. We created to be a SAS managed service. So now that that Altrix is moving to the same model, right? A cloud platform, a SAS managed service, we're just, we're just removing more of the friction. So we're going to be able to start to package these end to end solutions that are SAS based that are fully managed. So customers can, can go faster and they don't have to worry about all of the underlying complexities of, of, of stitching things together. Right? So, um, so that's, what's exciting from my viewpoint >>And I'll follow up. So as you said, we're investing heavily in the cloud a year ago, we had two pre desktop products, and today we have four cloud products with cloud. We can provide our users with more flexibility. We want to make it easier for the users to leverage their snowflake data in the Alteryx platform, whether they're using our beloved on-premise solution or the new cloud products were committed to that continued investment in the cloud, enabling our joint partner solutions to meet customer requirements, wherever they store their data. And we're working with snowflake, we're doing just that. So as customers look for a modern analytic stack, they expect that data to be easily accessible, right within a fast, secure and scalable platform. And the launch of our cloud strategy is a huge leap forward in making Altrix more widely accessible to all users in all types of roles, our GSI and our solution provider partners have asked for these cloud capabilities at scale, and they're excited to better support our customers, cloud and analytic >>Are. How about you go to market strategy? How would you describe your joint go to market strategy with snowflake? >>Sure. It's simple. We've got to work backwards from our customer's challenges, right? Driving transformation to solve problems, gain efficiencies, or help them save money. So whether it's with snowflake or other GSI, other partner types, we've outlined a joint journey together from recruit solution development, activation enablement, and then strengthening our go to market strategies to optimize our results together. We launched an updated partner program and within that framework, we've created new benefits for our partners around opportunity registration, new role based enablement and training, basically extending everything we do internally for our own go-to-market teams to our partners. We're offering partner, marketing resources and funding to reach new customers together. And as a matter of fact, we recently launched a fantastic video with snowflake. I love this video that very simply describes the path to insights starting with your snowflake data. Right? We do joint customer webinars. We're working on joint hands-on labs and have a wonderful landing page with a lot of assets for our customers. Once we have an interested customer, we engage our respective account managers, collaborating through discovery questions, proof of concepts really showcasing the desired outcome. And when you combine that with our partners technology or domain expertise, it's quite powerful, >>Dark. How do you see it? You'll go to market strategy. >>Yeah. Dave we've. Um, so we initially started selling, we initially sold snowflake as technology, right? Uh, looking at positioning the diff the architectural differentiators and the scale and concurrency. And we noticed as we got up into the larger enterprise customers, we're starting to see how do they solve their business problems using the technology, as well as them coming to us and saying, look, we want to also know how do you, how do you continue to map back to the specific prescriptive business problems we're having? And so we shifted to an industry focus last year, and this is an area where Altrix has been mature for probably since their inception selling to the line of business, right? Having prescriptive use cases that are particular to an industry like financial services, like retail, like healthcare and life sciences. And so, um, Barb talked about these, these starter kits where it's prescriptive, you've got a demo and, um, a way that customers can get off the ground and running, right? >>Cause we want to be able to shrink that time to market, the time to value that customers can watch these applications. And we want to be able to, to tell them specifically how we can map back to their business initiatives. So I see a huge opportunity to align on these industry solutions. As BARR mentioned, we're already doing that where we've released a few around financial services working in healthcare and retail as well. So that is going to be a way for us to allow customers to go even faster and start to map two lines of business with Alteryx. >>Great. Thanks Derek. Bob, what can we expect if we're observing this relationship? What should we look for in the coming year? >>A lot specifically with snowflake, we'll continue to invest in the partnership. Uh, we're co innovators in this journey, including snow park extensibility efforts, which Derek will tell you more about shortly. We're also launching these great news strategic solution blueprints, and extending that at no charge to our partners with snowflake, we're already collaborating with their retail and CPG team for industry blueprints. We're working with their data marketplace team to highlight solutions, working with that data in their marketplace. More broadly, as I mentioned, we're relaunching the ultra partner program designed to really better support the unique partner types in our global ecosystem, introducing new benefits so that with every partner, achievement or investment with ultra score, providing our partners with earlier access to benefits, um, I could talk about our program for 30 minutes. I know we don't have time. The key message here Alteryx is investing in our partner community across the business, recognizing the incredible value that they bring to our customers every day. >>Tarik will give you the last word. What should we be looking for from, >>Yeah, thanks. Thanks, Dave. As BARR mentioned, Altrix has been the forefront of innovating with us. They've been integrating into, uh, making sure again, that customers get the full investment out of snowflake things like in database push down that I talked about before that extensibility is really what we're excited about. Um, the ability for Ultrix to plug into this extensibility framework that we call snow park and to be able to extend out, um, ways that the end users can consume snowflake through, through sequel, which has traditionally been the way that you consume snowflake as well as Java and Scala, not Python. So we're excited about those, those capabilities. And then we're also excited about the ability to plug into the data marketplace to provide third party data sets, right there probably day sets in, in financial services, third party, data sets and retail. So now customers can build their data applications from end to end using ultrasound snowflake when the comprehensive 360 view of their customers, of their partners, of even their employees. Right? I think it's exciting to see what we're going to be able to do together with these upcoming innovations. Great >>Barb Tara, thanks so much for coming on the program, got to leave it right there in a moment, I'll be back with some closing thoughts in a summary, don't go away. >>1200 hours of wind tunnel testing, 30 million race simulations, 2.4 second pit stops make that 2.3. The sector times out the wazoo, whites are much of this velocity's pressures, temperatures, 80,000 components generating 11.8 billion data points and one analytics platform to make sense of it all. When McLaren needs to turn complex data into insights, they turn to Altryx Qualtrics analytics, automation, >>Okay, let's summarize and wrap up the session. We can pretty much agree the data is plentiful, but organizations continue to struggle to get maximum value out of their data investments. The ROI has been elusive. There are many reasons for that complexity data, trust silos, lack of talent and the like, but the opportunity to transform data operations and drive tangible value is immense collaboration across various roles. And disciplines is part of the answer as is democratizing data. This means putting data in the hands of those domain experts that are closest to the customer and really understand where the opportunity exists and how to best address them. We heard from Jay Henderson that we have all this data exhaust and cheap storage. It allows us to keep it for a long time. It's true, but as he pointed out that doesn't solve the fundamental problem. Data is spewing out from our operational systems, but much of it lacks business context for the data teams chartered with analyzing that data. >>So we heard about the trend toward low code development and federating data access. The reason this is important is because the business lines have the context and the more responsibility they take for data, the more quickly and effectively organizations are going to be able to put data to work. We also talked about the harmonization between centralized teams and enabling decentralized data flows. I mean, after all data by its very nature is distributed. And importantly, as we heard from Adam Wilson and Suresh Vittol to support this model, you have to have strong governance and service the needs of it and engineering teams. And that's where the trifecta acquisition fits into the equation. Finally, we heard about a key partnership between Altrix and snowflake and how the migration to cloud data warehouses is evolving into a global data cloud. This enables data sharing across teams and ecosystems and vertical markets at massive scale all while maintaining the governance required to protect the organizations and individuals alike. >>This is a new and emerging business model that is very exciting and points the way to the next generation of data innovation in the coming decade. We're decentralized domain teams get more facile access to data. Self-service take more responsibility for quality value and data innovation. While at the same time, the governance security and privacy edicts of an organization are centralized in programmatically enforced throughout an enterprise and an external ecosystem. This is Dave Volante. All these videos are available on demand@theqm.net altrix.com. Thanks for watching accelerating automated analytics in the cloud made possible by Altryx. And thanks for watching the queue, your leader in enterprise tech coverage. We'll see you next time.

Published Date : Mar 1 2022

SUMMARY :

It saw the need to combine and prep different data types so that organizations anyone in the business who wanted to gain insights from data and, or let's say use AI without the post isolation economy is here and we do so with a digital We're kicking off the program with our first segment. So look, you have a deep product background, product management, product marketing, And that results in a situation where the organization's, you know, the direction that your customers want to go and the problems that you're solving, what role does the cloud and really, um, you know, create a lot of the underlying data sets that are used in some of this, into the, to the business user with hyper Anna. of our designer desktop product, you know, really, as they look to take the next step, comes into the mix that deeper it angle that we talked about, how does this all fit together? analytics and providing access to all these different groups of people, um, How much of this you've been able to share with your customers and maybe your partners. Um, and, and this idea that they're going to move from, you know, So it's democratizing data is the ultimate goal, which frankly has been elusive for most You know, the data gravity has been moving to the cloud. So, uh, you know, getting everyone involved and accessing AI and machine learning to unlock seems logical that domain leaders are going to take more responsibility for data, And I think, you know, the exciting thing for us at Altryx is, you know, we want to facilitate that. the tail, or maybe the other way around, you mentioned digital exhaust before. the data and analytics layers that they have, um, really to help democratize the We take a deep dive into the Altryx recent acquisition of Trifacta with Adam Wilson It's go time, get ready to accelerate your data analytics journey the CEO of Trifacta. serving business analysts and how the hyper Anna acquisition brought you deeper into the with that in mind, you know, we know designer and are the products And Joe in the early days, talked about flipping the model that really birth Trifacta was, you know, why is it that the people who know the data best can't And so, um, that was really, you know, what, you know, the origin story of the company but the big data pipeline is hasn't gotten there. um, you know, there hasn't been a single platform for And now the data engineer, which is really And so, um, I think when we, when I sat down with Suresh and with mark and the team and, but specifically we're seeing, you know, I almost don't even want to call it a data warehouse anyway, Um, and we just have interfaces to collaborate And of course Trifacta is with cloud cloud data warehouses. What's the business analysts really need and how to design a cloud, and Trifacta really support both in the cloud, um, you know, Trifacta becomes a platform that can You're always in a position to be able to cleanse transform shape structure, that data, and ultimately to deliver, And I'm interested, you guys just had your sales kickoff, you know, what was their reaction like? And then you step back and you're going to share the vision with the field organization, and to close and announced, you know, at the kickoff event. And certainly the reception we got from, Well, I think the story hangs together really well, you know, one of the better ones I've seen in, in this space, And all of it has potential the potential to solve complex business problems, We're now moving into the eco systems segment the power of many Good to see So cloud migration, it's one of the hottest topics. on snowflake to consolidate data across systems into one data cloud with Altryx business the partnership, maybe a little bit about the history, you know, what are the critical aspects that we should really focus Yeah, so the relationship started in 2020 and all shirts made a big bag deep with snowflake And the best practices guide is more of a technical document, bringing together experiences and guidance So customers can, can leverage that elastic platform, that being the snowflake data cloud, one of the problems that you guys solved early on, but what are some of the common challenges or patterns or trends everyone has access to data and everyone can do something with data, it's going to make them competitively, application that they have in order to be competitive in order to be competitive. to enrich with your own data sets, to enrich with, um, with your suppliers and with your partners, So thank you for that. So now that that Altrix is moving to the same model, And the launch of our cloud strategy How would you describe your joint go to market strategy the path to insights starting with your snowflake data. You'll go to market strategy. And so we shifted to an industry focus So that is going to be a way for us to allow What should we look for in the coming year? blueprints, and extending that at no charge to our partners with snowflake, we're already collaborating with Tarik will give you the last word. Um, the ability for Ultrix to plug into this extensibility framework that we call Barb Tara, thanks so much for coming on the program, got to leave it right there in a moment, I'll be back with 11.8 billion data points and one analytics platform to make sense of it all. This means putting data in the hands of those domain experts that are closest to the customer are going to be able to put data to work. While at the same time, the governance security and privacy edicts

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Matt Provo, StormForge


 

(bright upbeat music) >> The adoption of container orchestration platforms is accelerating at a rate as fast or faster than any category in enterprise IT. Survey data from Enterprise Technology Research shows Kubernetes specifically leads the pack into both spending velocity and market share. Now like virtualization in its early days, containers bring many new performance and tuning challenges in particular insuring consistent and predictable application performance is tricky especially because containers, they're so flexible and they enable portability. Things are constantly changing. DevOps pros have to way through a sea of observability data and tuning the environment becomes a continuous exercise of trial and error. This endless cycle taxes resources and kills operational efficiency. So teams often just capitulate and simply dial up and throw unnecessary resources at the problem. StormForge is a company founded mid last decade that is attacking these issues with a combination of machine learning and data analysis. And with me to talk about a new offering that directly addresses these concerns is Matt Provo, founder and CEO of StormForge. Matt, welcome to theCUBE. Good to see you. >> Good to see you. Thanks for having me. >> Yeah, so we saw you guys at a KubeCon sort of first introduce you to our community but add a little color to my intro there if you will. >> Yeah, well, Semi stole my thunder but I'm okay with that. Absolutely agree with everything you said in the intro. You know, the problem that we have set out to solve which is tailor made for the use of real machine learning not machine learning kind of as a marketing tag is connected to how workloads on Kubernetes are really managed from a resource efficiency standpoint. And so a number of years ago, we built the core machine learning engine and have now turned that into a platform around how Kubernetes resources are managed at scale. And so organizations today as they're moving more workloads over, sort of drink the Kool-Aid of the flexibility that comes with Kubernetes and how many knobs you can turn. And developers in many ways love it. Once they start to operationalize the use of Kubernetes and move workloads from pre-production into production, they run into a pretty significant complexity wall. And this is where StormForge comes in to try to help them manage those resources more effectively in ensuring and implementing the right kind of automation that empowers developers into the process ultimately does not automate them out of it. >> So you've got news. You had launch coming to further address these problems. Tell us about that. >> Yeah, so historically, you know, like any machine learning engine, we think about data inputs and what kind of data is going to feed our system to be able to draw the appropriate insights out for the user. And so historically we've kind of been single threaded on load and performance tests in a pre-production environment. And there's been a lot of adoption of that, a lot of excitement around it and frankly amazing results. My vision has been for us to be able to close the loop, however, between data coming out of pre-production and the associated optimizations and data coming out of production environment and our ability to optimize that. A lot of our users along the way have said these results in pre-production are fantastic. How do I know they reflect reality of what my application is going to experience in a production environment? And so we're super excited to announce kind of the a second core module for our platform called Optimize Live. The data input for that is observability and telemetry data coming out of APM platforms and other data sources. >> So this is like Nirvana. So I wonder if we could talk a little bit more about the challenges that this addresses. I mean, I've been around a while and it really have observed... And I used to ask, you know, technology companies all the time. Okay, so you're telling me beforehand what the optimal configuration should be and resource allocation. What happens if something changes? >> Yeah. >> And then it's always, always a pause. >> Yeah. >> And Kubernetes is more of a rapidly changing environment than anything we've ever seen. So specifically the problem you're addressing. Maybe talk about that a little bit. >> Yeah, so we view what happens in pre-production as sort of the experimentation phase. And our machine learning is allowing the user to experiment in scenario plan. What we're doing with Optimize Live and adding the the production piece is what we kind of also call kind of our observation phase. And so you need to be able to run the appropriate checks and balances between those two environments to ensure that what you're actually deploying and monitoring from an application performance, from a cost standpoint is with your SLOs and your SLAs as well as your business objectives. And so that's the entire point of this edition is to allow our users to experience hopefully the Nirvana associated with that because it's an exciting opportunity for them and really something that no else is doing from the standpoint of closing that loop. >> So you said front machine learning not as a marketing tag. So I want you to sort of double click on that. What's different than how other companies approach this problem? >> Yeah, I mean, part of it is a bias for me and a frustration as a founder of the reason I started the company in the first place. I think machine learning or AI gets tagged to a lot of stuff. It's very buzzwordy. It looks good. I'm fortunate to have found a number of folks from the outset of the company with, you know, PhDs in Applied Mathematics and a focus on actually building real AI at the core that is connected to solving the right kind of actual business problems. And so, you know, for the first three or four years of the company's history, we really operated as a lab. And that was our focus. We then decided, we're trying to connect a fantastic team with differentiated technology to the right market timing. And when we saw all these pain points around how fast the adoption of containers and Kubernetes have taken place but the pain that the developers are running into, we actually found for ourselves that this was the perfect use case. >> So how specifically does Optimize Live work? Can you add a little detail on that? >> Yes, so when you... Many organizations today have an existing monitoring APM observability suite really in place. They've also got a metric source. So this could be something like Datadog or Prometheus. And once that data starts flowing, there's an out of the box or kind of a piece of Kubernetes that ships with it called the VPA or the Vertical Pod Autoscaler. And less than, really than 1% of Kubernetes users take advantage of the VPA mostly because it's really challenging to configure and it's not super compatible with the the tool set or, you know, the ecosystem of tools in a Kubernetes environment. And so our biggest competitor is the VPA. And what's happening in this environment or in this world for developers is they're having to make decisions on a number of different metrics or resource elements typically things like memory and CPU. And they have to decide what are the requests I'm going to allow application and what are the limits? So what are those thresholds that I'm going to be okay with so that I can, again, try to hit my business objectives and keep in line with my SLAs? And to your earlier point in the intro, it's often guesswork. You know, they either have to rely on out of the box recommendations that ship with the databases and other services that they are using or it's a super manual process to go through and try to configure and tune this. And so with Optimize Live, we're making that one click. And so we're continuously and consistently observing and watching the data that's flowing through these tools and we're serving back recommendations for the user. They can choose to let those recommendations automatically patch and deploy or they can retain some semblance of control over are the recommendations and manually deploy them into their environment themselves. And we, again, really believe that the user knows their application. They know the goals that they have and we don't. But we have a system that's smart enough to align with the business objectives and ultimately provide the relevant recommendations at that point. >> So the business objectives are an input from the application team? >> Yep. >> And then your system is smart enough to adapt and address those. >> Application over application, right? And so the thresholds in any given organization across their different ecosystem of apps or environment could be different. The business objectives could be different. And so we don't want to predefine that for people. We want to give them the opportunity to build those thresholds in and then allow the machine learning to learn and to send recommendations within those bounds. >> And we're going to hear later from a customer who's hosting a Drupal, one of the largest Drupal hosts. So it's all do it yourself across thousands of customers so it's, you know, very unpredictable. I want to make something clear though as to where you fit in the ecosystem. You're not an observability platform, you leverage observability platforms, right? So talk about that and where you fit into the ecosystem. >> Yeah, so it's a great point. We're also, you know, a series B startup and growing. We've the choice to be very intentionally focused on the problems that we've solve. And we've chosen to partner or integrate otherwise. And so we do get put into the APM category from time to time. We are really an intelligence platform. And that intelligence and insights that we're able to draw is because of the core machine learning we've built over the years. And we also don't want organizations or users to have to switch from tools and investments that they've already made. And so we were never going to catch up to to Datadog or Dynatrace or Splunk or AppDynamics or some of the other. And we're totally fine with that. They've got great market share and penetration. They do solve real problems. Instead, we felt like users would want a seamless integration into the tools they're already using. And so we view ourselves as kind of the Intel inside for that kind of a scenario. And it takes observability and APM data and insights that were somewhat reactive. They're visualized and somewhat reactive. And we add that proactive nature onto it, the insights and ultimately the appropriate level of automation. >> So when I think, Matt, about cloud native and I go back to the sort of origins of CNCF who's a, you know, handful of companies. And now you look at the participants it'll, you know, make your eyes bleed. How do you address dealing with all those companies and what is the partnership strategy? >> Yeah, it's so interesting because it's just that even that CNCF landscape has exploded. It was not too long ago where it was as small or smaller than the FinOps landscape today which by the way, the FinOps piece is also on a a neck breaking, you know, growth curve. We, I do see, although there are a lot of companies and a lot of tools, we're starting to see a significant amount of consistency or hardening of the tool chain, you know, with our customers and users. And so we've made strategic and intentional decisions on deep partnerships in some cases like OEM uses of our technology and certainly, you know, intelligent and seamless integrations into a few. So, you know, we'll be announcing a really exciting partnership with AWS and that specifically what they're doing with EKS, their Kubernetes distribution and services. We've got a deep partnership and integration with Datadog and then with Prometheus and specifically a few other cloud providers that are operating, manage Prometheus environments. >> Okay, so where do you want to take this thing? You're not taking the observability guys head on, smart move. So many of those even entering the market now. But what is the vision? >> Yeah, so we've had this debate a lot as well 'cause it's super difficult to create a category. You know, on one hand, you know, I have a lot of respect for founders and companies that do that. On the other hand from a market timing standpoint, you know we fit into AIOps, that's really where we fit. You know, we've made a bet on the future of Kubernetes and what that's going to look like. And so from a containers and Kubernetes standpoint, that's our bet. But we're an AIOps platform. You know, we'll continue getting better at the problems we solve with machine learning and we'll continue adding data inputs. So we'll go, you know, we'll go beyond the application layer which is really where we play now. We'll add, you know, kind of whole cluster optimization capabilities across the full stack. And the way we will get there is by continuing to add different data inputs that make sense across the different layers of the stack. And it's exciting. We can stay vertically oriented on the problems that we're really good at solving but we can become more applicable and compatible over time. >> So that's your next concentric circle. As the observability vendors expand their observation space, you can just play right into that. >> Yeah. >> The more data you get because your purpose built to solving these types of problems. >> Yeah, so you can imagine a world right now out of observability, we're taking things like telemetry data pretty quickly. You can imagine a world where we take traces and logs and other data inputs as that ecosystem continues to grow, it just feeds our own, you know, we are reliant on data. >> Excellent, Matt, thank you so much. >> Thanks for having me. >> Appreciate for coming on. Okay, keep it right there in a moment. We're going to hear from a customer with a highly diverse and constantly changing environment that I mentioned earlier. They went through a major replatforming with Kubernetes on AWS. You're watching theCUBE, you are leader in enterprise tech coverage. (bright upbeat music)

Published Date : Feb 23 2022

SUMMARY :

and CEO of StormForge. Good to see you. Yeah, so we saw you guys at a KubeCon that empowers developers into the process You had launch coming to and the associated optimizations And I used to ask, you know, And Kubernetes is more of And so that's the entire So I want you to sort And so, you know, for the And so our biggest competitor is the VPA. is smart enough to adapt And so the thresholds in as to where you fit in the ecosystem. We've the choice to be and I go back to the or hardening of the tool chain, you know, Okay, so where do you And the way we will get there As the observability vendors to solving these types of problems. as that ecosystem continues to grow, and constantly changing environment

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Matt Provo, StormForge


 

(upbeat music) >> The adoption of container orchestration platforms is accelerating at a rate as fast or faster than any category in enterprise IT. Survey data from enterprise technology research shows Kubernetes specifically, leads the pack into both spending velocity and market share. Now like virtualization in its early days, containers bring many new performance and tuning challenges, in particular ensuring consistent and predictable application performance is tricky especially because containers they're so flexible and they enable portability, things are constantly changing. DevOps Pros have to wade through a sea of observability data and tuning the environment becomes a continuous exercise of trial and error. This endless cycle taxes resources and kills operational efficiency. So teams often just capitulate and simply dial up and throw unnecessary resources at the problem. StormForge is a company founded mid last decade that is attacking these issues with a combination of machine learning and data analysis. And with me to talk about a new offering that directly addresses these concerns is Matt Provo, founder and CEO of StormForge. Matt, welcome to The CUBE. Good to see you. >> Good to see you. Thanks for having me. >> Yeah. So we saw you guys at CUBE con, sort of first introduce you to our community, but add a little color to my intro there if you want. >> Well, you semi stole my thunder, but I'm okay with that. Absolutely agree with everything you said in the intro. The problem that we have set out to solve, which is tailor made for the use of real machine learning, not machine learning kind of as a marketing tag is connected to how workloads on Kubernetes are really managed from a resource efficiency standpoint. And so a number of years ago, we built the core machine learning engine and have now turned that into a platform around how Kubernetes resources are managed at scale. And so organizations today, as they're moving more workloads over, sort of drink the cool-Aid of the flexibility that comes with Kubernetes and how many knobs you can turn and developers in many ways love it. Once they start to operationalize use of Kubernetes and move workloads from pre-production into production, they run into a pretty significant complexity wall. And this is where StormForge comes in to try to help them manage those resources more effectively and ensuring and implementing the right kind of automation that empowers developers into the process, ultimately does not automate them out of it. >> So you've got news, you a hard launch coming to further address these problems. Tell us about that. >> Yeah. So historically, like any machine learning engine, we think about data inputs and what kind of data is going to feed our system to be able to draw the appropriate insights out for the user. And so historically we've kind of been single threaded on load and performance tests in a pre-production environment. And there's been a lot of adoption of that, a lot of excitement around it and frankly, amazing results. My vision has been for us to be able to close the loop, however, between data coming out of pre-production and the associated optimizations and data coming out of production environment and our ability to optimize that. A lot of our users along the way have said, these results in pre-production are fantastic. How do I know they reflect reality of what my application is going to experience in a production environment? And so we're super excited to announce, kind of the second core module for our platform called optimized live. The data input for that is observability and telemetry data coming out of APM platforms and other data sources. >> So this is like Nirvana. So I wonder if we could talk a little bit more about the challenges that this addresses. I mean, I've been around a while and it really have observed, and I used to ask technology companies all the time. Okay. So you're telling me beforehand what the optimal configuration should be and resource allocation, what happens if something changes? And then it's always, always a pause. And Kubernetes is more of a rapidly changing environment than anything we've ever seen. So this is specifically the problem you're addressing, maybe talk about that a little bit more. >> Yeah. So we view what happens in pre-production as sort of the experimentation phase. And our machine learning is is allowing the user to experiment and scenario plan. What we're doing with optimized live and adding the production piece is what we kind of also call, kind of our observation phase. And so you need to be able to run the appropriate checks and balances between those two environments to ensure that what you're actually deploying and monitoring from an application performance, from a cost standpoint is aligning with your SLOs and your SLAs, as well as your business objectives. And so that's the entire point of this edition, is to allow our users to experience, hopefully the the Nirvana associated with that, because it's an exciting opportunity for them and really something that nobody else is doing from the standpoint of closing that loop. >> So you said up front, machine learning not as a marketing tag. So I want you to sort of double click on that. What's different than how other companies approach this problem? >> Yeah. I mean, part of it is a bias for me and a frustration as a founder of the reason I started the company in the first place. I think machine learning or AI gets tagged to a lot of stuff. It's very buzz wordy, it looks good. I'm fortunate to have found a number of folks from the outset of the company with PhDs and applied mathematics and a focus on actually building real AI at the core that is connected to solving the right kind of actual business problems. And so for the first three or four years of the company's history, we really operated as a lab. And that was our focus. We then decided, we're trying to connect a fantastic team with differentiated technology to the right market timing. And when we saw all these pain points around, how fast the adoption of containers and Kubernetes have taken place, but the pain that developers are running into, we actually found for ourselves that this was the perfect use case. >> So how specifically does optimize live work? Can you add a little detail on that? >> Yeah. So when you... Many organizations today have an existing monitoring APM, observability suite really in place, they've also got a metric source. So this could be something like Datadog, or Prometheus. And once that data starts flowing there's an out of the box or kind of a piece of Kubernetes that ships with it called the VPA or the vertical pod auto scaler. And less than, really less than 1% of Kubernetes users take advantage of of the VPA, mostly because it's really challenging to configure and it's not super compatible with the tool set or the ecosystem of tools in a Kubernetes environment. And so our biggest competitor is the VPA. And what's happening in this world for developers is they're having to make decisions on a number of different metrics or resource elements, typically things like memory and CPU, and they have to decide, what are the requests I'm going to allow for this application and what are the limits? So what are those thresholds that I'm going to be okay with? So that I can, again, try to hit my business objectives and keep in line with my SLAs. And to your earlier point in the intro, it's often guesswork. They either have to rely on out of the box recommendations that ship with the databases and other services that they are using, or it's a super manual process to go through and try to configure and tune this. And so with optimized live, we're making that one click. And so we're continuously and consistently observing and watching the data that's flowing through these tools and we're serving back recommendations for the user. They can choose to let those recommendations automatically patch and deploy, or they can retain some semblance of control over the recommendations and manually deploy them into their environment themselves. And we, again, really believe that the user knows their application. They know the goals that they have, we don't, but we have a system that's smart enough to align with the business objectives and ultimately provide the relevant recommendations at that point. >> So the business objectives are an input from the application team. And then your system is smart enough to a adapt and address those? >> Application over application. And so the thresholds in any given organization across their different ecosystem of apps or environment could be different. The business objectives could be different. And so we don't want to predefine that for people. We want to give them the opportunity to build those thresholds in and then allow the machine learning to learn and to send recommendations within those bounds. >> And we're going to hear later from a customer who's hosting a Drupal, one of the largest Drupal hosts. So it's all do it yourself across that of customers. So it's very unpredictable. I want to make something clear though. As to where you fit in the ecosystem, you're not an observability platform, you leverage observability platforms. So talk about that and where you fit in into the ecosystem. >> Yeah. So this is a great point. We're also a series B startup and growing where we've the choice to be very intentionally focused on the problems that we've solve and we've chosen to partner or integrate otherwise. And so we do get put into the APM category from time to time. We are really an intelligence platform and that intelligence and insights that we're able to draw is because of the core machine learning we've built over the years. And we also don't want organizations or users to have to switch from tools and investments that they've already made. And so we were never going to catch up to Datadog or Dynatrace or Splunk or UpDynamics or some of the other. And we're totally fine with that. They've got great market share and penetration. They do solve real problems. Instead, we felt like users would want a seamless integration into the tools they're already using. And so we view ourselves as kind of the Intel inside for that kind of a scenario. And it takes observability and APM data and insights that were somewhat reactive, they're visualized and somewhat reactive and we make those, we add that proactive nature onto it, the insights and ultimately the appropriate level of automation. >> So when I think Matt about cloud native and I go back to the sort of origins of CNCF, it was a handful of companies, and now you look at the participants make your eyes bleed. How do you address dealing with all those companies and what's the partnership strategy? >> Yeah, it's so interesting because, just that even that CNCF landscape has exploded. It was not too long ago where it was as small or smaller than the Finops landscape today, which by the way, the Finops piece is also on a neck breaking growth curve. I do see, although there are a lot of companies and a lot of tools, we're starting to see a significant amount of consistency or hardening of the tool chain with our customers and users. And so we've made strategic and intentional decisions on deep partnerships, in some cases like OEM, uses of our technology and certainly, intelligent and seamless integrations into a few. So we'll be announcing a really exciting partnership with AWS and that specifically what they're doing with EKS, their Kubernetes distribution and services. We've got a deep partnership and integration with Datadog and then with Prometheus, and specifically a few other cloud providers that are operating manage Prometheus environments. >> Okay. So where do you want to take this thing? You're not taking the observability guys head on, smart move. So many of those even entering the market now. But what is the vision? >> Yeah. So we've had this debate a lot as well 'cause it's super difficult to create a category. On one hand, I have a lot of respect for founders and companies that do that, on the other hand, from a market timing standpoint, we fit into AI Ops, that's really where we fit. We've made a bet on the future of Kubernetes and what that's going to look like. And so from a containers and Kubernetes standpoint that's our bet, but we're an AI Ops platform, we'll continue getting better at the problems we solve with machine learning and we'll continue adding data inputs. So we'll go beyond the application layer, which is really where we play now. We'll add kind of whole cluster optimization capabilities across the full stack. And the way we will get there is by continuing to add different data inputs that make sense across the different layers of the stack. And it's exciting. We can stay vertically oriented on the problems that we're really good at solving but we can become more applicable and compatible over time. >> So that's your next concentric circle. As the observability vendors expand their observation space, you can just play right into that? More data you get because your purpose built to solving these types of problems. >> Yeah. So you can imagine a world right now out of observability, we're taking things like telemetry data. Pretty quickly you can imagine a world where we take traces and logs and other data inputs as that ecosystem continues to grow. It just feeds our own, we are reliant on data. >> Excellent. Matt, thank you so much. Appreciate you coming on. >> Thanks for having me. >> Okay. Keep it right there. In a moment, we're going to hear from a customer with a highly diverse and constantly changing environment that I mentioned earlier. They went through a major replatforming with Kubernetes on AWS. You're watching The CUBE, your leader in enterprise tech coverage. (upbeat music)

Published Date : Feb 9 2022

SUMMARY :

And with me to talk about a new offering Good to see you. but add a little color to that empowers developers into the process, to further address these problems. and the associated optimizations And Kubernetes is more of a And so that's the entire So I want you to sort And so for the first three or four years And so our biggest competitor is the VPA. So the business objectives are an input And so the thresholds in of the largest Drupal hosts. is because of the core machine learning and I go back to the and that specifically what So many of those even And the way we will get there As the observability vendors as that ecosystem continues to grow. Matt, thank you so much. to hear from a customer

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Matt Provo | ** Do not make public **


 

(bright upbeat music) >> The adoption of container orchestration platforms is accelerating at a rate as fast or faster than any category in enterprise IT. Survey data from Enterprise Technology Research shows Kubernetes specifically leads the pack in both spending velocity and market share. Now like virtualization in its early days, containers bring many new performance and tuning challenges. In particular, ensuring consistent and predictable application performance is tricky especially because containers they're so flexible and the enabled portability things are constantly changing. DevOps pros have to wade through a sea of observability data and tuning the environment becomes a continuous exercise of trial and error. This endless cycle taxes, resources, and kills operational efficiencies so teams often just capitulate and simply dial up and throw unnecessary resources at the problem. StormForge is a company founded in mid last decade that is attacking these issues with a combination of machine learning and data analysis. And with me to talk about a new offering that directly addresses these concerns, is Matt Provo, founder and CEO of StormForge. Matt, welcome to thecube. Good to see you. >> Good to see you, thanks for having me. >> Yeah. So we saw you guys at CubeCon, sort of first introduce you to our community but add a little color to my intro if you will. >> Yeah, well you semi stole my thunder but I'm okay with that. Absolutely agree with everything you said in the intro. You know, the problem that we have set out to solve which is tailor made for the use of real machine learning not machine learning kind of as a marketing tag is connected to how workloads on Kubernetes are really managed from a resource efficiency standpoint. And so a number of years ago we built the core machine learning engine and have now turned that into a platform around how Kubernetes resources are managed at scale. And so organizations today as they're moving more workloads over sort of drink the Kool-Aid of the flexibility that comes with Kubernetes and how many knobs you can turn and developers in many ways love it. Once they start to operationalize the use of Kubernetes and move workloads from pre-production into production, they run into a pretty significant complexity wall. And this is where StormForge comes in to try to help them manage those resources more effectively in ensuring and implementing the right kind of automation that empowers developers into the process ultimately does not automate them out of it. >> So you've got news, your hard launch coming in to further address these problems. Tell us about that. >> Yeah so historically, you know, like any machine learning engine, we think about data inputs and what kind of data is going to feed our system to be able to draw the appropriate insights out for the user. And so historically we are, we've kind of been single-threaded on load and performance tests in a pre-production environment. And there's been a lot of adoption of that, a lot of excitement around it and frankly, amazing results. My vision has been for us to be able to close the loop however between data coming out of pre-production and the associated optimizations and data coming out of production, a production environment, and our ability to optimize that. A lot of our users along the way have said these results in pre-production are fantastic. How do I know they reflect reality of what my application is going to experience in a production environment? And so we're super excited to announce kind of the second core module for our platform called Optimize Live. The data input for that is observability and telemetry data coming out of APM platforms and other data sources. >> So this is like Nirvana. So I wonder if we could talk a little bit more about the challenges that this addresses. I mean, I've been around a while and it really have observed and I used to ask technology companies all the time, okay, so you're telling me beforehand what the optimal configuration should be in resource allocation, what happens if something changes? And then it's always a pause. And Kubernetes is more of a rapidly changing environment than anything we've ever seen. So this is specifically the problem you're addressing. Maybe talk about that a little bit. >> Yeah so we view what happens in pre-production as sort of the experimentation phase and our machine learning is allowing the user to experiment and scenario plan. What we're doing with Optimize Live and adding the production piece is what we kind of also call kind of our observation phase. And so you need to be able to run the appropriate checks and balances between those two environments to ensure that what you're actually deploying and monitoring from an application performance, from a cost standpoint, is aligning with your SLOs and your SLAs as well as your business objectives. And so that's the entire point of this addition is to allow our users to experience hopefully the Nirvana associated with that because it's an exciting opportunity for them and really something that nobody else is doing from the standpoint of closing that loop. >> So you said upfront machine learning not as a marketing tag. So I want you to sort of double click on that. What's different than how other companies approach this problem? >> Yeah I mean, part of it is a bias for me and a frustration as a founder of the reason I started the company in the first place. I think machine learning our AI gets tagged to a lot of stuff. It's very buzzwordy, it looks good. I'm fortunate to have found a number of folks from the outset of the company with, you know, PhDs in Applied Mathematics and a focus on actually building real AI at the core that is connected to solving the right kind of actual business problems. And so, you know, for the first three or four years of the company's history, we really operated as a lab and that was our focus. We then decided we're trying to connect a fantastic team with differentiated technology to the right market timing. And when we saw all of these pain points around how fast the adoption of containers and Kubernetes have taken place but the pain that the developers are running into, we found it, we actually found for ourselves that this was the perfect use case. >> So how specifically does Optimize Live work? Can you add a little detail on that? >> Yeah so when you, many organizations today have an existing monitoring APM observability suite really in place. They've also got, they've also got a metric source, so this could be something like Datadog or Prometheus. And once that data starts flowing, there's an out of the box or kind of a piece of Kubernetes that ships with it called the VPA or the Vertical Pod Autoscaler. And less than really less than 1% of Kubernetes users take advantage of the VPA mostly because it's really challenging to configure and it's not super compatible with the tool set or the, you know, the ecosystem of tools in a Kubernetes environment. And so our biggest competitor is the VPA. And what's happening in this environment or in this world for developers is they're having to make decisions on a number of different metrics or resource elements typically things like memory and CPU. And they have to decide what are the, what are the requests I'm going to allow for this application and what are the limits? So what are those thresholds that I'm going to be okay with? So that I can again try to hit my business objectives and keep in line with my SLAs. And to your earlier point in the intro, it's often guesswork. You know, they either have to rely on out of the box recommendations that ship with the databases and other services that they are using or it's a super manual process to go through and try to configure and tune this. And so with Optimize Live, we're making that one-click. And so we're continuously and consistently observing and watching the data that's flowing through these tools and we're serving back recommendations for the user. They can choose to let those recommendations automatically patch and deploy or they can retain some semblance of control over the recommendations and manually deploy them into their environment themselves. And we again, really believe that the user knows their application, they know the goals that they have, we don't. But we have a system that's smart enough to align with the business objectives and ultimately provide the relevant recommendations at that point. >> So the business objectives are an input from the application team and then your system is smart enough to adapt and adjust those. >> Application over application, right? And so the thresholds in any given organization across their different ecosystem of apps or environment could be different. The business objectives could be different. And so we don't want to predefine that for people. We want to give them the opportunity to build those thresholds in and then allow the machine learning to learn and to send recommendations within those bounds. >> And we're going to hear later from a customer who is hosting a Drupal, one of the largest Drupal host, is it? So it's all do it yourself across thousands of customers so it's very unpredictable. I want to make something clear though, as to where you fit in the ecosystem. You're not an observability platform, you leverage observability platforms, right? So talk about that and where you fit in into the ecosystem. >> Yeah so it's a great point. We, we're also you know, a series B startup and growing. We've made the choice to be very intentionally focused on the problems that we've solve and we've chosen to partner or integrate otherwise. And so we do get put into the APM category from time to time. We're really an intelligence platform. And that intelligence and insights that we're able to draw is because we, because of the core machine learning we've built over the years. And we also don't want organizations or users to have to switch from tools and investments that they've already made. And so we were never going to catch up to Datadog or Dynatrace or Splunk or AppDynamics or some of the other, and we're totally fine with that. They've got great market share and penetration and they do solve real problems. Instead, we felt like users would want a seamless integration into the tools they're already using. And so we view ourselves as kind of the Intel inside for that kind of a scenario. And it takes observability and APM data and insights that were somewhat reactive, they're visualized and somewhat reactive and we make those, we add that proactive nature onto it, the insights and ultimately the appropriate level of automation. >> So when I think Matt about cloud native and I go back to the sort of origins of CNCF, it was a, you know, handful of companies, and now you look at the participants, you know, make your eyes bleed. How do you address dealing with all those companies and what's the partnership strategy? >> Yeah it's so interesting because it's just that even at CNCF landscape has exploded. It was not too long ago where it was as smaller than the finOps Landscape today which by the way the FinOps pieces is also on a neck breaking, you know, growth curve. We, I do see although there are a lot of companies and a lot of tools, we're starting to see a significant amount of consistency or hardening of the tool chain with our customers and users. And so we've made strategic and intentional decisions on deep partnerships in some cases like OEM users of our technology and certainly, you know, intelligent and seamless integrations into a few. So, you know, we'll be announcing a really exciting partnership with AWS and specifically what they're doing with EKS, their Kubernetes distribution and services. We've got a deep partnership and integration with Datadog and then with Prometheus and specifically cloud provider, a few other cloud providers that are operating manage Prometheus environments. >> Okay so where do you want to take this thing? If it's not, you're not taking the observability guys head on, smart move, so many of those even entering the market now, but what is the vision? >> Yeah so we've had this debate a lot as well because it's super difficult to create a category. You know, on one hand, I have a lot of respect for founders and companies that do that, on the other hand from a market timing standpoint, you know, we fit into AIOps. That's really where we fit. You know we are, we've made a bet on the future of Kubernetes and what that's going to look like. And so from a containers and Kubernetes standpoint that's our bet. But we're an AIOps platform, we'll continue getting better at what, at the problems we solve with machine learning and we'll continue adding data inputs so we'll go beyond the application layer which is really where we play now. We'll add kind of whole cluster optimization capabilities across the full stack. And the way we'll get there is by continuing to add different data inputs that make sense across the different layers of the stack and it's exciting. We can stay vertically oriented on the problems that we're really good at solving but we become more applicable and compatible over time. >> So that's your next concentric circle. As the observability vendors expand their observation space you can just play right into that. The more data you get could be because you're purpose built to solving these types of problems. >> Yeah so you can imagine a world right now out of observability, we're taking things like telemetry data pretty quickly. You can imagine a world where we take traces and logs and other data inputs as that ecosystem continues to grow, it just feeds our own, you know, we are reliant on data. So. >> Excellent. Matt, thank you so much. Thanks for hoping on. >> Yeah, appreciate it. >> Okay. Keep it right there. In a moment, We're going to hear from a customer with a highly diverse and constantly changing environment that I mentioned earlier, they went through a major re-platforming with Kubernetes on AWS. You're watching theCube, your a leader in enterprise tech coverage. (bright music)

Published Date : Jan 27 2022

SUMMARY :

and the enabled portability to my intro if you will. and how many knobs you can turn to further address these problems. and the associated optimizations about the challenges that this addresses. And so that's the entire So I want you to sort and that was our focus. And so our biggest competitor is the VPA. So the business objectives are an input And so the thresholds in as to where you fit in the ecosystem. We've made the choice to be and I go back to the and certainly, you know, And the way we'll get there As the observability vendors and other data inputs as that Matt, thank you so much. We're going to hear from a customer

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Sandeep Lahane and Shyam Krishnaswamy | KubeCon + CloudNative Con NA 2021


 

>>Okay, welcome back everyone. To the cubes coverage here, coop con cloud native con 2021 in person. The Cuba's here. I'm John farrier hosted the queue with Dave Nicholson, my cohost and cloud analyst, man. It's great to be back, uh, in person. We also have a hybrid event. We've got two great guests here, the founders of deep fence, sham, Krista Swami, C co-founder and CTO, and said deep line founder. It's great to have you on. This is a super important topic. As cloud native is crossed over. Everyone's talking about it mainstream, blah, blah, blah. But security is driving the agenda. You guys are in the middle of it. Cutting edge approach and news >>Like, like we were talking about John, we had operating at the intersection of the awesome desk, right? Open source security and cloud cloud native, essentially. Absolutely. And today's a super exciting day for us. We're launching something called track pepper, Apache V2, completely open source. Think of it as an x-ray or MRI scan for your cloud scan, you know, visualize this cloud at scale, all of the modalities, essentially, we look at cloud as a continuum. It's not a single modality it's containers. It's communities, it's William to settle we'll list all of them. Co-exist side by side. That's how we look at it and threat map. It essentially allows you to visualize all of this in real time, think of fed map, but as something that you, that, that takes over the Baton from the CIS unit, when the lift shift left gets over, that's when the threat pepper comes into picture. So yeah, super excited. >>It's like really gives that developer and the teams ops teams visibility into kind of health statistics of the cloud. But also, as you said, it's not just software mechanisms. The cloud is evolving, new sources being turned on and off. No one even knows what's going on. Sometimes this is a really hidden problem, right? Yeah, >>Absolutely. The basic problem is, I mean, I would just talk to, you know, a gentleman 70 of this morning is two 70 billion. Plus public cloud spent John two 70 billion plus even 3 billion, 30 billion they're saying right. Uh, projected revenue. And there is not even a single community tool to visualize all the clouds and all the cloud modalities at scale, let's start there. That's what we sort of decided, you know what, let's start with utilizing everything else there. And then look for known badness, which is the vulnerabilities, which still remains the biggest attack vector. >>Sure. Tell us about some of the hood. How does this all work cloud scale? Is it a cloud service managed service it's code? Take us out, take us through product. Absolutely. >>So, so, but before that, right, there's one small point that Sandeep mentioned. And Richard, I'd like to elaborate here, right? He spoke about the whole cloud spending such a large volume, right? If you look at the way people look at applications today, it's not just single clone anymore. It's multicloud multi regions across diverse plants, right? What does the solution to look at what my interests are to this point? That is a missing piece here. And that is what we're trying to tackle. And that is where we are going as open source. Coming back to your question, right? How does this whole thing work? So we have a completely on-prem model, right? Where customers can download the code today, install it. It can bill, we give binary stool and Shockley just as the exciting announcement that came out today, you're going to see somewhat exciting entrepreneurs. That's going to make a lot more easy for folks out there all day. Yeah, that's fine. >>So how does this, how does this all fit into security as a micro service and your, your vision of that? >>Absolutely. Absolutely. You know, I'll tell you, this has to do with the one of the continual conferences I would sort of when I was trying to get an idea, trying to shape the whole vision really? Right. Hey, what about syncretism? Microservice? I would go and ask people. They mentioned that sounds, that makes sense. Everything is becoming a microservice. Really. So what you're saying is you're going to deploy one more microservice, just like I deploy all of my other microservices. And that's going to look after my microservices. That compute back makes logical sense, essentially. That was the Genesis of that terminology. So defense essentially is deployed as a microservice. You go to scale, it's deployed, operated just like you to your microservices. So no code changes, no other tool chain changes. It just is yet another microservice. That's going to look after you talk about >>The, >>So there's one point I would like to add here, which is something very interesting, right? The whole concept of microservice came from, if you remember the memo from Jeff Bezos, that everybody's going to go, Microsoft would be fired. That gave rise to a very conventional unconditionally of thinking about their applications. Our deep friends, we believe that security should be. Now. You should bring the same unconventional way of thinking to security. Your security is all bottom up. No, it has to start popping up. So your applications on microservice, your security should also be a micro. >>So you need a microservice for a microservice security for the security. You're starting to get into a paradigm shift where you starting to see the API economy that bayzos and Amazon philosophy and their approach go Beanstream. So when I got to ask you, because this is a trend we've been watching and reporting on the actual application development processes, changing from the old school, you know, life cycle, software defined life cycle to now you've got machine learning and bots. You have AI. Now you have people are building apps differently. And the speed of which they want to code is high. And then other teams are slowing them down. So I've heard security teams just screw people over a couple of days. Oh my God, I can wait five days. No, it used to be five weeks. Now it's five days. They think that's progress. They want five minutes, the developers in real time. So this is a real deal optimum. >>Well, you know what? Shift left was a good thing. Instill a good thing. It helps you sort of figure out the issues early on in the development life cycle, essentially. Right? And so you started weaving in security early on and it stays with you. The problem is we are hydrating. So frequently you end up with a few hundred vulnerabilities every time you scan oftentimes few thousand and then you go to runtime and you can't really fix all these thousand one. You know? So this is where, so there is a little bit of a gap there. If you're saying, if look at the CIC cycle, the in financial cycle that they show you, right. You've got the far left, which is where you have the SAS tools, snake and all of that. And then you've got the center where, which is where you hand off this to ops. >>And then on the right side, you've got tech ops defense essentially starts in the middle and says, look, I know you've had thousand one abilities. Okay. But at run time, I see only one of those packages is loaded in memory. And only that is getting traffic. You go and fix that one because that's going to heart. You see what I'm saying? So that gap is what we're doing. So you start with the left, we come in in the middle and stay with you throughout, you know, till the whole, uh, she asks me. Yeah, well that >>Th that, that touches on a subject. What are the, what are the changes that we're seeing? What are the new threats that are associated with containerization and kind of coupled with that, look back on traditional security methods and how are our traditional security methods failing us with those new requirements that come out of the microservices and containerized world. And so, >>So having, having been at FireEye, I'll tell you I've worked on their windows products and Juniper, >>And very, very deeply involved in. >>And in fact, you know what I mean, at the company, we even sold a product to Palo Alto. So having been around the space, really, I think it's, it's, it's a, it's a foregone conclusion to say that attackers have become more sophisticated. Of course they have. Yeah. It's not a single attack vector, which gets you down anymore. It's not a script getting somewhere shooting who just sending one malicious HTP request exploiting, no, these are multi-vector multi-stage attacks. They, they evolve over time in space, you know? And then what happens is I could have shot a revolving with time and space, one notable cause of piling up. Right? And on the other side, you've got the infrastructure, which is getting fragmented. What I mean by fragmented is it's not one data center where everything would look and feel and smell similar it's containers and tuberosities and several lessons. All of that stuff is hackable, right? So you've got that big shift happening there. You've got attackers, how do you build visibility? So, in fact, initially we used to, we would go and speak with, uh, DevSecOps practitioner say, Hey, what is the coalition? Is it that you don't have enough scanners to scan? Is it that at runtime? What is the main problem? It's the lack of visibility, lack of observability throughout the life cycle, as well as through outage, it was an issue with allegation. >>And the fact that the attackers know that too, they're exploiting the fact that they can't see they're blind. And it's like, you know what? Trying to land a plane that flew yesterday and you think it's landing tomorrow. It's all like lagging. Right? Exactly. So I got to ask you, because this has comes up a lot, because remember when we're in our 11th season with the cube, and I remember conversations going back to 2010, a cloud's not secure. You know, this is before everyone realized shit, the club's better than on premises if you have it. Right. So a trend is emerged. I want to get your thoughts on this. What percentage of the hacks are because the attackers are lazier than the more sophisticated ones, because you see two buckets I'm going to get, I'm going to work hard to get this, or I'm going to go for the easy low-hanging fruit. Most people have just a setup that's just low hanging fruit for the hackers versus some sort of complex or thought through programmatic cloud system, because now is actually better if you do it. Right. So the more sophisticated the environment, the harder it is for the hackers, AK Bob wire, whatever you wanna call it, what level do we cross over? >>When does it go from the script periods to the, the, >>Katie's kind of like, okay, I want to go get the S3 bucket or whatever. There's like levels of like laziness. Yeah. Okay. I, yeah. Versus I'm really going to orchestrate Spearfish social engineer, the more sophisticated economy driven ones. Yeah. >>I think, you know what, this attackers, the hacks aren't being conducted the way they worked in the 10, five years ago, isn't saying that they been outsourced, there are sophisticated teams for building exploiters. This is the whole industry up there. Even the nation, it's an economy really. Right. So, um, the known badness or the known attacks, I think we have had tools. We have had their own tools, signature based tools, which would know, look for certain payloads and say, this is that I know it. Right. You get the stuff really starts sort of, uh, getting out of control when you have so many sort of different modalities running side by side. So much, so much moving attack surfaces, they will evolve. And you never know that you've scanned enough because you never happened because we just pushed the code. >>Yeah. So we've been covering the iron debt. Kim retired general, Keith Alexander, his company. They have this iron dome concept where there's more collective sharing. Um, how do you see that trend? Because I can almost imagine that the open-source man is going to love what you guys got. You're going to probably feed on it, like it's nobody's business, but then you start thinking, okay, we're going to be open. And you have a platform approach, not so much a tool based approach. So just give me tools. We all know that when does it, we cross over to the Nirvana of like real security sharing. Real-time telemetry data. >>And I want to answer this in two parts. The first part is really a lot of this wisdom is only in the community. It's a tribal knowledge. It's their informal feeds in from get up tickets. And you know, a lot of these things, what we're really doing with threat map, but as we are consolidating that and giving it out as a sort of platform that you can use, I like to go for free. This is the part you will never go to monetize this. And we are certain about disaster. What we are monetizing instead is you have, like I said, the x-ray or MRI scan of the cloud, which tells you what the pain points are. This is feel free. This is public collective good. This is a Patrick reader. This is for free. It's shocking. >>I took this long to get to that point, by the way, in this discussion. >>Yeah, >>This is this timing's perfect. >>Security is collective good. Right? And if you're doing open source, community-based, you know, programs like this is for the collector group. What we do look, this whole other set map is going to be open source. We going to make it a platform and our commercial version, which is called fetch Stryker, which is where we have our core IP, which is basically think about this way, right? If you figured out all the pain points and using tech map, or this was a free, and now you wanted the remedy for that pain feed to target a defense, we targeted quarantining of those statin workloads and all that stuff. And that's what our IP is. What we really do there is we said, look, you figured out the attack surface using tech fabric. Now I'm going to use threat Stryker to protect their attacks and stress >>Free. Not free to, or is that going to be Fort bang? >>Oh, that's for, okay. >>That's awesome. So you bring the goodness to the party, the goods to the party, again, share that collective, see where that goes. And the Stryker on top is how you guys monetize. >>And that's where we do some uniquely normal things. I would want to talk about that. If, if, if, if you know public probably for 30 seconds or so unique things we do in industry, which is basically being able to monitor what comes in, what goes out and what changes across time and space, because look, most of the modern attacks evolve over time and space, right? So you go to be able to see things like this. Here's a party structure, which has a vulnerability threats. Mapper told you that to strike. And what it does is it tells you a bunch of stress has a vulnerable again, know that somebody is sending a Melissa's HTP request, which has a malicious payload. And you know what, tomorrow there's a file system change. And there is outbound connection going to some funny place. That is the part that we're wanting this. >>Yeah. And you give away the tool to identify the threats and sell the hammer. >>That's giving you protection. >>Yeah. Yeah. Awesome. I love you guys love this product. I love how you're doing it. I got to ask you to define what is security as a microservice. >>So security is a microservice is a deployment modality for us. So defense, what defense has is one console. So defense is currently self posted by the customers within the infrastructure going forward. We'll also be launching a SAS version, the cloud version of it. But what happens as part of this deployment is they're running the management console, which is the gooey, and then a tiny sensor, which is collecting telemetric that is deployed as a microservice is what I'm saying. So you've got 10 containers running defenses level of container. That's, that's an eight or the Microsoft risk. And it utilizes, uh, EDP F you know, for tracing and all that stuff. Yeah. >>Awesome. Well, I think this is the beginning of a shift in the industry. You start to see dev ops and cloud native technologies become the operating model, not just dev dev ops are now in play and infrastructure as code, which is the ethos of a cloud generation is security is code. That's true. That's what you guys are doing. Thanks for coming on. Really appreciate it. Absolutely breaking news here in the queue, obviously great stuff. Open source continues to grow and win in the new model. Collaboration is the cube bringing you all the cover day one, the three days. I'm Jennifer, your host with Dave Nicholson. Thanks for watching.

Published Date : Oct 13 2021

SUMMARY :

It's great to have you on. It essentially allows you to visualize all of this in real time, think of fed map, but as something that you, It's like really gives that developer and the teams ops teams visibility into That's what we sort of decided, you know what, let's start with utilizing everything else there. How does this all work cloud scale? the solution to look at what my interests are to this point? That's going to look after you talk about came from, if you remember the memo from Jeff Bezos, that everybody's going to go, Microsoft would be fired. So you need a microservice for a microservice security for the security. You've got the far left, which is where you have the SAS So you start with the left, we come in in the middle and stay with you throughout, What are the new threats that are associated with containerization and kind And in fact, you know what I mean, at the company, we even sold a product to Palo Alto. the environment, the harder it is for the hackers, AK Bob wire, whatever you wanna call it, what level the more sophisticated economy driven ones. And you never know that you've scanned enough because Because I can almost imagine that the open-source man is going to love what you guys got. This is the part you will never go to monetize this. What we really do there is we said, look, you figured out the attack surface using tech And the Stryker on top is how you guys monetize. And what it does is it tells you a bunch of stress has a vulnerable I got to ask you to define what is security as a microservice. And it utilizes, uh, EDP F you know, for tracing and all that stuff. Collaboration is the cube bringing you all the cover day one, the three days.

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Erez Berkner, Lumigo | CUBE Conversation


 

(bouncy music) >> Welcome to this Cube Conversation, I'm Lisa Martin. I'm joined by Erez Berkner, the CEO and co-founder of lumigo. Erez, welcome to the program. >> Hey Lisa, thank you for having me. Glad to be here. >> Excellent, we're going to have a great conversation. We're going to be talking about the growing trend of using cloud native and serverless. But before we do, Erez, give our audience an overview of lumigo. >> Excellent, so lumigo is an observability platform. Basically allowing developer, architects, the technology person in the organization to understand what's going on with his modern cloud, with his serverless, with his cloud native application. So at the end of the day, lumigo as assess platform, allow you to know what's happening, get visibility, and be able to get to the root cause of issues, many times before they actually hit your production. >> I saw on your website, in terms of speed, getting up and running quickly, in four minutes with four clicks. Tell me how developers do this that quickly. >> Yeah, that's actually great point. Because in general, when we talk about the modern cloud, people are really fed up with deploying agents, long processes of servers, and more and more we see the trend towards APIs, toward code libraries. At the end of the day, at the heart of lumigo, we built a very strong automation engine based on APIs, based on lomdalier integration. And this allows a developer to basically connect lumigo via the APIs in couple of clicks. Doesn't require code changes, deployment of agents, deployment of services. And this is why it's so fast, because it's lightweight. And that's a trend of managed services, of serverless, and lumigo is another stone in that wall. >> Excellent, lightweight, key there. Define serverless, what is considered serverless? >> Mmm, ooh, don't get me involved in dispute of those definitions. But I can share my view, but this is a.. Anyone, I would say, have his own definition. But the main concept with serverless is at the end of the day, really, like it says, serverless. You don't deploy a server. You don't rent a server, you don't manage a server, you don't deploy an operating system, you don't patch a server. You don't take care of scalability, of high visibility. Basically, all the chores of managing, of maintaining a server, basically go away. Now, they don't really go away. Somebody else is dealing with them. So there is a server, but it's not your server to manage. And that someone is a cloud provider, is Amazon, is Microsoft, is Google, it's IBM. And this is how I view serverless. Basically, a managed service that doesn't require to deploy or manage a server, and you use it via APIs. And if you think about that, in the past when serverless started, 2015, serverless was function as a service, Lambda, AWS started that. But today, in 2021, serverless, yeah, it's function as a service, it's Lambda, but it's also storage as a service, like S3, and data as a service, like Snowflake, like DynamoDB. And queue as a service like SNS, like EventBridge, like Kenesis. And even Stripe, payment a as service, and Twilio, and SendGrid. So all these API based services, that you just consume, and they're like Lego pieces that you connect together and you just connect and you go, and you start working and they up and running, this is how I define serverless today. And that's basically allowing you to run any application today with zero servers. >> That's a great definition, that nice and clean, and I think the Lego bricks really kind of clicked in my mind when you talked about that. Let's talk now about for business critical production applications, what are you seeing in terms of adoption of serverless for those cases? >> That's a great question, because I think that we are in a critical point of time, in cloud native, in modern cloud, in serverless market. And I think it's an evolution. You know, when we started, again, back in 2015, serverless was just one or two services. But we got to a critical mass of services, including DynamoDB and S3 and Lambda and EventBridge and all the other services, that step function, that basically allow you to build your application based on serverless. And this critical point of the architecture of serverless being mature enough, being wide enough, to allow you to do what you want, to have the confidence running serverless in production, to know that you have the tooling that you used to have in the past to monitor, to debug, to secure, to understand cost, all of this are really coming together this year. We actually see this year, and a bit of end of last year, but this is what's driving a trend in the industry. I think it's still not known enough to many of the organizations, or not wide enough, or not public enough. But our customers are focused on cloud native and serverless. And we've seen a dramatic change in the last six months. And the main change is organizations that used to play around with serverless, that used to do non-business critical usage of serverless, because it's easy, because it makes sense, because it's fast, all of a sudden they got the confidence to do that with their business critical application in production. And this is a shift that we're seeing. And that goes many times with the technology maturity. You start, you play around with something, it makes sense, it makes sense, you get confidence, and boom! This become more and more mainstream technology. And we're at the verge of that. >> In terms of a catalyst for that confidence, do you think that the events, the world events of the last 12 months and this acceleration of digital transformation, has that played any part in the maturation of the technology that's giving customers the confidence to adopt serverless? >> Yeah, I think it's fascinating, what we're seeing. Because I think the last event really push a organization to innovate. Because of different reason, because they don't have the head count, so they need to reduce the maintenance that they do, they need to reduce the developer head count, the DevOps head count, they need to reduce costs. Serverless is running only when it need to run, so you pay only for what you use. So this is another method that our customer, for example, reduce their cost. So I think beyond the maturity of the architecture, the push forward for optimization, for lower usage or lower usage of engineering force, really pushed serverless forward. And this paradigm, once it worked for one team, it's viral. It's viral with in organization and the cross-organization. So this team managed to reduce 50% of the cost, and 70% of the developers that need to maintain the production. Let's duplicate that. And let's do that four times, and five times, and 10 times. And this is the point in time that we are. So that's a trend and I think it's very much impacted by the world economics. >> Interesting, that trend of virality. Let's dig into, you mentioned a couple of benefits. I heard reduction in total cost of ownership, or costs. Talk to me about the lumigo solution, the technology, and what some of those key benefits are that it is consistently delivering to your customers. >> So I think the basic is that serverless makes a lot of sense, economical, maintenance. That's why the cloud providers are putting so much effort and power in delivering more and more serverless maturity. One of the challenges that we see for almost any organization adopting the new technology, it goes back to we understand the values, but at the end of the day I need to make sure that if something goes wrong in production, I will know about it and I will know how to react and fix it in a matter of minutes. 'Cause that's my service, that's my business. And I know how to do it in a server world, where there's one server or three servers, and everything running in the same server. I have the tools for that. And I want to go serverless, I want to go cloud native, but all of a sudden there are dozens of services that I consume via APIs and they're a part of a bigger picture of my application. So I'm lacking many times the confidence, the tools, the awareness of, something goes wrong, I'll know about it, and I'll be able to fix it. And this is where lumigo comes in. So we built lumigo from the ground up to be very much focused on the modern cloud, on serverless. And that means two main things that we provide for our customers. One is, I would say one thing. We provide confidence. You can use serverless in production, and you can rest assured that if something goes wrong, you will be the one alerting and we'll give you all the information to debug it. And we do it by two main things. One is the visibility that we create. Because we're connected to the environment, we alert on things that are relevant to serverless. It's not about CPU, it's not about a iO. It's about concurrency limits, it's about cold start, it's about time outs, it's about reaching duration limits. These are the things that we know to alert you about. It's very specific to the serverless services. And it's not a generic metric, it's serverless metric. So that's number one, visibility, getting alert whenever something is about to go wrong. But what do you do then? Let's say I have one million invocations a day, and one of them is actually, I have a trigger, something went wrong. And this is where lumigo allow the developers to debug. Basically, you click on a specific issue, and lumigo tell you the entire story of what happened, from the very beginning, an API gateway triggering a Lambda, right into DynamoDB, triggering an Lambda, it tell you the entire story end to end of what happened with that specific request, with inputs, with outputs, with environment variables. All the things the developer need in order to debug, to find the root cause, and then fix it in matter of minutes. And that's the game-changer that allow those organizations to run serverless with confidence. >> You talk about confidence, it's a word that I hear often when I'm talking with customers of vendors. It's not something to be underestimated. It's incredibly important that technology provide that confidence, especially given the events of the last year and a half that we've seen where suddenly folks couldn't get into data centers, for example. Talk to me a little bit about some of the customers. I saw from your website some great brand names, but talk to me about a customer that you think really not only has that confidence that lumigo is delivering, but is really changing their business and their approach to modern monitoring with lumigo. >> Yeah, so there are several interesting. I'll choose maybe one of the more interesting cases, a company called Medtronic. It's one of the largest medical device companies in the U.S. And it's very interesting because they have an IoT backend. Basically they have medical devices around the world that send IoT information back to their cloud. And they get metrics, they run machine learning on that. And they took a strategic decision to run the system with serverless. Because it can scale automatically, because it can deploy one more million devices and they don't need to change anything, and many, many other benefits of serverless. And we met them back in 20, end of 2019. They were looking for exactly a solution that allows them to get issues and drill down to analyze those issues. And they were just in the beginning. The early days they had 20 million invocations, requests per month. They knew they were going to scale, they knew that when they scale, they cannot correlate logs, and try to understand what happened manually. They need a professional tool. And this is where they started using lumigo. And today, a year and a half after, they reached one billion invocations a month. Again, the same concept, IoT devices, medical devices, sending metrics and information for the backend for processing. And today, lumigo is monitoring everything in that environment. And alert them from, you're about to have a problem, or you have an application error, or you have high latency, you have spike of cost, all of that are covered by lumigo. And the developers, once they get this to slot, to play the duty, you're just able to click on it, and drill down and see, one by one, requests that created the trigger that alert. And they can understand, again, the inputs, the output, the logs, the return values, everything. I call it debugging heaven. Because it's always there, it's always post-mortem, you don't need to do anything. At the same time you get the visibility and you can fix it, because this is their production, this is their business critical application. >> Debugging heaven, I love that. That's for developers, that is probably a Nirvana state. I want to wrap up Erez, just giving our folks in the audience an overview of the relationship that lumigo has with AWS. >> AWS is one of our strongest partner. I think there's a great synergy working with AWS. We've been partners for the last three years. And I think the reason for the... You know, we're still... AWS has thousands, tens of thousands of partners. I think that this partnership is specifically strong because there is a win-win relationship over here. On the one hand side lumigo is very much invested on Amazon. Our customers are mostly Amazon customers, and we are solving, providing confidence for those customers to run serverless in production, and answering a need of a customer. And this is also the win for Amazon. Amazon is basically have a great, great technology of serverless. But the lack of visibility, the lack of confidence, is hindering the adoption. And Amazon decided to work with lumigo, saying, we'll develop the core, we'll develop the services, we'll develop the serverless architecture, and you can use lumigo for monitoring, for debugging, for everything that you need in order to run that in production. And that's been very, very strong relationship that just grows as we develop together. And it's been on working together with customers, introducing customers, but also on the technology level. For the audience who sees Amazon announcement on serverless, many times lumigo is a design partner. It's part of the announcement, of lumigo was a design partner and the launch partner, and support the new feature out of the box. This is because we want to get the support as soon as possible, as soon as new features are released. So that's where we are today. >> Sounds like a very collaborative and symbiotic relationship. Erez, thank you for joining me on the program today, talking to us about some of the trends in serverless, some of the things that are catalyzing adoption, that visibility, that confidence, that lumigo delivers to its customers. We thank you for your time. >> Excellent, thank you very much Lisa. Have a good day. >> You too! For Erez Berkner, I'm Lisa Martin. Thanks for watching this Cube Conversation. (bouncy music)

Published Date : Sep 7 2021

SUMMARY :

the CEO and co-founder of lumigo. Glad to be here. about the growing trend So at the end of the day, in four minutes with four clicks. At the end of the day, is considered serverless? is at the end of the day, and I think the Lego bricks And the main change is and 70% of the developers solution, the technology, allow the developers to debug. of the last year and At the same time you get the of the relationship that and support the new that lumigo delivers to its customers. Excellent, thank you very much Lisa. this Cube Conversation.

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IBM and Brocade: Architecting Storage Solutions for an Uncertain Future | CUBE Conversation


 

>> Narrator: From theCUBE studios in Palo Alto in Boston connecting with our leaders all around the world. This is theCUBE conversation. >> Welcome to theCUBE and the special IBM Brocade panel. I'm Lisa Martin. And I'm having a great opportunity here to sit down for the next 20 minutes with three gentlemen please welcome Brian Sherman a distinguished engineer from IBM, Brian, great to have you joining us. >> Thanks for having me. >> And Matt key here. Flash systems SME from IBM, Matt, happy Friday. >> Happy Friday, Lisa. Thanks for having us. >> Our pleasure. And AIG Customer solution here from Brocade is here. AJ welcome. >> Thanks for having me along. >> AJ we're going to stick with you, IBM and Brocade have had a very long you said about 22 year strategic partnership. There's some new news. And in terms of the evolution of that talk to us about what's going on with with Brocade IBM and what is new in the storage industry? >> Yeah, so the the newest thing for us at the moment is that IBM just in mid-October launched our Gen seven platforms. So this is think about the stresses that are going on in the IT environments. This is our attempt to keep pace with with the performance levels that the IBM teams are now putting into their storage environments the All-Flash Data Centers and the new technologies around non-volatile memory express. So that's really, what's driving this along with the desire to say, "You know what people aren't allowed "to be in the data center." And so if they can't be in the data center then the fabrics actually have to be able to figure out what's going on and basically provide a lot of the automation pieces. So something we're referring to as the autonomous SAM. >> And we're going to dig into NBME of our fabrics in a second but I do want to AJ continue with you in terms of industries, financial services, healthcare airlines there's the biggest users, biggest need. >> Pretty much across the board. So if you look at the global 2000 as an example, something on the order of about 96, 97% of the global 2000 make use of fiber channel environments and in portions of their world generally tends to be a lot of the high end financial guys, a lot of the pharmaceutical guys, the automotive, the telcos, pretty much if the data matters, and it's something that's critical whether we talk about payment card information or healthcare environments, data that absolutely has to be retained, has to get there, has to perform then it's this combination that we're bringing together today around the new storage elements and the functionalities they have there. And then our ability in the fabric. So the concept of a 64 gig environment to help basically not be the bottleneck in the application demands, 'cause one thing I can promise you after 40 years in this industry is the software guys always figure out how to all the performance that the hardware guys put on the shelf, right? Every single time. >> Well there's gauntlet thrown down there. Matt, let's go to you. I want to get IBM's perspective on this. Again, as we said, a 22 year strategic partnership, as we look at things like not being able to get into the data center during these unprecedented times and also the need to be able to remove some of those bottlenecks how does IBM view this? >> Yeah, totally. It's certainly a case of raising the bar, right? So we have to as a vendor continue to evolve in terms of performance, in terms of capacity, cost density, escalating simplicity, because it's not just a case of not be able to touch the rates, but there's fewer people not being able to adjust the rates, right? It's a case where our operational density continues to have to evolve being able to raise the bar on the network and be able to still saturate those line rates and be able to provide that simply a cost efficiency that gets us to a utilization that raises the bar from our per capita ratio from not just talking about 200, 300 terabytes per admin but going beyond the petabyte scale per admin. And we can't do that unless people have access to the data. And we have to provide the resiliency. We have to provide the simplicity of presentation and automation from our side. And then this collaboration that we do with our network brother like Brocade here continued to stay out of the discussion when it comes to talking about networks and who threw the ball next. So we truly appreciate this Gen seven launch that they're doing we're happy to come in and fill that pipe on the flash side for them. >> Excellent and Brian as a distinguished engineer and let me get your perspectives on the evolution of the technology over this 22 year partnership. >> Thanks Lisa. It certainly has been a longstanding, a great relationship, great partnership all the way from inventing joint things, to developing, to testing and deploying to different technologies through the course of time. And it's been one of those that where we are today, like AJ had talked about being able to sustain what the applications require today in this always on time type of environment. And as Matt said, bringing together the density and operational simplicity to make that happen 'cause we have to make it easier from the storage side for operations to be able to manage this volume of data that we have coming out and our due diligence is to be able to serve the data up as fast as we can and as resilient as we can. >> And so sticking with you, Brian that simplicity is key because as we know as we get more and more advances in technology the IT environment is only becoming more complex. So really truly enabling organizations in any industry to simplify is absolute table stakes. >> Yeah, it definitely is. And that's core to what we're focused on and how do we make the storage environment simple. It's been one those through the years and historically, we've had entry-level us and the industry as a whole, is that an entry-level product mid range level products, high-end level products. And earlier this year, we said enough, enough of that it's one product portfolio. So it's the same software stack it's just, okay. Small, medium and large in terms of the appliances that get delivered. Again, building on what Matt said, from a density perspective where we can have a petabyte of uncompressed and data reduced storage in a two Enclosure. So it becomes from a overall administration perspective, again, one software stake, one automation stack, one way to do point in time copies, replication. So in focusing on how to make that as simple for the operations as we possibly can. >> I think we'd all take a little bit of that right now. Matt, let's go to you and then AJ view, let's talk a little bit more, dig into the IBM storage arrays. I mean, we're talking about advances in flash, we're talking about NBME as a forcing function for applications to change and evolve with the storage. Matt, give us your thoughts on that. >> We saw a monumental leap in where we take some simplicity pieces from how we deliver our arrays but also the technology within the arrays. About nine months ago, in February we launched into the latest generation of non technology and with that born the story of simplicity one of the pieces that we've been happily essentially negating of value prop is storage level tiering and be able to say, "Hey, well we still support the idea of going down "to near line SaaS and enterprise disc in different flavors "of solid state whether it's tier one short usage "the tier zero high performance, high usage, "all the way up to storage class memory." While we support those technologies and the automated tiering, this elegance of what we've done as latest generation technology that we launched nine months ago has been able to essentially homogenize the environments to we're able to deliver that petabyte per rack unit ratio that Brian was mentioning be able to deliver over into all tier zero solution that doesn't have to go through woes of software managed data reduction or any kind of software managed hearing just to be always fast, always essentially available from a 100% data availability guaranteed that we offer through a technology called hyper swap, but it's really kind of highlighting what we take in from that simplicity story, by going into that extra mile and meeting the market in technology refresh. I mean, if you say the words IBM over the Thanksgiving table, you're kind of thinking, how big blue, big mainframe, old iron stuff but it's very happy to say over in distributed systems that we are in fact leading this pack by multiple months not just the fact that, "Hey, we announced sooner." But actually coming to delivering on-prem the actual solution itself nine, 10 months prior to anybody else and when that gets us into new density flavors gets us into new efficiency offerings. Not just talk about, "Hey, I can do this petabyte scale "a couple of rack units but with the likes of Brocade." That actually equates to a terabyte per second and a floor tile, what's that do for your analytics story? And the fact that we're now leveraging NBME to undercut the value prop of spinning disc in your HBC analytics environments by five X, that's huge. So now let's take near line SaaS off the table for anything that's actually per data of an angle of value to us. So in simplicity elements, what we're doing now will be able to make our own flash we've been deriving from the tech memory systems acquisition eight years ago and then integrating that into some essentially industry proven software solutions that we do with the bird flies. That appliance form factor has been absolutely monumental for us in the distributed systems. >> And thanks for giving us a topic to discuss at our socially distant Thanksgiving table. We'll talk about IBM. I know now I have great, great conversation. AJ over to you lot of advances here also in such a dynamic times, I want to get Brocade's perspective on how you're taking advantage of these latest technologies with IBM and also from a customer's perspective, what are they feeling and really being able to embrace and utilize that simplicity that Matt talked about. >> So there's a couple of things that fall into that to be honest, one of which is that similar to what you heard Brian described across the IBM portfolio for storage in our SaaS infrastructure. It's a single operating system up and down the line. So from the most entry-level platform we have to the largest platform we have it's a single software up and down. It's a single management environment up and down and it's also intended to be extremely reliable and extremely performance because here's part of the challenge when Matt's talking about multiple petabytes in a two U rack height, but the conversation you want to flip on its head there a little bit is "Okay exactly how many virtual machines "and how many applications are you going to be driving "out of that?" Because it's going to be thousands like between six and 10,000 potentially out of that, right? So imagine then if you have some sort of little hiccup in the connectivity to the data store for 6,000 to 10,000 applications, that's not the kind of thing that people get forgiving about. When we're all home like this. When your healthcare, when your finance, when your entertainment, when everything is coming to you across the network and remotely in this version and it's all application driven, the one thing that you want to make sure of is that network doesn't hiccup because humans have a lot of really good characteristics. Patience would not be one of those. And so you want to make sure that everything is in fact in play and running. And that's as one of the things that we work very hard with our friends at IBM to make sure of is that the kinds of analytics that Matt was just describing are things that you can readily get done. Speed is the new currency of business is a phrase you hear from... A quote you hear from Marc Benioff at Salesforce, right. And he's right if you can get data out of intelligence out of the data you've been collecting, that's really cool. But one of the other sort of flip sides on the people not being able to be in the data center and then to Matt's point, not as many people around either is how are humans fast enough when you look... Honestly when you look at the performance of the platforms, these folks are putting up how is human response time going to be good enough? And we all sort of have this headset of a network operations center where you've got a couple dozen people in a half lit room staring at massive screens on the thing to pop. Okay, if the first time a red light pops the human begins the investigation at what point is that going to be good enough? And so our argument for the autonomy piece of of what we're doing in the fabrics is you can't wait on the humans. You need to augment it. I get that people still want to be in charge and that's good. Humans are still smarter than the Silicon. We're not as repeatable, but we're still so far smarter about it. And so we needed to be able to do that measurement. We need to be able to figure out what normal looks like. We need to be able to highlight to the storage platform and to the application admins, when things go sideways because the demand from the applications isn't going to slow down. The demands from your environment whether you want to think about take the next steps with not just your home entertainment home entertainment systems but learning augmented reality, right. Virtual reality environments for kids, right? How do you make them feel like they're part and parcel of the classroom, for as long as we have to continue living a modified world and perhaps past it, right? If you can take a grade school from your local area and give them a virtual walkthrough of the loop where everybody's got a perfect view and it all looks incredibly real to them those are cool things, right? Those are cool applications, right? If you can figure out a new vaccine faster, right. Not a bad thing, right. If we can model better, not a bad thing. So we need to enable those things we need to not be the bottleneck, which is you get Matt and Brian over an adult beverage at some point and ask them about the cycle time for the Silicon they're playing with. We've never had Moore's law applied to external storage before never in the history of external storage. Has that been true until now. And so their cycle times, Matt, right? >> Yeah you struck a nerve there AJ, cause it's pretty simple for us to follow the linear increase in capacity and computational horsepower, right. We just ride the X86 bandwagon, ride the Silicon bandwagon. But what we have to do in order to maintain But what we have to do in order to maintain the simplicity story is followed more important one is the resiliency factor, right? 'Cause as we increased the capacity as we increased the essentially the amount of data responsible for each admin we have to literally log rhythmically increase the resiliency of these boxes because we're going to talk about petabyte scale systems and hosting them really 10,000 virtual machines in the two U form factor. I need to be able to accommodate that to make sure things don't blip. I need resilient networks, right. Have redundancy and access. I need to have protection schemes at every single layer of the stack. And so we're quite happy to be able to provide that as we leapfrog the industry and go in literally situations that are three times the competitive density that we you see out there and other distributed systems that are still bound by the commercial offerings, then, hey we also have to own that risk from a vendor side we have to make these things is actually rate six protection scheme equivalent from a drive standpoint and act back from controllers everywhere. Be able to supply the performance and consistency of that service throughout even the bad situations. >> And to that point, one of the things that you talked about, that's interesting to me that I'd kind of like you to highlight is your recovery times, because bad things will happen. And so you guys do something very, very different about that. That's critical to a lot of my customers because they know that Murphy will show up one day. So, I mean 'cause it happens, so then what. >> Well, speaking of that, then what Brian I want to go over to you. You mentioned Matt mentioned resiliency. And if we think of the situation that we're in in 2020 many companies are used to DR and BC plans for natural disasters, pandemics. So as we look at the shift and then the the volume of ransomware, that's going up one ransomware attack every 11 seconds this year, right now. How Brian what's that change that businesses need to make from from cyber security to cyber resiliency? >> Yeah, it's a good point in, and I try to hammer that home with our clients that, you're used to having your business continuity disaster recovery this whole cyber resiliency thing is a completely separate practice that we have to set up and think about and go through the same thought process that you did for your DR What are you going to do? What are you going to pretest? How are you going to test it? How are you going to detect whether or not you've got ransomware? So I spent a lot of time with our clients on that theme of you have to think about and build your cyber resiliency plan 'cause it's going to happen. It's not like a DR plan where it's a pure insurance policy and went and like you said, every 11 seconds there's an event that takes place. It's going to be a win not then. Yeah and then we have to work with our customers to put in a place for cyber resiliency and then we spent a lot of discussion on, okay what does that mean for my critical applications, from a restore time of backup and mutability. What do we need for those types of services, right? In terms of quick restore, which are my tier zero applications that I need to get back as fast as possible, what other ones can I they'll stick out on tape or virtual tape in and do things like that. So again, there's a wide range of technology that we have available in the in the portfolio for helping our clients from cyber resiliency. And then we try to distinguish that cyber resiliency versus cyber security. So how do we help to keep every, everybody out from a cybersecurity view? And then what can we do from the cyber resiliency, from a storage perspective to help them once once it gets to us, that's a bad thing. So how can we help? How help our folks recover? Well, and that's the point that you're making Brian is that now it's not a matter of, could this happen to us? It's going to, how much can we tolerate? But ultimately we have to be able to recover. We can't restore that data and one of those things when you talk about ransomware and things, we go to that people as the weakest link insecurity AJ talked about that, there's the people. Yeah there's probably quite a bit of lack of patients going on right now. But as we look as I want to go back over to you to kind of look at, from a data center perspective and these storage solutions, being able to utilize things to help the people, AI and Machine Learning. You talked about AR VR. Talk to me a little bit more about that as you see, say in the next 12 months or so as moving forward, these trends these new solutions that are simplified. >> Yeah, so a couple of things around that one of which is iteration of technology the storage platforms the Silicon they're making use of Matt I think you told me 14 months is the roughly the Silicon cycle that you guys are seeing, right? So performance levels are going to continue to go up the speeds. The speeds are going to continue to go up. The scale is going to is going to continue to shift. And one of the things that does for a lot of the application owners is it lets them think broader. It lets them think bigger. And I wish I could tell you that I knew what the next big application was going to be but then we'd be having a conversation about which Island in the Pacific I was going to be retiring too. But they're going to come and they're going to consume this performance because if you look at the applications that you're dealing with in your everyday life, right. They continue to get broader. The scope of them continues to scale out, right. There's things that we do. I saw I think it was an MIT development recently where they're talking about being able to and they were originally doing it for Alzheimer's and dementia, but they're talking about being able to use the microphones in your smartphone to listen to the way you cough and use that as a predictor for people who have COVID that are not symptomatic yet. So asymptomatic COVID people, right? So when we start talking about where this, where this kind of technology can go and where it can lead us, right. There's sort of this unending possibility for it. But what that on, in part is that the infrastructure has to be extremely sound, right? The foundation has to be there. We have to have the resilience, the reliability and one of the points that Brian was just making is extremely key. We talk about disaster tolerance business continuous, so business continuance is how do you recover? Cyber resilience is the same conversation, right? So you have the protection side of it. Here's my defenses. Now what happens when they actually get in. And let's be honest, right? Humans are frequently that weak link, right. For a variety of behaviors that the humans that humans have. And so when that happens, where's the software in the storage that tells you, "Hey, wait there's an odd traffic behavior here "where data is being copied "at rates and to locations that that are not normal." And so that's part of when we talk about what we're doing in our side of the automation is how do you know what normal looks like? And once you know what normal looks like you can figure out where the outliers are. And that's one of the things that people use a lot for trying to determine whether or not ransomware is going on is, "Hey, this is a traffic pattern, that's new. "This is a traffic pattern. "That's different." Are they doing this because they're copying the dataset from here to here and encrypting it as they go, right? 'Cause that's one of the challenges you got to, you got to watch for. So I think you're going to see a lot of advancement in the application space. And not just the MIT stuff, which is great. The fact that people are actually able to or I may have misspoken, maybe Johns Hopkins. And I apologize to the Johns Hopkins folks that kind of scenario, right. There's no knowing what they can make use of here in terms of the data sets, right. Because we're gathering so much data, the internet of things is an overused phrase but the sheer volume of data that's being generated outside of the data center, but manipulated analyzed and stored internally. 'Cause you got to have it someplace secure. Right and that's one of the things that we look at from our side is we've got to be that as close to unbreakable as we can be. And then when things do break able to figure out exactly what happened as rapidly as possible and then the recovery cycle as well. >> Excellent and I want to finish with you. We just have a few seconds left, but as AJ was talking about this massive evolution and applications, for example when we talk about simplicity and we talk about resiliency and being able to recover when something happens, how did these new technologies that we've been unpacking today? How did these help the admin folks deal with all of the dynamics that are happening today? >> Yeah so I think the biggest the drop, the mic thing we can say right now is that we're delivering 100% tier zero in Vme without data reduction value props on top of it at a cost that undercuts off-prem S3 storage. So if you look at what you can do from an off-prem solution for air gap and from cyber resiliency you can put your data somewhere else. And it's going to take whatever long time to transfer that data back on prem, to read get back to your recover point. But when you work at economics that we're doing right now in the distributed systems, hey, you're DR side, your copies of data do not have to wait for that. Off-prem bandwidth to restore. You can actually literally restore it in place. And you couple that with all of the the technology on the software side that integrates with it I get incremental point in time. Recovery is either it's on the primary side of DRS side, wherever, but the fact that we get to approach this thing from a cost value then by all means I can naturally absorb a lot of the cyber resiliency value in that too. And because it's all getting all the same orchestrated capabilities, regardless of the big, small, medium, all that stuff, it's the same skillsets. And so I don't need to really learn new platforms or new solutions to providing cyber resiliency. It's just part of my day-to-day activity because fundamentally all of us have to wear that cyber resiliency hat. But as, as our job, as a vendor is to make that simple make it cost elegance, and be able to provide a essentially a homogenous solutions overall. So, hey, as your business grows, your risk gets averted on your recovery means also get the thwarted essentially by your incumbent solutions and architecture. So it's pretty cool stuff that we're doing, right. >> It is pretty cool. And I'd say a lot of folks would say, that's the Nirvana but I think the message that the three of you have given in the last 20 minutes or so is that IBM and Brocade together. This is a reality. You guys are a cornucopia of knowledge. Brian, Matt, AJ, thank you so much for joining me on this panel I really enjoyed our conversation. >> Thank you. >> Thank you again Lisa. >> My pleasure. From my guests I'm Lisa Martin. You've been watching this IBM Brocade panel on theCUBE.

Published Date : Dec 9 2020

SUMMARY :

all around the world. Brian, great to have you joining us. And Matt key here. Thanks for having us. And AIG Customer solution And in terms of the evolution of that that are going on in the IT environments. but I do want to AJ continue with you data that absolutely has to be retained, and also the need to be able to remove that raises the bar on the evolution of the technology is to be able to serve the data up in any industry to simplify And that's core to what we're focused on Matt, let's go to you and then AJ view, the environments to we're AJ over to you lot of advances here in the connectivity to the data store I need to be able to accommodate that And to that point, that businesses need to make Well, and that's the point And one of the things that does for a lot and being able to recover And because it's all getting all the same of you have given in the last 20 minutes IBM Brocade panel on theCUBE.

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Snowflake on Snowflake


 

>>Sony. Betty is here with me. He's the CEO and chief data officer for Snowflake. Sunny. Thanks for making the time today. Good to see >>you. Same here, Dave. Thanks for having me or >>yeah, so you're welcome. So before we get into it, I gotta ask you I mean, you recently left in video to join Snowflake. I mean, one of the few cos they're almost is hot. A snowflake. How come? Well, you know, >>Dave, I joined and video 12 years ago. I was there for 12 years when the video was less than 2000 people company and in video, you know, have an unbelievable growth trajectory. We went from 2000 employees to 16,000 when I left in, uh, December of 2019 and slowly kind of provided the same opportunity to come in Onda help scale the company. I thrive in an environment where I can be creative. I thrive in an environment where I can build things I can scale things. I could grow things, and it's been just a perfect opportunity to come and repeat that success over here. >>Awesome. Well, we wish you the best talking about your role. A little bit. I mean, it's not totally unique. I mean, especially in certain smaller organizations that have the same person in the role of chief information officer and chief data officer. But oh, which are you? Are you more CEO CEO? How do you balance that >>out? I would say that I'm both to be an effective CEO. You need immersion with automation. You need immersion with data. You need a motion with security. And you also need emotion with compliance. So if all these things are together, things that integrated, you have a cohesive way of handling all the pieces that come together. We believe if you keep them separated, you create silos and we definitely don't want silos. We want integration. We want seamless integration to drive and scale the company for future. I always felt nighttime is balanced between both areas. I >>mean, I always felt like a lot of the CEO, so I talked to They'd love to get more involved in the data, but they're just too busy trying to keep the lights on, you know, kind of. So maybe what are your thoughts on the priorities of each Hat CEO and CTO? >>Yeah. So look I mean, I think because we're full cloud company, we don't have anything on Prem. I don't have any work clothes in the on Prem. I don't We don't have a data center. I really don't have to worry about all the operational challenges that you have to deal with being a non prime company. So the cycles that I can be involved from a transformational perspective, trans driving transformation for the company, both on the data side as well as on the i d I t side I have I have that cycles to be to invest that time and energy into both areas. Uh, typically in a traditional company which is not yet migrated towards the cloud. A major portion of the abandoned gets wasted CEOs, bandwidth and I t professionals. Bandwidth gets wasted in dealing with the operational challenges that you have in an on prem environment. So having not to worry about that over here gives me all the cycles to be investing my time in both areas. >>Yeah, a lot of wasted I t labor over the decades. Let me ask you, how is running a data company? You know you're inside of a fast moving Silicon Valley Tech company. One of the similarities and the differences from some of the customers. I mean, on the one hand, you're moving faster than your customers, at least most of them. And you don't have the technical day. You just describe See XO Nirvana. On the other hand, you're an example of what's possible. You could sort of set the best practice. Mark, How do you see that dynamic >>eso? You know, for a world class I T organization, it needs to be data driven. It needs to be highly automated. It needs to enable world class user experience on then to secure and make the environment compliant, resilient. The cloud platform that we have inside snowflake allows us to achieve all of that. Now, that is, um, you know, an ideal situation to be in, but you don't have to deal with, you know, all the on time type of work clothes. Um, so finding that balance is what we're going after. And however this is a This is a journey right for other companies who are not on the cloud. It's a journey. They have to prioritize that they have to start moving things to the cloud and that's where we are Different and similar, right? Were different that we don't have to worry about that. Everything is in the cloud for us on then. Uh, that's kind of where we are, How we see it. >>So, you know, used to call the dog Fuding segment. But Oliver Bushman was the sea was the CEO of s a piece. I don't know, Dave. We call it drinking your own champagne, which is how you guys refer to it. But, you know, sometimes still in such situations, you're inside the sausage factory, which is, you know, good in a way, because you see it before it goes into production. But so what's your journey with with snowflake been like, Yeah, >>so that's a really good question. That's a major portion of what I do at work and the let's start with the first principles. We believe that we want to measure everything in the company that's important for companies performance. If we measure the right things, we believe we can drive. The best outcomes were driven through those first principles, and we leverage our business applications, our data, our security, our automation and our compliance to integrate our with our product to power. All these use cases and workloads, uh, in our own environment, we call that Snow house, which is nothing but a snowflake Instance. So, um, for all the new products that we are coming into market with, we work very closely with the engineering team with the product management team to make sure that we actually become customer zero and try Thio. Use as much functionality of that inside the our own enterprise and give as much feedback to our engineering and product management team so that they can make the customer one experience to be world class. Eso. That's kind of in a nutshell. What we how we go to market with all those products. So >>your customer zero So all the products that they suck up to you Are they afraid of you? >>I think I think it's I think it's a very mutual beneficial relationship. So, you know, they know that they that my feed, my team's feedback is important to how they're kind of shaping up the product. And it's just not necessarily I t right. We have folks in finance, folks and, um, sales, marketing. Everybody is you know, drinking the champagne. Right. And icty and the data team actually enable that deployment. But the use cases are pretty much in the entire enterprise off the company in every in every aspect of it. >>Well, you know, including security. Well, you know, there's I was saying we always talk about alignment, but its's almost alignment by design as opposed to being this force thing. I'm interested in this, you know, sort of snowflake on on snowflake, You know, concept that that you guys talk about. You know what? We're objectives you're going in and maybe thinking about the outcomes, you know? What did you expect? Did you work backwards from that? You know, what were you trying >>to achieve? Yeah. I mean, look the again, back to the first principles. We believe we want to measure everything that's important to our business. That would drive the outright outcomes. We then later the application layer. We then overlay the business process layer. We then overlay the, um, compliance and security layer and and the end result really is operational izing snowflake internally to drive a business making the right choices, right? Decisions for the company. Yeah. So we have a ton of use cases that are just ideal. Um, using snowflake on Snowflake. Um, you know, I can give you some examples of that if you like, But Security being one of the biggest use cases way use the the entire monitoring and remediation work that goes in the security compliance world all through snowflake. And we're finding real time events through data sharing with our key suppliers. And we're ensuring that we're protecting our environment as much as possible with that whole infrastructure. >>If you talk about layering, you know, governance, security, it's etcetera. Yeah, I'm imagining a you know, a coat of primer paint, you know, nice and smooth over. It's not a bolt on. I want you. I wanna press you on that because because it can't be an afterthought. And what you're describing is much more of a modern approach. And I want you to sort of differentiate between the layers that you talked about and what you surely seen in your experience over the years is a bolt on. What's the difference? >>Well, I mean, you know, security. Well, there's a lot of data and a lot of the data that is critical to your environment. Um, you wanna make sure it's fully complete? You're getting it in the right hands in the right platform to understand that and doing the correlation work that needs to happen. Really time. Our platform allows all that data to be ingested and, you know, real time and anything that is suspicious. That's being out there. We're finding that stuff in real time. The monitoring has to be real time. And if there is an event, somebody needs to take an action. Real time. Eso the platform allows it to integrate all together. And basically, um, the suppliers that we're using are also doing data sharing with us on this platform. So it makes the whole security remediation to be really, really fantastic experience. >>Well, I think two I share often with my audiences. When I talked to practitioners, they're using stuff like they surprising to me. When I first heard this, they said, Well, what you chose snowflake is the security. I went What? But the simplicity and the workflow is simpler, and it just means, you know, less human labor involved in setting, setting these things up. So I wonder if you could talk about the team that you put together the culture that you're you're building And you know what? What's the makeup look like? >>Sure s o e specifically asking about the characteristics off how we're building up the culture. Yeah, absolutely. Okay, So I think they're looking for, you know, obviously very much high energy folks. People who have hi accountability, their data driven. We want to measure everything that's important to us. We're looking for folks who have situational awareness on then finally, high sense of urgency. I think all of these elements, uh, allows I t organization to be integrated with the business in law of the traditional companies. I T organizations kind of disintegrate with the business. We wanna integrate with the business to drive the best outcomes that are needed for the company. >>I want to ask you about some of your favorite use cases, but you mentioned measurement. How do you measure? What do you What do you measuring? >>Uh, sure. So I would say that Let's let's just take security because we talked about security. Let's just use security as a use case. Eso insecurity. There are many different frameworks. As you may know, right, there is the nest framework. There is a C s framework. Um, there's a I S O framework we have adopted towards a CS framework inside Snowflake. Ah, that framework has 20 controls. And that 20 controls has, you know, another 20 sub controls. So we're talking about 400 controls? Potentially. Um, not every control is applicable to us, but majority of them are. And so, for every control, that is a source of data that's being ingested in snowflake or give you an example of that is asset management. So asset management for endpoints asset management for our servers or asset management for our network gear, all of that data gets ingested inside. Snowflake. We measure that we can tell you exactly how many endpoints I have. I can tell you exactly when an employee gets on boarded. What the what laptop we have given them. What is Ah, um you know, when the employee leaves the company are recollecting that laptop back on time. Are we revoking all that access? That's part of CS Control. One as an example. And we're measuring all of that and I can tell you exactly at my real time, inside Snowflake, How effective I am for that specific control. That's just an example of that day. Now imagine 400 of these items that make up the whole security CS framework that you know, you want to measure everything on that 400 controls or 400 sub controls. And you want to make sure that if any of that control is not being managed properly, you're alerted about it and you're remediating it to prevent a security issue that might that may pop up >>awesome visibility and the automation component are you Are you the sea? So to sunny? I >>don't really have that title. We don't really have a CSO title, but I do better security. Hadas. Well, it's actually a joint responsibility between I managed the corporate security. The product security is inside the product team, but we use the same common framework. We use the same common telemetry. We use the same common, um um methodology. Uh, incident management response teams are very similar. Andi, it's all power to snowflake. >>Okay? And thank you for watching. Keep it right there. We've got mortgage rate content coming your way

Published Date : Nov 20 2020

SUMMARY :

Thanks for making the time today. So before we get into it, I gotta ask you I mean, you recently left in video to join less than 2000 people company and in video, you know, have an unbelievable I mean, especially in certain smaller organizations that have the same person in the role of chief information officer We believe if you keep them separated, mean, I always felt like a lot of the CEO, so I talked to They'd love to get more involved in the data, but they're just too busy trying to keep the challenges that you have to deal with being a non prime company. I mean, on the one hand, you're moving faster than your customers, that is, um, you know, an ideal situation to be in, which is, you know, good in a way, because you see it before it goes into production. Use as much functionality of that inside the our own enterprise Everybody is you know, concept that that you guys talk about. I can give you some examples of that if you like, But Security being one of the biggest use cases And I want you to sort of differentiate between the layers that you talked about and what you surely Well, I mean, you know, security. the workflow is simpler, and it just means, you know, less human labor you know, obviously very much high energy folks. I want to ask you about some of your favorite use cases, but you mentioned measurement. And that 20 controls has, you know, another 20 sub controls. Well, it's actually a joint responsibility between I managed the corporate And thank you for watching.

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Sunny Bedi V1


 

>> Hello everyone, and welcome back to theCUBEs coverage of the Snowflake Data Cloud Summit 2020. We're tracking the rise of the data cloud Sunny Bedi is here with me. He's the CIO and Chief Data Officer for Snowflake. Sunny, thanks for making the time today. Good to see you. >> Same here, Dave. Thanks for having me over. >> Yeah, so you're welcome. So before we get into it, I got to ask you, I mean, you recently left Nvidia to join Snowflake. I mean(chuckles) one of the few companies that are almost as hot as Snowflake, how come? >> Well, you know Dave I joined Nvidia 12 years ago. I was there for 12 years, when Nvidia was less than 2000 people company. And Nvidia have an unbelievable growth trajectory, and then from 2000 employees to 16,000, when I left in December of 2019. And Snowflake kind of provided the same opportunity to come in, and help scale the company. I thrive in an environment where I can be creative, I thrive in an environment where I can build things, I can scale things, I can grow things. And its been just a perfect opportunity to come and repeat that success over here. >> Awesome, Well we wish you the best. Talk about your role a little bit. I mean, it's like totally unique. I mean, especially in certain smaller organizations that have the same person, in the role of Chief Information Officer and Chief Data Officer, but, which are you? Are you more CIO, CDO, how do you balance that out? >> I would say that I'm both, to be an effective CIO, you need immersion with automation, you need immersion with data, you need immersion with security, and you also need immersion with compliance. So if all of these things are together, things are integrated. You have a cohesive way of handling all the pieces that come together. We believe if you keep them separated, you create silos and we definitely don't want silos. We want integration. We want seamless integration to drive and scale the company for future. >> I always felt-- >> So my time is balanced between both areas. >> I mean, I always felt like a lot of the CIOs I talked to, they'd love to get more involved in the data, but they're just too busy trying to keep the lights on. So, maybe what are your thoughts on the priorities of each hats CIO and CDO? >> Yeah, so look, I mean, I think because we're a full cloud company, we don't have anything on-prem. I don't have any workloads on-prem. we don't have a data center. I really don't have to worry about all the operational challenges that you have to deal with being an on-prem company. So the cycles that I can be involved from a transformation prospect, driving transformation for the company, both on the data side, as well as on the IT side. I have that cycles to invest that time and energy into both areas. Typically in a traditional company, which has not yet migrated towards the cloud, a major portion of their bandwidth gets wasted. CIOs bandwidth and IT professionals bandwidth gets wasted, in dealing with the operational challenges that you have in an on-prem environment. So having not to worry about that over here, it gives me all the cycles to be investing my time on both areas. >> Yeah, a lot of wasted IT labor over the decades. Let me ask you, how is running a data company? We were inside of a fast moving Silicon Valley Tech Company. What are the similarities and the differences from some of the customers? I mean, on the one hand, you're moving faster than your customers at least most of them, and you don't have the technical that you just described, CX on Nirvana. On the other hand, you're an example of what's possible. You can sort of set the best practice mark. How do you see that dynamic? >> So, in our firm world-class IT organization, it needs to be data-driven, it needs to be highly automated, it needs to enable world-class user experience, and then to secure and make the environment compliant resilient. The cloud platform that we have, inside Snowflake, allows us to achieve all of that. Now that is, an ideal situation to be in. But you don't have to deal with, all the on-prem type of workloads. So finding that balance is what we're going after. And, however this is a journey, right. For other companies who are not on the cloud, its a journey. They have to prioritize that. They have to start moving things to the cloud, and that's where we are different and similar, right. We're different that we don't have to worry about that. Everything is in the cloud for us. And then, that's kind of how we see it. >> So, you know, used to call it the dogfooding segment, but Oliver Bussmann was the CIO of SAP. So no, no, Dave, we call it drinking your own champagne. (laughs) which is how you guys are referring to it. But, sometimes still in such situations you're (laughs) inside the sausage factory, which is good in a way because you see it before it goes into production. But, so what's your journey with, with Snowflake been like? >> Yeah, so that's a really good question. That's a major portion of what I do at work. And, let's start with the first principles of we believe, that we want to measure everything in the company, that's important for companies performance. If we measure the right things, we believe we can drive the best outcomes. We are driven through those first principles and we leveraged our business applications, our data, our security, our automation, and our compliance to integrate with our product to power, all these use cases and workloads. In our own environment, we call that snow house. Which is nothing but a Snowflake instance. So, for all the new products that we are coming into market with, we work very closely with the engineering team, with the product management team, to make sure that we actually become customer zero, and try to use as much functionality of that, inside our own enterprise and give as much feedback to our engineering and our product management teams, so that they can make the customer one experience to be world-class. So that's kind of in a nutshell how we go to market with those products. >> So you're customer zero. So all the product guys that they suck up to you, or are they afraid of you? (laughs) >> Well, I think it's a very neutral, beneficial relationship. So, they know that my team's feedback, is important to how they are kind of shaping up the product, and it's just not necessarily IT, right. We have folks in finance, folks in sales, marketing, everybody is drinking the champagne, right. And IT and the data team actually enabled that deployment, but the use cases are pretty much in the entire enterprise of the company in every aspect of it. Well you know-- >> Including security. >> Well, that's what we say. We always talk about alignment, but it's like, it's almost alignment by design, as opposed to being this forced thing. I'm interested in this, sort of Snowflake on Snowflake concept that you guys talk about. What were your objectives going in and maybe thinking about the outcomes, what did you expect? Did you work backwards from that? What were you trying to achieve? >> Yeah, I mean, look again back to the first principles. We believe we want to measure everything that's important to our business. That will drive the right outcomes. We then layer the application layer. We then overlay the business process layer. We then overlay the compliance and security layer. And the end result really is operationalizing Snowflake internally to drive our business, making the right choices, right decisions for the company. So we have a ton of use cases that are just ideal, using Snowflake on Snowflake. You know I can give you some examples of that if you like, >> Yes. >> But, >> Go on please. >> Security being one of the biggest use cases. We use the entire monitoring and remediation work that goes in the security compliance world, all through Snowflake. And we are finding real time events through data sharing, with our key suppliers. And we're ensuring that we're protecting our environment as much as possible with that whole infrastructure. >> You talked about layering, governance, security, et cetera. Yeah (laughs) I'm imagining a coat of primer paint in a nice and smooth over, it's not a bolt-on. I want to press you on that, because it can't be an afterthought. And what you're describing is much more of a modern approach. And I want you to totally differentiate between the layers that you talked about and what you've surely seen in your experience over the years as a bolt-on, what's the difference? >> Well, I mean the security wall, there's a lot of data, and a lot of the data that is critical to your environment. You want to make sure it is fully complete, you're getting it in the right hands, in the right platform to understand that, and doing the correlation work that needs to happen real time. Our platform allows all that data to be ingested and real time and anything that is suspicious, that's being out there. We're finding that stuff in real time. The monitoring has to be real time. And if there is an event, somebody needs to take an action real time. So the platform allows it to integrate altogether. And basically, the suppliers that we're using are also doing data sharing with us on this platform. So it makes the whole security remediation to be really really fantastic experience. >> Well I think too, I'd to share often with my audience when I talk to practitioners that are using Snowflake they, surprising to me when I first heard this, they said, "Well we choose Snowflake as the security," and I went, what! But the simplicity and the workflow is simpler, and it just means less human labor involved in setting these things up. So I wonder if you could talk about the team that you put together, the culture that you're building, and what's the makeup look like? >> Sure, so are you specifically asking about the characteristics of how we're building up the culture? >> Yeah, absolutely. >> Okay, so I think we're looking for, obviously very much high energy folks, people who have, high accountability, they're data-driven. We want to measure everything that's important to us. We're looking for folks who have situational awareness, and then finally high sense of urgency. I think all of these elements, allows IT organization to be integrated with the business. In large traditional companies, IT organizations kind of disintegrate with the business. We want to integrate with the business, to drive the best outcomes that are needed for the company. >> I Want to ask you about some of your favorite use cases, but you mentioned measurement. How do you measure? What are you measuring? >> Sure, so I would say that, let's just take security. Cause we talked about security. Let's just use security as a use case. So in security, there are many different frameworks, as you may know, right. There is the NIST framework, there is the CIS framework, there is an ISO framework. We have adopted towards a CIS framework inside Snowflake. That framework has 20 controls and that 20 controls has another 20 sub-controls. So we're talking about 400 controls potentially. Not every control is applicable to us, but majority of them are. And so for every control, there is a source of data, that's being ingested in Snowflake. I'll give you an example of that is asset management. So, asset management for end points, asset management for our servers, or asset management for our network gear. All of that data gets ingested inside Snowflake. We measure that. We can tell you exactly how many end points I have. I can tell you exactly when an employee gets onboarded, what laptop we have given them, when the employee leaves the company, I'll be collecting that laptop back on time, I'll be revoking all that access. That's part of CIS Control 1 as an example, and we're measuring all of that. And I can tell you exactly at my real time inside Snowflake. How effective I am for that specific control. That's just an example of that Dave. Now imagine 400 of these items that make up the whole security CIS framework. You want to measure everything on that 400 controls or 400 sub-controls. And you want to make sure that if any of that control is not being managed properly, you're alerted about it and you're remediating it to prevent a security issue that may pop up. >> Awesome, visibility and automation component. Are you a CSO too Sunny? We don't really have that title. We don't really have a CSO title, but I do wear a security hat as well. It's actually a joint responsibility between... I manage the corporate security. The product security is inside the product team, but we use the same common framework. We use the same common telemetry. We use the same common methodology. Incident management response teams are very similar, and it's all powered through a Snowflake. >> Awesome. Sunny Bedi you're great guests, I would imagine the sales guys love dragging you on zooms these days to sales calls, just to (laughs) share best practice, but love to have you back and continue the conversation. Sunny Bedi, really appreciate your time. Thank you. >> Thank you Dave. Thank you very much. >> All right, keep it right there everybody. We'll be right back with our next guest, right after this short break.

Published Date : Oct 14 2020

SUMMARY :

of the Snowflake Data Cloud Summit 2020. Thanks for having me over. I mean(chuckles) one of the few companies and help scale the company. that have the same person, and scale the company for future. So my time is balanced of the CIOs I talked to, it gives me all the cycles to be investing I mean, on the one hand, Now that is, an ideal situation to be in. it the dogfooding segment, and our compliance to integrate So all the product guys And IT and the data team that you guys talk about. of that if you like, that goes in the security And I want you to totally and a lot of the data that is that you put together, are needed for the company. I Want to ask you about some And I can tell you exactly at I manage the corporate security. but love to have you back We'll be right back with our next guest,

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Bob Evans, Cloud Wars Media | Citrix Cloud Summit 2020


 

>> Woman: From theCube studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is theCube conversation. >> Hey, welcome back everybody. Jeff Frick here with theCube coming to you from our Palo Alto studios to have a Cube conversation with a real leader in the industry he's been publishing for a long, long time. I've been following him in social media. First time I've ever get the met in person and kind of a virtual COVID 20, 20 way. And we're excited to welcome into the studio. Bob Evans. He's a founder and principal analyst, the Cloud Wars Media coming to us. Bob where are you coming to us from today? >> In Pittsburgh today. Jeff. Good to see you. >> Awesome. Pittsburgh Pennsylvania. There's a lot of Fricks in Pittsburgh Pennsylvania cause Henry Clay was there many moons ago so that's a good town. So welcome. >> Thank you, Jeff. Thanks. Great to be here. And I look forward to our conversation. >> Absolutely. So let's, let's jump into it. So I know you attended today, the Citrix Cloud Summit you know, we've covered Citrix energy in the past this year, they decided to go we'll obviously virtual like everybody did but they, you know, they did something a little creative I think as, and they broke it into pieces, which, which I think is the way of the future. There's no reason to necessarily aggregate all of your news, all of your customer stuff, all your customer appreciation, the party the partners, all for three days in Vegas. Cause that's the only time you could get the Science Convention Center. So today was the Cloud Summit all day long. First off, just, you know, your general impressions of the event, >> Jeff, you know, I just thought that the guys had hit a really good note about what's going on in the outside world. You know, sometimes I think it's a little awkward when tech companies come in and the first thing they want to talk about is themselves, which I guess in some ways fine but I think the Citrix guys did a really good job at coming outside in here's what's going on in the outside world. Here's how we as a technology player trying to adapt to that and deliver the maximum value to our customers in this time of unprecedented change. So I thought they really nailed that with cloud and some of the other big topics that they laid out >> Great. And you've been covering cloud for a long time and, and you know, COVID is, we're still in it. There's a lot of really bad things that are happening. There's hundreds of thousands of people that are dying and a lot of businesses are getting crushed especially hospitality, travel you know, anything that relies on an aggregation of people. Conversely though we're, we're fortunate to be in the IT industry and in the information industry. And for a lot of industries, it's actually been kind of an accelerant. And one of the main accelerants is this, you know kind of digital transformation and new way to work. And some of these things that were initiatives in play but on March 15th, approximately it was go, right? It was Light switch no more planning, no more talking, it's here now. Ready, set, go. And it's in, you know, Citrix is in a pretty good position in terms of the products that they offer, the services that they offer, the customer base that they have to take advantage of that opportunity and, and you know, go to this, we've all seen the social media memes right? Who's driving your digital transformation the CEO, the CIO, or COVID. And we all know what the answer to the question is. They're pretty well positioned and it seems like, you know, they're doing a good job kind of doubling down on the opportunity. >> Jeff. Yeah. And I'd sure echo your, your initial point there about the nightmare that everybody's experienced over the last six or seven months. There's, there's no way around that yet. It has forced in these categories like, you know, that we've all heard hundreds of thousand time digital transformation to the point where the term almost becomes a cliche but in fact right? You know, it has become something that's really you know, one of the driving forces, touching everybody in the planet, right? There's, and I think digital transformation. Isn't so much about the technology, of course but it's because, you know, there's a couple billion people around the world who want to live digitally enhanced digitally driven lifestyles. And the pandemic only accelerated that as you said. So it triggered things you know, in our personal lives and our new set of requirements and expectations sort of rippled up to the B2C companies and from them back up to the B2B companies So every company on earth, every industry has had to do this. And like you said, if they were, deluding themselves maybe telling themselves these different companies that yeah, we're going fast, we're aggressive. Well, when this thing hit earlier this year as you said, they just had to really slam their foot down. I think that David Henshall from Citrix said that they had some companies that had, they were compressing three years into five months or he said in some cases even weeks. So it's really been extraordinary. And cloud has been the vehicle for these companies to get over into their digital future. >> Right. And let's talk about that for a minute because you know, Moore's law is my favorite law that nobody knows which was, you know, we tend to underestimate, excuse me we tend to overestimate the impact of technology in the short term of specific technology and underestimate the longterm impact. You know, Gardener kind of uses a similar thing with the hype cycle. And then you know, the thing goes at the end, you know, had COVID hit five years ago, 10 years ago, 15 years ago you know, the ease in which the information workers were able to basically just not show up and turn on their computer at home and have access to most of their tools and most of the security and most of their applications that wasn't even possible. So it's a really interesting, you know, just validation on the enabler that we are actually able to not go to work on Tuesday the 16th or whatever the day was. And for the most part, you know, get most of our work done. >> Yeah. Yeah. Jeff, you know, I've thought about it a lot over the last several months. Remember the big consultant companies used to try to do these measures of technology and they'd always come out and say, well, we've done all these studies. And despite the billions of dollars of investment we can't show that IT has actually boosted productivity or, you know, delivered an ROI that customers should be happy with. I was always puzzled by some of the things that went into those. But I would say that today over these last six or seven months to your point, we have seen extraordinary validation of these investments in technology broadly. But specifically I think some of these things that are happening with the cloud, you know, as you've said how fast some companies have been able to do this and then not remarkable thing, Jeff right. About human nature. And we hear a lot about in, in when companies change that relative to changing human behavior changing technology is somewhat easy but you try to change human behavior and it's wicked. Well, we had this highly motivating force behind it, of the pandemic. So you had a desire on the part of people to change. And as you pointed out, there's also this corresponding thing of, you know, the technology was here. It was right. You've got a fast number of companies delivering some extraordinary solutions. And, you know, I thought it was interesting. I think it was a Kirsten Kliphouse from Google cloud. One of Citrix's partners who said that we're two best of breed companies, Citrix and Google cloud. So I thought that, that coming from Google you know, that is very high praise. So again, I think the guys at Citrix are sort of coming into this at the right time with the right set of outside in-approaches and having that flexibility to say that we're moving into territory nobody's ever been both been in before. So we better be able to move as fast as possible. >> Right. Right. And, and just to keep going down the quote line, you know once everyone is taken care of and you, you deal with the health and safety of your people which is a number one, right? The other thing is the great Winston Churchill quote which has never let a good crisis go to waste. And I think you know, David talked about in that, in his keynote that this is an opportunity, He said to challenge assumptions, challenge the models of the past. So, you know get beyond the technology discussion and use this really as a catalyst to rethink the way that you do things. And, you know, I think it's a really interesting moment because there is no model right? There is no, there is no formula for how do you reopen, there was no playbook for how do you shut down? You know, it was, everybody's figuring it out. And you've got kind of all these concurrent processes happening at the same time as everyone tries to figure it out and come to solutions. But clearly, you know, the path to, to leverage as much as you can, is the cloud and the flexibility of the cloud and, you know the ability to, to expand, add more applications. And so, you know, Citrix again, right place, right time right. Solution, but also you know, taking an aggressive tact to take advantage of this opportunity, both in taking care of their customers, but really it's a real great opportunity for them to change a little bit. >> It is. And Jeff, you know, I think if I could just piggyback on you know, your, your guy there Winston Churchill, one of his other quotes, I love it too. And he said, if find yourself crawling through hell, keep going. And I think so many companies have really had to do that now. It's, it's not ideal. It's not maybe the way they plan it but this is the reality we're facing here in 2020 and a couple of things right? I think it requires a new type of leadership within the customer companies right? What, how the CEO gets engaged in saying, I, I'm not going to relegate this to the CIO for this to happen and something else to the CMO. They've got to be front and center on this because people are pretty smart. And then the heightened sensitivity that everybody in every business has around the world today if you think your CEO is just paying lip service to this stuff about digital transformation and all these changes that everybody's going to make, the people aren't going to buy into it. So you've got the leadership thing happening on the one side and into that it's not a vacuum, but into that void or that opportunity of this unprecedented space that you mentioned come the smart, capable forward-looking technology companies that are less concerned with the stuff that they've dragged along with them for years or decade or more. But instead of trying to say, what is the new stuff that people are going to be desperately in need of and how can I help these customers do things that they never did before? It's going to require me as a tech company to do stuff that I've never done before. So I, I've just been really inspired by seeing a lot of the tech companies doing what they are helping their customers to do which is take a product development cycle, look at all the new stuff that came out around COVID and back to work, workspaces. And so on what Citrix, you know others are doing like this, the product development cycles Jeff, you study this stuff closely. It's, it's almost unimaginable. If you had said that somebody within three months within two months, we're going to have a new suite of product available we would have said it just, it's not possible the nice idea but it can't work, but that's happening now, right? >> Yeah. Isn't it interesting that had you asked them on March 10th, they would have told you it's not possible. And by March 20th, they were doing it. >> Yeah. >> At scale, huge companies. And to your point, I think that the good news is they had kind of their own companies to eat their own dog food and get their own employees you know, working from home and then, you know, bake that into the way that they had their go to market. But let's talk a little bit more specifically about work from home or work from anywhere or the new way to work. And it's funny cause that's been bantered about for, for way too long, but now, now it's here. And most indications are that for many people, many companies are saying you're not going to go back for a while. And even when you do go back it's going to be a lot different. So, you know, the new way to work is really important. And there's so much that goes into that. And one of the big pieces that I'm encouraged to hear is how do you measure work? And, you know, there's a great line I heard where, you know work is an output. It's not a place to go. And, you know, I had Martin Michaelson early on in this thing, and he had the great line, you know it's so easy to fake it at work, you know, just look busy and walk around and go to all the meetings where with a work from home or work from anywhere. What the leadership needs to do is, is a couple of things. One, is measure output right? Not activity. And you know, it's great. People can have dinner with their family or go see the kid's baseball game. Or I guess they don't have a baseball games right now but, you know, measure output, not activity which is, doesn't seem to be that revolutionary. But I think it kind of is. And, and then the other thing is really be an enabler and be a, an unblocker for people in terms of a leadership role right? Get out, help get stuff out of the way. And, but unfortunately, the counter is, you know how many apps does a normal person have to interact with every day? And how many notifications do those apps fire off every day between Slack and Asana and Salesforce and, and texts and tweets and everything else. You know, I think there's a real opportunity to take a whole nother level of productivity improvement by removing these, these silly distractions automating, you know, as much of the crap away as we can to enable people to use their brains and have some quiet time and think about things and deliver much better value than this constant reaction to nonstop notifications. >> Yeah. Yeah. Jeff, you know, I loved your point there about the difference between people's outlook on March 10th versus on March 20th. And I believe that, you know, all limitations are self-imposed, right? We tend to form constructs around how we think and allow those then to shape and often restrict or confine our behavior. And here's an example of the CEO of Novartis Pharmaceutical Company. He said, we have been brought up in the pharmaceutical industry to believe that it is immutable law of physics that it's going to take 12 and a half years and two and a half billion dollars to get a new drug approved. And he said in the past with the technology and the processes and the capabilities that that was true it is not true today yet too often, the pharmaceutical industries behave like those external limitations are put in there. So flip that over to one of the customers that, that was at the Citrix Cloud Summit today Jim Noga, who's the CIO at Mass General Brigham. I thought it was remarkable what he said when you asked about how are things going with this work from home? Well, Jim Noga the CIO there said that we had been averaging before COVID 9,000 virtual visits a month. And he said since then that number has gone up to a quarter of a million virtual visits a month or it's 8,000 a day. So they're doing an a day what they used to do in a month. Like, you said it, you tell them that on March 10th, they're not going to believe it but March 20th, it started to become reality. So I think for the customers, they're going to be more drawn to companies that are willing to say, I see your need. I see how fast you want to move. I see where you need to go and do things you never did before. I'm willing to lock elbows with you, and go in on that. And the tech number is that sort of sit back and say, ah well, I'd like to help you there, but that's not what I do. They're going to get destroyed. They're going to get blown out. And I think over the next year or two, we're going to see this massive forcing function in the tech industry. That's going to separate the companies that are able to move at the pace of market and keep up with their customers versus those that are trapped by their past or by their legacy. And it is, going to be a fascinating talk. >> So I throw on a follow up to make sure I understand that number. Those are patient visits per unit time. >> Yeah. At Mass Brigham. So he said 9,000 virtual visits a month is what they're averaging before COVID. He said, now we're up to 250,000 virtual visits per month. >> Wow. >> So it's 8,000 a day. >> Wow. I mean the thing that highlights to me, Bob, and the fact that we're doing this right now, and none of us had to get on an airplane is, you know, I think when people think back or sit back and look at what does this enable? right? What does digital enable? Instead of saying instead of focusing what we can't do, like we can't go out and get a cup of coffee after this is over and we can't and that would be great and we'd have a good time but conversely, there's so many new things that you can do right? And you can reach so many more people than you could physically. And, and for like, you know, events like the one today. And, you know, we cover events all the time. So many more people can attend if they don't have the expense, of flying to Vegas and they don't have to leave the shop or, you know, whatever the limitations are. And we're seeing massive increases in registrants for virtual events, massive increase in new registrants. Who've never attended the, the events before. So I think he really brings up a good point, which is, you know, focus on what you can do and which is a whole new opportunity a whole new space, if you will, as opposed to continuing to whine about the things that we can't do because we can't do anything about those anyway >> No, and you know, that old line of a wish in one hand and spit in the other and see which one fills up first (laughs) you know, one of the other guests that that was on the Cloud Summit today Jeff, I don't know if you got to see 'em, but Steve Shute from SAP who heads up their entire 40,000 person customer success organization he said this about Citrix. "Citrix workspace is the foundation to provide secure cloud based access for this new generation of remote workers." So you get companies like SAP, and, you know, you want to talk about somebody that has earned its way into the, you know the biggest companies in the world and how they go along. You know, it's pretty powerful. They end up, your point Jeff, about how things have changed, focus on what we can do. The former CEO of SAP, Bill McDermott. He recently said, we think of phones as, you know, devices that help us be more productive. We think of computers as devices that help us be more productive. He said, now the world's going to start thinking of the office or the headquarters. It's a productivity tool. That's all it is. It's not the place that measures Hey, he was only at work, four days today. So, you know, he didn't really contribute. It's going to be a productivity tool. So we're going to look at a lot of concepts and just flip them upside down what they meant in February. Isn't going to to mean that much after this incredible change that we've all been through. >> Right. Right. Another big theme I wanted to touch base with you on it was very evident at the at the show today was multicloud right and hybrid cloud. And, you know, I used to work for Oracle in, in the day. And you know Amazon really changed the game in, in public cloud. The greatest line, one of Jeff's best lines is you know, we had seven year headstart. Nobody even was paying attention to the small book seller in Seattle and they completely changed enterprise technology. But what came across today pretty clearly right? As horses for courses, and really focusing at the application first right? The workload first and where that thing runs and how that thing runs, can be any place in that in a large organization you know, this is pick an airline or, or a big bank right? They're going to have stuff running at Oracle. They're going to have stuff running at AWS. They're going to have stuff running on Google. They're going to to have stuff running in Azure. They're going to have stuff running in their data center. IBM cloud, Ali Baba. I mean there's restrictions for location and, and data sovereigncy and all these things that are driving it. And really, you know, kind of drives this concept where the concept of cloud is kind of simple but the actual execution day to day at the enterprise level and managing and keeping track of this stuff, it is definitely a multicloud hybrid cloud. Pick your, pick your, your adjective but it's definitely not a single cloud world. That's for sure. >> Yeah. Yeah. And Jeff, you know, the Citrix customer that I mentioned earlier, Jim Noga is that the CIO at mass General Brigham, one of the other points he made about this was he said he's been very pleased about some of the contributions that cloud has made in, in, in his hospital organizations, you know transformation, what they've been able today and all the new things that they're capable of doing now that they were not people poor. But he said, you know, cloud is a tool. He said, it's not Nirvana. It's not a place for everything. He said, we have some on-premises systems. He said, they're more valuable now than they were a couple of years ago. And then we've got edge devices and we have something else over here. He said, so I think his point was it's important to put the proper value on cloud for all the things it can do for a specific organization, but not the thing that it's a panacea for everything though, big fan, but also a realist about it. >> Great. >> And so from that to the hybrid stuff and multicloud and I know all the big tech vendors would love it and say Oh no, it's not a multicloud, but just be my cloud. Just, just use my stuff. Everything will be easy, but that's not true. So I think Citrix position itself really well big emphasis on security, big emphasis on the experience that employees need to have. It isn't just sort of like a road war you loose five or seven years ago, as long as he, or she can connect through email and, you know, sending a sales data back and forth, they're all set. Now. It's very different. You've got people sitting in a wildly different environments for, you know, six, eight, 10 hours a day and chunk of an hour or two or three here or there. But that, that seamless experience always dependable, always reliable is just, you know, it can't be compromised. And I just thought you have one you know, high level thought about what happened. It was impressive for me to see that Citrix certainly a fine company put it. It's not one of the biggest tech companies in the world but look at the companies we have, the Microsoft, SAP talking about Google Cloud, AWS, you know, up and down the line. So I just thought it was really impressive how they showed their might as sort of a part of a network effect that is undeniable right now. >> Right. Right. And I think it's driven, you know, we hear over and over right? I mean, co-opertition is a very Silicon Valley thing. And ultimately it's about customer choice and the customer's going to choose you know, kind of by workload, even if you will or by budget as to what they're going to do where so you have to be able to operate in that world or you're going to be you're going to get, you're going to get left out unless you're just super dominant and it's a single application and they built it on you and that's it. But that's not realistic. I want to shift gears a little bit Bob, since I'm so happy to be talking to you on another topic, that's, that's a big mega trend and we're slowly seeing more and more applications. That's machine learning and artificial intelligence and you know, and, and the generic conversations about these remind me of the old big data conversations. It's like okay. So what you know, who cares? It doesn't really matter until you apply it. And with all these new applications and even just around the work from home that we discussed earlier, you know, there's so many opportunities to apply machine learning and AI, to very specific functions and tasks to, again, help people prioritize what they're going to do help people not have to deal with the crap that they shouldn't have to do. And really, you know at a whole another level of, of productivity really, based on a smarter way to help them figure out what am I going to do in my next, my next marginal minute? You know, cause ultimately that's the decision that people make when they're sitting down getting work, done it, how do they do the best work? And I think the AI and machine learning opportunities are gargantuan. >> Jeff. The point you made a few minutes ago about, you know, we tend to overestimate the impact of a new technology in the short term and underestimate it, what it'll be overtime well, we've been doing that with AI for the last 40 years but this is going to be sort of the golden age of it. And one of the reasons why I have been so bullish on cloud is it presents like the perfect delivery system for it. This is we see in medicine, there's sometimes breakthroughs at the laboratory level where they've got the new breakthrough medication but they don't have the bullet. They don't have the delivery system to get it in there, cloud's going to be an accelerator for that. And it gives the tech companies, which and this is going to be very good for customers, every big tech company. Now as a data company, every company says, it's an analytics. Everybody says I'm into AI. Every company says I'm into ML. And in a way that's real good for customers cause the competitive level is going to soar. It's going to bring more choice. As you said, the more customers more types of solutions, more sorts of innovation. And it's also going to be incumbent on those tech vendors. You've got to make it as easy as possible, as fast as possible for these customers to get the benefit of it. I think it was Thomas Kurian, the CEO of Google cloud said, Hey, you know, if, if a shoe company or a retailer or a bank had fantastic expertise in data science, they could go out and hire 200 data scientists do this all themselves. He said, but that's not what they do. And they don't want to do that. >> Right. >> So he said, come to the companies who can do it. And I think that we will see changes in how business works driven by ML and AI, unlike anything that we've ever seen. >> Yeah. >> And that's going to happen over the next 12, 18 months. >> Yeah. Baked into everything. Well, Bob, I really am excited that we finally got to catch up in, in person COVID style. Like I said, I've been following you for a long time. So I just gave you the last word before we sign off. You know, you've been in this business for a long time. You've seen lots and lots of waves. You know, this is just another wave with this, with this, you know, gasoline thrown on the fire with, with COVID in terms of the rate of change. And the, you know there's no more talking, the time to move is now, share kind of your perspective as to kind of where we are. And, you know, we're, we're not that far from flipping the calendar to 2021, which is a good thing you know, as you, as you look forward a little bit you know, what's in your mind, what's getting you excited. What's getting you up in the morning. >> Yeah. Jeff, I guess it comes down to this thing of, we, I think here late in 2020, everybody's got a reason to be pretty proud of what we have done, not only in the last six months but over the last several years, if you look at the improvements that have been made in health care and making it available to more people, in education the things that teenagers or young teenagers or even pre-teenagers can do now to learn and explore the world and communicate with people from all over the globe, there's a lot of great things going on, but I think we're going to look back on this point and say, this was, this was a pivot point here in mid and late 2020, when we stopped letting in some ways, as you described it earlier worrying so much about the things we can't do. And instead put more time into what we can do, what breakthroughs can we make. And I think these things we've talked about with AI and ML are going to be a big part of that, the computer industry or the tech industry, maturing and understanding they're not in charge. It's the customers who are in charge here. And the tech companies have to reorient themselves and reimagine themselves to meet the demands of this new fast changing world. And so I think those are some of the mega trends and more and more Jeff, I think these tech companies are going to say that the customers are demanding that the tech companies give them the gift of speed, give them the gift of engaging with customers in new ways, give them the gift of seeing the world as other people see it rather than just through the narrow lens of, you know sometimes the tech bubble that can percolate somewhere out sometimes out in the Palo Alto area. So I, I'm incredibly optimistic about what the future is going to bring. >> Well, Thank you. Thanks for Bob for sharing your insight. You can follow Bob on Twitter. He's got podcasts, he's very prolific writer and again, really, really a great to meet you in person. And thanks for sharing your thoughts >> Jeff, thanks so much. You guys do a fantastic job and it's been a pleasure to be with you. >> Thank you. Allright. He's Bob Evans. I'm Jeff Frick. You're watching theCube from our Palo Alto studios. Thanks for watching. We'll see you next time. (soft music)

Published Date : Oct 12 2020

SUMMARY :

leaders all around the world. the Cloud Wars Media coming to us. In Pittsburgh today. There's a lot of Fricks And I look forward to our conversation. Cause that's the only time you could get Jeff, you know, I just thought And it's in, you know, Citrix but it's because, you know, And for the most part, you with the cloud, you know, as you've said to rethink the way that you do things. And Jeff, you know, I think that had you asked them and he had the great line, you know and do things you never did before. to make sure I understand that number. So he said 9,000 virtual visits a month And, and for like, you know, No, and you know, that old but the actual execution day to day But he said, you know, cloud is a tool. And so from that to the and the customer's going to choose and this is going to be So he said, come to the And that's going to happen the time to move is now, the narrow lens of, you know great to meet you in person. and it's been a pleasure to be with you. We'll see you next time.

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